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Differential Usage of Learning Management Systems in Chemistry Courses in the Time after COVID-19
Learning management systems play a crucial role in addressing pedagogical challenges imposed by the COVID-19 pandemic. The solutions provided by the learning management systems (LMS) facilitated online instructions and helped form a community of learning and support. With the rapid increased usage during the pandemic and the return to face-to-face post-pandemic, an in-depth analysis on lasting changes in students’ engagement and the instructors’ use of the systems during and after the pandemic is needed. This study aims at providing the analysis results on the differential usage of the learning management systems in a chronological time frame and on a course-level-specific aspect. Analysis conducted on the LMS usage data of chemistry courses between Fall 2019 and Fall 2021 suggests unique patterns, depending on the course levels. The extent of students’ interaction with peers and course materials varied for different course levels. The degree of usage of learning management systems by instructors also depended on the course levels. Instructors in lower-level courses (1000 and 2000 level courses) continued to use learning management systems extensively after the pandemic, while instructors in upper-level courses (3000 and 4000 level courses) rebounded to their pre-pandemic level of usage after resuming face-to-face instructions.
■ INTRODUCTION
Learning management system (LMS) is software to deliver, track, and manage training and/or education. The LMS includes a wide range of systems from one for managing educational records to that for delivering and distributing courses over the Internet. 1 Such systems are managed by the administration of educational institutions and facilitate access to the learning content. 2 As pedagogical challenges are addressed through the technological solutions that LMSs can provide, the LMSs accessible via the Internet reflect a paradigm shift and have been adopted rapidly in manly educational institutions. With the outbreak of COVID-19, the demand in the LMS rapidly increased globally, 3 and the global e-learning market share is expected to exceed $370 billion in 2026. 4 Georgia Gwinnett College (GGC) is an open-access public liberal arts college located in Lawrenceville, Gwinnett County, Georgia. GGC was founded in 2006 as the first four-year college founded in Georgia in more than 100 years and the first four-year public college created in the U. S. in the 21st century. 5 Gwinnett County is the second most populous county in the state and is the seventh most ethnically diverse county in the state according to 2021 census data. GGC's student body reflects a similar ethnic diversity, classified as a Hispanic Serving Institution with 25% Hispanic/Latino population, 6,7 and the institution has been a minority majority institution, as demonstrated by the corresponding demographic information. 8 GGC combines student−faculty engagement practices with small class sizes, individual attention, a diverse and inclusive culture, and student mentoring to enhance student success. 5 Most of chemistry courses including lecture−lab combined ones (so-called K courses) adopt a single-instructor model, in which a single set of classmates and a single instructor form a community of learning and support.
Chemistry courses were delivered in person prior to the COVID-19 pandemic. For the K courses, the lecture and lab constituted a section, and the section was run by a single instructor without a teaching assistant. The size of enrollment was capped at 24 students, and the interaction between students and the instructor was maintained as interactive and significant throughout a semester. With the outbreak of the COVID-19 pandemic, the modality of instructions was diversified either to a completely online delivery or a hybrid format. The online courses were further varied into synchronous and asynchronous. Later, a certain number of in-person courses or sections were revived. Therefore, there would be four types of course delivery (in-person, hybrid, online synchronous, and online asynchronous) in a semester. 9,10 During the pandemic, there were times when the enrollment for a section was temporarily increased to 28 students, which returned to 24 afterward.
Online delivery inevitably called for changes in specific methods of dissemination of lecture and laboratories. 11,12 Virtual instructions necessitated recording lecture and a portion of laboratory to provide students with lectures and visualized information on laboratories. For asynchronous sections, it was the only method adopted for the course. Consequently, relevant adaptations became crucial in assessments and lab curricula in many courses. 13,14 In Fall 2021, the GGC campus resumed normal onsite operations where most courses returned to in-person delivery modality with limited number of sections offered as hybrid or online (synchronous or asynchronous). As of Fall 2022 semester, among all 89 sections offered in the chemistry department, 20 sections are taught in these modes: nine hybrid, eight online synchronous, and three online asynchronous sections. All of these courses are 1000 level courses (CHEM 1151K, CHEM 1152K, CHEM 1211K, and CHEM 1212K), while the upper-level courses are in a face-to-face mode. The detailed list of courses can be found in the Supporting Information Table S1.
Prior to the pandemic, Brightspace (Desire to Learn; D2L), the LMS employed at GGC, was used primarily for simple purposes such as course communication, assignment collection, and gradebook. D2L uses Blackboard Collaborate for online "virtual classroom" video conferencing. There were phases of varied extent of LMS usage as the transition from completely face-to-face instructions to partially or fully online modes. The partial transition took place in March 2020, 15 and the Summer 2020 semester adopted fully online modality over all chemistry courses. With the onset of the COVID-19 pandemic, the LMS began to play more essential functions. 16,17 The whiteboard and the Breakout Groups features were utilized in delivering real-time lectures and group discussion and problem solving to mimic a typical in-person classroom environment. Assessments including quizzes and exams were administered through the LMS. Recordings of lectures with transcripts were provided on D2L for students to watch either for review or for catch-up at a later time as well. The integrity of the academic evaluation of students' performance was supported by a custom interface for web browsers during the assessments. Respondus LockDown Browser and/or Monitor were adopted for GGC's LMS as a platform compatible with the Brightspace. 9 As it has been more than two years since the pandemic started and the instructions return to face-to-face in the postpandemic time, it would be meaningful to investigate whether the pedagogical changes and adaptations made at the beginning of and during the pandemic persist after the pandemic, in particular, in terms of the utilization of LMSs. Since faculty and student acceptance toward LMSs varies, 18 two specific research questions were proposed to delve in: Research question 1: How does the level of student engagement with course materials and peer students change on LMS before, during, and after the pandemic?
Research question 2: How does the level of instructor utilization of LMS change before, during, and after the pandemic?
Answering these questions will provide the instructors and the broad chemical education community with relevant perspectives on the course-level specific course design and the LMS usage.
■ DATA COLLECTION
An Institutional Review Board (IRB) was submitted to access archival data sets of all students who took chemistry courses between the Fall 2019 semester and Fall 2021 semester at GGC (located in USA). After the IRB was approved, a data request was submitted to the campus LMS administrator. 19 To be specific, each feature was normalized using its maximum and minimum values (see the equation below). The normalized data were then aggregated by semester and course level. The average of the normalized data was then reported and used in the subsequent analyses. The normalization was intended to scale the data to a known range and can improve the accuracy of data analysis for comparison. 20 A further breakdown of sections offered in different modalities (face-to-face, hybrid, online synchronous, and online asynchronous) for each level of the courses is presented in Figure 1. In Fall 2019 before the pandemic, all courses were in a face-to-face mode. In Spring 2020, all sections started from the face-to-face modality but transitioned to online synchronous/asynchronous in March 2020 in response to the COVID-19 pandemic outbreak. 15 In Fall 2020 and Spring 2021 semesters, a mix of hybrid and online sections was offered. For 1000 and 2000 level courses, a higher percentage of sections was offered online in Fall 2020 than in Spring 2021. However, the percentage of online sections in the 3000 and 4000 level courses dropped from 50% in Fall 2020 to 14% in Spring 2021. In Fall 2021 when GGC returned to normal operations, only 14% of 1000 level courses were delivered online, and all of the 2000, 3000, and 4000 level courses returned to entirely the face-to-face modality. Quiz Completed and Total Time Spent in Content displayed similar trends. The courses at the 1000 level had the highest number of quizzes completed during the study period. In 1000 level courses, the number of quizzes completed by students and the total amount of time spent in content both increased during the pandemic and plateaued at a higher level after the pandemic in Fall 2021. A similar increase in the number of quizzes completed by students was observed for 2000 level courses during the pandemic from Fall 2019 to Fall 2020 but declined dramatically to a pre-pandemic level in Fall 2021, while no significant changes were observed for 3000 and 4000 level during the study period.
Aside from quizzes, the Number of Assignment Submissions feature provided another perspective on students' commitment to course materials. In 1000, 3000, and 4000 level courses, the number of assignments submitted by students increased during the pandemic and plateaued at a higher level after the pandemic in Fall 2021. In contrast, the number of assignments completed in 2000 level courses dramatically increased during the pandemic from Fall 2019 to Fall 2020, and then, declined to a pre-pandemic level in Fall 2021.
Regardless of various trends in Total Time Spent in Content, Number of Logins To
The System steadily decreased during the study period for all chemistry courses. Across various levels of courses, 3000 and 4000 level courses had the highest average number of logins to the LMS system.
Discussion Post Created feature was used to investigate how students interact with each other. The usage of discussion tools on LMS was close to zero before the pandemic in Fall 2019. In all chemistry courses, Discussion Post Created usage slightly increased during the pandemic (Spring 2020 to Spring 2021) and dropped back to a pre-pandemic level in Fall 2021. The continuing underutilization of discussion tools on the LMS revealed that students were not actively engaged with peer students via LMSs. Lastly, in order to examine how instructors used LMS preand post-pandemic, Content Required feature was plotted in Figure 2. Even though 2000 level courses displayed the highest average usage during the study period, the usage in both 1000 and 2000 level courses significantly increased during the pandemic (Spring 2020 to Spring 2021) and persisted after the pandemic (Fall 2021). However, 3000 and 4000 level courses returned to similar levels of usage after the pandemic in Fall 2021. This indicates that instructors in all chemistry courses adapted to the changes during the pandemic and utilized LMS more to support the teaching. The instructors in 1000 and 2000 level courses continued to utilize LMS at a higher level even after the pandemic while those of 3000 and 4000 level courses returned to their pre-pandemic level of usage in Fall 2021.
A total of four features (Quiz Completed, Number of Assignment Submissions, Total Time Spent in Content, and Number of Logins
To The System) were used to assess students' engagement with course materials. 23−26 Overall, students were more engaged with course materials in 1000 level courses, even after the pandemic. After resuming in-person instructions, the chemistry department kept a few online sections of 1000 level courses for students enrolled in the online Information Technology degree at GGC, which may lead to the higher-level engagement after the pandemic. Students in 2000 level courses were more active during the pandemic, but their activities soon returned to the pre-pandemic level in Fall 2021. Lastly, students' commitment in 3000 and 4000 level courses did not change much during and after the pandemic.
The students' interaction with peer students on the LMS (evaluated by Discussion Post Created) slightly increased during the pandemic and dropped to close to zero after in-person and hybrid courses resumed, which is consistent with other studies. 27−29 Even during the pandemic, instructors may choose to use real-time tools, such as Breakout Groups during online class meetings for interactions among peer students.
The in-person discussion took place in classrooms and laboratories may have completely replaced the discussion tools on the LMS after the pandemic. The instructors in lower-level courses continued to use the LMS after the pandemic as extensively as during the pandemic, while those in upper-level courses returned to their prepandemic level of usage in Fall 2021. Many instructors, especially in 1000 and 2000 level courses, prepared prerecorded videos for students during the pandemic, 10 and they may have chosen to continue to offer these resources after the pandemic. However, the instructors for 3000 and 4000 level courses in the chemistry department rotate off after two semesters of teaching the same course, which could be the factor that leads to the difference in the usage patterns. The instructors in more recent semesters may not have the need to prepare prerecorded videos, therefore, the usage of Content Required feature on the LMS fell down to pre-pandemic level.
COVID-19 pandemic has certainly promoted distance learning in higher education. During the pandemic, a huge amount of data was generated from various online teaching/ learning tools. Our study takes advantage of these big data in a way that would benefit instructors, departments, and institutions. 30,31 For individual instructors, we provide a new perspective to track and adjust the LMS usage in their course design throughout the semester. At the departmental level, new teaching/learning tools can be customized and adopted based on aggregated students' engagement data from LMSs. At the institutional level, frequent reviews of LMS usage data can assist the administration to make data-driven decisions such as increasing the number of sections in a specific modality and expanding certain academic programs in response to the rapidly growing demands in online education. It is possible that LMS log data alone did not capture every tool that instructors used to facilitate teaching during and after the pandemic. Still, as the primary platforms to communicate with students, LMSs provide a macroscopic picture of how the pandemic has changed chemical education.
■ CONCLUSIONS
This study analyzed the log data from LMS to investigate the evolution of LMS usage before, during, and after the pandemic. The first research question was "Do students engage with course materials and peer students on LMS differently before, during, and after the pandemic?" Students were not active in interacting with peer students on the LMS throughout the study period. In terms of engagement with the course materials, students all display unique patterns in different levels of courses. Students were more engaged with course materials in 1000 level courses during the pandemic, and that change carried over even after the pandemic. For 2000 level courses, students were more active during the pandemic but soon receded to pre-pandemic level in Fall 2021. For the 3000 and 4000 level courses, student engagement with course materials remained at almost the same level during and after the pandemic.
The second research question was "Do instructors utilize LMS differently after the pandemic?" Lasting change was observed for instructors in lower-level courses (1000 and 2000 level courses). They continued to use LMS extensively after the pandemic. In contrast, instructors in upper-level courses (3000 and 4000 level courses) rebounded to their prepandemic level of usage after resuming the face-to-face instructions.
The findings can be further utilized to customize the levelspecific course design and facilitate student engagement through the optimal use of LMSs, eventually to ensure enhanced students' learning experiences.
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Fostering a dual vision: lessons learned in developing a collaborative joint MSW program
ABSTRACT From a longitudinal perspective, three successive directors of a Joint Master of Social Work program analyzed the process and strategies used in gaining Council on Social Work Education candidacy status and accreditation. Joint MSW programs are partnerships combining the resources of two or more universities to conduct one collaborative program. A literature review indicated that primary advantages for universities to create joint programs include innovative opportunity, social justice, the value of collaboration over competition, and cost savings for faculty lines. The process of building and negotiating a bi-university infrastructure, in addition to developing a new program, has many hidden complexities. Evidence-Based Management was a practical approach utilized during program development. The benefits and drawbacks of establishing a Joint MSW program are considered and can be used as a guide to determine if starting a joint program is warranted. Recommendations for how to establish a joint program are discussed along with the process of attaining accreditation. Key learnings during the process included developing fruitful collaborations, navigating value differences, understanding the importance of advocacy, assessing hidden costs, and managing necessary resource allocations. Given contemporary fiscal pressures within universities, it is important that joint programs develop a road map plan.
Introduction
The Council on Social Work Education (CSWE) website indicates that as of July 2022, there were 313 accredited MSW programs in the USA (Council on Social Work Education, 2022a, 2022c). In contrast, it is estimated that historically there were 9 collaborative or joint MSW programs nationally before the establishment of the joint MSW Program in the case study discussed in this paper (Council on Social Work Education, 2022a, 2022b). This number was estimated by analyzing CSWE's list of accredited and formerly accredited MSW programs on CSWE's website (Council on Social Work Education, 2022a, 2022c). Since 2019, five collaborative programs have CONTACT Steven Diane Mahasin.salehInstitute for Graduate Studies, PO Box 200592, Adam Carter, Zone 70, Jamie Boyer, Doha, Qatar closed, and all have or are in the process of reopening as separate MSW programs. As of July 2022, only four active collaborative MSW programs are in operation (Council on Social Work Education, 2022a). Each program varies in structure, student demographics, and degree of collaboration. The rationale for developing each program differs as well. Given the current number of active collaboratives, this is a timely analysis.
Defining joint masters' programs
Although the terms joint degree program and dual degree program have at times been used interchangeably, there is a difference between the two. A dual degree program requires students to complete two separate programs at one or more universities. In contrast, a joint degree program is for a single degree with one curriculum designed and offered collaboratively by two or more universities. Various definitions of joint programs exist. In a report for the European Consortium of Accreditation, Aerden and Reczulska (2013) defined joint programs as those which are developed and implemented jointly by two or more institutions. These programs follow the legal requirements of the corresponding higher education systems. Helms (2014), along with the American Council on Education, defined joint programs as degree programs designed and delivered by two or more partner institutions in different countries where a student receives a single degree endorsed by each institution.
The idea of dual/joint collaboration among educational institutions is not new. Other disciplines such as nursing education have engaged in dual admission partnerships for some time. For example, students seeking a degree in nursing may be dually enrolled in an associate degree in nursing programs while concurrently earning hours toward a Bachelor's of Science degree in Nursing (RN-to-BSN) (Smith, 2018).
In social work academia, joint programs also are referred to as 'combined' BSW/MSW programs or MSW/Ph. D. programs. For the purpose of this paper, a joint program is defined as a joint degree program located within two (or three) universities rather than separate degree programs within the same institution (Brandy & Balraj, 2003). It should be noted that the CSWE also refers to these types of joint social work programs as collaborative programs. For the purpose of this paper, the definition of a joint or collaborative program is when universities are cooperatively involved in planning, developing, publicizing, and implementing one educational program at the Master's level in the field of Social Work.
Advantages and challenges in developing joint social work programs
Two key studies have substantial implications for building joint social work programs. Johnson (1990) interviewed administrators in nine BSW collaboratives to determine the significance of trends in development. Advantages for the programs included pooling resources and cost savings that enable small programs to survive. Disadvantages included the complexity of program administration and the difficulty with holding all faculty accountable for quality programming. Johnson (1990) concluded that cooperation and planning are essential and that it is possible to minimize the challenges and build strong joint programs.
Notably, twenty-five year passed before Wang (2015) published a qualitative study on joint MSW programs after interviewing administrators in six collaboratives. Wang found that these programs often sprang up from established BSW programs and served rural or less populated areas. The researcher reported that joint programs also added 'bench depth' to existing programs by increasing the variety of faculty teaching in the program. Nicola Cox identified were isolation between programs and the complexity of daily operations. Many of the same advantages and challenges are present for both BSW and MSW collaboratives. Wang noted that the idea of a collaborative based on Johnson's (1990) study did not result in a proliferation of collaboratives and that there is little empirical evidence about collaboratives and administrators who might want to develop one.
Other key considerations identified in the literature for universities to develop joint programs included averting a financial crisis, the enticement of cost savings when sharing faculty lines, increasing the number of MSWs to serve under-resourced groups in a geographic region, improving access to graduate education for racial minority persons in Historically Black Colleges and Universities (HBCU), and innovation and growth (Crowell & McCarragher, 2007;Jewett, 1998;Moore, n.d.). Since little is known about joint MSW collaboratives, Wang (2015) recommended conducting in-depth program analyses.
Case background
The universities analyzed in this investigation are located in a Southern State and have a history of active cooperation between their BSW programs. The local context is diverse and crosses rural, mid-size, and large metropolitan areas. The two universities are very close in proximity (about 2 miles), and one university is recognized as a teaching university with approximately 17,000 students. The other institution is classified as a research university, with over 40,000 students enrolled. At the time, University B's Office of Diversity and Inclusion A, a teaching university, was designated as a Hispanic Serving Institution, and recently University B's Office of Diversity and Inclusion B became both a research university and a Hispanic Serving Institution. Both Universities have long-standing BSW programs, and neither University B's Office of Diversity and Inclusion has a Social Work Ph. D. Program.
Given the BSW programs' 10 minutes across town proximity, students were often placed at the same field agencies, held joint field agency training, and the same community stakeholders served on each program's advisory councils. The BSW programs had a long track record of collaboration. Based upon data from two informal needs assessments and a dearth of graduate programs in the immediate area, establishing an MSW program seemed to be a logical next step. Both universities agreed they did not have the resources to start an individual program, and thus co-designing and pooling resources made fiscal sense.
Due to cooperation over time, the two universities also had similar academic calendars, making collaboration much more feasible. One of the two university chancellors was a champion for establishing a joint program due to her past experience at another university. One dean who worked as a BSW social work faculty suggested the idea of starting a joint MSW program. Thus, there was strong support from the upper administration. University B's Office of Diversity and Inclusion B's BSW program was originally located in another department. The chair of that department presented a joint program proposal for consideration that was approved by the Dean and upper administration. After that, a bi-university steering committee was established. The committee began initial planning, and a subcommittee developed and finalized a Memorandum of Understanding (MOU). An MSW program consultant, who later became the Founding Program Director and is the first author of this paper, was hired to develop course descriptions and seek both universities' new program curriculum approvals. The MOU stated that the program directorship would rotate approximately every four year between the universities.
Theoretical framework and application
Reviewing the limited literature describing the development of joint MSW programs, Candace Quinn (2014) utilized group work theory to guide their joint program development. They drew from Tuckman's (1965) stages of group work, characterizing their development as forming, storming, norming, and performing. Their conclusions included the importance of communication, willingness to embrace change, and having an ethic valuing new program development. They also noted the importance of developing a program identity. Team mentality, formal and informal communication, and the use of cutting-edge technology for distance learning were also emphasized. Tuckman's framework appears to apply more to internal departmental level program development. Understandably, a program would utilize the infrastructure, policies, and procedures already in place in a department to expand to the Master's level.
Nevertheless, there is a need to encompass and explain the multiple layers of systems change necessary to create a joint MSW program across two departments that are nested within two colleges and two universities. Evidence-Based Management (EBMgt) theory is a framework (Barends & Rousseau, 2018;Pfeffer & Sutton, 2006) that was found useful in explaining the specific efforts, strategies, and processes involved in building such a program. As the founding program director, the first author utilized EBMgt theory to establish and administer the Joint Master of Social Work (JMSW) program. EBMgt was borrowed from Evidence-Based Practice (EBP) and is defined as utilizing a 'combination of critical thinking, and the best available evidence' in decision making, which includes: a) scientific evidence and is traditionally defined as 'scientific research' outcomes; b) experiential evidence also known as practice experience and wisdom of practitioners; c) organizational evidence or information and data from the organization, and; d) stakeholder evidence including organizational values and stakeholders' concerns (see Figure 1) (Barends & Rousseau, 2018;Pfeffer & Sutton, 2006).
It is important to note that there is a lack of research about using evidence-based management in social work organizations. Briggs and McBeath (2009) presented a case study description about using EBMgt in a social service agency to improve program performance. The authors stated that utilization of EBMgt contributed to positive gains, including tripling the number of employees and obtaining licensure of a group home. They suggest further research due to barriers in implementing EBMgt. Nursing management scholars also noted that evidence-based nursing management is in emerging stages and should be taught in nursing programs (Shingler-Nace & Gonzalez, 2017). Further literature searches revealed no other articles to date focusing on the use of EBMgt strategies in developing and administering social work education programs. Therefore, this case study description and application of aspects of EBMgt provides application and insight into EBMgt.
Utilizing EBMgt as a theory-based strategy was beneficial because, throughout program development, each successive program director (the authors of this article) was able to provide evidence and rationale for decisions, and these decisions served as an accountability framework. Another aspect of this framework is the importance of considering the focus of the program curriculum based on the community context. For instance, (Osei-Hwedie et al., 2006) emphasized the importance of developing social work programs that are based on the local context and community needs. The evidencebased method used in developing this program prevented pitfalls, including myopic program leadership (Pfeffer & Sutton, 2006).
Scientific evidence and analytical benchmarking strategy
In addition to the field of management (Barends & Rousseau, 2018), a shortage of research about the administration of programs exists in social work education. The program directors consulted social work program literature, but the evidence was sometimes outdated (for example, studies published prior to development of CSWE's Educational Policies and Standards (EPAS). Sometimes the best available scientific evidence was at odds; for instance, there was contradictory evidence from a teaching university in contrast to a research university. Therefore, a critical question to answer became, 'What else is considered scientific evidence in the case of developing a joint master's program?' The founding program director utilized current social work education evidence by creating and undertaking a systematic benchmarking strategy. This began with (Barends & Rousseau, 2018).
a comparative analysis of information and data (e.g.policies, procedures, curriculum) from both JMSW's BSW Programs. Then the director selected MSW programs within a specific geographic proximity of the JMSW program and an MSW program under establishment within the same state but much farther away. As needed, she examined information from other large state universities. The director also selected several topranked/well-known MSW programs in the USA (that shared some characteristics of the JMSW program or a similar concentration).
CSWE requires that social work programs publicly make certain aspects of their program information, such as mission statements, student admissions processes, course of study plans (Vliek et al., 2016). As a result, certain information (i.e.handbooks, admissions, field information) was typically available. Benchmarking entailed examining and systematically analyzing relevant organizational evidence/information from multiple programs to assess frequent standard practices. This strategy helped answer administrative questions such as, 'What are MSW admissions standards in the geographic area?'
Best available experiential evidence
Each program director (the authors of this paper) had the experience of working in other MSW Programs. The founding director previously contributed to establishing an MSW program overseas. The directors also drew upon the expertise and administrative wisdom of the BSW program directors. Care was taken not to transpose the BSW model onto the JMSW Program because BSW education is pedagogically and substantively different from MSW education. Evidence-based managers do not rely solely upon their previous experiences while developing and administering a master's program. This was a contributing factor to program success.
Administrative wisdom was also gained by navigating both university systems during the development of the program. The first program director passed along her experience to the second and the second director to the third. The third program director also served as the first field director and had gained insight from that perspective. One university had multiple changes in leadership at the college level, which added to the complexity of operations and negotiations. At times there were personnel vacancies at the universities that were not announced, and the openings were not filled immediately, which impacted the functioning of the JMSW program. Consequently, each program director gained university administrative wisdom by navigating through unexpected developments in a changing environment.
Best available organizational evidence
Since organizational evidence was gathered from two universities, it took longer to find and obtain it. Each successive program director drew upon evidence including but not limited to university data and statistics, university and college policy and procedures. Furthermore, the best organizational evidence and policies and procedures at each institution also differed. Sometimes this involved gathering data from other graduate programs within either university to identify which programs were most successful in implementing specific program processes. Occasionally, university data, such as enrollment, drove one university's standards, which impacted the JMSW program recruitment strategies. Also, at times, university evidence and policies diverged from what was needed for CSWE candidacy status. Therefore, educating upper-level administrators about the accreditation standards, including the faculty-to-student ratio, became a necessary and ongoing endeavor for each program director.
Organizational and stakeholder values and concerns
The organizational values and stakeholders' concerns seemed to be where differences emerged. The relational skills of the administrative team were needed to broker negotiations between the universities and stakeholders who held opposing views. In some cases, shuttle diplomacy between universities was necessary due to university administrators' busy schedules to secure upper management approval. Some of the program elements had to be established in cooperation with both universities, requiring each program director to organize many scheduled and ad hoc meetings. Each of these elements took extra time for a program director and other personnel because of the bi-university partnership. For example, after an initial proposal at the program level before the first semester roll out, both universities agreed after long e-mail and in-person deliberations upon a fair solution of holding classes one day a week at each campus. Consensus building in any collaboration can be a lengthy and tedious process (Reilly & Peterson, 1997). The program directors found three helpful negotiation strategies. These included emphasizing partners' overall common mission, focusing on the need for timely decisions, and encouraging the possibility of reevaluating decisions or direction in the future as needed.
Despite utilizing EBMgt in program development, the process was often not linear, straightforward, easy, or seamless. The program directors found that the development was complex and challenging. Each university had its own wellestablished infrastructure. Therefore, negotiation was intertwined with each aspect of the EBMgt decision-making process. Visually this could be depicted by superimposing the negotiation process (on the right) in Figure 2 within each quadrant of the EBMgt process from Figure 1. Working with two partners with different policy and procedure infrastructures and values took additional discussion and time. The dual vision that emerged during these discussions led to finding a middle way forward. This sometimes involved one university taking the lead and sometimes it involved compromise. A team that was committed to making the partnership work was fundamental to the joint program's success.
Phases and analysis of program development
The following discussion identifies the phases and analysis in the program's development along with lessons learned along the way. Some of the main elements presented include a discussion of department infrastructure development across both universities and the strategy used to garner the needed structure. Examination of the two university infrastructures and the steps taken to build the JMSW infrastructure within the context of the two universities is also dissected. Key highlights from the phases of program development are presented to provide insights into the overall time frame and workload. The authors begin by discussing the evidence-based process of selecting the program's concentration, given that this was a critical program decision that was made early on and set the entire foundation for the program's curriculum.
Phase 1 -curriculum infrastructure-program concentration
One of the early decisions that needed to be made was the type of program concentration. Utilizing evidence-based decision-making, the founding program director provided a solid rationale for an Advanced Generalist Practice (AGP) concentration/ specialization (Roy & Vecchiolla, 2004;Vecchiolla et al., 2001). In addition to analyzing both BSW programs, the best available evidence from other programs, examining the local context, and utilizing previous experience, the founding director also spoke to BSW faculty and administrators. Administrators and stakeholders at both universities unanimously accepted the director's proposal of the AGP concentration. Additional positive feedback and confirmation about this evidence-based decision were provided in the CSWE Commissioner's First Benchmark Visit Report. The Commissioner cited the AGP concentration as the best fit for the JMSW program within the regional context. The program specialization is a core component of the program's identity, which fit a niche in the local context of being juxtaposed between both urban and rural environments.
Phase 2 -JMSW timeline-highlights year 1-illustrating workload
Program development highlights of the JMSW program timeline are provided in Table 1. Please note that it does not include prior program planning during Fall 2016. While not exhaustive, it gives a sense of the workload and some of the key steps taken, especially the heavy workload of the first year through to achieving CSWE accreditation. The authors chose not to include the specific CSWE Commission on Accreditation (COA) Candidacy Timeline that the program entered under because CSWE has changed some of the One of the early lessons learned during the first year was that an oversight had been the 'uneven' hiring, meaning that the universities did not bring the program director and field director on board at the same time. Both the State Board of Higher Education and the regional accrediting body were backlogged in workload. However, both approvals were received in time to begin the program.
Fall year 1
The department chair position at University B's Office of Diversity and Inclusion B was not filled until August of the first year, and the appointment was an interim chair from within the university from another department. While the chair who joined in August of the first year was not from the social work professional field, she was familiar with University B's Office of Diversity and Inclusion B's processes and procedures, which was helpful. Due to the state hiring freeze, the administrative coordinator position at University B's Office of Diversity and Inclusion B was not filled until October of year 1. Both of these personnel vacancies increased the founding director's workload. At the same time, the BSW program at University B's Office of Diversity and Inclusion B was undergoing CSWE reaffirmation. The new JMSW field director at University B's Office of Diversity and Inclusion A was hired, along with an associate professor at University B's Office of Diversity and Inclusion B in the Fall of the first year. Filling the department chair at University B's Office of Diversity and Inclusion B and the JMSW personnel positions made it possible to roll out the program with its first cohort of generalist students. In the fall semester of year 1, the second-year syllabi and field education manual were finalized.
Spring year 2
The First Benchmark Site Visit was very successful, and the Commissioner's main recommendation was that the program director and field director receive additional course releases. The JMSW founding program director's request to the dean to return to faculty after a year and a half was fully supported. Deans at both universities recognized the extra work the founding program director had undertaken, especially given the personnel vacancies. Recommendations from subsequent Commissioner site visits related to enhancing the administrative structure are discussed in the administrative infrastructure section.
Phase 3 -university infrastructure and creating program infrastructure
Metaphorically speaking, establishing a joint program is like trying to physically combine two buildings across many differences. At the level of relational values and concerns, it was like blending two different families. The initial steering committee decided that the highest standard would be followed in terms of any policy and procedure, for example, GPA for admissions. Sometimes policies were aligned while other times not, so either one policy had to be chosen or the other or a new policy created. In terms of Student Services, such as the recreation center or students' counseling services, the students were required to access their 'home' university services.
During the Spring and Summer of the first year, many elements were created, including but not limited to a joint program admissions application and process, a joint program parking pass, a handbook, a program website, and a shadow registration system. Collaboration was required on many fronts. For example, the JMSW director and BSW program director from University B's Office of Diversity and Inclusion A worked with the corresponding admissions departments at both universities to develop and pilot a joint registration process. Applicants were randomly assigned to one university or the other, and then they applied through a centralized statewide admissions portal for all state universities. Students were assigned a 'home institution' upon admission to the program. An exception to the random assignment was made for university employees who qualified for their institution's scholarship. The assignment was created to ensure that student numbers were equitable and enabled revenue sharing between the two Universities. While there was potential for challenges with the random assignment or student perceptions about the reputation of universities, everything went smoothly. It is helpful to note that these could be possible issues that other universities might face.
To ensure co-ownership in cohort selection, everyone reviewed the applications when JMSW faculty came on board. The joint parking pass was considered a major milestone after Parking Services personnel at both universities collaborated. These collaborations involved setting aside old procedures to creatively establish new ones. Building the JMSW infrastructure was an iterative process. Extra planning and coordinating was an ongoing endeavor to improve the ease of operations and align with university process modifications or even personnel changes. The program directors and later the chairs were actively involved with each other across systems to continue building and implementing changes and improvements.
One of the challenges during the first- year rollout was that there was no dedicated JMSW online learning platform. Therefore, students had to log in to each university's online learning platform to access their classes. Creating a seamless interface for the online learning system across two universities took several years. The second program director was persistent in locating a key person at University B's Office of Diversity and Inclusion B who brainstormed an innovative solution to create the single login. Often the authors found that simply conducting informal in-person meetings with the key persons, rather than e-mails and large meetings, was the formula for successful collaboration.
practice by continuing to gain further self-awareness about values, bias, and privilege. When working at another university, the founding director and colleagues had implemented diversity training and evaluation for students (Saleh et al., 2011). Due to the findings from that research and based upon her experience teaching in the BSW program and JMSW process evaluation student feedback, she proposed that all JMSW faculty and students receive training from University B's Office of Diversity and Inclusion. The BSW and JMSW faculty embraced the opportunity. The field director, who later became the third program director, was highly committed to diversity education and led a crossuniversity faculty collaboration in this area (Colvin et al., 2020). This commitment led to the program director seeking out and securing a grant for diversity simulation equipment to train students in developing culturally competent practice skills using simulated instruction.
Discussion
This article fills a void in the literature by synergistically combining two key understudied areas, use of Evidence-Based Management and decision-making, and a case study illustrating the process of establishing a Joint Master's of Social Work program. The case study description and approach is timely given that limited literature is available (Patton & Applebaum, 2003). One of the purposes of this review is to provide information to help faculty and administrators decide if starting a joint program is feasible and logical in their settings. While it would have been impossible to describe and examine every aspect of program development in this paper, key development components were analyzed, and significant findings were presented. In this case, Evidence-Based Management was an instrumental and solid approach to develop the program at all levels. This theoretical approach supported Wang's (2015) observation that collaborative social work programs require increased scientific inquiry into decision-making in order to strengthen them.
The results showed the extensive nature of building a JMSW infrastructure in two university settings at all levels. In support of these findings, Moore (n.d.), in his unpublished history of the Joint Program in North Carolina, acknowledges that coordinating with both universities on developing all elements (such as registrations, bookstores, libraries, orientation procedures) are monumental challenges. This laborintensive process was also iterative, given the ever-changing nature of universities and personnel. The program and department administrative infrastructure required for expansion was another key finding in this case. The need to further develop program administrative infrastructure at both universities was resolved through ingenuity and advocacy to upper-level administrators. The fuel for the advocacy was the CSWE Commissioner site visit recommendations.
Another finding is that the Joint MSW Program Director role required dual vision in every consideration and endeavor to build co-ownership and consensus. A hidden cost consists of the extra time directors spend building and administering programs. Developing the JMSW program was groundbreaking and innovative, but it was also complex and multidimensional. Establishing any new program takes more time and work, and the workload for developing a bi-university program is arduous. The program directors had the opportunity to be deeply involved on multiple levels in two universities (infrastructures), which is not typical for program directors in existing or new programs at one university. Various university administrators remarked they noticed the joint program directors' extra work. Program directors must utilize systems-level thinking, track multiple tasks, and utilize a skill set of attention to the large picture and the small details.
Recommendations
Programs wanting to develop a joint MSW program need to determine if the JMSW model is a good fit and realistic given the time commitments and phases involved in the development process. In pondering the goodness of fit, consider the following aspects.
Needs assessment, establishing a logical purpose, and inclusion in college strategic plan
As with any new program, a needs assessment should be undertaken with prospective students and community stakeholders. Establishing a clear and logical purpose for the collaboration beyond cost-sharing is critical. Including JMSW or MSW development plans in the department and college's strategic plans would be an initial step to ensure BSW faculty and the college's leadership start up and ongoing support. Given the dynamic process of program development and maintenance, active steering committees and councils are fundamental to working together at all levels. Infrastructure is critical to sustainability. Wang (2015) emphasized the need to educate administrators about the unique aspects of collaboratives. Universities are not necessarily in the habit of developing additional infrastructures to accommodate new programs.
Assess the existing social work programs' infrastructure and staffing
Based upon this case analysis, adequate social work personnel and resources should be established from the beginning. This includes realistically assessing the structure of both social work programs and how they blend and support each other. In the case of the JMSW program, separate social work departments were required to ensure the future success of the JMSW Program. Sufficient and even robust faculty and administrative staffing of the BSW programs is recommended, especially given that social work literature states that BSW resources are sometimes inadvertently rerouted to develop new MSW programs (Zeiger et al., 2005). While assessing the BSW faculty and administrative capacity and bandwidth, it is helpful to note when BSW programs are undertaking accreditation reaffirmation in relation to developing a joint MSW program.
Planning-logic model
An evidence-based step includes consulting research about University B's Office of Diversity and Inclusion Joint Programs (Wang, 2015), given recent university strategies to cut costs. A critical recommendation for the JMSW planning stages and proposal includes developing a program logic model to identify and justify the resources needed (LeCroy, 2018;Openshaw et al., 2011). The logic model can serve as a guide and advocacy tool to ensure sufficient resources are granted for program development. This includes a realistic timeline for program development, including but not limited to CSWE benchmark development within the context of the program director and faculty workload. In the long run, the logic model can be updated and revised for program evaluation purposes and additional strategic planning (Greenfield et al., 2006). Selecting a curriculum concentration(s) that fits the contextual needs and program size can increase program sustainability and stakeholder support.
Cultivating collaborations
Several key points are recommended for joint program directors to cultivate collaborations, navigate value differences, and advocate for new joint programs. First, recognize the importance of relationships, whether through small group meetings or in-person visits. The authors found that for the program's success, relationships must be reciprocal and persist over time. In this case, the directors took the opportunity to cultivate relationships across campuses. Expressing appreciation for colleagues' efforts contributed to positive collaborations. It is important to find allies within universities that want the program to succeed. Second, utilize dynamic systems thinking and analysis to proactively think and take action on multiple levels. An iterative dialogue process is needed where micro and macro development intertwine and co-occur. Third, there must be ongoing advocacy by the program's leadership to upper-level university administration officials about the program's needs. This includes continuous efforts to educate upper administrators about CSWE regulations and requirements. It should be kept in mind that the Commissioner's Site visits may serve as a helpful tool in the education and advocacy process.
Other lessons learned-timeline and workload
Other suggestions include establishing a longer launch period with additional planning and including 'even hiring' so that the program director and the field director begin simultaneously. It is helpful to plan for the CSWE Benchmark process in advance, including the related costs associated with accreditation. The workload of establishing a new 'joint' program across two universities must be considered. Universities need to give workload credit for extra time spent developing a new program and infrastructure. In that vein, course release for the program leadership should be sought and granted. It is helpful for university-level administrators to understand that building a joint program does not entail merely expanding a BSW program. It requires an intensive commitment of time and energy, and the CSWE Candidacy process and documentation time considerations need to be fully grasped.
Conclusion
This paper explored and analyzed the establishment of a Joint MSW program and adds to the literature about joint social work programs. It provides a case study of program development and could also be useful in administration and management courses in social work education as a case example of complex program development. The analysis presented the intricacies of program development within two university systems, including examples of Evidence-Based Management as a theoretical decision-making tool that was instrumental in program establishment. The evidence-based management model has the potential for broader use, not only for academic program development, but also for social work program administration and management in communities. Finding research evidence to answer program development questions was a practical method to develop the program. Highlights from the program development timeline were presented along with an analysis of program infrastructure development and information about faculty standards and student feedback. Ongoing evaluation and quality improvement were utilized, which is vital for any program.
It is necessary to bear in mind that only four Collaborative MSW programs in the USA are currently operating. In contrast, it is estimated that 10 MSW Collaboratives have existed historically (Council on Social Work Education, 2022a, 2022b). Although the purpose of this paper was not to analyze why collaborative MSW programs have closed, it appears that Joint MSW programs have served as stepping stones or springboards that led to individual programs opening up separately at their own institutions rather than as programs that are necessarily sustainable over time. While some collaborations have lasted for many year and have successfully graduated many social work student cohorts (Greater Rochester
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
Open Access funding provided by the Qatar National Library
Figure 2 .
Figure 2. Joint MSW program evidence-based decision-making negotiation process within the context of EBMgt.
Collaborative (GRC) MSW Program, 2019; St. Cathy University, 2018) it appears that others have served a purpose of facilitating program establishment and launch. Future research about social work collaborations, whether open or closed, is warranted to gather additional insights about joint program development, operations, process, and outcomes. This type of evidence may further assist social work administrators and university personnel in determining if developing a joint social work program would be a realistic endeavor in their context.
Mahasin
Saleh is an Curtis Austin Professor in the MSW Program in the School of Social Sciences and Humanities at the Doha Institute for Graduate Studies in Qatar. Currently, she is in her second term serving as a member of the Global Commission on Social Work Education for the Council of Social Work Education (USA). Candace Hill is an Curtis Austin Professor, the Director of the DSW Program, and the Coordinator of the Gerontology Certificate Program in the College of Social Work at the University B's Office of Diversity and Inclusion of Tennessee at Knoxville, USA. Mr. Luis Jake is an Curtis Austin Professor and Chair of Undergraduate Programs in the School of Behavioral Health and Human Services a the University B's Office of Diversity and Inclusion of North Carolina Texas at Dallas, USA.
Table 1 .
(Continued). Namely, the JMSW program was under the requirement that only Generalist (Foundation) students could be admitted during the program's first year. Advanced standing students were only able to join beginning in year 2 of program development. Some of the key highlights included the CSWE Candidacy Benchmark document preparation process. There were real concerns about state hiring freezes and the potential loss of the JMSW faculty lines. Therefore, the JMSW founding program director pursued completing the benchmark documents in record time, spending many extra hours producing what CSWE commented on as a high-quality benchmark document. This was not typical of a usual faculty program director's workload, even for new program development. At the same time, personnel searches were underway for the program field director, a JMSW faculty member, a BSW faculty member, and one department chair. During January through August of the first year, the program director consulted with University B's Office of Diversity and Inclusion B's Curtis Austin as needed and with University B's Office of Diversity and Inclusion A's BSW program director.
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The Perceptions, Motivations, and Attitudes of English Undergraduate Students Regarding the Use of Social Media
Recently, the utilization of social media among higher students has become increasingly prominent. Most studies regarding this phenomenon suggested that its updated insights are further required for gathering essential information. In this regard, as English undergraduate students are known as social media users thus, a study on how they utilize social media needs to be conducted. This study is a descriptive quantitative study describing the perception, motivation, and attitude of English undergraduate students towards social media usage. Involving 186 participants, this study employed close-ended questions to obtain the information. The data were analyzed statistically by using Interval conversion. The findings shows that (1) the majority of English undergraduate students had positive perceptions toward the use of social media in two domains: perceived usefulness and ease, (2) there are five motivations in using social media namely entertainment, personal utility, information seeking, convenience, and altruism, (3) the students shows positive attitude towards the use of social media since it enables them to communicate with their professors and peers successfully. To sum up, the result of the research shows that the social media usage has a role to impact English undergraduate students’ perception, motivation, and attitude toward their learning process.
INTRODUCTION
For learners, technology becomes a component of the learning process. Numerous sophisticated technologies have emerged as tools or apps that allow learners to collaboratively create, generate, and contribute knowledge in the areas of information exchange, exploration, and ideas (Sumuer, 2018). Furthermore, digital media technology plays an increasingly crucial part in teenage people's friendship and identity development, as well as online peer communication (Davis, 2012). Meanwhile, social networking has become a common international trend that has spread to practically every corner of the globe, and the internet is growing increasingly influential (Kaya & Bicen, 2016;Wu, 2015). As a result of technological advancements, the internet has evolved into a digital network that connects individuals all over the world. The term "social media" refers to a set of internet-based software that can be used to create social networking sites, social bookmarking, sharing tools, social citation tools, blogging and microblogging tools, virtual worlds, e-conferencing presentations, audio and video tools, e-project management tools, and research and writing with collaboration tools (Kaplan & Haenlein, 2010;Lee et al., 2016;Nwangwa et al., 2014;Selwyn and Stirling, 2016). As known that social media is a social network in which the medium has a role in the education system. The applications give instructional materials and learning management systems to students, especially those in higher education, using social media for interactive sharing of information with personal networks (Memmi, 2015). Several studies reported that social media as a part of technology in their learning process in which it seems to furnish an efficient media to gather insights within interactive opportunities to increase the students' potential (Dabbagh and Kitsantas, 2012;Dhanya, 2016;Talaue et al.,2018;Mushtaq and Benraghda, 2018). A study under education services company of Babson Survey Research Group and Pearson Learning Solution found that social media used by higher education in the learning process has grown 21% from 2012 to 2013 in the United States (Seaman & Tinti-Kane, 2013). A study also reported that social media had penetrated the lives of many young adults, the social media usage of American adults aged 18-29 years soared from 12% to 90% (Perrin, 2015).
The development of social networks has commonly been used by many institutions through social media usage for the learning management system (Al-Deen & Hendricks, 2011;Sloan & Quan-Haase, 2017). In terms of application, the researcher expands the understanding of the use of technology in academic achievement, particularly in the use of social media in English teaching programs. Furthermore, the researcher may employ these findings to guide future researchers in collecting data on social media for similar studies. Technology has the effect of raising student attention and involvement in order to promote information transmission (Yaros, 2012). In this sense, social media has evolved into a technology with a wide range of online activities. Social media includes social networking sites, microblogs, blogs, chat platforms, open-source mapping, and photo and video sharing, among other things (Gastelum & Whattam, 2013). To put it another way, social media offers a wide range of media applications that can clearly be used to mediate social network activities. In a more detailed context, YouTube has typically been seen as a beneficial learning resource for young learners. Studies have shown that utilizing YouTube to improve young learners' English abilities has a beneficial influence.
Social media is considered as teaching and learning tool through numerous activities, in accordance with the studies of phenomenon about social media utilization in higher students (Ariantini et al., 2021). However, several experts and researchers are still concerned about YouTube's shortcomings and risks as a learning resource for teaching English to young learners (Listiani et al., 2021). Study on other social media which focusing on higher level education such as undergraduate students is very limited. The previous findings of the studies also have called for a new study in expanding much detail about evaluations of using social media within several specific aspects. As a result, it is critical to analyze the phenomenon of social media in higher education level to explore the flaws. For this reason, this present study was worth conducted to examine and describe the utilization of social media within the learning process. The proposed study focused on describing several aspects, namely perception, motivation, and attitude of utilizing social media for their learning activities of English undergraduate students at the University of Muhammadiyah Jember. This current study offers to explore the utilization of social media by higher students in their learning activities through a survey study. The result of this study was expected to provide information regarding the use of technology in the higher education level.
METHOD
The present study was carried out using a survey method. The respondents' replies to the questionnaire were used to produce a survey. The descriptive quantitative survey was utilized to gain a comprehensive overview of the most commonly used social media by English undergraduate students, as well as their perceptions, motivations, and attitudes toward using social media for educational purposes. A "descriptive survey study" is a research method that is concerned with current events in terms of conditions, behaviours, beliefs, processes, linkages, or trends (Ary et al., 2006). This study aimed to gather information from English undergraduate students on what they think about using social media in their learning activities by reflecting on their experiences and needs as learners. For data collection, this study used a descriptive quantitative survey with closed-ended questions. The purpose of the survey was to learn about the perception, motivation, and attitude of English undergraduate students toward using social media. This study used a population that was easily accessible. A total of 190 English undergraduate students at the University of Muhammadiyah Jember participated in the study, with 186 English undergraduate students responding. The data in this study were obtained from the responses of English undergraduate students to a questionnaire. The researcher used a structured questionnaire with 33 items related to the research topic to collect the data. In order to complete the questionnaire, English undergraduate students should use a 5-point Likers scale to respond to the alternative responses. The researcher gathered the questionnaire responses and proceeded to examine the data. The Blueprint of the questionnaire can be seen in Table 1. This present study used content validity and reliability. To check the validation of the instrument, the researcher did a piloting test on 30 respondents out of the selected respondents. As a result (Table 2), the Pearson product-moment (r) results showed that the r values (0.379-0.810) were higher than the r table (0.344). Hence, it means that the questionnaire items were valid to be used. Besides, the researcher also assessed the reliability of the instrument. The Cronbach Alpha coefficient was applied to test the reliability of the instrument. The Cronbach's alpha values of the questionnaires were 0.661-0.928. Thus, it can be identified that both reliability results are categorized as reliable if the Cronbach's Alpha value is more than 0.60 (Cohen et al., 2011). The information were gathered by a questionnaire, which was tabulated and measured using a frequent basic percentage. The goal of the study was to discover more about the students' perceptions, motivations, and attitudes toward using social media for educational purposes. After that, all of the research findings were presented in a descriptive manner. Finally, the theme was used to examine the questionnaire. SPSS version 23 was used to calculate descriptive statistics (minimum, maximum, mean, range, and standard deviation) of English undergraduate students' perception, motivation, and attitude about using social media for learning activities. The researcher used interval conversion to divide the perception, motivation and attitude of English undergraduate students toward social media use into three measures. The formula is written following Azwar (2012). The participants of the survey were informed by instruction on Google form about the context, the problem area, and English undergraduate students as subjects for the study in this study. The questions were sent through the Google form into the survey approach, and then they were asked to participate with their satisfaction. The identity and the privacy of participants were promised to be kept anonymous. Current research consists of two research phases in which the data were described using SPSS 23 and supported by theoretical and empirical review. To reflect the relevant concepts of textual study and prepare a basis for final interpretations, theoretical and empirical materials helped the researcher to analyze. The theory was emerged as the result of the research both from collected data sets and analyzed data.
Result
For many students in today's society, learning English has become an interesting subject. Regardless, undergraduate students' use of social media has a significant impact on their ability to improve their language abilities throughout learning activities. The study's findings indicated the perception, motivation, and attitude toward using social media, as well as the most common social media use among English undergraduate students, based on the study's objectives. The information was gathered via a Google Form Link that was distributed to 186 English undergraduate students at Muhammadiyah Jember University. The result shows the perception, motivation, and attitude of the students towards the use of social media as follows.
The English Undergraduate Students' Perception of Utilizing Social Media for Learning Activities.
Perceptions of English undergraduate students are divided into two categories: perceived usefulness and perceived ease. The descriptive statistics of English undergraduate students' perceptions of social media use at the University of Muhammadiyah Jember. Shows the statistics result of students' perception towards the use of social media. The most students (125 students) perceived a positive belief towards the use of social media with the total percentage of 67.2%. The two categories were obtained towards the benefits of social media as can be seen in Table 2. Shows that that the questionnaire had a minimum score of 23 and a maximum score of 50. The total attitude mean score was 38.98 (SD=3.87). As a result, the English undergraduate students at the University of Muhammadiyah Jember showed a good perception of social media use. The two categories were obtained: perceived usefulness and perceived ease.
The English Undergraduate Students' Motivation of Utilizing Social Media for Learning Activities.
The statistics show thorough information about the motivation of English undergraduate students at the University of Muhammadiyah Jember in using social media. The results analysis indicated that with a score of 35-55, 144 or 77.4%, English undergraduate students had a score in the moderate category. According to the result score, 77.4 % of English undergraduate students at the University of Muhammadiyah Jember had a moderate motivation to use social media. There were several reasons that motivate them as can be seen in Table 3. Shows the statistics result of motivation behind the use of social media for student's learning. İt was identified that there were five reasons that motivate students to use social media namely entertainment, personal utility, information seeking, convenience, and alturism. Entertainment (SD=0.47) becomes the most motivated aspect that underlie the use of social media for students. However, Alturism (SD=0.89) becomes the least motivated aspect that underlie the use of social media for students.
The English Undergraduate Students' Attitude of Utilizing Social Media for Learning Activities.
The behavior domain is comprised of the attitude of English undergraduate students. The result of the analysis can shows that the overall behavior score of English undergraduate students' attitude about social media usage at the University of Muhammadiyah Jember was 29.53 within a mean score of 19-29. It can be seen that 59.7% of English undergraduate students, or 111 students, had a good attitude toward social media use. The mean score for overall behavior shows that the University of Muhammadiyah Jember's English undergraduate students have a good attitude about social media use.
Discussion
The findings revealed that English undergraduate students had a positive perception toward using social media for educational purposes. The researcher examined domain results, such as perceived as usefulness and perceived ease, in relation to the overall outcome of English undergraduate students' perception of using social media. The findings of the present study corroborated the prior studies who found that social media is viewed as having potential uses for learning (Alhababi et al., 2015;Odewumi et al., 2017). YouTube, Facebook, and WhatsApp were the three most popular tools for distributing materials. İt is similar to a prior study that the students obtained materials from classmates to finish their tasks using social media and vice versa (Li, 2017). İt shows that through the use of social media, the students are allowed to work collaboratively with their peers to gain information such as instructional materials in supporting their learning (Memmi, 2015;Sumuer, 2018). The social media platforms provide interactive sharing of information enable educators to give instructional materials and learning management systems to students, especially those in higher education (Memmi, 2015). The result of the present study also found that sometimes the use of social media could distract student's attention during studying. This is in line with the result of the previous research that students become addicted to social media, which bothers their attention, thereby causing a massive decrease in knowledge retention (Junco and Cotten, 2012). Furthermore, the findings of the present study indicated that English undergraduate students were moderately motivated to use social media for learning purposes. İt was found that there were five reasons that motivate students to use social media namely entertainment, personal utility, information seeking, convenience, and alturism. The majority of English undergraduate students also believed that they utilized social media to find free information and keep up with current events. They like answering questions on social media, which they may utilize at any moment. İt supports the studies which revealed that people who use social media for knowledge, enjoyment, convenience, and personal utility are more inclined to do so (Dabbagh and Kitsantas, 2012;Dhanya, 2016;Talaue et al.,2018;Mushtaq and Benraghda, 2018). In this regard, current technology is an important component in developing strategies for fostering learning through the facilitation of collaborative learning opportunities, as well as the best approach to combine a range of factors to produce effective learning experiences for students (Heflin et al., 2017;Su & Lai, 2021). Keeping with the social media theme, social media had become a popular educational tool (Neier and Zayer, 2015).
The final result of the analysis is the highest mean score, which describes the positive behavior. According to the English undergraduate students' assumptions, learning becomes interactive through social media, and sharing and receiving feedback from peers becomes simple. They can also efficiently communicate with their educators. This present finding supports the study by Tang et al. (2015) who revealed that social media provides a variety of social roles that can help students learn more effectively. It discusses the advantages of using social media in the classroom. For example, using Twitter for academic and co-curricular discussions has improved college students' grades (Junco et al., 2011). As a result, it showed that English undergraduate students were more likely to have an optimistic outlook. They were at ease using social media to communicate with their peers and educators, such as sharing, discussing, and looking up material. The result of the present study also found that sometimes the use of social media could distract student's attention during studying. This is in line with the result of the previous research that students become addicted to social media, which bothers their attention, thereby causing a massive decrease in knowledge retention (Junco and Cotten, 2012).
The result of this study implies that it is crucial for the English undergraduate students to realize that the utilization of the features of social media beyond the importance of the learning process might impact the negative effect on their learning achievement. The features personal utility of the entertainment side of social media may affect their learning performance which may interrupt their academic achievement. Although the result suggested that they have good perceptions and a good attitude, the utilization of social media is likely to influence their performance in the learning process. There is an opportunity for future research to explore more deeply by interviewing the stakeholder in a particular institution regarding the utilization of social toward their learning process. Although this study touched on the preferred social media used during the learning process, much more research is needed to justify this preference through the larger subject. Additionally, the descriptive survey to measure perception, motivation, and attitude of utilizing social media employed in this study is based on the instruments of the relevant previous studies that were also assumed to be reliable and valid. It can be considered as the weakness of this study. Analyzing the social media utilization in education through other methods could deliver a rich understanding with new perspectives and different insights on this subject. Therefore, a few limitations were faced in the current study that should be considered in future research.
CONCLUSION
Based on the result of the analysis, it can be concluded that the majority of English undergraduate students had positive perceptions toward the use of social media in two domains: perceived usefulness and ease. There are five motivations in using social media namely entertainment, personal utility, information seeking, convenience, and altruism. The students show positive attitude towards the use of social media since it enables them to communicate with their professors and peers successfully. To sum up, the result of the research shows that the social media usage has a role to impact English undergraduate students' perception, motivation, and attitude toward their learning process.
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Covid-19 And Factors Affecting Vietnamese Students’ Readiness For Digital Transformation
Education in Vietnam is trying to make use of the values of the digital technology revolution. As one of the eight key fields of National Digital Transformation, education needs to find ways to develop and take advantage of opportunities to be able to shape the future of society with high-quality human resources. As a huge challenge, the Covid-19 pandemic has quickly put pressure on the past predicted trends in education such as the “university of the future”, but, from a positive viewpoint, it also brings a big opportunity for universities to make the transformation, from classic one to the new and trendy university – the digital one. The paper analyzes in-depth the factors affecting the readiness of Vietnamese students for digital transformation in the above context. The research model is built based on the Technology Acceptance Model (TAM) theory and corrects necessary variables. The results show that the impact of Covid-19, self-study ability and attitude are the factors that have the most influence on the willingness to shift the learning method towards digitization. According to the result, the authors will propose several recommendations on improving the readiness of Vietnamese students for the digital transformation of education and training. Thereby helping students change to adapt to learning activities when the pandemic appears, and know how to take advantage of digital transformation.
Introduction
The outbreak of the Covid-19 pandemic has put pressure on the education industry around the world. Until now, it is clear that the digital transformation truly brought innovation and solutions to the education industry. According to UNICEF data released on 3/3/2021, about 168 million students worldwide had to miss school for nearly 1 year; 14 countries closed their schools between March 2020 and February 2021 because of the Covid-19 pandemic. This has caused a disruption in all teaching and learning activities, pushing educational and training institutions to immediately devise methods to allow students to "stop going to school but not stop learning".
In response to the Covid-19 pandemic outbreak, the Ministry of Education and Training (MOET) in Vietnam issued Official Letter code 795 on March 13, 2020, directing the deployment of online training methods in educational institutions. As the pandemic continues to worsen, official dispatch code 988 dated March 23, 2020, was proposed to unify distance learning implementation and acknowledge accumulated learning results. As can be seen, the Covid-19 pandemic has put pressure on the education industry, while simultaneously providing a tremendous motivation for digital transformation. Education and training institutions have made the most of the chances presented by the Covid-19 pressure to become "universities of the future" -a predicted educational trend (Etzkowitz et al., 2000, Marshall, 2018. Simultaneously, it is necessary to take advantage of IR 4.0 to close the space and time gap, bringing Vietnamese education closer to the quality of international education.
To research the impact of Covid19 and the factors affecting the readiness of Vietnamese students for digital transformation in learning, the article was conducted through a survey of 913 students at many universities in Viet Nam. The authors will next propose some methods to capitalize on opportunities created by the Covid-19 pandemic and encourage digital transformation in higher education, assisting teachers and students in fast adapting to digital transformation.
Literature review 2.1. Theoretical of Technology Acceptance Model
In order to identify and analyze the factors affecting intention and habit of using technology, authors have mainly used the Theory of Technology Acceptance Model -TAM of Davis (1989). According to Davis (1989), two factors ('Perceived Usefulness' and 'Perceived Ease of Use') are influenced by extrinsic factors and it can be predicted the "Attitude" of students. Moreover, "Perceived Usefulness" is not only an external factor but also directly affected by "Perceived Ease of Use". "Attitude" and "Perceived Usefulness" themselves will also influence the intention to use technology in a particular context and thereby, predict the intention and habit of using the system.
Research model
Previous studies have identified a variety of factors that can influence user behavior towards technology use. In terms of teaching and learning, Computer effectiveness (Chow et al., 2012), Social influence (Farahat, 2012), Feeling of enjoyment (Wu & Gao, 2011), Computer anxiety (Alenezi et al., 2010), and Experience (Martin, 2012) are the factors affecting students' decision to use online learning systems that researchers have pointed out. These are considered extrinsic variables in Davis' extended TAM model (Abdullah and Ward, 2016) and are limited to TAM's core beliefs (i.e. Perceived Usefulness and Perceived Ease of Use). Although studies have demonstrated that external factors also play an important role in explaining technology adoption behavior, due to limited resources, the research team did not go into depth to assess the influence of these factors; our research focuses on the acceptance of technology application in student learning activities. King and He (2006) after reviewing many studies, concluded that TAM is a perfectly suitable model to study the situation of accepting technology in learning. According to Šumak et al. (2011), TAM is the most popular theory in the research of technology and education, with 86% of the studies using TAM as the theoretical basis because this model provides the ability to solve problems. In the same opinion, Abdullah and Ward (2016) and Al-Qaysi (2018) believe that the application of the TAM model when researching technology acceptance in education and training will be more effective than other methods. Besides, through in-depth interviews and practical experiences, the research team found that students' acceptance of technology in learning is reflected in digital transformation and their willingness to change learning methods. Therefore, the team will use the TAM model as an important foundation theory and adjust the variables simultaneously to conduct research on learners' readiness for digital transformation in higher education. Since then, we have built the research model and the following hypotheses:
Attitudes (ATT)
Fatema et al (2015); Chu & Chen (2016) suggested that this attitude has a positive impact on students' acceptance of using online learning systems. The research of Salloum et al (2019) and Rizun & Strzelecki (2020) also reinforced this statement. From there, the group proposed the hypothesis: H2: Attitudes towards online learning have a positive impact on students' digital transformation readiness 2.3.3. Self-study Ability (SSA) According to the results of in-depth interviews conducted by the team, when all learning and teaching activities are online, students' self-study ability also contributes to their readiness. According to Knowles (1976), "selfstudy" is a process in which learners, with or without the help of others, can identify their own learning needs, develop learning goals, select learning aids, effectively implement learning strategies, as well as evaluate their learning results. From there, they can work independently and cooperate with others (Trinh & Rijlaarsdam, 2003). Simultaneously, Selim (2007) also suggested that the cooperation between learners can influence the use of the online learning system more. From there, the group proposed the hypothesis: H3: Self-study ability has a positive impact on students' readiness for digital transformation 2. In theory, the Covid-19 epidemic taking place in Vietnam has no relation to the change in students' learning methods. However, the outbreak of this pandemic has caused both "teachers and students to quickly adapt", and "requires changes to adapt to learning without direct interaction". Is there a positive relationship between the Covid-19 epidemic and digital transformation in learning? Research hypothesis H4 is proposed based on testing the controlling role of the Covid-19 variable on students' intention to convert digitally. Hypothesis H4 is stated as follows:
Research Methodology
The authors created a research model and a draft scale based on theory and research overview. This draft scale system was calibrated using in-depth interviews with lecturers and students from various majors and universities. Following that, the authors designed the questionnaire, conducted a preliminary quantitative survey with 53 responses, and analyzed the Cronbach's Alpha reliability coefficient to ensure that the variables and scale were adequate for the research model. The official questionnaire is completed in order to conduct a formal quantitative survey with a sample size of 913 students currently enrolled in universities in Vietnam.
The data analysis revealed that both sexes participated in the study, with women accounting for the majority at a rate of 69.1%. The majority of survey respondents live in cities (78.4% ). In fact, although students come from many regions, the proportion of individuals living, learning, and working in cities is frequently higher than in suburbs. Students from a variety of majors took part in the study as well. Students who participated in the poll studied Business and Management the most (54.3%), followed by Humanities, Social Sciences and Behavior, Journalism, and National Defense, as well as students from Health, Mathematics and Statistics, Information Technology, Engineering, and other majors such as Education and Training, Life Science, Natural Science, Law,... The obtained data were coded and quantitatively analyzed to test the scale by Cronbach's Alpha analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), hypothesis testing, and effect assessment through running the Structural Equation Modeling technique. The reliability of the scale is assessed by Cronbach's Alpha analysis on the preliminary survey sample. The overall Cronbach's alpha coefficient is 0.912 and the Cronbach's Alpha if item deleted coefficient is in the range of 0.653 to 0.910. The final results show that the value scales of the factor groups are reliable and the data correlation is consistent with the built scales. Then, the research team turned to EFA exploratory factor analysis to verify the convergence of the scale system of the factors in the model. Source: Summary of the research team's results, 2021 Exploratory factor analysis (EFA) with a group of factors helps to assess the convergence and distinguish the value of the scale. Both KMO and Bartlett tests in EFA show that the hypothesis of correlation between variables can be accepted (Sig. = 0.000). KMO coefficients of all factor groups are > 0.5 (group of factors Awareness = 0.789; group of 'Attitude, Self-study, Covid-19, Readiness level' = 0.923) shows that EFA can be used. The analysis results show that at Eigenvalue > = 1, with the "Principal Axis Factoring" method and the "Promax" rotation, there can be 6 factors extracted from 22 observed variables, and variance of the extraction of three groups factors is 67.99%, respectively (PU, PEOU); 65.19% (ATT, SSA, Covid-19, Readiness level for digital transformation) are > 50%. The EFA test can be used for confirmatory factor analysis (CFA).
Confirmatory factor analysis results
To test the model's fit with market data, the research team performed a CFA analysis. The scale of the independent variables has been grouped into the following groups: "Perceived value" (PU), "Perceived ease of use" (PEOU), "Attitude" (ATT), "Self-study Ability" (SSA), is shown in the The above results show that Chi-square / df = 3.765 (<5), GFI = 0.945 (>0.9), CFI = 0.970 (>0.9) and RMSEA = 0.055 (<0.06). Therefore, the model can fit the research data and can be used for the next steps of analysis.
Structural Equation Modeling (SEM) analysis
The research team used the Structural Equation Modeling (SEM) technique to analyze the multidimensional relationship between the dependent variable "Readiness for Digital Transformation" (CHA) and two independent variables in the model. The obtained results are shown in the figure 3: Figure 3: SEM results with the model without control variables Source: Summary of the research team's results, 2021 It can be seen that two factors: "Attitude" and "Self-study Ability" both have a significant impact on the "Readiness of digital transformation" of students. The independent variables contributed 54.8% of the change of the dependent variable. In which, two factors "Perceived Ease of Use" and "Perceived usefulness" can predict 69.2% of the variation of "Attitude". The P index (sig) of the variables are all < 0.05, reaching the 95% confidence level, so the relationships between the independent variables and the dependent variable are significant. Unstandardized regression weight shows the degree of impact of the independent variable on the dependent variable. ATT <---PEOU 0,284 0,000 Accepted H2 CHA <---ATT 0,329 0,000 Accepted H3 CHA <---SSA 0,539 0,000 Accepted Source: Summary of the research team's results, 2021 The independent variable "Self-study ability" (SSA) has the greatest impact on the dependent variable "Readiness for Digital Transformation" (CHA), followed by the moderator variable "Attitude" (ATT). Thus, if students support, feel excited and proactive when learning online, the level of readiness for digital transformation in learning will be higher.
As the strongest influencing factor, the independent variable "Self-study ability" contributes to promoting the level of readiness for the digital transformation of Vietnamese students. So, if students actively participate in learning activities or interact with lecturers, students will be more ready for digital transformation. This can be explained by the fact that when Vietnamese students are more active in their learning, they will also actively adapt to changes in the context to make learning easier and more effective, thereby leading to an increase in the willingness to change learning behavior towards digitalization. Moreover, digital transformation, as mentioned in the context section, is inevitable in education. Therefore, if students have the desire to be proactive with their learning, they will also have the mentality of quickly adapting to the digital transformation in education, thus enhancing students' readiness for digital transformation. In addition, Selim (2007) also explained that the active cooperation and exchange among students can influence the use of the online learning system more, hence positively affecting their academic performance (Laily et al., 2013). As a result, this can be considered as a new factor discovered by the research team to strengthen and contribute to previous works.
Besides, the variable "Attitude" (ATT) is more strongly affected by the independent variable "Perceived usefulness" (PU) than "Perceived Ease of Use" (PEOU) when the unstandardized regression weights are 0.725 and 0.284 respectively. This result reinforces Park's (2009) study, which demonstrated that perceived usefulness has a statistically significant impact on attitudes toward a willingness to accept new learning methods. In addition, the influence of attitude on the intention to accept the behavior has been confirmed through the unstandardized regression weights of 0.309 and shows the similarity with the study of Park (2009) that used to do in Korea -an Asian country like Vietnam. As students' attitudes towards digital transformation education can shape behavior towards online learning and ultimately lead to learners' acceptance of it or not. This is completely reasonable in Vietnam, students find that using software and technology equipment does not require too much effort because they always use them competently to serve their study. exercise as well as other activities such as entertainment, work, connection,...
Analyzing the impact of Covid19 on digital transformation readiness
As a control variable in the SEM model, COVID-19 also affects the dependent variable "Readiness for digital transformation" (CHA) and makes the relationships between factors might change. The results obtained are shown in the figure and table as follows:
Figure 4: Normalized SEM results with control variable of COVID-19
Source: Summary of the research team's results, 2021 The result showed that "Attitude" and "Self-study ability" still have a remarkable impact on the "Readiness for digital transformation" of Vietnamese students, control variable Covid-19 also contributes to this effect. The above three factors can explain up to 58% of the change of the dependent variable, higher than the SEM model analyzed in Section 4.3. In which, attitude can still be predicted by two variables "Perception of the value of online learning" and "Ease of doing online learning" with a squared multiple correlation index of 76, 9%. When Covid-19 is a control variable in the model, the P (Sig.) index of the hypotheses is still less than 0.05, reaching 95% reliability. Thus, the relationships of the independent variables and the control variable on the dependent variable are significant, the hypotheses H1a, H1b, H2, H3, H4 given with the SEM model have the appearance of Covid-19 are all accepted. Table 5 below will compare the impact of the independent variables between the two SEM models by the regression coefficients (Regression Weights) that have been synthesized by the group through 2 times of analyses.
Journal of Education and Practice www.iiste.org ISSN 2222-1735 (Paper) ISSN 2222-288X (Online) Vol.12, No.16, 2021 Source: Summary of the research team's results, 2021 Through the SEM results with the presence of a control variable, authors found that the influence level of independent variables has changed even though the impact relationships are still positive. Self-study ability is still the factor that has the strongest impact on the dependent variable "Readiness for digital transformation" but the unstandardized regression index has decreased to 45.9%. The control variable "Covid-19" now acts as the second strongest factor with 36.3% and the last variable is "Attitude" because the impact value has changed, which was reduced to only 15.1%. At the same time, when Covid-19 appeared, the effect of "Perceived usefulness" on attitude increased significantly (86.9%). Meanwhile, the influence of "Perceived ease of use" on attitude decreased very little with the unstandardized regression index of about 19.8%.
Covid-19, the control variable in the research model has shown an important role as the second most influential factor, only after the factor belonging to the students -self-study ability. It is witnessed that the Covid-19 pandemic causes all education and training institutions to suspend all activities, online learning is considered the only solution for students to continue their learning activities. Universities have immediately pushed to implement distance education in order to keep teaching and learning activities (Barnes, 2020). However, besides the support from the unviersity and the lecturers, students themselves need to familiarize, adapt, and actively learn with devices, software, and technology platforms, and this is considered the clearest indication of readiness for digital transformation. In fact, the pandemic has made it impossible for students to have a second choice, if they are not willing to change their learning methods, students will not be able to guarantee learning outcomes. Moreover, after going through three waves of the epidemic, Vietnamese students have experienced, adapted, and verified the effectiveness of the blended-learning model, which is a combination of online and face-to-face learning. MOET (2020) has commented that: "The results of online teaching during the Covid-19 epidemic are evaluated well. However, it is still necessary to reorganize digital transformation activities in a more methodical way to improve efficiency". It can be affirmed that Covid-19 has made learners more aware of the role of online learning and also made them use more technology, integrate more tools and software in learning. Going through such a long process has motivated and made them more ready for this educational transition.
From the research results along with the education situation in Vietnam, the authors found that if Covid-19 continues to happen, under inevitable pressure, students will still be ready to change their learning methods. However, research by Burke and Dempsey 2020 has shown that there is still a high probability that there will be a group of students who may not continue their studies if they still have to study online. This means that closing schools can exacerbate the risk of educational disruption, where learners may pause their studies (Baker 2020). Therefore, schools need to have a clear orientation about the online curriculum so that teachers can continue to deliver instruction or guide learners in an appropriate, flexible, effective, and unrestricted manner (Onwusuru and Ogwo, 2019). Thereby helping students get the best learning experience, motivating them to be more ready for this digital transformation of teaching and learning.
Digital transformation in higher education is inevitable
The world is witnessing dramatic changes in the digital age of Industry 4.0 and the far-reaching influence of science and technology on people's lives. These changes have had a comprehensive and profound impact on all areas of socio-economic life of countries. The goal of the current educational digital transformation is to train workers with enough knowledge and skills to respond to the rapid changes of society in order to avoid the risk of being fired. As a downstream training level, directly providing human resources for the labor market, only when the face of the education industry changes, universities, educational institutions, and training pioneers approach the job. Teaching and learning in a new way, making the most of technological advances and connected things, will be able to train quality human resources, keep pace with the needs of the market and meet the needs of the world. requirements of society. "The education sector is very interested in training Vietnamese citizens with digital transformation knowledge and skills to become global citizens. Doing well in digital transformation not only helps improve the quality of education but more importantly contributes to improving labor productivity, Journal of Education and Practice www.iiste.org ISSN 2222-1735 (Paper) ISSN 2222-288X (Online) Vol.12, No.16, 2021 40 creating great opportunities for international integration" (Ministry of Education and Training, 2020). With such a goal, education will be one of the main pillars, effectively contributing to the success of the national digital transformation.
Covid19 as a driver of digital transformation in higher education
It is experienced that context is one of the most important factors when discussing this issue. The Covid-19 epidemic has made a great impact on the acceptance of online learning methods as well as the willingness of students to shift their learning behavior. The essence of Industrial Revolution 4.0 is the application of technology, data science, and the use of artificial intelligence for production and human life. IR 4.0 brings many favorable conditions to help people discover new sources of knowledge, improve the scale and quality of the economy. That is a prerequisite for the transition to online learning. The Covid-19 epidemic appeared, causing all activities to stop and paralyze, but Education and Learning must always continue to change to adapt, to keep pace with the development of technology that has always existed in the current context. Besides, the Covid19 pandemic also brings many opportunities for Vietnamese universities. Tran Thi Van Hoa et al (2020) says that one of the biggest opportunities that schools must know how to seize is to accelerate the application of digital technology in all school activities from teaching, scientific research to the digitization of learning materials and management information to progress towards building a "smart university". Many institutions have determined Covid-19 is an opportunity to promote the digitalization of materials so that all lecturers, students, and administrators can exploit the positive factors in the application of information technology in management, teaching, and learning activities; and can be flexible in time and space for teaching and learning. Covid-19 has opened up a new vision, helping Vietnam's education industry orientate to build the "University of the future", contributing to the national digital transformation.
Universities and educational institutions
Firstly, it is necessary to have the policy to train and guide managers and lecturers to help them have enough IT knowledge and skills to know how to teach in the digital environment. Simultaneously, universities need to enhance research activities to find the best online teaching methods to ensure the quality of teaching and learning. Secondly, education and training institutions need to promote communication activities so that students can be more aware of the online learning process and the values of the e-learning system. Thereby promoting students' awareness of learning to help them adapt to this new learning method and be more active in the learning process. Thirdly, ít is recommended that universities should have specific plans on curricula, teaching and learning materials, etc. when universities implement online training methods. Simultaneously, universities should reduce procedures to avoid barriers for students to register for academic credits in the online learning process.
Lecturers
Firstly, lecturers need to actively use modern technology tools and apply new teaching methods to create an innovative and creative learning environment. This also contributes to strengthening students' consciousness, making them more aware of the usefulness of the online learning system. This is also the basis for creating excitement when learning according to the new learning method for students. Secondly, lecturers should actively interact with students during online teaching. Specifically, they can ask questions for students to discuss, actively communicate and answer questions for students via email, LMS, etc. This will contribute to promoting awareness of students, thereby contributing to improving students' attitudes towards new learning methods.
Students
Firstly, students -the destination of transferred knowledge, skills, and experience: In order to achieve good learning efficiency in a learning environment that lacks face-to-face interaction, they need to have a sense of self-discipline during the online learning process. Students need to actively interact with lecturers through platforms and software such as Teams, Zoom, LMS, email, etc. to discuss, communicate and answer questions about learning content.
Secondly, with the ability to use technology well, students need to equip themselves for integrating skills of using tools such as Google Drive, Powerpoint, etc., and modern technology devices such as Ipad, laptop, notetaking applications electronic, etc. to support the learning process, making online learning more effective.
Thirdly, to be able to quickly catch up with new training methods, students need to know how to arrange and manage their schedule appropriately so that they can balance between study and personal activities when taking part in online learning.\===
. The above document has 2 sentences that start with 'Thereby helping students', 2 sentences that start with 'From there, the group proposed', 2 sentences that start with 'The Covid-19 epidemic', 2 sentences that end with 'in the model', 2 sentences that end with 'the dependent variable', 2 sentences that end with 'readiness for digital transformation', 2 sentences that end with 'teaching and learning', 2 paragraphs that end with 'the national digital transformation'. It has approximately 4175 words, 156 sentences, and 40 paragraph(s).
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Effective Circuit Configuration and Control for Coil-Array Wireless Power Transmitters
This article presents a circuit configuration and control for coil-array wireless power transmitters. The target coil arrays have coils that are uniform in shape and dimensions and are regularly arranged with an angular interval of 120°. The system has a three-leg half-bridge inverter, which simultaneously feeds the three coils in the transmitter. It can deal with more than three coils by adding a switch set between the inverter and the coils. The system has a configuration to cancel mutual inductances between the transmitter coils and improve the power factor of the system. It can maximize the efficiency from the transmitter coils to the receiver coil and can output uniform power regardless of the receiver position. The current condition for achieving these features is derived, and a field-programmable-gate-array-based control for realizing the current condition is presented. The performance of the proposed system is experimentally validated with an implemented prototype. Results show that the system has a power variation of less than 5.8% depending on the receiver position. The system can operate at approximately maximum efficiency.
I. INTRODUCTION
When discussing wireless power transfer technology, misalignments between a transmitter and a receiver are inevitable issues. One of the approaches to the issue is the employment of a coil-array structure for the transmitter. The coil array arranged along a pathway gives one-dimensional freedom to the receiver. This array can be applied to a charger for moving vehicles [1], [2]. Coil array expanded on a plane gives twodimensional freedom to the receiver, without exact position control of the receiver [3], [4], [5], [6], [7].
There are several circuit configurations to feed the coilarray transmitters [8]. An inverter simultaneously energizes multiple serial coils via a series resonant capacitor [9] or multiple parallel coils via an LC and LCL compensator [10], [11]. These configurations can be fabricated simply and costeffectively. On the other hand, the same number of inverters [12], [13] as that of the coils or a half-bridge inverter [14], [15], [16], [17], [18] with the same number of legs can be used. Only the transmitter coils close to the received coil are energized by the inverter, which leads to high-efficiency and low-magnetic-leakage operation. In recent years, configurations where the switches are set between the inverter and the transmitter coils have been researched [19]. The switch selects the transmitter coils close to the receiver to connect the coils with the inverter. The switch can be a low-speed-switching device, such as electromagnetic relays, which is more costeffective than switching devices used in the inverters. Thus, the configurations can be realized in low cost and can be operated in high efficiency and in low magnetic leakage. However, the following issues have not been addressed yet.
1) The power assignment of the transmitter coils is not optimized. For instance, a current is uniformly drawn into all the active coils regardless of the magnetic coupling with the receiver coil. This operation is inefficient because the coils away from the receiver do not contribute to the power transfer while the coils generate loss. To gain higher transfer efficiency, the currents through the transmitter coils should be allocated appropriately. 2) Uniform power transfer is not always ensured with respect to the receiver position. A multilayer coil-array transmitter [3], [20] is a structure capable of uniform power transfer. However, it is not suitable for high-power applications. In the coil-array transmitters formed on a layer, the magnetic coupling with the receiver varies considerably with respect to the receiver position. Therefore, for example, the receiver above the clearance between the transmitter coils and the receiver just above a transmitter coil have different powers unless the currents through the coils are not controlled appropriately. 3) Mutual inductance between the transmitter coils is not considered or is disregarded. The mutual inductance as well as the self-inductance of the coils degrade the power factor of the system. They should be canceled to improve performance. This article proposes an effective circuit configuration and a control method for coil-array wireless power transmitters. The proposed configuration and control can be applied to the coil-array transmitter with considerably variable magnetic coupling with the receiver. In this article, the target transmitter is a coil array formed on a layer. The system comprises a three-leg half-bridge inverter, which simultaneously feeds three coils in the transmitter. The system can deal with numerous coils by adding a switch set between the inverter and the coils in the system. The system can cancel the mutual inductances between the transmitter coils with the additional resonant reactance element that is set between the connection of the transmitter coils and the inverter. The system can control the currents through the transmitter coils so that the efficiency between the transmitter coils and the receiver coil is maximized and the transfer power is uniform regardless of the receiver position. Unlike [21], [22], and [23], the control can achieve this performance with the voltage and current information in the inverter and without knowing the values of the mutual inductance between the transmitter and the receiver and the receiver position. Therefore, the proposed control can operate dynamically.
The rest of this article is organized as follows. Section II describes the circuit configuration and parameters of the resonant reactance element. Section III derives the optimal current through the coils, and Section IV validates the performance of the optimal current control numerically. Section V presents the implementation of the field-programmable gate array (FPGA)-based control. In addition, the pulse-width modulation algorithm to eliminate the influence of dead time is presented. Section VI experimentally examines the proposed system with an implemented prototype and validates its performance. Finally, Section VII concludes this article. Fig. 1 shows a concept of target coil-array transmitters, where the three coils L u , L v , and L w with the same structure and the same dimensions are regularly arranged with an interval of 120°. In addition to the coils forming a hexagonal shape [3], [20], the proposed circuit configuration and control can also be applied to circular-shaped and square-shaped coils. The receiver coil L 2 is set over the array via a vertical air gap l g in length. The arrangement of the transmitter coils does not ensure a uniform power transfer, even if current uniformly flows through the coils. Fig. 2 shows the proposed circuit configuration for a coil array with three coils. The three-leg half-bridge inverter feeds the coil array. Each coil is connected to a leg of the inverter via the capacitor C 1 . Another end of the coil is y-connected with the others, and the connection is led to the inverter via the resonant reactance element X 0 . In the figure, although the connection leads to a potential of E/2 in the inverter, any potential between zero and E can be applied to it.
A. CIRCUIT CONFIGURATION
Because of the symmetrical structure of the coil-array transmitter, the self-inductances and the resistances of the coils and the mutual inductances between the coils can be represented by L 1 , r 1 , and M 1 respectively. The equivalent equation of the transmitter is given as follows: whereV u ,V v , andV w are the output phase voltages of the inverter, andİ u ,İ v , andİ w are the currents through the transmitter coils. M u2 , M v2 , and M w2 denote the mutual inductances between the transmitter coils and the receiver coil. Arranging this equation yields the following: Setting the capacitor C 1 and the reactance value X 0 at Thus, the reactance in the transmitter can be completely canceled. In the coil-array transmitter shown in Fig. 1, the mutual inductance M 1 has a negative value, and an inductor L 0 with the following inductance is used as X 0 : Alternatively, when the coils in the transmitter are widely overlapped with each other, M 1 can have a positive value. In this case, a capacitor C 0 with the following capacitance is used as X 0 : Fig. 3 shows an expanded coil-array transmitter. Fig. 4 shows the circuit configuration for the expanded coil-array transmitter. The transmitter circuit has a configuration where a switch set is added to the circuit shown in Fig. 2. The circuit can be fabricated with less switches than that presented in [19], although the magnetic coupling with the receiver varies larger, which leads to ununiform power transfer unless the proposed configuration and control are not employed. In the circuit, a resonant capacitor is set on every coil. If the self-inductances of the coils in a group are the same, a capacitor can be set in every group. Three groups, U, V, and W are assigned to the coils and the legs in the inverter. The switch set connects an inverter leg to the coil that belongs to the same group as the leg and is the closest to the receiver coil in the group. For example, when the receiver coil is set at the position shown in Fig. 3, the U-leg, V-leg, and W-leg are connected with L t6 , L t7, and L t3 , respectively. As a result, any combinations of active three coils have a positional relation with the receiver coil, like the relation shown in Fig. 1, where L u , L v , and L w are the coils of the U-group, V-group, and W-group, respectively. This article is focused on the efficient power transfer in the coil-array transmitter with three coils, and the switchover of the coils is outside the scope of this article.
III. CONTROL ALGORITHM
The optimal current maximizing the efficiency between the transmitter coils and the receiver coil is derived in this section. The first discussion is for the case where three coils are different in shape and dimensions and are arbitrarily arranged in three-dimensional space, as shown in Fig. 5. In this case, the coils have different resistances, r u , r v , and r w . The circuit configuration shown in Fig. 2 is used to feed the wireless power transfer coils. The receiver coil has the self-inductance L 2 and the resistance r 2 . C 2 completely resonates with L 2 . The load is assumed to be a resistor R for simplification. The output power P R and resistive losses P r1 and P r2 in the transmitter and the receiver are given as follows: where ω = 2π f is the operation angular frequency of the system, andV 2i is the induced voltage in the receiver coil. The voltage is given as follows: The transfer efficiency η c between the transmitter coils and the receiver coil is defined as follows: Equations (7) and (9) imply that the maximum efficiency is available when P r1 is minimized under a fixed voltage |V 2i |. The current condition required to satisfy this can be obtained by solving the geometric question that asks the tangent point of a plane represented by (8) and an ellipsoid represented by (7a) in the rectangular coordinate system with I u , I v , and I w . At the tangent point, the directions of the normal vectors of the two geometries correspond to each other. Therefore, the optimal currents are given as follows: where λ is a coefficient. Because the mutual inductances are in proportion to the induced voltages V ui , V vi , and V wi in the transmitter coils: ⎡ equation (10) can be changed to ⎡ Thus, optimal currents are available with these induced voltages and the resistances of the coils. Based on (4) with the perfectly resonant receiver, the induced voltages can be calculated with ⎡ Consequently, on the basis of (12), the current command values I uc , I vc , and I wc for the optimal current control are defined by the following equation: where P 2c is a power command value. The phase angle of the currents is set at 0 or π . When the induced voltage has a positive value, the phase angle is set to 0, otherwise, the phase angle is set to π . Controlling the currents at I uc , I vc , and I wc can achieve uniform power transfer regardless of the receiver position. This is proved by substituting (14) into (8), which yields the following: Multiplying I 2 to both sides of the aforementioned equation and then arranging it yields the following: Thus, the power V 2i I 2 , which implies a power transferred to the receiver, corresponds to a constant, P 2c . Since the power V 2i I 2 is the sum of the output power P R and the resistive loss in the receiver coil, P R is given as follows: When the load resistance R is a constant, P R is also a constant under a constant P 2c . When r 2 is much smaller than the load resistance R, P 2c can be assumed to be equal to P R , that is, the system is robust over the fluctuation of the load resistance. Fig. 6 shows a coil-array transmitter used to test the performance of the proposed system. The three coils, L u , L v , and L w , with a hexagonal shape, are tightly arranged with an interval of 120°. They have the same structure and the same dimensions. In [3] and [20], coil-array transmitters with hexagonal coils are implemented on multilayers of a printed circuit board. The arrangement with positional shifts every layer contributes to the uniform power transfer when a current is uniformly drawn to the coils. Alternatively, the array shown in Fig. 6 consists of windings made of wires on a layer. The one-layer structure is employed for the system dealing with a larger power [15]. Its drawback is that uniform power transfer is not ensured even if a current is uniformly drawn to the coils. The receiver coil has a circular shape and is set above the transmitter via an air gap. In the figure, the three positional points are defined; remarkably, P1 is the center of L u and P2 is the contact point of the three coils. These points are used as representatives of the center positions of the receiver coil. Table 1 lists the parameters used in the analysis. Because the transmitter coils have the same structure and the same dimensions, their resistances and self-inductances can be represented by r 1 and L 1 , respectively. Fig. 7 shows the mutual inductance M u2 between L u and the receiver coil at receiver positions. These were calculated with finite-element analysis. The mutual inductances M v2 and M w2 of L v and L w with the receiver coil are distributed in the same manner. Fig. 8 shows the distribution of resistance values that maximize transfer efficiency at receiver positions. The equilateral triangle in the figure has corners at the centers of the transmitter coils. In the expanded system shown in Figs. 3 and 4, when the receiver coil is outside the triangle, another combination of transmitter coils is used. Inside the triangle, the variation of the resistance is slight; 7.14 is marked as a peak at P1, whereas 5.70 is marked as a valley at P3. The average over the inside of the triangle is 5.81 . 9 shows the power transfer efficiency η c under P R = 500 W and optimal load resistances at transmitter coil currents. As aforementioned, the currents distribute on a plane when the power is fixed at a level. To be exact, there is another plane capable of transferring the same power, which is arranged in point symmetry with the origin. In the symmetrical plane, the signs of the currents are inverse to the plane shown in these figures. It is confirmed that the optimal current command values calculated by (14) mark maximum efficiency. Fig. 10 shows the variation of the optimal current command value I u for L u at receiver positions. Currents over 1.0 A distribute widely above parts of L v and L w . This implies that simultaneous energization of the three coils is necessary to improve the efficiency, especially around the contact edge of the coils. As a result, even at P2, an efficiency of 94.9% is available, as shown in Fig. 11. Fig. 12 shows the transfer efficiencies when a current is uniformly drawn to the three coils. In comparison with the optimal current condition, the area with efficiencies of more than 80% is smaller, and the peak value is lower by 1.5%. Thus, the proposed control using optimal currents has higher efficiencies than the conventional method. Fig. 13 shows the control block diagrams. The sensed current i u through L u is transformed to the real and imaginary components I u_re and I u_im of the fundamental with the discrete Fourier transform (DFT). The currents are controlled to a command value I uc and zero, respectively, using proportionalintegral (PI) control. I u_im is zero without the control when the reactance of the coil array is completely canceled. The control can compensate for the deviation of the current phase owing to the existence of a slight reactance. The outputs of the PI control blocks are transformed into voltage with the phase angle θ u and the magnitude V u . Through similar control blocks, the voltages V v and V w for L v and L w are calculated to control i v and i w , respectively. The amplitudes of these voltages are used to generate current command values with (13) and (14). When the receiver coil is absent or away from the transmitter coils, the sum of squared induced voltages is significantly small. In this condition, the controller sets the current command values at a low level instead of (14), which can prevent overcurrent and allow the controller to detect the proximity of the receiver coil. Alternatively, the voltages V u , V v , and V w are inputted to the one pulse modulation block, which generates switching signals for the inverter. Unlike one of the techniques described in [24], the one pulse modulation block has a function for compensating for dead time. Fig. 14 explains the algorithm for it. The signal S op in Fig. 14(a) is an output of the conventional one pulse modulation block. The signals S up and S un turn ON with a lag of dead time t d behind the switching of S op . Since the output current in the inverter varies sinusoidally as shown in Fig. 14 owing to the resonant circuit, the output voltage is -E/2, during the dead time. As a result, the output voltage differs from the desired voltage. In the proposed method, turn-ON of S op is advanced, and the turn-ON duration is expanded by t d . It should be noted that the turn-ON duration is limited to half of the operation period. Consequently, the output voltage can have a desired width, as shown in Fig. 14(b).
B. FPGA IMPLEMENTATION
The control was implemented in XILINX FPGA, XC7K160T-1FBG484C. The system clock is set at 87.04 MHz, which is 1024 times the fundamental operation frequency of 85 kHz. The currents are sensed and A/D converted every 16 clocks. Therefore, 64 digital data points are available per one cycle period of the fundamental. For DFT, 128 data points are used. The PI controls are executed every 4096 clock cycle. The command generation is executed every 65 536 clock cycle. Fig. 15 shows the experimental setup. Its system configuration is shown in Fig. 2, where the load consists of a rectifier and a resister R. The parameters of the system are listed in Table 2. The load resistor R is set to 8.85 , which is calculated as the average value over the area inside of the triangle shown in Fig. 8, based on the measured parameters. This value is larger than the value obtained by numerical analysis. This is because the mutual inductances used in the analysis are lower than the measured mutual inductances. The transmitter coils form a hexagonal shape and have the dimensions as presented in Fig. 6. Because the mutual inductances M uv , M vw , and M wu between the transmitter coils are negative, an inductor L 0 is employed as X 0 . Since there are differences between the mutual inductances because of manufacturing error, an average of the inductances is used to set L 0 . Similarly, the selfinductances of the transmitter coils differ from each other. The different resonant capacitances are set so that the reactance values become nearly zero for every transmitter coil. Table 3 lists the measured reactance values of the transmitter coils that have been compensated by the inductor and capacitors. For example, X u stands for the reactance value of the coil L u while the other coils are in an open circuit. Similarly, X uv stands for the reactance value of the compensated coil L u and coil L v in parallel while the coil L w is in open circuit. It is confirmed that the reactance values are significantly low in every case. For the command generation in the control, the resistance r 1 was set to the sum of the averaged coil resistance and a conductive resistance of 60 m of the switches (MOSFET of ROHM, SCT3060) in the inverter. The receiver coil forms a circular shape, with an outer diameter of 200 mm and an inner diameter of 152 mm. The receiver coil is set with a vertical gap length, l g of 50 mm. Fig. 16 shows waveforms under the proposed control with a P 2c of 550 W. The receiver coil is set at P3, where the mutual inductances M u2 , M v2 , and M w2 are 9.45, 2.70, and 0.315 μH, respectively, in measurement. Because the resistances of the transmitter coils are uniform, the ratio of the optimal currents approximately corresponds with the ratio of these mutual inductances. The result confirms that the controller can adjust the currents in this manner. Although the current i v is distorted, the receiver current varies sinusoidally. Thus, the harmonics in the currents through the transmitter coils do not influence the power transfer. This is why control deals with only the fundamentals of the currents. Fig. 17 shows the output powers under the proposed control. The power command value is set at P 2c = 550 W. Inside the triangle, 520 W is measured as a peak power at the center of L v , and 490 W is marked as a valley at P2. The variation is only 5.77%. Fig. 18 shows the breakdowns of the losses and output power in the system, which were obtained by the measurements. At P1, the transferred power P 2 , which is the sum of the output power, the resistive loss of the receiver coil, and the loss of the rectifier, is approximately 550 W. Alternatively, at P2, the transferred power is 525 W, which is lower than P 2c = 550 W. This slight reduction is caused by the conduction loss in L 0 , the switching loss in the MOSFET, and, especially, the deviation of the resonant circuit. The mutual inductance used for determining L 0 is an average value. The difference from the actual values generates a little reactance and causes the controller to fail in accurate estimation of the induced voltages V ui , V vi , and V wi . These factors are reinforced at P2, because the sum of squared currents through L 0 is the largest. Fig. 19 shows efficiencies η s of the whole system at P 2c = 550 W. An efficiency of 93.13% is marked as a peak at the center of L v and 81.42% is marked as a valley at P3. The lowest efficiency at P3 is caused by the largest losses in the inverter as well as the coils due to the largest currents, as shown in Fig. 18. Fig. 20 shows efficiencies η s at P R = 200 W, without the proposed control, when the receiver is at P3. The current command calculated by (14) is close to the current combination with the maximum efficiency. The maximum efficiency is 87.40%. The efficiency at the command value is 86.72%, which is only 0.7% lower than the maximum efficiency. The deviation between the command and the optimal current is caused by the loss in the inverter. Fig. 21 shows the waveforms in the transient state when the receiver is at P3. When the receiver coil is absent, the controller outputs currents with a low amplitude, which is needed for the controller to detect the proximity of the receiver coil. When the receiver coil approaches, the induced voltages V ui , V vi , and V wi increase, and then the controller starts operating in accordance with the optimal current command. In this experiment, the inverter flows currents with an amplitude of 1.4 A ahead of the optimal current control. At 15 ms, the inverter begins the optimal current control. Then, the amplitudes of the currents gradually change and end up with the optimal current at 100 ms.
VII. CONCLUSION
This article proposed a circuit configuration for coil-array wireless power transmitters with regularly arranged coils with an angular interval of 120°. The system has a circuit configuration where the inductances of the coils, including the mutual inductances between the transmitter coils, can be canceled. The system controls the currents through the transmitter coils so that the efficiency between the transmitter coils and the receiver coil is maximized and the transferred power is uniform regardless of the receiver position. The experiments validate the effective performance of the system; the variation of the output power can be suppressed to less than 5.8%, and the efficiency of the whole system is approximately maximized. Theoretically, these effective performances are available regardless of the shape, dimensions, and number of turns of the transmitter coils. Future work should deal with the expanded coil array with more than three coils and reveal an effective switching method for the switch set between the inverter and the coils, in addition to an algorithm for receiver position detection.
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Back to School after Corona Virus Disease of 2019: New Relationships, Distance Schooling, and Experienced Routine
The Corona Virus Disease of 2019 (COVID-19) pandemic has upset the students’ daily routine, forcing them at first into a sudden transition to distance learning and then to a return to school modelled on the basis of infection containment measures. The present research involved 157 students from schools in central Italy with a mean age of 13.58 years old to investigate the affective impact of the pandemic on the school experience and its components (recess, oral testing, relationships with classmates, and relationship pupils-teachers). The results show that only a few have experienced school interruption in a traumatic way: they have appreciated neither distance learning, nor the return to school; for these teenagers, the school of the past has died. Other adolescents and pre-adolescents tried to replace the face-to-face mode with distance learning, maintaining certain attention to the school even during the quarantine. However, the online mode did not keep its promise. Those who have invested more in digital innovation find it difficult to return to normality today. For all of them, socialization mediated by school experience is decisive in supporting the return to ordinary life after the pandemic.
COVID-19 AT SCHOOL
Preadolescents are faced with major and rapid physical transformations that engage them in constant vigilance concerned with bodily characteristics (Petter 1990;Senín-Calderón et al. 2017). Parallel to the changes in the timbre of the voice, the appearance of secondary sexual characteristics and the menstrual cycle in girls, the remarkable growth of stature especially in boys, there is a metamorphosis at a psychological, cognitive and affective level that initiates the appearance of anxieties and insecurities related to the sense of estrangement and acceptance of the new self-image (Bonanno, n.d.). Moreover, for preadolescents, parenting figures are no longer the only affective referent, social comparison processes emerge and childhood identifications begin to integrate with the significant objects of the present. In this particularly turbulent emotional dimension (Steinberg 2005) concerns with interpersonal identity become acute, increasing preadolescents' vulnerability to interpersonal influences. However, if in puberty strong residues of childhood dependence remain, in adolescence the detachment from parental figures is decidedly more marked, the adult community is perceived as "other than oneself" while the peer group becomes the counterculture opposed to the adult world in which the adolescents recognize themselves (Lutte, 1980). At the heart of the adolescent's evolutionary tasks is acquiring a sense of individuality and consolidating an autonomous identity, and the surrounding social environment plays a fundamental role in this (Erikson, 1995).
ROUTINE AND AFFECTS AT SCHOOL
School is where pre-adolescents and adolescents spend most of their time, and it provides an ideal setting to acquire social and emotional skills, as well as behaviours that translate into positive real-life health outcomes. In addition to providing knowledge and learning, schools offer an appropriate environment to promote healthy functioning and well-being for the youth, allowing them to build their identity in a constant testing both in educational and affective terms. Alerby (2003) elucidated pupils' experience of school and interpreted the meaning of their experiences showing how learning and knowledge, social relations, orderliness and rules, subjects, feelings and time-dimensions are the main aspects of youth's school experience. In particular, he demonstrated that school is constituted by multifaceted experiences which have many nuances, such as a lack of time to accomplish schoolwork, the importance of breaks and relations between friends, the importance of the relations between the teacher and the pupils, the fact that rules are decided upon over the pupils' heads and the fact that learning things and developing knowledge are positive even if school is sometimes experienced as boring.(p.17) The social structure of school consists of the patterns of social relationships occurring between the members of the school. On the one hand, we find the pupils and teachers relationship, through which adolescents can integrate their concept of the reference figure (Cooper, 2002;Guo et al., 2020;King, 2017;Uitto & Syrjälä, 2008;Wentzel, 2009). Socio-relational competencies are an essential component of teachers' professionalism linked to the well-being of their students: positive relationships between teachers and pupils have a positive association with students' self-esteem and future expectations (Marini et al., 2023). On the other hand, we find the peer-to-peer relationship, indispensable for the construction of one's own identity (Ferrer & Fugate, 2003). The school is a promoter of new acquaintances and friendships, in particular recess is a really interesting space in the school day because it's a time when there could be a lot of academic, social and emotional physical growth happening. It is characterized as that moment in which students have the opportunity to engage with their peers, get to know each other, play together, tell each other about school, extracurricular experiences and create new bonds (Alerby, 2003), which in many cases accompany the adolescent also in the subsequent stages of life.
The COVID-19 pandemic has forced the school system to a sudden and unprepared transition to distance learning, upsetting the daily routine of the youth (Aristovnik et al., 2020;de Figueiredo et al., 2021;Guo et al., 2020;Rothstein & Olympia, 2020;Sama et al., 2021) and engendering negative emotions (Brooks et al., 2020;Cao et al., 2020;Elmer et al., 2020;Ma & Miller, 2021;Zimet et al., 1988). The closure of educational institutions in order to contain the spread of the disease, has required the activation of measures to maintain continuity of learning. The Italian Ministry of Education, with the support of other organizations, has provided professional development to teachers and technological devices to students, accelerating the integration of technology in the teaching and learning process (Pellegrini & Maltinti, 2020). Due to the containment measures imposed during the state of emergency, important aspects of the lives of preadolescents and adolescents have been negatively impacted (Vicari & Pontillo, 2022), and they have had to shape their social practices (Welch, 2016) according to new times and spaces (Sabato et al., 2021). These forced changes make it even more important to gather new research evidence on adolescents' affective experience.
In this article we take into account a peculiar concept of affective experience based on psychological theory that uses the term "affect" to refer to the underlying experience of feeling, emotion, attachment and mood (Hogg et al., 2010). The psychoanalytic origins of the concept is claimed by Andre Green (1999) who describes the affect as a complex mental phenomena in which the embodied experience is connected with an idea whereas emotions can be independent from intellectual thinking. Affects begin at the dawn of mental life, when ideas first become associated with sensations of pleasure-unpleasure. The latter are primarily connected with gratification and/or lack of gratification of drives and wishes. The development of affects and their differentiation from one another constitute an aspect of Ego development. Freud (1915) described the affect as a subjective state: What is an affect in the dynamic sense?It is in any case something highly composite. An affect includes in the first place particular motor innervations or discharges and secondly certain feelings; the latter are of two kinds -perceptions of the motor actions that have occurred and the direct feelings of pleasure and unpleasure which, as we say, give the affect its keynote.(p.396) Within affective experience we can include feelings, emotions even as first reactions, affectional bonds and attachment that human beings live in their significant relationships since their childhood. Further current research about the concept of affect can be found in Aguillaume (2008).
Giving importance to affective experience we can ask if with distance learning has it been possible to preserve the affective ties based on face-to-face relationships, active participation, personal engagement, social interactions that characterize school life in-person.
SCHOOLING EXPERIENCE DURING THE PANDEMIC
Distance learning has had important implications both on a strictly didactic and psychological level, with a strong impact also on the relational dimension (Aguilar et al., 2020;Viner et al., 2020) bringing out in young people the thought that it is not possible to substitute the complex experience of school with only distance learning (Montanari, 2021;Pediconi et al., 2021). Adolescent, forced to restrict their relational space within the home, have suffered the effects of a collapse of boundaries in which roles and activities have merged with each other, making the distinction between the various environments, between school experiences and extracurricular experiences in general, blurred (Micalizzi, 2021;Segre et al., 2021).
Research has shown that a positive family climate, a good relationship with the teachers, and a good self-regulation of emotions were important factors in facing the difficulties due to distance learning (Pozzoli et al., 2022). Authenticity and collaboration have facilitated children's learning, as well as supportive pedagogies and motivational strategies, improving their well-being and enabling academic progress (Yates et al., 2021). However, for the majority of children distance education increased social class academic disparities: youth with disadvantaged families (low economic resources, only one shared computer, lower quality of hardware, software and internet access, absence of individual study space, lower digital skills, the main use of digital resources for entertainment rather than for work and education, less drive for autonomy and independence) have had huge repercussions in the continuity of learning rather than those with upper/middle-class families (Goudeau et al., 2021). Studies in special education also show significant losses in the developmental and educational processes of students with a disability compared to a pre-pandemic ordinary school setting, highlighting as protective factors specific teaching tools and caring human contact, a supportive home environment, adequate Information and communications Technology (ICT) devices and a good internet connection (Capurso & Roy Boco, 2021).
However in a relevant number of cases distance learning has brought with it many psychological problems such as an increased level of restlessness, aggressiveness, anxiety, depression, irritability, boredom, inattention, a scarce commitment and autonomy during lessons in the youngest, and exacerbated the difficulty of children with pre-existing behavioral problems like autism and attention deficit hyperactivity disorder (Maggio et al, 2021;Panda et al., 2021;Scarpellini et al., 2021), in some cases it has also stimulated the resilience of young people who have chosen to occupy an active role in the choice of methods, activities and organization, using the experience of distance education to develop more profound self-regulation and call for reshaped, more collaborative roles and relationships with teachers for the future (Kovács Cerović et al., 2021). In particular, recent research has highlighted the importance of selfefficacy in developing and dealing with the experience of distance learning: adolescents most confident have emphasized their successes by making the best use of relational resources, whereas those less confident children have more strongly perceived the difficulties not only in learning but also in the more social aspects of the school (Pelikan et al., 2021).
During distance learning, students felt the need to participate in more interactive activities, inviting teachers to make every effort to transform the online "traditional" frontal teaching into more practical activities (Cadamuro et al., 2021). By meeting the teachers online every day, the students were able to maintain only very partially those informal relational aspects (physical contact and informal gestures) that characterize the pupils-teachers relationship and which are so decisive for the school experience. The voice remained almost the only one supporting online schooling relationships (Addimando et al., 2021).
BACK TO SCHOOL
Once the educational institutions reopened after the lockdowns, adolescents and preadolescents returned to school but did not find the same situation they had experienced before the COVID-19 pandemic, and they have adapted to the return to in-person education (Klootwijk et al., 2021). If before the pandemic the school represented an ordinary setting and gave adolescents a sense of normality and continuity, the return to post-lockdown school meant for young people a break in the "new-normal" routines that they had experienced with distance learning and families at home (Pelaez & Novak, 2020). At school they had to adapt to a new "abnormality" (Crick, 2021): made of masks, daily temperature checks, washing hands upon entry into the classrooms, frequent cleaning and ventilation spaces, break time sitting in the chair, and keeping a distance of 1.5 meters from their friends which all required psychoemotional processing (Levinson et al., 2020).
Although generally among most students positive affections prevailed on their return to school, testimony to the success of an adaptive and dynamic process capable of coping even with sudden changes, it should not be underestimated however the difficulties, especially of those who already showed pre-existing psychological problems, special needs or disadvantages, and who returned to school with fewer resources, feeling more vulnerable and in need of more targeted support (Fegert et al., 2020;Flynn et al., 2022). Taking into account the demographic variables, it seems that the female secondary school students who experienced the return to school at a particularly critical moment reacted to the new school reality in a more pessimistic manner.(Branquinho et al., 2021;Lessard & Puhl, 2021;Pediconi et al., 2021).
Several authors have highlighted how the school could play an important role in helping children to analyze past events and identify key coping trauma strategies (Capurso et al., 2020;Dvorsky et al., 2021;Waters et al., 2021). This could be done by giving voice to adolescents and adopting a positive education following the principles of prevention-based psychology and promotion-based psychology (Slemp et al., 2017;Waters et al., 2017), so that school could become the favourite place for adolescents and preadolescents in which to process emotional critical events connected to the COVID-19 pandemic, rediscover interpersonal connections, develop an awareness of effective coping strategies, build up their resilience and minimise the risk of long-lasting difficulty. Activities that encourage classroom discussions about the event and that promote different narrative modes (e.g., story-telling, drawing, writing, fantasy) without prejudice or suggestion allow youth to express feelings and thoughts, to accept them as a normal part of their individuality and to learn new strategies through sharing and comparison with others (Capurso et al., 2020). Through narratives, youth can explore hypotheses and test different solutions (Bruner, 1986), reflect on different ways of coping with events and assess the consequences of different responses (Kratochwill et al., 2016).
Taking into account research evidence, this work aims to investigate and identify the aspects that support the school experience and distance learning, as well as the impact that their absence/presence has had on the emotional experiences of young people during the pandemic. It could therefore provide important information on how to best invest efforts and resources in future emergency situations.
THE PRESENT STUDY
Recent studies about "school hesitancy" (Bushweller & Lloyd, 2021;Goldstein, 2021;Polikoff et al., 2022) point out the resistance of families to leave the established routines based on remote learning. Some are reluctant to interrupt their newfound stable alternatives for a return to school shaped by hybrid schedules -with students in class some days of the week and working from home on others -in facing the risk of closures and quarantines.
We can observe that some teenagers, even knowing their schools had reopened, started to feel that remote learning works better for them. As a consequence, superintendents and school leaders are now in a bind. Most believe that endless remote school poses health and social risks for kids, but they do not want to pressure families. Continuing adherence to social-distancing guidance also means most schools cannot operate at full capacity, and staffing remains an issue.
Most researchers asked teachers and families about the well-being, motivations and health of adolescents during distance schooling in the pandemic period (Scarpellini et al., 2021;Toseeb et al., 2020). Although the transition from pre-pandemic school to post-pandemic school implied an entire new educational system, only limited research has been conducted in which adolescents have been asked directly about their school experiences (e.g. Duckworth et al., 2021;Fisher et al., 2021;Holzer et al., 2021;Klootwijk et al., 2021;Montanari, 2021). Indeed, at the current time research in literature lacks data about how the aspects of school routine, relations, and moments experienced before the pandemic have favoured or hindered the return in person, and the experiences related to distance learning. The present study aims to address this gap by answering three research questions about the school experience described by students themselves: • RQ1 -What aspects of schooling experience before the pandemic did students hold when they returned to their desks after distance learning?Both the formal and informal aspects of the school routine will be analyzed.
• RQ2 -What was the students' schooling experience during distance learning?Middle and high-school students will be considered.
• RQ3 -What components of students' schooling experience promoted or impeded their return to school in person?It will be analyzed how distance learning influenced the affective experience linked to the return to in person classes.
SAMPLE AND PROCEDURE
The research involved 157 students (50, 3% male and 49,7 % female) with a mean age of 13,58 years old (SD = 2,107) from central Italy. In order to compare the experiences of preadolescents and those of adolescents, participants were selected from lower secondary school (Age 11-13, N = 87, 48 females and 39 males ) and upper secondary school (Age 14-18, N = 70, 30 female and 40 males). The sample didn't include students with the declared conditions of fragility (i.e.hospitalized students, students with mental health issues, learning difficulties, language difficulties, and foreign students).
The data were collected in-person both in lower and upper secondary schools (October 2021) after the reopening of schools ended the acute phase of the health emergency from COVID-19.
The anonymous questionnaire was dispensed during school hours by two school psychologists after obtaining informed consent from parents and assent by the participants. The activity was approved by the local school board.
MEASURES
In line with the recent studies about online distance learning (Kovács Cerović et al., 2021;Mishra et al., 2021) and on the impact of the COVID-19 pandemic on the experiences of young people (Branquinho et al., 2021;Scott et al., 2021;Yates et al., 2021), we prepared an ad hoc questionnaire inspired by the Sacks and coll."Sentence Completion Test" (Sacks & Levy, 1950). It was administered in October 2021 in person, when the state of emergency was lifted and schools were reopened. It consisted of two types of items: "sentences to complete" relating to the teenager's experience of school during the quarantine (distance learning) and after strict emergency state (i.e."The return to school in September 2020…", "When I think of DAD/DID…", "My teachers…") and multiple-choice questions for demographic and educational variables. In particular, the questionnaire was used to investigate: • daily school routine including both informal (recess and relationships with classmates) and institutional school moments (oral testing and relationship pupils-teachers) to answer RQ1; • emotional experience of distance learning to answer both RQ2 and RQ3; • emotional experience of returning to school to answer RQ3; • who adolescents and preadolescents spent time and space with during the lockdown to answer RQ3.
Demographic and educational variables were the type of school, age, and gender we con. All responses were classified as "positive", "neutral" or "negative" by two independent observersraters, both psychologists with professional experience in the research field, with an inter-rater reliability of 0.81. Any disagreements regarding attribution were discussed until a consensus was achieved. Specifically, the responses were classified as positive when the completed sentence showed positive experiences or feelings towards the subject of the proposition (i.e."When I think of DAD/DID I think that I had less anxiety and it was easier for me to follow the lesson"), as negative when the completed sentence showed negative experiences or feelings towards the subject of the proposition (i.e. The return to school in September 2020 was stressful and awful for me"). Sentences that did not have any affective connotation were classified as neutral (i.e."My teachers were mostly women/as always).
To deepen the analysis of the affective experience that supports the school one, a general synthetic indicator has been constructed by adding the evaluations that adolescents and preadolescents have reserved for the individual components of the daily school routine and it has been labelled the "feeling of the school". In particular: positive responses have been encoded as +1; negative responses have been coded as -1; neutral responses have been coded as 0. For each participant, a numerical indicator was thus obtained, represented by the algebraic sum of all his/her evaluations, called "feeling of the school".
DATA ANALYSIS
Psychometric analyses were conducted through the IBM SPSS Statistics statistical software version 25.0. Data analysis was performed using frequency distributions for categorical variables, Anova, T-test and Pearson correlations for numeric variables.
To answer RQ1 the a Chi-Square test was performed on differences between adolescents and preadolescents about feelings towards the components of daily school routine: oral testing, recess, and relationships with classmates and teachers.
To answer RQ2 Pearson correlation and test of Chi-Square were performed to detect differences between adolescents and preadolescents about feelings towards distance learning; in addition, a test of Chi-Square was performed to analyse feelings about distance learning matched by the affective relationship with teachers and by the informal routine during the recess. To answer RQ3 a test of Chi-Square was performed to detect the feelings linked to returning to school matched by age (adolescents and preadolescents), the experience of distance learning, the relationship with classmates and by other aspects of informal routine (recess). Chi-Square was also performed to analyse the influence of attachment figures with which the children experienced the quarantine on the feelings related to going back to school. A T-test was performed to detect a significant difference in averages of "general feeling of school" related to experienced distance learning. Anova was performed to analyse how the general feeling of school changed based on age (adolescents and preadolescents).
DAILY SCHOOL ROUTINE IN CONTINUITY PRE-POST PANDEMIC PERIOD
In this first section the findings presented are related to RQ1 about what aspects of schooling experience before the pandemic the students had held when they returned to their desks after distance learning schooling. Both the formal and informal aspects of school routine will be analysed.
As can be seen in Figure 1, once back at their school desks the middle school students (preadolescents) consider the relationship with the teachers very important (80.2%rate them positively) and seem less willing to note any shortcomings or defects, indeed only 16.3% express a negative opinion. For pre-adolescents an affectionate bond with teachers is confirmed as an extension of emotional ties with significant figures even at school. High school students estimate their teachers (61.5% positive) as well, although a not insignificant number prefers to maintain a position of neutrality (21.4%) that could conceal more critical comments. It should not be forgotten that for high school teenagers the relationship with teachers becomes challenging as an expression of a growing confrontation with adult figures (Cooper, 2002;Wentzel, 2009).
Considering the institutional aspects of school experiences, Figure 2 shows that the experience of oral tests improves with age. In an oral test the teacher asks several oral questions to the student in order to evaluate his/her preparation on specific topics. Preadolescents are in greater difficulty than high school boys (60.9% vs 34.3%). Most middle school students have a negative and anxious attitude towards oral tests, which they see as challenging not only their academic performance but also their self-esteem. On the contrary, adolescents, while not hiding experiences of difficulties during the oral test, seem ready to take up the challenge, and are more willing to test themselves (51.4% vs 35.7), in fact there are just a few who neutralize the feelings related to being evaluated (14.3% vs 3.4%). Among the informal aspects of the school routine, for sure it is recess that has a privileged position -it is the pre-adolescents who are most enthusiastic about it, even if there are good experiences also among the adolescents. Figure 3 shows that very few speak badly of recess, yet among adolescents there is a greater impatience, as shown by the high number of neutralizations (55.7%) concerning break times. Adolescents that neutralized judgement could therefore hide a certain emotional distance.
WHAT AFFECTED THE DISTANCE SCHOOLING EXPERIENCE
This second section presents the findings related to the second research question (RQ2) about what was the students' experience, both for preadolescents and adolescents, of distant learning during the pandemic. Students' approval rating of distance learning matched by age will be statistically analysed.
The statistical analysis of the correlation between the experience related to distance learning and age (r(154) = .27,p = .001)shows that the positive evaluation of distance teaching grows proportionally to age. The high school students appreciated it more. The significant differences in Figure 4 also confirms this fact: the vast majority of middle school students (69.8%) have negatively assessed distance learning, highlighting problems and disadvantages, while among the students of high school there are slightly more of those who rate it positively (54.3%). Both preteens and adolescents had to process their surprise about the school interruption due to the pandemic, only partially replaced by distance learning.
In the literature there are interesting qualitative gender differences relating to the lockdown experience (Capurso et al., 2023;Capurso et al., 2022): data report that females missed school, family and relatives, hanging out, and having direct contact with others more than males. Adolescent girls present higher emotional sensitivity to stressful life events, and consequently, they tend to report higher levels of attachment to peers and favour quality intimate relationships. Instead, especially among middle school students, males missed sport and hobbies but were helped by video games and TV. Other studies found that females experienced more negative emotions during the distance learning experience (Cadamuro et al., 2021). Despite many researches showing important results about gender differences, our statistical analysis did not notice them.
Figure 5 shows the links between the evaluation of students' relationships with teachers (positive, negative, neutral) and their experience of distance learning (positive, negative). Among those who have negatively experienced distance learning as a new way of doing school, there are many who express a positive opinion about their teachers (79.4%). Those who have enjoyed distance learning (60.3%) also have a good relationship with teachers, but the number of those who feel negative towards them (22.2%) or prefer to remain neutral (17.5%) is increasing.
As we have seen, the moment of recess remains a cornerstone of the traditional school experience, but it is interesting to note how feelings related to recess are influenced by feelings related to the experience of distance learning. In Figure 6 it can be seen that most of those who have struggled with distance learning appreciate moments of recess (79,3%), when the school experience moves into the corridors. Only a small minority prefer not to express themselves (20.7%), while there is no negative opinion on recess among those who have negatively experienced distance learning, confirming the fact that recess is a milestone of the school experience, but in person. On the contrary, most of the young students who rated distance teaching positively preferred to avoid expressing an opinion about the moment of recess (48.4%), a good number expressed a positive response (42.2%). Note the few who do not appreciate recess at all (9,4%). Distance learning has taken away from children a distinctly social and recreational aspect of the educational experience.
EMOTIONAL EXPERIENCE OF RETURNING TO SCHOOL
In this section we present findings related to the third research question (RQ3): what components of schooling experience promoted or impeded the return to school and how distance learning influenced the affective experience of returning to school. The results highlight significant differences between adolescents and preadolescents (Figure 7) showing how students experienced their return to school. Most preadolescents of the sample (59,8%) experienced the return to school as a positive moment. Preadolescents were enthusiastic about going back to school, reaffirming the centrality of the school experience in their social life.
Most adolescents of the sample (52,9%) negatively described going back to school. Older students seem to have been more affected by the interruption caused by the pandemic. The results show significant different attitudes about returning to school between preadolescents and adolescents. Preadolescents experience a profound extension of social and emotional relationships thanks to school. However, for adolescents school instead challenges their emotional experience and success. Now, one might wonder whether the experience of distance learning has encouraged or hindered the return to school in person (Figure 8). The figure shows that most of the students who have experienced distance learning as a negative interruption express a very positive response on returning to school in person (60.9%). On the contrary, the majority of students who have enjoyed distance learning have struggled to return to school in person (54.7%): for It could be read in the light of considerable uncertainty also the number of those who effectively neutralise their return to school, and refrain from judging it positively or negatively. In addition, they are more numerous precisely among those who say they have experienced distance teaching positively (20,2%). It could be said that the students tried to replace the inperson mode with distance learning, they tried to pay some attention to school even during the quarantine, but the online mode has not kept its promise and today these students find it difficult to return to normality, precisely those who have invested more in digital novelty.
The data indicate that it is not the institutional components of the school experience (oral testing and relationship pupils-teachers) that hinder the return to school. Indeed, in matching feelings of returning to school and the perception of oral tests, were not found any significant results. These students are not afraid of questions and the more rigorous aspects of the school experience do not prevent them from seeing the school first of all as a living environment. Rather it is among the informal components of the daily school routine (recess and relationships with classmates) that can be found the inconvenience that weighs down feelings of returning to school. Data (Figure 9) confirm that for adolescents the school is the place of social life. Being able to go back to meet friends and share life with them is the main desire of those who have experienced a positive return to school (51.6%). Although among those who return to school willingly, are many who grow dissatisfied with classmates (39.3%). The difficulties among peers and with classmates are shared, as could be expected, even by those who have negatively experienced the return to school (50%).
Keeping in mind the informal components of school experience, in Figure 10 it is observed the relationship between the moment of recess and the experience of returning to school. Those who returned to school willingly could not wait to return to the enthusiasm of the bell that signals the break between lessons (57.4%). There are some who do not appreciate recess (32.7%) and only a minority who prefer not to respond (9.9%). The figure for those who have not returned willingly to school is fairly similar: most do not appreciate the moment of recess (66.7%). The moment of recess is not appreciated even by those who maintain a neutral position towards returning to school (52%).
xAnalysing the emotional complexity of the return to school, it could be important to note how the relational figures that accompanied the lockdown supported the return to normality.
Figure 11 shows the relationship between the attachment figures with which the children experienced the quarantine and the feelings related to going back to school. Among those who have experienced quarantine with only one parent, none express a positive opinion on returning to school. This data could indicate the greater relational difficulty of the children who have experienced the quarantine in close contact with a single figure of attachment in returning to the social life that the school represents. For these teens, the return to school seems to have represented the breaking of a symbiosis which, however, denounces regressive impulses that risk slowing down the conquest of emotional independence. A fact that could be read as a resistance of these teens to come out of a kind of regressive affective shell, a tête-àtête that confinement may have fuelled. Those who have spent lockdown with both parents and any siblings (nuclear family) are equally divided into positive and negative feelings about returning to school between difficulty and desire. They interpret on the one hand thoughts of difficulties about returning to normality, and on the other, the desire to return to social life. It is the extended family (composed of parents, children and other relatives or cohabitants) that supports a clear majority of children who have positively experienced the return to school (50.4%) even if they are accompanied by a certain percentage that has had a negative experience (36.4%). Only a minority prefer to abstain from evaluation (13.2%). For students of the sample the sharing of lockdown with more than one attachment figure seems to have facilitated the return to social life.
To deepen the relevance of the affective dimension that supports the school experience, a synthetic affective indicator has been developed, resulting as the algebraic sum of the evaluations of the individual components of daily school routine (both informal and institutional school moments), which connotes the general feeling with which each student invests the school experience. The findings show that the experiences related to distance learning are significantly related to the general feeling of the school. Indeed, T test (t(153) = -4.393,p =.000) shows a significant difference in averages of "general feeling of school" between those who have positively and negatively experienced distance learning: they are those who love school (M = 4.00, SD = 2.95) who suffered a lot from the transition to distance schooling. By contrast, the children who are less keen on school (M = 1.87,SD = 2.97) tolerated distance teaching better. The feeling for school becomes an important indicator also to interpret the experience of the return to school of adolescents and preadolescents. In Figure 12 it is possible to observe the chart of the averages (F(2, 153) = [12,565], p = .000)relative to the match between feeling for school and going back to school.
Those who reserve special affection towards the school (M = 4.36, SD = 2.67) are excited to go back. Less enthusiastic are the students who are less passionate about school (M = 2.42, SD = 3.16). The data relating to students who have a low feeling towards school (M = 1.23,SD = 3.01) is more complex, and who abstain from evaluating their return to school in person. An abstention that could be interpreted as an implicit confirmation of the fact that the neutralized feelings conceal difficulties of an affective nature. Tukey's HSD Test for multiple comparisons found that the mean value of feeling for school was significantly different between students who had positive feelings toward distance learning and those who lived it with more sorrow (p = .001,95% C. I. = [0.7379, 3,1272]). Also, a significant difference was detected between students that appreciated distance learning and those that neutralised feelings about it (p = .000,95% C. I. = [1.4056, 4,8405]). Instead, there was no statistically significant difference in mean scores of feeling for school between those who experienced distance learning as negative moments and those who reported neutral feelings (p = 0.243). Those who have experienced an emotionally flattened or more markedly negative return would therefore seem to have something in common: an affect for school impoverished by the pandemic or experienced as potentially painful that hinders them in returning to invest positively in school.
DISCUSSION RQ1: DAILY SCHOOL ROUTINE IN CONTINUITY PRE-POST PANDEMIC PERIOD
In view of the fact that the children spoke about school experience in general at a time when the precautionary rules dictated by the pandemic were still very restrictive, upper school students report a certain intolerance to adapt to the new "abnormality" (Crick, 2021), made up of wearing masks, washing hands upon entry into classrooms, sitting chairs at recess, as well as maintaining a 1.5-meter distance from their friends (Levinson et al., 2020). The adolescents of our sample that did not explicitly express their perplexities could experience a certain annoyance about the new forms of recess in which, due to the post-pandemic, socialisation must be forcibly "contained". Their neutralised judgement could therefore hide a certain emotional distance.
In particular, our results show that the continuity of the pre-post-pandemic school experience has been supported by both formal aspects such as oral tests and informal school routines such as recess. On the one hand, teachers have taken on a leading role confirming themselves as the main focus of the school experience both during distance learning and as guarantors of continuity in the moment of come back to school (Guo et al., 2020;King, 2017;Marini et al., 2023), as was school in person although it has been strongly influenced by Covid safety measures. On the other hand, affectional bonds with teachers and memories of the schooling routine both formal and informal had given continuity to the school experience even during the pandemic, underlying the importance of school as the most important place for the socialisation of pre-teens and adolescents.
RQ2: WHAT AFFECTED THE DISTANCE SCHOOLING EXPERIENCE
Both preteens and teenagers had to process their surprise at the interruption of school activities due to the pandemic, which were only partially replaced by distance learning/teaching. Distance schooling was experienced more resiliently by high-school students. Only a few have experienced the interruption of the school in a traumatic way: they did not appreciate either distance learning, or the return to school, reporting a kind of blackout of the school experience altogether. Other students have tried to replace the in-person mode with distance learning, paying some attention to school even during the quarantine. However, for them the online mode has not kept its promise. Those who have invested more in digital innovation, found it difficult to return to normality. For all, socialisation mediated by school experience was decisive as a support to the resumption of ordinary life after the pandemic.
Teachers remain the pivot of school experience even at a distance, assuming that positive feelings towards them have mitigated the effects of negative experiences related to distance learning (Marini et al., 2023). On the one hand, the results are consistent with other research (Cadamuro et al., 2021;Kovács Cerović et al., 2021) about the more collaborative roles and relationships with teachers. During distance learning, students participated in more interactive activities, inviting teachers in order to transform the frontal instruction into something more involving. On the other hand, those who had more detached relationships with teachers, probably due to the impossibility of having a relationship with teachers in person in which the voice remained the only one support of online schooling relationships (Addimando et al., 2021), may have had negative feelings tied to online learning.
Distance learning has taken away from the youth a distinctly social aspect of the schooling experience. Students struggling with distance learning missed informal moments of schooling in person (recess) while students better adapted to new modality at distance tended to neutralise feelings related to social aspects of school. This suspension could be read on the one hand as an effect of uncertainty that distance learning has thrown on the school in general. On the other hand, it could be read as emotional distancing from the memory of an aspect of the school routine left in the past.
Recess is undoubtedly the moment of school when students play and physically meet with peers; with distance learning teenagers have lost all that interpersonal dynamic dimension -friendships and peers, freedom, autonomy, hanging out, going out to play, physical contactthat transform school life in the arena where students undertake sense-making of the events and actively take part in a social and developmental network (Capurso et al., 2023).
A warning for the future: the maintenance of learning modalities and the spread of impersonal teaching could heavily compromise the feeling towards school of the young generation, endangering the most important experience for education and socialisation of teenagers and preteens.
RQ3: EMOTIONAL EXPERIENCE OF RETURNING TO SCHOOL
In line with other studies, our results showed that preadolescents and adolescents experienced coming back to school as a delicate moment, and the new school reality in a more pessimistic way (Branquinho et al., 2021;Lessard & Puhl, 2021;Pediconi et al., 2021). The results showed significantly different attitudes about returning to school between preadolescents and adolescents. On the one hand, preadolescents willingly come back to school showing profound openness and extension of social and emotional relationships. On the other hand, most adolescents of the sample negatively described going back to school, they seem to say: "School can never be the same again!". The previous experiences of adolescents relating to school in person could come into conflict and comparison with the new "abnormality" (Crick, 2021). Older students seem to have been more affected by the interruption caused by the pandemic, the new school has tested their emotional experience and success. They considered it a broken time that could have negatively compromised their school feeling and their feeling of self, going back to school means going back to facing new questions, confronting adults and professors who expect them to learn new information, and peers who expect new interactions (Scott et al., 2021). This data confirms the impossibility of replacing the complex experience of school only by means of distance learning (Lara-Prieto et al., 2021). It could provide further evidence of the long-term effects of the pandemic, during which pre-adolescents and adolescents were forced to restrict their relational space with deleterious effects on the distinction between the various living environments, a consequent indistinct spread of school dropout, and a certain disaffection in daily commitments (Micalizzi, 2021;Montanari, 2021;Scarpellini et al., 2021).
What favours the desire to go back to school and what slows it down?Do the students want to go back to meeting their classmates in person or are they afraid to return to the routine that forced them to get up at dawn and cope with going on school trips and the slowness of everyday real life?
The return to school becomes more exciting for those who have experienced distance teaching in a negative way, while those who felt comfortable in front of the screen experienced being frightened, shocked or disturbed returning to school. The pandemic experience seems to have complicated the indispensable relational commitments during pre-teens and adolescence (Vicari & Pontillo, 2022), a time when relationships with classmates are a blessing and a curse of the school experience (Foulkes & Blakemore, 2021), especially when they meet each other again at school. Most of those who declared neutral or negative feelings thinking about the school moment of recess have not returned willingly to school. This could signal a despondency of those teenagers who seem to almost protect themselves from moments of school socialisation, showing some difficulty in the resumption of ordinary life after the pandemic.
The composition of the family with which the student shared the quarantine was another aspect that affected the return to school. The extended family has given greater social and interpersonal continuity for adolescents, confirming the family as a factor of resilience even in the COVID-19 emergency (Cimino et al., 2021;Maftei et al., 2022). However, it cannot be excluded that the positive feelings for the return to school for children who have been quarantined with a large family has been favoured by a new-found freedom, even more appreciated after suffering the stringent and forced sharing of time and space. Also the analysis related to the general feeling toward school gives important information about the return to post-pandemic school. Those who experienced the positive return seem to have clung to the feeling for school keeping it alive within them, while those who returned to school without enthusiasm (negative or neutral return to school) they may have been disappointed by too high expectations that were not met by the restrictive measures. Disappointed students risk developing a defensive feeling (negative or neutralized) that detaches them from a school experience (Altwaijri et al., 2022;Leuzinger-Bohleber & Montigny, 2021).
CONCLUSION
In conclusion, the results show that even though online learning has been a useful tool for delivering didactic (theoretical) concepts, it has been unable to replace conventional schooling and education. However, despite the students and teachers being overwhelmed at the beginning of the pandemic, they have shown remarkably resilient aspects of schooling during different phases of contagion.
About distance learning the students tried to replace the in-person mode with distance learning. However, the online mode has not kept its promise: in particular those who have invested more in digital novelty seem to find it more difficult to return to normality.
From the perspective of affectional bonds, if the family, teachers, and memories of social moments of school routine are confirmed as the protective factors during the quarantine that have favoured the return to life in person, distance learning seems to have weighed down the
Figure 4
Figure 4 Age * Experience of Distance Learning.
Figure 5
Figure 5 Experience of Distance learning * Teachers.
Figure 6
Figure 6 Experience of Distance learning * Recess.
Figure 7
Figure 7 Age * Return to school.
Figure 8
Figure 8 Experience of Distance learning * Return to school.
Figure 9
Figure 9 Classmates * Return to school.
Figure
Figure 10 Recess * Return to school.
Figure 11
Figure 11 With whom they spent the lockdown * Experience of Return to school.
Figure 12
Figure 12 ANOVA -Return to school * Feeling toward school.
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A Conversation With Sylvia Richardson
Harvard Data Science Review’ s interim Co-Editor-in-Chief Francesca Dominici recently met with Dr. Sylvia Richardson, Emeritus Director of the Medical Research Council Biostatistics Unit at the University of Cambridge, Immediate Past President of the Royal Statistical Society, and HDSR Associate Editor. The pair discussed the definition of data science, Dr. Richardson’s data science journey, her areas of research, and what it means to be an effective data science leader. This interview is part of HDSR ’s Conversations with Leaders series. HDSR includes both an audio recording and written transcript of the interview below. The transcript that appears below has been edited for purposes of grammar and clarity with approval from all contributors.
Richardson. I've been having the pleasure of knowing Sylvia for a very long time and looking up to her as a 0:00 0:00 / 24:09 / 24:09 Audio recording of the interview.
really good role model for women in statistics. And she's a professor at the University of Cambridge and past president of the Royal Statistical Society (RSS). Welcome, Sylvia.
Francesca Dominici: [00:00:52] I'm honored to host Sylvia today on behalf of Harvard Data Science Review.
And as you might know, our Xiao-Li Meng formally launched Harvard Data Science Review a few years ago with the idea to make data science truly, truly accessible to everyone and to build a community of data scientists to try to understand what data science is about. And this is part of a series of podcasts that we have with Conversations with Leaders, where we are actually learning from them what has been their career and their ideas about data science. Sylvia, so tell us: What's data science for you?
Sylvia Richardson: [00:01:44] It's hard to be original, but I was racking my brain for a good metaphor, and came up with the metaphor of a rainbow of interconnected disciplines, sharing the common aim of making the best use of data-rich environments we live in to solve problems in society. So, like in a rainbow, data scientists have to work together to draw out information from data. And the colors must match, tough they are different.
Similarly, there are different but intersecting data science tasks, taking different shapes and forms. As data scientists, we recognize and enjoy diversity, we're not doing all the same tasks. Nevertheless, there is a backbone, a shape to the rainbow. And for us, this backbone is probability theory, study design, and quantifying uncertainty using statistical thinking. We also know that rainbows change all the time. They don't last, but they keep reappearing. Data science is also evolving constantly because new questions and new types of data keep arising. In a similar way to the rainbow which is strongly influenced by the atmosphere, one key aspect of data science is that we have a strong link to practice. So, we work together to solve problems from different perspectives, we evolve, we try to be relevant to science and society, and make the best use of the data. [00:06:32] Now, a natural way to fully explore heterogeneity in biomedical data is to turn to mixture and partition models. And this was my next focus. Mixtures can be used at the observational level or in Bayesian hierarchical models, for specifying flexible prior distributions of latent quantities. In either case, if you want to be flexible-this was my purpose-you don't want to assume you know in advance the number of components, but you want to learn it. Using Peter Green's reversible jump paradigm, together we worked to develop fully Bayesian mixture analysis with unknown number of components, and this led to our 1997 RSS discussion paper. But while I was developing that work, I was always very conscious that clustering and mixture modeling are fundamentally unidentifiable problems. What is the 'right' mixture?It has to be defined with respect to an objective. For answering health questions, I thought that a useful way to make the clustering output more interpretable was to look for mixtures or partitions which are predictive of a health outcome of interest. For example, to cluster patients sharing similar biomolecular profile and level of risks. And so we develop what we called "outcome-guided clustering," in which cluster membership is associated with an outcome. This approach has found many applications in epidemiology and beyond. Currently, we're using it to characterize patterns of multimorbidity in electronic health records. So, it really is quite versatile.
[00:08:36] Finally, like many of us, I was excited by the explosion in the collection of genetics and genomics data in the years 2000, and I got interested, in particular, in integrative genomics and understanding gene regulation. Luckily, I had many biological colleagues to work with and to learn biology from. And so, I developed an ambitious analysis framework of hierarchical regressions adapted to this question. It was ambitious because it was high dimensional in two directions. My aim was to analyze jointly many responses, typically whole sets of gene expressions, and many predictors, typically a block of correlated genetic variants.
The key idea was that by borrowing information between the responses, we would have more power to find genetic variants, so-called hotspots, which are associated with the expression of multiple genes. Because we embrace diversity in data science, but this diversity could lead to fragmentation or, on the contrary, be very beneficial. We have to make sure that the distinct disciplines involved in data science with their different application fields and different way of thinking, are not made into silos, and that we manage to make this ecosystem something very rich for all of us and for data science. The project of Harvard Data Science Review saw the potential threat of fragmentation and took the lead in trying to counter it, so that data scientists talk to each other. And I would really encourage more initiatives to translate concepts across the disciplines that make up data science. I would also encourage that we endorse some key ideas across the disciplines. For example, that all data scientists have to be educated about selection bias!Because if you think of all the algorithms which use training data without really scrutinizing the provenance of the training data and whether it could have potential bias, there is a lack of awareness of the potential consequences of selection bias on the performance of the predictive algorithms. This is just one example of a key challenge and focus of attention that should be endorsed by all of us. More broadly, it would be useful to gather a list of key concepts that we should all understand in a fairly similar and deep way. Then we could build interactions more effectively.
Francesca [00:16:06] When we were working during COVID in the Turing-RSS Health Data Lab supporting the UK Health Security Agency, we tried to operationalize scalable data integration and we focused on modularity as one of the key ingredients. There is great interest in the topic of modularity at the moment in data science. I view that trying to understand how to build large scale models in a modular fashion and how to transfer information between the modular components, possibly, in an approximate way, will make data science have a key impact on the big challenges that the world is facing; for example, climate change. Such an approach to modelling was very useful during the pandemic. So, implementing knowledge-informed data fusion and making it scalable and modular seems to me an important opportunity.
Francesca Dominici: [00:17:02] Thank you. Thank you, Sylvia. And it's incredible how you're talking about challenges and opportunities, again, that are really illustrations of the central role of data science in tackling the most important societal problems, including COVID and climate change. So, we're getting at the end of the conversation, but I wanted to take the opportunity by talking to a leader like yourself to give us some information and some advice about leadership. You have been the president of the Royal Statistical Society.
You have so many accomplishments, took many leadership positions. So how is it to be a leader in data science?What is your leadership style, and what are the recommendations for the future generation of how to be an effective leader in this new world of data science?
Sylvia Richardson: [00:18:09] Well, it will be quite challenging because, to be an effective leader in data science, I think you need depth and breadth. Usually, it was enough to have depth. The standard recognized qualities for a leader in academia were very good publications, having trained a lot of people, having made an impact, and having thought very deeply into one domain and be a recognized expert in that domain. Data science leaders, indeed, have to be deeply anchored and expert in one domain. But, on top of that, they also need to be able to reach across the unique breadth of the data science fields. Crucially, that means having the ability to work effectively in an interdisciplinary manner and being convinced of the benefit of bringing different disciplines to bear on problems. So, you need to be open and able to make connections between your own set of experience and questions in other domains. In effect, to be constantly looking for connections between different topics and suggesting these to others, as well as be very generous in sharing your ideas and your intuition, so that you encourage people to take up and try these ideas. That has been my style of leadership.
[00:19:28] Another quality which I think is important is to keep a critical mind and be prepared to be openly critical. That comes with experience. As part of our training, each of us develop a critical mind, but the next step is to be able to ask nicely a critical question; that is, dare to criticize. Discussion meetings at the RSS are an excellent training school to see how people can be highly critical but in a nice and constructive way. This is something to encourage in the future.
[00:20:04] Also, to be a good leader you need to encourage equality and diversity and put that high on the agenda and think of the consequences of whatever decision you take with respect to diversity. In the RSS, we appointed last year an Honorary Officer for Equality and Diversity and we're pushing this agenda to the forefront. I am highly supportive of that, as every leader should be.
[00:20:33] On the data science front, while I was president, I felt a sense of urgency to encourage the RSS to revisit its engagement with data science, and I created a data science task force right at the beginning of my presidency. It didn't get going earlier because there was COVID to keep us busy!Nevertheless, the Data Science Task Force got underway in 2021 and came up with two major recommendations. One was to give more resources to the practitioners' community, which led the RSS to create a Real World Data Science online platform. A second direction was to brainstorm on what is still needed for the discipline to thrive. [HDSR Founding Editor-in-Chief] Xiao-Li was part of this task force and helped the task force to brainstorm. The idea that it would be good for the RSS and for the whole of the community to create a new data science journal emerged from these discussions, and we are now in the process of developing a pan-data science journal!So, if I look back at my presidency, I am happy to have been able to contribute to formulate a renewed strategy of engagement with data science at a time when it was absolutely topical. It was urgent that the RSS increased its visibility and its direct impact on the field.
[00:22:08] We have a lot of responsibility nowadays as data scientists, because one consequence of COVID has been that people have realized how important it is to analyze data in a correct way. The pandemic has shown that analyzing data is not just an abstract exercise-it can directly impact people's life. There are huge societal implications to our work. The future leaders will have to build on that increased recognition, take this responsibility in hand, be conscious of the great interest that society has for data science, and take a view on how to best progress our endeavors. We all have to consider work-life balance, but as a woman, there are particular types of 'balances' you have to deal with, and particular issues you have to contend with. The most helpful is to be open about it and make sure people don't think there's only one way to achieve a successful career, but that there are many paths to becoming a good data scientist and having a voice as a woman leader. And what you yourself need to do is encourage and support women colleagues and women students to find their own fulfilling path. Mentoring and finding mentors to help younger generations of women make crucial choices at some key time points is how I like best to share my experience. I believe very strongly in mentoring.
Francesca Dominici: [00:23:52] Thank you, Sylvia. This has been so illuminating and fun. Thank you so much for your time and for sharing your experience and your wisdom.
Disclosure Statement
Sylvia Richardson and Francesca Dominici have no financial or non-financial disclosures to share for this interview ©2023 Sylvia Richardson and Francesca Dominici. This interview is licensed under a Creative Commons Attribution (CC BY 4.0) International license, except where otherwise indicated with respect to particular material included in the interview.
Francesca
Dominici: [00:00:02] Welcome to Conversations with Leaders. My name is Francesca Dominici, and I am a professor of biostatistics at the Harvard T. H. Chan School of Public Health and a faculty co-director of the Harvard Data Science Initiative. It is really my honor today to be speaking with Professor Sylvia
Francesca
Dominici: [00:22:50] So how is it to be a woman leader in data science?Sylvia Richardson: [00:22:55] As you know, you do become a role model as you get older, whether you want it or not. I've tried to be very open about the struggles I have faced and the different choices one has to make.
Such variantsare of interest as they may initiate key biological mechanisms. Recently, we proposed a variational Bayes version of this model, which scales up to 20,000 gene expressions and thousands of genetic variants. In fine, our hierarchical regressions framework and its scalable implementation gives a powerful tool to biologists for understanding gene regulation. Lately, both for mixtures and genomics, I have focused on making Bayesian computations effectively scalable-and I have turned to use, if necessary, approximate inference in order to increase the impact and take up of the models and tools that we are developing. Thank you. Thank you, Sylvia. I think what has been fascinating to me, listening to your career path, is that I think all of your interests really exemplify what data science is about, which is extracting new information from data and your interests into extracting information from data that can be spatially varying. They are collected at different level of aggregation, they are complex, and developing a model that needs to be flexible to understand heterogeneity and as well to allow for scalability. It's really these are all real importance statistical concepts in statistics. And I know that you have made enormous contribution also in the field of genetics and genomics, which is also one of the really high-importance areas in data science. And it is, I think, one of this foundational thinking in data science that is underlying most of the data application, right?Whether you are thinking about environmental data or genomics data or biomedical data, we are all dealing with the issue of heterogeneity. So, what do you think are the biggest challenges that the field of data science is facing?
So, going back to you, and there are really too many contributions than we have time to talk about, but tell us, what's your favorite one?What was the one that got you more excited?That kept you up at night?Is there one, or did you embrace everything with the same amount of enthusiasm?Sylvia Richardson: [00:11:48] I embrace everything with the same amount of enthusiasm, but I would say that a key strand of my research has been mixture model, flexibility, and understanding sources of heterogeneity -from the macro to the micro levels. For example, understanding the drivers behind heterogeneity of risks at the aggregated geographical level or investigating heterogeneity of molecular phenotypes at the biological level. And I'm carrying on working on that topic at the moment, in particular on scalability of clustering methods for large data. I would say that this is one area which has been a constant strand of my research. Francesca Dominici:[00:12:24]\===
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COMPTEL data analysis using GammaLib and ctools
More than 20 yr after the end of NASA’s Compton Gamma-Ray Observatory mission, the data collected by its Imaging Compton Telescope (COMPTEL) still provide the most comprehensive and deepest view of our Universe inMeV gamma rays. While most of the COMPTEL data are archived at NASA’s High Energy Astrophysics Science Archive Research Center (HEASARC), the absence of any publicly available software for their analysis means the data cannot benefit from the scientific advances made in the field of gamma-ray astronomy at higher energies. To make this unique treasure again accessible for science, we developed open source software that enables a comprehensive and modern analysis of the archived COMPTEL telescope data. Our software is based on a dedicated plug-in to the GammaLib library, a community-developed toolbox for the analysis of astronomical gamma-ray data. We implemented high-level scripts for building science analysis workflows in ctools, a community-developed gamma-ray astronomy science analysis software framework. We describe the implementation of our software and provide the underlying algorithms. Using data from the HEASARC archive, we demonstrate that our software reproduces derived data products that were obtained in the past using the proprietary COMPTEL software. We furthermore demonstrate that our software reproduces COMPTEL science results published in the literature. This brings the COMPTEL telescope data back into life, allowing them to benefit from recent advances in gamma-ray astronomy, and gives the community a means to unveil its still hidden treasures.
Introduction
The Imaging Compton Telescope (COMPTEL) was one of the four telescopes aboard NASA's Compton Gamma-Ray Observatory (CGRO) satellite, which was operated in low Earth orbit from April 1991 to May 2000 (Schönfelder et al. 1993). The telescope scrutinised the gamma-ray sky in the 0.75-30 MeV energy range, and its observations still present the most sensitive survey of the MeV sky ever performed. Since the end of the CGRO mission, our view of the gamma-ray Universe has evolved considerably, including observations of very highenergy gamma rays from a plethora of objects and the discovery of new source classes, such as novae, gamma-ray binaries, starforming regions, globular clusters, and starburst galaxies. Today, the latest catalogue based on data from the Fermi Large Area Telescope lists more than 5000 gamma-ray sources (Abdollahi et al. 2020), and exploring the COMPTEL archive in light of this knowledge has the potential to provide new insights into the MeV sky (Collmar & Zhang 2014).
While most of the COMPTEL data accumulated during the nine-year mission are stored at NASA's High Energy Astrophysics Science Archive Research Center (HEASARC) 1 , no publicly available software had existed to analyse these data. During CGRO operations the COMPTEL data were analysed using the COMPTEL Processing and Analysis Software System (COMPASS) (de Vries & COMPTEL Collaboration 1994), but 1 [URL]/ this system was only available at the COMPTEL collaboration institutes and was decommissioned after the end of the mission. Nevertheless, a few science results were still obtained from COMPTEL data after the end of the mission thanks to efforts at some COMPTEL collaboration institutes to keep Linux ports of the COMPASS data-analysis system alive (Strong & Collmar 2019;Coleman & McConnell 2020).
In order to preserve the capability to analyse the unique COMPTEL archive and to make COMPTEL data analysis accessible to the astronomical community at large, we have implemented a dedicated COMPTEL plug-in for the GammaLib library, a community-developed toolbox for the analysis of astronomical gamma-ray data (Knödlseder et al. 2011). The plug-in enables a reanalysis of COMPTEL data from the HEASARC archive, including the computation of the COMPTEL instrument response functions that until now had not been publicly available. The plug-in benefits from generic data analysis capabilities provided by GammaLib, including the joint maximumlikelihood fitting of multiple energy bands and the combination of COMPTEL data with data from other gamma-ray telescopes, enabling novel analysis approaches that go beyond the capabilities of the COMPASS system.
We furthermore extended the ctools gamma-ray astronomy science analysis software (Knödlseder et al. 2016) with the addition of several dedicated Python scripts. These scripts provide basic building blocks that each perform well-defined COMP-TEL data analysis tasks. These building blocks can be combined A&A 665, A84 (2022) to create flexible COMPTEL data analysis workflows for the exploration of the MeV sky.
In this paper we present the GammaLib plug-in and the ctools COMPTEL science analysis scripts, including the algorithms that were implemented, so that any science analysis that makes use of the software has a solid reference. We demonstrate that COMPTEL data analysis products derived using GammaLib and ctools, such as data cubes and response functions, are identical to equivalent products produced with the COMPASS software. We show that the background model that is implemented in GammaLib and ctools provides a reliable description of the COMPTEL instrumental background, and we discuss potential biases and limitations. Finally, we apply the software to a number of science cases and demonstrate that our software reproduces results published in the literature. All the algorithms and results presented in this paper were produced with GammaLib and ctools version 2.0.0. The analysis scripts and data presented in this work are available for download from Zenodo 2 .
The COMPTEL telescope
Before describing the software implementation, we recall some COMPTEL fundamentals that are important for understanding the remainder of the paper. COMPTEL was an imaging spectrometer that was sensitive to gamma rays in the energy range 0.75-30 MeV with an energy-dependent energy and angular resolution of 5-8% (full width half maximum) and 1.7 • −4.4 • (full width half maximum), respectively. The telescope had a large field of view of about one steradian and was sensitive to detected gamma-ray sources at a 1-30 MeV flux level of 10 −9 erg cm −2 s −1 within an observing time of 10 6 s (Schönfelder et al. 1993).
COMPTEL was composed of two modular detector layers D1 and D2, separated by 158 cm, where an incident gamma-ray photon was first Compton scattered in one of the 7 modules of D1 and then eventually interacted in one of the 14 modules of D2. The Compton scatter direction (χ, ψ) was obtained from the interaction locations in D1 and D2, the Compton scattering anglē ϕ was computed from the measured energy deposits E 1 and E 2 in D1 and D2, respectively, usinḡ where E = E 1 + E 2 is the total energy deposit in the detectors, and m e c 2 = 0.511 MeV is the rest energy of the electron. The detector layers were surrounded by an active anticoincidence shield, composed of two veto domes for each layer, that allowed for the reduction of instrumental background 3 due to charged particles. A further strong discriminator of instrumental background was the time of flight (ToF) measurement, which is the time difference between the interactions in D1 and D2 (cf. Sect. 3.3).
COMPTEL data were often analysed in four standard energy bands, covering 0.75-1, 1-3, 3-10 and 10-30 MeV, and if not otherwise stated, the same energy bands will be adopted in the present paper. Event selection parameters used in this paper are discussed in Sect. 3.3.
GammaLib plug-in
The COMPTEL support was implemented in GammaLib as an instrument plug-in that provides instrument-specific implementations of abstract virtual C++ base classes defining the data format and the instrument response functions. The plug-in also comprises wrapper functions providing access to all COMPTELspecific C++ classes through the gammalib Python module. All COMPTEL-specific classes begin with the letters GCOM.
COMPTEL data
COMPTEL data are available in the HEASARC archive and are grouped by so-called viewing periods with typical durations of two weeks during which the CGRO satellite had a stable pointing. In total, the HEASARC archive contains 255 exploitable viewing periods, which is about 71% of the total number of 359 viewing periods that were executed by COMPTEL 4 . All data are provided in FITS format.
The input data that are relevant to GammaLib for a given viewing period are event files, good time intervals, and orbit aspect data. The orbit aspect data comprise satellite orbit and telescope pointing information that are needed for coordinate transformations. COMPTEL data types are identified by a three-letter code, which is EVP for event files, TIM for good time intervals, and OAD for orbit aspect data. Each viewing period comprises a single EVP and TIM file, OAD files are provided per day. EVP data are handled by the GammaLib class GCOMEventList, TIM data by GCOMTim, and OAD data by GCOMOad and GCOMOads, where GCOMOad implements a single OAD record (or superpacket), and GCOMOads implements a collection of OAD records. These data structures are combined in an unbinned COMPTEL observation, implemented by the GammaLib class GCOMObservation. To construct an unbinned COMPTEL observation, the input data for a viewing period can be specified either by their file names or via a so-called observation definition XML file.
The HEASARC archive mixes different versions of EVP files that have different levels of processing for the ToF values. GammaLib will automatically correct for these differences, assuring that ToF values accessed through GammaLib are always ToF III values (see Appendix B).
Event cubes
COMPTEL data analysis is performed on binned event data using three-dimensional event cubes spanned by the Compton scatter direction (χ, ψ) and the Compton scattering angleφ. The binning is performed for events within a given interval of total energy, and each energy interval is treated as an individual COMPTEL observation. Combining multiple energy intervals for spectral analysis can be achieved by collecting the relevant COMPTEL observations in an observation container. The same holds for the combination of multiple viewing periods for a joint maximum likelihood analysis.
The COMPTEL data space is implemented by the GCOMDri class, and the GCOMDri::compute_dre method bins the events found in an EVP file into an event cube. In this process, event and then in D2 lead to a peak around channel 120, while upward moving photons interacting first in D2 and then in D1 produce a peak around channel 80. In the calibration data the upward moving photons can be clearly distinguished from the downward moving photons, while in the flight data the downward moving photons are blended with the tail of the dominating upward moving photons. The figure is adapted from Knödlseder (1994).
selection parameters are specified through the GCOMSelection class, comprising selection intervals for D1 energy deposit, D2 energy deposit, ToF channel value, pulse shape discriminator (PSD) channel value, rejection flag and veto flag. Standard event selection parameters that were used throughout this paper are summarised in Table 1. The ToF value measures the time between the interaction of the photons in the D1 and D2 modules, and provides a strong discriminator against instrumental background. Figure 1 illustrates that the ToF distribution of the events shows two distinct features: a forward peak associated with celestial photons that first interact in D1 followed by an interaction in D2, and a background peak due to events arising from a first interaction in D2 followed by an interaction in D1. While both peaks were clearly distinguishable in calibration data taken on ground (left panel of Fig. 1), they are heavily blended in orbit due to the dominance of upward moving background events (right panel of Fig. 1). Selecting only events from the forward peak considerably improves the signal-to-noise ratio, and Fig. 1 illustrates that the minimum ToF value has a strong impact on the background discrimination, with larger values removing more background at the expense of rejecting also an increasing number of celestial photons.
To correct for the photon rejection by the ToF selection an energy-dependent correction factor is applied to the instrument response. This ToF correction is performed internally by Gam-maLib (see Appendix C for details). Consequently, flux values returned by GammaLib are always corrected for ToF selection, in contrast to the COMPASS system where the correction had to be applied by the user posterior to the analysis.
An additional, but less important, event selection parameter is the PSD value, which discriminates between neutron and photon interactions in D1, with gamma rays found around channel 80 and neutron-induced events above channel 100 (Schönfelder et al. 1993). By default, the PSD selection interval is sufficiently large so that no flux correction factor needs to be applied, yet more stringent selection intervals that lead to improved performance (Collmar et al. 1997) eventually require the application of a PSD selection correction factor that is not implemented in GammaLib.
Furthermore, the Earth atmosphere being a strong gammaray source, an important background reduction is obtained by excluding events that may originate from the Earth atmosphere. This is achieved by requiring that event circles have a minimum angular distance ζ min from the Earth horizon. In the process of event binning, this requirement is translated into a constraint on the so-called Earth horizon angle (EHA), which is defined as the angular distance between the scatter direction of an event and the Earth horizon. Specifically, only the events are retained that satisfy EHA ≥ EHA min (φ) with whereφ min is the lower boundary of the event cube layer that comprises the Compton scattering angleφ. By default, ζ min = 5 • . Event selection and binning in GammaLib is done per superpacket, which is a bunch of eight spacecraft telemetry packets of 16.384 s duration that define the temporal granularity on which spacecraft orbital data information is available. Orbital data per superpacket are provided by the orbit aspect data (OAD) files, and events will be used only if their times are contained in the validity interval of any of the available superpackets. Furthermore, superpackets are considered valid only if their start and stop times are fully enclosed in one of the good time intervals, specified by the TIM file 5 .
Finally, the GCOMSelection class also supports the specification of phase intervals, so that events can be selected according to the orbital phase of a gamma-ray binary or the rotational phase of a pulsar. Owing to the different timescales involved, the handling of orbital phases differs from that of pulsar phases. For orbital phases, the phase as a function of event time is defined via an instance of the GModelTemporalPhaseCurve class, and the phase selection is done at the level of superpackets, implying that only orbital periods that are significantly longer than the superpacket duration of 16.384 s will produce meaningful results. We illustrate this capability below by a phase-resolved analysis of the gamma-ray binary LS 5039 (cf. Sect. 4.3). For pulsar phases, the phase selection is done at the level of individual events, using pulsar ephemerides and a Solar System barycentre time correction that is applied to the onboard time of the events. Details of the implementation are given in Appendix D, and we illustrate this capability below by a phase-resolved analysis of the Crab pulsar and pulsar wind nebula (cf. Sect. 4.2.2). 5 We note that COMPTEL times are specified by two values: the truncated Julian days (TJD), which is defined as the number of modified Julian days (MJD) minus 40 000, and the COMPTEL tics, which are 1/8 milliseconds long. As an example, TJD = 8393 and zero tics corresponds to 1991-05-17T00:00:00 UT. Only events for modules that are signalled as active are considered for the event binning. The detector module status is provided by the GCOMStatus class that relies on a database of daily status values that is provided with GammaLib. During the COMPTEL operations a certain number of photomultiplier tubes (PMTs) of the D2 modules failed, degrading the localisation precision of the event interactions in the respective modules. One option is to exclude these modules from the analysis, reducing the number of available events by about 25%. Alternatively, events from zones around the faulty PMTs can be excluded in the analysis, allowing recovery of a large fraction of the events for the analysis. Both analysis options are implemented in GammaLib (see Appendix E) and are explored in the analysis of LS 5039 (cf. Sect. 4.3).
COMPTEL event cubes are stored as three-dimensional FITS images with the file type designation DRE. Projections of an event cube generated using GammaLib for viewing period 2.0 6 and total energies in the interval 1-3 MeV are shown in Fig. 2 where for comparison the projections of an equivalent DRE obtained using the COMPASS software are shown. The projections of the datasets are nearly indistinguishable, illustrating that the event cubes generated by GammaLib are equivalent to those produced by the COMPASS software.
Factorisation
The COMPTEL instrument response function, given in units of events cm 2 photons −1 , is factorised using where DRX(α, δ) is the exposure in units of cm 2 s towards a given celestial direction (α, δ), DRG(χ, ψ,φ) is a geometry function that specifies the probability that a photon that was scattered in one of the D1 modules into direction (χ, ψ) will encounter one of the active D2 modules (the term also accounts for the Earth horizon event selection, which introduces theφ dependence), 6 We have chosen the second viewing period in the HEASARC archive to illustrate the data cube comparisons in our paper since for the first viewing period we encountered percent-level differences that are plausibly attributed to differences in our and the COMPASS processing configuration that we were not able to track down.
IAQ(φ|ϕ geo , E γ ) is the probability that a gamma-ray photon with energy E γ being Compton scattered in D1 interacts in D2, with ϕ geo = arccos (sin ψ sin δ + cos ψ cos δ cos(χ − α)) being the angular separation between (χ, ψ) and (α, δ), L is the livetime in units of s, and T is the exposure time in units of s. The fraction L/T is the so-called deadtime correction factor, specifying the fraction of time during which the telescope is able to register events. For COMPTEL this fraction is rather constant and was determined by van Dijk (1996) to be L/T = 0.965. This value is hardcoded in GammaLib, and automatically applied to all analysis results.
Exposure
The exposure map DRX(α, δ) is computed in GammaLib by the method GCOMDri::compute_drx using where T sp = 16.384 s is the duration of a superpacket and r 1 = 13.8 cm is the radius of a D1 module. The cos θ i factor takes into account the reduction of the effective D1 surface when viewed from an off-axis direction θ i , measured as the angle between the celestial direction (α, δ) and the COMPTEL pointing direction for a given superpacket i. The fraction accounts for the increased interaction length of off-axis photons within the D1 modules, where τ = 0.2 is the typical thickness of a D1 module in radiation lengths. The sum is taken over all superpackets {S } that satisfy the same selection criteria that were applied to the event selection (cf. Sect. 3.3). The exposure map is given in units of cm 2 s and is stored as a two-dimensional FITS image with the file type designation DRX. For illustration, Fig. 3 compares projections of the DRX obtained by GammaLib for viewing period 2.0 to the projections for an equivalent DRX that was obtained by COMPASS. The projections of the datasets are indistinguishable, illustrating that the exposure maps generated by GammaLib are equivalent to those produced by the COMPASS software.
Geometry function
The geometry function DRG(χ, ψ,φ) is the probability that a photon that was scattered in one of the D1 modules towards the direction (χ, ψ) will encounter one of the active modules of D2. It is computed by determining the geometrical area of the shadow of the D1 modules that is cast on the D2 modules relative to the total area of all seven D1 modules as a function of the scatter direction. Optionally, zones around failed D2 module PMTs can be excluded during this computation. The geometry function also accounts for the Earth horizon event selection, which introduces aφ dependence in the probabilities. As the position of the Earth with respect to the telescope changes continuously, the geometry function is recomputed for each superpacket, and the results are then averaged to provide an effective geometry function that applies to a given event cube. Similar to the computation of the exposure map, the superpackets {S } considered are those that satisfy the same selection criteria that were applied to the event selection. Details are provided in Appendix F.
The computation of the geometry function is implemented in the method GCOMDri::compute_drg and results are stored as three-dimensional FITS images with the file type designation DRG. Figure 4 illustrates the result of the geometry function computation, again in the form of projections for viewing period 2.0. Equivalent projections for a geometry function obtained using the COMPASS system are superimposed. The projections of the datasets are indistinguishable, illustrating that the geometry functions generated by GammaLib are equivalent to those produced by the COMPASS software.
Compton scattering probabilities
The Compton scattering probabilities IAQ(φ|ϕ geo , E γ ) were computed employing the method GCOMIaq::set using where P eff (ϕ geo , E γ ) is an efficiency factor that is detailed in Appendix G.1, P KN (ϕ geo , E γ ) is the contribution of the Klein-Nishina cross-section to a given bin in ϕ geo that is detailed in Appendix G.2, and R D1 (E 1 |Ê 1 ) and R D2 (E 2 |Ê 2 ) are the energy response functions of the D1 and D2 modules, respectively, that are detailed in Appendix G.3. The transformation from (ϕ geo , E γ ) to (Ê 1 ,Ê 2 ) is done usinĝ gives the D2 energy deposit as a function of the D1 energy deposit (E 1 ) and the Compton scattering angle (φ), and is the Jacobian for the variable transformation. Here K(ϕ geo |ϕ geo , θ) is a Gaussian kernel that provides some smearing of the response in ϕ geo to take into account the event location uncertainties in the D1 and D2 modules. The kernel formally depends on the zenith angle θ of the incoming gamma-ray photons. However, the IAQ is assumed independent of θ, and hence the kernel will be computed for an average zenith angle of θ = 25 • (see Appendix G.4 for details). The Compton scattering probabilities are stored as a twodimensional FITS image with the file type designation IAQ. For illustration, Fig. 5 compares projections of the Compton scattering probabilities obtained by GammaLib for the energy band 1-3 MeV to the projections for an equivalent file that was obtained using COMPASS. Both projections are indistinguishable, and the same is true for the other energy bands that were investigated. As demonstrated, the GammaLib implementation accurately reproduces the response computations that were implemented in COMPASS. We note that the implementation of the COMPTEL response computation within GammaLib is crucial for the preservation of COMPTEL data analysis capabilities, since response functions are lacking in the HEASARC archive. In addition to the internal response computation, Gam-maLib also includes several response functions that were derived using simulations (Stacy et al. 1996), and that can be used as an alternative to the internally computed response functions.
Background modelling
A considerable effort was undertaken by the COMPTEL collaboration to understand and model the instrumental background in the three-dimensional COMPTEL data space (e.g. Bloemen et al. 1994;Knödlseder 1994;van Dijk 1996;Weidenspointner et al. 2001). Satisfactory, although not perfect, results were obtained using the so-called SRCLIX method that was developed by Bloemen et al. (1994) and that has undergone several evolutions (van Dijk 1996). The SRCLIX method iteratively applies the BGDLIX algorithm, of which we implemented two variants in GammaLib. For reference, we also implemented the PHINOR algorithm (described below), and all background modelling methods are invoked in GammaLib via the GCOMObservation::compute_drb method. The iterative SRCLIX method is implemented as a ctools script (cf. Sect. 3.6).
PHINOR
The motivation for the PHINOR algorithm is the observation that the ratio of DRE and DRG multiplied by the solid angle Ω(χ, ψ) of the event cube bins is to first order independent of χ and ψ. This leads to a background model given by where is the convolution of a model of celestial sources I(α, δ, E γ ) with the instrument response function used to subtract any source contribution from the data before normalisation. The evaluation of DRM(χ , ψ ,φ) is implemented by the method GCOMObservation::drm. Despite its simplicity, the PHINOR algorithm yields generally empty residual maps above 10 MeV. However, for lower energies significant large-scale residuals are frequently observed (van Dijk 1996).
BGDLIXA
The BGDLIXA algorithm applies a correction to the PHINOR background model by adjustingφ templates TPL(χ, ψ,φ) over a limited interval ofφ values to a normalisation function n(χ, ψ,φ) that reflects the background event distribution DRE(χ, ψ,φ) − DRM(χ, ψ,φ) smoothed in χ and ψ using a running average (see below). The BGDLIXA algorithm evaluates the expression where the summation is performed over the range A84, page 6 of 31 ∆φ incl = ∆φ (N incl − 1)/2 , ∆φ excl = ∆φ (N excl − 1)/2 , N incl and N excl are either odd integers or zero, and ·/· designates the integer division operator. ∆φ is the bin size inφ of the three-dimensional event cube, which typically is 2 • . While in early days N excl > 0 was used, later analyses set N excl = 0, which simplifies the summation range to Rφ = [φ − ∆φ incl ,φ + ∆φ incl ]. Past COMPTEL analyses generally used N incl = 13 resulting in Rφ = [φ − 12 • ,φ + 12 • ]. As we will see later, N incl is the most critical parameter of the BGDLIXA algorithm, and specifies the number ofφ layers of the three-dimensional event cube over which the templates are adjusted. If N incl is large the fraction in Eq. (12) varies little withφ, leading to a background model that essentially follows the templates. For small values of N incl the fraction in Eq. (12) accommodates for differences between the templates and the normalisation function, leading to a background model that follows more closely the background event distribution at the expense of including also some of the source events. Theφ templates are computed using which are an adjustment of the PHINOR background model to match theφ-integrated χ, ψ distribution of the data after subtracting the contributions of celestial sources. To reduce the impact of statistical fluctuations of the data on the model, the match is performed by a running-average summation over a small range in χ and ψ, with R χ = [χ − ∆χ runav , χ + ∆χ runav ] and R ψ = [ψ − ∆ψ runav , ψ + ∆ψ runav ] where ∆χ runav = ∆χ N runav and ∆ψ runav = ∆ψ N runav . Here, 2N runav + 1 specifies the number of χ and ψ bins over which the running-average summation is performed, with ∆χ and ∆ψ being the bin size in χ and ψ of the three-dimensional event cube, and N runav is an integer number. Usually, ∆χ = ∆ψ = 1 • , and past analyses employed N runav = 3 resulting in a running averaging of ±3 • around each χ, ψ pixel (van Dijk 1996). The adjustment of theφ templates is done using a normalisation function computed using which is an analogue of Eq. (10) that is limited to a small range of χ, ψ around the pixel of interest. Specifically, A χ = [χ − ∆χ avgr , χ + ∆χ avgr ] and A ψ = [ψ − ∆ψ avgr , ψ + ∆ψ avgr ] where ∆χ avgr = ∆χ (N avgr − 1)/2 and ∆ψ avgr = ∆ψ (N avgr − 1)/2 . Here, N avgr is an odd integer that specifies the number of χ and ψ bins over which the adjustment is performed, with ∆χ and ∆ψ being the bin size in χ and ψ of the three-dimensional event cube. Past analyses usually employed N avgr = 3 resulting in an averag- 1996).
We want to point out that the COMPASS analysis system implemented instead of Eq. (14), which can lead to unreasonably large normalisations at the edge of the three-dimensional event cube where DRG values are small. Using Eq. (14) avoids such problems, and in fact leads to a simplified background modelling algorithm that we implemented in GammaLib under the acronym BGDLIXE (see below). Furthermore, we added a globalφ normalisation step, at the end of the computation so that the model is normalised to the number of background events in eachφ layer.
BGDLIXE
Recognising that Eqs. (13) and (14) both do the same thing (that is, they normalise the solid-angle-weighted geometry function to the measured event distribution), the BGDLIX background model can be simplified to which is a local fit of the PHINOR background model to the three-dimensional event distribution after subtracting any celestial sources. We note that N runav is no longer a parameter of the model, and the number of pixels in χ and ψ that are used for the local fit is determined by N avgr . We also included ā ϕ normalisation at the end of the computation equivalent to Eq. (16). Figure 6 compares the event cube projections to the projections for background models obtained using PHINOR, BGDLIXA and BGDLIXE using the parameters N runav = 3, N avgr = 3, N incl = 13 and N excl = 0 proposed by van Dijk (1996). While the PHINOR model provides a first-order description of the event distribution, it shows significant differences in the details. The BGDLIXA and BGDLIXE models follow the event distribution very closely, and both models are in fact indistinguishable from each other, demonstrating that their results are equivalent for the parameter values chosen.
ctools scripts
To support the science analysis of COMPTEL data, we extended the ctools package with a number of dedicated Python scripts, providing basic building blocks that each perform well-defined science data analysis tasks. This includes the generation of a database based on the data available in the HEASARC archive, the selection of COMPTEL viewing periods from this database, event binning and response computation, data combination, background modelling, model fitting, generation of test statistic (TS) maps, residual inspection, observation simulations, and source detection, as well as generation of pulsar pulse profiles. These scripts complement the already existing generic science analysis tools in ctools that may be used in combination with the new scripts. Table 2 summarises the COMPTEL-specific scripts that we added to ctools. Before starting a COMPTEL data analysis, a database needs to be generated from the data that are available in the HEASARC archive. This analysis step, which only needs to be performed once on a given computer, is performed by the comgendb script.
Once the database is generated, a typical COMPTEL analysis starts with executing comobsselect to select the relevant viewing periods for a given source or source region and observing time interval from the database. Results are provided as an observation definition file in XML format, which contains all the relevant information for the subsequent analysis steps. Following selection, the data are binned into three-dimensional event cubes and the corresponding DRX and DRG cubes are generated using comobsbin. The binning can be done for an arbitrary number of energy bands, enabling a joint spectral-spatial analysis that was not supported by the original COMPASS software. comobsbin also computes an initial background model DRB using the PHINOR algorithm (see Sect. 4.1), as well as the IAQ response matrices for the relevant energy bands. All output files are stored as FITS files in a data store, avoiding the recomputation of identical data files in subsequent analyses. Alternative background models using the algorithms described in Sect. 3.5 can be generated using comobsback.
Individual viewing periods can be combined into single event cubes for each energy band {E} using the comobsadd script, leading to a considerable speed-up of the data analysis. The combination of viewing periods is however not required, and alternatively the data can be analysed using a joint maximumlikelihood analysis of the selected viewing periods, a possibility that was not supported by the original COMPASS software. Combination of the viewing periods i is done using where T i is the exposure time of viewing period i and T = i T i is the total exposure time of the combined data. We note that Eq. (20) leads to an exposure map that is independent of α, δ and that is given by the maximum of the DRX for each viewing period, an approximation that is justified by the fact that the DRX is rather flat (see Fig. 3) and that the zenith angle variation in the response computation (cf. Eq. (3)) is dominated by the geometry function DRG (see also Knödlseder 1994).
In order to perform a maximum-likelihood analysis of the data, a model definition file in XML format needs to be generated. We automatised this task with the comobsmodel script, which in particular generates an adequate model definition for fitting the background model DRB to the data. COMPTEL background model fitting is done using the DRBPhibarBins model type, which introduces one scaling factor for eachφ layer for all viewing periods and energy bands. In addition, comobsmodel supports adding of a point source and diffuse model components to the model definition XML file.
The main script for maximum-likelihood model fitting is comlixfit, which implements the iterative SRCLIX algorithm. The algorithm starts from an input model definition XML file and computes a DRM model of the celestial sources using Eq. (11), which is then used to compute an initial background model using one of the PHINOR, BGDLIXA, or BGDLIXE algorithms. The script then uses the ctlike tool to fit the source and background models to the binned data. The celestial source model that results from the fit is then used to update the DRM model and to regenerate a background model using the selected algorithm. A new ctlike fit is then performed using the updated model, and the procedure is repeated until the maximum log-likelihood change between subsequent iterations becomes negligible, typically less than 0.05. Usually, the SRCLIX algorithm converges after a few iterations. Figure 7 illustrates the algorithm by showing TS maps for subsequent SRCLIX iterations for viewing period 1.0 that were obtained using the cttsmap tool. The TS is defined as (Mattox et al. 1996), where ln L(M s + M b ) is the log-likelihood value obtained when fitting the source and the background models together to the data, and ln L(M b ) is the log-likelihood value obtained when fitting only the background model to the data. Under the hypothesis that the background model M b provides a satisfactory fit of the data, TS follows a χ 2 n distribution with n degrees of freedom, where n is the number of free parameters in the source model component. Therefore, gives the chance probability (p-value) that the log-likelihood improves by TS/2 when adding the source model M s due to statistical fluctuations only (Cash 1979). We note that viewing period 1.0 is an observation of the Crab pulsar and pulsar wind nebula, which is by far the brightest source of gamma rays in the COMPTEL energy range. For the SRCLIX analysis, the data of the four standard energy bands were analysed jointly, and the Crab was modelled as a point source with power-law spectrum. The source location, prefactor and spectral index were free parameters in the fit. After each iteration of the SRCLIX algorithm, a TS map 7 was generated by replacing the Crab in the fitted model by a test source with fixed power-law spectral index of Γ = 2. The source visible at 7 The TS map comprises 50 × 50 pixels of size 1 • × 1 • situated around the Crab position. the centre of the TS maps is the Crab, which is already significantly detected after the first SRCLIX iteration. Subsequent iterations slightly increase the source significance, but overall the TS maps change little. The SRCLIX algorithm converged after six iterations.
The TS maps show a halo of marginal significance around the Crab, which can be explained by the fact that the maps were obtained using a background model that assumed the presence of a point source at the location of the Crab. The event cone of a test source placed a few degrees away from the Crab will pick up some of the excess counts left by the background model, which explains the halo in maps.
An alternative way to generate TS maps is provided by the comlixmap script, which applies the SRCLIX algorithm to each test source position, and which is the algorithm that was implemented by the COMPASS task SRCLIX. Here each pixel in the TS map corresponds to a different background model, and when moving away from the source location, no excess counts will remain in the data. This reduces the halo around the sources, as illustrated in the last panel of Fig. 7 that shows the TS map that was obtained using comlixmap for viewing period 1.0. At the same time, negative residuals are amplified, which is explained by the fact that the events of the Crab for test source positions offset from the source will be included as a smoothed event cone in the background model. We note, however, that this is only a feature of the TS maps, as ultimately, an adequate model of celestial sources that describes the COMPTEL event distribution should be derived from the data. Using that model as DRM in the BGDLIX algorithm will exclude any source events from the smoothing algorithm, and hence provides a reliable background model. For this approach the comsrcdetect script can be used, which extracts significant sources from TS maps and adds them to a model definition XML file. A subsequent run A84, page 9 of 31 A&A 665, A84 (2022) of the comlixmap script will then show whether any additional celestial sources remain in the data, building up iteratively an adequate model of celestial sources.
Following model fitting an inspection of the fit residuals is crucial. The comobsres script enables such an inspection by projecting the residual between the event and model cubes onto the sky by summing their content along the event cone using and where ϕ geo is the angular distance between a sky position (α, δ) and the Compton scatter direction (χ, ψ), and [ARM min , ARM max ] defines a selection window for the so-called angular resolution measure that is typically taken to be [−3 • , 3 • ]. We note that DRM designates here the model cube that comprises both the source and background components. By default, comobsres uses to compute the significance of the residuals R(α, δ) in Gaussian σ, where the sign term indicates whether the measured number of counts is larger or smaller than the number of counts predicted by the model. Some special cases need to be treated separately. Namely, if N(α, δ) = 0 the residual significance is while if M(α, δ) = 0 the significance cannot be computed and we set R(α, δ) = 0. The comobssim script enables the simulation of DRE event cubes by sampling the events according to a Poisson distribution using the expectation given by a model. Specifically, simulated events for a given celestial source model can be added by comobssim to existing observations, allowing the study of celestial sources with known properties in real data, a possibility that we use extensively in the next section.
Finally, compulbin will generate pulsar phase profiles by applying the algorithms described in Appendix D to individual events. Only events that satisfy the ARM selection according to Eq. (24) will be retained in the phase profiles, with typical values for the ARM window being [−3.5 • , 3.5 • ].
Science validation
Having verified that GammaLib and ctools reproduce data products that are identical to the ones that were generated with the COMPASS system, we now verify that the use of our software for an analysis of the data provided by HEASARC reproduces COMPTEL science results that were published in the literature. If not stated otherwise, for the analyses that follow we apply the event selection parameters specified in Table 1, a value of ζ min = 5 • , and we exclude D2 modules for which there were faulty photomultipliers.
Background model validation
An important step prior to any science analysis is the validation of the background model. An accurate background model predicts the background event distribution within statistical fluctuations, and allows for a reliable and accurate determination of the contribution of celestial gamma-ray sources to the measured events. As is obvious from Fig. 6, the PHINOR model certainly does not satisfy the first criterion; hence, we no longer consider this model here. On the other hand, the BGDLIXA and BGDLIXE models look promising, and were generally used in the past for science analysis of COMPTEL data. Since the BGDLIXA and BGDLIXE algorithms are equivalent as long as N runav ≤ N avgr , we limit our study here to the simpler BGDLIXE algorithm. Specifically, we investigate which values of N avgr and N incl provide reliable background models without introducing a significant bias in the reconstruction of celestial gamma-ray source characteristics. In agreement with previous studies of the algorithms (cf. van Dijk 1996) we always set N excl = 0.
Residual maps
We started with modelling the background for all COMPTEL viewing periods and the four standard COMPTEL energy bands using comobsback and the BGDLIXE algorithm under variation of the parameters N avgr and N incl . For each viewing period and energy band we created residual maps and histograms using comobsres that we inspected visually. We note that due to the dominance of the instrumental background in COMPTEL data, we do not expect to see celestial gamma-ray emission in the residual maps of individual viewing periods, with the exception of emission from the Crab pulsar and pulsar wind nebula, which is the strongest gamma-ray source at MeV energies. We find a general trend of stronger residuals at lower energies, with the largest residuals observed in the 1-3 MeV band. Notably, residuals are stronger for viewing periods for which the Earth horizon selection Eq. (2) introduces a strongφ dependence in the χ, ψ distribution of the events. The amplitude of the residuals changes strongly under variation of N incl , with larger residuals for larger values of N incl , while variations of N avgr impact the residuals only moderately.
For illustration we show residual maps obtained using the BGDLIXE algorithm for different values of N avgr and N incl and for three representative viewing periods and the 1-3 MeV energy band in Figs. 8 and 9. Viewing period 1.0 is an observation of the Crab pulsar and pulsar wind nebula, which is clearly visible in the residuals maps. Viewing period 223.0 is an observation of 1E 1740.7-2942, a low-mass X-ray binary that is also known as the 'Great Annihilator' and that is situated near the Galactic centre. The residuals in this viewing period are relatively modest. Viewing period 518.5 is an observation of the BL Lacertae object S5 0716+714, which is among the viewing periods with the worst residuals, featuring large zones of significant excess counts and negative depressions. The amplitude of the residuals clearly decreases with decreasing value of N incl , while at the same time smaller value of N incl also reduce the signal from the Crab. As we will show later, some of this signal can be recovered using the iterative SRCLIX algorithm, yet small values of N incl tend to lead to an underestimation of source fluxes. Therefore, the choice of N incl is necessarily a trade-off between the amplitude of background residuals and the suppression of source flux. On the other hand, the amplitude of the residuals changes only moderately with N avgr , with a slight increase of the residual amplitudes for increasing values of N avgr . To systematically quantify the residuals for a given choice of BGDLIXE parameters we computed for all viewing periods and the four standard COMPTEL energy bands the mean and random mean scatter (rms) of the residual maps. The results for the BGDLIXE algorithm as a function of N incl for N avgr = 5 and as a function of N avgr for N incl = 13 are shown in Fig. 10. The violins represent the density distribution of the mean and rms of the residual maps for all viewing periods. Viewing periods including the Crab were excluded to avoid any bias due to the presence of a strong source.
The plots confirm that the largest spread in the mean and rms are observed for lower energies, with a particularly large spread for the 1-3 MeV energy band. A large spread indicates that for some viewing periods the background model results in important residuals, while for other viewing periods the algorithm performs rather well, as illustrated in Figs. 8 and 9. Reducing N incl considerably reduces the spread in the mean and rms values for all energy bands, yet at some point the rms drops below the expected value of 1, indicating that the background model partially follows the statistical fluctuations of the data. This is also the regime where the source fluxes start to get underestimated.
This overfitting can be slightly reduced by increasing N avgr so that more events get included in the χ, ψ averaging, as indicated in the lower row of Fig. 10. On the other hand, increasing N avgr leads to a slight increase of the mean and rms distributions; hence, the selected value of N avgr should also not be too large.
Flux reconstruction
As the next step we studied the impact of the BGDLIXE parameters on the fitted values of celestial source parameters, such as source position, extent, flux and spectral index. We do this by using comobssim to add a simulated source at an offset angle of 20 • with respect to the pointing axis to the data of each viewing period for the four standard energy bands. In that way, our study relies essentially on the observed event distribution, and hence is representative for a real analysis situation, while the characteristics of the celestial source are known. As simulated source model we use a spatially extended disk component with radius of 3 • combined with a spectral power-law component with an energy flux of 1.068 × 10 −8 erg cm −2 s −1 within 0.75-30 MeV and a spectral index of 2.1, which roughly corresponds to the spectral parameters that are observed for the Crab. The simulated data of each viewing period were then fit jointly for the four energy bands using comlixfit, determining the maximum likelihood right ascension, declination, disk radius, energy flux, and spectral index of the source. Initial values for the iterative fitting procedure were offset from the simulated values since in a real data analysis the true source parameters are generally not known in advance. Viewing periods including the Crab were excluded from the analysis to avoid any interference with a known strong source of gamma rays. We furthermore assume that no other source of gamma rays is significantly detected in any of the remaining individual viewing periods, considering these viewing periods as empty fields for the purpose of this analysis.
For each fitted source parameter, i, we determine the pull where p i is the fitted value, v i is the simulated value, and σ i is the statistical parameter uncertainty as determined by comlixfit. In the absence of systematic uncertainties, and under the assumption that the statistical uncertainties are following a Gaussian distribution, Pull(p i ) follows a Gaussian distribution with a mean of zero and a standard deviation of σ = 1. Figure 11 summarises the results of the analysis, showing the pull distributions for all considered viewing periods as violin plots, with violins for right ascension, declination, disk radius, energy flux, and spectral index. The expectations for purely statistical parameter fluctuations are indicated by semi-transparent violins with grey borders, the horizontal black bars indicate the maximum, median and minimum pull of the distributions. The upper row shows results as a function of N incl for N avgr = 5, the lower row shows results as a function of N avgr for N incl = 13. Figure 11 indicates that large values of N incl lead to pull distributions that are broader than expected from statistical fluctuations only, in particular for the energy flux, but also for the spectral index and to a lesser extent for the other source parameters. The broadening is due to background residuals in some of the viewing periods for large N incl , as illustrated in Fig. 8, which impact the reconstructed source parameters. Reducing N incl brings the pull distributions more in line with the expectations, yet for N incl ≤ 13 the median pull of the fitted energy flux drops below zero, indicating a systematic bias towards too low fluxes. Specifically, for N incl = 5, where background residuals are very small (cf. Fig. 8), the flux reconstruction is strongly biassed, resulting is a significant underestimation of gammaray fluxes. The optimum value for N incl is hence a trade-off between reduction of background residuals and biassing the flux determination.
Flux biassing is also observed with increasing value of N avgr , with a minimum bias that occurs for N avgr = 5. Using hence N avgr = 5 and N incl = 15 for the BGDLIXE background modelling leads to results that are basically free from any systematic bias, although some significant background residuals may persist for this choice of values. As illustrated in Fig. 11, these background residuals translate into an additional uncertainty beyond the statistical fluctuations only. In the present case, the standard deviation of the energy flux pull distribution for N avgr = 5 and N incl = 15 is about twice as large as expected from statistical fluctuations only. In other words, when analysing individual viewing periods using BGDLIXE parameters N avgr = 5 and N incl = 15, the uncertainties in the energy flux related to the background modelling roughly doubles the uncertainties due to statistical fluctuations only.
In the following we use N avgr = 5 and N incl = 15 for the analysis in our paper, and we generally recommend to use these parameters for COMPTEL data analysis with GammaLib and ctools. We note that these values apply for a binning of 1 • in χ and ψ and 2 • inφ, and that for a different binning the parameters need to be adjusted accordingly. Specifically, we used an equivalent value of N incl = 29 for analyses in our paper for which a binning of 1 • is applied inφ.
Gamma-ray emission from the Crab
We began the science validation of our software with a spectral analysis of the gamma-ray emission from the Crab pulsar and pulsar wind nebula, which is the brightest source of gamma rays at MeV energies. The MeV flux is dominated by emission from the pulsar wind nebula, yet using pulsar ephemerides derived from radio observations the emission from the pulsar is also clearly detectable over the entire COMPTEL energy range. The emission from the Crab pulsar and pulsar wind nebula was studied extensively by COMPTEL in the past (e.g. Much et al. 1995aMuch et al. ,b, 1996van der Meulen et al. 1998;Kuiper et al. 2001).
Total spectrum
We first considered the combined emission from the Crab pulsar and pulsar wind nebula. In their analysis of five years of COMPTEL observations, van der Meulen et al. (1998) analysed the spectrum of the total Crab emission within the energy range 0.78−30 MeV in 30 narrow energy bins. Since this is the only work that quotes total flux values for the Crab (cf. Table 2 of the publication), we used this study as reference.
We analysed the same data that was used by van der Meulen et al. (1998) with GammaLib and ctools, except for viewing period 0 that is not available at HEASARC and viewing period 426.0 for which the EVP file in the HEASARC archive has a corrupted content. We binned the data according to the 30 energy bins defined by van der Meulen et al. (1998) and combined the data for all viewing periods using comobsadd using 80 bins in χ and ψ that were centred on the position of the Crab pulsar, taken here to be 83.6331 • in right ascension and 22.0145 • in declination (J2000). Similar to van der Meulen et al. (1998) we used 50 bins inφ, bin sizes of 1 • in all three data space dimensions, and instrument response functions derived by analytical modelling.
We modelled the Crab using a point source with fixed position, as given above, and using power-law, exponentially cut-off power-law or curved power-law spectral models. We fitted the data jointly for the 30 energy bins using comlixfit with BGDLIXE background model parameters N avgr = 5 and N incl = 29. The best fit was obtained using the exponentially cut-off power law with k = (1.81 ± 0.06) × 10 −4 ph cm −2 s −1 MeV −1 , Γ = 2.00 ± 0.03, and E c = 39.1 ± 9.7 MeV. van der Meulen et al. (1998) do not quote the parameters of a fitted spectral model to the total Crab emission data, so we used the GammaLib multi-wavelength interface to adjust the same spectral models to the data of their Table 2, which also favoured the exponentially cut-off power law with best fitting parameters k = (1.70 ± 0.05) × 10 −4 ph cm −2 s −1 MeV −1 , Γ = 1.97 ± 0.02, and E c = 29.8 ± 5.0 MeV. While our prefactor k is about 6% larger than the one obtained from fitting the spectrum of van der Meulen et al. (1998), the other spectral parameters are equivalent within statistical uncertainties. We then used ctbutterfly to determine uncertainty bands for the spectral models and csspec to derive flux points for the 30 energy bins. The results of our analysis are compared to those of van der Meulen et al. (1998) in Fig. 12. The uncertainty bands for the data of van der Meulen et al. (1998) were determined using ctbutterfly. Overall the agreement between both analyses is quite good, yet as mentioned earlier, our flux points lie somewhat above the ones determined by van der Meulen et al. (1998). Possibly this discrepancy may be related to correction factors that were applied posterior to COM-PASS analyses at the time that were not automatically taken into account by the software. These correction factors include an energy-dependent ToF correction factor (cf . Table C.1), an energy-independent deadtime correction factor of 0.965 as well as an energy-independent flux correction factor that was eventually applied to SRCLIX analyses to correct for a flux suppression that arose from the modification of the instrument response function (van Dijk 1996). We recall that GammaLib automatically applies the ToF and deadtime correction factors to the results. Whether or not such correction factors were applied by van der Meulen et al. (1998) is not known, yet they may plausibly explain the 6% discrepancy observed between the analyses.
Pulsar and nebula components
We now turn to an analysis that separates the emission from the Crab pulsar and the pulsar wind nebula to validate the implementation of the pulsar phase computations. The most comprehensive analysis of the emission from the Crab pulsar and pulsar wind nebula components using COMPTEL data was performed by Kuiper et al. (2001) using data collected over the nine years mission duration of CGRO. While Kuiper et al. (2001) used data from 33 viewing periods with pointing axis within 30 • of the Crab pulsar, we analysed 24 viewing periods that we found with the same selection criteria in the HEASARC database, covering the viewing periods specified in Table 1 of Kuiper et al. (2001) between viewing period 1.0 and viewing period 616.1. As in the analysis above, viewing period 426.0 was excluded from the list since no usable EVP file exists for this observation in the HEASARC database. Similarly to Kuiper et al. (2001) we used ephemerides for the Crab pulsar from the Princeton radio pulsar database, provided in the form of an ASCII file named psrtime.dat 8 that is part of the reference data of the X-ray Timing Explorer (XTE) module of the HEASoft software (version 6.29) 9 . We first used compulbin with an angular resolution measure of ±3.5 • to produce pulse profiles for the four standard COMPTEL energy bands, as displayed in Fig. 2 of Kuiper et al. (2001). The results of this analysis are shown in Fig. 13, on which we overlay for comparison the pulse profiles obtained by Kuiper et al. (2001). Since the Kuiper et al. (2001) profiles were obtained for a larger dataset and angular resolution measures that were not specified in their paper, we scaled the profiles so that the minimum and maximum number of events in the profiles matches the numbers that we obtained in our analysis. We also applied a phase shift of −0.03 to the pulse profiles of Kuiper et al. (2001) to match them to our profiles. While we do not know the origin of this small discrepancy in the pulse phases, we note that a phase shift of −0.03 corresponds to a difference of about 0.5 arcsec in the assumed right ascension of the Crab pulsar. In GammaLib, the pulsar position is taken from the ephemerides file, which in the present case is the radio position in the Princeton database, while Kuiper et al. (2001) do not specify the position that they assumed for the Crab pulsar. We note that the radio position in the Princeton database differs by about 0.5 arcsec from the International Celestial Reference System (ICRS) position provided by the Set of Identifications, Measurements, and Bibliography for Astronomical Data (SIMBAD) service 10 , which could be at the origin of the observed phase shift. 10 1 Energy (MeV) Fig. 14. Spectral energy distributions of the Crab pulsar and pulsar wind nebula components as determined using GammaLib and ctools (red) and by Kuiper et al. (2001) using COMPASS (blue). Results for the Crab pulsar are shown as dots, and results for the Crab pulsar wind nebula are shown as triangles. The figure also shows the 1σ uncertainty bands of the best fitting spectral models for both components.
As the next step we determined the spectra of the Crab pulsar and pulsar wind nebula to compare them to those given in Table 3 of Kuiper et al. (2001). For this purpose, we binned the events using comobsbin for the 12 energy bins specified in that table. The data were binned separately for the Off Pulse and Total Pulse phase intervals as defined in Table 2 of Kuiper et al. (2001), shifted by −0.03 to accommodate for the observed phase shift. Specifically, the Off Pulse interval comprises phases 0.49-0.85 while the Total Pulse interval comprises phases 0.85-1 and 0-0.49. We fitted the data for both intervals jointly using comlixfit with the BGDLIXE parameters N avgr = 5 and N incl = 29. We used two point-source model components in our fit, one for the Crab nebula that was fitted to the data of both phase intervals, and one for the Crab pulsar that was only fitted to the data of the Total Pulse interval. Consequently, the Crab pulsar component modelled only events that were in excess of the pulsar wind nebula component. Both point-source model components were located at the position of the Crab pulsar, as defined above, and had a spectral model with a free flux value for each of the 12 energy bins. Similar to Kuiper et al. (2001), we used simulated instrument response functions and 50 bins inφ with bin sizes of 1 • for our analysis.
The spectra obtained with our analysis are shown in Fig. 14 together with the spectra obtained by Kuiper et al. (2001). The agreement between the results is quite satisfactory and differences are generally well within statistical uncertainties. We note that there is no general flux offset between ours and the COM-PASS analysis, as observed above for the total Crab spectrum, and that differences are plausibly explained by the use of a different lists of viewing periods. Kuiper et al. (2001) noticed an enhanced emission in the 10-15 MeV energy interval for the Crab pulsar, and also in our analysis we found an equivalent feature. We note, however, that by shifting the phase interval definition by +0.03 (i.e. using the original phase interval definition of Kuiper et al. 2001) this spectral enhancement is considerably reduced in our analysis, suggesting that the enhancement is probably a statistical fluctuation rather than a physical feature.
We also fitted different spectral models to the data of the Crab pulsar and pulsar wind nebula, including power laws, exponentially cut-off power laws and curved power laws. We determined the corresponding uncertainty bands using ctbutterfly and overlay them on the spectral points in Fig. 14. Using an exponentially cut-off power law for the nebula component instead of a simple power law improved the TS value of the nebula component by 6.5, corresponding to a detection significance of 2.5σ for the spectral cutoff. For the pulsar component no improvement was achieved when allowing for a cutoff or a curvature in the power law. For the Crab pulsar wind nebula, the best fitting parameters of Eq. (29) were k = (13.7 ± 0.5) × 10 −5 ph cm −2 s −1 MeV −1 , Γ = 2.15 ± 0.03, and E c = 53.3 ± 15.5 MeV. For the Crab pulsar the best fitting power-law parameters were k = (5.1 ± 0.3) × 10 −5 ph cm −2 s −1 MeV −1 and Γ = 2.29 ± 0.06. This compares to the spectral indices of 2.227 ± 0.013 and 2.24 ± 0.04 determined by Kuiper et al. (2001) for the nebula and pulsar components using power-law models, respectively. While our index for the pulsar component is compatible with their result, our index for the nebula component is flatter, which can be explained by the spectral cutoff in our model. Using a simple power law for the nebula component, as Kuiper et al. (2001) did, we obtained a steeper index of 2.24 ± 0.02 that is compatible with their result.
Phase-resolved analysis of LS 5039
We now turn to an analysis of COMPTEL observations of the gamma-ray binary LS 5039 in order to validate the ability to conduct phase-resolved analyses with GammaLib and ctools. Using an orbit-resolved analysis, Collmar & Zhang (2014) found strong evidence that the MeV flux of GRO J1823-12, the strongest unidentified COMPTEL source in the Galactic plane, is modulated along the binary orbit of about 3.9 days of LS 5039. Specifically, using maximum likelihood significance maps, the authors demonstrated that GRO J1823-12 shows a more significant signal for the inferior conjunction period of LS 5039 as compared to the superior conjunction period. The same trend was also observed in their spectral analysis.
We repeated the analysis of Collmar & Zhang (2014) by choosing all viewing periods with pointing within 35 • of (l, b) = (17.5 • , −0.5 • ) from the HEASARC database. In total this resulted in a list of 41 viewing periods, starting with viewing period 5.0 and ending with viewing period 712.0. Up to viewing period 712.0 our list is identical to Table 1 of Collmar & Zhang (2014), yet the authors included 12 more viewing periods in their analysis that are not available in the HEASARC archive. For our analysis we combined the data in a data space of 140 × 123 × 25 bins of 1 • × 1 • × 2 • in size and centred on (l, b) = (15.0 • , −4.5 • ), which corresponds to the same dimensions that were used by Collmar & Zhang (2014) in some of their analyses. We used the four standard COMPTEL energy bands for our analysis. Similar to Collmar & Zhang (2014) we used the binary ephemeris of Casares et al. (2005), which is an orbital period of 3.90603 days with periastron passage (corresponding to phase 0) at JD 2451943.09, and we define phases 0.45 ≤ Φ < 0.9 as the inferior conjunction interval (INFC) and phases Φ ≥ 0.9 and Φ < 0.45 as the superior conjunction interval (SUPC).
As the first step we created TS maps of the region around LS 5039 using comlixmap for the INFC and SUPC phase intervals. The data for the four standard energy bands were analysed jointly, using a model composed of a test point source and an additional point source at the location of the quasar PKS 1830-210 that is spatially close to LS 5039. The spectra of both components were modelled using power laws. In addition, the source model included components for Galactic diffuse emission based Collmar & Zhang (2014) for an identical event selection (blue). The right panel compares the ctools and GammaLib results (red) to the results obtained using the COMPASS software by excluding D2 modules with faulty PMTs (blue). Data points from Collmar & Zhang (2014) and derived using COMPASS were displaced by 3% in energy for clarity. on template maps for bremsstrahlung and inverse Compton emission with free scaling factors for each energy bin 11 . Furthermore, an isotropic component was included to account for the cosmic gamma-ray background emission, with intensity fixed according to I(E γ ) = 1.12 × 10 −4 (E γ /5 MeV) −2.2 ph cm −2 s −1 MeV −1 sr −1 as suggested by Weidenspointner (1999). The background was modelled using the BGDLIXE algorithm with parameters N avgr = 5 and N incl = 15.
The resulting TS maps are shown in Fig. 15 for the INFC (left) and SUPC (right) phase intervals. The maps can be compared to those shown in Fig. 6 of Collmar & Zhang (2014), which were determined separately for the 3-10 MeV and 10-30 MeV energy bands. In both analyses, LS 5039 is considerably more significant in the INFC phase interval but only weakly detected in the SUPC phase interval. In the latter interval, the emission maximum seems to be displaced towards the north-east with respect to the position of LS 5039 in ours and the analysis of Collmar & Zhang (2014), yet the emission location is still compatible within the 3σ uncertainty contour with the position of LS 5039.
As the next step we derived the spectral energy distribution of LS 5039 for the four standard energy bands using csspec for both phase intervals to reproduce Fig. 7 of Collmar & Zhang (2014). In addition, we also derived for both phase intervals the uncertainty band of the fitted power-law model using ctbutterfly. The results are shown in Fig. 16 used by Collmar & Zhang (2014) which is a minimum distance from the Earth horizon of ζ min = 0 • and the use of circular exclusion regions to handle D2 modules with failed PMTs (i.e. fpmtflag = 2; cf. Appendix E). Only with this event selection we were able to reproduce the 1-3 MeV flux point of Collmar & Zhang (2014), while using our standard setting of ζ min = 5 • and fpmtflag = 0 that excludes D2 modules with failed PMTs produced a notable variation of the 1-3 MeV flux point between inferior and superior conjunction. To verify that this variation can indeed be attributed to differences in the event selection, we also did an equivalent analysis with COMPASS using ζ min = 5 • and fpmtflag = 0. This resulted in a 1-3 MeV flux variation between inferior and superior conjunction that was similar to that observed in our analysis, confirming that the spectral differences are due to differences in the event selection. The corresponding results are summarised in the right panel of Fig. 16. As illustrated by the uncertainty bands of the fitted powerlaw model, the use of circular exclusion regions for D2 modules with faulty PMTs leads to a flatter (or softer) spectrum in superior conjunction, yet the variation seems still to remain within statistical uncertainties, given the broadness of the uncertainty band. After all, LS 5039 is a very faint source in SUPC, and hence its spectral properties are only poorly constrained in this phase interval.
Finally, we derived the orbital flux variation in the 10-30 MeV energy band for the two different event selections to reproduce Fig. 8 of Collmar & Zhang (2014). For this purpose we split the 10-30 MeV data into five phase intervals of equal length and fitted the data using comlixfit with a source model comprising components for LS 5039, PKS 1830-210, bremsstrahlung emission, inverse Compton emission and cosmic background emission (see above for details). The background was modelled using the BGDLIXE algorithm with parameters N avgr = 5 and N incl = 15. The results are shown in Fig. 17.
Our analysis reproduces the orbital light curve of Collmar & Zhang (2014) within statistical uncertainties. Differences between their flux points and ours can be explained by differences in the event selection, as Collmar & Zhang (2014) use a larger number of viewing periods compared to our analysis. Notes. Bins 1 and 11 serve primarily to constrain continuum gammaray emission, while bins 2-10 serve to trace the shape of the 1.8 MeV gamma-ray line.
Variations of the same size are also observed in our analysis for the two different event selections, which, however, are well within statistical uncertainties, as expected.
26 Al line emission from Carina
As the next step we validated the capacities of GammaLib and ctools for gamma-ray line emission analysis together with its abilities to assess the spatial morphology of the emission. As reference, we chose the COMPTEL detection of point-like 1.8 MeV line emission from the Carina region for this validation, as reported by Knödlseder (1994) and Knödlseder et al. (1996a), which are to our knowledge the only published studies where an analysis using a parametric spatial model was performed with COMPTEL.
In their studies the authors analysed COMPTEL data from viewing periods 1 to 301 combined in a data space of 100 × 100 × 25 bins of 1 • × 1 • × 2 • in size, centred on (l, b) = (286.5 • , 0.5 • ), which corresponds to the peak position of the observed 1.8 MeV line emission feature. The emission feature was found to be compatible with a point-like source with an 1.8 MeV flux of (3.1 ± 0.8) × 10 −5 ph cm −2 s −1 that was determined through model fitting. Using fits of models with uniform intensity within a circular region centred on (l, b) = (286.5 • , 0.5 • ), Knödlseder et al. (1996a) determined a 2σ upper limit of 5.6 • for the diameter of the 1.8 MeV emission region. The analysis was done in a single energy bin covering 1.7-1.9 MeV, and the instrumental background was modelled using measurements in adjacent energy intervals that were corrected for the energy dependence of the Compton scatter angleφ. This method suppresses to first order emission from continuum gamma-ray sources (Knödlseder et al. 1996b).
We analysed the same data and adopted the same data space definition that was used by Knödlseder et al. (1996a), yet we tested an alternative analysis method that jointly handles the 26 Al line signal and any underlying continuum emission. This is more in line with the GammaLib and ctools philosophy of explicitly modelling all emission components and provides a more accurate handling of underlying continuum emission. Specifically, we split the data within the 1-3 MeV energy interval into 11 energy bins, specified in Table 3, and analysed them jointly using a combination of model components describing the 1.8 MeV line signal, any underlying continuum gamma-ray emission and the instrumental background. To model the 1.8 MeV line emission A84, page 18 of 31 spectrum we used a Gaussian spectral component with a fixed mean of 1.809 MeV and a standard deviation of σ = 58.9 keV that corresponds to COMPTEL's instrumental energy resolution at that energy. Similarly to our analysis of LS 5039 we modelled continuum emission using template maps for Galactic bremsstrahlung and inverse Compton emission and an isotropic component for the cosmic gamma-ray background. The spectra of the three continuum components were model using power laws, where the prefactors and indices were free for the Galactic components, while the prefactor and index were fixed to I(E γ ) = 1.12 × 10 −4 (E γ /5 MeV) −2.2 ph cm −2 s −1 MeV −1 sr −1 for the cosmic gamma-ray background component, as suggested by Weidenspointner (1999). The TS map was generated using comlixmap and model fitting was done using comlixfit with the standard BGDLIX parameters N avgr = 5 and N incl = 15. We illustrate our analysis procedure in Fig. 18, which shows the counts spectrum determined using Eq. (24) for the position (l, b) = (286.5 • , 0.5 • ) at which Knödlseder (1994) found the 1.8 MeV line emission maximum and an ARM window of ±3 • . We also show the model components that were fitted using comlixfit and that we extracted using Eq. (25). We used a point source located at the fixed position (l, b) = (286.5 • , 0.5 • ) as spatial model for the 1.8 MeV line component. Figure 18 illustrates that the data are dominated by instrumental background, followed by cosmic gamma-ray background. The bottom panel illustrates that, once these components are subtracted, a clear line signal becomes apparent that is compatible with the expected signature of the 26 Al decay line. In addition, a continuum signal is detected that is dominated by Galactic bremsstrahlung emission.
In their Fig. 2, Knödlseder et al. (1996a) present a 1.8 MeV line emission maximum likelihood map of the Carina region, and we produced an equivalent TS map with the same spatial binning using comlixmap. Specifically, we fitted point-source models for the 1.8 MeV line emission and the 1-3 MeV continuum emission for a grid of source positions, producing hence TS maps for both emission components. In the fitting the fluxes of both point sources were constrained to non-negative values. The resulting maps are shown in Fig. 19, where the left map can be compared to the maximum likelihood map presented in Fig. 2 of Knödlseder et al. (1996a). Both maps show qualitatively comparable features, yet we obtained a maximum TS value of 23.1 at (l, b) = (285.5 • , 1.5 • ) while Knödlseder et al. (1996a) found a lower maximum TS value of 14.7 at (l, b) = (286.5 • , 0.5 • ). Eventually, these differences may be explained by the background modelling techniques and analysis methods that differ significantly between the studies. We recall that Knödlseder et al. (1996a) analyse the 1.8 MeV line data in a single energy bin covering 1.7-1.9 MeV and used a background model derived from adjacent energy bands, which to first order includes also continuum emission, but which does not properly account for spectral differences between instrumental background and diffuse emission components as well as differences in theirφ distributions (Bloemen et al. 1999).
It is actually rather reassuring that both approaches produce qualitatively comparable maps, as already suggested by Bloemen et al. (1999) who implemented a comparable analysis method to ours. The continuum TS map indicates that the continuum emission is located towards the Galactic plane, suggesting that it originates from our Galaxy. We emphasise, however, that the statistical significance of the emission features is modest, and consequently the appearance of the map is notably affected by the statistical fluctuations of the data. Nevertheless, we note that observed TS maxima are not too far from maxima in the Galactic bremsstrahlung emission, which eventually may be the dominant MeV emission component near the Galactic plane (Strong et al. 1996).
As the next step we fitted the data with a source model composed of a 1.8 MeV line component modelled using a point source and a 1-3 MeV continuum component modelled using a combination of bremsstrahlung and inverse Compton spatial maps as well as an isotropic component for the cosmic gamma-ray background. The position of the point-source model as well as the spectral parameters for the Galactic continuum power-law components were free parameters in the fit. Fitting the data using comlixfit gave a best fitting position of (l, b) = (285.4 • ± 0.8 • , 1.3 • ± 0.7 • ), a flux of (3.1 ± 0.6) × 10 −5 ph cm −2 s −1 and a TS value of 22.3 for the 1.8 MeV line component. Our 1.8 MeV line flux is consistent with the value of (3.1 ± 0.8) × 10 −5 ph cm −2 s −1 found by Knödlseder et al. (1996a), yet our best fitting position is offset by about 1.4 • from the one found in their analysis. Replacing the point source for the 1.8 MeV line component by a radial disk model did not improve the fit and led to a best fitting disk radius of 0.003 • , which is near the minimum value of 0.001 • that we allowed in the analysis. Using the ctulimit tool we derived a 2σ upper limit of 5.1 • for the diameter of the disk, a bit smaller than the value of 5.6 • determined by Knödlseder et al. (1996a). This difference is plausibly explained by the larger detection significance of the 1.8 MeV line emission signal in our analysis, allowing us to put a stronger constraint on the extent of the emission region.
Finally, we tried to reproduce analyses is very similar, yet our analysis turns out to be a bit more constraining, probably owing to the more significant detection of the 1.8 MeV line emission feature with respect to the analysis of Knödlseder (1994). The flux attributed to the 1.8 MeV line component changes actually very little with disk radius in our analysis, while in Knödlseder (1994) the flux decreases with increasing disk radius. This difference is probably partly due to fact that our analysis detects the 1.8 MeV line signal more significantly, but may also be related to our analysis method that gives freedom to the continuum emission model components to adjust as a function of the 1.8 MeV disk model radius, while in Knödlseder (1994) the continuum emission was implicitly subtracted by the background model, resulting in a much more constrained overall model that leaves little freedom for the model to adjust.
Conclusion
We have implemented a comprehensive science analysis framework for COMPTEL gamma-ray data in the GammaLib and ctools software packages, and we have demonstrated that our software reliably reproduces published analysis results that were derived using the COMPASS software. Having public, free, and validated software for COMPTEL science data analysis now opens the HEASARC COMPTEL archive to the community for scientific exploration. In the medium-energy gamma-ray band, from 1-30 MeV, the COMPTEL archive still contains the most sensitive observations ever performed, and a unique dataset for exploring the non-thermal Universe and nuclear transition lines.
Since the 1990s when the COMPTEL data were taken, the field of gamma-ray astronomy has made impressive progress thanks to satellites such as the International Gamma-Ray Astrophysics Laboratory (INTEGRAL) and Fermi and ground-based observatories such as the High Energy Stereoscopic System (H. E. S. S.), the Major Atmospheric Gamma-ray Imaging Cherenkov Telescope (MAGIC), and the Very Energetic Radiation Imaging Telescope Array System (VERITAS). Many source classes that are known today were not established as gamma-ray emitters during the COMPTEL era, and the COMPTEL data were never comprehensively analysed with the current knowledge in the field. An exception to this is the post-mission discovery of the orbital modulation of MeV gamma-ray emission of LS 5039 in the COMPTEL archival data by Collmar & Zhang (2014), a source that was not an established gamma-ray emitter in the 1990s. Thanks to GammaLib and ctools, such discoveries are now achievable by the community at large. We want to stress that our work was also motivated by the goal of reducing the carbon footprint of astronomical research. As recently pointed out by Knödlseder et al. (2022), the current deployment rate of new astronomical observatories is not compatible with the imperative of reducing the carbon footprint across all activity sectors of modern societies, and this calls for fundamental changes in astronomical practices in the future. Among the many possible alternatives to the building of ever more and ever bigger new astronomical facilities is the exploitation of archival data from past missions that may have scientific treasures yet to be discovered. Since version 2.0.0, ctools estimates the carbon footprint of its use based on the assessment of Berthoud et al. (2020) for the GRICAD computing centre, and, using this feature, we estimate that the work presented in this publication resulted in the generation of 600 ± 300 kgCO 2 e of greenhouse gases (GHGs) due to the computing related to the analysis of archival data. This is about 40 times less than the median per-publication emissions associated with the analysis of data from an active astronomical observatory (Knödlseder et al. 2022). Taking all sources of emissions related to this work into account, we estimate the carbon footprint of this research to be 1.9 ± 0.3 tCO 2 e (see Appendix H).
This assessment illustrates that the exploitation of archival data instead of the development of new astronomical observatories has the potential to dramatically reduce the carbon footprint of astronomical research, which would help realise the reductions that are needed to limit global warming and reach the goals of the Paris Climate Agreement. Past missions can be seen as our scientific carbon legacy since the GHGs that were emitted during their construction and operations are to a large extent still present in the Earth's atmosphere. To assure that these GHGs were at least not emitted in vain, conservation of the archival data and the development and maintenance of software for their exploitation should therefore be of the utmost importance. The HEASARC archive was created from the original COMPTEL data using dedicated file conversion software that generated FITS files following recognised standards (Pence et al. 2010). While interpreting these FITS files using Gam-maLib we found that the units in some of the table columns were not correct. We summarise the inconsistencies that we encountered in Table A.2. We furthermore found that the good time interval dataset for viewing period 8.0 with the identifier MPE-TIM-11481 only contains about half of the good time intervals that were defined in COMPASS, probably as the result of a file truncation error in the input ASCII file that was used for the generation of the FITS file in the HEASARC archive.
The HEASARC archive also comprises binned data products for standard energy bands that can be used for analysis using GammaLib, yet we note that the world coordinate system information attached to these data products is incorrect. While the FITS headers suggest that the data cubes are provided in Mercator projection, the event cubes are presented in a cartesian pro- jection with a reference latitude value of 0. For all event cubes given in Mercator projection GammaLib assumes that they originate from the HEASARC archive and corrects the world coordinate system information upon reading of the event cubes.
The HEASARC archive comprises further data products such as telescope housekeeping data, gamma-ray burst detector data and sky maps that are not used by GammaLib.
Appendix B: Time of flight conversion
The HEASARC archive mixes different versions of EVP files that have different levels of processing for the ToF values. The versions can be distinguished by the header keyword DSD_REP in the EVP file, specifying either 2 for ToF II or 3 for ToF III , where the latter corrects for energy dependent effects, aligning the forward peak at channel number 120 (see van Dijk 1996 andWeidenspointner 1999 for an explanation of the ToF corrections). If a version 2 EVP is encountered, the GCOMEventList class will automatically convert ToF II values into ToF III using
Appendix C: Flux correction due to time of flight selection
To correct for the photon rejection by the ToF selection an energy-dependent correction factor needs to be applied to the instrument response. Since this correction factor depends on the ToF selection interval, it is computed in GammaLib during the A84, page 22 of 31 J. Knödlseder et al.: COMPTEL data analysis using GammaLib and ctools
Appendix D: Pulsar timing
GammaLib supports generation of event cubes, geometry functions and exposure maps for phase-resolved pulsar analysis. For this purpose a specific processing is implemented in the methods GCOMDri::compute_dre, GCOMDri::compute_drg, and GCOMDri::compute_drx that is used if the specified GCOMSelection instance includes pulsar ephemerides data and the specification of pulsar phase intervals. All three methods will first trim the good time intervals of the observation so that they only cover periods for which the specified pulsar ephemerides are valid. In that way, GammaLib assures that only data will be used for an analysis that cover intervals with valid pulsar ephemeris information.
The remaining pulsar-specific code is implemented in GCOMDri::compute_dre. First, the method converts arrival times t CGRO of COMPTEL events at the CGRO satellite, specified in the Coordinated Universal Time (UTC) time system, into arrival times t SSB at the Solar System barycentre, specified in the barycentric dynamical time (TDB) system.
As a side note, before 1992-06-25T01:00:00 UTC the CGRO onboard clock was early by 2.042144 seconds, and this time difference needs to be subtracted from the measured onboard time to get the true arrival time in UTC. In GammaLib, this subtraction is automatically performed when converting onboard times, given in truncated Julian days (TJDs) and tics, into GTime objects using the gammalib::com_time function, and the conversion is undone when using the inverse functions gammalib::com_tjd and gammalib::com_tics.
After applying the clock correction, event times are converted using where ∆t CGRO→SSB corrects for the light travel time from CGRO to the Solar System barycentre, ∆t Shapiro corrects for the gravitational time delay near the Sun, also known as Shapiro delay, ∆t UTC→TT converts from UTC to terrestrial time (TT), and ∆t TT→TBD converts from TT to the TDB time system. We note that all time correction terms are themselves time dependent, yet we ignore this time dependence in Eq. (D.1) to simplify the notation. All terms are given in units of seconds. The computation of the three terms ∆t CGRO→SSB − ∆t Shapiro + ∆t TT→TBD is implemented by the GEphemerides::geo2ssb method, which regroups all time corrections that depend on planetary ephemerides. GammaLib deals with planetary ephemerides through the GEphemerides class, and the software includes the Jet Propulsion Laboratory (JPL) Development Ephemeris 200 including information about the Sun position, the Earth position and its first three time derivatives, and the time difference between TT and TDB in seconds on a daily basis between Julian day (JD) 2436913 (10 December 1959) and 2469807 (31 December 2049). Specifically, the method computes is the unit vector in celestial coordinates of a pulsar with right ascension α and declination δ, e is the vector from the Solar System barycentre to the centre of the Earth, s is the vector from the Solar System barycentre to the centre of the Sun, r is the vector from the centre of the Earth to the CGRO spacecraft, and t = 4.92549 × 10 −6 (D.5) is half the Schwarzschild radius of the Sun divided by the speed of light. All vectors are given in units of light seconds and are specified in the celestial coordinate system. The Earth vector e at a given time t CGRO (specified in the TT time system) is computed using the Taylor expansion e = e(i) +ė(i)∆t + 1 2ë (i)∆t 2 + 1 6 ... e (i)∆t 3 , (D.6) where i is the index of the nearest entry in time in the JPL database, e(i),ė(i),ë(i), and ... e (i) is the Earth position and its first three time derivatives for this entry, and is the time difference between the event time and the nearest entry in the JPL database in units of days, which by definition is in the range −0.5 and +0.5. Since the Sun moves only a little around the Solar System barycentre, it is sufficient to take for the Sun vector the nearest entry in the JPL database, which is A84, page 23 of 31 A&A 665, A84 (2022) s = s(i). Finally, the conversion from the TT to the TDB time system at a given time t CGRO is computed using ∆t TT→TDB = ∆t TT→TDB (i) + (∆t TT→TDB (i + 1) − ∆t TT→TDB (i))∆t, (D.8) where ∆t TT→TDB (i) is the nearest entry in the JPL database. The last term in the time correction, ∆t UTC→TT , does not depend on planetary ephemerides and is given by where n leap is the number of leap seconds. The computation of ∆t UTC→TT is implemented by the GTime::utc2tt method. The HEASARC archive includes for most of the viewing periods files that provide for each superpacket the vectors e + r as well as the correction terms ∆t UTC→TT + ∆t TT→TBD , avoiding the need for planetary ephemerides. These so-called BVC data can be handled by GammaLib through the classes GCOMBvc and GCOMBvcs that manage individual data records as well as entire files. Specifically, the method GCOMBvcs::tdelta computes ∆t CGRO→SSB − ∆t Shapiro + ∆t UTC→TT + ∆t TT→TBD , and if the observation that should be binned includes BVC information, GCOMDri::compute_dre will use this method instead of the algorithm described above for the barycentric time correction. The formulae used by GCOMBvcs::tdelta are identical to those described above, except for the Shapiro time delay for which the displacement of the Sun from the Solar System barycentre is neglected: Following the time correction, the pulsar phase Φ is computed using the GPulsarEphemeris::phase method that implements where ν,ν andν is the pulsar frequency and its first two time derivatives, ∆t = t SSB − t 0 is the elapsed time since the reference time of the ephemeris, and Φ 0 is the pulsar phase at the reference time. Only the fractional part of the pulsar phase is retained so that its value is within the interval [0, 1). Pulsar information, including specifically the ephemerides of a pulsar, is handled by the GPulsar class that supports reading of ephemeris information from various file formats. The format most relevant to COMPTEL is the psrtime format, which is an ASCII file format containing the radio pulsar database as maintained during the CGRO mission by the pulsar group at Princeton and nowadays by the Jodrell Bank Centre for Astrophysics. 12 Upon loading of a psrtime file, the GPulsar::load_psrtime method computes from the data the pulsar phase at the reference time using
Appendix E: Handling of failed photomultiplier tubes
COMPTEL comprised two detector layers, composed of 7 and 14 circular modules for D1 and D2, respectively. Modules of the first layer were composed of the liquid scintillator NE 213A while modules of the second layer were made of NaI(Tl) scintillator crystals. Each D1 module was viewed by eight PMTs while each D2 module was viewed by seven PMTs. The relative amplitudes of the PMT signals for a given module allowed localisation of the interactions within the module with an average 1σ spatial resolution of 2.3 cm for D1 modules and 1.5 cm for D2 modules (Schönfelder et al. 1993). During the operations of COMPTEL a certain number of D2 module PMTs failed (cf . Table E.1), degrading the interaction localisation capabilities within the concerned modules and hence increasing the uncertainties in the determination of the event scatter directions (χ, ψ). GammaLib implements several options for handling data from D2 modules with failed PMTs, controlled through the GCOMSelection::fpmtflag method that takes an integer value of 0, 1, or 2. This integer value is a user parameter of the ctools scripts comobsbin and compulbin that, by default, is assumed to be 0.
For fpmtflag = 0, events registered in D2 modules with failed PMTs are ignored, and the corresponding modules are also excluded in the computation of the geometry function (cf. Appendix F). Conversely, for fpmtflag = 1 the failure of the PMTs is ignored, and events from D2 modules are treated as if the failed PMTs were still operating. Finally, for fpmtflag = 2, circular exclusion regions are applied around the zones of the failed PMTs for dates after their failure, as defined in Table E.1. Events localised within these regions are ignored and the regions are removed in the computation of the geometry function (cf. Appendix F). Using circular exclusion regions was the default for most of the COMPTEL analysis published in the literature in the past. The impact of the fpmtflag value on the analysis results is illustrated for the case of the spectral energy distribution of LS 5039 in Sect. 4.3.
Appendix F: Computation of the geometry function
The geometry function DRG is computed in GammaLib by the method GCOMDri::compute_drg using where EHA(χ, ψ) is the distance between scatter direction (χ, ψ) and the Earth horizon, EHA min (φ) is given by Eq.
(2), and N is the number of selected superpackets. The G i (χ, ψ) is the geometry factor for a given superpacket and corresponds to the area of the shadow that is cast by all active D1 modules on all active D2 modules for a given scatter angle (χ, ψ) divided by the total area of all D1 modules. The computation of the geometry factor is implemented in GCOMDri::compute_geometry and calculated using are determined using the GCOMStatus class. In case of fpmtflag = 0, failed modules according to Table E.1 are also considered as inactive for superpacket dates after the dates of PMT failure. Furthermore, with r 1 = 13.8 cm being the radius of a D1 module and r 2 = 14.085 cm being the radius of a D2 module. We note the margin of 0.1 cm in Eq. (F.6), which assures numerical stability with respect to rounding errors. The d kl is the projected distance between the centres of the D1 and D2 modules, given by where x k and y k are the geometric positions of the D1 modules and x l and y l the positions of the D2 modules with respect to the optical axis in cm, h = 158 cm being the vertical separation between D1 and D2 modules, (θ, φ) being the zenith and azimuth angles of the Compton scatter direction (χ, ψ) with respect to the COMPTEL pointing direction, and o kl (θ, φ) = r 2 1 (α kl − sin α kl cos α kl ) + r 2 2 (β kl − sin β kl cos β kl ) πr 2 1 (F.8) being the projected overlap of a D1 module and a D2 module with cos α kl = d 2 kl + (r 2 1 − r 2 2 ) 2d kl r 1 (F.9) and cos β kl = d 2 kl − (r 2 1 − r 2 2 ) 2d kl r 2 . (F.10) The term f kle (θ, φ) accounts for the exclusion of circular regions around failed PMTs and differs from zero only for fpmtflag = 2. It quantifies the fractional overlap between the projected D1 module k and the part of the exclusion region for failed PMTs that is contained within D2 module l. The exclusion region is circular, and specified by a geometric centre position x e and y e and a radius r e as given in Table E.1. Specifically, for fpmtflag = 2 being the distance between the projected D1 module centres x k and y k and the centre x e and y e of the exclusion region. The f contained le (θ, φ) is the overlap for the case that the exclusion circle is fully contained in the projected D1 module circumference. In this case, the relevant overlap to take into account is the overlap between the exclusion circle and the D2 module, given by (F.13) with d le = (x e − x l ) 2 + (y e − y l ) 2 (F.14) being the distance between the centres of the exclusion circle and the D2 module, and f contained le (θ, φ) = r 2 1 (α le − sin α le cos α le ) + r 2 2 (β le − sin β le cos β le ) πr 2 1 (F.15) being the overlap of the exclusion region and the D2 module with cos α le = d 2 le + (r 2 1 − r 2 2 ) 2d le r 1 (F.16) and cos β le = d 2 le − (r 2 1 − r 2 2 ) 2d le r 2 . (F.17) The evaluation of Eq. (F.13) is implemented by the method GCOMDri::compute_surface. Finally, f partial kle (θ, φ) specifies the fractional overlap between the projected D1 module, the D2 module and the exclusion circle. This quantity is evaluated numerically by testing a grid of 25 × 25 x and y positions around the exclusion circle. The numerical evaluation is implemented by the method GCOMDri::compute_overlap.
Appendix G: Response computation
The following sections describe some details of the response computations implemented in GammaLib.
Appendix G.1: Efficiency factors
The efficiency factor P eff (ϕ geo , E γ ) in Eq. (6) is factorised according to being the energy of the photon entering the D2 module for a true scatter angle ϕ geo and an incident photon energy of E γ , and E 1 = E γ −Ê 2 being the true energy deposit in D1 for a single Compton scattering by an angle of ϕ geo . The GammaLib methods that implement the computation of the efficiency factors are summarised in Table G.1. Factor Method P eff (ϕ geo , E γ ) GCOMIaq::weight_iaq P A1 (E γ ) GCOMInstChars::trans_D1 P V1 (E γ ) GCOMInstChars::trans_V1 P D1 (E γ ) GCOMInstChars::prob_D1inter P C (E γ ) GCOMIaq::weight_iaq P MH (E γ ) GCOMInstChars::prob_no_multihit P SV (E γ ) GCOMInstChars::prob_no_selfveto P PSD (Ê 1 ) GCOMInstChars::psd_correction P A2 (Ê 2 ) GCOMInstChars::trans_D2 P V23 (Ê 2 ) GCOMInstChars::trans_V23 P D2 (Ê 2 ) GCOMInstChars::prob_D2inter P MS (ϕ geo , E γ ) GCOMInstChars::multi_scatter The P A1 (E γ ) is the transmission probability for photons for the material above D1, which is composed essentially of aluminium, and is computed using where µ Al (E γ ) is the energy-dependent interaction coefficient of aluminium in units of cm −1 that is interpolated using a log-log interpolation of the values given in Table G.2 and l above = 0.147 cm is the thickness of the material above D1. The P V1 (E γ ) is the transmission probability for photons for the first Veto dome and is computed using where µ Veto (E γ ) is the energy-dependent interaction coefficient for the Veto dome in units of cm −1 that is interpolated using a log-log interpolation of the values given in Table G.2 and l V1 = 1.721 cm is the thickness of the first Veto dome. P D1 (E γ ) is the interaction probability in D1 and is computed using where µ D1 (E γ ) is the energy-dependent D1 attenuation coefficient in units of cm −1 that is interpolated using a log-log interpolation of the values given in Table G.2 and l D1 = 8.5 cm is the thickness of the D1 modules. P C (E γ ) is the fraction of Compton scatter interactions among all possible photon interactions within D1 and is given by with the additional constraint of 0 ≤ P Compton (E γ ) ≤ 1. The P MH (E γ ) is the probability that there is no multi-hit. This probability is computed using a log-log interpolation of the values of Table G.2. P SV (E γ ) is the probability that the photon was not self-vetoed. This probability is computed using a linear interpolation of the values of Table G.2.
The P PSD (Ê 1 ) is the D1 energy-dependent PSD correction and is given by P PSD (Ê 1 ) = 1 − 1 1727.9 ×Ê 1 2.53 + 1 , (G.7) whereÊ 1 is in units of MeV. This correction applies to a standard PSD selection of 0-110. P A2 (Ê 2 ) gives the transmission probability of the aluminium below the D1 modules and is computed using P A2 (Ê 2 ) = e −µ Al (Ê 2 ) l T23 , (G.8) where µ Al (Ê 2 ) is the energy-dependent interaction coefficient for aluminium in units of cm −1 that is interpolated using a loglog interpolation of the values given in Table G.2 and l between = 0.574 cm is the thickness of the aluminium plate. P V23 (Ê 2 ) gives the transmission probability of the second and third veto domes that are situated between the D1 and D2 modules, and is computed using P V23 (Ê 2 ) = e −µ Veto (Ê 2 ) l V23 , (G.9) where µ Veto (Ê 2 ) is the energy-dependent interaction coefficient of the Veto domes in units of cm −1 that is interpolated using a log-log interpolation of the values given in Table G.2 and l V23 = 3.442 cm is the combined thickness of the second and third veto domes. P D2 (E γ ) gives the interaction probability in D2 and is computed using P D2 (E γ ) = 1 − e −µ D2 (Ê 2 ) l D2 , (G.10) where µ D2 (Ê 2 ) is the energy-dependent D2 attenuation coefficient in units of cm −1 that is interpolated using a log-log interpolation of the values given in Table G.2 and l D2 = 7.525 cm is the thickness of the D2 modules. The P MS (E γ ,Ê 2 ) is the probability that a photon that has interacted in D1 leaves the D1 module without any further interaction. This probability is computed using P MS (ϕ geo , E γ ) = azimuth angle φ of the module and is given by with R(r, φ) = r 2 D1 − r 2 sin 2 φ − r cos φ. (G.13) Figure G.1 illustrates the energy dependence of the efficiency factor P eff (ϕ geo , E γ ) and its components.
The spectral response R D1 (E 1 |Ê 1 ) is illustrated in the left panel of Fig. G.2 for a selected number of input energiesÊ 1 . The figure can be compared with Fig. 3c in Diehl et al. (1992), which presents the response functions as implemented in COMPASS at the time of the CGRO launch for comparable energies.
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New Neighbor Selection Method for Blockchain Network With Multiple Regions
One of the features of the Bitcoin network today is that its participating nodes are located in different regions of the world. Generally, inter-region data transmission is relatively time-consuming compared with intra-region data transmission. Thus, an important challenge for a blockchain network is shortening the block propagation time in order to reduce forks and maintain fairness, i.e., similar mining durations, for all miners. Previous methods have tried to increase the block propagation speed at the expense of imposing a higher burden on each node and a higher risk of eclipse attack. This paper proposes a new neighbor selection method that is based on only the neighbor’s regional information and assumes that a node has a relatively small number of neighbors located outside its region. By using this simple method, the distribution of blocks throughout the network becomes faster and the random neighbor-selection nature of the blockchain network is kept intact; thus, risk of an eclipse attack is low. This paper also proposes a block propagation model over multiple regions for exploring the theoretical reasons for the effectiveness of the proposed neighbor selection method. Finally, it examines a migration scenario to the proposed method from the default neighbor selection method implemented in Bitcoin nodes, and evaluates the migration effects in various sizes of networks.
The associate editor coordinating the review of this manuscript and approving it for publication was Barbara Guidi .
A feature of a blockchain network is its decentralized verification mechanism, wherein the participating nodes can be located in various regions of the globe. In addition, while new blockchain networks start with a smaller number of nodes (e.g., around 500), the Bitcoin network, for example, currently has grown to have more than 10,000 nodes. For such circumstances, this paper proposes a neighbor selection method that can speed up block propagation in blockchain networks of various sizes with multiple regions.
One of the important effects of speeding up block propagation is reduction of the fork rate. Fork models [18], [19] assume that the forking probability decreases as the block propagation time throughout the network is reduced. Another effect of faster block propagation is that the miner nodes in a blockchain network can be made to have similar mining start times. The miner who created the previous block has the earliest mining start time for the next block and the miner who is the latest in receiving the block in the network has the latest mining start time; thus, reducing the block propagation time is beneficial for maintaining similar mining durations, i.e., fairness, among miners.
In the default configuration, each Bitcoin node picks eight nodes randomly as its outbound neighbors [20], but this random selection may lead to inappropriate neighbors being chosen for fast block propagation. Relay networks like Falcon [21] and FABRE [22] can make a network much faster than a peer-to-peer network by using relay gateways. However, in terms of fairness to miners, the miners near the relay gateways have the advantage of spreading their newly mined blocks faster than miners farther away.
A neighbor selected from inside a region is defined as an inside neighbor and a neighbor selected from outside a region is defined as an outside neighbor. In [23], we proposed each node selects its neighbors randomly from inside and outside the region to which it belongs. Because the neighbor selection is random, it is resilient against eclipse attacks. In addition, the only restriction on neighbor selection is fewer number of outside neighbors for each node, so its computational burden is light. This paper extends this neighbor selection method. The following summarizes the work it presents.
• The number of outside neighbors for each node is set to one or two, which is much smaller than that of the total random neighbor selection. This feature of having fewer outside neighbors helps to shorten block propagation times not only in each region, but also in outside regions. To demonstrate this effect, this paper analyzes a block propagation wave model in detail; the theoretical equations based on this model prove that setting one or two outside neighbors to each node speeds up block propagation throughout the world.
• Simulation results show that the theoretically-proved best number of outside neighbors also gives the fastest block propagation speed in each network with 500-6500 nodes. In addition, the proposed method with fewer outside neighbors is superior to previous methods in terms of the block propagation speed in each network. We analyzed the superiority of the proposed method based on the simulation results and the theoretical equations proposed in this paper.
• This paper also describes a migration scenario from total random neighbor selection, which is the default method for Bitcoin nodes, to the proposed method. For this purpose, the ratio of the nodes using the proposed method is gradually increased from 0% to 100%. It is found that there is no network where the average block propagation speed is degraded because of adoption of the proposed method. Rather, even a small infusion of nodes implementing the proposed method significantly reduces the block propagation times.
The remainder of this paper is as follows. Section II shows related works of this study, Section III provides background information, while Section IV presents the proposed neighbor selection method, the new block propagation model with multiple regions, and its theoretical advantages over previous methods. Section V describes the evaluation results using a simulator and discusses the applicability of the proposed method to blockchain networks. Section VI concludes this paper.
II. RELATED WORKS
Many researchers have tried to shorten the block propagation time in a blockchain network by periodically replacing the neighbors of each node with nodes that have faster block propagation speeds (which is called the Aoki method) [24], wider bandwidth [25], or shorter physical distances [26], [27], [28]. These neighbor selection methods, however, have two drawbacks. First, they are vulnerable to eclipse attacks [29], [30], [31]. That is, if an attacker aims to attack a target node, the attack nodes will send blocks quickly, or the attacker will place its nodes near the target node. In these ways, the attacker can allocate its malicious nodes as the neighbors of the target node without difficulty. Second, if the block propagation speed or the bandwidth of a node is used for the neighbor selection criterion, each node has to monitor all of its neighbors all the time, so its computational burden of neighbor selection will increase.
Besides, neighbors can be chosen on the basis of their mining power and their node degree [32]. The cited paper recommended that each node should choose neighbors with larger mining power or with higher node degree, but information on these features is not exchanged in the current blockchain protocols. Furthermore, the information may not be accurate because some nodes in a blockchain network may have an incentive to send false information to get other nodes to connect to them.
There is another approach that uses a minimum spanning tree (MST) for the neighbor selection [33]. In that method, a leader node in a blockchain network creates an MST in the network by taking all the network edge costs into consideration. However, it takes a long time for a leader node to gather all the necessary information for creating an MST; it is also time-consuming to notify all the other nodes of the created MST especially when there are many nodes in the network. In addition, there is only one route between two nodes on an MST, meaning that a created block may not be delivered to some nodes if one of the edges of the MST has a problem. The method proposed in this paper, on the other hand, does not seek the optimal block propagation time by considering all the edge information in the world. Rather, it focuses on making the most effective use of the local IP addresses of the neighbor candidates for faster block propagation. Thus, in the following sections, we compare the proposed method with other neighbor selection methods that use local neighbor information rather than network-wide information.
Note that one of the important characteristics of a public blockchain network is the high level of anonymity of the participating nodes. There are previous studies on identifying users in the Bitcoin network by linking their IP addresses with their transactions [34]. However, it is difficult to identify the VOLUME 10, 2022 real IP addresses of the Bitcoin users if they use a VPN or TOR, i.e., the Onion routing project. In these cases, other Bitcoin nodes can recognize the disclosed VPN servers and TOR exit routers, but the real IP addresses of the users are concealed from them. In this paper, it is assumed that each node utilizes only the disclosed IP addresses in the blockchain network for selecting its neighbors, even if their real IP addresses are different from the disclosed ones. This is because these disclosed nodes are the closest gateways in the blockchain network for receiving or sending blocks to the users.
Note that some permissioned private blockchains are used within only one region [35], [36]. The proposed neighbor selection method is not for such private blockchains; it is rather for public permissionless blockchains in which the participating nodes are located in multiple regions, such as the Bitcoin and Ethereum networks.
III. RESEARCH BACKGROUND A. BLOCKCHAIN PROTOCOL
The blocks are distributed in the blockchain network and stored in a ledger that is possessed by all the blockchain nodes. Miners compete to find a nonce, i.e., an arbitrary number to be used just once in a cryptographic communication, that can create a satisfactory hash value for the new block by using the hash value of the previous block. In this way, a miner's ability to generate a new block is determined by the power of its computer, so this block generation process is called a proof of work (PoW) system. Any node in a blockchain network can become a miner, so we will use miners and nodes interchangeably in the rest of the paper.
After a new block is created, the miner broadcasts the block over the network through its outbound neighbor nodes. The nodes that receive the incoming block verify it and add it to their local copy of the blockchain. The block transmission protocol between two nodes is shown in Fig. 1. First, node_1 sends an inv message to its outbound neighbor node_2 after the verification process. If node_2 does not have the block, it sends a getdata message to node_1 to request the block. A block can be up to 1 MB, while an inv message has only a few bytes. Therefore, by using this protocol, unnecessary transmissions of blocks containing a large amount of data are avoided.
B. BLOCKCHAIN P2P NETWORK
Blockchain nodes transmit transactions/blocks to their outbound neighbors through the transmission control protocol (TCP)/ Internet protocol (IP). Each node has new and tried tables to store the IP addresses of blockchain nodes in the same network. The new table is initially set using information on a domain name system (DNS) server when the node first joins the network. Nodes update their new table periodically, reflecting recent neighbor information by using addr messages. The tried table maintains the IP addresses of neighbors to which the node had a connection.
In the default configuration [20], a Bitcoin node picks eight nodes from the tables randomly for setting its outbound neighbors, to which blocks or transactions are broadcast. This paper calls this outbound neighbor selection method total random selection. There are also inbound neighbors, which are selected in response to the neighbor addition requests by other nodes. One node can have at most 125 neighbors.
Its P2P nature, however, makes a blockchain network vulnerable to various malicious attacks, such as distributed denial of service (DDoS) attack, eclipse attack, and sybil attack [37]. Among them, eclipse attacks are sometimes facilitated by an inappropriate neighbor selection. Fig. 2 shows an example of an eclipse attack on a blockchain network. The target node is surrounded by seven malicious nodes out of eight outbound neighbors. These malicious nodes can manipulate the blocks received from the target node and send the manipulated blocks to the network through their outbound neighbor nodes. These malicious nodes can also stop propagating the block, so that the target node becomes isolated from the network. In these ways, an eclipse attack can ruin the target node in the blockchain network. In this example, outbound neighbors are used for the attack, but inbound neighbors can be also used, by their not sending important information, such as transactions and newly mined blocks, to the target nodes. The previous neighbor selection methods have narrow criteria for choosing neighbors for each node, such as block propagation speed, bandwidth, and physical distance between the neighbor and the node. In these cases, the selected neighbors can be easily replaced with malicious nodes for an eclipse attack. The TendrilStaller attack [38] is a kind of eclipse attack that replaces high-bandwidth mode neighbors of the target node with malicious nodes in the Bitcoin network. Fig. 3 shows the data structure and procedure each node uses to choose its outbound neighbors and inbound neighbors. In this example, the upper limit of inside neighbors is six, and the upper limit of outside neighbors for each node is two. As explained in Sect. III, each blockchain node downloads information on the IP addresses of the network from a DNS server and it stores this information in the new table. ICANN (Internet Corporation for Assigned Name and Numbers) [39] allocates IP addresses region by region. Thus, from the IP address of a node in the new table, blockchain node A can determine if it belongs to the same region as node A. In the figure Bitcoin nodes are grouped into six regions: North America, Europe, South America, Asia Pacific, Japan, and Australia. According to data provided by the SimBlock simulator, in 2019, North America had 33.16% of the total number of Bitcoin nodes, Europe 49.98%, South America 0.9%, Asia Pacific 11.77%, Japan 2.24 %, and Australia 1.95% [40]. Under these conditions, when outbound neighbors are randomly selected, at least half of them will be outside neighbors on average. In contrast, the proposed method determines a smaller upper limit of outside neighbors compared with the total random selection method. For instance, in Fig. 3, the upper limit of the outside neighbors is set to two, so one or two neighbors in the outbound neighbor list are outside node A's region.
IV. PROPOSED NEIGHBOR SELECTION METHOD A. DESCRIPTION OF METHOD AND ITS MERITS
In the proposed neighbor selection method, the condition on the inbound neighbors can optionally be set to be the same as that for the outbound neighbors. That is, the upper limit of inside neighbors and the upper limit of outside neighbors can be set for inbound neighbors in the same way as for outbound neighbors. In Fig. 3, if blockchain node A receives an inbound neighbor addition request from node B, it judges if node B is located in the same or an outside region from its IP address. Then, if node B is located in an outside region and if there is one or no outside neighbor in the inbound neighbor list, node B is added to the list. Moreover, if node B is located in the same region and if there are less than six inside neighbors in the inbound neighbor list, node B is added to the list.
In this way, except for the upper limit of inside/outside neighbors, the neighbors of each node are randomly selected.
The previous methods have narrow neighbor selection criteria that makes easy to attack the target node, such as faster block propagation, wider bandwidth, and shorter distance. Here, if the criterion is faster block propagation, an eclipse attacker can place its attack nodes next to the target node and send it only the most recently created blocks. If the criterion is wider bandwidth, the attack nodes can allocate a large bandwidth when sending blocks to the target node, and if the criterion is shorter distance, the attack nodes should be located as close as possible to the target node. By taking advantage of its neighbor selection criteria, the proposed method can avoid the risks of these eclipse attacks.
However, it is conceivable that an eclipse attacker could put its attack nodes in the same region as the targeted node and thereby exploit the feature that the proposed method sets each node to have more inside neighbors. The probability that all six inside neighbors of a target node using the proposed method are replaced with attack nodes can be calculated as P rep (6,6) where N A is the number of attack nodes and N R is the total number of nodes, except for the target node, in the region where the target node is located. P rep (6,6) in (1) is obtained because the target node happens to select an attack node as a neighbor six times in a row, and the probability of selecting (i + 1)th attack node is N A −i N R −i . In the same way, the probability that x out of six inside neighbors are replaced with attack nodes is calculated as .
(2) P rep (6,x) in (2) is obtained because the probability of selecting the (i + 1)th attack node in the (k + 1)th inside neighbor selection is N A −i N R −k , and the probability of selecting the (j+1)th non-attack node in the (k + 1)th inside neighbor selection is and there are 6 C x different combinations depending on when (from 1 st to 6 th inside neighbor selection) these x attack nodes are selected as neighbors by the target node.
Here, we define P rep(6,x>n) = 5 x=n P rep (6, x + 1) as the probability that the target node has more than n of its inside neighbors replaced with attack nodes, which is equivalent to saying that more than n out of 8 of its neighbors are replaced with attack nodes. N A = 100, P rep(6,x>2) is 0.21%; i.e., there is almost no chance that the target node has more than two of its neighbors replaced with attack nodes if the target node uses the proposed method. P rep (6,x>1) is about 3%, and P rep (6,x>0) is about 26.5%; thus, it is unlikely that even one node will be replaced with an attack node if N A ≤ 100. As N A increases to 500 or more, P rep (6,x>0) becomes more than 80%, so the target node is likely to have at least one attack node as its neighbor. However, P rep (6,x>3) remains relatively low, at about 34%, even when N A is 1000, i.e., half of the region nodes are attack nodes. That is to say, even if half of the region nodes are attack nodes, it is unlikely that half or more of the target node's neighbors are attack nodes.
On the other hand, if each node in a region has a narrow criterion like those above for selecting its six neighbors, and the attack nodes know the criterion, it is inevitable that the target node will have five or more of its neighbors replaced with the attack nodes, even if the number of attack nodes is less than 100 in the same scale of network with 2001 nodes. Thus, when the number of participating nodes is large, an eclipse attacker will find it much more difficult to attack a target node that uses the proposed neighbor selection method than a target node using the other neighbor selection methods.
Moreover, the inside/outside judgement for each node can be done without imposing a substantial computational burden. This is because, except for the neighbor selection based on the IP addresses of the neighbor candidates, there is no extra burden imposed on each node. In particular, if each node separates IP addresses of the nodes located in the same region from the other IP addresses in the new table, the burden of choosing eight outbound neighbors is the same as that of choosing eight outbound neighbors in the random selection method. This is because each node can randomly select six IP addresses from the same region and select two IP addresses from the other regions.
On the other hand, if each node has to acquire the neighbor candidates' computational power, distance, or available bandwidth, it has to allocate O(N ) memory space, where N is the number of nodes in the network, to evaluate its neighbor candidates. This is because every node in the network can become a neighbor of any other node; thus, all possible neighbor candidates should be evaluated using a determined criterion. In addition, each node has to update the ranking of the neighbor candidates whenever the criterion value in each neighbor candidate changes, of which the corresponding time complexity is O(log(N )) if each node uses a binary search tree for managing the rank of its neighbor candidates. In contrast, each node implementing the proposed method does not have to allocate this additional O(N ) memory space and does not have to use its CPU power for ranking its neighbor candidates. Table 1 shows the matrix of average transmission delays among the six regions in the Bitcoin network in 2019 according to the SimBlock simulator. Table 2 shows the matrix of ping transmission times between cities located in the six regions, as measured on an Internet site [41] in July, 2022. From Table 1, the Bitcoin inter-region transmission delays were on average 5.2 times larger than the inner-region transmission delays in 2019. From Table 2, the inter-region ping transmission times were on average 5.9 times longer than the inner-region ping transmission times. Generally, these ping times are proportional to the distance between the source and destination cities, but we also found that if the distances between source/destination pairs are similar, pairs within a region tend to have a shorter transmission time. For example, the distance between Los Angeles and New York is about 3936 km, while the distance between Dallas in the US and Bogota in Columbia is about 3909 km, which is a little shorter. The ping transmission time between Los Angeles and New York (73 ms) was, however, about 24% shorter than that between Bogota and Dallas. Therefore, we consider it is beneficial to reduce the number of outside neighbors for each node so that the inter-region transmissions are reduced.
To show the effectiveness of having fewer outside neighbors for each node, let us consider a network with five different regions (r_A ∼ r_E) as shown in Fig. 5. Here, each node has five outbound neighbors. In the figure, n 0 indicates the miner that has created the new block in r_A, and the block is sent to its outbound neighbors in the first wave. In the second wave, the nodes that received the block in the first wave send it to their outbound neighbors.
In Fig. 5(a), each node uses the total random selection method, so it has just one inside neighbor and four outside neighbors on average; i.e., at most four outside neighbors can receive the block directly from r_A. Here, r_E has not received the block directly from r_A by the third wave. Note that indirect block reception whereby some of the nodes in r_E receive the block from nodes via another region except for r_A is not considered in Fig. 4, as it would entail multiple inter-region transmissions taking much longer for the block to reach r_E. In addition, there is only one inside neighbor for each node in (a), so it takes a long time until all the nodes in r_A can receive the block if there are many nodes in r_A.
In Fig. 5(b), on the other hand, there is just one outside neighbor, so the maximum number of nodes (4 n−1 ) can receive the block in the nth wave. In the third wave, the number of outside nodes receiving the block directly from r_A is much larger than in (a). In addition, the maximum number of inside nodes receiving the block in r_A is 4 n in the nth wave, so the block propagations in each region are much faster than in (a).
As can be seen in Fig. 5, the proposed method offers faster block propagation that is independent of the block size. Thus, having fewer outside neighbors not only speeds up block propagation but also small-sized transactions over a network. We suppose, therefore, that the proposed neighbor selection method enhances the decentralized nature of a blockchain network by enabling all the nodes in the network to share the same transactions and blocks in a faster manner regardless of their regions. Fig. 6 shows the block propagation wave model in a region based on [43], starting from the miner labeled n 0 . In the figure, each blue arrow shows a block transmission between nodes and each red arrow shows an inv message sent to a node to which the block is not delivered because the node has already received the block. In the following, |W k | in is defined as the expected number of nodes that receive the block created by miner n 0 in the kth wave in the region. It is calculated as
2) ANALYSES USING BLOCK PROPAGATION MODEL WITH MULTIPLE REGIONS
where |W k(m) | add_i is the expected number of nodes receiving the block from the mth node in the kth wave in the region. In the (k − 1)th wave, |W k−1 | in nodes are expected to receive the block. These nodes send the block to their inside outbound neighbors in the kth wave in the region. Denoting the number of inside outbound neighbors as A, |W k(m) | add_i can be expressed as where p f k(m) is the block forwarding probability from the mth node in the kth wave in the region. For the mth node in the kth wave, p f k(m) for each inside neighbor is expressed as where N in is the number of nodes in the region. The value of the denominator in (5), N in − 1, indicates the number of nodes except for n 0 in the region. The value of the numerator indicates the expected number of nodes that have not received the block before the mth node in the kth wave sends it. k−1 j=0 |W j | in indicates the expected number of nodes having received the block by the (k − 1)th wave, and m−1 j=0 |W k(j) | add_i indicates the expected number of nodes having received the block in the kth wave before the mth node sends the block to its outbound neighbors. (5) indicates that as the number of waves and the number of nodes having sent the block become larger, the block forwarding probability in the region goes down. Now let us analyze the block propagation wave model with multiple regions in detail. Fig. 7 shows a block propagation wave model from one region to its outside regions. The block created by miner n 0 is propagated to the five outside regions. Except for R_1, in all the outside regions, at least one node has received the block by the third wave directly from the region where n 0 is located. As such, it is critical to send the block to at least one node in each region with fewer waves from n 0 without passing through multiple regions in order to propagate the block in a swift manner. As is discussed above, it is not helpful to count the nodes receiving the block that has passed through multiple regions because of the long transmission delay. |W k | out is the expected number of nodes in the outside regions that receive the block created by n 0 in the kth wave directly from the region where n 0 is located; it is calculated as where |W k(m) | add_o is the expected number of nodes receiving the block from the mth node in the kth wave outside the region. In the (k − 1)th wave, |W k−1 | in nodes are expected to receive the block inside the region, and these nodes send the block to their outside outbound neighbors in the kth wave. If the number of outside outbound neighbors is B, where p g k(m) is the block forwarding probability from the mth node in the kth wave outside the region. This is because for the mth block sender in the kth wave, there are B outside outbound neighbors. p g k(m) is calculated as where N out is the number of nodes outside the region. The numerator indicates the expected number of outside nodes that have not received the block before the mth node in the kth wave sends it. k−1 j=0 |W j | out indicates the expected number of outside nodes having received the block by the (k − 1)th wave, and m−1 j=0 |W k(j) | add_o indicates the expected number of outside nodes having received the block in the kth wave before the mth node sends the block to its outbound neighbors.
Like p f k(m) in (5), it is clear that p g k(m) decreases as the number of waves and the number of nodes having sent the block become larger. (4) indicate that having more inside outbound neighbors, i.e., a larger A, is beneficial for increasing the nodes receiving the block in the region for each wave, while (6) and (7) indicate that larger values of both inside and outside outbound neighbors, A and B, are beneficial for increasing the nodes receiving the block outside the region for each wave.
Equations (3) and
Therefore, we compared the block propagation times between networks with nodes having 32 outbound neighbors (A + B = 32) and networks with nodes having eight outbound neighbors (A + B = 8) [23]. We found that the networks with nodes having eight outbound neighbors had the shorter block propagation times, though theoretically the condition: A + B = 32 has more nodes receiving the block inside and outside the region in each wave. In other words, this result shows if each node has a large number of outbound neighbors, it takes longer for each node to forward a block to all of its neighbors; thus, the block propagation times throughout the network suffer from the individual nodes' broadcast overhead, as is discussed in [26]. On the other hand, a previous study [42] showed that in order to minimize the fork rate in a network, it is desirable that logN < A + B ≤ N /100 , where N is the total number of nodes in the network and denotes the ceiling function. It also showed that in a network with 500 nodes, A + B = 5 is most effective choice with which to minimize the fork rate. In this study, we examined networks having between 500 and 6500 nodes and found that, except for the network with 500 nodes, A + B = 8 satisfies the above condition. Under the condition A+B = 5, Fig. 5 compares the proposed method with the total random selection method. In addition, asking the individual nodes to change the number of their outbound neighbors depending on the number of network nodes is difficult in a public blockchain network. For these reasons, each node has eight outbound neighbors.
In the following, the expected number of nodes receiving the created block inside and outside the region is visualized on the basis of equations (3) -(8) in networks with multiple regions. The number of regions in a network and the number of nodes in each region are based on the Bitcoin network in 2019. Fig. 8 shows the theoretically calculated ratio of nodes that are expected to receive a block inside the region where the block is created. The networks have between 500 and 6500 nodes. The expected number of nodes receiving the block in the kth wave, |W k | in , is calculated using (3), while N in in (5) is set to half the number of the network nodes, as Europe had 49.98% nodes in the Bitcoin network in 2019. At that time, Europe likely had the longest block propagation times in the Bitcoin network, thus it is important to find the necessary number of the block propagation waves in the region.
From Fig. 8, it is clear that A = 7 and A = 6 have an advantage over the other values. For these choices of number of inside outbound neighbors, block propagation almost finishes by the 4th wave in the network with 500 nodes and by the 5th wave in the other networks. In the last wave, the gap between A = 7 and A = 6 is less than 4.6% on average, so there are many cases in which these values give the same number of waves for a block to propagate in a region. Fig. 9 shows the theoretical number of outside nodes that are expected to receive a block created inside a region by the third wave in each network. The expected number of outside nodes receiving the block in the kth wave, |W k | out , is calculated using (6). N in is set to 1/6th of the total network nodes in each network, so N out in (8) is 5/6th of the total network nodes. When the number of waves, k, is 5, |W k | out grows proportionally larger as A is increased. However, as long as k < 4, A = 5, and hence B = 3, is the best setting with which to increase the number of the outside nodes receiving the block by the third wave.
As discussed above, an important factor in reducing the block propagation time throughout a network is for all of its regions to receive at least one block from the originating region in fewer waves. The probability whereby the kth block-receiving outside node does not belong to the target region p k is calculated as Here, N targetR is the number of nodes located in the target region. Among the N out outside nodes, there are (N out −k −1) nodes that have not received the block. Moreover, nodes located in the target region should not be chosen as the kth node. The probability of the k outside nodes that have received the block and do not belong to the target region, p k_out_targetR , VOLUME 10, 2022 is calculated as We obtain this probability because the non-target-region node selection with probability p j has to be continued until the kth node selection. For each network in Fig. 9 N targetR is set as N targetR = 0.009N , because it corresponds to the lowest node ratio in the Bitcoin network in 2019, i.e., that of the South America region. In other words, South America is considered to be the bottleneck region for propagating a block throughout the world. Fig. 10 shows the theoretical values of p 3_out_targetR in the seven networks.
The results in Fig. 9 and Fig. 10 show that, in each network, all of the outside regions can receive the created block from its region of origin within the first three or four waves if A is set to 4 or more. This is because the theoretical number of nodes receiving the block outside the region by the fourth wave exceeds 200 if A > 3, and p 4_out_targetR is nearly 0% when the number of outside nodes reaches 200. Therefore, delivering the block propagation to all the outside regions by the third wave in each network is important for shortening the propagation time.
When A = 7, and hence B = 1, many fewer outside nodes are expected to receive the block by the third wave than when 2 < A < 7, even though A = 7 is the most efficient choice in terms of the block propagation within a region (Fig. 8). In the case of the network with 6500 nodes in Fig. 9(g), the expected number of outside nodes receiving the block by the third wave is 55.5 when A = 7, and p 3_out_targetR is about 41% (Fig. 10), meaning there is a 41% chance that the block will not have propagated to all the regions. On the other hand, the expected number of outside nodes receiving the block is 91.3 when A = 5 and p 3_out_targetR is about 17%. Thus, the probability of a block propagating to all the regions by the third wave is much larger than in the case with A = 7. This difference is large in the networks with many nodes. Even in the network with 1500 nodes, the expected number of outside nodes is 50.8 with A = 7 (p 3_out_targetR is about 20%), whereas it is 85.8 with A = 5 (p 3_out_targetR is about 2%).
In the network with 500 nodes, however, the expected number of outside nodes is 40.8 with A = 7, and p 3_out_targetR is about 8%. Thus, the probability of the block being delivered to all the regions is about 92%. In other words, A = 7 is appropriate for a relatively smaller network with around 500 nodes considering its higher effectiveness for the block propagation in a region as demonstrated in Fig. 8.
On average, p 3_out_targetR is only 2.8% larger when A = 6 compared with A = 5. This small disadvantage is outweighed by the large gap in terms of the block receiving ratio inside a region for each wave, as shown in Fig. 8. For example, after the fourth wave in each network, the average expected block receiving ratio inside the region is 19% higher with A = 6 than with A = 5.
In summary, this theoretical analysis shows that A = 7 (B = 1) and A = 6 (B = 2) are appropriate outbound neighbor selection parameters for a faster block propagation in a network with multiple regions. In the case of a small network with around 500 nodes, A = 7 is more appropriate than A = 6, whereas in a larger network with 1500 or more nodes, A = 6 is the most appropriate choice.
In addition, our assumption of targeting the blocks coming directly from the region in which they were created is appropriate. This is because a block directly propagates to all the regions in the first four waves, whereas a block coming via multiple regions generally comes later than the fifth wave, because inter-region block transmission takes 5.2 times longer than inner-region block transmission, as shown in Table 1.
V. EVALUATION
We evaluated our neighbor selection method as follows. First, we determined the optimal numbers of outbound inside and outside neighbors for each network by using the SimBlock simulator. Second, we compared our method with the total random selection method and the Aoki method [24] in terms of block propagation time throughout the network using the simulator. Third, we examined a migration scenario wherein the ratio of nodes using the proposed neighbor selection method to those using the total random selection method is gradually increased.
A. SIMULATION ENVIRONMENT
SimBlock can be used to simulate multi-region blockchain networks under the same conditions as Bitcoin in 2015 or in 2019. We chose the 2019 Bitcoin network and varied the number of nodes between 500 and 6500. In particular, the nodes were randomly located in one of the six regions with the same probability as in the 2019 network, and the transmission delays were as in Table 1. PoW was used as the consensus algorithm, and each node was set to be able to be a miner, but the computer power for mining on each node was set randomly. The number of outbound neighbors was set to 8, the block size was set to 535 KB or 1MB, and the block creation interval was set to 10 minutes.
B. SIMULATION OF OPTIMAL NUMBER OF INSIDE/OUTSIDE NEIGHBORS FOR EACH NODE
The optimal numbers of outbound inside neighbors, A, and outside neighbors, B, for each node in various sizes of network were theoretically analyzed under the condition of eight outbound neighbors examined in the previous section. Here, we evaluated the parameters of the proposed methods by using SimBlock. The inbound option, which determines the upper limit of inside/outside inbound neighbors, was not used in the evaluation, and the maximum number of inbound neighbors for each node was set to 30. Fig. 11 shows the block propagation times of the proposed method with different values of A and B. The main-chain height was set to 200, so one simulation ended after the 201 st block of the main chain was delivered throughout the network. The block size was set to 535KB in this subsection. Each plot in the figure indicates the average block propagation time to all the nodes in the network. That is, if a mined block failed to be distributed to a node in the network, the block propagation time was not included in the average value. To make the values trustworthy, we ran the simulation three times under the same conditions and took the average of the three runs.
As in the previous section, A = 7 turned out to be the most effective for the network with 500 nodes, while A = 6 was most effective for the networks with 1500 or more nodes. It is an important factor to reduce the number of block propagation waves for delivering the block to all the outside regions. In the network with 500 nodes, it was highly likely for the block to reach all the outside regions by the third wave when A = 7. However, A = 7 ended up having the longest block propagation time in the networks with 3500 or more nodes in Fig. 11, because the fourth wave was more necessary for these networks with A = 7.
Instead, A = 6 had the shortest block propagation time for the networks with 1500 or more nodes. It had a high probability to deliver a block to all the outside regions by the third wave. Even though A = 5 is theoretically a bit faster in the sense of propagating the block to the outside regions by the third wave as shown in Fig. 9, this small advantage was surpassed by the much faster block propagation speed in each region with A = 6 in Fig. 11.
C. BLOCK PROPAGATION TIMES OF PREVIOUS AND PROPOSED METHODS
We compared the block propagation times of the proposed method with those of the total random selection method and the Aoki method. To evaluate the block size effects, we changed the block size between 535KB and 1MB. The inbound option, in which the upper limit of the inbound neighbors is set to 8 as shown in Fig. 3, was also evaluated. Except for the proposed method with the inbound option, the VOLUME 10, 2022 maximum number of inbound neighbors for each node was set to 30. For the proposed method, B = 1 outside neighbor was set for the network with 500 nodes and B = 2 was set for the other networks; these values were theoretically and quantitatively proved to be efficient in the preceding sections.
1) AOKI METHOD
The Aoki method aims to minimize the block propagation time in a multi-region environment. It chooses an outbound neighbor for each node on the basis of the block propagation time through that neighbor. Each block has a time stamp in which the block creation time is stored. Thus, if a node receives a block from an inbound neighbor (M ), the node can calculate the block propagation time starting from the block creation (T block ) and ending with the inv message received time (T inv ). The node considers the propagation time as the score of the neighbor M (SCORE M ): If the node has already received inv messages from M , SCORE M is defined as where P is a parameter in the range [0,1]. Neighbor candidates having a smaller SCORE M are chosen as the outbound neighbors. Aoki and Shudo [24] found that P = 0.3 has the shortest block propagation time. In addition, to prevent eclipse attacks from happening, at least one neighbor should be chosen randomly for each node. Under this restriction, it is claimed to be best to replace 7 out of 8 outbound neighbors in accordance with the scores defined in (12). The outbound neighbor renewal interval was set to 10 received blocks for each node. After referring to the evaluation results in [24], we set P = 0.3 and chose 7 neighbors on the basis of (12) in 10 received blocks for each node. The Aoki method is optimized for high block propagation speed at the expense of a heavy burden on each node and vulnerability to eclipse attacks. The results of the following experiments show that the proposed method can propagate a block throughout a network faster than the Aoki method can.
2) BLOCK PROPAGATION TIME Fig. 12 shows the 535KB block propagation times for each method under the condition A + B = 8. In this figure, ''proposed (outbound)'' indicates the proposed method without the inbound option, whereas ''proposed (out/inbound)'' indicates the proposed method with the inbound option. The results clearly show that the proposed method is far superior to the total random selection method and the Aoki method for all network conditions. Each node in the total random selection method has five or more outside neighbors on average, so it is equivalent to A ≤ 3 and B ≥ 5. Under this condition, block propagation in and outside the region becomes slower, as shown in Figs 8 -10. The Aoki method updates the outbound neighbors by prioritizing the propagation speed every ten block receipts, so the propagation times to most nodes in a network are considered to be very close to the optimal values. Looking at Fig. 12, however, it is clear that the Aoki method prevents some nodes from receiving blocks quickly. Equation (12) can be used to explain the reason. (12) determines the new outbound neighbors of each node every 10th block arrival, and a lowscoring node at that point tends to be selected as a new neighbor by many nodes as their outbound neighbor. Other nodes, however, may suffer in this situation because their inbound neighbors are reduced by the high concentration of connections to the low-scoring node, and as a result, they may receive blocks more slowly.
In Fig. 12, the inbound option has a clear effect on all the networks, and the upper limit of the inbound neighbors helps to prevent some nodes from having much fewer inbound neighbors compared with the other nodes. If there are some nodes with much fewer inbound neighbors, there are more miners who cannot propagate their newly mined blocks to the nodes within a small number of waves, and this lengthens the block propagation time.
This phenomenon can be explained in terms of the block propagation speed in each region. The block propagation probability, p f k(m) , in the block-created region with the inbound option is in which N in_full indicates the number of inside nodes that have received the block (before the mth node in the kth wave sends it) up to the maximum limit of inside nodes, which is determined to be 7 in a network with 500 nodes or 6 with 1500 or more nodes. The number of these inside nodes is subtracted in the denominator of (13), because there is no chance for them to receive the block from inside the region because of the limitation determined by the inbound option. Therefore, p f k(m) with the inbound option becomes larger than that in (5), which is assumed to have no inbound node restriction on each node. In particular, the gap between p f k(m) in (13) and in (5) widens as k grows because N in_full increases with k.
This theory is also applicable to outside the block-created region. Here, the block propagation probability, p g k(m) , outside the block-created region with the inbound option is , (14) in which N out_full indicates the number of outside nodes that have received the block up to the maximum limit of outside nodes, which is determined to be 1 in a network with 500 nodes or 2 with 1500 or more nodes. The number of these outside nodes is subtracted in the denominator of (14), because there is no chance for these nodes to receive the block from outside the region due to the limitation determined by the inbound option. Therefore, p g k(m) with the inbound option becomes larger than that in (8), which is assumed to have no inbound node restriction on each node. In addition, the gap between p g k(m) in (14) and in (8) widens as k grows because N out_full increases with k. In this way, even from a theoretical point view, it is beneficial to take the inbound option in the proposed method. Fig. 13 shows the 1MB block propagation times for each method, with which all the conditions except for the block size were set to those in Fig. 12. Proposed (outbound) and proposed (out/inbound) had shorter block propagation times than the other two methods in every network condition, though the gap between proposed (outbound) and the Aoki method narrowed when the number of network nodes was increased to 4500 or more, compared with Fig. 12. We found that, for a block size of 1MB, choosing the neighbors with smaller block propagation times in the Aoki method was more effective, because the block propagation times between two different nodes in a network were increased due to the larger block size. In Fig. 13, however, the inbound option had a clear effect on all the networks like in Fig. 12. This is due to the higher block forwarding probabilities in and outside the blockcreated region, as shown in (13) and (14). Because of these enhanced block forwarding probabilities, the number of block propagation waves needed to reach all the nodes in a network was reduced, and this effect became clearer when a 1MB block was used. We analyze this is because each wave took more time due to the larger block size. The effect of the inbound option became clearer especially when the number of nodes in the network was large (Fig. 13). This phenomenon can be explained by comparing (13) with (5) and comparing (14) with (8). In (13), the denominator, N in −1−N in_full , becomes larger as N in increases. Thus, p f k(m) grows as N in_full approaches N in −1. Without the inbound option, the denominator is fixed to N in −1, as shown in (5); thus, the gap between p f k(m) in (5) and (13) becomes larger as N in grows. This theory is also applicable to p g k(m) in (8) and (14): the gap between p g k(m) in (8) and (14) becomes larger as N out grows.
D. SCENARIO OF MIGRATION TO PROPOSED NEIGHBOR SELECTION METHOD
Even though the theoretical analyses and simulation results presented above have proven the superiority of the proposed method to the previous methods, we cannot force every node in the blockchain to adopt it. Therefore, in this subsection we propose a migration scenario from a network with nodes using the total random selection method, which is the default setting for a Bitcoin node, to one with nodes using the proposed method with the inbound option. During the migration phase, there is a hybrid network situation with two different types of node, each adopting its own neighbor selection method. We evaluated this situation by changing the ratio of nodes implementing our method.
The networks had 500, 3500, or 6500 nodes and block size was set to 535KB; the rest of the evaluation conditions were the same as those mentioned in subsections A and B above. Fig. 14 shows the average block propagation times versus ratio of the nodes adopting the proposed method in each network. The plots are the average values of three evaluations. It can be seen that even with 10% of the nodes adopting the proposed method, the average propagation time was reduced by 3.3%; with 90% adoption, the reduction rate was as much as 26.9%, even higher than when all nodes use the proposed method.
The largest reduction rate with 90% adoption of the proposed method was for the network with 500 nodes. In this case, the reduction rate was 33.3%, which was about 1% higher than when all the nodes use the proposed method.
This phenomenon can be explained using Figs. 9 and 10. In Fig. 9(a), the expected number of outside nodes receiving the block by the third wave is 40.8 when A = 7, and this value means that the ratio for South America to receive the block is about 92% from the data in Fig. 10. However, if there are a small number of nodes that have more outside neighbors, the expected number of outside nodes by the third wave can be increased to more than 41. We suppose that this is why South America's block receiving rate by the third wave was increased, and the average block propagation time was reduced. Of course, we have to consider the negative effect on the block propagation time in each region because of the 10% of nodes with the total random selection method, but from this result, it is clear that this negative effect was offset by the dominant 90% of nodes adopting the proposed method.
Another interesting phenomenon we observe in this evaluation is that, in the network with 500 nodes, there is a strong tendency for a miner adopting the proposed method to propagate the blocks it creates faster to all the other nodes in the network. This advantage becomes apparent when the ratio of the nodes adopting the proposed method is lower, such as less than 50%. This phenomenon is illustrated in Fig. 15, which plots average propagation time versus adoption rate of the proposed method: miners with the proposed method propagated the created block faster than miners with the total random selection method. When 10% and 20% of the miners used the proposed method; their propagation speeds were about 10% faster than those of the miners using the total random selection method. We performed this analysis on a small network with 500 nodes, so setting the miner's number of inside neighbors to a large number, i.e. 7, was beneficial for propagating the block inside the region faster. This is especially important for a network with a smaller rate of nodes adopting the proposed method because many nodes in each region have few inside neighbors and they have thus less power for propagating the block in the region at a fast speed.
From this evaluation, we can say that gradually infusing the proposed method into a network does not have any harmful effect and it leads to a significant improvement in block propagation speed even when only 10% of the nodes adopt it. In addition, this beneficial effect should encourage new nodes participating in a small blockchain network to use the proposed method, because the blocks created by the new nodes will be propagated to all the other nodes faster.
VI. CONCLUSION
We proposed a new neighbor selection method for a blockchain network that enhances the block propagation speed throughout the network and fairness among miners. In addition, because of its random neighbor selection, it is robust against eclipse attacks, and the burden incurred by the neighbor selection is light because it uses only the IP addresses of the neighbor candidates. We also proposed a block propagation wave model with multiple regions that clarifies the optimal numbers of inside/outside neighbors for propagating a block throughout a network in relation to the number of nodes in that network.
In the simulation experiment, we showed the theoretically optimal number of outside neighbors for each node also gave the shortest block propagation time in each network with 500-6500 nodes. We also demonstrated the applicability of the proposed method to blockchain networks by showing that its block propagation times are much shorter than those of the total random selection method and the Aoki method in networks with 500-6500 nodes. The inbound option was also evaluated and it was shown to be effective at shortening the block propagation times. Equations (3) -(8), (13), and (14) clarified the superiority of the proposed method and the inbound option in a theoretical manner.
We also examined a scenario depicting migration from the total random neighbor selection method to the proposed method. We found that the block propagation speed significantly increases even when a small proportion of nodes in the blockchain network adopt our method. We also found that a miner adopting the proposed method will have an advantage in propagating blocks it creates faster throughout a small network with 500 nodes.
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Partial replacement of portland cement by bamboo ashes
ABSTRACT Partial replacement of Portland cement by industrial waste or materials of natural origin can improve the mechanical strength of concrete and mortar and reduce production cost. In this context, ash from burning bamboo appears as a potential material for use, as it is natural with a renewable source and fast growth, which presents a higher concentration of silica in the outer walls of the stalks. Therefore, the objective of this work is to evaluate the use of bamboo stalk ash (Bambusa Vulgaris) as a partial replacement for Portland cement. For this purpose, bamboo ash was produced at three calcination temperatures (500ºC, 600ºC and 700ºC). The ashes were not characterized as pozzolans based on their chemical composition, however the ash produced at 600ºC obtained a performance index higher than that established by the Standard. The hydration of cement partially replaced by this ash was evaluated, in proportions of 0%, 6%, 10% and 14%, in relation to its mass. Mortars with the same replacement proportions were evaluated in the fresh state and hardened. The consistency in the fresh state remained constant at 227 mm, while the compressive strength, in the hardened state, increased by 15% with the addition of bamboo stem ash.
INTRODUCTION
More than fifty years ago, researchers already found that the world's most widely used building material is concrete. This is produced from a mixture of Portland cement, aggregates, and water. At that time, 63 million tons of cement were converted into 500 million tons of concrete per year, and its consumption, in mass, was already five times greater than that of steel. The success of this material is mainly due to its excellent water resistance, easy moldability in different shapes, relatively low cost, and availability in the market [1].
The search for the coexistence of technological development with environmental preservation is a significant challenge faced by the cement industry. Besides the high energy consumption and CO 2 emissions, there is the problem of exploitation of natural raw materials used, mainly limestone and clay. Moreover, the calcination of these raw materials in the manufacture of cement clinker is a significant carbon dioxide gas released into the atmosphere. According to Moir [2], a way to minimize all this is to partially replace clinker with industrial waste or materials of natural origin with a renewable source. Besides advantages for the environment, this possibility of replacement can improve specific properties of concrete and reduce its cost.
Bamboo is a vegetal material with the potential to use its ashes as a partial replacement for cement. It is a natural resource that renews itself in a shorter time interval [3], and Brazil has the most considerable diversity and highest index of endemic forests in Latin America [3]. However, in the country, its use is still quite early, and, except for the production of paper, it is destined for traditional applications, such as handicrafts, fishing rods, and furniture, among others [3].
Given the environmental problems generated in cement manufacture and the incipient destination of bamboo plantations in Brazil, this work aims to evaluate the potential use of bamboo thatch ash as a partial replacement for Portland cement. This proposal has several advantages, linked to the incorporation of mineral admixtures in Portland cement and the use of bamboo as a raw material.
Mineral admixtures are finely ground materials added to cement, usually of natural origin, and can be used in their original form or after treatment. Over time, various industrial wastes have become the primary sources of additions. The incorporation of mineral admixtures into the composition of Portland cement has many environmental, economic and technological benefits.
The main environmental benefit is the partial replacement of Portland clinker by the addition. The types of cement composed of mineral additions have lower costs since they replace a high-cost manufacturing material (clinker) with lower-cost ones. At the technological level, such additions also positively affect the technological performance of cement, such as increased mechanical strength and greater durability.
The use of bamboo as a raw material is justified once it is a natural material, with a renewable source and fast growth. Its cultivation does not require particular soil. In bamboo, silica is concentrated mainly in the outermost parts of the canes. Fast-growing plants tend to have a more significant amount of silica than slower-growing ones.
Silica stands out among the inorganic components of bamboo. After the calcination of the bamboo stalks, the organic matter is eliminated, resulting in ash-rich in silica. Siliceous materials, among other factors, have the potential to be used as a pozzolanic mineral admixture. The silica in the pozzolans reacts with the calcium hydroxide produced in the Portland cement hydration and produces more resistant materials, bringing technical benefits. Even though bamboo thatch ash does not present significant reactivity when incorporated into Portland cement, it can produce a physical effect due to the densification of the matrix by filling the pores of the mixture with fine inert material.
Incorporating bamboo stalks ash into Portland cement brings many benefits to the environment. First, it reduces the number of greenhouse gases and exploitation of raw materials generated in the manufacture of Portland clinker by incorporating a natural origin with a source of rapid renewal (bamboo). Second, it can positively affect the material's performance, such as greater mechanical strength. Finally, it would reduce the cost of the product.
Bamboo belongs to the subfamily Bambusoideae of the family Poaceae and is divided into three groups: Arundinarieae, Bambuseae, and Olyreae [4]. Most bamboo species thrive in temperatures between 8ºC and 36ºC and are naturally distributed across all continents except the European. Asia has the most native species, about 62%, followed by the Americas (34%), Africa (4%), and Oceania (4%) [5]. The worldwide geographical distribution of bamboos can be seen in Figure 1.
In Brazil, there are 258 species of bamboos distributed in two tribes, Bambuseae and Olyreae, and 35 genera, 12 genera and 175 species are endemic. The tribe Bambuseae has larger, lignified and woody stems and contains 18 genera and 165 species, while the tribe Olyreae has smaller herbaceous bamboos divided into 17 genera and 93 species [7,10]. The most common species in the country are Bambusa vulgaris vittata (imperial bamboo), Bambusa vulgaris (green bamboo), Bambusa tuldoides (common bamboo), Dendrocalamus giganteus (giant bamboo or bamboo-balde) and some species of the genus Phyllostachys. Being of Asian origin, these species were brought by the first immigrants and were disseminated throughout the country, due to their good adaptation to the Brazilian tropical climate [8].
Although Brazil is the country with the greatest diversity of woody bamboo species in the Americas, with 81% of the genera [7], its exploitation is still small compared to its versatility. Countries like Colombia and Ecuador use bamboo as a popular construction material and in agro-industries, enhancing rural development.
Although the exploitation of bamboo in Brazil is subject to Law No. 12,484 of September 8, 2011 -which encourages its cultivation and sustainable management -there is still a lack of greater technological input for the production of stalks with standards for commercialization. he National Policy of Incentive to the Sustainable Management and Cultivation of Bamboo (PNMCB) recognizes a need for much investment in the production chain of bamboo so that it is valued as an efficient agro-silvo-cultural product that serves as a source of income for family farming [7].
Although bamboo is considered one of the main non-timber forest products, it is a suitable alternative to wood in activities that seek sustainable development since it can rapidly sequester atmospheric carbon, besides having excellent physical and mechanical characteristics [9]. According to MOGNON et al. [9], the most extensive carbon stock in bamboos is concentrated in the stems, followed by branches and leaves. This amount also varies according to the species.
The use of bamboo as a raw material has many advantages. The first one would be its fast growth since it takes much less time than any other tree to achieve its growth, about 4 to 5 years. It is also easy to plant, harvest, and maintain since there is no need to use pesticides and fertilizers when planting it, harvesting is done manually, and transportation is favored because it is lighter than wood. Another advantage is the versatility of bamboo, which has several applications, such as fuel, in paper manufacturing, civil construction, and the food and textile sectors. By replacing wood, bamboo also reduces the environmental impact caused by deforestation, besides contributing to the reduction of soil [10].
MATERIALS AND METHODS
This study was divided into four stages. First, it was the production of bamboo thatch ash (CCB) from calcination at three different temperatures. Secondly, the ashes' characterization to verify their mineralogical, physical, chemical, and pozzolanic properties were performed. Analysis was also made to determine the most suitable bamboo calcination temperature. The third step consisted of analyzing the hydration of the cement partially replaced by the bamboo thatch ash from the production of pastes. The fourth step consisted of producing mortars with the partial replacement of cement with bamboo ash. The mortars were evaluated in the fresh and hardened states. Table 1 describes the steps and methods applied in the experimental program. The performance index with Portland cement was determined at 28 days. The test used Portland cement composed of filler (called CP II-F) strength class 32 MPa, as prescribed by NBR 5752 [11]. A Brazilian high initial strength Portland cement (CP V-ARI) was also used in this study. CP V-ARI is the purest cement (higher amount of clinker) among those available in Brazil, enabling more accurate analysis regarding the behavior of bamboo stem ash used as a partial replacement for cement. The cement's gravity weight was determined according to the NBR 16605 [12] (Table 2).
Fine aggregate
The fine aggregate used in the research was quartz sand from riverbeds near the metropolitan region of Belém.
The aggregate underwent a previous drying process in an oven so that its humidity did not interfere with the water/cement ratio of the mortars. The characterization of the sand used is shown in Table 3, so that the gravity weight was determined according to NBR NM 52 [13], the unit mass and the voids index according to NBR NM 45 [14], and the fineness module according to NBR 7211 [15].
According to the particle size curve (Figure 2) obtained according to NBR 7211 [15], the sand used in the research fits in the inferior usable zone, being characterized as a very fine material.
Mixing water
To produce the cementitious matrices, tap water from the Cidade Universitária Professor José da Silveira Netto (UFPA's campus in Belém) was supplied by its water treatment station.
Bamboo stalk ash (CCB)
The bamboo used for the production of ash belongs to the Bambusa Vulgaris species from the metropolitan region of Belém. The stems of this material were supplied by the Empresa Brasileira de Pesquisa Agropecuária -EMBRAPA -Amazônia Oriental and cut into approximately 1 meter long (Figure 3a) due to the easiness of transportation. Before producing the ash, the stalks were cut into smaller pieces and later submitted to a knife and hammer mill (Extraction Center of the Chemistry College of UFPA). It was removed with a sawdust aspect (Figure 3b). Due to the grinding, the smaller the size of the grains, the greater the specific surface of the material, enabling an increase in chemical reactions and giving greater compactness to the mixture.
The ground bamboo was transformed into ash from the calcination process, carried out in a microprocessed muffle furnace (Figure 4) with 3720w of power and 220V (Materials Plant of the Chemical Engineering College of UFPA). Several authors have already characterized the ashes from bamboo leaves [24][25][26][27][28]. However, the characterization of ashes from bamboo stalks is still incipient; only the work developed by RODIER et al. [21] is a reference. The bamboo stalks from these cited researchs were calcined in three temperatures 500ºC, 600ºC and 700ºC. To correlate the calcination temperature at which the bamboo thatch ash was produced and its respective physical and mineralogical characteristics. The ashes were named according to the temperature at which they were produced, as shown in Table 4.
The ground bamboo remained at a constant temperature for two hours. Four porcelain containers were used so that the material was deposited inside the muffle, avoiding contamination. The cooling was slow inside the muffle, which was opened 24 hours after it was turned off.
Characterization of bamboo stalk ash
CCB500, CCB600 and CCB700 were submitted to mineralogical, physical, chemical and pozzolanic analyses.
These analyses allowed determining the potential use of CCB in Portland cement matrices.
Grinding
After the calcination process, the ashes of the bamboo thatch were submitted to grinding in a horizontal ball mill (Figure 5) in the Civil Engineering Laboratory of UFPA -LEMAC. The proportion of 5 kg of balls for 1 kg of ash was used, being 2/3 small balls and 1/3 large balls, according to the methodology used by POUEY [22]. The ashes were ground at 1, 2, 4, 6 and 8 hours and later submitted to laser granulometry analysis.
Particle size analysis
The methodology of laser particle size analysis consisted of 1 g of material in 7 ml of distilled water, which was pipetted into a dispersion unit that also uses water as a suspension liquid. A laser particle analyzer model Analysette 22 Micro-Tec Plus from Fritsch GmbH, with a measuring range of 0.08 to 2000 µm, was used to generate the particle size curves of the ash. This analysis was performed in the Laboratory of Mineralogy, Geochemistry and Applications of the Institute of Geosciences of UFPA.
Determination of gravity weight
The determination of the gravity weight was performed at LEMAC, according to NBR 16605 [12]. The test was performed twice in each of the samples produced with different calcination temperatures.
X-ray diffraction
The analysis was performed in the Research Laboratory of the Physics School of UFPA, in a BRUKER model D8 ADVANCE diffractometer. The High Score Plus software was used to identify minerals in the diffractogram peaks. The conditions for the analysis were: i) radiation: Cu Kα; ii) voltage: 40 kV; iii) current: 40 mA; iv) scanning with a 0.02º 2θ step; v) time per step: 0.3s; vi) scanning interval: 5 to 60º (2θ); vii) divergent slit: 0.6 mm; viii) Soller slit: 2.5º; ix) filter: Kβ of Ni.
X-ray fluorescence
The chemical analysis of the CCB was obtained from the x-ray fluorescence (FRX) assay in a RIX 2000 spectrometer of the RIGAKU brand, performed in the Geochemical Laboratory of the Federal University of Rio Grande do Sul (UFRGS), with Rh x-ray tube. In this research, quantitative analysis was carried out using the molten sample technique, with a calibration curve from rock standards and artificial standards for the majority of element found. The presence of volatiles was evaluated through gravimetric techniques. The performance index with Portland cement was verified as prescribed in NBR 5752 [11]. This method evaluates the pozzolanicity of the materials from the simple compression test in mortars. Four mortars were prepared and mixed in a mechanical mixer, according to NBR 7215 [23], and described in Table 5. The use of admixture was dispensed.
After mixing, the mortars were submitted to consistency testing (Figure 6a) according to Annex B of the same standard. Four 50 x 100 mm cylindrical specimens were molded for each mortar (Figure 6b). After 28 days, the specimens were subjected to compression testing (Figure 7), according to NBR 7215 [23], in an EMIC DL200 testing machine, with a loading speed of 0.25 MPa/s. The performance index with Portland cement at 28 days was calculated for each of the mortars. For the material tested to be considered pozzolanic, this index should be greater than or equal to 90%, according to the physical requirements of NBR 12653 [24].
Production of the pastes
The pastes were produced with Portland cement CP V-ARI and CCB at varying levels, according to Table 6. The water/binder ratio was 0.40 for all samples. The replacement levels were based on CP II-Z type cement, according to NBR 11578 [25]. On the date of the analyses, the samples (Figure 8a) were fragmented and ground (Figure 8b). The resulting powder was passed through a sieve of 0.075 mm and the passing material was stored and destined for the tests (Figure 8c).
Pastes mineralogy
The produced pastes were submitted to XRD analysis at ages 28 and 56 days. The samples can be seen in Figure 9. The analysis was performed in the same equipment and conditions of the analyses in item 3.1.4.
Thermogravimetry of the hydrated pastes
The paste samples described above were analyzed at 56 days. The mass losses observed in the TG results occurred due to the dehydration of the hydration products of Portland cement. The test was performed in the Laboratory of Amazonian Oils, in the Guamá Science and Technology Park, and a Shimadzu thermobalance was used, with the following test conditions: i) alumina crucible; ii) temperature range: 20-1000ºC; iii) rate: 10 °C/ min; iv) nitrogen gas atmosphere; v) flow: 40 ml/min.
Thermogravimetric (TG) and its derived (DTG) curves were plotted. TG shows the sample mass variation, in percentage, in relation to temperature, while DTG is the derivative of TG in relation to time, in which the TG steps are replaced by peaks that delimit areas proportional to the sample mass variation.
Mortars with partial replacement of cement by bamboo ash
The last stage of the research consisted of the production of mortars with the same proportions of partial replacement of cement by CCB used in the pastes produced in the previous stage, based on the Portland cement compound, according to NBR 11578 [25]. The same CCB600 selected for the production of the pastes was also used. The mortars produced were analyzed for consistency in the fresh state and mechanical compressive strength. Finally, after the tests, fragments of the mortars were analyzed by SEM.
Mortar mixture and consistency evaluation
The mortars (ACB -Bamboo brace mortar) were composed of Portland cement CP V-ARI and CCB in different proportions, according to Table 7; and sand and water in constant quantities, with the binder/sand ratio equal to 1:3 and the water/binder ratio, 0.55. The mixing procedure in a mechanical mixer, and the consistency test, on a table for consistency index, were performed according to NBR 7215 [23].
After mixing the mortars and determining the consistency index, 12 50 × 100 mm specimens were molded according to NBR 7215 [23] for each mortar to be submitted to compression testing at 3, 7 and 28 days (4 specimens for each age). Figure 10 shows a specimen of each mortar produced.
Mechanical analysis -determination of compressive strength
According to NBR 7215 [23], the compressive strength test was performed on specimens molded from the previously mentioned mortars at 3, 7 and 28 days. The compressive strength testas performed in a universal hydraulic press model WAW -1000C, with a maximum capacity of 100 tf and indicator division of 0.01 tf. Each specimen was positioned in the testing machine and centered on the loading axis, which was applied at a speed of 2 mm/min.
Microstructure of mortars
The microstructure of the mortars was visualized by analysis with a TESCAN VEJA 3 LMU scanning electron microscope at the IFPA Metallurgy Laboratory. For this purpose, fragments were extracted from the mortar specimens and submitted to the compressive strength test at 28 days. The tested specimens were sectioned with a circular saw so that a cylindrical mortar section with approximately 0.5 cm in height was extracted. The extracted samples were submitted to a temperature of 100ºC in an oven. The images generated in the SEM were not harmed by humidity and were later fragmented into small rectangular pieces, which were stored and destined for analysis. All samples were metalized with gold prior to the start of the analysis. The granulometric curves obtained from the laser granulometry analysis of the CCB500, CCB600, and CCB700 can be seen in Figures 11, 12 and 13, respectively. Curves were obtained for each grinding time to which the ash was submitted: 1, 2, 4, 6, and 8 hours. In general, the distribution of the curves shows that for the CCB600 and CCB700 ashes, the longer the grinding time, the smaller the grain sizes obtained. The CCB500, however, presented a finer material with 6 hours of grinding, to obtain with 8 hours of the process.
The average diameter (d50) of all samples was measured to evaluate the grain size (Table 8) quantitatively. It can be seen that grinding CCB500 for 6 hours was the most effective in decreasing the grain size, with an average diameter equal to 11.51 µm. Grinding CCB500 for 8 hours resulted in a d50 equal to 62.35 µm. The CCB600 and CCB700 presented the smallest average diameters with 8 hours of milling, 76.06 µm and 56.45 µm, respectively.
According to NBR 12653 [24], for a material to be considered pozzolanic, 80% of it must have a particle size less than 45 µm. Therefore, only the CCB500 ground for 6 hours fits this standard since it has an average diameter of 11.51 µm.
For the rest of the research, the ash ground at the times that presented the smallest average particle diameter was used: CCB500 ground for 6 hours, CCB600 ground for 8 hours and CCB700 ground for 8 hours.
Determination of gravity weight
The results of the gravity weight of the SCC, obtained by the average of two consecutive tests are shown in Table 9.
X-ray diffraction
From XRD results of the samples of CCB500 (Figure 14), CCB600 (Figure 15) and CCB700 (Figure 16), the presence of the minerals sylvite (KCl), calcite (CaCO3) and dolomite (CaMg(CO3)2) were identified, regardless of calcination temperature. The mineral that presented the highest peaks was sylvite, demonstrating that CCB can present large amounts of potassium oxide in the chemical composition. The diffractogram of CCB700 was the only one that showed a peak identified as quartz (SiO2), a crystalline form of silica.
The superposition of the CCB diffractograms (Figure 17) show that all the ashes present an amorphous hamp between the 10º and 25º 2θ angles for all calcination temperatures. Its intensity decreases with the increase of the calcination temperature. The XRD analysis allowed the determination of the crystalline mineral peaks present in the sample. All samples presented peaks of sylvite, calcite and dolomite, being the most expressive peaks of sylvite, a mineral composed by potassium and chlorine. An amorphous halo was also observed in all diffractograms, and from the superposition of the graphs, it was noted that the amorphous halo was more intense the lower the calcination temperature to which the ash had been submitted. The diffractogram of CCB700 was the only one that showed a peak of quartz, silica in crystalline form.
Chemical composition
The XRF analysis (Table 10) showed that CCB600 has a silica content of 12.25% (SiO2), refuting the hypothesis that ash from bamboo stalks is a silica-rich material.
The CCB does not meet some important chemical requirements of NBR 12653 [24], which determines the requirements for a material to be considered pozzolanic. Only the percentage of alkali available in Na2O meets the chemical requirement of the standard, which is a maximum of 1.5%; the CCB has 0.16%. According to the standard, the sum of SiO2, Al2O3 and Fe2O3 should be equal to at least 50%; CCB presented 12.93% in the sum of these compounds. The loss on ignition must not be greater than or equal to 10%; the CCB presented 27.38% loss on ignition.
Performance index with Portland cement at 28 days
The results of individual compressive strength of specimens, average compressive strength of mortars evaluated, relative deviations and consistency index are shown in Table 11. The PSI: CCB500 presented the lowest consistency index, followed by PSI: CCB700 and PSI: CCB600, respectively. The IAP: REF presented the highest consistency index, 0.5cm higher than the IAP: CCB600.
The performance indices with Portland cement at 28 days can be seen in Figure 18. According to NBR 12653 [24], this index should be greater than 90% for the evaluated material to be considered pozzolanic. The mortar with CCB600 was the only one that exceeded this value, with an index of 93.51%.
Given the results obtained in the stage of characterization of the CCB, it was decided to continue the research using only the sample of bamboo stem ash calcined at 600°C (CCB600), because when used in mortar, the CCB600 guaranteed 93.51% of the compressive strength of the reference mortar, despite not meeting the chemical requirements of NBR 12653 [24]. Thus, further research on the use of CCB600 becomes relevant.
Mineralogy of hydrated pastes
The diffractograms generated from the XRD analysis of PCB0, PCB6, PCB10 and PCB14, are arranged in Figures 19, 20 It was observed in all pastes the presence of the anhydrous phases of Portland cement, bellite (C2S), both at 28 and 56 days of age. There were not identified, in turn, peaks of alite (C3S), since this compound is much more reactive than the C2S, and the first, under normal temperature conditions, is usually 50% hydrated in 3 days and 80% at 28 days.
Ettringite is usually one of the first compounds to precipitate during cement hydration [1]. It was identified in all diffractograms. In order to be able to evaluate the intensity of the ettringite peak comparatively, the detail of the peak at 15.73°2θ of all samples was superimposed at 28 (Figure 23a) and 56 days (Figure 23b). No significant distinction was observed in the behavior of pastes with different CCB contents with respect to ettringite formation and the difference between ages was practically imperceptible.
The detail of the calcite peak at 29.4°2θ is illustrated in Figure 24 for the two ages of analysis. It can be seen that at 28 days the peak intensity is quite similar among all the samples. However, over time, the PCB0 sample showed a decrease in the intensity of this peak, while in the other samples, the peak remained practically unchanged. Figure 25, which illustrates in detail overlapping peaks of portlandite at 18.1°2θ of all samples. It is visualized at 28 days that all samples presented peaks with practically the same intensity. At 56 days, samples PCB6, PCB10 and PCB14 showed a decrease in the peaks' intensity, while that of sample PCB0 was slightly increased. The PCB10 sample presented lower peak intensity, on the order of 1000, while the intensity of the PCB0 peak was close to 1350. It is known that this phenomenon is common in the incorporation of pozzolans into cement, which consumes calcium hydroxide in the presence of water and forms more resistant materials. However, the CCB incorporated in the pastes does not meet the chemical requirements of NBR 12653 [24] to be considered pozzolanic.
Thermogravimetry of the hydrated pastes
TG and DTG curves of PCB0, PCB6, PCB10 and PC14 samples showed typical behavior of hydrated cement pastes, with the identification of three endothermic reactions in distinct and well-defined temperature ranges (Table 12), generating peaks of mass loss. The temperature ranges were defined as I, II and III. I) referring to the water evaporation reaction of the paste hydrated compounds, such as ettringite and hydrated calcium silicates and aluminates; II) refers to the decomposition of calcium hydroxide; III) to the decomposition of carbonate phases, as proposed by EL-JAZAIRI and ILLSTON [26] apud RODIER et al. [21].
The graphs obtained from the thermogravimetric analysis, containing the TG and DTG curves of samples PCB0, PCB6, PCB10 and PCB14, at 56 days, can be seen in Figures 26,27 In all samples, the temperature range I presented two peaks of mass loss in DTG. The first is related to mass loss by evaporable water. While the second is interlamellar water from hydrated phases such as ettringite, C-S-H and/or C-A-S-H. A subtle decrease in the DTG peak was identified in range II, demonstrating a possible decrease in the amount of calcium hydroxide present in the samples with the increase in CCB content. In range III, PCB0 and PCB6 samples have a mass constancy around 750°C, while PCB10 and PCB14 pastes, small amounts of mass are lost between 750°C and 950°C. For these variations to be quantified, the mass loss, in percent, of each temperature range was determined (Table 13).
An increase in mass loss occurred in range I with the addition of CCB in the pastes, indicating a greater amount of evaporable water bound to the hydrated compounds. In range II of temperature, the effect was inverse; the addition of the ashes caused a lower mass loss referring to the decomposition of calcium hydroxide. PCB6 suffered a mass loss in range II almost equal to that of PCB0 (4.33% and 4.36%, respectively). PCB10 and PCB14 showed a loss quite close to each other (1.74% and 1.77%, respectively) and lower than the other two samples. In range III, the higher the amount of CCB, the higher the mass loss related to the decomposition of carbonate phases due to the carbon present in the ash.
MORAES [27], when studying the hydration of pastes with 15% replacement of Portland cement by ash from sugar cane leaf, found results very close to those of this study for mass loss due to dehydration of calcium hydroxide. At 28 days, the control sample lost 2.92% mass, while the sample with replacement lost 1.53%. At 60 days, the value of the control sample increased to 3.20%, while the sample with the substitution was increased to only 1.60% From the mass loss in temperature range III, all the evaluated pastes contain carbonate phases. However, the amount of mass loss in range III increases with the increase in CCB content. The ACB6 paste already presents practically twice the mass loss, in this temperature range, concerning ACB0. The chemical composition of the ashes, with a large amount of potassium oxide, an alkali, may have facilitated the occurrence of the carbonation phenomenon. The considerable percentage of ash loss on ignition may also have been responsible for increased carbonate content.
According to POSSAN [28], carbonation occurs by the reaction of CO 2 with hydroxides, especially calcium hydroxide, which is found in larger quantities in the presence of moisture. Calcium and potassium hydroxides also stand out. Consequently, carbonation decreases the pH of mixtures. In reinforced concrete, it can reduce the passive protection of reinforcement and decrease the structure's durability, which becomes vulnerable to corrosion.
Finally, the amount of calcium hydroxide present in the pastes was calculated from the mass loss in temperature range II (Table 14). The decrease in calcium hydroxide in the pastes was very significant in the samples, with 10% and 14% of CCB in the reference sample. The sample with 6% presented practically the same amount of calcium hydroxide as the PCB0.
Analysis in the fresh state -consistency
The water/cement ratio was constant in all mortars produced. The use of a superplasticizer was unnecessary because from the determination of the normal consistency index, according to NBR 7215 [23], all mortars produced presented practically the same consistency (Table 15). According to NBR 5752 [11], the consistency index of mortars with substitution can vary up to ± 10 mm from the index of the reference mortar. Figure 30 illustrates the appearance of the mortars after the test.
Mechanical analysis -determination of compressive strength
The compressive strength results of the mortars ACB0, ACB6, ACB10, and ACB14 at 3, 7 and 28 days are presented in Figure 31. The appearance of the mortars after the test at 28 days is shown in Figure 32. In general, the compressive strength increased at longer ages. The partial replacement of Portland cement with bamboo stalks ash calcined at 600ºC increased the compressive strength of mortars due to the physical and chemical effects. The filler effect and particle packing with the addition of fine material concomitantly can explain that. The chemical effect is based on the reaction of the small content of amorphous silica present in CCB during hydration of Portland cement, consuming calcium hydroxide and forming more resistant hydrated products, as tended the result of thermogravimetric and XRD analysis.
The statistical analysis showed a significant difference between all mortars evaluated at 3 days. CBA6 presented the highest result, 21.96 MPa, and CBA0, without the addition of CCB, the lowest, 15.59 MPa. There was an increase of approximately 41% in compressive strength of the mortar, with 6% of CCB higher than reference mortar. However, by increasing the substitution content, the increase in strength at 3 days decreases. The CBA10 had an increase of 31.49% and CBA14, of 23.80%, both higher than CBA0. At 7 days, the behavior of the mortars' compressive strength remained similar to that of 3 days, increasing proportionally due to the age in each mortar. All mortars showed significant differences among themselves. The increase in compressive strength of PCB6 about PCB0 was around 36%. CBA10 had an increase of 27.98% and CBA14, of 15.18%, about CBA0.
At 28 days, all mortars with CCB (ACB6, ACB10 and ACB14) showed between 10 and 15% increase in relation to the compressive strength of the reference mortar (ACB0). By subjecting only the mortars with CCB to statistical analysis, it became evident that at 28 days, the compressive strength of ACB6, ACB10 and ACB14 is equal (Figure 33). The mineralogical and thermogravimetric analyses showed a decrease in the concentration of calcium hydroxide. However, the CCB evaluated in this research does not have the necessary chemical composition to be considered pozzolanic and reactive. Moreover, the increase in compressive strength of mortars with CCB can also be attributed to the physical effect of filling voids, densifying the structure from the filler effect by the non-reactive part of the CCB.
Microstructure of mortars
Images were generated from secondary and backscattered electron beams with 100x magnitude of all mortars to compare the microstructural appearance of their surfaces. Figures 34, 35, 36 and 37 correspond to the images generated from samples ACB0, ACB6, ACB10 and ACB14, respectively. Some images have micro-cracks since all samples come from mortar compressive strength samples. Note that the samples were extracted from the bases of the specimens, which remained intact to the naked eye. From the images on the right, generated by backscattered electron beams, one can see more concentrated areas with darker coloration in the ACB0 and ACB6, while the samples ACB10 and ACB14 present homogeneous coloration. In the images generated by backscattered electrons, the lighter the color illustrated, the denser the component of the sample.
CONCLUSIONS
The first step was to characterize the bamboo stalks ashes from three calcination temperatures (500ºC, 600ºC and 700ºC). The results showed that the ashes are not classified as pozzolanic material because they do not meet the chemical requirements of the standard.
The granulometric analysis defined that the CCB500 obtained the smallest average diameter from grinding for 6 hours, while the CCB600 and CCB700 for 8 hours. The particle size distribution curves for the chosen times characterized the distribution of the samples as discontinuous, i.e., they have tiny and other very large particles, with an absence of intermediate sizes. The ash's gravity weight of the underwent a slight increase with increasing calcination temperature and remained between 2.11 g/cm 3 and 2.20 g/cm 3 .
XRD analysis concluded the presence of amorphous silica in samples CCB500 and CCB600 from 700ºC. During the calcination of the material, this silica tends to crystallize in the form of quartz. In its chemical composition, the CCB presents an amount of SiO2, Al2O3 and Fe2O3 much lower than the chemical requirement of NBR 12653 [24]; thus it is considered pozzolanic. According to the FRX analysis, the CCB has 12.93% of these oxides. Moreover, the CCB showed a high loss on ignition, greater than 20%, while the standard above requires a maximum limit of 10%. The chemical analysis of the CCB also showed a large amount of potassium 50.42%, one of the alkalis that can cause damage in cementitious matrices.
The performance index with Portland cement at 28 days is one of the physical requirements of NBR 12653 [24] and despite not meeting the chemical requirements of the same standard, CCB600 showed an index of 93.51%, higher than the minimum limit of the standard, which is 90%. The rates of CCB500 and CCB700 were respectively 75, 93% and 84.65%.
From characterization and physical requirements, it was decided to perform a further investigation on the properties of the bamboo stalks ash calcined at 600°C (CCB600) when inserted into Portland cement matrices as a partial replacement of the binder. This choice was also based on two aspects. First, the mineralogy of the ash showed a tendency of crystallization of amorphous silica in the form of quartz from 700°C. Then, the performance index with Portland cement at 28 days allowed verifying that the CCB600 guaranteed 93.51% of the compressive strength of the reference mortar, even replacing 25% of Portland cement, making relevant a continuity of studies.
The study also evaluated the hydration of cement partially replaced by bamboo ash. For this purpose, cement pastes were evaluated with binder substitution contents by CCB600 based on the composite Portland cement, according to NBR 11578 [25]: 0%, 6%, 10% and 14%.
From the XRD of the pastes hydrated at 28 and 56 days, it was possible to compare the intensity of the prominent mineral peaks: ettringite at 15.73°2θ, calcite at 29.4°2θ and portlandite at 18.1°2θ. The incorporation of ash into the mixtures caused no effects on the ettringite peak at both ages evaluated. The intensity of the calcite peak, on the other hand, remained the same for all samples at 28 days. However, at 56 days, the sample with 0% CCB showed less intensity than those with CCB. Finally, it was evaluated that the intensity of portlandite at 28 days was practically the same in all samples. However, at 56 days, the sample with 0% CCB slightly increased the peak intensity, while all samples with CCB had a decrease. The sample with 10% CCB showed lower peak intensity, on the order of 1000, while the peak intensity of the reference sample was close to 1350. This phenomenon is expected to incorporate pozzolans into cement, which consume calcium hydroxide in the presence of water and form more resistant materials. However, the CCB incorporated into the pastes does not meet the chemical requirements of NBR 12653 [24] to be considered pozzolanic.
From the decomposition of calcium hydroxide and decomposition of carbonate phases in different temperature ranges (seen in TG results), it was to quantify the mass loss by dehydration of hydration products (C-S-H, C-A-S-H and ettringite) at 56 days. The incorporation of ash increased the mass loss by dehydration of the hydration products and by decomposition of the carbonate phases. However, the amount of calcium hydroxide tended to decrease with ash incorporation. Confirming what was seen from the XRD analysis of the pastes, the sample with 10% of cement replacement by CCB presented the lowest amount of calcium hydroxide among the pastes. However, from this analysis, the incorporation of ash significantly increased the number of carbonate phases in the mixture, which may have caused the carbonation phenomenon, which can cause damage to reinforced concrete structures. A large number of alkalis may have facilitated the carbonation in the chemical composition of ash. The increase of carbonatic phases can also be explained by the high loss on ignition of ash.
The last stage of the work consisted of evaluating mortars with partial replacement of Portland cement by CCB. In the fresh state, the incorporation of CCB in the mortars did not cause damage to the consistency. All mortars presented practically the same consistency in the fresh state. In the hardened state, the influence of the incorporation of CCB in the mechanical resistance of mortars was evaluated. At 3 and 7 days, the samples with CCB showed higher strengths than the reference sample, and the mortar with lower substitution content (6%) reached the highest strength. At 28 days, all mortars with CCB reached equal resistance, according to the statistical tests applied, and higher than the reference mortar. The increase in strength with the incorporation of ash was in the order of 15%.
From the microstructural analysis of the mortars, after the rupture in the compressive strength test, it was possible to visualize the appearance of the surface of the samples, and it was found that the samples with 10% and 14% substitution presented a denser surface, as visualized in the images with 100x magnitude, than the reference samples and those with 6% CCB.
Figure 4 :
Figure 4: Muffle furnace used in the research.
Figure 5 :
Figure 5: Grinding process of the bamboo stalk ash.
Figure 9 :
Figure 9: Samples of the pastes destined for X-ray diffraction.
, 21 and 22, respectively. Where * are identification of the peaks of Portlandite.
Figure 31 :
Figure 31: Result of the mortar compressive strength.
Figure 2: Sieve
Size Curve of Sand and Limits of the Optimal and Usable Zones.
Table 4 :
Nomenclature of bamboo stalk ash.
Table 5 :
Mortar composition for pozzolanicity evaluation of CCB.
Table 6 :
Cement and CCB600 contents in pastes.
Table 7 :
Cement and CCB600 contents in the mortars.
Table 8 :
Determination of the average diameter (d50) of the SCC after grinding.
Table 9 :
Gravity weight of the CCB.
Table 11 :
Consistency and average mortar strength.
Table 12 :
Decomposition temperature ranges of the hydration products of the pastes.
Table 13 :
Loss of mass of the pastes by temperature range.
Table 14 :
Amount of calcium hydroxide in the pastes.
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Isoquinoline Alkaloids and the Ionophore Monensin Supplemented Alone or Combined on Ruminal Fermentation and Nutrient Digestibility in Steers Fed a High-Energy Diet
Facultad de Medicina Veterinaria y Zootecnia. Universidad Autónoma de Sinaloa. Blvd. San Ángel s/n, Fraccionamiento San Benito CP 80246, Culiacán, Sinaloa, México Instituto de Investigaciones en Ciencias Veterinarias. Universidad Autónoma de Baja California. Km 4.5 carretera Mexicali-San Felipe, CP 21386, Mexicali, Baja California, México Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, Col. CU, Coyoacán, CP 04510, Cd. de México, México Department of Animal Science, University of California, Davis, United States Departamento de Ciencias Naturales y Exactas, Universidad Autónoma de Occidente, Unidad Regional Guasave, Avenida Universidad s/n, Flamingos, CP 81048, Guasave, Sinaloa
Introduction
The ionophore Monensin (MON) is commonly included in feedlot cattle growing-finishing diets to enhance feed efficiency. The enhancement in feed efficiency has been attributed, at least in part, to shifts in ruminal fermentation patterns favoring increased propionate and decreased molar proportions of acetate and butyrate (Russell et al., 1988). Although MON may also lead to reduced ruminal microbial efficiency, it may increase flow of non-ammonia N to the small intestine by reducing the ruminal feed protein degradation (Zinn, 1988). Nevertheless, 203 the magnitude of the response to supplemental MON on feed efficiency quite varied, fluctuating from nil (Zinn and Borquez, 1993;Depenbusch et al., 2008) up to increases of 18% (Bartley et al., 1979). A major factor influencing the feed efficiency response to MON is diet energy density (Barreras et al., 2013). Duffield et al. (2012), observed that the magnitude of response of MON on feed efficiency decreased from 8.1 to 3.5% during the past 4 decades, coincident with increases in diet energy density brought by decreased dietary forage levels, increased use of supplemental fat and flaking grain (Samuelson et al., 2016). These changes in diet formulation lend to enhanced ruminal molar proportions of propionate and decreased methanogenesis (Wang et al., 2018). Some phytogenic compounds, such as certain isoquinoline alkaloids (IQA, specifically quaternarybenzo (c) phenanthridine alkaloids sanguinarine and chelerythrine) have effects on ruminal fermentation that could be complementary to MON in high-energy diets. When IQA was added to a substrate comprised of 50:50 forage-to-concentrate, the in vitro molar proportion of acetate increased (Smink and van der Kolk, 2004). Similarly, supplementation of a high-energy diet with a standardized source of IQA (equivalent from 15.8 to 23.8 mg IQA/kg diet DM) increased ruminal acetate molar ratio, but decreasing butyrate in cannulated steers without affect ruminal propionate ratio (Aguilar-Hernández et al., 2016). These same researchers reported that supplemental IQA increased flow of non-ammonia N to small intestine due to both reduced ruminal on feed protein degradation and increased net microbial protein synthesis. These findings indicate a possible synergistic action on digestion and ruminal fermentation in cattle fed with high-energy diets supplemented with both additives combined.
For this reason, the aim of this experiment was to evaluate the effects of supplementation of isoquinoline alkaloids and MON on ruminal fermentation and nutrient digestibility in steers fed a high-energy finishing diet.
Materials and Methods
The trial was conducted at the Ruminant Metabolism Experimental Unit of the Instituto de Investigaciones en Ciencias Veterinarias of the Universidad Autónoma de Baja California located 10 km south of Mexicali City in northwestern México (32° 40' 7" N and 115° 28' 6"W). The area is about 10 m above sea level. All procedures were conducted within approved locally animal care guidelines (NOM, 1999).
Animals, Diets and Sampling
Four Holstein steers [302±15 kg initial shrunk Live Weight (LW)] were fitted with a 3.8 cm i.d. ruminal Tygon "T" cannula and a 1.9 cm i.d. Tygon "T" duodenal cannula (situated approximately 6-cm from pyloric sphincter) with the aim to examine the effects of feeding a combination of Isoquinoline Alkaloids (IQA) and Monensin sodium (MON) in finishing diets on the characteristics of ruminal fermentation and digestive function. Steers were housed in an indoor facility in individual pens (3.9 m 2 ), with a concrete floor covered by a neoprene carpet, automatic waterers and individual feed bunks. Chromic oxide was used as an indigestible marker to estimate nutrient flow and digestibility. Chromic oxide (3.5 g/kg of diet air-dry basis) was premixed with minor ingredients (MON, urea and mineral supplement) in a 2.5 m 3 capacity concrete mixer (mod 30910-7, Coyoacán, Mexico) for 5 min and then, the final product was incorporated after that steam-flaked corn was added to the mixer. Ingredient composition, chemical analysis and calculated dietary net energy (NASEM, 2016) of the basal diet are shown in Table 1. All steers received ad libitum access to the basal diet (Control) for 3 wk before the initiation of the experiment. To avoid feed refusals during experimental period, daily feed intake (as feed basis) was restricted to 90% of observed ad libitum intake during last 7-d of preliminary period (6.9 kg as-fed basis, equivalent to 2.28% of average shrunk initial LW). Treatments consisted of a steam-flaked corn-based finishing diet supplemented as follows: (1) Basal diet with no additives (Control), (2) basal diet plus 15 mg IQA/kg diet DM, (3) basal diet plus 30 mg MON/kg diet DM and (4) basal diet plus 15 mg IQA and 30 mg MON (IQA + MON)/kg diet DM. Source of IQA was Sangrovit RS (Phyto biotics; Futtermittelzusatzstoffe GmbH, Eltville, Germany) containing a standardized mixture of isoquinoline alkaloids, specifically quaternary-benzo (c)-phenanthridine alkaloids, sanguinarine and chelerythrine in a 2:1 ratio with a concentration of 2.25% (w/w). The source of MON was Rumensin 90 (Elanco Animal Health, Greenfield, IN) containing 200 g MON/kg of product. The daily dosage of additives was weighed using a precision balance (Ohaus, mod AS612, Pine Brook, NJ). Supplemental IQA was added (top-dressed) in equal proportions (2.3 g of product per serving) to the basal diet at time the morning and evening feeding, while supplemental Rumensin 90 was premixed with minor ingredients (Cr2O3, urea and mineral supplement) before incorporation into complete mixed diets. The amount of feed of each steer was weighed on a digital scale (Ohaus, NVT 16000/1, México City, México). Diets were fed in two equal proportions at 0800 and 2000 h daily. Experimental periods consisted of 21 days, with 10 days for dietary treatment adjustment, 4 days for collection and 7 days of additive withdrawal (during this period all steers received the control diet). During the collection period, duodenal and fecal samples were taken from all steers following procedure described by Aguilar-Hernández et al. (2016). Briefly, samples were taken twice daily as follows: d 1, 0750 and 1350 h; d 2, 0900 and 1500 h; d 3, 1050 and 1650 h; and d 4, 1200 and 1800 h.
204
Individual samples consisted of approximately 500 mL of duodenal chyme and 200 g (wet basis) of fecal material. Samples from each steer and within each collection period were prepared for analysis. During the final day of each period, ruminal samples were obtained to measure microbial populations (protozoa, cellulolytic bacteria and total bacterial). Ruminal samples were prepared and stored by the method described by Dehority (1984) and by Mendoza et al. (1993). During the final day of each collection period, ruminal fluid was obtained, via the ruminal cannula, from each steer at 4 h after feeding. Ruminal sample was taken from the ruminal ventral sac by vacuum pump (Cole Parmer Instrument, Vernon Hill, IL) using a tygon tube (1.9 cm i.d.; USP Lima, Ohio). Ruminal fluid pH was determined on fresh samples. Samples were then strained through four layers of cheese cloth. For VFA analysis, 2 mL of freshly prepared 25% (w/vol) meta-phosphoric acid was added to 8 mL of strained ruminal fluid, centrifuged (17,000 × g for 10 min) and supernatant fluid stored at -20°C. Upon completion of the trial, ruminal fluid was obtained from all steers and composited for isolation of ruminal bacteria via differential centrifugation (Bergen et al., 1968) as follows: (1) ruminal fluid was diluted 50:50 with 0.16N saline (37°C) agitate gently for about 30 seconds and strained through 4 layers of cheesecloth; (2) strained fluid was promptly transferred into centrifuge bottles and spun at 2000 × g for 10 min at 10°C; (3) supernate was decanted and centrifuged at 43,000 × g for 20 min at 10°C and (4) supernate was decanted and the pellet isolated, oven-dried (70°C) and then ground with a mortar and pestle. The microbial isolate served as the purine: N reference for the estimation of microbial N contribution to chyme entering the small intestine (Zinn and Owens, 1986). Additionally, during the final day of each period, blood samples (5 mL) were taken via jugular vein 5 h post-feeding in order to determine the enzymes Gamma-Glutamyl Transferase (GGT) and aspartate Aminotransferase (AST), analyzed enzymatically on a Beckman Olympus AU640 auto analyzer (Myko Analytical, Lake Tapps, WA, USA). These enzymes were measured as indicators of possible liver damage due to supplemental additives.
Sample Analysis and Calculations
Feed, duodenal and fecal samples were subject to the following analysis: Dry matter (method 930.15); ash (method 942.05) and Kjeldahl N (method 984.13) following the procedures published by AOAC (2000). Neutral detergent fiber [aNDFom, corrected for NDF-ash, incorporating heat stable α-amylase (Ankom Technology, Macedon, NY) at 1 mL per 100 mL of NDF solution (Midland Scientific, Omaha, NE)] was determined following the procedures described by Van Soest et al. (1991) and chromic oxide (Hill and Anderson, 1958) and starch (Zinn, 1990). In addition, ammonia-N (method 941.04; (AOAC, 2000) and purines (Zinn and Owens, 1986) were determined in duodenal samples. Concentrations of VFA in ruminal fluid were determined by gas chromatography (Zinn, 1988). The counting procedures for total protozoa and total bacterial were performed according to Dehority et al. (1989). Cellulolytic bacteria was cultured and counted by the method described by Van Gylswyk and Hoffman (1970). Bacterial and protozoal counts are expressed as log10/mL.
Total DM flow to the duodenum and fecal excretion were estimated using Cr2O3 as an external marker. Feed, duodenal and fecal OM was determined by difference between DM and ash content. Microbial Organic Matter (MOM) and Microbial Nitrogen (MN) leaving the abomasum (as obtained from a duodenal cannula placed approximately 6 cm from the pyloric sphincter) were calculated using purines as a microbial marker (Zinn and Owens, 1986). Organic matter truly fermented in the rumen was considered equal to the OM intake minus the difference between the amount of total OM reaching the duodenum and the MOM reaching the duodenum. Feed N escape to the small intestine is considered equal to the total N leaving the abomasum minus the sum of ammonia-N plus MN reaching duodenum and, thus, includes any endogenous N contributions. Ruminal microbial efficiency was estimated as duodenal MN, g /kg OM fermented in the rumen and protein efficiency represent the duodenal non-ammonia-N, g/g N intake.
Statistical Design and Analysis
Treatment effects on characteristics of digestion were analyzed as a balanced 4 × 4 Latin square design in a 2 × 2 factorial arrangements using the MIXED procedure according to SAS (2004). The fixed effect consisted of treatment and random effects consisted of steer and period. The statistical model for the trial was as follows: where: Yijk is the response variable, µ is the common experimental effect, Si is the steer effect, Pj is the period effect, Tk is the treatment effect and Eijk is the residual error. Treatment effects were separated into the following orthogonal contrasts: (1) Non-additive vs. IQA; (2) non additive vs MON; and (3) IQA× MON interaction. In addition, means separations were performed using Fisher's LSD. Contrasts are considered significant when the P value was ≤0.05 and as tendencies when the P-value was >0.05 and ≤0.10.
Results and Discussion
Treatment effects on characteristics of ruminal and total tract digestion are summarized in Table 2. Flow of ammonia-N to the small intestine was greater (interaction, P<0.01) for non-supplemented control than for the other three treatments. Flow non-ammonia N (NAN; interaction, P = 0.04) was greater for supplemental IQA alone than for the other three treatments. When IQA was added to the control diet, duodenal flow of NAN increased (9.2%) and NH3-N flow decreased (23.7%). In contrast, when IQA and MON were added to the Control diet no effect on NAN flow to the small intestine was observed and NH3-N flow decreased only 18.2%. This interaction was also observed (P<0.05) in protein efficiency (NAN flow to the small intestine/N intake) and postruminal N digestion. Addition of IQA to control diet resulted in a 9.1% increase in protein efficiency and 6.1% increase in postruminal N digestion. Whereas, IQA in combination with MON did not increase (interaction, P<0.05) protein efficiency or postruminal N digestion. The basis for this response is unclear. Earlier reports indicate that MON decrease ruminal concentration of microorganisms with high proteolytic activity and it may have direct effect on protease and deaminase enzymes as well (Bergen and Bates, 1984;Russell and Strobel, 1989). On the other hand, IQA could modulate metabolism of rumen microbes with minor changes on rumen microbial population and species diversity (Petri et al., 2019). The effects of both additives alone, decrease the ruminal degradation of feed N; however based on the duodenal flows of NAN, ruminal scape feed N and microbial N with the combination, apparently the effects of each additive are negatively affected. More research is is needed to further assess these interactions, as well as possible interactions with other additives (including alternative ionophores) that may be supplemented in feedlot diets.
IQA supplementation increased (5.6%, P = 0.02) flow of NAN and decreased (11.8%, P = 0.01) flow of NH3-N to the small intestine. The increase in NAN flow to the small intestine was due in part to increased (6.5%, P = 0.01) flow of microbial N to the small intestine. This increase is a reflection of increased (7.6%, P = 0.03) ruminal microbial efficiency (expressed as duodenal MN, g/kg OM fermented in the rumen) and increased (9.1%, P = 0.02) ruminal protein efficiency (expressed as duodenal non-ammonia N, g·g-1 N intake). Aguilar-Hernández et al. (2016) observed that in steers fed a diet similar that of the present study, 206 supplementation with 16.8 mg IQA/kg diet DM decreased ruminal ammonia N concentration; presumably due to decreased proteolysis and deamination of amino acids (Drsata et al., 1996). More recently, Petri et al. (2019) likewise observed decreased amino acids metabolism in IQA supplemented treatments. They noted that predicted amino acid metabolism pathways were down-regulated in all IQA supplemented groups in comparison to the control group, a key mode of action for these IQA supplementation in regard to improving ruminal amino acid bypass. The increase of net microbial N flow to duodenum in steers fed IQA may be partially explained (as indicated below) by reduced recycling of microbial protein as consequence of decreased ruminal protozoa.
There Supplemental MON decreased (9.4%, P = 0.03) flow of ammonia-N and NAN (4.8%, P = 0.02) to the small intestine and in turn, ruminal N efficiency (5.7%, P = 0.02). The latter is attributable to decreased (7.4%, P = 0.02) ruminal microbial efficiency and associated decrease (8.6%, P = 0.02) in microbial N flow to the small intestine. Consistent with previous studies (Morris et al., 1990;Salinas-Chavira et al., 2009), supplemental MON did not affect (P>0.10) site and extent of OM, NDF and starch digestion. Comparable effects of supplemental MON on feed N degradation and microbial synthesis in feedlot steers has been reported previously (Zinn, 1987;Zinn et al., 1994). Due to antimicrobial properties of MON some decrease in ruminal NDF degradation can be expected. However, the effects of MON of fiber digestion has not be consistent (Salinas-Chavira et al., 2009). Both increases and decreases in fiber digestion have been associated with ionophore feeding (Spears, 1990). Varying effects are apparently dependent on fiber level and source. As with the present study, NDF levels are low in conventional finishing diets for feedlot. Due to high dietary starch and consequent low ruminal pH, the extent of ruminal fiber digestion is low (≤40%), independently of MON supplementation. Although, in the present study MON numerically decreased (10%, P = 0.18) ruminal digestion of NDF.
Treatment effects on ruminal pH, VFA molar proportions are shown in Table 3. There were no treatment main effects, or synergism (P>0.10), on ruminal pH. Contrary to our hypothesis, there was no treatment synergism (P>0.10), on ruminal VFA proportions. However, IQA increased (10.9%, P = 0.02) acetate molar ratio, this effect reflected a tendency of increase (P = 0.06) the acetate: Propionate molar ratio. The absence of effects of IQA on ruminal pH and total VFA production are consistent with lack of treatment effect on ruminal OM digestion. Similar findings have been reported for steers fed both medium energy diets (Petri et al., 2019) and high energy diets (Aguilar-Hernández et al., 2016;Zhang et al., 2019). In vitro studies of Smink and van der Kolk (2004) also showed increased acetate: Propionate molar ratio without effect on total VFA production. However, Khiaosa-ard et al. (2020) using a rumen simulation technique (Rusitec) noted that IQA supplementation increased ruminal propionate at dose of 8.75 mg IQA/kg DM, but at dose of 17.50 mg IQA/kg DM did not registered differences between ruminal molar proportion of VFA in a medium-energy substrate (35:55 forage concentrate ratio).
Lack of an influence of MON on ruminal pH, VFA molar proportions is consistent with numerous studies in which MON was supplemented in high-energy diets (Zinn et al., 1994;Salinas-Chavira et al., 2009;Felix and Loerch, 2011).
Treatments effects on ruminal microbial counts are shown in Table 4. Combining IQA with MON increased (interaction, P < 0.01) total protozoa count and nullified the effects (interaction P = 0.04) of MON on the ruminal total bacterial count. It has been previously observed that combinations of antimicrobials may act differently on microorganisms than when they are administered separately (Mitosch and Ballenbach, 2014).
There were no treatment effects (P > 0.16) on cellulolytic bacteria counts. The total bacteria count was lower (interaction, P = 0.04) for MON alone than for the other three treatments. Supplemental IQA alone decreased (interaction, P<0.01) ruminal protozoa counts compared to that of controls (28%) and MON, alone (21%). Whereas protozoal counts for control and MON plus IQA were not different. Likewise, Petri et al. (2019) using a rumen simulation technique (Rusitec) noted that IQA supplementation decreased ruminal protozoa population. Sanguinarine and chelerythrine, principal compounds on IQA source used here, have a significant dose-dependent antibacterial activity (since 16 µg/mL) against Gram-positive and Gram-negative bacteria when tested in vitro (Opletal et al., 2014). Protozoal recycling of microbial protein depresses ruminal microbial efficiency (net flow of microbial N to the small intestine). The decrease in ruminal protozoal counts and concomitant increase in observed microbial efficiency with IQA supplementation is consistent with this observation.
Development of MON resistance has been shown to occur in both gram-positive and negative species (Russell and Strobel, 1988). Apparently, prolonged use of MON alters the ruminal microbial ecosystem, selecting for ionophore-resistant members of the microbial population (Callaway et al., 2003). Although MON has consistently reduced in vitro protozoal counts, that effect is less consistently observed in vivo (Russell and Houlihan, 2003).
Conclusion
Isoquinoline Alkaloids mixture (IQA) supplementation improve of N utilization by promotes a lesser ruminal degradation of N and by greater microbial N flow to the small intestine. The inclusion of IQA to the diet increase molar proportion of ruminal acetate. IQA plus MON combination failed to be synergic on digestion nor ruminal fermentation, in opposite, had a negative associative effect on N utilization. More research is needed to further assess these interactions, as well as possible interactions with other additives (including alternative ionophores) that may be supplemented in feedlot diets. Isoquinoline alkaloids mixture (IQA) represent a strategy to improve N utilization in ruminants fed high-energy diets.
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Semi-Annual Report for Modular Integrated Gas High Temperature Reactor Development during Performance Period October 2021-March 2022
Modular Integrated Gas High Temperature Reactor (MIGHTR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed MIGHTR in 3 years and support its commercialization as a safe and low-cost HTGR. Argonne National Laboratory is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Work performed by Argonne also includes the thermal hydraulics analysis of the primary heat transport system including reactor pressure vessel (RPV) internals for normal operation, shutdown, and accident conditions. This first semi-annual report summarizes the progress made at Argonne on the two tasks since the start of the project. For the RCCS design task, high-level design work was performed including identification of design requirements for the conceptual MIGHTR RCCS and initial design calculations. The baseline dimensions of the MIGHTR RCCS were derived from scoping analysis results and preliminary steady state performance was estimated. At the initial stage of the primary system analysis task, the primary system thermal fluids model for the MIGHTR core was outlined to use a simplified two-dimensional model to predict the temperature distribution and coolant pressure losses in the fuel assembly blocks.
This first semi-annual report summarizes the progress made at Argonne on the two tasks since the start of the project. For the RCCS design task, high-level design work was performed including identification of design requirements for the conceptual MIGHTR RCCS and initial design calculations. The baseline dimensions of the MIGHTR RCCS were derived from scoping analysis results and preliminary steady state performance was estimated. At the initial stage of the primary system analysis task, the primary system thermal fluids model for the MIGHTR core was outlined to use a simplified two-dimensional model to predict the temperature distribution and coolant pressure losses in the fuel assembly blocks.
Introduction
Modular Integrated Gas High Temperature Reactor (MIGHTR) is being designed by a multidisciplinary team of nuclear, mechanical, and structural engineers led by MIT under the support of a DOE-NE Advanced Reactor Demonstration Program's Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed MIGHTR in 3 years and support its commercialization as a safe and low-cost HTGR with a focus on minimizing the overnight capital cost of the power-generation system and explicit considerations of functionality, constructability, transportability, modularity, safety, and future licensing.
Argonne National Laboratory ("Argonne") is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Work performed by Argonne also includes the thermal hydraulics analysis of the primary heat transport system including reactor pressure vessel (RPV) internals for normal operation, shutdown, and accident conditions. This first semi-annual report summarizes the progress made at Argonne on the two tasks since the start of the project. Chapter 2 documents the identification of design requirements and the highlevel design work for the initial concept of the MIGHTR RCCS. A design parametric study was performed incorporating the unique features of the MIGHTR. The baseline dimensions of MIGHTR RCCS were derived and preliminary steady state performance was estimated. Chapter 3 outlines the primary system thermal fluids model for the reactor core. A simplified twodimensional model will be used to predict the temperature distribution and coolant pressure losses in the fuel assembly blocks. Additional coolant paths will be modeled to predict bypass coolant flow rates. Where possible, predictions made using the simplified two-dimensional model will be verified against a coupled 1D fluid-to-3D solid model of a fuel assembly.
Task 1 Update: RCCS Design
The Reactor Cavity Cooling System (RCCS) is a safety-related system that provides a passive means of removing decay heat in the core when the power conversion system, the primary and secondary heat transport systems, and the normal shutdown cooling system are unavailable to remove decay heat. As ex-vessel cooling means the RCCS achieves heat removal by radiation and convection cooling from the reactor pressure vessel walls to a network of cooling channels. There are design variations that have been chosen to feature specific reactor types and design choices such as primary coolant, geometry, and dimensions of individual cooling channels.
The MIGHTR concept is a prismatic high-temperature gas-cooled reactor (HTGR) in a horizontal layout with a total power of 160-230 MWt. The MIGHTR integrates the reactor pressure vessel (RPV) and steam generator into a single vessel. It has a horizontal orientation to achieve its construction cheaper and faster instead of a vertical alignment of traditional HTGR and steam generator (SG) housed in the tall reactor building [1], but it poses additional challenges for passive decay heat removal using the RCCS concepts. The MIGHTR's ex-vessel natural circulation utilizing RCCS targets a high performance with relative simplicity and inherent safety characteristics maintaining its compactness.
Initial Concept of MIGHTR RCCS
The initial concept of the RCCS design proposed by Boston Atomics is described in [1]. It uses water as a primary coolant and consists of two tanks one above the RPV and one below and interconnecting pipes surrounding RPV as shown in Figure 1. The ultimate heat sink is not described at its present state, but this could be an active non-safety system during normal operation and rely on the thermal inertia of the water inventory in accident conditions such as a station blackout with a conduction cooldown situation. Initial assessment of this concept showed that it can potentially provide sufficient cooling for 5 to 10 days without replenishment [1].
Functional Requirements
The RCCS is designed to use natural forces and be relatively simple and potential for high levels of performance for the passive safety of HTGR to remove core decay heat during both normal operation and off-normal conditions [2]. Differences between various RCCS designs are mainly in their working fluid and passive mode of operation for the range of the reactor design, for instance, General Atomics (GA) modular high temperature gas-cooled reactor (MHTGR) [3], Next Generation Nuclear Plant (NGNP) [4], and Framatome Steam Cycle -High Temperature Gas Cooled Reactor (SG-HTGR) [5]. GA's MHTGR and NGNP are good references on the basis of system design requirements, where both have experienced the license application process in the past. Since they adopted the air-cooled natural convection open loop type system, those requirements could be modified to be applicable to other concepts, such as the water-based design or the design having different operating strategies.
The key functions of the RCCS are defined with acceptable RPV wall temperature and reactor cavity concrete temperature during power operation, startup, shutdown, anticipated operational occurrences (AOOs), and various Design Basis Events (DBEs). Working with the project team, design requirements applicable to the MIGHTR RCCS were derived in Table 1, where its designspecific values and features are represented in bold. It could be updated as the core, nuclear system design, and plant configurations of the MIGHTR evolve. Other categories in design requirements such as codes and standards, physical protection, material control, and safeguards, quality assurance, construction, or decommissioning have been considered, but not listed in the table.
A potential strategy for cooling the reactor cavity could be supported by a heating, ventilation, and air-conditioning (HVAC) system along with the RCCS performance, which capability might be adjustable to satisfy the design limits of the reactor building concrete and the RPV. Nevertheless, the design of the MIGHTR RCCS shall target potential licensing basis events to remove most of the decay heat from the core to protect the RPV and the reactor cavity concrete from overheating together with the conduction through the reactor cavity concrete wall without HVAC when the reactor is shutdown. 2) The heat loss through the RCCS will be as low as reasonably achievable while the reactor is operating between 0 % and 100 % power. A target maximum heat loss is ~1 MWt.
2.3) The RCCS shall limit the maximum reactor vessel
temperature below 427 C for a pressurized conduction cooldown and below 482 C for a depressurized conduction cooldown 2.4) As designed for continuous operation, the RCCS heat load during normal plant operation will be based on the module operating conditions. 2.5) The RCCS will be designed for an operating life of 40 years.
Structural requirements
3.1) All components and piping of the RCCS shall be designed against seismic loads and tornado.
High-level Design of MIGHTR RCCS
The initial MIGHTR RCCS design targets the reactor with a total power of 160 MWt at first, such that it could be utilized for assessing the feasibility of the concept. Design work for the MIGHTR RCCS design was performed in the first principle including an estimation of the total water inventory and a standalone RCCS analysis. Total water inventory was estimated by calculating the time elapsed until all amounts of water in the system are boiled off using the existing decay heat curve. Standalone RCCS analysis was performed to set design boundaries including system dimensions and operating conditions in de-coupled conditions. Then, the baseline dimensions of the MIGHTR RCCS design were derived based on the results.
Estimation of system inventory
According to the design objectives, the total water inventory in the system should be sufficient to secure at least 7 days until the boil-off of all coolant inventory in the system. To estimate the total water inventory required, two reference decay heat data were considered; ANS standard [7] and calculation results from a reference HTGR [8], shown as the ratio of decay power (P) to the nominal power (P0) in Figure 2. As the ANS standard is specific to light water reactors, particularly for the UO2 fuel decay power curve. Afterheat power was calculated for GA's MHTGR modeled as a semi-homogeneous graphite-moderated core using thorium-uranium cycle, where results predicted a bit higher than that from ANS standard as a larger amount of thorium and 235 U enrichment of the HTGR fuel considered in calculations [8]. Figure 2 Reference decay power rates [7,8] Assuming the RCCS is an open system operating in the system pressure of 1 atm and all decay heat is transferred to the RCCS coolant without any cooling that would otherwise be available during normal operation, the estimated amount of water required for securing 7 days of operation were approximately 170 tons and 220 tons for MIGHTR RCCS having a total power of 160 MWt based on the ANS standard and GA's decay heat curve, respectively. This result is consistent with Boston Atomics' preliminary calculation of ~200 tons of water inventory. It could be updated to accomplish design objectives in desired operation conditions according to the system design of MIGHTR RCCS.
Standalone RCCS analysis
Design analyses were performed to determine the design and operational conditions boundaries of the MIGHTR RCCS. As the MIGHTR primary system design is in the early stage, the RPV temperature could be set as the boundary condition independent of the decay heat level after shutdown in a standalone RCCS analysis. It consists of a coupled thermal resistance network analysis and a simplified natural circulation loop analysis. Thermal resistance network analysis estimates the amount of heat transfer from the RPV in desirable RCCS operation conditions. The simplified natural circulation loop analysis predicts a natural circulation flow rate according to the system dimensions. Two steps are then combined by exchanging the amount of coolant temperature increase across the riser tube (T) and the natural convective heat transfer coefficient (htc) of the riser tube while iterating until achieving heat balance. It estimates steady state RCCS performance in desirable RCCS operation conditions to derive the baseline design of the system. The flowchart of the analysis is summarized in Figure 3. Each analysis model is briefly described in the following subsections.
Thermal resistance network model
The domain of the thermal resistance network consists of the RPV, the panel, and the coolant in the riser tubes. Heat transfer in the gap from the uninsulated RPV outer wall to the RCCS riser tubes/panels consists of natural convection and thermal radiation. The convective and radiative components are assumed to be independent processes in the model. Heat transfer from the panel to the coolant in the riser tube consists of natural convection. From the initial concept of MIGHTR RCCS, the panel plays the role of heat transfer fin. By assuming a sufficiently high efficiency of heat transfer between the panel and the riser tube, conductive heat transfer between the panel and the riser tube wall is ignored. A schematic of the representative thermal resistance network is shown in Figure 4.
Natural circulation loop analysis model
The domain of the natural circulation loop analysis consists of the top/bottom tanks, the collectors, pipes connecting the tank and collector, riser tubes, and downcomers representing half of the MIGHTR RCCS configuration, as shown in Figure 5. For modeling simplicity, it was assumed that a single-phase fluid flow in a steady state and negligible heat conduction from the panel to the fluid and inside the fluid. A minimum number of elbows were considered in the form loss pressure drop calculation. Calculations were iterated until a set of system dimensions and operation conditions which satisfy design requirements is sufficient to form a natural circulation flow, then the flow rate is calculated and the temperature difference between the hot and cold regions. Governing equation is from total pressure drop (Ptotal) across the loop expressed in Equation (1), which consists of the sum of pressure drop from friction (Pf), form loss (Pform), acceleration (Pac), and head loss (Pg) between two nodes divided into the inlet and outlet of each component.
Baseline Design of MIGHTR RCCS
The design space of system parameters was prepared based on the Boston Atomics inputs and major design requirements, where the selected design criteria are listed below. For the scoping study of the RCCS performance, some flexibilities in the design of the piping system could be allowed.
-The total water inventory of the system should be larger than ~ 200 tons as estimated for securing 7 days until boiled off. -The MIGHTR has 9 vertical load supports on each side of the RPV equally spaced, 1.25 m in the axial direction. The RCCS panel and the riser tubes will be located between the structural supports and should have compatible dimensions with those. -The top and bottom water tanks are assumed to be inside the reactor building. As the reactor building configuration is compact, the top and bottom tank dimensions are strictly restricted by height and width. -The gap between the RPV side wall and the panels is assumed to be 10-20 cm.
Design parametric study
Standalone RCCS analysis was performed with the boundary conditions of the RPV surface temperature of 220 C, and coolant bulk temperature of 60 C assuming them during normal operational conditions of RPV and desirable RCCS operating conditions. A total ~262,000 (4 points per 9 design parameters) sets of dimensions were compared to narrow down the design space range to have better performance in terms of the heat removal rate of RCCS as shown in Figure 6. Baseline dimensions of the MIGHTR RCCS were derived based on the results to have the best performance within design ranges. Some of the design parameters were adjusted from engineering judgment by consulting the project team. For instance, the elevation change of the inlet and outlet ports of the bottom tanks is set as 0.65 m to secure marginal space for engineering purposes, while a smaller value is preferable from the parametric analysis showing the minimal influence on the RCCS performance. In the next half of the year, we will proceed with in-detail components design work based on the derived RCCS baseline dimensions. It will include exploring configurations of top/bottom collector, heat sink options, and sectorizing top/bottom tank and relevant pipelines for system redundancy. Since standalone RCCS analysis was performed based on the lumped parameters, we have started system modeling using RELAP5-3D to incorporate the dimensional effect of the system configurations and details of system components. Then, coupled RCCS analysis for comprehensive system analysis will be performed coupling with primary system thermal-hydraulic modeling.
Task 2 Update: Primary System Thermal Fluids Analysis
Preliminary work has begun on the primary system thermal fluid analysis. A system-level approach with the System Analysis Module (SAM) [9,10] is being used to construct a thermalhydraulic model of the core region. In this model, shown in Figure 8, the average flow within assembly coolant channels is modeled in one axial dimensional. These coolant channels are coupled via heat convection to a two-dimensional representation of solid fuel assembly blocks to create a simplified prediction for the temperature distribution within the core. To verify the predictions made by this simplified model, a coupled 1D fluid-to-3D solid model [11] of the fuel assemblies will be used to create a more detailed and accurate prediction of the temperature distribution. Figure 8 Left: Fuel assembly cross section with coolant-fuel unit cell outlined. Right: Representative 2D SAM model with δ1 and δ2 representing fuel radius and effective matrix thickness respectively.
It is anticipated the bypass coolant flowing through gaps between assemblies will have a significant impact on the primary system thermal fluid model. As shown in Figure 9, predictions for assembly gap sizes have been made by collaborators at MIT based on thermal expansion and graphite irradiation calculations. Using these geometries, SAM will be used to predict the coolant flow distribution within the core based on calculations for the pressure losses in each assembly and bypass channel. Figure 10 shows a schematic of the flow paths in the SAM model with each channel connected to a common inlet and outlet branch. In addition to frictional losses in the channels, the impacts of form loss factors in the inlet and outlet plena will also be considered. Flow redistribution via cross-flow in axial assembly gaps may also play a significant role and can be included in future SAM models.
While the amount of heat removed by the bypass is expected to have a minimal impact on fuel temperatures (aside from the impacts of reduced assembly coolant channel flow rates), the increase in bypass flow temperature may have a significant impact on bypass coolant velocities and thus pressure losses, making it an important calculation. Work is ongoing to determine how to accurately implement thermal coupling between the coolant in bypass channels and the simplified two-dimensional assembly model.
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Editorial: Signals in motion
COPYRIGHT © 2023 Tan and Elgar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Signals in motion
Introduction
Animals use signals and cues to derive information about their environment, including the presence of food, enemies and mates, the location of nesting and provisioning sites, and the assessment of reproductive and social partners. The nature and reception of signals and cues is therefore a key focus of evolutionary and behavioral ecology, and our understanding of animal signals has expanded with the development of conceptual and technical advances. Nevertheless, our insights about the function and efficacy of animal color patterns remains largely shaped by a focus on stationary animals, typically in a static background, which rarely reflects the natural world (Cuthill et al., 2019;Tan and Elgar, 2021): most animals are mobile in their search for food and mates, and their surrounding environment is usually dynamic. There is considerable variation in animal signals within different signal modalities, including the color patterns of visual signals; the odor cocktails of chemical signals; and the amplitude and frequency of acoustic signals. These signals may act multimodally, which makes disentangling the additional contributions of animal motion and a dynamic environment even more challenging.
Our Research Topic Signals in motion asks how the efficacy of these signals to convey information to the intended or unintended receiver is affected by both animal movement and a potentially dynamic background. For example, there is emerging interest in how individual motion can reveal information about the signaler to the receiver but can also be a means of concealing visual cues to unintended receivers. In contrast, the impact of movement when signaling in acoustic or olfactory modalities has received little, if any, attention. The primary intention of this Research Topic is to draw attention to the importance of motion in animal signaling. Contributing authors report on diverse organisms with different behaviors, signaling modalities and background environments, and detail how motion is linked to signaling and how signalers and background movement may affect signal reception. There are few direct tests of the effects of signals in motion, but the studies in this Research Topic provide the initial steps toward understanding how motion affects signals.
Coevolution of morphology and signals
Morphology and patterns can act together to affect the signal that is perceived by predators (Linke et al.). For example, the shape of butterfly wings affects their aerodynamic performance (Ortega Ancel et al., 2017), but whether these shapes can act as cues that indicate unprofitability to potential predators has been largely overlooked. Linke et al. .
/fevo. . examined how the shape and markings of butterfly wings can affect signaling unprofitability to predators. Their experiments revealed that blue tits Cyanistes caeruleus can associate white bands and hindwing tails with the difficulty of capture of dummy butterflies. This raises the intriguing possibility that butterfly tails act both to signal evasiveness as well as to divert attacks to non-essential parts of the wing. The impact of animal movement on species that signal with volatile odors is rarely considered. Johnson et al. conducted interspecific comparative analyses to examine how the complexity of moth antennae have evolved with the mobility of female signallers, who use sex pheromones to reveal their location to males. These analyses revealed that the loss of flight in female moths has evolved more frequently in species where males have elaborate antennae, and that elaborate antennae in males evolved more frequently in species where females are monoandrous (where remating frequency is <30%). Together, these data highlight how elaborate antennae are associated with selection favoring efficient signal detection, which in turn allows females to invest less in movement and dispersal. suggest that the Carolina grasshopper use their contrasting hindwings to deter predators through three mechanisms: first, by startling predators through deimatic defense; secondly, by confusing the predators and disrupting their search images through protean defense; and finally, returning to crypsis. Pohl et al. examined the behavioral responses of phasmids at different ontogenetic stages to a wind stimulus (a proxy for a dynamic environment). They found that adult behaviors were mostly species-specific, while nymph behaviors varied with appearance and environmental condition. Pohl et al. suggest that the behavioral responses interact with the morphology of the insects-depending on their species and ontogeny-to help reduce detection or recognition cues by potential predators.
Animals employ a complex suite of behaviors in motion
Animals may employ signals from several modalities. For example, male wolf spiders Schizocosa are thought to use static and dynamic visual signals together with vibratory signals. Nevertheless, mating in S. retrorsa takes place in the absence of visual and vibratory stimuli. Kundu et al. show, experimentally, that these spiders use another signal modality-air particle movement or near field sound, that is generated by rapid leg waving.
Interestingly, these signals are specific to courtship: female foraging success did not depend on near field sound (Kundu et al.).
Many signals can vary over both space and time, requiring an experimental procedure that is more nuanced than the traditional approach of investigating static models against a static background. Miller et al. provide details on how the dynamic visual signals of birds can be investigated using three dimensional multi-spectral models, which allow measures of color (including in the UV), pattern, 3D shape and motion to be considered quantitatively. This novel approach is likely to be a crucial first step at analyzing visual signals in motion.
Signals in motion may serve to benefit the animal when it resumes a stationary position. Flash signals are displayed by cryptic animals when they move: for example, the cryptic blue-winged grasshopper Oedipoda caerulescens, flashes highly conspicuous blue wings when in flight. While this behavior may startle the predator, the conventional view is that the putative predator incorrectly assumes the prey is always conspicuous, which compromises its subsequent searching efforts. This view has some empirical support but the underlying process leading to this benefit has not been investigated. Sherratt and Loeffler-Henry use Bayesian search theory to show that the degree of the conspicuousness of a prey item is negatively correlated with the time the predator should give up searching for it in an area where it appears to have settled. The model makes several predictions that can be readily tested experimentally.
Environmental complexity and natural context
Most experimental studies of signaling utilize a static background, yet this is rarely the experience for animals (Cuthill et al., 2019;Tan and Elgar, 2021). Environmental noise is often dynamic and multi-faceted, and the individual effects on signals can be difficult to disentangle (Pohl et al.; Ramos and Peters). Ramos and Peters examined the displays of six closely related agamid lizards of the Ctenophorus decresii complex. They compared the signal structures and contrasts in the context of the lizards' natural habitats and showed that the signaling behavior of the different lizard clades reflected local adaptations to their specific habitats. Ramos and Peters suggest common morphological and behavioral traits are likely from the ancestral state, and their study highlights the importance of taking account of the natural habitat or environment when interpreting signals and signaling behavior.
Considering the natural context is equally important for theoretical modeling. Tan
Future directions
Several themes emerge within the Signals in motion Research Topic: the coevolution of morphology and signals; the complexity of behaviors in motion; and the impact of environmental complexity. A common insight across these papers is a reiteration of John Endler's seminal paper highlighting the importance of considering the natural context (Endler, 1990). It is clear, from the contributions to the Signals in motion Research Topic, that this includes the dynamic nature of both the signal and the background, neither of which are likely to be entirely stationary. While the papers in the Signals in motion Research Topic identify technical and logistic challenges in developing ways of experimentally and theoretically investigating dynamic signals and backgrounds, they also highlight a rich seam of research possibilities. We hope this stimulates increasing interest in dynamic signals in dynamic backgrounds.
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A Pexider system of additive functional equations in Banach algebras
In this paper, we solve the system of functional equations
Introduction
Let B be a complex Banach algebra and let g : B → B be a C-linear mapping. Mirzavaziri and Moslehian [1] introduced the concept of g-derivation f : B → B as follows: f (xy) = f (x)g(y) + g(x)f (y) (1.1) for all x, y ∈ B. Park et al. [2] introduced the concept of hom-derivation on B, i.e., g : B → B is a homomorphism and f satisfies (1.1) for all x, y ∈ B.
The stability problem of functional equations originated from a question of Ulam [3] concerning the stability of group homomorphisms. Hyers [4] gave a first affirmative partial answer to the question of Ulam for Banach spaces. Hyers' theorem was generalized by Aoki [5] for additive mappings and by Th. M. Rassias [6] for linear mappings by considering an unbounded Cauchy difference. A generalization of the Th. M. Rassias theorem was obtained by Găvruta [7] by replacing the unbounded Cauchy difference by a general control function in the spirit of Th. M. Rassias' approach. Recently, Lee et al. [8,9] extended more general functional equations, which were mixed types of additive, quadratic and cubic functional equations in Banach spaces, and Park and Rassias [10] applied the functional equation theory to study partial multipliers in C * -algebras. Many mathematicians developed the Hyers results in various directions [11][12][13][14][15][16][17][18].
The method provided by Hyers [4] which produces the additive function will be called a direct method. This method is the most significant and strongest tool to study the stability of different functional equations. That is, the exact solution of the functional equation is explicitly constructed as a limit of a sequence, starting from the given approximate solution [19,20]. The other significant method is the fixed point theorem, that is, the exact solution of the functional equation is explicitly created as a fixed point of some certain map (see [21,22]).
We consider a fixed point alternative theorem.
Theorem 1.1 [23] Assume that (B, d) is a complete generalized metric space and I : B → B is a strictly contractive mapping, that is, for all u, v ∈ B and a Lipschitz constant L < 1. Then for each given element u ∈ B, either for some positive integer n 0 . Furthermore, if the second alternative holds, then: (i) the sequence (I n u) is convergent to a fixed point p of I; (ii) p is the unique fixed point of I in the set In this paper, we consider the following system of functional equations: The aim of the present paper is to solve the system of functional equations (1.2) and prove the Hyers-Ulam stability of g-derivations in complex Banach algebras by using the fixed point method.
Throughout this paper, we assume that B is a complex Banach algebra.
Stability of the system of functional equations (1.2)
We solve and investigate the system of additive functional equations (1.2) in complex Banach algebras. Proof Letting x = y = 0 in (1.2), we get 2), we have for all x ∈ B. Setting y = 0 in (1.2), we obtain 2), we have for all x, y ∈ B. Hence the mapping f : B → B is additive and thus by (2.1) the mapping g : B → B is additive.
Using the fixed point technique, we prove the Hyers-Ulam stability of the system of the additive functional equations (1.2) in complex Banach algebras.
for all x, y ∈ B. Then there exist unique additive mappings F, G : B → B such that for all x ∈ B.
Proof Putting x = y = 0 in (2.3), we get 3), we obtain (2.4) and we consider inf ∅ = +∞. Then d is a complete generalized metric on (see [25]). Now, we define the mapping J : ( , Actually, let δ, γ ∈ ( , d) be given such that d(δ, γ ) = μ. Then for all x ∈ B. Hence for all x ∈ B and all δ, γ ∈ . Using (2.4), we obtain for all x ∈ B, which imply that d(f , J f ) ≤ L 2 and d(g, J g) ≤ L 2 . Using the fixed point alternative, we deduce the existence of unique fixed points of J , that is, the existence of mappings F, G : B → B, respectively, such that with the following property: there exist μ, η ∈ (0, ∞) satisfying for all x ∈ B. Since lim n→∞ d(J n f , F) = 0 and lim n→∞ d(J n g, G) = 0, for all x ∈ B. Using (2.2) and ( 2.3), we conclude that for all x, y ∈ B, since L < 1. Therefore by Lemma 2.2, the mappings F, G : B → B are additive.
Corollary 2.4 Let η, p be nonnegative real numbers with p ≥ 1 and let f , g : B → B be mappings satisfying for all x, y ∈ B. Then there exist unique additive mappings F, G : B → B such that Proof The proof follows from Theorem 2.3 by taking L = 2 1-p and (x, y) = η( x p + y p ) for all x, y ∈ B.
Stability of G-derivations in Banach algebras
In this section, by using the fixed point technique, we prove the Hyers-Ulam stability of g-derivations in complex Banach algebras.
for all x, y ∈ B and all λ ∈ T 1 . Then the mappings f , g : B → B are C-linear.
Proof If we put λ = 1 in (3.1), then f and g are additive by Lemma 2.2.
Letting y = x in (3.1), we have for all x ∈ B and all λ ∈ T 1 . Since the mappings f and g are additive, for all x ∈ B and all λ ∈ T 1 . So by Lemma 2.1 the mappings f and g are C-linear.
Theorem 3.2 Suppose that : B 2 → [0, ∞) is a function such that there exists an L < 1 with for all x, y ∈ B. Let f , g : B → B be mappings satisfying for all x, y ∈ B and all λ ∈ T 1 . Then there exist unique C-linear mappings F, G : B → B such that F is a G-derivation and for all x ∈ B.
Proof Let λ = 1 in (3.3). By Theorem 2.3, there are unique additive mappings F, G : B → B satisfying (3.5) and (3.6) given by for all x ∈ B. Using (3.2) and (3.3), we conclude that for all x, y ∈ B and all λ ∈ T 1 , since L < 1. Therefore by Lemma 3.1, the mappings F, G : Corollary 3.3 Let p, q, η be nonnegative real numbers with p + q > 2 and let f , g : B → B be mappings satisfying ⎧ ⎨ ⎩ f (λ(x + y)) + g(λ(yx)) -2λf (x) ≤ η x p y q , g(λ(x + y))f (λ(yx)) -2λg(y) η x p y q and f (xy)f (x)g(y)g(x)f (y) ≤ x p y q for all x, y ∈ B and all λ ∈ T 1 . Then there exist unique C-linear mappings F, G : B → B such that F is a G-derivation and x p+q , G(x)g(x) ≤ η 2 p+q -2 x p+q for all x ∈ B.
Proof The proof follows from Theorem 3.2 by taking (x, y) = η x p y q for all x, y ∈ B.
Choosing L = 2 2-p-q , we obtain the desired result.
Conclusion
We solved the system of functional equations (1.2) and we proved the Hyers-Ulam stability of g-derivations in Banach algebras.
x, y) = 0 for all x, y ∈ B. SoF(xy) = F(x)G(y) + G(x)F(y)for all x, y ∈ B. Thus the C-linear mapping F is a G-derivation.
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Model Analysis of Axial PM Bearingless Flywheel Machine
The special rotor structure of the axial PM bearingless flywheel machine(APM-BFM) makes its critical speed more easily affected at high speed, but there are few studies on its rotor dynamics, especially under load conditions. In the paper, the model analysis study of the APM-BFM is carried out. First, the mechanism model of APM-BFM is used to explain its structure and its system is analyzed in conjunction with the experimental prototype; The rotor centroid deviates from the center of rotation due to rotor eccentricity, which is an important reason for the serious complex vibration; and then, the rotor mode principle is explained from the mechanism model. To be more specific, the finite element method and the analytical technique are used to compare and check the accuracy of the finite element method model analysis; after that, the rotor model is simulated and studied. Finally, the influence of bearing stiffness, gyro effect and flywheel load on critical speed is analyzed, which provides theoretical basis for high-speed and stable motor control.
I. INTRODUCTION
Flywheel Energy Storage (FES) is a mechanical energy storage technology whose advantages include high power and energy density, fast response speed and long life. FES has received a lot of attention because of its unique advantages in the fields of power grid frequency regulation, new energy grid connection, rail transportation, uninterruptible power supply, aerospace satellites, and so on [1]. Due to the highspeed operation of the flywheel, mechanical bearings will produce a lot of heat, and the cost of the cooling equipment to ensure steady operation is high. The magnetic bearing (MB) allows the shaft to rotate without touching anything, which reduces heat and saves cost. As a result, combining a MB with a switched reluctance machine (SRM) to create a bearingless switched reluctance machine (BSRM) with compact structure, high critical speed, and minimal friction is a compelling option. This can be incorporated into Flywheel Energy Storage Systems (FESSs) to form a bearingless flywheel machine (BFM), which can improve system integration, critical speed, and reliability, and be known as the ideal choice of flywheel energy storage motor [2].
An axial PM bearingless flywheel machine (APM-BFM) separates the stator and rotor cores into two phases (phase A and B) along the axial direction. The PM is attached between the two-phase stator cores, giving an axial path for the PM flux [3], allowing for four-degree-of-freedom suspension through bias magnetic flux generated by the PM. APM-BFM merges two sets of windings into one motor, providing for four degrees of freedom suspension and integrated charging or discharging operation, which greatly improves system integration and reduces system power consumption. In recent years, it has received considerable attention. Reference [4] proposed that the use of a magnetic guide sleeve improves the magnetic permeability and reduce the amount of rare earth permanent magnet materials consumed, and the design of pole shoe teeth effectively improves the output torque and suspension force. To construct an APM-BFM nonlinear dynamic equivalent magnetic network model, reference [5] divided the stator-rotor air gap magnetic circuit into multiple regions and introduced local saturation coefficients to consider the local magnetic saturation of the rotor yoke, which improved the model accuracy. The APM-BFM equivalent thermal network model was developed in Reference [6] to solve the difficulties of high thermal load and small heat dissipation area of the centralized winding, and the validity of model was confirmed using magnetothermal coupling simulation. There has been a lot of studies on the mechanism model, electromagnetic model, and magneto-thermal coupling model of APM-BFM, but there is little study on the rotor motion model features under highspeed operation.
High-speed and ultra-high-speed flywheel rotor stability problems are particularly prevalent in FESSs, which makes the model characteristics of rotor motion become a hot topic, and it is also the key to exploit the high-speed superiority of APM-BFM. Dynamic analysis of the APM-BFM model is needed to prevent the resonance-induced instability problem due to the influence of system bearing stiffness, gyroscopic effect, rotor structure, and other variables that cause the APM-BFM speed to be closer to the critical speed. When evaluating complex rotor systems, dynamic analysis methods such as finite element analysis (FEA) and transfer matrix method (TMM) are used [7]. When studying complicated rotor systems, the matrix order in TMM does not grow with the number of system degrees of freedom, which makes the computation fast and compact, but prone to numerical instability. FEA is characterised by discretizing the continuous object, dividing it into finite units, interpolating each unit, and establishing the interpolation function. FEA is more complicated than TMM, but it has better computation accuracy and can effectively avoid numerical instability, which makes it frequently utilized and has become a generally acknowledged and successful algorithm.
Based on the FEA of electromagnetic and structural coupling, the finite element model of SRM rotor dynamics was established to simulate the dynamic characteristics of rotor eccentricity [8]- [9]. FEA was used to analyze the rotor mode and inherent frequency of high-speed PM motor, and the critical speed of motor in the free state. Bearing position, and actual operating condition were obtained, and compared with the experimental method to verify the effectiveness of the model method [10]- [11]. FEA was used to calculate the inherent frequency of high-speed motor, and the influence of support stiffness and rotor gyroscopic effect on the inherent frequency of the system were obtained [12]- [13].
APM-BFM is a new structure of magnetically levitated motor, lots of previous papers on the mechanism model and magneto-thermal coupling of APM-BFM have ignored the operating mode characteristics of APM-BFM under highspeed operation, and its outer rotor structure will have obvious gyroscopic effects under high-speed drive. However, little attention has been paid to the performance of the APM-BFM system in actual operation. This paper proposed the influencing rule of bearing stiffness, gyroscopic effect and flywheel load on APM-BFM from the perspective of model dynamics. Based on the fundamental structure and the experimental prototype of APM-BFM system, the FEA method is introduced into APM-BFM for model analysis and simulation, so as to lay the theoretical basis for the high speed and high stability operation of APM-BFM in the flywheel field.
A. STRUCTURE OF APM-BFM
The structure of APM-BFM is shown in Fig.1, including rotor, torque winding, suspension winding, isolated magnetic ring, torque pole, suspension pole, shaft, permanent magnets, phase A and phase B. The outer rotor of APM-BFM is installed inside the flywheel and integrated with the flywheel. There are 12 rotor poles of equal width evenly distributed on the inner side of phase A and phase B rotors respectively, and the axes of the two-phase rotors differ by 15 . An axially permanent magnet is installed in the middle of the two-phase stators. Each phase adopts inner stator and outer rotor, which are made up of a 12/12 pole arrangement. Four suspension poles (wide tooth) and eight torque poles (narrow tooth) constitute the 12 poles of the inner stator. The APM-BFM achieves decoupling of the suspension and torque by using a magnetic isolation ring between the torque pole and the suspension pole. It utilizes torque windings and suspension windings to realize rotor rotation and radial four-degree freedom suspension, and then the flywheel operates to realize the conversion between mechanical energy and electrical energy.
III. ROTOR MODE ANALYSIS IN PRINCIPLE
In the high-speed functioning of the APM-BFM, rotor eccentricity is a natural occurrence. The eccentricity of the rotor causes the centre of mass of the rotor to wander from the rotation centre, resulting in noticeable and complicated vibration phenomena. This is a significant factor impacting high-speed operation stability of the APM-BFM, and the rotor model principle must be investigated.
According to the finite element theory of elasticity, the kinematic equations of the rotor system can be expressed as： Here: M represents the mass matrix, C is the damping matrix, K is the stiffness matrix, x is the displacement vector, x is the velocity vector, x is the acceleration vector, and F(t) is the system load. As long as there is no deflection of the rotor rotation, the differential equation of rotor dynamics can be stated as: Here: m stands for the rotor mass, Here: c are the rotor's damping coefficients in x, y, and z directions respectively; k are the rotor's bearing stiffness coefficients in x, y, and z directions, respectively. T he displacement of the flywheel rotor system may be stated as： Here: 0 r is a constant. When no external force is applied, both The imaginary component of formula (6) represents the intrinsic frequency of the rotor in free rotation, and S has two roots, positive and negative. Idealizing the rotor's surroundings with ignoring external damping, the rotor's undamped modal frequency in free rotation under shaft-supported circumstances is: Here: 1,2 is the motor rotor's inherent frequency in forward and against precession, respectively. In the absence of a rotor, the motor's uniform mass rotor is removed and regarded as a free rotor, at which point the rotor's intrinsic frequency can be expressed as: Here: E is the outer rotor material's modulus of elasticity; the outer rotor material is silicon steel sheet 50W470. J is the rotational inertia of outer rotor, is the rotor density, D is the rotor diameter. The values of constant are listed as follows: Table Ⅲ.
IV. ANALYSIS OF ROTOR MODE SIMULATION
The previous sections analyzed the APM-BFM system structure, whose special structure makes the process of FEA difficult, and therefore rare literature studies critical speed of APM-BFM, analyzing the influence of bearingless stiffness, gyroscopic effect, flywheel load on critical speed which are beneficial to study the modal characteristics of APM-BFM under high speed operation.
1) PRE-PROCESSING OF FEA ANALYSIS
3D model is imported into the workbench and simplified, and then the bearing is converted to a spring unit with stiffness based on the APM-BFM structural characteristics, so that the stiffness of the spring unit can be changed to see how the bearing stiffness affects the critical speed. A simple finite element module is shown in Fig.3.
FIGURE 3. The system simplified model of APM-BFM
The mesh division level is set to 2 and free mesh division is utilized. The geometry of the APM-BFM is discretized automatically into basic building blocks, that is tetrahedra in 3D. The assembly of all tetrahedra is referred to as the finite element mesh of the model or simply the mesh, and the mesh is automatically refined to achieve the required level of accuracy in field computation. Fig.4(a) illustrates the mesh section. Fig.4(b) demonstrates how Workbench is used to build up the pre-stress model analysis and how the computation is done by inputting the boundary pressure values.
2) CALCULATION OF CRITICAL ROTOR SPEED
The model of the APM-BFM system is analyzed using FEA, and the model analysis is utilized to understand the rotor's vibration characteristics. The vibration pattern of the system from the 1st order to the 6th order is shown in Fig.5. 2 nd order model deformation locations are mainly located at the motor shell and the connection between the motor shell and the induction ring for sensors, which indicates that the force here is greater. Under the 3 rd , 4 th , and 5 th order model conditions, the stress deformation near the connection between the motor shell and the induction ring for sensors becomes increasingly apparent as the rotating speed increases. This means that the higher the APM-BFM speed, the stronger the motor shell material should be, and the stronger the material at the motor shell-to-sensor inductor ring connection should be.
The intrinsic frequencies associated with each rank are listed in Table Ⅳ. It shows that the 1 st order modal frequency corresponding to the stiffness of 10 12 N/M is 49.421Hz, and the corresponding speed is 2965.3r/min. At this time, the APM-BFM system vibrates axially. The 2 nd and 3 rd order inherent frequencies are similar, representing the 1 st critical speed of bending. The 4 th and 5 th order inherent frequencies are similar, representing the 2 nd critical speed of bending. The critical speed value is high, and when the rated speed is close to the critical speed, the motor will vibrate violently. Therefore, the safe working range of the 1 st order bending mode and the 2 nd order bending mode is between the two critical speeds.
B. THE INFLUENCE OF BEARINGLESS STIFFNESS ON THE CRITICAL SPEED
The influence of bearing stiffness on APM-BFM critical speed is further investigated. Fig.6 depicts the relationship between the bearing stiffness and the 1 st order to 4 th order critical speed of the motor. The bearing stiffness has different impacts on the critical speed in different modes, as shown in Fig.6. In the 1 st order mode, bearing stiffness has little effect on the rotor critical speed, however in the 2 nd , 3 rd , and 4 th order modes, bearing stiffness has a greater impact on the rotor critical speed. Furthermore, as shown in Fig.6, the critical rotor speed changes more slowly in the 2 nd , 3 rd and 4 th order modes when the bearing stiffness is less than 10 9 N/M; in the 2 nd order mode, the critical rotor speed remains relatively stable when the bearing stiffness is between 10 8 N/M and 10 10 N/M, whereas the critical rotor speed increases faster in the 3 rd and 4 th order modes when the bearing stiffness is greater than 10 9 N/M. When the rotor 2 nd order model bearing stiffness is more than 10 10 N/M, this phenomenon happens. It can be seen that when the bearing stiffness is between 10 7 N/M and 10 9 N/M, the influence on the critical speed is minimal; however, when the bearing stiffness exceeds 10 9 N/M, the effect on the critical speed is significant, and as the stiffness rises, the critical speed increases more rapidly.
C. The GYROSCOPIC EFFECT ON CRITICAL SPEED
The rotational inertia of the APM-BFM flywheel rotor will not change drastically due to the addition of any form of load, but the gyroscopic effect will have an influence on the critical speed. The gyroscopic effect of the rotor should be addressed in the dynamics simulation of APM-BFM, the impact of gyroscopic effect on the motor should be verified using FEA, and the Campbell diagram is created as shown in Fig.7. The red line segment with Ratio=1 in Fig.7 denotes the line segment where the flywheel speed and critical speed are equal, from which the system's critical speed value may be calculated, as indicated in the red square. Under the impact of the gyroscopic effect, the APM-BFM rotor mode may be divided into forward and reverse precession as the speed rises, and the forward precession frequency increases as the speed rises, while the reverse precession frequency decreases. However, as shown in the Fig.7, the structural design of this study reduces the influence of the gyroscopic effect on the critical speed by making the change of both forward and reverse precession frequencies relatively modest.
D. EFFECT OF FLYWHEEL LOAD ON CRITICAL SPEED
The rotor structure will alter in real-world operation as a result of varied flywheel loads, and the impact of the flywheel structure on the critical speed cannot be overlooked. Fig.8 depicts the APM-BFM model with the flywheel module. The green and blue sections of the illustration depict the six-flywheel load rings installed on the housing, each flywheel load ring weights 1kg, a total of 6kg. The effect of carrying the flywheel load ring on the critical speed is studied using FEA, and Table IV shows the inherent frequency of the APM-BFM system carrying the flywheel load ring. Comparing Tables Ⅳ and Ⅴ, it can be seen that the 1st order critical speed increases to 6494.2r/min when the flywheel load ring is carried, which is roughly twice the critical speed without the flywheel load ring, and there is no bending critical speed at the APM-BFM speed of 14000r/min, indicating that the rotor critical speed is effectively increased by adding the flywheel load ring.
Ⅴ. APM-BFM STATIC OPERATION ANALYSIS
The vibration stabilization is achieved using conventional PID with P=2, I=60, D=0.006. The blue trajectory curve represents the x-direction amplitude curve of APM-BFM static levitation, whereas the red trajectory curve represents the y-direction amplitude curve, as shown in Fig.9. At first APM-BFM achieves 0.15mm where is the center of mass displacement in the x-direction, then achieves stable levitation in the x-direction within a certain range after 50ms of vibration, and the amplitude change in the y-direction occurs at 0.65s due to the small value given by the limiting link, after which APM-BFM achieves stable levitation in both the x and y directions simultaneously.
Ⅵ. CONCLUSIONS
This paper focuses on the operation stability of the APM-BFM, emphasizing its high-speed superiority, develops a simulation model, and uses FEA to undertake a joint simulation analysis of the APM-BFM system model. The following are the primary conclusions: (1) By comparing and evaluating the FEA and the analytical method, the correctness of the FEA was validated, and its error range was estimated.
(2) If the APM-BFM speed is raised, the material strength of motor shell and the connection between the motor shell and the induction ring of sensors must be improved.
(3) Both the 1 st and 2 nd critical speeds of bending are high, and the APM-BFM can run in a safe range without resonance until it achieves a steady speed of 14000r/min.
(4) When the bearing design stiffness is between 10 7 N/M and 10 9 N/M, the critical speed effect is essentially nonexistent, and when the bearing stiffness surpasses 10 9 N/M, the critical speed change accelerates.
(5) The critical rotor speed is effectively raised by adding a flywheel load ring, demonstrating that the APM-BFM can ensure that the rated speed is far from the critical speed under load to avoid resonance affecting operation.
In general, improving the edge strength of the motor can reduce the deformation, the rotor structure is designed as a rigid rotor that can effectively avoid the resonance phenomenon, operation range of the APM-BFM increases with the increase of bearing stiffness and flywheel load, and using the traditional PID method, the stable suspension of APM-BFM can be realized in a short time. The simulation and analytical results presented in this study give the theoretical foundation for optimum design and high-speed stable control of APM-BFM.\===
. The above document has 2 sentences that start with ' FEA was used to',
3 sentences that end with 'the critical speed',
2 sentences that end with 'critical speed of bending',
2 paragraphs that end with 'ON CRITICAL SPEED'. It has approximately 3069 words, 110 sentences, and 37 paragraph(s).
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Volatile Network as a Simple Memory Model
: Technical information systems, from PCs to supercomputers, are characterized over time by ever-increasing storage capacities, while biological systems are permanently characterized by their trainable memory abilities. Although both systems are not comparable with each other, because they are based on different phenomena, the existing efficiency of biological systems offers a constant borrowing for the further development of technical systems. For this purpose, it is necessary to develop technical equivalence models. The following considerations aim to reproduce the factually limitless abilities of biological systems to store memory content as a result of the plasticity of neuronal populations. The difference between technical and biological systems becomes particularly clear under this aspect: while the development of technical systems aims to permanently increase the existing storage capacity, biological systems are based on independently separating relevant from irrelevant information and, moreover, permanently reorienting existing memory structures, called plasticity. Accordingly, the transmitter flow between the neurons constantly changes in direction and intensity. A network with a transient topology that is marginally able to model a memory-capable neuronal population characterized by a permanent loss of neuronal contact points is proposed for discussion. Such a loss permanently changes the direction and intensity of the transmitter flow between the neurons. Another focus of the topic is the question of how different stimuli, meaning optical, acoustic, tactile, etc., can become one and the same memory description of a neuron population. Here it is assumed that a pre-processing takes place in the biological system in the form of a functional transformation, the result of which is a neutral basis for representing the information. Although such an assumption seems to be highly speculative, a discussion of it would contribute to answering the question of which physiological mechanisms have to be taken into account to explain memory phenomena, reproduced in a model.
Introduction
Architectures of technical and biological systems are fundamentally not comparable with each other, neither in their structure nor in their function. Nevertheless, a technical borrowing from biological model systems is of interest, although a formal transfer of neuronal into technical structures has not proven to be expedient. Although the discovery of gestalt neurons (Hubbel and Wiesel) in the cat brain in the second half of the last century was important for the development of artificial neural networks, it soon turned out that in a neuron population a single neuron has no singular significance [1]. The assumption of a so-called grandmother neuron, which reacts singularly to an excitation in lateral independence, is irrelevant. Rather, the interest in brain research has developed in the direction of finding out which track (: engram) neuronal excitation takes in a population in space and time. Richard Semon (a member of the Leopoldina) coined the term engram as the permanent memory entry and thus explained the inheritance of properties [2]. In this context, it is of interest how engrams permeate each other, how they can self-organize from dysfunctional to functional areas of the brain (: plasticity). These effects inspired and still inspire the development of technical systems for information processing, for example those with associatively organized storage mechanisms.
Equally interesting are the different signal carriers in the case of a technical borrowing from biological model systems. One and the same system not only picks up different signal carriers in parallel, but also processes them together in order to subsequently store them in one and the same neuron population. This applies, for example, to the overall impression of space and acoustics in a concert hall and in an opera house. Due to the complex perception of space and acoustics, a memory entry is formed that differs significantly from the singular perception of the acoustics [3].
The question is: Which signal carriers represent a lasting complex impression in one and the same biological system?Brain researchers are responsible for answering such a question. In the following, the question of whether the original memory content received via a certain channel is subject to a functional transformation before being stored in a neuron population is attempted, which offers a common basis for all channels [4].
A next question is: How does the biological system independently organize the whereabouts or loss of recorded memory content. In the event that content is of negligible relevance, it will be deleted, formulated in the technical terminus, otherwise it will be preserved. To simulate this phenomenon, a technical arrangement is presented, consisting of a network with volatile topology and an integrated memory stimulator. Parameters are consistency rate λ and memory ability η. Both parameters together measure the memory loss along the trace of an engram, equated along a time axis. No matter how intense the ability to remember, any memory content is only temporary and is lost over time.
Storage of Memory Contents
A nervous system represents a higher-dimensional action space, consisting of a myriad of locations for accommodating neurons, which are linked to one another via synapses. Sperry, Nobel Prize winner for medicine, held the view that humans are born with an excess of synaptic connections, but over time they degrade in a problem-oriented manner in order to develop over time their individual, unmistakable nature [5]. According to this, neural connections only exist temporarily, which raises the following questions from a system-theoretical point of view: 1) What transformation exists between the arousal environment and the structure of the nervous system, derived from this the question: 2) Who or what determines the coupling weights of the synapses, closely related question: 3) What breakdown processes take place in the nervous system?Question (1) refers to the large number of qualitative and quantitative stimuli on the nervous system, their filtering and their entry into existing memory structures. Due to the plasticity of the nervous system, it can be expected that the topology of the nervous system will adapt to this complexity. Although a dedicated description of this with the help of systems theory would be interesting, for example to be able to distinguish between self-perception and external perception, it would contradict any capacity for tolerance.
However, such an ability should be indispensable for the coexistence of living systems.
Question (2) can be answered decisively. Existence and perception of stimuli are two different phenomena. Sensory organs such as the light-sensing cells in the visual system of vertebrates receive an optical pattern as a conglomerate of a multitude of complex light stimuli and convert them in detail into generator potentials for further processing in the downstream layers. Finally, the storage of the optical pattern in a memory structure is not true to the texture, that means isomorphic, but relational. It is not the local intensity distribution of the pattern that is stored in a memory structure, but rather the relationships between the locations of the intensities in the pattern, referred to as coupling weights.
These entries in the memory structure are autonomous and volatile in order to guarantee an orderly filing of memory content within the memory structure over time.
Question (3) relates to gerontological and pathological changes in the nervous system. As a result, the memory structure increasingly loses its ability to store memory content, caused, for example, by plaque formation on the membrane of postsynaptic neurons, but also by tauopathy inside the neuron [6,7,8].
Interactions Between the Points in Space
Given is a population of a large number of neurons coupled to each other via synapses, modeled as a traffic field of nodes that interact with each other via an embossed coupling structure. The interactions of the nodes are to be simulated. A marked coupling flow circulates between them, controlled by an associated reference field (Figure 1).
From an abstract point of view, the traffic field exists as an n-dimensional accommodation R of m space points P from P , . . ., in an n-dimensional discrete Action space , i.e. R : P → , where ξ n-dimensional coordinate tuple of P in . A marked corpuscle flow is driven across the traffic field, the orientation of which is determined both by the topology between the resources and by the reference distribution between them.
The dynamics of the traffic field is observed at discrete points in time τ on a discrete time scale in a n-dim.discrete time-based observation space × .
; , … , ; !" At the initial point in time τ 0 , an inhomogeneously distributed concentration pattern may act on all m spatial points P from P, referred to as the excitation pattern X = $ , . . ., % , … , & of the traffic field. Diffusion is a concentration equalization through undirected random movements [14]. In the present case, it is a question of controlled referencing by a reference field. The necessary references A(P',P;τ) from P to P' at time τ are to be calculated. The time invariance A P′, P; τ granted here guarantees the maintenance of the inner dynamics of the action space during the balancing process.
The interactions manifest themselves in the permanent referencing of emitting through emitting nodes, as a result of which the status of the nodes and thus their weighting in relation to one another changes constantly. Under certain circumstances, and this is the actual goal of the procedure, some nodes in the traffic field lose their relevance and must therefore be relegated. Likewise, all incoming and outgoing connections are eliminated. The aim is to achieve a maximum number of connection extractions in this way.
The process is modeled taking into account the time invariance in the n-dim.discrete action space ℤ , the simulation on the other hand in n-dim. Vector space R n .
Referencing Between the Spatial Points
Multidimensionality of a discrete space means splitting the space into a corresponding number of coordinate axes ξ. In ℤ , the function values X(ξ) in the n-tuples ξ =(ξ1, …,ξn) are interpolation points of a function f in a continuous vector space R. In fact, the metric distance is the Interpolation points in relation to each other for the formation of the discrete Fourier transform * X ξ ; k as a discrete spectral function A(k) of X(ξ) are of no importance, as a result of which a 1-dim vector space R 1 can suffice for the formation of *. Each n-tuple ξ =(ξ1, …,ξn) in ℤ is assigned an argument x from f(x) in R 1 .
Suppose f(x)=f(x±nL), then -→ .: * -; / = 0 / = . W is a column and row ordered coefficient matrix for performing the Discrete Fourier Transform. W F→E generates the spectra a 0, …,N-1 weighted with the corresponding Fourier coefficients cosJω • x • k ,…, 2 K the function value f(x) at the point x into arousal pattern.
In a figurative sense, the architecture of (2-2) describes the interaction of the traffic and reference fields. If the elements of the traffic field do not exist in the original but in a previously determined spectral range, the sum of the references of all spatial points P to a spatial point P' represents its function value f in the original [9].
All references between the spatial points, accordingly all interactions between the neurons of a population, are positively signed. Accordingly, the coefficients A(k)cos(ω 0 xk) in (2-2) are to be normalized. Let ] = 0 / ABC 9 ./| ., / = 0, … , ?− 1 set of all Fourier coefficients, then 0 ≤ `M is positively signed reference from P k to x P, the space points from P.
Topology Reduction
In biology, the term "evolution" stands for the increase in resilient properties of a biological system or for overcoming inhibiting properties. At the same time, changes of state also take place in physical systems. Change energy is consumed for this. If this energy is spent inside a system and no external supply is supplied, it retains its assumed state. A capacitor, for example, is able to store energy by separating charges. This requires internal energy, mediated by an applied voltage. The capacitor has reached its capacity limit, its change energy is exhausted, and there is no longer any charge separation. Its condition is preserved [10].
With regard to the energy supply and capacity limit of physical systems, a borrowing can be used to optimize the topology of neuronal memory structures. Memory structures, so-called engrams, are formed, they penetrate each other, interact with each other and thus process information. Frequencies of synaptic connections taken thereby reflect their relevance for storing memory content.
From a physical point of view, the formation of engrams is an energy-consuming process, supported, among other things, by the consumption of glucose, the more intense the more frequently a synaptic connection is used. It seems plausible to dissolve less frequently used connections in order to gain energy for more frequently used ones. The reduction algorithm in a discrete action space for modeling and simulating the ability to remember is based on this assumption [11].
If all nodes continue to exist, the topology reduction in the discrete action space is carried out solely by a conditional removal of existing arcs between them.
First, the most weakly referenced node of all arcs is declared as one to be removed.
Should the arc so removed result in either loss of mutual reachability between all nodes, indicated by a minimum matrix M, or loss of corpuscular flow balance between nodes, the removal is annulled. Subsequently, the second weakest referenced of all arcs is declared as one to be removed, and so on.
The reduction ends when no more arcs can be found that fulfill requirement 2.
Between the nodes of the traffic field (Figure 1), corpuscular flows circulate, the thicknesses of which change as arcs are removed, so they have to be recalculated after each removal.
According to its references, each node emits and emits its contribution to all corpuscle flows in the traffic field, consuming time. The transfer times between the nodes are related to their references. Balance exists when the time consumption for corpuscle immission and emission correspond to each other. Each node P emits corpuscle streams in a distribution time and emits incoming corpuscle streams in a collection time in the time shadow, parameterized by 1) Preparation time c for the transfer of a corpuscle massif along an arc, 2) Transfer time q of a corpuscle along an arc, depending on 3) Velocity v of the corpuscle transfer and actually taken 4) Path length s of a corpuscle. The demand for balance in relation to the transfer time between the nodes results in a linear system of equations K ⋅ l ⊗ b for the calculation of balanced sizes of circulating corpuscle flows.
Memory Stimulator
From a system-theoretical point of view, memory is understood to mean the acquisition and maintenance of a state. Richard Semon (Member of the Leopoldina) explained the memory ability of a neuron population with the formation of a memory trace (: engram). The Freiburg scientists M. Bartos and Th. Hainmüller [12] support this phenomenon and suspect that memory formation in the brain is accompanied by a change in synaptic connection strengths between inhibitory and excitatory nerve cells (: synaptic plasticity). In this context, it is of interest how engrams permeate each other, how they can self-organize from dysfunctional to functional areas of the brain (: plasticity). Neural connections only exist temporarily, and the following is of interest: What is the transformation between the arousal environment and the structure of the nervous system, derived from this the question: Who or what determines the coupling weights of the synapses, closely related question: What breakdown processes take place in the nervous system?
Conditional retention and loss of memory content is modeled in Figure 3.
Not every neuron in the population is connected to every other neuron via synapses, an adjacency matrix A models the concrete topology. In view of Sperry's assumption that humans are born with an excess of synaptic connections, the adjacency matrix is fully occupied in the initial state, excluding a connection with oneself.
Synapses change their connection strength; the presynaptic release of transmitter molecules can vary. Catalysts (: enzymes) influence their transfer across the synaptic cleft. They are temperature-dependent, their effect in the organism is linked to the ambient temperature. The receptors of the postsynaptic membrane bind the transferred molecules.
Figure 3. A reference matrix Y results from the Fourier transform of an excitation pattern X(j). The program MPS.jar constantly simulates the topology reduction the population. A resulting memory loss can be compensated for within limits by a memory simulator.
For the duration of their connection, sodium channels open for the influx of positively charged sodium ions into the interior of the postsynaptic neuron. In addition, the connection strength of a synapse is related to the frequency of its use. In the simulation model [8], a synapse is characterized by its transfer speed for transmitter molecules, parameterized by the elements v of a speed matrix V, but also by the relative frequencies y as elements of a reference matrix Y.
After each influx of NA+ ions, a neuron goes through a refractory period -a time interval in which no new transmitter molecules can be released. This property takes into account a refractory matrix C whose elements c are called refractory periods. From a physical point of view, this is how a neuron protects itself from energetic exhaustion.
The simulation model [13] for retention and loss of memory content exists in a discrete observation space. All components, here the neurons of the population, exist Neuronal status S: The simulation network for the neuron population loses its consistency λ with an increasing number ε of reduction steps (: number of direct couplings), and accordingly also the ability to reconstruct an initial excitation X(j). This is counteracted by the effort required for memory training, parameterized by the ability to remember η. Both parameters λ and η determine the neuronal status S(ε) of the network in the reduction step ε for the simulation of the neuron population. A distinction is made between imprinting and memory. The imprinting of a network means the initial excitation pattern X(j). It loses significance as a result of the ongoing reduction in direct connections between the nodes. The imprint that still exists in a reduction stage ε depends on the existing ability to remember η. The memory stimulator relativizes the interplay between loss of significance and imprinting. Its task is to filter out the smoothing of the initial excitation pattern X(j) according to the neuronal status S by means of selectors f. A distinction is made between the selectors f _U for the area around the embossing and f _K along the embossing.of the secondary excitation distribution X''(j) -the output from the memory stimulator (Figure 4).
The correlation r X j ; X {{ j describes the quality of the memory stimulator.
Example
In order to clarify properties, the following explanations use both the planar representation of locations as a 2-tuple (j 1 ,j 2 ) and (k 1 ,k 2 ) in 1…11 and a linear representation as a 1tuple (j) in the following explanation and (k) given in 1…121.
A neuron population (Figure 5) is to be modeled and simulated by a network with a volatile topology. The discrete distance between the neurons is measured as d, their coupling intensities are simulated by the relative reference frequencies y. Figure 5 shows a section of a neuron population in which the initial excitation pattern X(j) is entered and subsequently smoothed out by the abolition of synaptic connections to X''(j). The effect of such a smoothing can be determined by the dedicated distribution of the transmitter densities on the membrane surfaces of the neurons as well as the local flux density of transmitter currents between the neurons. This process is modeled by the volatile network described above, where the corpuscle density in the nodes of the network corresponds to the transmitter density in the population and the flux density of circulating corpuscle currents corresponds to the flux density of transmitter molecules. If there is consistency λ of the fleeting network, these densities are used as indicators for the characterization of memory retention of X(j), parameterized by the memory depth η. It is plausible that the memory retention for one and the same excitation pattern in η is pronounced differently.
Figure 6 shows a discrete excitation pattern in a planar X(j 1 ,j 2 ) and linear representation over N=121 spatial points, including the planar 2-dim. A(k 1 ,k 2 ) and linear 1-dim. Spectral distribution A(k) as a Fourier transform of X. Inverse transformation Under 1≤k≤121 with -0.10≤A(k)≤0.2, the spectral distribution A(k) (Figure 6) is inverse transformed into the excitation pattern X(j) by means of Fourier inverse transformation without significant blurring of the contour (Figure 6). In this regard, there is still a correlation of 0.9 if the spectral frequency is narrowed to 7≤k≤110 and the amplitudes of the spectral function are discriminated in -0.10≤A(k)→A'(k)≤0.18. On a planar level, Figure 7 shows the reduced spectral distribution A'(k 1 ,k 2 ) and its re-transform X { j * 2 A′ / , / 1 ; , / 1 . Band limitation and amplitude discrimination of the spectral distribution minimize the energy required to reconstruct an excitation pattern. It is more difficult to reconstruct topologically smooth excitation patterns in a network with volatile topology. It is characterized by a loss of direct connections, which corresponds to the loss of synaptic contact points in a population of neurons.
Simulation of Reconstruction Without a Memory Stimulator
The neuron population to be simulated drives a transmitter flow with a speed of 1cm/s, the refractory period of a neuron is c=10 s. The development of the population is to be simulated in a fleeting topology. The transit times of the corpuscles from node to node in the network correspond to those from neuron to neuron in the population. The reconstruction of a registered excitation pattern shows a greater smoothing, the more synaptic contact points have been damaged in the meantime. The increasing reduction ε:=+1 of direct connections in the network increases both the transit times between the nodes and the thicknesses of transferred corpuscle massifs. Without a memory stimulator, the correlation between the excitation pattern X(j) and its reconstruction X''(j) falls to less than 15% with the removal of a single direct connection and falls to -5% with the removal of further connections (Figure 9). Without loss compensation, the volatile network would therefore no longer be able to reconstruct the entered excitation pattern X(j). In a network with an volatile and a memory stimulator, there are the following possibilities for a reconstruction of X(j) by the stimulator, albeit only approximately: 1) isometric reconstruction of the excitation patterns X(j) and X''(j), indicated by the distribution of corpuscle densities over N spatial points P of the network; 2) Reconstruction of all vorticity strengths of the corpuscular flows circulating between the nodes of the network.
Isometric Reconstruction of the Excitation Pattern X(j)
Due to consistency λ and memory η, the stochastic distribution of the correlation coefficients r(X(j);X''(j)) develops more and more differently as direct connections are progressively removed. The volatile network, parameterized with c=10 s and v=1m/s, reaches its balance limit after ε=527,621 reduction steps. Figure 9 shows the course of the correlation coefficients ρ up to the reduction step ε=10 5 for different values η. The partial decrease of ρ for 0.8<η<1,0 to the local value 0.8 (Figure 10) at the point ε=10 3 is an exceptional situation, due to the stochastic character of the memory stimulator.
The curves shown in Figure 10 correspond to the statistical average over 24 sample sets of N=121 random numbers each. In detail, Figure 10 shows the fluctuation range of the distribution of the correlation coefficients r over 24 sample sets in the event of a loss of approx.10 3 direct connections depending on η .
Up to a loss of approx.1.000 direct connections (Figure 11) an almost complete reconstruction of the initial excitation pattern takes place under η=0.9. Increasing loss of connections as well as declining memory η reduce this possibility. For example, a correlation coefficient greater than r=0.9 with reduced memory η=0,8 requires 13.750 direct connections to remain, which excludes exceeding ε=300 reduction steps. A higher-order correlation coefficient below a minimum requirement for memory ability η cannot be achieved with an isometric reconstruction of the excitation pattern X(j) and X''(j) using a memory stimulator, for example for η=0.5 (Figure 10). Variation range of the correlation ρ in ε=10,000 (consistency rate λ=0.935) between X''(j) and X(j) over 24 samples for different memory abilities η=1.0(,0.9;0.8 and 0.5).
Up to a loss of approx.1.000 direct connections (Figure 11) an almost complete reconstruction of the initial excitation pattern takes place under η=0.9. Increasing loss of connections as well as declining memory η reduce this possibility. For example, a correlation coefficient greater than r=0,9 with reduced memory η=0,8 requires 13.750 direct connections to remain, which excludes exceeding ε=300 reduction steps. A higher-order correlation coefficient below a minimum requirement for memory ability η cannot be achieved with an isometric reconstruction of the excitation pattern X(j) and X''(j) using a memory stimulator, for example for η=0.5 (Figure 10).
Reconstruction of the Vorticity of Circulating Corpuscular Flows
An alternative to the isometric reconstruction of the excitation patterns is the reconstruction of the patterns on the basis of vortex strengths that interact with each other. Each node in 1" carries a corpuscular charge caused by the circulating corpuscular massif. In detail, z s t r is the corpuscle massif transferred in the reduction step ε from P ν to µ P over the taxametric distance C s t r . For ε:=+1, the distributions of the corpuscle massif lose more and more their resemblance to the initial excitation pattern X(j), which can at best be compensated for (within limits) by the memory stimulator.
Due to the unequal distribution of taxametric distances s between the spatial points P in 1" , it is advisable to transfer them to the vertices of N unit vectors in an orthogonal action space √1 . In it, each of the N nodes is at the vertex of a unit vector e. Since all unit vectors are perpendicular to each other, there is an identical distance √2 between them. The size of z s t r has to be adapted to this distance, realized by multiplying ⊗ z s t r with the metric calculus … s t r . If in the reduction step ε a point in space P carries a corpuscle massif as charge ρ at time τ , then this charge should have been distributed to the neighboring points in space P' at a subsequent time τ'. Such a process consumes energy and its orientation is described as a vector flow. Vector flows from all points P in space form a vector field. Thus, the components of the vector field represent a force field at every point in space and in every spatial direction. Force is converted energy along a dedicated path. Assuming that in the reduction step ε the spatial point P ν has a corpuscular charge Y ν , equivalent to its energy input in ε, then a portion ∆Y ν is transferred to i P along a path ∆x i . The required force to be applied is ∆ F ‰ |‚ [14].
The large number of spatial points accommodated in √1 requires an extensive variety of paths along which kinetic energy is converted. It is plausible that a large number of forces act against each other -a "mixed situation" which the Jacobian matrix • ' ' orders [9]. Its elements are denoted by ∆ F ‰ , taken at time τ in the reduction step ε.
From the signed difference Figure 12 shows the planar X''(j 1 ,j 2 ) and linear X''(j) reconstruction of the initial excitation pattern X (Figure 6), projected into a volatile with memory stimulator, next to it the reconstruction of X over 121 vortex strengths w in linear representation w(j) with j=1…121. Below λ=1.0 (: consistency), the excitation pattern X is completely reconstructed due to the exclusion of lesion-related losses.
If the consistency is reduced to (only) λ=0.935, which corresponds to a removal of 1060 direct connections in the network and simulates a moderate age-related loss of synaptic contact points, the ratios change significantly. Figure 13 shows the consequences for different memory depths η with isometric and rotation-based reconstruction X''(j) of X(j).λ=1,0 With decreasing memory depth η the ability of the population to reconstruct, simulated by the memory stimulator of the volatile network, generally evaporates. This drop is measured by the correlation coefficient r(X(j);X''(j)) [11].
If X''(j) is the result of an isometric reconstruction of X(j), then in the reduction step ε=1,000 for 0.8<η<1,0 the partial drop in the correlation coefficient r ends at 0.9 (Figure 10). From the reduction step ε=10.000 on isometric reconstruction with a memory depth of (only) η=0,9 no correlation r>0.9 can be established. From ε=60.500, this also applies to the (maximum) memory depth η=1,0. If, on the other hand, X''(j) is the reconstruction of X(j) on the basis of circulating corpuscular flows, such a limitation does not exist.
Figure 13 illustrates the development of vortex strengths in the nodes of the network. Assuming a fully coupled topology, the strongly emphasized curve reflects the conditions at a consistency rate of λ=1,0, identical for all(!) memory depths η. Decreasing consistency rates λ also form here for different memory depths η a smoothing of the reconstruction X''(j) compared to X(j), now caused by a differentiated flow field that swirls around each node, referred to as vortex strength w. It provides information about which Consequence the removal of direct connections between the nodes takes place. To a certain extent, information about whether a reconstruction of the initial excitation pattern is still possible or not. A complete reconstruction for all memory depths η is also given for the parameter set λ=1.0 given in Figure 13. Even with a decreasing consistency rate λ and decreasing memory depth η, this ability based on a reconstruction of X(j) using vortex strengths stands out compared to the isometric reconstruction.
Conclusion
Isometric reconstructions and reconstructions based on vortex strengths of initial excitation patterns of a neuron population were compared. The prerequisite is that the interactions between the neurons of the population correspond to one and the same discrete functional transformation through the coefficients. On the basis of a functional transformation, different classes of excitation patterns, acoustic, optical, etc., can be related to one another.
With regard to the reconstruction of the excitation pattern, the correlation coefficient r(X(j);X''(j)) is used as a quality criterion. In isometric reconstruction, the congruence of the density distribution of transmitter molecules on the membrane surfaces of the neurons is important. On the other hand, if the correlation coefficient is based on the distribution of vortex strengths in the population, triggered by location-variable changes in the direction and intensity of the transmitter flows between the neurons, an alternative situation exists.
In principle, the ability of a neuron population to reconstruct depends on its consistency, but also depends, last but not least, on an existing, lost or poorly acquired memory ability. With reference to the previous explanations, the curves in Figures 10 and 3-9 favor the assumption that the memory ability of a neuron population on the basis of vortex strengths, the expression of which is characterized by the direction of transmitter flows of different densities, is superior to the memory ability through isometric reconstruction seems to be. Under this condition, the assumption of engrams for the storage of memory contents proves to be close to reality, the penetration of which also provides information processing.
From the point of view of systems theory, the extracorporeal evaluation of engrams on the basis of evoked potentials would be a starting point for the non-invasive perception of pre-diagnostic symptoms of neurodegenerative diseases [16].
Figure 1 .
Figure 1. Topology of a sandwich architecture, consisting of traffic and processor field.
Figure 2 .
Figure 2. Structogram of the topology reduction: The elements of the adjacency and reference matrix are accommodated in a linearly ordered set F with the relation <. Outside of the 0 elements, the infimum of F and its address or indices are determined. Subsequently, the corresponding element a of the adjacency matrix A is converted from 1 to 0 and it is determined whether the accessibility of the spatial points P to each other has been retained. Then there is a solution of the system of equations o ⋅ l ⊗ p for at a discrete distance from each other, either directly or only indirectly coupled. The distances change with the structuring of the population, that means change permanently with the problem-oriented removal of direct connections. The remaining path lengths between them are the elements s of a taximetrics' path length matrix S. If all neurons were directly connected, S would be a Euclidean distance matrix. In summary, the simulation model for simulating transient activities in a neuron population consists of the following Parameter set: A (: adjacency matrix for the topology of the neuron population), C (: refractory matrix for the passive time of the neurons), V (: velocity matrix for excitation transfer along a direct connection), S (: Matrix of taximetrics' path lengths in the initial state ε=0) with ε as index for the current reduction step in the model (: reduction step). Due to the permanent loss of synaptic connections, the power of circulating transmitter flows in the population changes constantly. In the simulation model, this effect is simulated by a permanently changing thickness of circulating corpuscle massifs. It is d ⊗ r s t the thickness of a corpuscular massif emitted in P ν and immitted by µ P in reduction level ε.
Consistency rate λ: Ratio of the number of existing direct connections to the number potentially possible connections in a network. Memory rate η : Rate of recognition of patterns from an ensemble initial arousal pattern, 0<η<1.0.
Figure 4 .
Figure 4. Architecture of a memory stimulator. A sequence of binary selectors f, developed from the correction factors π related to the neuronal state S, is multiplied by the normalized elements d of the corpuscle matrix D, resulting in the elements x'' of a secondary excitation distribution X'' taken in the reduction step ε. In detail, fj_K denotes a selector along the excitation contour and fj_U in the vicinity.
Figure 5 .
Figure 5. Isometric reconstruction: Simulation of the reconstruction X''(j)=X''(j1…N) from the initial excitation X(j) based on remaining direct connections with the connection strength y.
Figure 8 .
Figure 8. Resulting thicknesses of circulating corpuscle massifs with the loss of direct connections. The thickness of circulating corpuscle massifs plausibly increases with the progressive loss of direct connections -but not proportionally, shown for the reduction intervals in ‚ ∈ 10 : • 0 10 100 4üT .1,2, … ,5.
Figure 9 .
Figure 9. Correlation between initial and rudimentary excitation pattern without compensation for connection removals in the network.
Figure 10 .
Figure 10. Fluctuation range of the correlation between X''(j) and X(j) with loss compensation by a memory stimulator, simulated for different memory abilities η.
Figure 12 .
Figure 12. Initial excitation pattern X in a planar X(j1,j2) representation and as an ordered sequence X(j) of excitation elements, on the right the ordered distribution of the vortex strengths w(j) over all N nodes.
Figure 13 .
Figure 13. Distribution of vorticity w in the network of 121 nodes.
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Parents' Awareness and Knowledge of Testicular Torsion in the Western Region of Saudi Arabia
Introduction Testicular torsion (TT) is the most common urological emergency in children that requires immediate intervention. The prognosis of testicular torsion depends on the patient's time of presentation to the emergency department (ED), as well as on the time at which the diagnosis is established and treatment is initiated. Raising public awareness of testicular torsion, particularly among parents, plays a crucial role in preventing delay in presentation and reducing the frequency of orchiectomy. To this end, the study is designed to assess the level of awareness and knowledge of testicular torsion, as well as the response of parents to the scrotal pain of their children. Methods A descriptive cross-sectional study was conducted among parents in the western region of Saudi Arabia. Data was collected between the 23rd of November and the 22nd of December 2022. A simple random sampling technique was implemented. The data was collected and analyzed using SPSS software (IBM Corp., Armonk, NY). Results A total of 394 parents participated in this study. It showed that 13.5% of parents reported having a child with a previous experience of pain in the scrotum. Of them, only 25.4% previously heard about torsion of the testicles. Only 68.8% and 76.6% correctly reported that if the child complains of pain in the scrotum during working hours or over the weekend, they will drive him to the hospital immediately. Good knowledge about TT was significantly higher among children's fathers compared to mothers (66.7% vs. 33.3%) (p≤0.05). Conclusion Testicular torsion (TT) represents significant morbidity among male patients and early identification is crucial to avoid the need for orchiectomy and all its prominent physical and psychological consequences. To improve children's well-being, we need to raise parents' awareness of TT and the potential future implications of this critical condition as it is not widely known in our community. Further studies evaluating the knowledge regarding testicular torsion among preadolescent and adolescent boys are warranted.
Introduction
Acute scrotum pain can have several different etiologies, such as ischemia, trauma, infections, inflammation, referred pain, or idiopathy. However, the prevalence and incidence of these causes differ significantly by age group, showing that twisting of the testicular appendages or spermatic cord is significantly more prone to be the reason for acute scrotal pain in children [1].
Testicular torsion (TT) is the most common pediatric urological emergency that necessitates immediate intervention [2]. It is characterized by a longitudinal twisting of the spermatic cord, which restricts blood supply to the testis and results in ischemia of scrotal tissue which may alter testicular function temporarily or permanently, affects hormone production, cause eventual infertility, and in late presentation, may lead to orchiectomy [3,4].
Intravaginal torsion is the cause of the majority of TT cases in children. Bell clapper deformity is the term used to describe the anatomical condition that allows for intravaginal torsion. It is a congenital malformation in which the tunica vaginalis envelops the testis rather than attaching to the epididymis and the posterior surface of the testis, allowing the testis to rotate along a longitudinal axis [5]. It results in a 1 1 1 1 1 42% orchiectomy rate in males, accounting for up to 15% of pediatric acute scrotal pain. In the past, testicular torsion has been estimated to affect 3.8 out of 100,000 boys under the age of 18 [6].
All males who report scrotal or lower abdomen pain, scrotal enlargement, nausea, or vomiting should be evaluated for TT [4]. A high-ridden testicle with an absent cremasteric reflex may be discovered on physical examination [7]. Detorsion within four to eight hours after symptom onset has typically been considered to be the ideal window of opportunity to salvage testicular function in individuals with testicular torsion [2,8].
The prognosis of testicular torsion depends on the patient's presentation time to the emergency department (ED) and the time at which the diagnosis is established and treatment is initiated [6].
Orchidectomy significantly affects boys, and this influence cannot be neglected [9]. Raising public awareness of testicular torsion, particularly among parents, plays a crucial role in preventing delay in presentation and reducing the frequency of orchiectomy [10]. That is why it is necessary to evaluate what parents believe and how they will respond to it. A previous prospective study showed that an estimated 96% of parents whose kids experienced acute scrotal pain think it's critical to raise awareness of this condition [9].
Studies have been published on parents' awareness of testicular torsion in Saudi Arabia and around the world [8][9][10][11][12]. However, no studies have been conducted in the western region of Saudi Arabia to address parental knowledge and awareness of TT. To this end, the study is designed to assess the level of awareness and knowledge of testicular torsion, as well as the response of parents to the scrotal pain of their children among parents in the western region of Saudi Arabia; hopefully, this will work to reduce prehospital delays and increase the likelihood that testicles can be saved.
Materials And Methods
This is a descriptive cross-sectional study conducted among parents in the west of Saudi Arabia. Data was collected between the 23rd of November and the 22nd of December 2022. In total, 435 individuals consented to take part in this study. The inclusion criteria were all parents of all nationalities in the four administrative regions: Makkah, Jeddah, Madinah, and Taif. We excluded the parents who are working in the medical field (physicians, nurses, technicians), participants residing outside the western region, and parents of boys with a history of testicular torsion, genitourinary malformations, or history of cryptorchidism repair. After the exclusion criteria were applied, 394 parents were included.
An online structured, modified questionnaire was developed based on the reviewed literature [8]. The survey included three parts: the first asked about sociodemographic details, the second inquired about how parents responded to their children's acute scrotal pain, and the third asked about parents' knowledge of TT and where they learned about it.
Ten questions were used to test knowledge; for seven of the questions, there was only one right response, earning a score of "1". A score of "0" was assigned for the incorrect response. For symptoms, risk factors, and complications of testicular torsion, every right answer was given a score of "1" leaving a total knowledge score ranging from 0-18. A participant's knowledge level was classified as "low" if they got fewer than 50% of the questions right, "fair" if they got between 50% and 75% of the questions right, and "good" if they got more than 75% of the questions right.
The completed questionnaires were analyzed by using (SPSS) version 26 (IBM Corp., Armonk, NY). Qualitative data were expressed as numbers and percentages to assess the relationship between variables, and the Chi-square test (χ2) was used. Quantitative data were expressed as mean and standard deviation (mean ± SD). Spearman's test was used for correlation analysis, and a p-value of less than 0.05 was regarded as statistically significant.
Results
A total of 394 parents participated in this study; In 17.5%, ages ranged from 45-49 years, 91.1% were of Saudi nationality, and 40.6% were from Jeddah city. The majority (70.8%) were the children's mothers. Most of the participants (72.8%) received a university-level education, 60.2% were employed, 55.1% had one to two daughters, and 60.7 % had one to two sons ( Table 1).
TABLE 1: Distribution of studied parents according to their demographic data and number of daughters and sons (n=394)
Our analysis showed that only 13.5% of parents reported having a child with a previous experience of pain in the scrotum (Figure 1), Of them, only 25.4% previously heard about torsion of the testicles ( Figure 2). The parents' knowledge about items related to torsion of the testicles is illustrated in Table 2. It showed that 68.8% and 76.6% correctly reported that if the child complains of pain in the scrotum during working hours or over the weekend, they will drive him to the hospital immediately. Only 6.3% reported that what makes them think this pain is a serious condition is their previous knowledge about how serious scrotal pain is.
No. (%)
If your child complains of pain in the scrotum (during working hours), what will you do?
Will arrange an appointment with the urology clinic 44 About 21% (21.3%) knew that symptoms of testicular torsion appear immediately, and only 2.5% knew that torsion of the testicles is more common between 12-18 years. The correct known symptoms of TT by parents were scrotal pain (43.7%), swelling of the scrotum (37.1%), change in the color of the skin surrounding the scrotum (19%), and abdominal pain (12.2%). The correct known risk factors of TT by parents were anatomic malformation (14.7%), previous testicular torsion (10.7%), family history of testicular torsion (7.4%), and age (5.1%).
The correct known complications of testicular torsion by parents were lower fertility (24.1%), infertility (16.8%), and death of the testicle (13.7%). Only 17.8% of the participants knew that the appropriate time for surgical intervention is within four to six hours.
The most common sources of information about testicular torsion among participants were the internet (38.6%) and a friend (33%) as illustrated in Figure 3. The mean knowledge score was 4.36 ± 2.62 and based on the knowledge scores; 91.1%, 6.1%, and 0.8% of parents had poor, fair, and good knowledge about testicular torsion respectively (Figure 4). The good knowledge about TT was significantly higher among children's fathers compared to mothers (66.7% vs. 33.3%) (p≤0.05). On the other hand, a non-significant relationship was found between parents' knowledge level and other demographics or the number of daughters and sons (p≥0.05) ( Table 3).
TABLE 3: Relationship between parents' knowledge level about testicular torsion and their demographics, and the number of daughters and sons (n=394)
It was demonstrated that good knowledge about TT was significantly higher among parents who reported having a child who had experienced scrotal pain before (p≤0.05) ( Figure 5). In addition, a significant positive correlation was found between knowledge scores and the number of sons (r = 0.13, p-value = 0.01) as shown in Figure 6.
Discussion
Since there is limited evidence in the literature about parental awareness of TT in children, we found it crucial to survey parents to ascertain their awareness and attitude in such critical conditions. The level of awareness and understanding of testicular torsion among parents in the western region of Saudi Arabia were evaluated for the first time in this study.
Most of the time, parents or guardians are in charge of their children's health and well-being [1]; they owe them the responsibility to decide whether or not an urgent presentation to the emergency department is necessary. Studies showed that pediatric patients are more likely to have delayed presentation and subsequent complications if their parents have poor knowledge about their disease [10]. The study by Barada et al. has shed more light on the correlation between orchidectomy rates and patient age; it showed a significant difference when compared between pediatric patients under the age of 18 (44%) and adult patients beyond the age of 18 (8%) [13]. In addition, the Nevo et al. findings support those of Barada et al. which demonstrated that orchidectomy is significantly influenced by younger age [14]. According to Yap et al. study, there is a statistically significant correlation between parents' knowledge of testicular torsion and their likelihood of presenting immediately to ED in the setting of severe pain. Parents who were aware of testicular torsion were four times more likely to do so than those who were not, and parents who correctly identified the critical time frame were three times more likely to do so than those who did not [10]. Twothirds of the testicular torsion patients in the Ubee et al. study presented six hours after the onset of symptoms [9]. In children with torsion, any factor influencing a delayed hospital presentation is crucial as it might be a key contributing factor in boys ending up having an orchidectomy. Our findings showed that only 17.8% of our participants knew that the appropriate time for surgical intervention is within four to six hours. Reduced delay at presentation might be achieved by raising community awareness of testicular torsion.
According to parents' responses to their children's testicular pain, our results determined that most of the parents correctly reported that if the child complains of pain in the scrotum during working hours (68.8%) or over the weekend (76.6%), they would drive him to the hospital immediately. Friedman et al. similarly observed from their data which targeted the parents in ear, nose, throat (ENT), and urology clinics, the parents in both clinics gave statistically similar answers (72.5% and 75%) regarding their responses during business hours for taking their children immediately to the emergency department or call their physician within one hour. Similar trends were reported in their response during the weekends (80.4% and 81.9%) [12]. These results are in line with those obtained by Alyami et al. who compare the awareness of pediatric urology clinics and general pediatric clinics among parents of children who have attended both clinics. The family's response was the same in all situations, with their decision to head straight to the emergency room being the most favorable [8].
In contrast, what particularly stands out is these results are not in line with those of Ubee et al. study which found only (22%) of his cohorts brought their children to the ER immediately. The remaining parents sought counsel from other sources, and some even waited all night for the medical facilities to open [9]. This attitude was comparable to Anzaoui et al.'s study, which showed that 72% of patients would arrive at hospitals late, six hours after the onset of pain [15]. All of these responses show that those parents are unaware of the severity of the illness and the potential consequences that could arise if immediate intervention is not provided, where studies have found that if a patient seeks medical attention within the first six hours of the onset of symptoms, their chance of having their testicles saved is over 100%; but it soon falls to less than 50% if more than 12 to 24 hours pass [6].
Our results are consistent with those obtained in the Alyami et al. study; it found that as the number of boys in the family increases, the parents' awareness of TT also increases [8]. Parents with only girls in the family will not directly be impacted, but if they were aware of it, they might share the knowledge with other parents who have boys in their family since several studies have demonstrated that parents who were aware of testicular torsion mostly learned about it via friends, relatives, and the internet, which stands as the most common source of knowledge [8][9][10][11][12][13][14][15][16].
The parent's response about the indicator of a serious condition in our study was if the pain didn't relieve in a short time (48%), while the parents in Alyami et al. study (46.95) responded that severe pain and the appearance of the testicle were indicators of a serious condition [8]. Our results demonstrate that the good knowledge about TT was significantly higher among children's fathers compared to mothers (66.7% vs. 33.3%); The father's prior experience with circumstances comparable to these or learning about the experiences of friends of the same sex might also provide an explanation of this significant difference in awareness between mothers and fathers. Moreover, according to our survey, a relatively high number of parents (93.1%) had poor knowledge about TT, which is also similar to Alyami et al. results [8]. Additionally, 55.1% of parents' responses in our study were not aware of the complications of TT. As part of the care we provide for our patients, we think that raising awareness of TT is essential to avoid its consequences. Educating the general Saudi population, particularly parents and young males, is warranted through targeted community-based campaigns and social media platforms. Focusing on raising awareness of testicular torsion among preadolescent and adolescent boys as well as their parents should result in a drop in pre-hospital delays, directly corresponding to a decrease in rates of testicular loss.
Conclusions
Testicular torsion (TT) represents significant morbidity among male patients. Early identification is crucial to avoid the need for orchiectomy and all its prominent physical and psychological consequences. To improve children's well-being, we need to raise parents' awareness of TT and the potential future implications of this critical condition as it is not widely known in the surveyed community. By doing this, we can hopefully reduce prehospital delays and increase the likelihood that testicles can be saved. Further studies evaluating the knowledge regarding testicular torsion among preadolescent and adolescent boys are warranted.
Additional Information Disclosures
Human subjects: Consent was obtained or waived by all participants in this study. Committee of Bio-Medical Ethics of Umm Al-Qura University issued approval HAPO-02-K-012-2022-11-1232. Ethical approval was obtained on the 12th of November 2022 from the Medical Ethics Committee in the Faculty of Medicine at UQU University (OFKQ271022). We wrote a statement to clarify the purpose of the survey and to obtain consent from the participants; they were informed that all information provided will be kept confidential and used only for research purposes. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.
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FCOS-LSC: A Novel Model for Green Fruit Detection in a Complex Orchard Environment
To better address the difficulties in designing green fruit recognition techniques in machine vision systems, a new fruit detection model is proposed. This model is an optimization of the FCOS (full convolution one-stage object detection) algorithm, incorporating LSC (level scales, spaces, channels) attention blocks in the network structure, and named FCOS-LSC. The method achieves efficient recognition and localization of green fruit images affected by overlapping occlusions, lighting conditions, and capture angles. Specifically, the improved feature extraction network ResNet50 with added deformable convolution is used to fully extract green fruit feature information. The feature pyramid network (FPN) is employed to fully fuse low-level detail information and high-level semantic information in a cross-connected and top-down connected way. Next, the attention mechanisms are added to each of the 3 dimensions of scale, space (including the height and width of the feature map), and channel of the generated multiscale feature map to improve the feature perception capability of the network. Finally, the classification and regression subnetworks of the model are applied to predict the fruit category and bounding box. In the classification branch, a new positive and negative sample selection strategy is applied to better distinguish supervised signals by designing weights in the loss function to achieve more accurate fruit detection. The proposed FCOS-LSC model has 38.65M parameters, 38.72G floating point operations, and mean average precision of 63.0% and 75.2% for detecting green apples and green persimmons, respectively. In summary, FCOS-LSC outperforms the state-of-the-art models in terms of precision and complexity to meet the accurate and efficient requirements of green fruit recognition using intelligent agricultural equipment. Correspondingly, FCOS-LSC can be used to improve the robustness and generalization of the green fruit detection models.
Introduction
With the successful application of artificial intelligence technology in many fields, the development of this modern technology has also stimulated the development of agriculture, making the application of intelligent agriculture in agricultural production more and more extensive. As an important part of automated agricultural intelligent equipment, vision systems have realized practical operations such as fruit picking, yield estimation, fruit counting, and crop type classification in agriculture [1,2]. Intelligent agricultural picking robots can replace or assist manual picking and reduce production costs, so efficient fruit recognition and picking research has received a lot of attention in recent years as an important branch of agricultural robotics [3][4][5][6]. Rapid recognition and accurate positioning of fruits in natural scenes can provide key technical support for the machine vision system of fruit-picking robots [7,8].
However, fruit growth in natural environments is characterized by random distribution and mutual occlusion, and fruit images also change dynamically depending on light changes, shooting angles, and distances. In the unstructured agricultural environment, target fruit recognition has become a major challenge for agricultural intelligent devices in production applications [9]. In recent years, fruit detection has been the primary focus of research to identify target fruits from natural environmental backgrounds [10]. Fruit recognition methods mainly include traditional recognition methods based on manual features and deep learning methods for automatic feature extraction.
Traditional fruit recognition algorithms mainly extract information such as color, geometric shape, and texture features of targets and then classify and detect fruiting targets on the basis of machine learning methods. Arefi et al. [11] selected ripe tomatoes in a greenhouse environment for their experimental study and successively processed background informational and color information to finally achieve 96.36% detection accuracy, and the method showed excellent detection only for cases where the fruit color was more clearly distinguished from the background. When the fruit target is close to the background color features, the shape and texture features between the fruit and the background are needed to determine the target region.
Kurtulmus et al. [12] combined color, shape, and texture features using 3 different scales of moving windows to scan unripe green citrus images, and the results of multiple voting window classifiers resulted in a final correct detection rate of 75.3%. Jia et al. [13] segmented the collected apple images under Lab color space using the K-means clustering algorithm and inputted the extracted image red green blue (RGB) and hue saturation intensity color features and geometric shape features into a neural network for fruit recognition, achieving 96.17% fruit recognition accuracy, but the algorithm was relatively tedious to recognize over. Tian et al. [14] proposed a combination of depth images and RGB images to recognize apple fruits by locating the center of the target fruit using depth images and by segmenting it using RGB images with a final recognition efficiency of 96.61%, but the performance of this method was rather poor when dealing with overlapping fruits. Ji et al. [15] proposed an apple recognition and classification algorithm based on a support vector machine with a recognition success rate of 89%, but the algorithm was less effective in detecting fruit with branch and leaf occlusions. Moallem et al. [16] applied K-means clustering and multilayer perceptron to extract apple texture and geometric features and achieved 92.5% and 89.2% classification accuracy.
The above traditional fruit recognition algorithm often involves a series of complicated operations, such as image preprocessing, feature selection, and extraction, which affects the recognition accuracy and speed of the algorithm and makes it difficult to meet the requirements of real-time operation of intelligent devices. Especially when the fruit is close to the background color, a large number of overlapping blocks lead to the inconspicuous shape of the fruit contour, while the change of lighting conditions also leads to the loss of texture features, which seriously interferes with the recognition effect of the algorithm.
With the rapid development of convolutional neural network (CNN), the end-to-end detection process and the advantage of automatic extraction of depth features have reduced many complex operational steps in traditional algorithms. On the basis of this, numerous deep learning-based recognition algorithms such as Faster R-CNN [17], YOLO [18], SDD [19], YOLOv5, FoveaBox [20], and many other mainstream algorithms have been developed, which are far more robust and accurate than traditional recognition algorithms and have been widely used in the field of fruit image detection and segmentation [21][22][23]. Zhang et al. [24] replaced the original feature extraction network of Faster R-CNN with VGG19 through pretraining network migration and improved the region proposal network structure of the network to improve the detection accuracy of the model for apple fruit and reduce the false detection rate.
Tu et al. [25] designed the model to fuse image color and depth image information with the help of an RGB-D camera and finally achieved 90.9% F1 score to effectively improve the detection accuracy of small target passion fruit. Liang et al. [26] first performed a series of data augmentation techniques to optimize the operation of the data, then redesigned the single shot multibox detector detection frame shape according to the processed dataset, and finally implemented a mango detection model with better performance than Faster R-CNN. Bresilla et al. [27] detected fruits on trees on the basis of an optimized YOLO model, which achieved 90% fruit detection precision by reducing convolutional and pooling layers to make the model shallower and to increase the speed without decreasing the detection precision. Wang et al. proposed a lightweight deep learning model YOLOv5s on the basis of channel pruning, which achieved accurate apple fruit detection with 95.8% detection precision [28].
The above methods require feature area selection based on anchors, requiring the design of anchors of various scales and shapes, and the setting of parameters such as scale, aspect ratio, and number of anchor frames also affects the detection performance of the model. To overcome the drawbacks of anchorbased algorithms, anchor-free algorithms are emerging. Jia et al. [29] used EfficientNetV2-S backbone and a bidirectional weighted feature pyramid network (FPN) as the backbone network for feature extraction, and they used an adaptive training sample selection method to directly select positive and negative samples to obtain higher recall for green fruits at different scales, with detection precision of 62.3%. To eliminate the limitation of the anchor boxes on the model in terms of speed and generalization ability situation, Jia et al. [30] embedded the position attention module in FoveaBox and MaskIoUhead mask calibration module, achieving efficient green fruit recognition.
Considering the problems of the anchor-based methods such as long training time and complicated calculation, the effective and accurate fruit detection model (full convolutional one-stage object detection) algorithm based on LSC attention blocks (FCOS-LSC) is proposed to recognize green fruit by improving anchor-free FCOS [31] as the base model. Instead of normal convolution operation, a deformation convolution [32] is adopted in the backbone network to better extract the fruit features with different shapes. In addition, attention operations [33] are introduced into the multiscale features on scale, space, and channel dimensions to enhance the feature representation of the network. In the classification branch of the detection head, a new positive and negative sample selection strategy is employed to set loss weights for both positive and negative samples to better distinguish between positive and negative samples [34]. The method provides more discriminable supervisory signals and enhances the detection of foreground targets and background environments.
In general, this study has at least the following contributions: 1. In the backbone network, deformable convolution is introduced to better adapt to different fruit shape features during detection. 2. In the neck network, the LSC attention module is embedded in the 3 dimensions of scale, space, and channel of the feature map, which suppress the noise interference in the feature map and make the model focus more on the effective pixel information. 3. In the detection head, a new positive and negative sample determination method is designed to improve the discriminative ability for supervised signals. 4. The proposed method outperforms other advanced methods in terms of accuracy and robustness, which is more suitable for detecting green fruits in complex orchards.
The rest of this paper is organized as follows: Materials and Methods presents the green fruit dataset including image acquisition and dataset production. Next, this section illustrates the proposed FCOS-LSC model including the backbone network, the feature fusion network, and various parts of the detection head, as well as the details of optimization. In Results, experiments are conducted to compare other advanced detection models from different aspects to validate the effectiveness of FCOS-LSC in green fruit detection. Finally, Conclusion summarizes the proposed model and presents future research directions.
Dataset
There are many disturbances in the complex orchard environment that affect the detection of the vision system, making it difficult for fruit-harvesting robots to recognize green fruits from similarly colored green backgrounds. To better cope with the complexity of the detection task, this study collects and produces 2 green fruit datasets from actual orchards for the experiments, including green apples and green persimmons.
Data acquisition
Collection locations: Apple images are collected from the apple production base in Fushan District, Yantai City, Shandong Province, and persimmon images are collected from the back mountain of Shandong Normal University. Image acquisition equipment: All images are taken with the same camera, Sony Alpha 7II. A total of 1,361 images of green apples and 553 images of green persimmons are taken at a resolution of 6,000 × 4,000 and stored in JPG format.
Acquisition environment: To get closer to the working conditions of the picking robot, fruits in different lighting conditions and different periods are selected as far as possible when capturing images.
Shown in Fig. 1A to D, the images of fruits are captured under soft light in the early morning, strong light at noon (which includes images of fruits under low backlight and high backlight conditions), and light-emitting diode lighting at night. As shown in Fig. 1E and F, images from different angles of distant and close views and different directions are captured to imitate the operation of the robot in actual orchards. There are many occlusions and overlaps in the image, including fruit overlapping each other and branch and leaf occlusions. The specific fruit images are listed in Fig. 1G to H.
Dataset production
The collected images take full account of the complexities of the orchard, with a certain degree of randomness and representation, and are as close as possible to the requirements of the real-time operation of the machine and equipment. In this paper, the captured images are compressed and scaled to a size of 600 × 400 pixels to enable the fruit detection network to better adapt to the detection requirements of machine equipment for low-resolution images. LabelMe [35] software was used to annotate the information on green fruits, and corresponding category labels and annotation points are generated and uniformly saved in JSON files. Finally, datasets are generated according to Microsoft COCO [36] format.
Datasets are divided into the training set and validation set according to the ratio of 7:3, in which the training set contains 953 images and the validation set contains 408 images in the apple dataset. The persimmon dataset contains 388 images in the training set and 165 images in the validation set.
FCOS-LSC detection network
FCOS-LSC is an optimization method based on the one-stage object detection model FCOS. The overall framework of the FCOS-LSC model includes the backbone network for feature extraction, the feature fusion structure, the attention module of each dimension on the feature map, and the detection head. The detection head also includes subnetworks for processing classification, bounding box regression, and center point detection. As shown in Fig. 2, the optimized ResNet50 with the addition of deformable convolutional structures is used as the backbone network to improve the feature extraction capability of the network. FPN is utilized to fully fuse the extracted multiscale fruit features. Before input to the detection head, the attention mechanisms are added to the scale, space, and channel dimensions of the feature map by the convolution-based method, which helps the feature map to distinguish foreground fruit objects and background information more effectively. In the detection head, a new label assignment strategy is designed to distinguish between positive and negative samples, providing the detector with a more discriminative supervised signal.
Feature extraction and fusion network
As a feature extraction network, ResNet50 performs a series of convolution downsampling operations on the input fruit image to extract fruit feature information. The residual structure solves the problem of gradient disappearance, explosion, and degradation caused by deeper network layers by completely mapping shallow features into deeper networks.
However, in the feature extraction network, the convolution kernel is set to a fixed shape. Fruit feature maps are also limited to extracting valid information only in rectangular filters. The efficiency of fruit detection in complex orchard backgrounds is greatly reduced under uncontrollable conditions such as shooting angles and fruit growth forms, and the design of convolutional kernels with dynamically transformable shapes can adapt to targets with variable morphology and improve recognition accuracy. Therefore, the deformable convolution [32] is added to the C 3 , C 4 , and C 5 layers of the ResNet50 backbone network to improve feature extraction performance.
The deformable convolution structure is shown in Fig. 3. The size of the convolution kernel is set to 3 × 3, and the same padding as the normal convolution is used to ensure that the size of the output feature map is the same as the size of the input feature map. The 2 × 3 × 3 shift offset values in the convolution kernel correspond to the (x, y) offset values of each pixel in the 3 × 3 convolution kernel, respectively.
To achieve greater degrees of freedom, different from deformable convolutional networks [37], a learning coefficient of sampling points is added to it, and the coefficient of some useless background sampling points in fruit detection can be set to 0. This coefficient indicates that it has different weights for different pixel values, which improves the feature expression capability. The feature output dimension of the ith stage is mapped to 1/2 i of the input image. There are usually many layers that produce output maps of the same size. In this paper, the network layers with the same mapping size are grouped into the same stage layer. After each stage of the ResNet50 layer {C 2 , C 3 , C 4 , C 5 }, the output feature map is mapped to the input image as {1/2 2 , 1/2 3 , 1/2 4 , 1/2 5 }, respectively, as shown in the backbone part of Fig. 2.
The output of the ResNet50 network is a relatively high-level feature map with high semantic information. However, the feature maps after a series of convolution and pooling operations have low resolution. The mappable features are easy to lose details such as boundaries when detecting small objects.
Backbone
Neck Head FPN realizes the fusion of low-level detail information and high-level semantic information to solve the problem of multiscale prediction. The feature maps C 3 , C 4 , and C 5 output by the last 3 layers after the ResNet50 network are horizontally connected to the FPN through 1 × 1 convolution. Then, the feature maps perform a 2-fold up-sampling and top-down method to fuse the information of each layer by element addition to obtain F 3 , F 4 , and F 5 . The F 6 and F 7 are obtained from F 5 by 2 convolution operations with a convolution kernel of 3 × 3 and a step of 2, as shown in Fig. 2, Neck section.
LSC attention module
To enhance the representational capability of the model, an attention learning module implemented by a convolution-based approach is added to the output of the feature fusion network. The LSC attention module is embedded behind the FPN to extract more feature information. The structure is shown in Fig. 2, and the specific implementation is shown in Fig.4.
In this paper, the feature maps output from the FPN are up-sampling and down-sampling to process the high feature layer and low feature layer map scales and adjust to the scale size of the middle feature layer. The feature map can be converted to a 4-dimensional tensor X ∈ R L×H×W×C , redefining S = H × W, where L denotes the feature level, H denotes the feature map height, W denotes the feature map width, and C denotes the feature channel. The 3-dimensional representation of the feature map is X ∈ R L×S×C . Focusing on the role of the 3 dimensions of the feature map separately can help improve the model feature extraction. Figure 4 shows the attention operations implemented in the convolution-based feature maps. First, feature maps improve the relationship between fruit scale size differences and features at different levels by operating on the scale dimension. Scale attention can improve the representation ability of feature maps at different levels, thereby improving the perception ability of fruit scale features. Then, through the operation in the spatial dimension, the spatial location information of fruit detection with different geometric shapes is extracted to improve the spatial perception ability of fruit detection. The last part of the cascade operation is the feature channel. The multitasking of fruit detection and segmentation and target representation correspond to features on different channels. Improving the representation learning ability on the feature channel can effectively improve the perceptual ability of the fruit detection task. Finally, the processing in the 3 dimensions is concatenated and multiplied as the input of the detection head. The operation of the attention module in 3 dimensions is as follows.
As shown in Fig. 5, the M L module is operated on the scale. The input feature map undergoes a global averaging pooling operation to compress the spatial and channel features into a real number with a global sensory field on space and channel. The linear function is approximated with a 1×1 convolution to generate weights for the feature layer scale by computation. Then, a linear rectification function (ReLU) is used to obtain the nonlinear relationship, which can fit the complex correlation between spatial channels. Finally, the approximate sigmoid is simulated by a hard-sigmoid activation function, which can also shorten the calculation time. The formula is expressed as follows.
where the f(⋅) linear function represents the 1 × 1 convolution and σ(⋅) is the hard-sigmoid activation function.
With the understanding of the importance of different semantic information between feature layers in the perception module, the feature map focuses more on the information of each spatial location of the fruit. This includes distinguishing areas where the spatial location of each target in the feature map coexists consistently with the feature layer. Considering the high dimensionality of the spatial dimension, we use deformed convolution to make the spatial feature awareness learning more sparse and then aggregate the features at the same spatial location across feature levels. Figure 5 illustrates the operation process of the M S module in space. The feature map input to this module is subjected to the convolution kernel size of 3 × 3 deformation convolution to learn the offset and mask information of the spatial position. The feature map focuses on the spatial position of the intermediate layer that is not adjusted at this time and propagates the obtained information to other adjacent feature layers that need to be adjusted in subsequent executions. The input feature map adapts to the same size by performing up-sampling and downsampling operations on its neighboring feature maps according to the feature level. Aggregate features across layers by simple summation and spatial attention can be learned to obtain more accurate information about offsets at spatial locations. Feature map F 7 , as the top layer, only carries out the up-sampling operation, while F 3 , as the lowest layer, only carries out the downsampling operation. The other remaining feature layers are scaled accordingly according to the layer determination. The spatial attention formula is expressed as follows.
Deformation convolution operation X′(l; p n + △ p n ; c) △ m n focuses on the p n + △ p n position information of the cth channel of the lth layer feature, and the self-learning spatial offset is △p n used to move the position to focus on more obvious areas. The network learns to gain spatial weights W l n . We set learnable confidence weights for more important locations △m n .
The Dynamic ReLU [38] is applied in the M C module shown in Fig. 5 to execute the feature channel dimensionality awareness module. The input feature map is subjected to global average pooling to compress features in space and scale, and 2 fully connected layers perform channel dimension compression and restoration. The full connection operation is used to predict the importance of each channel and to understand the importance of different channels. The last normalization layer restricts the output to be between [−1, 1]. The calculated weight values of each channel are multiplied by the 2-dimensional matrix of the corresponding channel in the input feature map to realize the weighting of its channel. The weighted feature is added to the input to obtain the output. Feature maps can be shared across spatial channels, channel-shared across spaces. Finally, the input parameters are used to filter the features through the function as the output features.
Detection head for green fruit prediction
As shown in the head section of Fig. 2, the FCOS-LSC detector consists of task-specific subnetworks. The 3 subnetwork modules of classification, regression, and center point detection constitute the detector part. The classification subnetwork performs the prediction of the confidence that each pixel on the feature map belongs to an apple or a persimmon. Moreover, the regression subnetwork predicts the distance to the 4 edges of the real bounding box of the fruit. The center point detection subnetwork predicts the offset from the target center and shares a portion of the network parameters with the regression network, while the classification network module as a separate network does not share network parameters. Therefore, we use 2 different full convolutional channels to perform specific prediction tasks by decoupling the classification subnetwork and regression molecular network tasks.
The classification subnetwork processes each feature level output from the model Neck structure, and all feature maps share the parameters of the classification subnetwork. The module has 4 convolutional layers with kernel size 3 × 3 and one convolutional layer that performs the prediction of fruit confidence. The bounding box regression subnetwork and the center point detection subnetwork share a part of the fully convolutional network. The full convolution of this part implements 4 convolution layers in parallel with the classification subnetwork, with the size of the convolution kernel 3 × 3. Finally, two 3 × 3 convolution branches are used to output the prediction results of the feature map bounding box and the predicted offset from the center point. The predicted offset is multiplied by the category predicted by the classification subnetwork to output the final confidence score.
Positive and negative sample determination: The original FCOS model assigns positive and negative samples in such a way that the center of the real object bounding box is the center of the circle, and the positive sample area is delimited by a fixed radius. According to the step of feature level, the pixels on the feature map are converted to the coordinates of the corresponding perceptual field region on the input image to directly determine whether the coordinates fall within the divided region. If it falls within the divided region, then it is considered as a positive sample; otherwise, it is a negative sample. When training the sample loss weights, the weights of negative samples are simply obtained from the weights of positive samples, resulting in no new supervisory information provided to the negative sample weights, which limits the detection performance. The proposed method provides more signal discriminative supervision to the detector from different perspectives by specifying the loss weights of positive and negative samples.
The built positive sample weighting function takes the predicted fruit category confidence and the intersection over union (IoU) between the predicted box and the ground truth as input. This paper sets positive sample weight by estimating the degree of agreement between the class network and the regression network. The negative sample weight function takes the same input as the positive sample weight function, but the negative sample weight is represented by the product of the probability that the anchor frame is a negative sample and its importance if it is a negative sample. The fuzzy prediction frame with the same positive sample weight can get a finer supervision signal because of the different negative sample weights.
First, this paper constructs a set of candidate positive samples by selecting the detection box near the center point of the ground-truth bounding box. During testing, all predictions for the fruit category are appropriately ranked by a combination of a confidence score and the predicted IoU as a ranking metric to rank detection boxes in the candidate set. The correctness of each prediction box is checked from the beginning of the ranked list. Highly ranked fruit category prediction scores and high IoU are sufficient requisites for positive prediction. Positive sample weights are positively correlated with prediction scores and IoU. Therefore, the positive sample weighting function is defined as follows.
where s is the category score of the predicted fruit, and b, b' are the positions of the predicted box and the ground box. The s × IoU β can indicate the degree of agreement between the predictions of the classification network and the regression network in forward prediction. The β is used as a balancing factor. The exponential function is used to enhance the variance of positive sample weights. The μ is used as a hyperparameter to control the relative gap between different positive sample weights. Positive sample weight can emphasize that consistent boxes have higher classification scores and higher IoU, but inconsistent boxes cannot be distinguished by positive sample weight. According to the IoU, to determine whether the detection box is incorrectly predicted, the IoU smaller than the threshold is the only factor to determine the negative sample probability denoted by P neg .
The interval is divided into [0.5,0.95] according to the evaluation index of the COCO data format. When the IoU is less than 0.5, the lower limit of the evaluation interval, the probability of a negative sample is 1. When the IoU is greater than the upper limit of the evaluation interval, the probability of a negative sample is 0. In the evaluation interval, the negative sample probability takes the value [0,1], which satisfies the linear functional relationship. During inference, negative sample predictions with higher rankings in the index list can help the network to optimally distinguish difficult samples, so they are more important than negative sample predictions with lower rankings. The negative sample probability multiplied by the importance can be expressed as a negative sample weighting function.
where γ is the modulation factor. The k and b are the coefficients of the linear equation.
The design of the weighting function of positive and negative samples can distinguish between important and non-important samples. The method dynamically assigns a separate loss weight for positive samples and loss weight for negative samples to detection boxes, which is highly compatible with evaluation metrics.
Loss function
The loss function reflects the error size between the predicted value and the real value of the model in this paper, which is helpful to the iterative optimization in the process of model training and to evaluate the effectiveness of the model to the detection fruit. The model loss in the object detector consists of a combination of fruit classification loss and positive sample prediction bounding box bias loss.
The loss L detection of the FCOS-LSC is composed of L cls and L reg . Here, L cls denotes the predicted fruit category loss, L reg represents the predicted regression loss, and λ is the modulation factor. N and M represent the number of detected frames in the candidate set and the number of detected boxes outside the candidate set, respectively. FL stands for focal loss [39]. GIoU is the regression GIoU loss [40]. b, b' are the positions of the predicted box and the real box.
Equations regarding FL in Eq. 10 and GIoU in Eq. 11 are shown below.
Here, α is responsible for balancing the importance between positive and negative samples, and η is responsible for regulating the rate of weight reduction for simple samples. Bbox min is the smallest enclosing convex object of b and b'.
Results
In this paper, abundant experiments are conducted to verify the effectiveness of the optimized model for fruit detection. This section first introduces the experimental environment and the implementation details of the model during the training and testing periods. Then, the network is trained with the apple training dataset and the persimmon training dataset. The optimal training model is selected for testing on 2 validation datasets and for analyzing the results. Finally, state-of-the-art object detection algorithms are selected for experimental comparison in the same environment, and the results are analyzed and compared to verify the performance differences of the models in this paper in terms of fruit detection.
Experimental settings
Experiments run on Ubuntu 18.04 64-bit operating system, 24 GB GTX 3090 graphics card, and 11.3 CUDA environment. All models use Python 3.7 version and Pytorch 1.11 version and build model components with the help of MMDetection 2.22.0 version learning library.
Image preprocessing
ResNet50 is used as the backbone network to extract fruit image features and then is inputted to the FPN for feature fusion. The fused features are features learned in 3 dimensions-scale, space, and channel-to obtain better information representation. The output 5 feature layers are all in 256 channel dimensions. The operation of the detection head is performed at each level, and its parameters are shared among each level. The final detection head outputs the prediction results for fruit category confidence and bounding box regression. Image preprocessing operations are performed before network training. First, the image is resized to a uniform scale. Next, the image is flipped with a random inversion probability of 0.5, then regularized, and finally padded to be divisible by 32 in downsampling. Image enhancement of the dataset prevents overfitting of the model due to insufficient data and enhances the generalization ability of the model.
Training
The learning rate for model training is set to 0.00125, the weight decay rate is set to 0.0001, and the momentum factor is set to 0.9. In this paper, the mini-batch method is used for training iterations for 12 epochs. The batch size per iteration is set to 2 fruit images, so the maximum number of iterations is 5,736. To prevent the gradient explosion during model training, the learning rate is adjusted using the warm-up strategy. The initial learning rate is adjusted linearly, i.e., the learning rate of the model increases linearly from 0.001 to 0.00125 in the first 1,000 iterations. The gradient is updated using the stochastic gradient descent optimizer (SGD) [41], and then the learning rate transformation is adjusted according to the number of iterations, that is, at the 8th epoch and 11th epoch of the iteration, it is reduced respectively to 1/10 of the original. The transformation of the learning rate is shown in Fig. 6.
Using the above training parameters, the model profiles are set up in this paper to obtain the training loss variation curves on the apple dataset and the persimmon dataset, as shown in Fig. 7.
Testing
The same data preprocessing operations are performed before the images are input to the network, such as image cropping, random inversion, regularization, and padding. After the network prediction is over, the lower predicted values are filtered by setting a fruit confidence threshold of 0.4. The network then outputs the top 1,000 detection boxes with high confidence for each prediction layer. The network filters overlapping detection boxes by non-maximum suppression. The filtered detection boxes are still sorted by confidence. Each fruit image retains, at most, the first 100 confidence prediction boxes.
The models with the above test parameters are used to validate the fruit images of the apple dataset and the persimmon dataset. The change curve of average precision (AP) obtained is shown in Fig. 8.
Evaluation metrics
To better evaluate the FCOS-LSC model, this paper uses the AP and average recall (AR) under the IoU threshold of [0.5:0.05:0.95] to evaluate the performance of the model on fruit detection, where precision and recall can be expressed as the following formulas: where TP is the number of fruits predicted as positive samples. FP is the number of backgrounds predicted as fruits, i.e., the number of false-positive samples. In addition, FN is the number of fruits not predicted as positive samples, i.e., the number of false-negative samples. Furthermore, the AP formula under a specific threshold can be obtained.
The AP at a certain threshold is obtained by taking the precision of 101 recalls at [0, 0.01, 1] and averaging them. This paper selects the IoU thresholds in the range of [0.5:0.95] every 0.05, a total of 10 thresholds, and averages them to obtain the evaluation indicators AP and AR. We also counted the AP and AR values at specific thresholds and different scales of large, medium, and small as the evaluation metrics for this experiment. The PR curves at 10 different thresholds on the apple dataset are shown in Fig. 9. Parameters (Params) are used to examine the number of parameters contained in the model to measure the simplicity of the model; floating point operations (FLOPs) measure the computational complexity of the model.
Model detection effect
The proposed model is trained and tested on the apple dataset and the persimmon dataset, respectively. Figure 7 shows the visualization of all losses when our method is trained on the training set. The horizontal coordinates in the figure represent the number of iterations of the model during training, and the vertical coordinates represent the loss values. The red curve represents the total prediction loss of the model throughout the training period, including the negative sample weight loss change and positive sample weight loss change in classification loss. Negative and positive sample loss changes are presented by the blue and orange curves, respectively, as well as the green curve of regression loss change. The model optimizer SGD continuously optimizes until the model weight parameters converge during the training process. During each training epoch iteration, the test set is evaluated by the AR and AP. As shown in Fig. 8, the horizontal coordinate is the number of training iterations and the vertical coordinate is the prediction precision. In the first row, the AP values with thresholds of 0.75 and 0.5 for each epoch and AP with 10 thresholds within Precision(r) Fig. 6. Learning rate change during training. the interval are indicated by the green, orange, and blue curves. As shown in Tables 2 and 3, the method in this paper achieves 63% and 75% AP on the apple dataset and persimmon dataset, respectively. The second row of Fig. 8 compares the performance of the baseline model and FCOS-LSC on the green apple and green persimmon datasets, and the images show that FCOS-LSC is more stable during training and its performance is much better than that of the baseline. In this paper, fruit images under mixed environments such as different lighting conditions, fruit occlusion, and distant view are selected for detection. The proposed method can accurately detect randomly taken fruit images with almost no misses and false detections, realizing a high detection accuracy. Acceptable results are achieved even when fruit images are mixed with background images that are not easily distinguishable, especially in the 2 cases of backlighting and blurred distant fruit. The model can also output detection results in a friendly manner when there are severe fruit overlaps and branch occlusions in the captured images, whose fruit contours are not clear. It can be seen that the model in this paper can perform the detection task accurately even with the occurrence of mixed interference conditions of various overlapping occlusions, lighting conditions, and shooting angle distances for fruit detection. Thus, the model based on improved FCOS is competent for the task of green fruit detection in orchards.
Ablation experiment
To verify the effect of the LSC attention module and the positive and negative sample judgment methods, this paper further verifies the effectiveness of the 2 methods through ablation experiments. To understand the contribution of the 2 methods to the model, the new positive and negative sample selection method constructed is applied to the base model for a before-and-after comparison of apple detection effects, and the LSC module is added to further compare the effects. The experimental results are shown in Table 1.
First, on the basis of the original FCOS network, the positive and negative sample determination method is applied to the detection head, under the condition that the model parameters and computational complexity are the nearly same as the original model. The LSC module is then added to this, and after adding only a small number of parameters, the precision is improved by 1.0 percentage point and the complexity of the model is reduced. Therefore, the positive and negative sample determination method can better improve the ability to distinguish between green fruits and complex green backgrounds during training. Meanwhile, the LSC module enhances the ability of the model to represent features. The results are shown in Table 1. Although a small number of model parameters is added, the combination of the 2 methods results in an AP 4.4 percentage point higher than the original mode.
Comparisons
To further analyze the effectiveness of this model in the implementation of fruit detection tasks, this paper selects the most advanced object detection algorithms for comparison. The comparison models include 2-stage anchor-based algorithms Faster R-CNN, Mask R-CNN, and its variant MS R-CNN, as well as one-stage anchor-based algorithms RetinaNet, YOLOv3, and ATSS, where ATSS is also compared as a label assignment policy method. Compared with the one-stage FCOS algorithm without anchor boxes, there is also the FoveaBox algorithm. All models are trained and tested on the apple dataset and persimmon dataset. The detection effect of each model is shown in Tables 2 and 3. It is observed that, compared with other algorithms, FCOS-LSC has strong competitiveness in the performance of each evaluation metric on both the apple and the persimmon datasets. Despite considering the accuracy of model detection, it is also necessary to examine the capacity and computational complexity of the algorithm to balance the quality of the model design. Under the premise that the input image size is uniformly 600 × 400, each detection model capacity and complexity are calculated as shown in Table 4. Although FCOS-LSC is slightly inferior to ATSS in AP 0.5 in the apple dataset and AP 0.75 in the persimmon dataset as well as AP s , its algorithm complexity is reduced by 11.07G compared to ATSS. Compared with the model capacity and computational complexity of other algorithms, FCOS-LSC has the lowest computational complexity after introducing a small number of model parameters.
In this paper, Faster R-CNN, Mask R-CNN, YOLOv3, and ATSS algorithms are selected for the detection of fruit images in the apple dataset, as shown in Fig. 12. MS R-CNN, RetinaNet, FoveaBox, and FCOS algorithms are selected for the detection of fruit images in the persimmon dataset, as shown in Fig. 13. From the figure, it is easy to find that the fruits with clear fruit contours can be detected and have the highest detection accuracy performance. At the same time, fruits with blurred edges and even unlabeled fruits can be detected accurately, as shown in the first image of the apple dataset. This is very helpful to deal with the situation of fruit detection in complex orchards with multiple interference factors.
In summary, the FCOS-LSC model is more concise in design, has fewer requirements on memory and calculation, and realizes the prediction of higher probability values, which can meet the real-time orchard operation tasks and present more comprehensive and efficient results.
Failure detections
This section further analyzes the difficult problems of the existing detection tasks in orchards. To better illustrate the detection effectiveness of FCOS-LSC, we chose fruits with a heavy overlap in the orchard and fruits under a distant and backlight condition. The visualization of all the models mentioned in this paper on the apple dataset is presented as shown in Fig. 14. FCOS-LSC can still accurately detect the target fruit in the presence of missed detection by other comparison models. However, not all target fruits can be detected, as detailed in the marked section. The model misses the obscured target fruits in the close-up images because of the severe shape deficit, and this is also a common problem with other models. In addition, when dealing with backlight images, the model does not work well because of factors such as the small size of the fruit and the presence of occlusion.
Discussion
In previous studies, a combination of deep learning techniques and image processing has made significant progress in target fruit recognition tasks [42]. The 2-stage detection model has high detection accuracy relative to the 1-stage model but involves the design of the anchor frame, and the complexity and computational volume of its model increase along with it. Considering the needs of orchard robot operations, designing algorithms with high detection accuracy and low computational cost is the key to coping with the target fruit identification and localization problem. Object detection task embedding visual attention during model training is an effective way [43][44][45][46] to focus on some of the input features instead of the whole input for solving the target task. In addition, to improve the generalization ability and robustness of the model, it is crucial to design a more reasonable positive and negative sample selection strategy [47,48]. Experimental results show that the proposed model achieves better accuracy with relatively fewer parameters and fewer FLOPs. The proposed FCOS-LSC model outperforms other state-of-the-art algorithms in terms of detection accuracy and efficiency. As shown in Tables 1 and 4, FCOS-LSC exhibits high AP, and the analysis reveals that the model does not have its model computational complexity enhanced by the addition of the LAC module but instead has the least FLOPs, which is due to the dimensional adjustment of the feature map that promotes the model to focus more on effective features, as described in detail in the "LSC attention module" section. Although FCOS-LSC performs well in the visualization effect map, it is relatively poor in small target fruits, as shown in Tables 2 and 3, where the enhancement effect of model optimization shows AP l > AP m > AP s . This phenomenon is caused by the positive and negative sample selection strategy. The method first selects the detection frame with the true bounding box near the center point to better discriminate the supervised signal, which may lead the method to be more focused on important samples compared to samples near the target fruit boundary, while this method is friendly to large targets. In conclusion, the high accuracy and robustness of the model provide further possibilities for its deployment with intelligent agricultural equipment, which can meet the needs of real-time operations
Conclusion
The purpose of this study is to deploy and apply the technology of green fruit detection to agricultural intelligent equipment to meet the task of fruit identification in complex orchards. The one-stage anchor-free FCOS model is optimized to avoid the reliance on anchors in the fruit detection process, thus shortening the detection time, which can be widely applied to other agricultural fields. The deformable convolution is added in the backbone network to better adapt to the green fruit target with different shapes. The convolution-based attention operation is applied to the fused features, which combines low-level detail information and high-level semantic information to improve the scale, space, and channel feature representation of the features. Moreover, this operation helps the network deal with overlapping occluded fruits to achieve better detection results. To distinguish the green target fruit from the background, a new sample selection strategy is constructed to provide more discriminable supervised signals by specifying loss weights for positive and negative samples and applying them directly to the detection head.
Although the FCOS-LSC model achieves better detection results on green apple and persimmon datasets, there is still space for improvement. More types of green fruit images are collected to verify the effectiveness of the model, and the model is designed to improve the detection of small target fruits. In the practical application of unstructured orchards, the accuracy and time efficiency of the model need to be considered, so the model will be further optimized to improve the overall efficiency of the model by shortening the computation time while improving the detection accuracy.
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Effect on Ziziphus jujuba Mill. fruit powders embedded on physicochemical properties, biological activities, and rheologic quality of cake
Abstract This study aimed to improve the effects on the physical, textural, and rheological characteristics of cake supplied with Ziziphus jujuba fruit powder at rates of 0%, 3%, 5%, and 10%. The Physicochemical and antioxidant as well as the antibacterial activity and sensory qualities of Z. jujuba fruits were also investigated. The highest levels reached the values of 245.15 mg GAE/g DW (phenol) and 180.23 mg RE/g DW (flavonoids). Pulp extracts were also subjected to HPLC analysis in order to identify and quantify the sugar composition. This technique allowed us to identify Mahdia as the richest provenance especially in glucose (136.51%) and sucrose (113.28%) contents. The antioxidant activities investigated using DPPH assay decreased slightly from 175 μg/mL (Sfax) to 55 μg/mL (Mahdia). Furthermore, the antibacterial activity indicated that the S. aureus was the most inhibited especially by Sfax powder extracts (from 12 to 20 mm). Our results showed that the incorporation of Z. jujuba powder ameliorated the physicochemical and rheological characteristics (humidity, gluten yield, tenacity, falling time, and configuration) of the dough. Sensory analysis showed that consumer scores were increased with the increasing supplementation powder levels. Highest scores attributed to the cake supplied with 3% jujube powder collected from Mahdia provenance and confirmed that Ziziphus fruit could be advised a part of our diet. These results could validate a novel method to conserve Z. jujuba fruits in order to avoid their soilages for a long period.
to date fruit. So why it was named Chinese jujube or Chinese date.
Unfortunately, shelf life could not exceed more than 3 months because jujube cannot be stored for a long period under ambient conditions. In addition, some properties such as vitamin C and antioxidant activity cease in fruit stored in cold conditions. Many problems were associated with jujube storage. Tunisian people usually store the fruit at −5°C. In fact, this fruit can be freeze-dried or frozen. Many methods were used to dry Z. jujuba fruits such as sun oven, microwave, and freeze-drying, but the most to conserve jujube was the microwave. Other's studies showed that the sun dry method was the efficient technical to dry pinus halepensis Mill. seeds with the highest (0.08 and 0.05 mg/mL) antioxidant activities (Mahdhi et al., 2021).
So in order to increase the consumption of jujube and to conserve it for a longer duration, we tried to use this fruit as an active ingredient in the food industries by transforming it to powder and adding it to jam, cookie, and cake (Rashwan et al., 2020). The idea to combine Z. jujuba fruit powder in food products, such as cake, could play an important role in stored pulp protection and reduction of the associated risks. In fact, food companies were faced with an increased demand by health professionals and consumers for healthier food products. In addition, this combination contributed to the nutritional and therapeutic benefits by using this fruit as an active ingredient in the food industry.
However, to the best of our knowledge, no studies were reported on cake enrichment with Z. jujuba fruits. So this investigation aimed to establish the impact of this incorporation on the physicochemical and rheological quality of the flours and on the sensory quality of the Z. jujuba cake. The result revealed that jujube powder could be a better substitute for wheat flour in preparation of flour products. In addition, Tunisian Z. jujuba fruit was known for its long history of uses as a vital food and for traditional medicine (Rashwan et al., 2020). It could be used or consumed as beverage, juice, brandy, wine, jelly, and also candied jujube. In addition, the biochemical fruit composition's enhanced many therapeutic effects against several diseases such as obesity, cardiovascular disease, diabetes, and even certain types of cancers (Elaloui et al., 2016;Etebari et al., 2015). Therefore, it was the suitable time to improve the technological quality and nutritional value of this fruit. In this context, the aim of the present work was to evaluate biochemical Z. jujuba fruit powder contents collected from five Tunisian provenances (Choutrana, Mahdia, Regueb, Sfax, and Mahres) and to evaluate their effects on physicochemical properties and sensory evaluation of cake. This experimental station with an area of 200 km 2 was characterized by irregular rainfall events especially between January and February (El Aloui, 2013). The temperature levels ranged from 4°C (January) to 33.4°C (July and August).
| ME THODS
The ripe jujube fruits (selection was based on reaching the stage of full maturity in terms of color, flavor, and structure) were immediately transferred to our laboratory. So the disease-free and identical in shape jujubes were selected for the sun drying process in order to evaporate water from fruits by sun and conserve their biochemical and biological activities (Anjum et al., 2020). The dried fruits were first grounded using a mill equipped with a grid with holes 1.00 mm in diameter and then stored in plastic bags until the chemical analysis began.
| Mineral composition
The mineral composition (K, Fe, Ca, and Mg) of Z. jujuba fruits was evaluated according to calcination methods. Briefly, 0.5 g of Z. jujuba fruit powder was calcinated at 550°C for 4 h. The ash, already cooled, was moistened with a few drops of distilled H 2 O (3 mL). It was combined with 10 mL of hydrochloric acid and then filtered into 50 mL graduated flasks. The solution was then stored in vials until it was analyzed. The mineral element contents were determined using a flame spectrophotometer (Genway, Model PSP7).
| Physicochemical analysis of Z. jujuba fruits
Physicochemical analysis focused specifically on the water, fat, and protein contents. The water content was determined after desiccation of the fresh material at a temperature of 103 ± 2°C in an isothermal oven ventilated at atmospheric pressure to a nearly consistent measurement. The protein contents were evaluated according to Kjeldahl methods (1883). Water level contents were evaluated by weight difference after drying the fresh pulp (Audigie et al., 1978). Z. jujuba powder fat contents were achieved by extracting samples in a Soxhlet apparatus using the hexane as solvent. The extractions were carried out in duplicate.
| Yield extraction
Ziziphus fresh pulp (1 g) was macerated in 10 mL of Ultra High Quality (UHQ) water for 30 h. After centrifugation and filtration, the supernatant extracts were kept in the freezer before HPLC analysis.
The postcolumn injection was used with a volume of 25 μL. The HPLC worked under suitable programs: First it was stabilized with 1 mM of KOH during 10 min, and then 100 mM KOH solution was used as a mobile phase during the analysis. Evaluation was done at a flow rate of 1 mL min −1 with constant Helium purge. The identification and the quantification of the compounds were performed in comparison with the commercial standards. A column wash between two successive injections was made with methanol.
| Secondary metabolite contents
The total phenol contents (TPC) were carried out by the Folin Ciocalteau's reagent (Singleton & Rossi, 1965). Results were expressed as mg of Gallic acid equivalents per gram of dry weight (GEA/g DW). Briefly 1 mL of extracts and of Folin Ciocalteu (1.25 mL) was added to 2 mL of sodium carbonate (7%). The absorbance was carried out at 765 nm using Shimadzu 1600-UV spectrophotometer. Flavonoid contents (FC) of jujube extracts were determined according to Earp et al. (1981) methods. So 1 mL of each extract was mixed with 1 mL of AlCl 3 (2%) in darkness. The flavonoid was used to prepare the curve calibration and the absorbance was measured at 430 nm. Results were expressed as mg quercetin equivalent per gram dry weight (mg QE/g DW). All analyses were run in triplicate. Tannin condensed contents (TC), expressed as mg Catechin Equivalent per gram dray weight (mg CE/g DW), werealso quantified (Sun et al., 1998). A Shimadzu 1600-UV spectrophotometer was used to perform the absorbance at 500 nm. were carried out in triplicate and the IC 50 (Concentration required for 50% inhibition) was determined according to the following formula where a 0 is the absorbance of the blank sample and a 1 is the absorbance in the presence of the sample.
| Antibacterial activities
The antibacterial activities were evaluated using 2 g-positive bacte-
Agar diffusion method
The various methanol extracts from Z. jujuba were dissolved in sterile water. Before use and for the detection of the antimicrobial activity, each extract was diluted to 50 μg/mL and sterilized by filtration through a 0.2 μm pore size filter.
Antibacterial tests were performed by agar well diffusion methods as described by Dharajiy et al. (2016). Broth microdilution assay using sterile Mueller-Hinton media (BioRad, France) for bacterial strains and yeast malt extract agar YMA (Bio-Rad, France) for antifungal tests were used. A fresh cell suspension (0.1 mL) adjusted to 10 7 CFU/mL for bacteria and 10 5 cell/mL for fungus were inoculated onto the surface of agar plates. Afterward, wells 6 mm diameter, were punched in the inoculated agar medium and 30 μL of the extract was added to each well. Negative controls consisted of using 30 μL water. The plate was allowed to stand for 40 min at 4°C to permit the extract diffusion followed by incubation at 37°C for 24 h for bacteria.
The antibacterial activities were evaluated by measuring the zones of inhibition (clear zone around the well) against the test microorganisms. All tests were repeated three times (Essghaier et al., 2014).
Determination of minimum inhibitory concentration (MIC)
The minimum inhibitory concentration (MIC) of each extract was determined by using the microdilution broth method. MIC values were estimated visually by the absence of turbidity as previously reported by Khemiri et al. (2020). 2.6 | Effects of adding jujube flour on the physicochemical and rheological characteristics of the cake 2.6.1 | Cake preparation The cake was prepared using the Expert Design V 6 in order to formulate a product that meets customer and industrial approval.
The cakes were prepared in a local pastry industry. The eggs were mixed with an electric mixer (Electra EK-230 M, Japan) at 128 rpm for 4 min with sugar. The oil and the milk were added to mixture (M 1 ). A second mixture (M 2 ) was prepared by adding jujube powder or wheat flour with vanilla. Finally, the two mixtures were combined.
The baking operation was then carried out in an oven (Zuccihelli Forni, Italy) at 180°C for duration of 30 min.
After cooling, each sample was packed in polyethylene bags for evaluation of different characteristics and stored at ambient temperature.
| Rheological characterization
The dough was characterized rheologically by a Chopin Alveograph (according to NF V03.710, 1991;ISO 5530-4, 1991). This method was used to describe dough resistance against the biaxial deformation. Different stages of the Chopin Alveograph test were resumed in Figure 2.
| Sensory analysis
Sensory analysis defined as texture, flavor (taste), aroma, and visual aspect was achieved according to international standardized (NF ISO 5492) hedonic method (Drake et al., 2004). So sixty panelists aged between 20 and 60 years old were used to carry out this test.
Results were noted according to a numbered scale from 0 (unacceptable) to 7 (very desirable). Each panelist noted his appreciation for cake supplemented by Z. jujuba fruits. The studied parameters were taste, color, texture, volume, and global appreciation.
Samples were presented in arbitrary order to each panelist on plastic plates using a 3-digit code for each sample.
| Statistical analysis
Statistical analysis results were statistically analyzed using STATISTICA (Statsoft, 1998). Each data presented was mean ± standard deviation of three replicates. Multiple mean comparisons were performed using the Student-Newman Keuls test with a significance level of p = 0.05.
| Fruit characterization
Jujube fruit was known for many uses as a vital food due to its richness on many components such as ash, protein, fat, and carbohydrate ( Table 1). This composition was affected by the maturity stage of the fruit. Furthermore, others showed that the variation of these chemical compositions depended on the provenance.
The analysis of the protein levels varied between 0.40% and 0.64%. The Mahres provenance was the richest one, and the Choutrana was the poorest one (Table 1).
| Total sugar contents
Total sugar levels as mentioned in Figure 3 ranged from 14.12% to 16.59%. The Mahdia provenance was the richest one. The present results could enhance the nutritional value of Z. jujuba fruit.
This composition varied deeply among provenances. In fact, Mahdia provenance was the richest one in glucose (136.51%) and sucrose (113.28%) contents ( Table 2). The pulp's sugars were also rich in galactose ranging from 0.2% in Sfax to 0.45% in Mahdia.
Such results confirmed the high nutritional value of Z. jujuba fruit due to its richness in large quantities of nutrients and phytochemicals. So the idea to incorporate this fruit in some foods.
| Total polyphenol, flavonoid and tannin contents
Many research projects focused on medicinal plants due to their huge role in both food and pharmaceutical industries. Therefore, a study of phenolic compounds has become a specific necessity due to their intervention to reduce the stress oxidative and to neutralize radicals in the human organism.
As shown in Figure 5, the richest provenance for phenolic
| Antibacterial activities
Due to the multi-resistance microorganisms, there were great demands to research new molecules from alternative sources like plants.
The antibacterial potential of various extracts revealed high differences between each of the tested provenances. The results indicated that the S. aureus was the most inhibited microorganism especially when they were treated by Sfax extracts. The diameters of zone inhibition expressed in mm varied from 12 to 20 mm (Table 3).
In addition, the Sfax and Regueb provenances showed a strong antibacterial activity against Kleibsella Pneumoniae with an inhibitor diameter ranging respectively between 16 and 18 mm. The
F I G U R E 4 Essential sugars of five
Ziziphus jujuba fruits using HPLC analysis (Chromatogram).
nutritional value of Z. jujuba fruits was deeply confirmed by the antioxidant and antibacterial activities. However, fresh fruits have a short shelf-life. So it will be very necessary to transform it as a novel product in order to preserve it for a long time. So the idea to incorporate Ziziphus powder into cake.
| Effects on water absorption
The water absorption levels, as shown in Figure 7, decreased from 15% (control cake) to 13.6% (5% of jujube incorporation). This diminution was more notable with the jujubes from Regueb provenance.
Our results were compared to the Tunisian normative data (TN 51.21, 1989) that fixed the humidity of the flour between 13% and 16%.
As showed in Figure 7, the decline of the humidity influenced the yield of the final product (high-quality flour) that could be conserved for a long period, without yeast or mold deterioration and food decomposition.
| Effects of ash contents
The ash contents informed us about the flour extraction ( Figure 8).
Our results showed that the ash levels increased with the augmen- This study proved that edible and delicious Z. jujuba fruit could ameliorate some physical properties (the humidity and ash contents) of the cake formulated with jujube powder.
| Rheologic properties of cake supplemented by Z. jujuba powder
Rheologic behavior briefly could predict dough processing parameters and the quality of the final product. Some rheological parameters,
F I G U R E 5
Phenolic compounds in fruits of five Z. jujuba provenances. The data are means values of three measurements. The confidence intervals were calculated at the threshold of 5%.
investigated in this study, were past tenacity, extensibility, swelling capacity, baking strength index, elasticity index, and falling number.
• Past tenacity
Rheological properties of dough and gluten contents were greatly affected during the mixing process by the flour compositions (low or high protein contents), the processing parameters (mixing time, energy, and temperature) and the ingredients (water, salt, yeast, fats, and emulsifiers). As shown in Figure 9a, past tenacity deceased after the addition of the Z. jujuba powder, especially those of the Mahdia provenance powder. In fact, this parameter decreased from 87 to 37 mm H 2 O for the control and the Z. jujuba powder of Mahdia provenance, respectively.
• Extensibility
Contrarily, the incorporation of the Z. jujuba powder increased the extensibility of the past (Figure 9b). This augmentation was observed after adding the jujube powder at a rate of 3%, whereas, at certain levels of incorporation, this extensibility was reduced.
• Swelling capacity
This parameter informed us about dough extensibility. As shown in these results, we can conclude that the swelling capacity increased with the augmentation of the Z. jujuba powder, especially for the use of the Mahdia provenance powder (Figure 9 c).
• Baking strength index
The baking strength index was a protein quality parameter that expresses loaf volume. The results showed a decrease in baking strength with the increase in the rate of substitution of wheat flour by jujube powder (Figure 9d).
• Configuration
As shown in Figure 9 e, the incorporation of jujube powder at a rate of 5% decreased the configuration rate from 0.49% (for the control) to 0.28 (Rgueb provenance). This result confirmed that the dough was doubly extensible. So the elasticity of the dough increased with the incorporation of Z. jujuba powder.
F I G U R E 6
Variation of inhibition percentage (%IP) of five Z. jujuba provenances. The data are mean values of three measurements. Ampicillin was used as standard.
Extraits[mg/mL] Souches
Extracts were used as concentration equal to 50 and 100 mg/ml.
• Falling time
The falling time increased with the rate of Ziziphus powder addition without exceeding the Tunisian norm (Figure 9 g). In addition, the increase in falling number demonstrated a decrease in α-amylase activity that created sticky dough.
| Effects on wet, index, and dry gluten
The protein dough strength measurements and gluten properties, in particular, significantly impacted dough strength measurements. In fact, fruits with high gluten levels could ameliorate dough handling properties. The rheological properties of the gluten (the combination of its viscous, elastic, and cohesive properties) were also studied….
Results mentioned that the incorporation of Z. jujuba powders reduced the wet, index, and dry gluten contents of the pastry flour.
This reduction was observed for Mahres provenance (Figure 10).
In fact, based on ISO 5531 and 6645 norms, the wet gluten levels varied between 24 and 30%. That was compared to our sample (25% and 30%). This characteristic could inform us about the quality of the flour and its rheological parameter. As showed in this study, the F I G U R E 7 Water absorption (%) of cake supplemented by Ziziphus jujuba powders. The data are mean values of three measurements.
F I G U R E 8
Ash contents (%) of cake supplemented by Ziziphus jujuba powder. The data are mean values of three measurements.
incorporation of Ziziphus powder did not modify the index gluten of dough. In fact, this level was between 86% and 98% that was compared with the control test.
In fact, higher amounts of gluten proteins increased the dough elasticity and prevent hamper molding of the dough (Hanee, 2013).
In addition, the gluten index allowed us to highlight the deterioration caused by insects and heat. At 5% of Z. jujuba incorporation, dry gluten percentages ranged between 6% and 9.4%. This inveterate the conservation of heat-resistant protein, so our flours keep their nutritional qualities.
According to this result we can validate a novel method to conserve Z. jujuba fruits and avoid their soilage for a long period.
| Sensory analysis
The result of sensory analysis of Z. jujuba powder cake was evaluated through taste, color, texture, volume, and global appreciation ( Figure 11). Results showed that consumer scores were increased with the increasing supplementation level. In fact, highest scores were attributed to the cake supplied with 3% jujube powder.
| Taste of cake
Sensory analysis of cake supplemented by Z. jujuba powder showed a great change in the taste of the cake. This variation between provenances could be attributed to the richness of Z. powder on lipoxygenase inhibitory activity, so the synthesis of many volatile compounds such as alcohols, ketones, and aldehydes (Molteberg et al., 1995).
Taste scores were affected by the jujube powder substitution.
From the mean scores of the organoleptic evaluation, the Mahdia provenance powder supplemented at the concentrations of 1% and 3% were higher for all examined attributes and ranked at 9.1.
Oppositely, consumer scores increased with increasing supplementation levels. This characteristic could be attributed to the strong F I G U R E 9 Rheologic properties of cake supplemented by Ziziphus jujuba powder. The data are mean values of three measurements.
F I G U R E 1 0 Effects of Ziziphus jujuba powder on wet, index and dry gluten of dough The data are mean values of three measurements.
F I G U R E 11
Sensory analysis of cake supplemented by Ziziphus jujuba powder. The data are mean values of three measurements.
lipase activity that caused many oxidative reactions responsible for the savory taste (O'Connor et al., 1992).
This incorporation modified the sucrosity of cake and reached the maximum values (7.7 and 8) for Mahdia provenance added at rates of 1% and 3%, respectively. Such variability could be attributed to high levels of sugar fruits.
| Color
The color of the cake expressed the sensation the cake produced on the eyes. The difference between the mean of the provenance was quite significant. In fact, the comparison between provenances showed that the color of Mahdia provenance had the highest mean (11). The Sfax provenance had a low mean relative to the other provenances (2.4).
| Texture
The texture of the cake referred to the smoothness or appearance of the feel of the cake in the mouth. This variation changed with the rate of jujube powder incorporation. In fact, compared to the control, in which the texture was heavy estimated (0.75), the texture levels ranged between 6.9 and 9 for Sfax and Mahdia provenances, respectively, incorporated rates of 1% and 3%. The result indicates that the texture of the Mahdia provenance was preferred to other samples. In addition, as shown in Figure 11, this parameter increased with the addition of Z. jujuba powder. This increase could be explained by the high content of polysaccharides, which may lead to the dilution of gluten and extensive gluten structure (Zarroug et al., 2021).
| Volume
The difference in volume of all samples was easily detected among consumers. However, the volume of the control cake was low with the mean scores of the cakes evaluated equal to 4. This could be explained by the absence of cells in this cake.
The comparison between provenances showed that the cake enriched with Mahdia jujube powder (1% et 3%) had scored the highest volume mean (8.4) by panelists, while cake sample supplemented with Sfax jujube powder at 1% and 3% were less accepted than all other provenances, but more important than those made only with wheat flour (3.5). Such variability in volume varied not only according to the provenances but also the rates of their additions to the cakes.
| Global appreciation
This parameter expresses how the panelists accept the jujube cake.
As shown in Figure 11, consumers were more inclined to accept cakes of Mahdia and Regueb provenances with the means of 9.5 and 8.5, respectively. In addition, cake jujube supplemented with Sfax powder (1%) were less accepted.
| DISCUSS ION
Ziziphus jujuba fruit characterizations showed that protein contents varied between provenances and attempt the value of 0.60%. Such results were higher than those cited by El Aloui (2013) Secondary metabolites analysis enhanced the richness of our extracts on phenolic compounds. Levels were higher than those found (10.43 to 15.85 mg/ L) by Elaloui et al. (2014). Other works done by Rashwan et al. (2020) showed that total phenolic ranged from 1.1 to 2.4 g/100 g DW, and flavonoid contents ranged from 0.7 to 1.8 g/100 g DW. These results could validate jujube fruit as a good source of phenolics compound and therefore recommended it by nutritionists to be part of our diet. This idea was also confirmed by Rashwan et al. (2020).
The cake supplemented by Z. jujuba powder increased the ash contents to 70% especially for the Mahdia provenance. These results were not in accordance with the findings of John et al. (2021) who noticed that ash contents increased with increasing levels of Finger millet flour. They explained that the high level of the ash content in the composite cakes was due to the richness of Finger millet flour on minerals.
In order to decrease the consummation of our specie, the Z.
jujuba fruits were incorporated into Neapolitan pizza, the sensory analysis proved that this incorporation increased the fiber, total phenolic and flavonoid contents, and the radical scavenging activity (Falciano et al., 2022).
In addition, the Z. jujuba fruits incorporation decreased the tenacity of our cake. This could be attributed to the richness of our fruits on proteins without glutelin (protein responsible for past tenacity) or also for the diluting gluten (Godon et Loisel, 1984). The extensibility was also reduced after this incorporation. This decline could be attributed to the diminution in the gluten level in particular the gliadins level that gave rise to larger cake volume during baking.
Such variation reflected an increase in the gas retention property within the dough bubble and thus the retention of carbon dioxide within the cake dough. From these results, the dough which will be obtained from the basis of the mixture of two flours (wheat and Z. jujuba) will exhibit a decreasing density with the rate of incorporation and a cake of increasing volume.
In addition, the increase in falling number demonstrated a decrease in α-amylase activity that created sticky dough. This idea was also cited by Tozatti et al. (2020). In opposition, the diminution of amylasic activities decreased the fermentation of the dough.
Our results showed that the incorporation of Z. jujuba powder ameliorates the physicochemical and rheological characteristics of the dough by reducing its humidity; gluten yields. So Z. jujuba powder could be recommended by nutritionists and industrial to formulate cake supplement with Z. jujuba powder. According to overall acceptability of results, the cake enriched with Mahdia jujube powders used at dose of 3% and 1% were the most acceptable, by panelists. Other studies carried out on biscuits supplemented with jujube flour had as acceptable quality as the control (Masmoudi et al., 2021). In addition, a diminution in acceptability of cookies at higher level of substitution with Ziziphus lotus was observed by Zarroug et al. (2021).
| CON CLUS ION
This study proved the benefits of Z. jujuba fruits as an active ingredient in the food industry by transforming it to cake. In fact, the Z.
jujuba fruits incorporation increased the physicochemical and rheological characteristics (humidity, gluten yields, tenacity, falling time, and configuration) of the dough. In addition, cakes prepared with 3% (w/w) fruit powders of Mahdia provenance had comparatively the best nutritional and sensory characteristics over other provenances. According to these results we can validate a novel method to conserve Z. jujuba fruits especially these of Mahdia provenance and avoid their soilages for a long period. Ziziphus fruit was advised to be to be part of our diet.
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Domain: Agricultural And Food Sciences
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Soil Water Content Regression Analysis of Measurement Data from Hyperspectral Camera in Weathered Granite Soils
. Soil water content is one of the most common physical parameters that cause landslides or debris flow. Therefore, it is of very importance to determine or predict the water content quickly and non-destructively. This study investigates the hyperspectral information in the visible near-infrared regions (VNIR) of different samples of granite soils possessing varying water content. Totally 162 granite samples were taken from each mountain area. The samples with different water contents were examined using a hyperspectral radiometer operating in the 400~1000nm range by obtaining the spectral curves. It was found that the variation of VNIR is consistent with the water content variation of weathered granite soils, and the hyperspectral camera was able to detect it. A Partial Least Squares Regression (PLSR) analysis was applied to develop a calibration-model. The PLSR model resulted in a good correlation between the water content and VNIR profile. The results demonstrate that the hyperspectral camera combined with the PLSR model can be a useful and non-destructive tool for determining soil water contents in the weathered granite soils.
Introduction
Soil water content seriously affects soil's physical and chemical properties, and changes in soil properties can lead to landslides or debris flow. The prediction of soil water content plays a decisive role in landslides and debris flow monitoring. Existing water content measurement has been instruments made based on field tests or field sensor-based measurements.
However, both methods have limitations in that they can measure water content in relatively local areas. Therefore, it is necessary to develop a technology that can measure a large area's water content variation. During the last two decades, near-infrared (NIR) spectroscopy has been widely employed as a useful tool for analyzing soil properties. NIR spectroscopy can be used to evaluate the properties of soil that are not disturbed by light [7,11]. Mouazen et al. [5] used visual and near-infrared (VNIR) hyperspectral imaging to determine the presence of chemicals (carbon and phosphorous) in soil and to measure soil parameters, such as moisture content and pH. Zhang et al. [13] developed a technique for the classification of soil using NIR hyperspectral images. Wang et al. (2018) [12] developed a technique for analyzing the degree of heavy metal contamination of soil using remote sensing and hyperspectral images in NIR.
In this study, we developed a variation of the soil water content prediction model using the hyperspectral technique to overcome the limitations of existing measurement techniques. The objectives of this study are to develop a water content prediction model using _______________________________ * Corresponding authorhyperspectral images. For this purpose, the change of reflectance according to the water content in the nearinfrared region was confirmed, and the most relevant parameter was analyzed. Finally, the water content prediction model developed with the corresponding parameters is compared with the actual soil water content. Based on these findings, we intend to provide reference materials that can be used for analyzing the water content of soil using hyperspectral near-infrared images to decide the susceptibility of landslides in a mountainous area.
Study area
The study areas are placed in Seoul's southern part (Mt. Umyeon: 37.45° N, 126.9° E; Mt. Guryong: 37.47° N, 127.06° E; Mt. Daemo: 37.48° N, 127.08° E), as shown in Figure 1. The study areas are comprised of granitic gneiss. A total of 162 granite soil samples were collected from the study areas within a depth of 30 cm from the surface. First, a sieve analysis was conducted using soil that passed through a No. 40 sieves (0.425 mm). The soils were also dried at 110 ℃ in an oven for 24 hours. And the water was added step by step to measure the water content. Soil water content was calculated by the following equation (Equation 1). Table 1 shows the material properties of the 162 soils.
Hyperspectral camera system
The hyperspectral camera system consists of a hyper spectral camera, a complementary metal-oxid semiconductor (CMOS) sensor, six 150W Halogen lamps, and a 40 x 20 Lab-scanner (Spectral Imaging Ltd., Oulu, Finland, Figure 2a). The software for scanning speed (CNC USB controller) and hypercube data recorder (Lumo Recorder) provides exposure time, binning mode, wavelength range, and image acquisition [8]. Hyperspectral cameras were placed in a dark room to minimize errors. The design of the hyperspectral camera is shown in Figure 2b.
Image correction
Hyperspectral images were acquired using the line scanning technique of the hyperspectral camera system. Each sample was placed on a slider table and scanned line by line to get an initial hyperspectral image. After capturing the hyperspectral image, a dark reference and a white reference were obtained. The normalization process is essential. We can remove noise values from hyperspectral images and convert them to relative values using 100% reflectance of the white reference through this process. The white reference was acquired from a Teflon whiteboard with 99% reflectivity. The dark reference was obtained by turning off the light source and completely covering the camera lens with a cap. The reflectance (%) of the sample acquired based on the white reference was calculated using the following equation.
where the Raw reflectance is the reference measured on an actual object, Dark is the dark reference, and White is the white reference, t1 is the integration time in a white reference, and t2 the integration time in a dark reference [10].
Investigation of parameters related to water content variation
The near-infrared regions (NIR, 800~1000 nm) are suggested as having a strong correlation with soil water content variation [4]. Three parameters related to water content variation were selected in NIR: the water index (R970/R900, Figure 3a), which is one of the spectral vegetation indices; the depth of 800nm to 1000nm (Figure 3b); and the area of reflectance (Figure 3c). Partial Least Square Regression (PLSR) analysis was performed by setting each parameter and variation of water content as variables. Figure 4 shows the relationship between water content variation and the selected three parameters from each of Mt. Umyeon, Mt Guryong, and Mt. Daemo weathered granite soils. Among the parameters, the area of reflectance in NIR showed the highest coefficient of determination, and the water index and depth at 1000nm showed the lower coefficient of determination overall. In all 162 weathered granite soils, it was confirmed that the area of reflectance in NIR is the parameter most correlated with the water content variation in VNIR.
Estimation of water content variation of soil according to reflectance
In general, the indicators used to evaluate the goodness of fit of predictive models are mean absolute percentage error (MAPE), root mean square error (RMSE), mean absolute error (MAE), and maximum absolute percentage error (Max-APE) [9]. MAPE has become increasingly popular as a performance measure in forecasting [1,2,6], as it is easy to interpret and understand in addition to being highly reliable [3]. All data points, both predicted values and results from laboratory tests, were used to compute the coefficient of determination (R 2 ).
where is the predicted value, is the actual value, and n is the duration of the observed value. The 162 weathered granite soils were randomly assigned to the calibration and the validation sets with a 7:3 ratio, which Figure 5 shows the MAPE analysis results of the regression analysis model. The MAPE of Mt. Umyeon is 7.3%, the MAPE of Mt. Guryong is 10.2%, and the MAPE of Mt. Daemo is 7.1%, which is a relatively accurate prediction.
Conclusions
In this study, we demonstrated the potential of hyperspectral techniques to estimate the variation of soil water content. The parameter most correlated with the water content in the VNIR was determined from the hyperspectral reflectance data. We also developed a regression analysis model for predicting the variation of the water content of each weathered granite soils. The research can be summarized as follows: 1) A total of 162 granite weathered soil samples were collected from Mt. Umyeon, Mt. Guryong, and Mt. Daemo in Seoul. Hyperspectral near-infrared images were acquired in 224 bands from 400 to 1000nm. 2) Water index (R970/R900), the depth at 1000nm, and the area of reflectance in NIR were used to find the parameters most relevant to water content variation in VNIR. The regression analysis result of the regression analysis showed that the area of reflectance in NIR is the best parameter correlating to the soil water content variation.
3) The variation of soil water content regression model was developed using the area of reflectance in NIR parameter. As a result of comparing and verifying with the actual soil water content variation, it was confirmed that the MAPE of each soil was less than 11%. Therefore, it can be concluded that the regression model can be successfully used to predict variations in soil water content accurately.
This study aimed to classify soil types and predict soil water content over large areas to detect landslide hazards, which traditionally require a considerable time and human power, by implementing a simple method using the hyperspectral technique. A total of 162 granite soils (Mt. Umyeon, Mt. Guryong, and Mt. Daemo) were examined by applying the hyperspectral technique. The results demonstrated that the developed models were capable of variation of water content prediction.
There are not many studies on the acquisition of soil properties for a wide area using hyperspectral reflectance; therefore, it is expected that it can be used as primary data for a later study on obtaining properties of a wide area using the hyperspectral technique. The accuracy may be somewhat inferior to the existing measurement method. However, it is expected that the variation of the water content of the wide-area can be measured using a drone in the future, so active disaster prevention is likely possible. Finally, for modeling the acquisition of soil property values, research is needed to estimate different characteristics according to the type of soil. It is determined that an applicability study using drone and satellite images is necessary for future research.\===
Domain: Agricultural And Food Sciences. The above document has 2 sentences that start with 'Soil water content', 2 sentences that start with 'Therefore, it is', 2 sentences that start with 'A total of 162 granite', 2 sentences that end with 'landslides or debris flow', 2 sentences that end with 'soil water content', 2 sentences that end with 'the MAPE of Mt', 2 sentences that end with 'using the hyperspectral technique', 2 paragraphs that start with 'In this study, we', 2 paragraphs that end with 'water content variation'. It has approximately 1656 words, 94 sentences, and 23 paragraph(s).
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Investigating a Method for a Horizontal Comprehensive Eco-Compensation Standard of Interregional Ecological Regulating Services
Horizontal eco-compensation lacks effective solutions for implementing comprehensive multifactor compensation and determining the compensation standard. To meet those needs, a method named entropy flat surface was proposed and put into practice. However, some scientific problems were found. More specifically, the measurement method of the ecological value was controversial, and the value diffusion model did not reflect the change in the value gradient caused by spatial distance, while the value diffusion had an unclear scope. Therefore, this work optimized and studied the entropy curved-surface method in the case of E’zhou City. The main goal was to build a value-surface model of ecological regulating services based on maximum entropy production. As far as a tangible normal distribution surface is concerned, the model was more consistent with the ecosystem’s energy flow characteristics. The external output of value could be precisely expressed by the dynamic and stable expansion state of the surface model. Therefore, the eco-compensation relations and results were clear. Theoretically, the E’Cheng and Huarong Districts should pay a total of 114 million CNY to the Liangzi Lake District. Our work provided a new perspective, in terms of finding a rule of the ecological regulating service values of the macro morphological structure, simulating the transmission and diffusion of multiple values in interregional areas, solving the calculation problem of the horizontal ecological comprehensive compensation standard, and clarifying the relations of compensation.
Introduction
Opinions on Improving the Ecological Protection Compensation Mechanism issued by China's State Council clearly proposed establishing a diversified eco-compensation mechanism, of which horizontal eco-compensation was a vital part [1,2]. Horizontal eco-compensation is an institutional arrangement that adjusts the interest relations between regions without administrative subordination but with close ecological relations [3]. Two main types of eco-compensation are popular, which are (1) a market operation based on the Coase theorem (the Coase theorem states that if trade in an externality is possible and there are sufficiently low transaction costs, bargaining will lead to a Pareto-efficient outcome regardless of the initial allocation of property. In practice, obstacles to bargaining or poorly defined property rights can prevent Coasian bargaining < [URL] (accessed on 7 January 2019)>. However, the Coase theorem provides a new way of thinking and a method to solve external problems through a market mechanism. Under this theory, the solution for the eco-compensation problem based on market operations belongs to Coasian PES.); (2) government operation based on Pigouvian theory (Pigouvian theory describes that the solution to correct externalities is for the government to correct the private costs of economic parties through taxation or subsidies < [URL] on 7 January 2019)>. As long as the government takes measures to make the private costs and interests equal to the corresponding social costs and interests, the allocation of resources can reach the optimal Pareto state. Similarly, government-operated eco-compensation belongs to the Pigouvian PES.). The Coasian and pure-market approach generally is regarded as a more reasonable and democratic way of eco-compensation [4]. However, it cannot be easily implemented in practice because of the reluctance of individuals to pay for ecological services [5]. Currently, the majority of eco-compensation practices in the world require the government to push and operate through mandatory policies, taxation, transfer payments or other forms of implementation, which may be considered low flexibility and low efficiency [6][7][8][9].
It is important to explore and pilot horizontal compensation in China. First, it can address the defects of vertical transfer payments, which can promote market-based and diversified development. Second, it can reduce financial expenditure pressures on the central government and motivate local potential. Third, the level of ecosystem services and their provision could be improved by the use of horizontal compensation. Fourth, it helps clarify the relation between the rights and responsibilities of adjacent administrative regions [10,11].
China's horizontal eco-compensation focuses mainly on the upstream and downstream compensation of river basins [12,13]. In the past decade, some instances of representative horizontal compensation have been implemented, such as the Xin'an River Basin compensation: Zhejiang and Anhui provinces each contributed 100 million CNY, while China's central government contributed 300 million for water environment management [14]. That amount resulted from consultation between the two provinces under the guidance of the superior (the central government then withdrew from the project while encouraging the provinces to introduce market-oriented capital). Given that success, the Tingjiang, Hanjiang, Jiuzhou, Luanhe, and Chishui Rivers have also implemented cross-provincial horizontal eco-compensation, which has generally achieved good results [15].
Overseas eco-compensation is included in most laws, governmental taxes, and preferential policies closely related to ecosystem protection [16,17]. Specific horizontal ecocompensation is carried out mainly through purchases of ecosystem services directly by local governments or other market economic methods [18][19][20][21]. In general, most foreign scholars emphasize the important role of politics, institutions, and culture in implementing eco-compensation plans, or they focus on the importance of micro-individual differences in compensation design [22,23]. They also attach importance to the influence of compensation plan participants' decisions on improving eco-compensation [17][18][19].
Generally, horizontal eco-compensation in China has the following problems: (1) most are pilot projects, have a single element, and lack comprehensive interregional compensation. The fields of practice and research are basin and water resource compensation, most of which are paid by users and polluters [10,22]. The object of compensation is water quality and quantity; there is little comprehensive compensation for various ecological regulating services between regions [24]. (2) Most of the compensation is unscientific and subjective [25,26]. Unlike standards in Western countries, few horizontal eco-compensation standards in China can be calculated and implemented according to scientific theory [27]. No interaction occurs between the recipient and the compensator, but higher government directly promotes or guides the negotiation among the stakeholders, and the compensation scope and scale are small [15,28,29]. China has not established a standard horizontal transfer payment system, and the stakeholders' willingness to compensate horizontally is weak [24,30]. Therefore, full consultation is needed between the compensator and the recipient with the government's guidance, and incentive mechanisms are needed to explore a sustainable system design [2,31].
With the improvements in China's environmental management system, eco-compensation follows the principle of "who benefits and who compensates" [1,32,33] and generally develops in a multifactor, comprehensive, and systematic direction. However, due to the externalities of the ecological regulating services, the complicated compensation relations make it difficult to determine the compensation standard [34,35]. Given the output areas of multifunction and multifactor regulating services, scientific solutions to the problems of compensation scope, objects, amounts, and so forth are still lacking and need a breakthrough [15,36].
Because E'zhou City began to explore a needed eco-compensation scheme in 2017, the authors of this study designed and studied a compensation method for that area. In 2019, a paper was published by us titled "Study on eco-compensation standard for adjacent administrative districts based on the maximum entropy production" [34]. Based on the scientific theory of maximum entropy production (MEP), that method, called entropy flat surface, solved the above problems to a certain extent and provided a standard method for interregional compensation. The research was awarded "Typical Cases of Value Realization of Ecological Products (First batch)" by the Ministry of Natural Resources of China, which was promoted nationwide in 2020 [37].
However, the original method is in its initial stage and must be further developed theoretically. For example, the model of output value cannot reflect the change in value gradient caused by spatial distance, and the scope of value diffusion is unknown. On that basis, with the support of the Hubei provincial government, the provincial department of natural resources took the Liangzi Lake District of E'zhou City as a pilot in the Notice on Pilot Project of Ecological Compensation for Realizing the Value of Ecological Products. That pilot project required continuous optimization of related research work, making up for the existing deficiencies and improving the scientific and systematic methods. The E'zhou municipal government has paid much attention to eco-compensation work and will continue it in the future. Consequently, these researchers chose E'zhou City as the object because it met practical requirements and was significant for deepening their research.
Therefore, the research goal was to find the structural rules of the macroscopic existence of functional values in space and provide a new method for interregional horizontal eco-compensation. In the perspective of methodology, a new concept was associated with the original exploration, which was called an "entropy curved surface". Particularly, an ecological regulating service value surface was established, combining environmental sciences, ecological economy, mathematical statistics, and other perspectives. In addition, mathematical modeling was implemented, and a geographical information system (GIS), remote sensing, and computer technologies were cross-integrated, and this was applied to the analysis of the public environmental management problems. The method was used to determine the output range and quantity of the ecological regulating service values, and the eco-compensation model was optimized to calculate the compensation standard objectively and to solve the problems of the quantitative evaluation method of the horizontal compensation standard.
Research Ideas
In 1935, A. G. Tansley coined the term "ecosystem" to refer to a comprehensive system consisting of a community of organisms, their abiotic environment, and their dynamic interactions. The whole system should be considered, including biological and physical factors, and these components cannot be separated or treated separately. By proposing that ecosystems are dynamic, interacting systems, Tansley's concept of ecosystems evolved into modern ecology. Modern ecology has directly attracted people's attention and research on ecosystem energy flow [38,39]. The underlying idea of this work was to consider the eco-compensation process from the idea of system, whole, and functional flow.
In our opinion, the ecological function of each region not only serves the local area but has fluidity and overflow outward [40,41] and affects such factors as gas regulation, climate regulation, and environmental purification. Horizontal eco-compensation is necessary to consider the calculation and supplementation of the fluidity value. The essence of flowing ecological value is that matter and energy are transported. However, how can the ecosystem values be calculated, and how can the complex multisystem and multifunction compensation problems be analyzed?
Eco-compensation should value the ecosystem first. The value of the ecosystem service can be calculated by the method of "equivalent factor per unit area" [42]. That method was inspired by R. Costanza and first issued by Prof. Xie. It systematizes the measuring of the ecosystem function value and aggregates it into a table (Table A1 in Appendix A). The method has significant advantages in evaluating the overall service function value of an ecosystem: it has consistent standards, is intuitive and easy to use, has fast and comprehensive evaluations, and has fewer data needs and strong generalization. Therefore, it has a good application prospect in planning decision making and policy making [43].
Maximum entropy production theory provides a systematic solution in the face of a multidimensional complex ecosystem. MEP assumes that an open system like the Earth, far from having thermodynamic equilibrium, may form a stable and ordered structure in which energy is dissipated and entropy is produced. The open system maintains a stable non-equilibrium state at the rate of maximum possible entropy increase [44,45]. In other words, the motion of matter and energy on the Earth is in a state of dynamic equilibrium. A variety of ecological regulating service functions in a particular area (such as gas regulation, climate regulation, waste treatment, and water regulation shown in Table 1) and the dynamic flow of matter and energy happens continuously. In a given unit of time, such as a year, the process of the ecological regulating service flows follows a specific statistical rule, and if a given mean and variance were set, it is likely to form a normal distribution [46,47]. That state can be described by an ecological regulating service value surface. The central limit theorem provides theoretical support for the value surface tending to a normal distribution. Based on MEP, it is conceived that if the value of the ecological regulating services is visualized, the dynamic equilibrium state of the value surface is likely to form a normal bell-shaped distribution. The value curved surface expands around to form a dynamic and stable surface structure [48,49]. When it extends to the adjacent districts, the surface can be Entropy 2023, 25, 1319 5 of 23 calculated to obtain the ecological regulation output value, and the transmission relation of eco-compensation is formed naturally.
Framework
Based on the above novel ideas, the research in this study was under the framework of "calculation, modeling, and validation" to study the eco-compensation methods. Relevant information and data were collected and investigated. The main parts were (1) calculation of ecosystem and regulating service values based on the equivalent-factor method, (2) construction of an ecological regulating value curved-surface model based on MEP, and (3) validation of the curved-surface model. The second part was the focus of this study. Parts 1 and 3 supported the value data in the early stage and the empirical study in the later stage. Finally, the model was used to calculate the output value and determine the compensation standard. Specific study steps can be seen in Figure 1 and in Section 2.3.
visualized, the dynamic equilibrium state of the value surface is likely to form a norm bell-shaped distribution. The value curved surface expands around to form a dynam and stable surface structure [48,49]. When it extends to the adjacent districts, the surfa can be calculated to obtain the ecological regulation output value, and the transmissi relation of eco-compensation is formed naturally.
Framework
Based on the above novel ideas, the research in this study was under the framewo of "calculation, modeling, and validation" to study the eco-compensation methods. Re vant information and data were collected and investigated. The main parts were (1) c culation of ecosystem and regulating service values based on the equivalent-fac method, (2) construction of an ecological regulating value curved-surface model based MEP, and (3) validation of the curved-surface model. The second part was the focus this study. Parts 1 and 3 supported the value data in the early stage and the empiri study in the later stage. Finally, the model was used to calculate the output value a determine the compensation standard. Specific study steps can be seen in Figure 1 and Section 2.3.
Research Data and Location
E'zhou City is in Hubei Province, China, which comprises the E'cheng, Huarong, a Liangzi Lake Districts. The three districts are interregional and adjacent to each oth covering an area of 1596 km 2 (Figure 2). Eco-compensation is conducted among the th districts. Demand data include remote sensing images, environmental monitoring da water conservancy data, meteorological data, the Third National Land Survey data ("th survey" for short), agricultural product prices, and social and economic data within t research area.
Research Data and Location
E'zhou City is in Hubei Province, China, which comprises the E'cheng, Huarong, and Liangzi Lake Districts. The three districts are interregional and adjacent to each other, covering an area of 1596 km 2 (Figure 2). Eco-compensation is conducted among the three districts. Demand data include remote sensing images, environmental monitoring data, water conservancy data, meteorological data, the Third National Land Survey data ("third survey" for short), agricultural product prices, and social and economic data within the research area.
Ecosystem Value
1. Correspondence between land type and ecosystem type: According to the ecosystem types of Table 1 [43] and the land data of the third survey, from the concept, the land types of E'zhou city and the ecosystem types in the table were selected and corresponded.
2. Adjustment of the equivalent-factor value: The factor values of different levels were determined in accordance with the water quality and forest stock grades in the Natural Resources Balance Sheet (the Natural Resources Balance Sheet is a natural resources status report reflecting the levels and changes of natural resource assets and their value at the beginning and end of a year [50]). Then, a new equivalent-factor table (Table 1) was adjusted and established.
3. Value of ecosystem (ecosystem value is an important part of natural resource assets. It includes ecosystem stock values comprising forest, wetland, ocean, and other ecosystems, and ecological resources such as water and biological, marine, environmental, and other resources. Ecosystem value also includes the ecosystem flow value, consisting of ecosystem products produced by the ecosystem, environmental regulation, water regulation, and other ecosystem service values [51]) and their regulating services: Using Table 1, the values of a standard equivalent factor (according to the comprehensively determined prices of agricultural products including rice, wheat, and corn), the resources' areas and the ecosystem were calculated using Equation (1) in the study area. Table 1 includes 4 regulating services (gas regulation, climate regulation, waste treatment, and water regulation) that have the characteristics of flow and diffusion. Their concepts can be seen in Table A2. In the geographic space, GIS was used to grid the 4 regulating service values, and the value distribution was recorded as H0: where ESV is the ecological service value, t is a particular year, i is a specific ecological function (total 11 functions), j is an ecosystem type (total 8 types), S is the area of the ecosystem type, X is the revised equivalent factor, and D is the price of a standard equivalent factor whose value follows the Consumer Price Index (CPI).
Ecological Regulating Service Value Curved-Surface Model
1. Position of the ellipse on the projection of the curved surface: The geographic boundary coordinates of each study area were determined using GIS analysis, and the coordinates were imported into MATLAB R2013b for ellipse fitting. The center point of the fitting ellipse was (xj, yj), the length of the major axis was Lx, and the length of the minor axis was Ly.
2. Basic model of a single-value surface: A curved surface will likely express a bellshaped normal distribution form. A 3D coordinate system x-y-z was established in
Ecosystem Value
1. Correspondence between land type and ecosystem type: According to the ecosystem types of Table 1 [43] and the land data of the third survey, from the concept, the land types of E'zhou city and the ecosystem types in the table were selected and corresponded.
2. Adjustment of the equivalent-factor value: The factor values of different levels were determined in accordance with the water quality and forest stock grades in the Natural Resources Balance Sheet (the Natural Resources Balance Sheet is a natural resources status report reflecting the levels and changes of natural resource assets and their value at the beginning and end of a year [50]). Then, a new equivalent-factor table (Table 1) was adjusted and established.
3. Value of ecosystem (ecosystem value is an important part of natural resource assets. It includes ecosystem stock values comprising forest, wetland, ocean, and other ecosystems, and ecological resources such as water and biological, marine, environmental, and other resources. Ecosystem value also includes the ecosystem flow value, consisting of ecosystem products produced by the ecosystem, environmental regulation, water regulation, and other ecosystem service values [51]) and their regulating services: Using Table 1, the values of a standard equivalent factor (according to the comprehensively determined prices of agricultural products including rice, wheat, and corn), the resources' areas and the ecosystem were calculated using Equation (1) in the study area. Table 1 includes 4 regulating services (gas regulation, climate regulation, waste treatment, and water regulation) that have the characteristics of flow and diffusion. Their concepts can be seen in Table A2. In the geographic space, GIS was used to grid the 4 regulating service values, and the value distribution was recorded as H 0 : where ESV is the ecological service value, t is a particular year, i is a specific ecological function (total 11 functions), j is an ecosystem type (total 8 types), S is the area of the ecosystem type, X is the revised equivalent factor, and D is the price of a standard equivalent factor whose value follows the Consumer Price Index (CPI).
Ecological Regulating Service Value Curved-Surface Model
1. Position of the ellipse on the projection of the curved surface: The geographic boundary coordinates of each study area were determined using GIS analysis, and the coordinates were imported into MATLAB R2013b for ellipse fitting. The center point of the fitting ellipse was (x j , y j ), the length of the major axis was Lx, and the length of the minor axis was Ly.
2. Basic model of a single-value surface: A curved surface will likely express a bell-shaped normal distribution form. A 3D coordinate system x-y-z was established in MATLAB, where x-y represents geographical coordinates, and z represents ecological value per unit area. The integral of the initial value surface to the fitted ellipse area was equal to the total value of the corresponding ecological regulating service in the study area. No matter how the surface shape changed, the total value remained unchanged. The 2D normal probability density function was proposed to construct the curved surface, that is, the potential function of the value flow-the general solution of the differential Equation (2) (set as f j ).
where the value of a j determines the total size of the ecological value contained in the surface; the sign of a is positive to indicate that the surface is convex; a j = H j /[2π (Lx j b)(Ly j c)]; H j is the value of an ecological regulating service measured in the j region; Lx j is the length of the long axis; Ly j is the length of the short axis in the j region; and b and c are the adjustment coefficients, which are used to adjust the flattening degree of the surface in the x and y directions, respectively.3. Surface expansion state: f j expands in all directions, and the expanded shape on the plane was consistent with that of all study areas. In MATLAB, the initial state of f j is that b and c are 1. Then, parameters b and c gradually advanced the value to 1, 2, 3, . .., n in the trial calculation programming operation, achieving a surface shape that gradually became a flat, smooth process.
4. Surface extension boundary setting: The µ value was set, which was the base value of the unit area ecological value within the research range, such as wasteland and bare land values. When the functional value was z = µ on the surface, the range formed by the surface coordinate was the judgment value B j of the diffusion boundary. The curved surface expanded outward, and the height decreased, and its stability can be considered if the following conditions are met. The trial was programmed to (1) ensure that the surface extended to cover more than 90% of the research land area, and (2) at the same time, the value within the scope of the extended value-containing surface accounted for over 90% of the total value. The surface shape can be accepted if the above conditions are satisfied.
5. Synthesis of multiple surfaces: Multiple surfaces were superimposed using functions (Max {f 1 , f 2 , . .., f n }) as the envelope surface, and then the synthetic surface M was made continuous and smooth using the moving average filtering method. The peripheral boundary of surface M was B', which was part of B j 's peripheral synthesis (see Figure 3a,b). Screening of suitable natural physical quantities and validation of the design: Given the regulation function, the physical quantities were selected by combining qualitative and quantitative analysis methods. They included data queries and literature analyses to judge their relation to ecological value on time scales, different seasons, and ecological benefit impacts. Climate regulation may be related to temperature and humidity; concentrations of particulate matter, nitrogen oxide, and volatile organic compounds can reflect gas regulation. Water regulation may be closely related to precipitation and evapotranspiration. Many objects had to be tested, and the relations were complex, so the specific test design had to be flexibly adjusted based on the actual situation and data availability.
2. Distribution surface of natural physical quantity: Measurable physical quantities, such as air pollutants, temperature, and humidity, were monitored multiple times in different time periods using Sniffer4D, a mobile air-monitoring device, to obtain multiple sets of discrete data. A trend surface of physical quantities was fitted by using a spatial interpolation and global polynomial method (the fitting surface was collectively called Q). In corresponding geographical coordinates, several batches of data were randomly extracted from value surface M and trend surface Q to form vectors to be verified.
3. Validation of surface model: The corresponding variables on the M and Q surfaces were verified by a 2-sample t-test and a Pearson correlation analysis, respectively, to test the mean difference and correlation between the 2 data groups. If the t-test difference was significant, it indicated that the samples were not comparable or there were problems and the data should be checked from the source, or the test group should be redesigned. If the correlation analysis was weak or opposite, the model had to be revised to modify its spatial position or adjust the surface's flatness. If Q showed prominent non-normal distribution characteristics, other probability density functions could be used to reset the model.
4. Output value of the regulating service and eco-compensation results: For the value output area, the extended surface would cover surrounding areas. By integrating the value of the area, the value obtained in the value input area can be calculated. The output value of each research area can be calculated, and then the expenditure and income of each research area can be compared to calculate the net output value and determine the eco-compensation amount.
Adjustment of the Corresponding Relation between Land and Ecosystem
There are 13 land categories according to the third survey: wetland, cultivated land, planting garden, forest land, grassland, commercial and service land, industrial and mining land, residential land, public use land, special land, transportation land, water and water conservancy facilities land, and other land ("wetland" is the latest addition) (the Rules for the Identification of Land Categories for the Third National Land Survey (provided by the Ministry of Natural Resources of China) shall apply to the latest land classifications. It added "Wetland" in "Current Land Use classification GB/T 21010-2017", which has the original 12 land categories).
In light of the corresponding relations between land use properties and equivalent factors, and combined with the characteristics of natural resources and the environment in E'zhou, the following eight main systems and land use classifications are proposed: I.
Paddy field-corresponds to paddy fields and irrigated land in "cultivated land" II. Dry land-corresponds to the dry land in "cultivated land" III. Broad-leaved forest-corresponds to tree forest, bamboo forest, shrub forest, and other forest types IV. Garden-corresponds to "planting garden" V.
Shrub grass-corresponds to "grassland"; it is mainly general grassland, without natural/artificial forage grass, etc.
VI. Water area and wetland-corresponds to "water area and land for water conservancy facilities", including rivers, lakes, ditches, reservoirs, etc. VII. Desert-corresponds mainly to "other land", including sandy land, bare land, rock and gravel land, etc. VIII. Bare land-corresponds to all kinds of construction land, such as commercial service, residential, facilities' agricultural land, industry, mining, storage, roads, special land and idle land, etc.
Adjustment of Equivalent-Factor Table
Based on the original equivalent-factor table (see Table A1), III, IV, and VI in Table 1 are adjusted factors, taking forest quality and water quality into account, while other factors remain unchanged. The specific details are as follows: (1) the medium quality of broadleaf corresponds to the value of the original table and is reduced by 50% in the original value, corresponding to "low", and the other is increased by 50%, corresponding to "high." (2) The garden factor is half of the broad-leaved forest and paddy field factor. Referring to the Technical Provisions for Continuous Inventory of National Forest Resources, the forest is "low" because its average stock is less than 50 m 3 /ha.(3) The factors reflecting water quality are divided into five levels in accordance with the Environmental Quality Standards for Surface Water, among which Class IV corresponds to the original factors (because the surface water of lakes in China is approximately Class IV), and other levels increase or decrease by 20% successively. In addition, the water regulation factors of Class I to V remain unchanged (Table 1).
The economic value corresponding to a standard equivalent-factor value was 3406 CNY/ha in 2010 [43]. From 2011 to 2019, according to the annual average Consumer Price Index (CPI) in China, the economic value of a factor was 4256 CNY/ha. After adjustment, the adjusted table, the land area data of the third survey, and a standard equivalent-factor value were used to calculate the ecosystem value of the three districts. The results show that the ecological value of E'zhou City was 15.63 billion CNY, that of E'cheng District was 5.224 billion CNY, that of Huarong District was 5.123 billion CNY, and that of the Liangzi Lake District was 5.284 billion CNY. The unit area values of the three districts were 85,956 CNY/ha, 103,959 CNY/ha, and 106,548 CNY/ha, respectively. Overall, the Liangzi Lake District was slightly higher than the other two areas.
The values of the regulating service (includeincludeing gas regulation, climate regulation, waste treatment, and water regulation) were obtained: (1) regulating service values in E'cheng District were 298 million, 526 million, 394 million, and 2.114 billion CNY, respectively. The total regulation value was 3.332 billion, accounting for 63.78% of the ecosystem value.(2) For the Huarong District, they were 277 million, 438 million, 381 million, and 2.177 billion CNY, respectively. The total was 3.273 billion, accounting for 63.89%.(3) For the Liangzi Lake District, the values were 291 million, 518 million, 394 million, and 2.124 billion CNY, respectively. The total was 3.327 billion, accounting for 62.96%.
Curved-Surface Model Building
The GIS data of the boundary and grid center point coordinates were imported into MATLAB. The boundary coordinates were used for ellipse fitting and the standard ellipse equation; the grid center point coordinates were used for value integration. The research area was divided into several 2 × 2 km grids, and the value integral was obtained by multiplying the value on the surface at the grid's center point by the grid's area.
Initial Form of the Curved Surface
The coordinates of the administrative area boundary of each research area were input into MATLAB, and ellipse fitting was performed. The ellipse boundaries of Liangzi Lake District, Huarong District, and E'cheng District, the center point O, the long and short axes Lx and Ly, and the inclination angle θ were obtained, respectively.
The general elliptic Equation (3) can be obtained by elliptic fitting of the boundary of three districts: Then, the central coordinates, the long and short axes, and the long axis inclination angle of the ellipse can be obtained using Equation (4): The results are as follows (subscripts 1, 2, and 3 represent Liangzi Lake, Huarong, and E'cheng Districts, respectively) (Figure 4a): Then, the central coordinates, the long and short axes, and the long axis inclination angle of the ellipse can be obtained using Equation ( 4): , The results are as follows (subscripts 1, 2, and 3 represent Liangzi Lake, Huarong, and E'cheng Districts, respectively) (Figure 4a): (1) O1 = (914,938.9,3,237,419.9),O2 = (919,735.9,3,270,589.9),O3 = (939,920. Figure 4b,c shows the initial value surfaces of Liangzi Lake District, taking gas regulation as an example. Under the initial conditions, the regulation value is mainly concentrated in its own region but not fully diffused to the other two districts (this moment in the model b = c = 1). The value surface is essentially an infinite outward expansion and has value at the far end of the surface, but the distribution at the far end is very thin. The dark purple represents a low value: the large area in Figure 4 shows the color. Figure 4b,c shows the initial value surfaces of Liangzi Lake District, taking gas regulation as an example. Under the initial conditions, the regulation value is mainly concentrated in its own region but not fully diffused to the other two districts (this moment in the model b = c = 1). The value surface is essentially an infinite outward expansion and has value at the far end of the surface, but the distribution at the far end is very thin. The dark purple represents a low value: the large area in Figure 4 shows the color.
Extension of Curved Surface
The above method shows that µ reflects the ecological background value, and the cross between the µ value and the surface defines the range and forms the boundary B j . To meet the requirements of 90% coverage of the study area and the containing value of not less than 90%, the selection of the background value requires trials according to the actual situation, so the specific selection of the µ value set three scenarios: (1) paddy field, dry land, bare land, wasteland; (2) dry land, bare land, wasteland; (3) bare land, wasteland.
After a trial calculation, the µ was selected as the third case; paddy field and dry land belong to farmland, so, as the background value, their value is relatively high, therefore only the bare land and wasteland value was considered as the background µ value.
Removing the "highland" area of ecological value (including farmland, forest, grassland, water, and wetland), the base value (bare land and wasteland) µ of the four regulations were 2115.9,777.1, 8714.6, and 3523.6 CNY/km 2 , respectively.
If the above conditions are met, the shape of surface diffusion is a stable state and a high-probability event with high reliability. After calculation, the adjustment coefficients b and c of the ecological value-surface diffusion to stability are shown in Table 2. 5 and Table 3. Note: L, H, and E stand for Liangzi Lake, Huarong, and E'cheng districts, respectively.
L to H L to E H to L H to E E to L E to H L's Income H's Income E's Inco
The ecological value surfaces of the three districts of E'zhou were superimpos obtain the synthetic ecological regulation value-curved surfaces, as shown in Figure The ecological value surfaces of the three districts of E'zhou were superimposed to obtain the synthetic ecological regulation value-curved surfaces, as shown in Figure 6. The ecological value surfaces of the three districts of E'zhou were superimposed to obtain the synthetic ecological regulation value-curved surfaces, as shown in Figure 6.
Validation of Curved-Surface Model
Two validations were conducted in total. The data provided by government departments for the first test were of limited variety and covered a small area. The validity of
Validation of Curved-Surface Model
Two validations were conducted in total. The data provided by government departments for the first test were of limited variety and covered a small area. The validity of the model was initially discussed from only two perspectives: the relation between the gas regulation and the PM 2.5 average concentration, and the relation between the waste treatment and the average concentration of ammonia nitrogen in water.
The first validation idea was to compare the data of the regulating service value surface with the monitoring data. In the study area, the higher the gas regulation value, the lower the PM 2.5 concentration should be; the higher the waste treatment value, the lower the concentration of ammonia nitrogen in the water, showing a negative correlation.
The first validation was unsatisfactory. The correlation between PM 2.5 and the gas regulation value was 0.84, whereas the correlation between the ammonia nitrogen and the waste treatment value was 0.077, contrary to the verification logic (it should have been a negative correlation). That indicates that the data used had almost no correlation with the value surface.
Considering the problems in the first validation process, the portable air monitor Sniffer4D was adopted to obtain more environmental elements and a more extensive geographical range of data. The equipment records a batch of data every second and monitors the environmental elements by vehicular means (Figure 7). The specific elements include PM 1 , PM 2.5 , PM 10 , SO 2 , NO 2 , O 3 , CO, VOCs, air pressure, humidity, temperature, longitude, and latitude (PM 1 is ultrafine particulate matter, PM 2.5 is fine particulate matter, and PM 10 is inhalable particulate matter. SO 2 is sulfur dioxide, NO 2 is nitrogen dioxide, O 3 is ozone, CO is carbon monoxide, and VOCs are volatile organic compounds. They are common air pollutants.). In the second validation, air humidity and climate regulation, PM 2.5 , PM 10 , VOCs, and gas regulation were initially selected to determine the model's effectiveness.
Entropy 2023, 25, x FOR PEER REVIEW 15 of 23 lower the PM2.5 concentration should be; the higher the waste treatment value, the lower the concentration of ammonia nitrogen in the water, showing a negative correlation. The first validation was unsatisfactory. The correlation between PM2.5 and the gas regulation value was 0.84, whereas the correlation between the ammonia nitrogen and the waste treatment value was 0.077, contrary to the verification logic (it should have been a negative correlation). That indicates that the data used had almost no correlation with the value surface.
Considering the problems in the first validation process, the portable air monitor Sniffer4D was adopted to obtain more environmental elements and a more extensive geographical range of data. The equipment records a batch of data every second and monitors the environmental elements by vehicular means (Figure 7). The specific elements include PM1, PM2.5, PM10, SO2, NO2, O3, CO, VOCs, air pressure, humidity, temperature, longitude, and latitude (PM1 is ultrafine particulate matter, PM2.5 is fine particulate matter, and PM10 is inhalable particulate matter. SO2 is sulfur dioxide, NO2 is nitrogen dioxide, O3 is ozone, CO is carbon monoxide, and VOCs are volatile organic compounds. They are common air pollutants.). In the second validation, air humidity and climate regulation, PM2.5, PM10, VOCs, and gas regulation were initially selected to determine the model's effectiveness. The second validation idea was as follows: similar to the first time, the higher the gas regulation value, the lower the PM2.5, PM10, and VOC concentration. The value and monitoring data should show a negative correlation; the greater the value of climate regulation, the higher the relative humidity, and the value data should show a positive correlation with the monitoring data.
1. Validation of gas regulation value: Several PM2.5, PM10, and VOC data obtained by the device were randomly selected by GIS. There was no significant difference between the data and gas regulation by t-test, t(PM2.5)= 0.3133, t(PM10) = 0.1874, t(VOCs) = 0.5679, all >0.05. Figure 7 shows the data collection track. Those data were used to form a surface through GIS spatial interpolation, which covered the whole area of E'zhou. Then, the values extracted from random points generated on the surface formed the corresponding (x, y, z1) values. After that, the parameters of the gas regulation value surface were extracted at the corresponding coordinate points, and the values of (x, y, z2) were obtained.z1 and z2 were tested for correlation. The correlations between PM2.5, PM10, VOC data, and gas regulation data directly output by Excel were -0.11, -0.53, and -0.05, respectively (Figure 8a-c).
2. Validation of climate regulation value: There was no significant difference between The second validation idea was as follows: similar to the first time, the higher the gas regulation value, the lower the PM 2.5 , PM 10 , and VOC concentration. The value and monitoring data should show a negative correlation; the greater the value of climate regulation, the higher the relative humidity, and the value data should show a positive correlation with the monitoring data.
1. Validation of gas regulation value: Several PM 2.5 , PM 10 , and VOC data obtained by the device were randomly selected by GIS. There was no significant difference between the data and gas regulation by t-test, t (PM2.5)= 0.3133, t (PM10) = 0.1874, t (VOCs) = 0.5679, all >0.05. Figure 7 shows the data collection track. Those data were used to form a surface through GIS spatial interpolation, which covered the whole area of E'zhou. Then, the values extracted from random points generated on the surface formed the corresponding (x, y, z 1 ) values. After that, the parameters of the gas regulation value surface were extracted at the corresponding coordinate points, and the values of (x, y, z 2 ) were obtained.z 1 and z 2 were tested for correlation. The correlations between PM 2.5 , PM 10 , VOC data, and gas regulation data directly output by Excel were −0.11, −0.53, and −0.05, respectively (Figure 8a-c).
Entropy 2023, 25, x FOR PEER REVIEW 16 of 23 were generated to form the corresponding (x, y, z1). The parameters of the climate regulation value surface were also extracted at the same coordinate points, and the values of (x, y, z2) were obtained.z1 and z2 were tested for correlation. The correlation between the two columns of data directly output by Excel was 0.253. The surface of the climate regulation value and the sample points of the humidity value were drawn using MATLAB (Figure 8d). From the comparison of natural physical quantities (PM2.5, PM10, VOCs, and humidity) with the gas regulation and climate regulation surfaces, the verification result was an improvement over the first verification after the data range expansion.
First, in the first validation, the amount of data and the coverage were too small, the comparability was weak, and the test results were illogical. The second validation was an improvement. Although the negative correlations between PM2.5 and VOC and gas regulation were insignificant, they were in general accord with the validation logic, and PM10 had a good negative correlation. Additionally, the comparisons between different physical quantities and gas regulations did not have ideal results. The result of PM10 at least provides evidence that the surface was comparable with some air pollutants. Moreover, climate regulation also showed a positive correlation with humidity.
Second, there was a large conceptual difference between natural physical quantities and the value of the curved surface itself. The natural one was arbitrary and not predictive, while the surface was a conceived ideal value concept derived from the ecological economy and based on the MEP assumptions. Consequently, comparison and validation of the two were a considerable challenge and difficult to test, so they were unlikely to result in a high correlation. Therefore, at least the trend of the above results was ideal, which also provides evidence for the model's credibility.
Validation of climate regulation value:
There was no significant difference between humidity and climate regulation by t-test (t = 0.6845, p > 0.05). The humidity space was interpolated by GIS to form a surface, and then the values extracted from random points were generated to form the corresponding (x, y, z 1 ). The parameters of the climate regulation value surface were also extracted at the same coordinate points, and the values of (x, y, z 2 ) were obtained.z 1 and z 2 were tested for correlation. The correlation between the two columns of data directly output by Excel was 0.253. The surface of the climate regulation value and the sample points of the humidity value were drawn using MATLAB (Figure 8d).
From the comparison of natural physical quantities (PM 2.5 , PM 10 , VOCs, and humidity) with the gas regulation and climate regulation surfaces, the verification result was an improvement over the first verification after the data range expansion.
First, in the first validation, the amount of data and the coverage were too small, the comparability was weak, and the test results were illogical. The second validation was an improvement. Although the negative correlations between PM 2.5 and VOC and gas regulation were insignificant, they were in general accord with the validation logic, and PM 10 had a good negative correlation. Additionally, the comparisons between different physical quantities and gas regulations did not have ideal results. The result of PM 10 at least provides evidence that the surface was comparable with some air pollutants. Moreover, climate regulation also showed a positive correlation with humidity.
Second, there was a large conceptual difference between natural physical quantities and the value of the curved surface itself. The natural one was arbitrary and not predictive, while the surface was a conceived ideal value concept derived from the ecological economy and based on the MEP assumptions. Consequently, comparison and validation of the two were a considerable challenge and difficult to test, so they were unlikely to result in a high correlation. Therefore, at least the trend of the above results was ideal, which also provides evidence for the model's credibility.
Policy Implications
In China, most eco-compensation and its promotion are initiated and implemented by the government. As the comprehensive decision maker, the government not only wants to know the will of the public but also to understand the value of the ecosystem and ecocompensation amount from a macro and systematic perspective. At present, China attaches great importance to environmental protection. Key river basins and localities across the country are promoting and exploring horizontal eco-compensation. The eco-compensation laws or policies follow the principle of "who benefits and who compensates", and the specific compensation content, standard, and method are usually carried out according to contracts signed between different regions.
Our work has been adopted by the local government to formulate the three-zone compensation policy in E'zhou City. From 2017 to 2019, Liangzi Lake District received ecocompensation of 50.31 million CNY, 82.86 million CNY, and 105.31 million CNY, respectively, jointly paid by E'zhou City Finance, the E'cheng District, and the Huarong District. The Liangzi Lake District of E'zhou City is an ecological environmental protection area, where the regional development is backward, and the per capita income is low after the restriction of development. Eco-compensation in E'zhou City has a positive impact on promoting local development, and the funds can be used to maintain the cost of environmental protection, promote infrastructure construction, motivate green industries or tourism, and improve the income and living standards of local people.
Method Comparisons
Our previous research work published in 2019 can be called the Entropy Flat Surface method (version 1.0). The basic idea and characteristics of version 1.0 were that each research unit's ecological function (and its value) would spread to the surrounding area. It was assumed that that value diffusion would fully spread in the larger scope, consisting of the research area and the designated area, and would reach a uniform state. In other words, ecological functions and values are not distributed like a bell curve but like a plane, which is an ideal extreme case. That assumption made the mathematical model simple. Only the difference between the unit area of each high ecological value and the ecological average value could be obtained to calculate the total ecological value of the highland flowing out. Then, the compensation standard of each unit in the research area was revised and optimized by considering the actual economic development situation. In the calculation process, three districts having three equivalent-factor tables were used to reflect the environmental quality differences. Fewer data, including the equivalent-factor table, land area, GDP, and so on, were needed for calculation and could be obtained through Excel (Microsoft Office 2019).
The output of the regulating service value in this study was calculated using the entropy curved-surface method (version 2.0); its important characteristics and optimization lie in the following: (1) the eco-compensation method is more systematic and scientific than the previous method. First, the previous method exaggerated the ecological value gap between districts to reduce the subjective adjustments of equivalent factors in calculating value. Second, the value diffusion model is more in line with the description of MEP. The ecological value in highlands expanded outward, and the value distribution was in the form of a normal distribution surface rather than a plane; that was a marked improvement. The ecological value in this model was concentrated in the center, and the further it expanded, the lower the value became, leading to an apparent decrease in the value of ecological output.(The output of version 1.0 was 270 million CNY [36], while in this case, it was 110 million CNY.)It is not that the greater the compensation, the better; we hoped to obtain more scientific calculation results.(2) The eco-compensation process was programmed, standardized, and objectified. In version 1.0, the output value's diffusion scope, namely, the designated area, and the equivalent factors in three tables contained artificial subjectivity or were predetermined. However, the original factors were not modified very much in this study, which kept the factors consistent and standard for the three districts, resulting in a pronounced decrease in the total amount of compensation.(3) Steps were simplified, and there was a highly optimized logical process. Version 2.0 dispensed with the designated area (it referred to administrative units that surrounded the study area) and simply analyzed the study area. The analysis of GDP and the ecosystem service value (ESV) in the study area and designated area, and the distribution of compensation amount were all removed. At that point, it was no longer necessary to extract the compensation weight determined by GDP and ESV for the compensation results. What the government needs is the most objective result possible. As for some specific operations of eco-compensation, whether or not a district has the ability and willingness to pay, it needs comprehensive coordination.
The previous and new methods are compared in Table 4. (1) The results of eco-compensation should be made more systematic and scientific, and the model should be more in line with the characteristics of ecosystem energy flow.(2) Analysis is programmed, standardized, and objectified with less subjectivity.(3) Its greater universality streamlines steps with no need to set up designated areas, markedly simplifying the logical process.
Disadvantages
(1) The model is idealized, which does not conform to the characteristics of energy flow and the dissipation structure of ecosystems and is not a normal distribution.
(2) Determining the data of designated areas outside the research area is necessary. Data, such as GDP, administrative divisions, and various land resources, need to be determined, which is in great demand.(3) Compensation funds should be allocated according to GDP and ecological values.
The calculation operation is more difficult for administrative staff. ArcGIS and MATLAB software is needed for analysis and operation.
Limitations and Future Work
(1) Methods for value evaluation The limitation of the equivalent-factor method is that it is considered by some scholars to be subjective and unscientific. There are many ways to account for ecosystem value. The first type is the market-or semi-market-based theory in economic principles. From the perspective of ecological protectors, the standard of eco-compensation is proposed considering direct input and opportunity cost. From the perspective of profit of ecological beneficiaries, the contingent valuation method, the selection test method, the market value method, and the alternative market method are commonly used to measure the basis of payment of beneficiaries [4,20].
Second, from the perspective of ecosystem service value, the value evaluation can be obtained by determining the amount of ecosystem service functional quantity and the unit price of functional quantity, which is referred to as the "Functional value method" (the equivalent-factor method which is suitable for ecosystem valuation in China is derived from it). More specifically, like the market value method, the opportunity cost method, the shadow engineering method, the human capital method, the tourism cost method, the production cost method, etc., are usually used to estimate the value of the ecosystem service function [23]. "Functional value method" is the basic method for carrying out value evaluation and is the mainstream method for determining eco-compensation standards at home and abroad.
In September 2020, the "Technical Guideline on Gross Ecosystem Product" (1.0 Version), i.e., GEP accounting was released, which promoted the functional value method from a theoretical stage to a standardized practice. In 2021, the GEP accounting concepts and methodologies were included in the Framework for Ecosystem Accounting (SEEA-EA) by the United Nations Statistical Commission. Many works in the literature use the functional value method to calculate the value of ecosystem service or put forward eco-compensation standards [51][52][53].
Therefore, in addition to the equivalent-factor method, the functional value method (GEP accounting system) is also the current mainstream method; different valuation methods will be used for value accounting in the future, which may cause completely different compensation results.
(2) Uncertainty of validation At present, one or two samples used for validation do not easily correspond to the value surface based on the annual average state, which is the spatiotemporal correspondence having poor performance with contingencies and uncertainties. In the future, on the one hand, the number of the sampling batches and coverage in space can be increased so that there is a better validation response in time and space; on the other hand, it may be necessary to use other methods, such as the InVEST model, to estimate water evapotranspiration to provide better experimental conditions for model validation.
Conclusions
Entropy curved surface is a creative method based on equivalent factors and MEP. A set of interregional, horizontal, ecological regulating service value, curved-surface models were constructed, an important improvement on the original method. The equivalent-factor method can be used to estimate ecosystem value quickly and effectively and can also be adjusted according to the actual situation. Maximum entropy production explains the flow features of the ecological function. In the peaks of ecological value, the value might be normally distributed with high probability and is in dynamic equilibrium. Therefore, the value is regarded as a tangible normal distribution surface. The expansion of the surface expresses the external output of value, and the eco-compensation relation becomes clear.
In the example of E'zhou City, the new method was used to calculate the eco-compensation standard. It found a rule for the ecological regulation function value of a macro morphological structure, simulated the transmission and diffusion of multiple values in interregional areas, solved the calculation problem of the horizontal ecological comprehensive compensation standard, and clarified the relation of "what, who, and how much should be compensated". The new method improves the systematic and scientific characteristics of eco-compensation results and makes the model more consistent with the characteristics of the energy flow of an ecosystem. The analysis is programmed, standardized, and objectified with less subjective thought. It has better universality, streamlines steps, and markedly simplifies the logical process.
The results show that the ecological value of E'zhou City was 15.63 billion CNY, that of the E'cheng District was 5.224 billion CNY, that of the Huarong District was 5.123 billion CNY, and that of the Liangzi Lake District was 5.284 billion CNY. The unit area values of the three districts were 85,956 CNY/ha, 103,959 CNY/ha, and 106,548 CNY/ha, respectively. Little difference was observed in ecological value among the three districts, but the ecological value density of the Liangzi Lake District was the highest. Furthermore, ArcGIS and MATLAB applications were used as the main tools to numerically calculate the horizontal eco-compensation, and the final compensation results among the three districts of E'zhou were as follows: Liangzi Lake District should be compensated 114.40
Water supply
The water resources provided by various ecosystems are used for living, agriculture, and industrial processes.
Regulating
Gas regulation Maintains atmospheric chemical composition balance, such as releasing oxygen and absorbing CO 2 , SO 2 , NO x , etc.
Climate regulation
Maintains temperature, keeps humidity, and increases precipitation.
Water regulation Intercepts, absorbs, and stores precipitation, regulates runoff, restores flood water, and reduces drought and water logging.
Waste treatment
Vegetation and biomes remove the excess nutrients and degrade compounds, intercept dust, decontaminate, etc., including purification of water and air.
Soil formation
Reduces the loss of surface soil, protects soil fertility, reduces sediment deposition, and reduces the wind sand.
Nutrient cycling
Maintains the storage, circulation, biological and non-biological element exchange of nutrients in the ecosystem.
Biodiversity
Provides wildlife genetic sources and evolution; provides habitat.
Cultural
Cultural recreation Provides the entertainment, aesthetics, culture, science, education, and spiritual value of the natural environment.
Figure 1 .
Figure 1. Research framework and steps.
Figure 1 .
Figure 1. Research framework and steps.
Figure 3 .
Figure 3. (A) The subfigure labels (a-d) illustrate that (a) the geometric center of the research area corresponding to the center of the ellipse, (b) the center of initial value surface corresponding to the center of the ellipse, (c) extension of a single surface, (d) synthesis of multiple surfaces. Two-dimensional section diagram of value surface showing that H0 is the natural distribution of the regulation value, and H is the regulation value of H0 after normalization and visualization. The total value of fj before and after expansion remained unchanged, and μ was the background value of ecological value per unit area within the research scope, such as the value of wasteland and bare land.(B) Three-dimensional diagram of the synthetic value surface. The x-o-y plane represents geographical coordinates, and z represents the regulating service value per unit area.
Figure 3 .
Figure 3. (A) The subfigure labels (a-d) illustrate that (a) the geometric center of the research area corresponding to the center of the ellipse, (b) the center of initial value surface corresponding to the center of the ellipse, (c) extension of a single surface, (d) synthesis of multiple surfaces. Two-dimensional section diagram of value surface showing that H 0 is the natural distribution of the regulation value, and H is the regulation value of H 0 after normalization and visualization. The total value of f j before and after expansion remained unchanged, and µ was the background value of ecological value per unit area within the research scope, such as the value of wasteland and bare land.(B) Three-dimensional diagram of the synthetic value surface. The x-o-y plane represents geographical coordinates, and z represents the regulating service value per unit area.
Figure 4 .
Figure 4. (a) Boundary of each district and fitting elliptical boundaries.(b) Top view and (c) isometric view of initial value-curved surface of gas regulation in Liangzi Lake District as an example.
Figure 5 .
Figure 5. Relationship and net payments of eco-compensation among E'zhou's three districts
Figure 5 .
Figure 5. Relationship and net payments of eco-compensation among E'zhou's three districts.
Figure 5 .
Figure 5. Relationship and net payments of eco-compensation among E'zhou's three districts.
Figure 8 .
Figure 8. Physical quantity correlations between various value surfaces with the same corresponding coordinates in space.(a) PM2.5 and gas regulation.(b) PM10 and gas regulation.(c) VOC and gas regulation.(d) Humidity and climate regulation.
Figure 8 .
Figure 8. Physical quantity correlations between various value surfaces with the same corresponding coordinates in space.(a) PM 2.5 and gas regulation.(b) PM 10 and gas regulation.(c) VOC and gas regulation.(d) Humidity and climate regulation.
Table 2 .
Adjustment coefficient of each value surface in the three districts.
CNY/km 2 ) Adjustment Coefficients b and c
Liangzi Lake District pays E'cheng and Huarong 107.22 million and 128.30 million CNY, respectively; and Huarong District pays E'cheng and Liangzi Lake 132.62 million and 197.95 million CNY, respectively. The final net payment is that the Liangzi Lake District gains 44.50 million from E'cheng and 69.90 million from Huarong, totaling 114.40 million CNY. The mutual payments among the three districts are shown in Figure
Table 3 .
Eco-compensation amounts between the three districts (unit: million CNY).
Table 3 .
Eco-compensation amounts between the three districts (unit: million CNY).
Note: L, H, and E stand for Liangzi Lake, Huarong, and E'cheng districts, respectively.
Table 4 .
Comparison of the previous and new eco-compensation methods.
million CNY, Huarong District should pay 69.90 million CNY, and E'cheng District should pay 44.50 million CNY.
Table A2 .
Contents of ecosystem service functions.
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Domain: Agricultural And Food Sciences
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Evaluation of How Nursery Pig Performance is Affected by Evaluation of How Nursery Pig Performance is Affected by Fermented Corn Protein as a Replacement to Enzymatically Fermented Corn Protein as a Replacement to Enzymatically Treated Soybean Meal Along With High or Low Branch Chain Treated Soybean Meal Along With High or Low Branch Chain Amino Acid to Leucine Ratios Amino Acid to Leucine Ratios
Summary Two experiments were conducted to determine if fermented corn protein can serve as a replacement to enzymatically treated soybean meal and what the effects may be with high or low branch chain amino acids (BCAA):Leu ratios on nursery pig performance. In Exp. 1, a total of 350 barrows (200 × 400, DNA; initially 13.2 lb) were randomly allotted to 1 of 5 treatments with 5 pigs per pen and 14 replications per treatment. Dietary treatments were arranged in a 2 × 2 + 1 factorial with a control diet or diets with 5 or 10% fermented corn protein or enzymatically treated soybean meal. Pigs were fed phase 1 diets for 10 d followed by phase 2 diets for 21 d. There were no interactions observed throughout the experiment. Overall (d 0 to 31), pigs fed increasing levels of fermented corn protein had decreased (linear, P ≤ 0.026) BW, ADG, and ADFI with no differences in F/G, whereas increasing enzymatically treated soybean meal had no effect on growth performance. Pigs fed enzymatically treated soybean meal had improved ( P ≤ 0.034) BW, ADG, and F/G compared to pigs fed fermented corn protein diets, with no effect on ADFI. In Exp. 2, a total of 350 pigs (241 × 600, DNA; initially 26.7 lb) were used to determine the effects of fermented corn protein with high or low BCAA:Leu ratio on nursery pig growth performance. At weaning, pigs were randomly assigned to pens
Summary
Two experiments were conducted to determine if fermented corn protein can serve as a replacement to enzymatically treated soybean meal and what the effects may be with high or low branch chain amino acids (BCAA):Leu ratios on nursery pig performance. In Exp. 1, a total of 350 barrows (200 × 400, DNA; initially 13.2 lb) were randomly allotted to 1 of 5 treatments with 5 pigs per pen and 14 replications per treatment. Dietary treatments were arranged in a 2 × 2 + 1 factorial with a control diet or diets with 5 or 10% fermented corn protein or enzymatically treated soybean meal. Pigs were fed phase 1 diets for 10 d followed by phase 2 diets for 21 d. There were no interactions observed throughout the experiment. Overall (d 0 to 31), pigs fed increasing levels of fermented corn protein had decreased (linear, P ≤ 0.026) BW, ADG, and ADFI with no differences in F/G, whereas increasing enzymatically treated soybean meal had no effect on growth performance. Pigs fed enzymatically treated soybean meal had improved (P ≤ 0.034) BW, ADG, and F/G compared to pigs fed fermented corn protein diets, with no effect on ADFI.
In Exp. 2, a total of 350 pigs (241 × 600, DNA; initially 26.7 lb) were used to determine the effects of fermented corn protein with high or low BCAA:Leu ratio on nursery pig growth performance. At weaning, pigs were randomly assigned to pens (5 pigs per pen). On d 24 after weaning (d 0 of the trial), pens of pigs were weighed and then allotted to treatment. Pigs were assigned to 1 of 5 dietary treatments with 14 replications per treatment. Dietary treatments were arranged in a 2 × 2 + 1 factorial. Diets consisted of 10 or 20% fermented corn protein either with high or low BCAA:Leu in addition to a control diet. There was no interaction observed between fermented corn protein concentration and BCAA:Leu. Overall (d 0 to 21), BW, ADG, ADFI, and F/G worsened (linear, P < 0.001) as fermented corn protein increased in the diet. High BCAA:Leu improved (P = 0.023) F/G compared to low BCAA:Leu with no effect on BW, ADG, and ADFI. In summary, using fermented corn protein to replace enzymat-
Introduction
Removing fibrous components of corn before fermentation provides a high crude protein dried distillers grains with solubles value (40% crude protein). When various components of the fermentation process are added back to high protein dried distillers grains with solubles, it results in a fermented corn protein product with up to 50% crude protein and 2% Lys. Because of its high Lys content, fermented corn protein has the potential to become an excellent replacement for specialty soy protein products, such as enzymatically treated or fermented soybean meal in nursery pig diets.
Corn-based ingredients, such as fermented corn protein, contain relatively high amounts of the branch chain amino acid Leu, which increases the dietary requirement of the other branch chain amino acids Ile and Val. 2 Taking this into account and balancing for the branch chain amino acids appears to improve growth performance of finishing pigs fed diets containing excess Leu. 3 Based on these findings, we believe that growth performance may also be improved in nursery pigs fed diets containing excess Leu (typically corn-byproduct-based diets) by increasing levels of Ile and Val.
Therefore, the objective of these studies was to evaluate fermented corn protein as a replacement for enzymatically treated soybean meal in phase 1 and 2 starter diets, and increasing fermented corn protein concentrations in phase 3 starter diets with or without the inclusion of high levels of Ile and Val.
Materials and Methods
The Kansas State University Institutional Animal Care and Use Committee approved the protocols used in both experiments. Exp. 1 was conducted at the Kansas State University Segregated Early Weaning facility in Manhattan, KS. Exp. 2 was conducted at the Kansas State University Swine Teaching and Research Center. In both experiments, each pen was equipped with a 4-hole, dry self-feeder and a nipple waterer to provide ad libitum access to feed and water.
Animals and diets
In Exp. 1, 350 barrows (200 × 400, DNA; initially 13.2 lb) were used in a 31-d phase 1 and 2 trial. Pigs were weaned at approximately 21-d of age and placed in pens of 5 pigs each based on initial weight. At weaning pigs were randomly allotted to 1 of 5 dietary treatments with 14 replications per treatment. Dietary treatments were arranged in a 2 × 2 + 1 factorial with main effects of fermented corn protein (5 or 10%) or enzymatically treated soybean meal (5 or 10%). A control diet consisted of a standard corn-soybean meal diet with no fermented corn protein or enzymatically treated soybean meal.
The concentrations of fermented corn protein and enzymatically treated soybean meal in the diet were consistent in phase 1 and 2. Diets (Table 2 and 3) were formulated to contain 1.40% (phase 1) and 1.35% (phase 2) standardized ileal digestible (SID) Lys and met or exceeded nutrient requirements established by the NRC (2012). 4 Treatment diets were fed for 10 d in phase 1 (d 0 to 10) and 21 d in phase 2 (d 10 to 31). The experimental diets were manufactured in pellet form at Provimi North America in Lewisburg, OH. Individual pig weights and feed disappearance were measured on d 10, 17, 24, and 31 to determine ADG, ADFI, and F/G.
In Exp. 2, 350 pigs (241 × 600, DNA; initially 26.7 lb) were used in a 21-d phase 3 trial. Pigs were weaned at approximately 21 d of age and placed in pens of 5 pigs each based on initial weight and gender. On d 24 after weaning (d 0 of the trial), pens of pigs were weighed and then allotted to 1 of 5 dietary treatments with 14 replications per treatment. Dietary treatments were arranged in a 2 × 2 + 1 factorial with main effects of fermented corn protein (10 or 20%) and BCAA:Leu (high or low). The control diet was a standard corn-soybean meal diet with no added fermented corn protein. Diets were manufactured in pellet form at Provimi North American in Lewisburg, OH, with a high or low BCAA:Leu. The 10 and 20% fermented corn protein diets were similar in decreasing amounts of soybean meal, but with or without the addition of the branch chain amino acids Ile and Val. The diets (Table 4) were formulated to contain 1.30% SID Lys and met or exceeded nutrient requirements established by the NRC. 4 Experimental diets were fed for 21 d (d 0 to 21) in phase 3 of the nursery program. Individual pig weights and feed disappearance were measured on d 10 and 21 to determine ADG, ADFI, and F/G.
Representative diet samples were obtained from every fifth bag of manufactured feed. The diet samples were stored at -20°C (-4°F) until they were homogenized, subsampled, and submitted for analysis of crude protein (CP), dry matter (DM), and ether extract (EE) to the University of Missouri Experiment Station Chemical Laboratories (Columbia, MO). A sample of fermented corn protein and enzymatically treated soybean meal were submitted for analysis of amino acid profile, Ca, and P to the University of Missouri Experiment Station Chemical Laboratories (Columbia, MO;
Statistical analysis
Data were analyzed as a randomized complete block design using the RStudio environment (Version 1.3.1093, RStudio, Inc., Boston, MA) using R programming language [Version 4.0.2 (2020-06-22), R Core Team, R Foundation for Statistical Computing, Vienna, Austria] with body weight serving as the blocking factor and pen as the experimental unit. Block was included in the model as a random effect. Linear and quadratic main effects of increasing levels of enzymatically treated soybean meal or fermented corn protein were tested, as well as any interactions. Differences between treatments were considered significant at P ≤ 0.05 and marginally significant at 0.05 < P ≤ 0.10.
Results and Discussion
The analyzed DM, CP, and EE (Table 2, 3, and 4) were reasonably consistent compared to formulated values between treatments. For both experiments, the analyzed CP percentage was slightly less than formulated values. As expected, the analyzed fermented corn protein (Table 1) was high in CP and the BCAA:Leu.
Fermented corn protein was found to contain 51 ppb aflatoxin and 16.7 ppm of total fumonisin. All other mycotoxins were below practical quantitation limit.
In Exp. 1 (Table 5), there were no interactions observed between protein source and inclusion level throughout the duration of the experiment.
From d 0 to 10 (phase 1), pigs fed fermented corn protein tended to have decreased (P = 0.084) BW compared to pigs fed diets containing enzymatically treated soybean meal. All other growth performance criteria were not significantly different between treatments in phase 1.
From d 10 to 31 (phase 2), pigs fed fermented corn protein had decreased (P ≤ 0.045) BW and ADG compared to pigs fed enzymatically treated soybean meal. Pigs that were fed increasing levels of fermented corn protein had decreased (linear, P ≤ 0.011) BW, ADG, and ADFI with no difference in F/G. However, pigs that were fed fermented corn protein regardless of inclusion percentage tended to have decreased (quadratic, 0.051 ≤ P ≤ 0.079) BW and ADFI compared to pigs fed the control diet. Pigs fed increasing levels of enzymatically treated soybean meal tended to have decreased (linear, P = 0.068) ADFI.
Overall (d 0 to 31), pigs fed enzymatically treated soybean meal had improved (P ≤ 0.034) BW, ADG, and F/G compared to pigs fed fermented corn protein, with no difference in ADFI. Pigs fed increasing levels of fermented corn protein had decreased (linear, P ≤ 0.026) BW, ADG, and ADFI, with no difference in F/G. However, pigs that were fed fermented corn protein regardless of inclusion percentage tended to have decreased (quadratic, 0.051 ≤ P ≤ 0.090) BW and ADFI.
In Exp. 2 (Table 6), there were no BCAA × fermented corn protein interactions observed throughout the duration of the experiment.
In the first weigh period and overall (d 0 to 21), pigs that were fed fermented corn protein diets with high BCAA:Leu had improved (P = 0.034) F/G compared to pigs fed fermented corn protein diets with low BCAA:Leu.
In both weight periods and overall, pigs fed diets containing increasing levels of fermented corn protein had worsened (linear, P ≤ 0.020) BW, ADG, ADFI, and F/G. fermented corn protein diminishes growth performance in the diets of nursery pigs and increasing BCAAs can only improve feed efficiency.
Brand names appearing in this publication are for product identification purposes only. No endorsement is intended, nor is criticism implied of similar products not mentioned.
Persons using such products assume responsibility for their use in accordance with current label directions of the manufacturer. A total of 324 pigs (initial BW of 26.7 ± 3.41 lb) were weaned at approximately 21 d of age and placed in pens of 5 pigs each based on initial weight and gender. On d 24 after weaning (d 0 of the trial), pens of pigs were weighed and then allotted to 1 of 5 dietary treatments with 14 replications per treatment. Dietary treatments were arranged in a 2 × 2 + 1 factorial with main effects of fermented corn protein (10 or 20%) and BCAA:Leu (high or low). 2 Branch chain amino acids. 3 Fermented corn protein was included at 0, 10, or 20% of the diet. 4 The BCAA and fermented corn protein columns compare the low and high BCAA:Leu formulation and the 10/20% inclusion of fermented corn protein and do not include the control treatment. The Linear and Quad columns include the control (0%), 10, and 20% fermented corn protein averaged across low/high BCAA:Leu. There were no significant BCAA × fermented corn protein interactions observed (P > 0.05).
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Domain: Agricultural And Food Sciences
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Hypoglycaemic effect of Bawang Dayak extracts ( Eleutherine palmifolia (L.) Merr.) on Sprague Dawley rats
. The Dayak tribe in Kalimantan has long used bawang dayak as a traditional cure for various degenerative diseases. Previous research showed that bawang dayak bulb has an active compound that can inhibit the enzyme alpha-glucosidase, known as alpha-glucosidase inhibitor (AGI). Compounds that have such ability has a potential in controlling blood glucose level in diabetes mellitus. This research aims to study the effective dosage of aqueous extract and ethanolic extract of bawang dayak bulb as an AGI through an oral glucose tolerance test in male Sprague Dawley rats. Experimental rats were divided into 14 groups, 7 for the ethanolic extract test and 7 for the aqueous extract test. The extracts were applied in 5 dosage levels in each test, with acarbose as a drug control and distilled water as a positive control. Data were plotted to determine the area under the curve (AUC). The effective dosage was the lowest dosage that gave a significantly smaller AUC value than the AUC value of the positive control group. The effective dosage for bawang dayak aqueous extract and bawang dayak ethanolic extract was 200 mg/kg and 100 mg/kg, respectively.
Introduction
Diabetes mellitus (DM) is a degenerative disease that affects many of the world's population. In 2015 the number of people with diabetes globally was 422 million and was estimated to reach 642 million people in 2040. Prevalence is rising higher in low and middle-income countries. In 2015 the percentage of adults with diabetes was 8.5%, which means 1 in 11 adults live with diabetes. Diabetes became one of the largest health expenditures in the world in 2013, amounting to 612 billion dollars or 11% of total health spending. Diabetes is one of the global health emergencies in the 21st century. There are 318 million adults who have impaired glucose tolerance and are at high risk of developing diabetes [1]. Persons with impaired glucose tolerance (IGT) -15.6% of the U. S. population -are at high risk for developing diabetes. In addition, IGT is an important risk factor for a number of other adverse health conditions and mortality. IGT is defined on the basis of an abnormal oral glucose tolerance test (OGTT). Persons without diabetes but with an OGTT 2-hour value of 140-199 mg/dl are considered to have IGT [2]. The person who develops pre-diabetes will become diabetes in several months or years, if he/she goes untreated appropriately and adequately.
One mechanism that can be used to prevent an increase in blood glucose levels is through inhibition of glucose absorption in the intestine. This mechanism involves a substance that can inhibit the action of enzymes that break down starch into glucose, known as alpha-glucosidase inhibitors (AGI). AGI works in the intestinal tract to prevent disaccharides from breaking down into glucose, thereby decreasing glucose absorption. Many studies have been carried out on various medicinal plants in vitro to determine the potential of these plants as AGI agents. Bawang Dayak (Eleutherine palmifolia (L.) Merr.) is an indigenous plant of Kalimantan Island, Indonesia. Dayak people have long used this plant as a traditional medicine for several diseases. It is known by various other names such as bawang tiwai, bawang hantu, bawang sabrang, babawangan beureum, bawang siyem, bawang sayup, bawang kapal and bawang lubak. Bawang dayak plants have good adaptations and can grow in various climates and soil types. In addition, this plant can also be reproduced and harvested in a short time so that it is easily developed for industrial scale [3]. Bawang dayak aqueous and ethanolic extracts have antioxidant and alpha-glucosidase inhibitor activities that have been proven in vitro [4]. The methanolic extract of Eleutherine americana bulb contains eleutherinoside A, a naphthalene derivative, which has strong AGI activity with IC50 0.5 mM [5]. The existence of eleutherinoside A in Eleutherine palmifolia ethanolic extract also has been confirmed [6].
This research aims to verify the AGI activity of bawang dayak extracts work in vivo and determine the effective dosage of bawang dayak aqueous extract and bawang dayak ethanolic extract to decrease intestinal glucose uptake Oral Glucose Tolerance Test (OGTT) in male Sprague Dawley rats. This study will give pre-clinical proof and reveal the potential of bawang dayak extracts as a local resource for developing the phytopharmaceutical products in controlling and preventing hyperglycaemia in people with Impaired Glucose Tolerance (IGT).
Plant material and extraction process
Bawang dayak bulbs (Eleutherine palmifolia (L.) Merr.) were collected from Air Hitam Village, Samarinda City, East Kalimantan. The bulbs were identified and authenticated by Dr Joeni Setijo Rahajoe from Herbarium Bogoriense, Indonesian Institute of Sciences. Bawang dayak extraction was carried out by maceration using water and ethanol solvents according to the procedure explained by Febrinda et al. [4]. Fresh bawang dayak bulbs were added with water (or ethanol) with a ratio of 1:4 (b:v) and crushed using a blender. The solutions then were soaked for thirty minutes in an ultra-sonic bath and followed by incubation in a shaker incubator at room temperature for two hours. Then the solutions were centrifugated, and the dissolved phase was collected to be filtered using Whatman filter paper No. 1. The extract solutions obtained were frozen and dried using a freeze dryer for 48 hours, followed by pounding the extracts to become a dry powder named bawang dayak aqueous extract (BD aqueous extract) and bawang dayak ethanolic extract (BD ethanolic extract).
Experimental animal and oral glucose tolerance test
This research was conducted under the Guide for The Care and Use of Laboratory Animals [7]. 70 male Sprague Dawley rats aged around eight weeks weighing 180 to 200 g were obtained from the Food and Drug Supervisory Agency, Jakarta. The experimental animals were maintained under standard laboratory conditions (26 °C, 12 hours of light/ dark cycles) and fed and watered ad libitum. The animals were divided into 14 groups: 7 groups for BD aqueous extract test and the other seven groups for BD ethanolic extract test. The animals fasted for 10 hours, from 10:00 p.m. to 8:00 a.m. The following day, the fasting blood glucose levels of the experimental animals were measured immediately using a glucometer (Accu-Chek Active, Roche, Germany). The animals were grouped and given the following treatment: (1) positive control group (PC) treated with distilled water; (2) drug control group (DC) treated with 5 mg/kg BW of acarbose solution; (3) treatment group (A1/E1) treated with BD aqueous extract or BD ethanolic extract at a dose of 100 mg/kg BW; (4) treatment group (A2/E2) treated with BD aqueous extract or BD ethanolic extract at a dose of 200 mg/kg BW; (5) treatment group (A3/E3) treated with BD aqueous extract or BD ethanolic extract at a dose of 300 mg/kg BW; (6) treatment group (A4/E4) treated with BD aqueous extract or BD ethanolic extract at a dose of 400 mg/kg BW; and (7) treatment group (A5/E5) treated with BD aqueous extract or BD ethanolic extract at a dose of 500 mg/kg BW. Thirty minutes after the administration of treatment solution, the animals received sucrose solution with a concentration of 25% at a dose of 2 g/kg BW by oral. The solution was administered through gastric gavage. Blood glucose levels were collected and measured on the 30 th , 60 th , 90 th , and 120 th minutes after the sucrose administration. The data obtained were plotted to form a curve, and the area under the curve (AUC) was calculated for each experimental group.
Statistical analysis
The AUC values of all experimental groups were analyzed using Analysis of variance (Anova). If the Anova result showed significance, further statistical post hoc test would be carried out using DMRT. Data were displayed as Mean ± SD.
OGTT result of BD aqueous extract
The curves of OGTT result on BD aqueous extract showed that the acarbose and all treatment groups had lower curves than the positive control (Fig. 1). The area measurement under the curve showed that the entire treatment group had a smaller AUC than the positive control (Fig. 2). However, the dose groups with a significantly smaller AUC than the positive control were 200, 300 and 500 mg/kg BW. These groups had AUCs, which were not significantly different from the acarbose group. Based on DMRT post hoc test at α 0.01, the lowest dose that gave significantly lower AUC than the positive control was 200 mg/kg BW (Fig. 2).
OGTT result of BD ethanolic extract
The curves of OGTT result on BD ethanolic extract showed that the acarbose and all treatment groups had lower curves than the positive control (Fig. 3). The area measurement under the curve showed that the entire treatment group had a smaller AUC than the positive control (Fig. 4). However, the dose groups with a significantly smaller AUC than the positive control were 100, 300 and 500 mg/kg BW. These groups had AUCs, which were not significantly different from the acarbose group. Based on DMRT post hoc test at α 0.01, the lowest dose that gave significantly lower AUC than the positive control was 100 mg/kg BW
Discussion
The ability of bawang dayak extracts in inhibiting alpha glucosidase enzyme in the intestine was compared to acarbose as a well-known diabetes mellitus medicine. Both extracts showed that they had no significantly different ability from acarbose, although in different dose levels. BD ethanolic extract had a more remarkable ability to reduce blood glucose levels shortly after sucrose consumption than BD aqueous extract ( Fig. 1 and Fig. 3). The administration of BD ethanolic extract at a dose of 100 mg/kg BW significantly gave a lower AUC value compared to positive control, while for the aqueous extract a dose of 200 mg/kg BW was needed. This is consistent with in vitro research carried out previously where BD ethanolic extract had significantly lower IC50 of alpha glucosidase inhibition (241 ppm) than the aqueous extract (505 ppm) and not significantly different from acarbose (288 ppm) [6].
A naphthalene derivated compound named Eleutherinoside A in methanolic extract of Eleutherine americana bulb, could act as an alpha-glucosidase inhibitor (IC 50 of 0.5 mM) [5]. This compound, along with two other naphthalene derivates (eleuthoside B, and eleutherol), was also found in bawang dayak bulb from Air Hitam Village, Samarinda (Eleutherine palmifolia (L.) Merr.) that was used in this research. The presence of those compounds was shown by an NMR analysis on Eleutherine palmifolia ethanolic extract [4]. A result of phytochemical screening analysis on Eleutherine palmifolia extract also showed that phytochemical compounds presence in BD ethanolic extract was more abundant than those found in the aqueous extract. There were strong positive indications of alkaloid and triterpenoid compounds in BD aqueous extract. In contrast, there were strong positive indications for triterpenoids, flavonoids, and phenolic compounds [6]. Those compounds also had AGI activities which were stated by several research reports [8][9][10][11][12].
Due to the higher presence of Eleutheinoside A and phytochemical compounds in BD ethanolic extract than in the aqueous extract, the ethanolic extract had a higher ability than the aqueous extract in inhibiting alfa glucosidase enzyme activity. Those resulted in a greater decrease of glucose absorption in the intestinal tract of the experimental animal. This result was consistent with the OGTT experiment result of another Kalimantan indigenous plant, pasak bumi root (E. longifolia), which showed that the methanolic extract had a higher hypoglycaemic effect than the water infusion due to its phytochemical contents [13].
Synthetic AGI, such as acarbose, has long been used to manage type 2 diabetes mellitus. In addition to slowing down the absorption of glucose by the intestine, various diabetes drugs with the mechanism of action of AGI are reported to have side effects in the form of gastrointestinal discomfort [14,15]. Although it has a significant effect on glycemic control and insulin levels, synthetic AGI such as acarbose does not significantly affect blood lipids. On the contrary, bawang dayak extract significantly improved blood lipid profile and antioxidant status in Sprague Dawley alloxan-induced diabetic rats. Those experimental results on bawang dayak revealed the potential of this Kalimantan indigenous plant to be a local resource for developing phytopharmaceutical products for treating diabetes mellitus and preventing its cardiovascular complication.
Conclusion
The AGI activity of bawang dayak extracts was effective in vivo in reducing glucose uptake in the intestine of Sprague Dawley male rats. The effective dose of BD aqueous extract and ethanolic extract to inhibit the action of the alpha-glucosidase enzyme determined through OGTT in male Sprague Dawley rats were 200 and 100 mg/kg BW respectively. The combination of antioxidant capacity and the ability to inhibit the activity of alpha glucosidase enzyme in bawang dayak extracts showed that this plant had great potential as a source of the phytopharmaceutical product in controlling and preventing hyperglycaemia. Therefore, it is necessary to further assess the acute and chronic toxicity of bawang dayak extract to determine its safety for long-term usage.
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Domain: Agricultural And Food Sciences
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Effects of essential mineral elements deficiency and supplementation on serum mineral elements concentration and biochemical parameters in grazing Mongolian sheep
Traditional sheep grazing is the pillar industry and the main source of income for local herders in the Inner Mongolia Autonomous Region of China. However, grazing sheep often suffer from mineral deficiency. In the present study, the feeding experiment was performed on 84 grazing Wu Ranke sheep. After being divided into calcium (Ca), zinc (Zn), copper (Cu), cobalt (Co), manganese (Mn), and selenium (Se) treatment groups, they were fed with a mineral deficient diet for 60 days and then a mineral supplement diet for 41 days. Serum samples were collected three times, 10 concentrations of essential mineral elements and 15 concentrations/activity of biochemical parameters were measured to assess the effects of mineral deficiency and supplementation on the physical health of sheep. The results revealed that the sheep showed mineral Ca, Cu, Co, Mn, and Se deficiencies after feeding their respective mineral deficient diet. Deficiency in dietary Ca, Zn, Cu, Co, Mn, and Se may adversely affect the liver, myocardium and pancreas of sheep. The prompt supplementation of dietary Zn, Cu, Co, Mn, and Se may alleviate the damage caused to the liver, myocardium and pancreas, while that of dietary Ca improved energy generation. In conclusion, the adequate supplementation of dietary Ca, Zn, Cu, Co, Mn, and Se is essential for avoiding the impairment caused to the liver, myocardium and pancreas function of sheep by the deficiency in essential dietary minerals.
Introduction
Sheep and goats are one of the most important livestock providing meat, milk, fur and essential nutrients for humans, including protein, vitamins, fatty acids and minerals (1,2). Located along the northern border of China, the Inner Mongolia Autonomous Region is the most significant origin of mutton for the country. With more than three-quarters of this region covered by flat natural grassland, traditional ruminant grazing husbandry are the pillar industry and the major source of income for local herdsmen. Thus, the intake of various nutrients by livestock is closely related to the types and amounts of nutrients provided by the grassland in OPEN ACCESS EDITED BY Fazul Nabi, Lasbela University of Agriculture, Water and Marine Sciences, Pakistan the pasture. However, some research has revealed that pasture is incapable to provide all the nutrients needed for the normal growth and metabolic processes of livestock, especially minerals (3,4). Various mineral elements are required for the metabolism of livestock through various physiological and biochemical processes. Thus, mineral deficiency often occurs to the livestock if no sufficient mineral elements are provided (5,6).
In general, the essential mineral nutrients needed by livestock are categorized into macro-elements and micro-elements, with macroelements including calcium (Ca), phosphorus (P), sodium (Na), sulfur (S), potassium (K), magnesium (Mg), and micro-elements including cobalt (Co), copper (Cu), iodine (I), iron (Fe), zinc (Zn), manganese (Mn), and selenium (Se) (7). The appropriate amounts of these essential mineral elements play a key role in maintaining various biochemical processes for livestock (8). If the sufficient provision of essential mineral nutrients cannot be ensured, the livestock will suffer mineral deficiency (5,6). Ca is one of the most abundant mineral elements found in livestock, the deficiency of which during the critical growth period often reduces growth rate and hinders skeletal development (9). Sheep and goats often suffer from osteoporosis when Ca is deficient in diets (10). Zn, as the critical component of more than 300 types of metalloenzymes, participates in cellular communication, cellular proliferation and cellular differentiation, playing an important role in the antioxidant system (11). The deficiency of dietary Zn often results in the loss of appetite, metabolic disorders, and the reduction of hemoglobin concentrations (12). Cu is widely found in various enzymes and cofactors, especially in the liver (13,14). In some research, it is revealed that copper deficiency causes reproductive disorders and alters the immune response of ruminants (15). A persistently low concentration of Cu in the serum of sheep can lead to an increase in the risk of mortality (16). The Co deficiency in ruminants suppresses the synthesis of vitamin B 12 in the rumen, thus reducing the diversity of rumen microbes (17). Severe Co deficiency leads to liver fat metabolism disorders and muscle lesions in sheep and goats (18,19). Mn plays a vital role in antioxidants, immunity, and the growth and reproduction of animals (20). The deficiency of Mn in animals causes disruption to bone-regulating hormones and reduces bone metabolic indexes in serum (21). Early studies have shown that feeding Mn deficiency diets to ruminants reduced conception rates (22). The adequate provision of Se, which is an important component of selenoprotein, is essential for bone metabolism, immunity and endocrine (5). The ruminants with Se deficiency are prone to white muscle disease and immunosuppression, especially for junior ruminants (23).
There are many studies revealing that the grazing sheep farmed on the grassland in many parts of China and other countries around the world are often deficient in various mineral elements including Ca, Zn, Cu, Co, Mn, Se (24)(25)(26). Similarly, some studies have shown that soils, pastures and grazing sheep in the Inner Mongolia Autonomous Region are also deficient in Ca, Zn, Cu, Co, Mn, and Se (27)(28)(29)(30). Up to now, it remains unclear how the lack of dietary minerals is reflected in the serum and affects the health of grazing Mongolian sheep. Totalreflection X-Ray Fluorescence (TXRF) is an analytical technique that is applicable to detect various elements simultaneously at trace level (31). Currently, TXRF technique has been widely used in bioscience due to its fastness, precision and accuracy. Mineral nutrient deficiency can be accurately diagnosed through serum tests, while biochemical parameters in serum can effectively assess the tissue damage, which reflects the health status of animals (32). Ca, Zn, Cu, Co, Mn, and Se are susceptible to deficiency in grazing sheep, due to insufficient mineral nutrients from pasture under the natural grassland grazing ecosystem. Therefore, an approval was granted for the feeding experiments on a total of 84 grazing Wu Ranke sheep divided into 6 treatment groups fed with Ca, Zn, Cu, Co, Mn, and Se deficient multinutrient salt diet, respectively, for 60 consecutive days and then supplemented multi-nutrient salt diet, respectively, for 41 consecutive days. The essential mineral elements and biochemical parameters in the serum of 84 grazing Mongolian sheep were detected to explore the impact of respective diets on animal health. Aiming to provide guidance for the rational mineral supplementation of grazing sheep.
Experimental design
All the procedures of animal experiments were approved and conducted in strict accordance with the requirements set out by the Inner Mongolia University Animal Care and Use Committee (IMU-2020-sheep-040). A total of 84 4-month-old female grazing Wu Ranke sheep were purchased from Abaga Banner, Xilin Gol League, Inner Mongolia Autonomous Region, China. All of the sheep were housed and fed individually with native grasses as roughage, crushed oats as concentrate, and multi-nutrient salts as recommended by the National Research Council (NRC) (33).
During the 28-day pre-feeding period, all the Mongolian Wu Ranke sheep were fed with crushed oats and native grasses. Afterward, these 84 Mongolian Wu Ranke sheep were equally divided into Ca (LCa), Zn (LZn), Cu (LCu), Co (LCo), Mn (LMn), and Se (LSe) deficient groups on a random basis and fed with Ca, Zn, Cu, Co, Mn, and Se deficient multi-nutrient salt diet, respectively, for 60 consecutive days. Then, 7 sheep were randomly selected out of each group to continue feeding on Ca, Zn, Cu, Co, Mn, and Se supplemented multinutrient salt diet, respectively, for 41 consecutive days, with them denoted as Ca (SCa), Zn (SZn), Cu (SCu), Co (SCo), Mn (SMn), and Se (SSe) supplemented group ( Figure 1). The formulation of the multinutrient salts for each group is detailed in Tables 1, 2.
Sample collection
The blood samples of each Mongolian Wu Ranke sheep were collected on day 28 (the end of the pre-feeding period, n = 14 for each group), on day 88 (the end of the feeding deficient multi-nutrient salts period, n = 14 for each group), and on day 129 (the end of the feeding supplement multi-nutrient salts period, n = 7 for each group) of the feeding period, respectively. At 8:00 a.m., Jugular vein blood was collected from the Mongolian Wu Ranke sheep using serum separator vacuum tubes following 12 h fast. Then, the blood was centrifuged at 3,000 rpm for 10 min to obtain serum samples and stored in microtubes at −20°C for later laboratory analysis.
Detection of essential mineral elements in serum 2.3.1. Digestion of serum samples by microwave
The serum samples were digested by a microwave digester (REVO, Labtech, Beijing, China). 300 uL of each serum sample was added to 6 mL 65% HNO 3 , and then digested in strict accordance with procedures shown in Supplementary Table S1. Each of the digested samples was filled to 10 mL by ddH 2 O as the sample to be measured (34).
Measurement of the serum essential mineral elements
Firstly, 200 uL of the digested sample was mixed with 2 uL of gallium (Ga) solution (1,000 mg/L) and 20 uL of polyvinyl alcohol solution (0.3 g/L) to obtain the mixed sample. After thorough homogenization, 10 uL of the mixed sample was transferred to a number of quartz glass sample carriers and dried in the oven at 50°C (35). The concentration of 10 essential mineral elements including P, S, K, Ca, Mn, Fe, Co, Cu, Zn, and Se was measured by the TXRF spectrometer (S4 T-STAR, Bruker Nano GmbH, Berlin, Germany) fitted with a molybdenum (Mo) X-ray tube. A voltage of 50 kV and a current of 1,000 uA were applied to excite the serum sample. The measurement lasted 300 s for each sample (36).
Each concentration of the digested standard solution was measured by the TXRF spectrometer, with the measurement result as the concentration of the respective element standard solution. Both the actual and measured concentrations of the standard solution were fitted to the standard curve of each element. All the results of serum element measurement were calibrated with the standard curve.
Measurement of serum biochemical parameters
The automatic biochemical analyzer (BS-240VET, Mindray, Beijing, China) was used to measure the 8 serum biochemical
Statistical analysis
The normality of data distribution was checked by the Shapiro-Wilk test (38). T-test was performed to determine the significant difference between the pre-feeding period, the feeding deficient multi-nutrient salts period, and the feeding supplement multinutrient salts period of the measured serum essential mineral elements and biochemical parameters. The Paired sample t-test was carried out using GraphPad Prism (v.9.3.1). The test results were expressed as mean ± standard error (SE), and the differences of p < 0.05 was considered as significant. The results were visualized by R (v.4.1.2). Vector drawing was performed using Adobe Illustrator 2020. Ca deficiency treatment made no difference to the concentration of serum S, K, Fe, and Mn compared with the untreated. In addition, the concentration of S, Fe, and Mn showed an increasing trend while that of K exhibited a decreasing trend. Ca deficiency treatment led to a significant increase in the concentration of P (59.17 ± 4.21 mg/L vs. 51.71 ± 2.27 mg/L, p < 0.05), Zn (1.31 ± 0.077 mg/L vs. 0.81 ± 0.060 mg/L, p < 0.05), Cu (0.77 ± 0.033 mg/L vs. 0.59 ± 0.037 mg/L, p < 0.05), and Se (0.087 ± 0.0035 mg/L vs. 0.018 ± 0.0019 mg/L, p < 0.05) when compared with the untreated.
Ca supplement treatment had no impact on the serum concentration of K, P, Fe, Zn, Cu, and Mn in comparison with the Ca deficiency treatment. In addition, the concentration of P, Fe, and Zn exhibited an increasing trend while that of K, Cu, and Mn displayed a decreasing trend. Ca supplement treatment caused a significant increase in the concentration of S (617.27 ± 12.76 mg/L vs. 502.22 ± 15.07 mg/L, p < 0.05) and Se (0.096 ± 0.0082 mg/L vs. 0.082 ± 0.0055 mg/L, p < 0.05) when compared with Ca deficiency treatment. Figure 3 shows the concentration of measured serum essential mineral elements in Zn treatment group. Both Zn deficiency treatment and Zn supplement treatment made no difference to the concentration of serum Zn.
Concentration of serum essential mineral elements in Zn treatment group
After Zn deficiency treatment, the concentration of serum Cu (0.73 ± 0.033 mg/L vs. 0.52 ± 0.042 mg/L, p < 0.05) and Se (0.083 ± 0.0043 mg/L vs. 0.026 ± 0.0048 mg/L, p < 0.05) was significantly improved when compared with the untreated, while that of serum S, K, P, Ca, Fe, and Mn showed an increasing trend.
In comparison with the Zn deficiency treatment, Zn supplement treatment had no effect on the concentration of serum S, K, Ca, Fe, Mn, and Se. The concentration of serum S, K and Fe showed an increasing trend while that of Ca, Mn and Se exhibited a decreasing trend. Zn supplement treatment significantly increased the Figure 4 shows the concentration of measured serum essential mineral elements in Cu treatment group. Cu deficiency treatment contributed to a sharp decline in serum Cu concentration (0.46 ± 0.046 mg/L vs. 0.61 ± 0.034 mg/L, p < 0.05). Followed by the Cu supplementation treatment, serum Cu concentration showed a significant increase in serum (0.61 ± 0.046 mg/L vs. 0.52 ± 0.062 mg/L, p < 0.05).
Concentration of serum essential mineral elements in Cu treatment group
Compared with the untreated, there were no significant differences observed in the concentration of serum S, P, Ca, Fe, Zn, and Mn after the Cu deficiency treatment. Specifically, the concentration of Fe, Zn, and Mn showed an increasing trend but that of the S, P, and Ca showed a decreasing trend. After Cu deficiency treatment, Se concentration (0.091 ± 0.0043 mg/L vs. 0.013 ± 0.0013 mg/L, p < 0.05) increased significantly but K concentration (132.65 ± 9.49 mg/L vs. 166.80 ± 10.25 mg/L, p < 0.05) was reduced sharply compared to the untreated period.
Following the Cu supplement treatment, the concentration of serum K, Ca, Zn, and Se showed no significant difference. Except for Zn that exhibited an increasing trend, all the other measured elements showed a decreasing trend. Compared with the Cu deficiency treatment, the concentration of S (674.50 ± 17.99 mg/L vs. 513.77 ± 34.059 mg/L, p < 0.05), P (58.48 ± 6.32 mg/L vs. 38.05 ± 3.16 mg/L, p < 0.05), Fe (5.95 ± 1.034 mg/L vs. 2.16 ± 0.24 mg/L, p < 0.05), and Mn (0.078 ± 0.016 mg/L vs. 0.053 ± 0.021 mg/L, p < 0.05) increased significantly after dietary Cu supplementation. Figure 5 shows the concentration of measured serum essential mineral elements in Co treatment group. Co was not detected in the Mongolian Wu Ranke sheep studied regardless of the treatment, which may be due to the serum Co concentration falling below the lower limit of detection.
Concentration of serum essential mineral elements in Co treatment group
Despite no significant increase in the concentration of serum S, K, P, Ca, and Mn after Co deficiency treatment, they all showed an increasing trend. The concentration of Fe (4.038 ± 0.39 mg/L vs. 1.44 ± 0.20 mg/L, p < 0.05), Zn (0.94 ± 0.10 mg/L vs. 0.60 ± 0.068 mg/L, p < 0.05), Cu (0.72 ± 0.040 mg/L vs. 0.58 ± 0.025 mg/L, p < 0.05), and Se (0.090 ± 0.0029 mg/L vs. 0.0095 ± 0.0011 mg/L, p < 0.05) increased significantly after Co deficiency treatment when compared with the untreated. The concentration of measured serum essential mineral elements in Ca treatment group. The paired samples t-test was performed to determine the significant difference between untreated (n = 14) and deficient treatment (n = 14), between deficient treatment (n = 7) and supplement treatment (n = 7). The differences of p < 0.05 were considered as significant. The solid point in the figure represents p < 0.05 and the hollow point represents p > 0.05. The lines on either side of the point represent the standard error for the data.
Frontiers in Veterinary Science 06 frontiersin.org After Co supplement treatment, there was no effect observed on the concentration of S, K, Ca, Fe, Zn, Cu, and Mn. To be specific, the concentration of S, Fe, Zn, and Mn exhibited an increasing trend but that of K, Ca, and Cu showed a decreasing trend. Following the Co supplement treatment, the concentration of P (64.07 ± 3.63 mg/L vs. 39.04 ± 5.05 mg/L, p < 0.05) increased significantly but that of Se (0.074 ± 0.0040 mg/L vs. 0.088 ± 0.0057 mg/L, p < 0.05) decreased significantly compared with Co deficiency treatment. 0.56 ± 0.019 mg/L, p < 0.05) and Se (0.082 ± 0.0034 mg/L vs. 0.014 ± 0.00086 mg/L, p < 0.05) increased significantly compared with the untreated.
Concentration of serum essential mineral elements in Mn treatment group
After the Mn supplement treatment, the concentration of S exhibited an increasing trend but that of Fe and Se showed a decreasing trend compared with the Mn deficiency treatment. After Mn supplement treatment, the concentration of P (71.099 ± 6.63 mg/L vs. 52.28 ± 2.50 mg/L, p < 0.05) rose sharply but that of K (126. 17 3.1.6. Concentration of serum essential mineral elements in Se treatment group Figure 7 shows the concentration of measured serum essential mineral elements in Se treatment group. Se deficiency treatment resulted in a significant decrease in the concentration of serum Se (0 ± 0 mg/L vs. 0.11 ± 0.010 mg/L, p < 0.05). A sharp rise in the level of serum Se concentration occurred after the Se supplement treatment (0.090 ± 0.0060 mg/L vs. 0 ± 0 mg/L, p < 0.05). The concentration of measured serum essential mineral elements in Zn treatment group. The paired samples t-test was performed to determine the significant difference between untreated (n = 14) and deficient treatment (n = 14), between deficient treatment (n = 7) and supplement treatment (n = 7). The differences of p < 0.05 were considered as significant. The solid point in the figure represents p < 0.05 and the hollow point represents p > 0.05. The lines on either side of the point represent the standard error for the data.
Frontiers in Veterinary Science 07 frontiersin.org Se deficiency treatment had no effect on the concentration of S, K, P, and Ca. In addition, the concentration of K displayed an increasing trend but that of S, P, and Ca exhibited a decreasing trend when compared with the untreated period. Se deficiency treatment caused a significant increase in the concentration of Fe (6.04 ± 1.36 mg/L vs. 1.74 ± 0.20 mg/L, p < 0.05), Zn (1.06 ± 0.080 mg/L vs. 0.55 ± 0.069 mg/L, p < 0.05), Cu (0.81 ± 0.059 mg/L vs. 0.57 ± 0.044 mg/L, p < 0.05), and Mn (0.11 ± 0.026 mg/L vs. 0.022 ± 0.0054 mg/L, p < 0.05).
Measurement of the serum biochemical parameters
3.2.1. Concentration and activity of serum biochemical parameters in Ca treatment group Figure 8 shows the results of serum biochemical parameters concentration and serum biochemical parameters activity in Ca treatment group. After Ca deficiency treatment, there were no significant differences observed in serum TP, TC concentration and γ-GT activity compared with the untreated period. After Ca deficiency treatment, there was a significant increase in the concentration of GLU (3.93 ± 1.05 mmol/L vs. 3.36 ± 0.93 mmol/L, p < 0.05), ALB (26.59 ± 7.11 g/L vs. 25.14 ± 6.72 g/L, p < 0.05) and TBil (7.58 ± 2.19 umol/L vs. 6.08 ± 1.76 umol/L, p < 0.05) and the activity of ALT ( There were no significant differences found after Ca supplement treatment in the concentration of serum ALB, TBil, UREA, TP, TC and CREA and the activity of ALT, AST, LIP, α-AMY, CK, and γ-GT when compared with the Ca deficiency treatment. The concentration of TG (0.25 ± 0.10 mmol/L vs. 0.18 ± 0.066 mmol/L, p < 0.05) and GLU (5.23 ± 1.98 mmol/L vs. 3.62 ± 1.37 mmol/L, p < 0.05) and the activity The concentration of measured serum essential mineral elements in Cu treatment group. The paired samples t-test was performed to determine the significant difference between untreated (n = 14) and deficient treatment (n = 14), between deficient treatment (n = 7) and supplement treatment (n = 7). The differences of p < 0.05 were considered as significant. The solid point in the figure represents p < 0.05 and the hollow point represents p > 0.05. The lines on either side of the point represent the standard error for the data. The concentration of measured serum essential mineral elements in Co treatment group. The paired samples t-test was performed to determine the significant difference between untreated (n = 14) and deficient treatment (n = 14), between deficient treatment (n = 7) and supplement treatment (n = 7). The differences of p < 0.05 were considered as significant. The solid point in the figure represents p < 0.05 and the hollow point represents p > 0.05. The lines on either side of the point represent the standard error for the data. Figure 12 shows the results of serum biochemical parameters concentration and serum biochemical parameters activity in the Mn The concentration of measured serum essential mineral elements in Mn treatment group. The paired samples t-test was performed to determine the significant difference between untreated (n = 14) and deficient treatment (n = 14), between deficient treatment (n = 7) and supplement treatment (n = 7). The differences of p < 0.05 were considered as significant. The solid point in the figure represents p < 0.05 and the hollow point represents p > 0.05. The lines on either side of the point represent the standard error for the data. Figure 13 shows the results of serum biochemical parameters concentration and serum biochemical parameters activity in Se treatment group. Se deficiency treatment had no effect on the concentration of TBil, TG, TC, GLU, and ALB or the activity of γ-GT, LIP. After Se deficiency treatment, the concentration of UREA The concentration of measured serum essential mineral elements in Se treatment group. The paired samples t-test was performed to determine the significant difference between untreated (n = 14) and deficient treatment (n = 14), between deficient treatment (n = 7) and supplement treatment (n = 7). The differences of p < 0.05 were considered as significant. The solid point in the figure represents p < 0.05 and the hollow point represents p > 0.05. The lines on either side of the point represent the standard error for the data.
Discussion
Mineral elements are the essential nutrients needed by ruminants. The appropriate concentration of essential mineral elements enables the normal development of their physiological, catalytic, and regulatory functions (39). Although many researches indicated plasma samples were more suitable for measuring concentrations of mineral Ca, P, S, and Cu, there were many studies using serum samples to detected these mineral elements and established ranges of the standard concentration for sheep (15, [40][41][42][43]. To uniform this study, the serum samples were used to measure both the concentration of the mineral elements and the biochemical parameters. It was found out that the normal serum Ca concentration in junior sheep ranged from 70 mg/L to 80 mg/L (3). In this research, the mean value of the initial concentration of Ca reached 51.61 mg/L, indicating that the Ca deficiency found in Mongolian Wu Ranke sheep resulted from their long-term pattern of grazing in the grassland. Serum Ca usually does not fluctuate with the concentration of Ca in the diet (42). After 60 days of Ca deficiency treatment, there was only an insignificant decrease observed in the concentration of serum Ca. Similarly, there was no significant increase found in the other treatment group's serum Ca concentration after Ca supplement was treated based on the addition of NRC-recommended. Bone tissues, which are intended to maintain Ca homeostasis in the blood and extracellular fluid, play a major role in Ca storage for animals (42). When animals are severely deficient in Ca, the body shows an increase in bone resorption to maintain serum Ca concentration as normal. Eventually, the mineral concentration in bone tissues is reduced to the minimum, which impairs bone mineral deposition (44). Therefore, bone health is worthy of attention for the Mongolian Wu Ranke sheep with low serum Ca concentrations. Although serum Ca concentration does not change immediately with the level of dietary Ca concentration, the concentration of serum Ca in the Ca supplement group still increased significantly from 47.69 mg/L to 61.98 mg/L after 41 days of dietary Ca supplementation. Interestingly, the level of serum Ca concentration was not significantly improved in the other treatment groups during the 101-day rearing period. This may be due to the sheep with Ca deficiency requiring s large-scale Ca supplementation for the change in serum concentrations. The serum P and Ca have a combined effect on bone health for animals (42). There was a metabolic correlation discovered between mineral elements, and the concentration of serum Ca has affected the utilization of serum P. As revealed by the previous research, a diet with high P concentrations increased serum P concentration but decreased serum Ca concentration, suggesting a The results of the serum biochemical parameters concentration and the serum biochemical parameters activity in Ca treatment group. NS p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001.
Frontiers in Veterinary Science 12 frontiersin.org negative correlation (45). Our research also indicated that low Ca diets reduced serum Ca concentration but increased serum P concentration to a significant extent. Notably, there was a significant increase in serum P concentration but a sharp decline in serum Ca concentration after Mn supplement treatment, which is suspected to result from the dietary Mn promoting the absorption of serum P and thus decreasing the level of serum Ca concentration. Therefore, the ratio of dietary P to Mn must be considered to avoid reduced Ca absorption. The concentration of serum P in healthy sheep ranged from 46.5 mg/L to 58.9 mg/L (36). In comparison, the initial serum P concentration of the 84 Mongolian Wu Ranke sheep was 50.77 mg/L, which indicates that the concentration of P derived from the pasture could meet their nutritional needs. Therefore, the supplementation of dietary P is not required for those Mongolian Wu Ranke sheep. As one of the essential mineral elements, Zn plays an important role in various life activities (46). The concentration of serum Zn in healthy sheep ranged from 0.6 mg/L to 1.2 mg/L (36). Comparatively, the mean value of initial serum Zn concentration was 0.65 mg/L in these 84 Mongolian Wu Ranke sheep studied. It is indicated that these Mongolian Wu Ranke sheep were not deficient in Zn. There was no decrease observed in serum Zn concentration after Zn deficiency treatment, which is consistent with the result of some other research (47). This may be attributable to the concentration of Zn in oats and natural pastures meeting the need of sheep for Zn. Similarly, after 41 days of Zn supplementation, there was no significant increase found in serum Zn. Usually, Zn is involved in the generation of metallothionein and gene regulatory proteins (48). The diets with high Zn concentrations can enhance metallothionein production in mucosal cells. When mucosal cells are shed, Zn returns to the gastrointestinal tract, thus inhibiting Zn absorption (49). Moreover, due to the inhibitory mechanism of high Zn, the supplementary dietary Zn was not fully absorbed by the Mongolian Wu Ranke sheep in this research (49). Interestingly, there was a sharp decrease in serum Cu concentrations after 41 days of Zn supplement, which is coherent with the result of many other studies (47,50). This may also result from the high affinity of copper for metallothionein. In the high Zn state, mucosal cells return Cu to the gastrointestinal tract when shed (49, 51). Competing for the binding sites on enzymes, metalloproteins and metal transporter proteins, Cu and Zn produce antagonistic effects to some extent (52).
Although Cu deficiency can occur in all mammals, it is more common in ruminants (53). This is because Fe reacts with sulfide in the rumen to form the Fe-S complexes that can get dissociated from the abomasum to form insoluble CuS, thus reducing the uptake of Cu (54). The initial concentration of serum Cu was 0.57 mg/L in the 84 Mongolian Wu Ranke sheep. In the previous research, the serum Cu concentration was found to range from 0.70 mg/L to 1.36 mg/L in healthy sheep, indicating that the Mongolian Wu Ranke sheep under study developed Cu deficiency (36). The feeding on Cu deficient diet for 60 days significantly reduced serum Cu concentration to 0.46 mg/L, which suggests that dietary Cu content can reflect serum Cu concentration. The serum Cu concentration rose sharply to 0.61 mg/L after 41 days of Cu supplementation. Thus, long-term dietary Cu The results of the serum biochemical parameters concentration and the serum biochemical parameters activity in Zn treatment group. NS p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001.
Frontiers in Veterinary Science 13 frontiersin.org supplementation is recommended for the Mongolian Wu Ranke sheep as the accumulation of Cu in sheep may be instantaneous. In this research, the concentration of serum Cu in the Ca, Zn, Co, Mn, and Se treatment groups showed a decreasing trend after 101 days of feeding on the diets containing multi-nutrient salts, which may result from serum Fe and serum Cu competing for the binding sites on intestinal proteins, with excess Fe inhibiting the absorption of Cu (55). The mean value of initial serum Fe concentration in these 84 Mongolian Wu Ranke sheep studied was 2.03 mg/L. By comparison, the serum Fe concentration in healthy sheep was in the range of 1.00 mg/L to 2.00 mg/L (36). On day 101 of feeding with multinutrient mineral salts, the serum Fe concentration in these 84 Mongolian Wu Ranke sheep increased to 4.80 mg/L, which is beyond the normal range. For the sheep, serum Cu and Fe showed a significant negative correlation, with excess Fe decreasing the Cu concentration in the sheep serum (56). At the same time, the multi-nutrient mineral salts in the diet contained S, and serum S concentration gradually increased in the blood collected three times. This also provided elements Fe and S required for the formation of Fe-S complexes in the rumen, which reduces Cu absorption. It is demonstrated that Mongolian Wu Ranke sheep have sufficient Fe, which means no need for dietary Fe supplementation. Mn is involved in energy metabolism and is effective in promoting the utilization of fat (32). The mean value of the initial concentration of serum Mn was 0.033 mg/L. According to some research, the serum Mn concentration in healthy sheep was 0.04 mg/L to 0.05 mg/L, which indicates a slight deficiency of Mn in the sheep studied (36). The deficiency of Ca and Mn could impede bone formation and thus reduce the growth rate for animals (42,57). Therefore, it is worth paying attention to the skeletal health of the Mongolian Wu Ranke sheep regularly. The serum Mn concentrations in the Mn treatment group decreased after 60 days of feeding on the Mn deficiency diet and then increased after 41 days of feeding on the Mn supplement diet. The mean value of serum Mn concentration was 0.094 mg/L, 0.10 mg/L, 0.056 mg/L, 0.045 mg/L and 0.11 mg/L in the Ca, Zn, Cu, Co, and Se treatment groups after 60 days of feeding with multi-nutrient mineral salts, which shows that Mn can be replenished in the serum of Mongolian Wu Ranke sheep through the prompt supplementation of Mn in the diet.
Among all of the measured essential mineral elements, serum Se deficiency was found most severe in this study. The serum Se concentration in healthy sheep was determined to be in the range of 0.09 mg/L to 0.50 mg/L (36). However, the initial concentration of serum Se was merely 0.015 mg/L in the sheep studied, which indicates Se deficiency. Although the ruminants with Se deficiency may suffer from leukodystrophy, the Mongolian Wu Ranke sheep in the study showed no clinical signs, such as hair loss or muscular dystrophy (5,58). Due to the strong reducing environment in the rumen of ruminants, selenium was partially converted into insoluble compounds, which is adverse to the Se storage (59). Therefore, timely Se supplementation is required for the sheep. After 60 days of feeding with multi-nutrient salts, the serum Se concentration in Se deficiency treatment exceeded the lower limit of detection and could not be measured. The mean value of serum Se concentration in Ca, Zn, FIGURE 10 The results of the serum biochemical parameters concentration and the serum biochemical parameters activity in Cu treatment group. NS p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001.
Frontiers in Veterinary Science 14 frontiersin.org Cu, Co, and Mn deficiency groups increased significantly to 0.087 mg/L, 0.083 mg/L, 0.091 mg/L, 0.090 mg/L, and 0.082 mg/L, which falls within the normal range as recommended. This result is similar to that of some other research (60), indicating that serum Se can be used to indicate the short-term Se status of the sheep. In spite of this, long-term dietary supplementation of Se is still recommended. However, dietary mineral element status may not be the only factor affecting the concentration of serum mineral elements. They are also influenced by the animal species, individual animal variability, metabolic processes and interactions between mineral elements (55). Serum biochemical parameters are closely related to a range of physiological processes such as animal performance and lipid metabolism (61,62). These parameters can be used to effectively assess animals for their nutritional status, tissue damage and organ dysfunction. ALT (63), AST (63), ALP (64), γ-GT (65), T-Bil (66), ALB (67), and TP (68) are applicable to evaluate the animal for liver function or impairment. In addition, ALP is a reliable indicator of bone mineralization identification. Abnormal ALP activity can disrupt the dynamic balance inside animals through certain factors. When exceeding the normal levels, ALP activity may also indicate the development of many diseases, such as excessive bone mineralization, tumors, and potentially Alzheimer's disease (69). In the research, it is indicated that the normal activity of sheep serum ALP varied from 70 U/L to 390 U/L (70). The activity of ALP of all the Mongolian Wu Ranke sheep studied fell within the normal range for the three serum collections. The broiler fed with Ca-deficient diet showed increased ALP activity, which impairs bone development (71). The level of serum Ca concentration in this study was usually low Due to the enhanced serum ALP activity and insufficient Ca concentration, the skeletal development of the Mongolian Wu Ranke sheep may be hindered.
ALT accumulates mainly in the cytoplasm of hepatocytes, in which the ALT activity is approximately 3,000 times stronger than in serum. Therefore, when the liver suffers damage, the damaged hepatocytes release ALT, which significantly enhances the serum ALT activity (72). As a cytoplasmic and mitochondrial enzyme used to catalyze the reversible reaction of aspartate deamination to oxaloacetate, AST can participate in the Krebs cycle. AST elevation may occur in hepatocyte or muscle damage diseases (73). In the context of liver injury, fatty liver and hepatitis, serum AST and ALT activity are significantly increased. It has been shown that the ALT and AST activities increased significantly in Ca-deficient rats (74). In the Ca deficiency treatment, the activities of serum AST and ALT increased significantly, as did the concentrations of ALB and T-Bil. ALB is produced mainly by the liver and the rise of ALB concentration may be associated with liver dysfunction (67). As a breakdown product of hemoglobin, TBil can be used as a diagnostic indicator of liver and blood disorders. TBil can be divided into non-conjugated bilirubin and conjugated bilirubin. Elevated non-conjugated bilirubin can lead to liver damage and dysfunction, thus causing hyperbilirubinemia (66). The elevation of these indicators indicates a possibility that feeding on Ca-deficient diet causes liver damage in the sheep studied. In Ca supplement treatment, there were no significant differences observed in serum AST, ALT, ALB, and T-Bil when compared with Ca deficiency treatment, which may suggest that the dietary Ca supplementation for 41 days failed to alleviate liver damage FIGURE 11 The results of the serum biochemical parameters concentration and the serum biochemical parameters activity in Co treatment group. NS p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001. or dysfunction. In the research, it was indicated that the Cu deficiency in Kazakh sheep caused a significant increase in ALT and AST activities, which resulted in hepatocyte damage (13). The same results were also found in the sheep serum in the Cu deficiency group. TP is an important indicator of liver damage (68). A significant increase in the activity of AST, ALT and the concentration of ALB, TP may also indicate that Cu deficiency contributed to hepatocyte damage for the Mogolian Wu Ranked sheep. However, there was no significant reduction observed in these four indicators among the Cu supplement group, which may be due to the ineffectiveness of short-term dietary Cu supplementation in reducing the liver damage caused by Cu deficiency. Serum ALT activity was significantly elevated in Co deficiency treatment indicating that Co deficiency may have a negative effect on the liver. However, there was a significant decrease in serum ALB concentration and γ-GT activity after feeding on Co supplementation diet. The enhancement of serum γ-GT activity was associated with liver damage. Due to γ-GT elevation, glutathione was degraded to cysteine-glycine, which led to the generation of ROS. By inhibiting the elevation of γ-GT activity, cellular oxidative stress and membrane damage can be prevented (75). Although Co was not detected in serum in the study, the results of serum biochemical parameters still showed that Co supplementation could contribute to alleviating the liver damage caused by Co deficiency. In general, the increase in serum ALT and AST activity can be referenced to diagnose the Se deficiency in sheep (5). Se deficiency caused a significant increase in the activity of serum AST, ALT, and concentration of TP for the Mongolian Wu Ranke sheep, thus resulting in the impairment of liver function. Following the dietary supplementation with Se, Se supplement treatment significantly suppressed the activity of AST, γ-GT and the concentration of ALB, which may demonstrate that timely Se supplement can reduce the value of liver-related parameters and promote liver function. After 60 days of feeding on Mn deficiency diet, there was a significant increase found in the concentration of TBil and ALB and the activity of ALT, which adversely affects liver function. For the Mn supplement treatment, the serum γ-GT activity and ALB concentration decreased significantly after the Mn supplement. Previous research showed that Mn supplement significantly inhibited AST and ALT activity in rats (74). Despite no significant differences in Mn supplement treatment. ALT and AST, γ-GT, and ALB can also be taken as the indicators of liver function. It is suggested that Mn supplement may have a beneficial effect on the liver of the Mongolian Wu Ranke sheep. A significant increase in the concentration of ALB, TP and the activity of AST, ALT may also indicate that Zn deficiency contributed to hepatocyte damage for the Mongolian Wu Ranked sheep. Following the dietary supplementation with Zn, Zn supplement treatment significantly suppressed the concentration of ALB and TP and the activity of γ-GT, which may demonstrate that timely Zn supplement could contribute to alleviating the liver damage caused by Zn deficiency.
In addition to impairing liver function, the deficiency in dietary essential mineral elements can also cause damage to the skeletal muscle or myocardium of the sheep. CK is known as one of the most abundant intracellular enzymes in skeletal muscle and myocardium, and serum CK serves as a good indicator of skeletal muscle and myocardium injury. Besides, the elevation of serum CK activity has been accepted as a means to detect myocardial infarction (76). In the FIGURE 12 The results of the serum biochemical parameters concentration and the serum biochemical parameters activity in Mn treatment group. NS p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001. TC and TG are used as the parameters of lipid metabolism in serum biochemical analysis (61). TC concentrations were found significantly higher in Cu deficiency treatment. The decrease in serum Cu concentration may be partly responsible for the increase in TC concentration. The intracellular concentrations of reduced glutathione elevation can enhance the activity of cholesterol synthesis rate-limiting enzymes. If the cellular concentration of reduced glutathione increases due to Cu deficiency, then the activity of rate-limiting enzymes increases as well, thus enhancing cholesterol synthesis (55). The two important components of TC are high-density lipoprotein and low-density lipoprotein. By affecting lipid metabolism, excess TC leads to metabolic disorders. TG refers to a fat molecule formed by the condensation of long-chain fatty acids and glycerol. Produced by the oxidative breakdown of fats, ATP can provide energy to most tissues (61). It has been demonstrated that the concentration of TC is correlated with that of TG. TG concentration was found higher in junior sheep and TC concentration was found irrelevant to the age of sheep (77). In the research, a positive correlation was discovered between serum Ca and TG concentrations (78). The TG concentration of the sheep was significantly lower in Ca deficiency treatment but significantly higher in Ca supplement treatment, which is consistent with the result of some other research. Also, dietary Co supplements increased the level of serum TG concentrations, which shows the possibility of dietary Ca and Co supplements increasing the body fat content in the Mongolian Wu Ranke sheep. Interestingly, serum LIP activity was enhanced significantly in Ca deficiency treatment. LIP can help digest fat and the increase in LIP activity can decrease TG concentration (79). This translates into a decrease in serum TG concentration for Ca deficiency. LIP and α-AMY are the biomarkers of pancreas injury, the elevation of which provides a diagnostic basis for acute pancreatitis (80). In the research, it is shown that Mn deficiency caused a significant increase in α-AMY activity, which is consistent with the results of this study (81). According to the results of serum LIP and α-AMY, such mineral elements as Ca, Zn, Cu, Co, Mn, and Se deficiency may impair pancreas function for the Mongolian Wu Ranke sheep. After 41 days of Se supplementation, the α-AMY activity decreased significantly in Se supplement treatment. It may be attributed to the effectiveness of dietary Se supplementation in restoring pancreas function.
Frontiers in
In normal circumstances, serum GLU concentration is 2.8 mmol/L to 5.6 mmol/L for sheep (60). The serum GLU concentration of all the Mongolian Wu Ranke sheep studied fell within the normal limits, with no hypoglycemia or hyperglycemia detected. However, there was a significant increase observed in GLU concentration for the Wu Ranke sheep receiving Ca, Cu, Co and Se supplement treatments. It has been shown that the dietary Co and Se supplementation for sheep can increase glucose concentrations (59, 60,82). It may be because propionic acid is the primary precursor of glucose in ruminants. For The results of the serum biochemical parameters concentration and the serum biochemical parameters activity in Se treatment group. NS p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001.
sheep, Co supplementation led to a significant increase in propionic acid concentrations, while the higher propionic acid concentrations resulted in higher serum glucose concentrations (17). This is coherent with the finding of the previous research, which may indicate that the dietary supplementation of Ca, Cu, Co, and Se can improve the generation of energy for the Mongolian Wu Ranke sheep.
CREA and UREA are commonly used as biomarkers of renal function. The kidneys are responsible for various important physiological functions, such as filtering blood and removing toxins (83). As a kind of metabolic waste, CREA is mainly excreted by the kidneys. When the kidney is dysfunctional, the level of serum CREA concentration rises sharply (84). As the main nitrogen metabolite in the blood, UREA is derived mainly from the degradation of proteins. Its content is higher in adult sheep than in junior sheep (77). However, the elevation of UREA and CREA does not necessarily indicate the development of kidney disease. This is considered to be normal within the standard range (85). The normal range of CREA and UREA in sheep is 44.2 umol/L-132.6 umol/L and 2.8288 mmol/L-9.984 mmol/L, respectively (86). The concentration of serum CREA and UREA was within the normal range for all the Mongolian Wu Ranke sheep studied, indicating that the kidney function of the Mongolian Wu Ranke sheep was unaffected by mineral element deficiency and supplementation. In addition, there are still many limitations in this study. Firstly, the feeding experiments might be better to design 30, 60, and 90 days to obtain more reasonable days of supplementation for grazing sheep. In this research, the effects of essential mineral element deficiency and supplementation on the liver, myocardium and pancreas were determined only by serum levels of mineral elements and biochemical parameters. In the future, morphological, pathological and biochemical parameters might be explored directly on the liver, myocardium and pancreas to further validate the results from this research.
In conclusion, according to the results of the serum essential mineral element measurement, the grazing Mongolian Wu Ranke sheep in this study developed Ca, Cu, Co, Mn, and Se deficiencies. During the 60 days of experiment on dietary Ca, Zn, Cu, Co, Mn, and Se deficiency, the serum biochemical parameters showed that the deficiency of the essential mineral elements was damaging to the liver of the Mongolian Wu Ranke sheep, and their myocardium and pancreas functions. In the 41 days of dietary Ca, Zn, Cu, Co, Mn, and Se supplements after the deficiency experiment, the supplementation with Ca, Cu, and Se significantly increased the level of serum Ca, Cu, and Se concentrations. The dietary supplementation of Zn, Co, Mn, and Se reduced liver-related indicators and alleviated liver damage. The supplementation of Cu possibly restored myocardium function. Se supplementation reduced pancreas parameters. The supplementation of Ca and Co possibly increased the fat content. Ca, Cu, Co, and Se supplementation increased the serum glucose concentration and possibly improved the generation of energy. To sum up, serum elements and biochemical parameters measurement indicated that the prompt supplementation of essential mineral elements like Ca, Zn, Cu, Co, Mn, and Se is required for grazing Mongolian Wu Ranke sheep to avoid the damage caused to their liver, myocardium and pancreas. This study provided data guidance for rational mineral supplementation in grazing sheep, which can help improve the overall health and productivity of grazing sheep and further promote increased production and income of herders.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.
Ethics statement
The animal study was reviewed and approved by Inner Mongolia University Animal Care and Use Committee.
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Domain: Agricultural And Food Sciences
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Quantitative Analysis of Mixed Minerals with Finite Phase Using Thermal Infrared Hyperspectral Technology
It is crucial but challenging to detect intermediate or end products promptly. Traditional chemical detection methods are time-consuming and cannot detect mineral phase content. Thermal infrared hyperspectral (TIH) technology is an effective means of real-time imaging and can precisely capture the emissivity characteristics of objects. This study introduces TIH to estimate the content of potassium salts, with a model based on Competitive Adaptive Reweighted Sampling (CARS) and Partial Least Squares Regression (PLSR). The model takes the emissivity spectrum of potassium salt into account and accurately predicts the content of Mixing Potassium (MP), a mineral mixture produced in Lop Nur, Xinjiang. The main mineral content in MP was measured by Mineral Liberation Analyzer (MLA), mainly including picromerite, potassium chloride, magnesium sulfate, and less sodium chloride. 129 configured MP samples were divided into calibration (97 samples) and prediction (32 samples) sets. The CARS-PLSR method achieved good prediction results for MP mineral content (picromerite: correlation coefficient of correction set (Rp2) = 0.943, predicted root mean square error (RMSEP) = 2.72%, relative predictive deviation (RPD) = 4.24; potassium chloride: Rp2 = 0.948, RMSEP = 2.86%, RPD = 4.42). Experimental results convey that TIH technology can effectively identify the emissivity characteristics of MP minerals, facilitating quantitative detection of MP mineral content.
Introduction
During the mineral production process, the composition of intermediate and terminal products can change within a certain range due to factors such as alterations in the original ore's nature, production operations, or other variables. In this type of product, although the mineral content varies within a certain range, the types of minerals are basically unchanged and can be referred to as "finite phase minerals". Not adjusting production parameters in a timely manner based on actual production conditions can cause production instability, leading to a waste of resources and increased economic costs. As a result, it is essential to conduct intermittent sampling and tests to gather production information that can aid in the production process [1]. The chemical volumetric method is the primary analytical technique in production. In this method, minerals are dissolved, and specific chemical reagents are used to identify relevant elements. Although this method can meet production requirements to some extent, the low detection speed and incapable of detecting mineral phases cannot be neglected. Other mineral quantitative detection methods [2,3], such as hyperspectral to accurately detect salt mineral content [29], it is promising in detecting salt minerals that have a tendency to form dense mixtures. Based on this, this study utilized TIH technology to acquire and quantitatively analyze the emissivity data of potassium salt. The contributions of this study are as follows: (1) TIH technology was employed to obtain thermal infrared spectral characteristic information of potassium salt; (2) The thermal infrared spectrum characteristics of pure minerals in potassium salt were obtained and the potassium salt grade was detected by CARS-PLSR method.
Technical Route
In this study, we aim to figure out the feasibility and accuracy of the TIH technique in the application of the mineral phases of potassium salts detection. The potash samples used in the study came from Xinjiang Lop Nur Potash Co., China's largest potash sulfate producer. The main research process ware as follows: (1) Based on the actual MP samples, mixed potassium samples were designed and prepared by adding varying amounts of Pure minerals. A batch of potassium salt samples were obtained with sufficient and known mineral phase composition. (2) The samples were standardized by the pellet method, which stabilized the roughness of each sample and reduced the "noise" in the spectrum data. Subsequently, the spectral data of the potassium salt samples were collected using the Hyper-Cam hyperspectral imager in an open environment. (3) The TIH data for potassium salt was processed to obtain its emissivity data. Based on this emissivity data, prediction models were established for the mineral phase composition of potassium salt using the CARS and PLSR methods. (4) The prediction results of the model were evaluated and analyzed. The flowchart of the experimental and modeling process is shown in Figure 1.
contents in soil, there is currently limited literature available on the identification of various salt contents [14,17]. Since TIH technology could capture feature information with hyperspectral to accurately detect salt mineral content [29], it is promising in detecting salt minerals that have a tendency to form dense mixtures. Based on this, this study utilized TIH technology to acquire and quantitatively analyze the emissivity data of potassium salt. The contributions of this study are as follows: (1) TIH technology was employed to obtain thermal infrared spectral characteristic information of potassium salt; (2) The thermal infrared spectrum characteristics of pure minerals in potassium salt were obtained and the potassium salt grade was detected by CARS-PLSR method.
Technical Route
In this study, we aim to figure out the feasibility and accuracy of the TIH technique in the application of the mineral phases of potassium salts detection. The potash samples used in the study came from Xinjiang Lop Nur Potash Co., China's largest potash sulfate producer. The main research process ware as follows: (1) Based on the actual MP samples, mixed potassium samples were designed and prepared by adding varying amounts of Pure minerals. A batch of potassium salt samples were obtained with sufficient and known mineral phase composition. (2) The samples were standardized by the pellet method, which stabilized the roughness of each sample and reduced the "noise" in the spectrum data. Subsequently, the spectral data of the potassium salt samples were collected using the Hyper-Cam hyperspectral imager in an open environment. (3) The TIH data for potassium salt was processed to obtain its emissivity data. Based on this emissivity data, prediction models were established for the mineral phase composition of potassium salt using the CARS and PLSR methods. (4) The prediction results of the model were evaluated and analyzed. The flowchart of the experimental and modeling process is shown in Figure 1.
MP Samples
Based on a random survey of 738 MP mineral phase data from the Lop Nur Potash production site in the first half of 2021, 138 MP samples of 5 g each were designed and
MP Samples
Based on a random survey of 738 MP mineral phase data from the Lop Nur Potash production site in the first half of 2021, 138 MP samples of 5 g each were designed and configured. The 400 g MP sample from the production site of potassium salt (dried at 50 • C, mixed evenly by shifting cone method) was used as a master sample. The mineral phases and contents of the master sample were accurately analyzed with multiple detection methods. The 138 MP samples were then configured by adding one or more salts (contained in the MP) to the master sample.
Mineral Facies Analysis
By comprehensive analysis of X-ray diffraction analysis (XRD) [30], MLA [31], Chemical titration, and ASS [32], the types and specific contents of various minerals in the MP master sample were defined. The specific parameters of the test method are as follows: XRD: The D8 Advance X-ray diffractometer with Cu target from Bruker, Germany was used for XRD testing. The acceleration voltage is 40 kV and the anode current is 150 mA. Wide-angle diffraction patterns are collected in the range of 5-70 • (2θ) at a scanning speed of 5 • /min. MLA: The system consists of a ZEISS Sigma model 300 high-resolution field emission scanning electron microscopy (FESEM), a Bruker XFlash 6|60 type X-ray spectrometer (EDS), and a set of AMICS software (including 4 subroutines, AMICSTool, Investigator, MineralSTDManager, and AMICSProcess). Experimental conditions: accelerating voltage 20 kV, High vacuum mode, a working distance of about 8.5 mm, backscattered electron detector (HDBSD), High Current mode. The sample was sprayed before testing to eliminate the charge on the surface of the non-conductive sample. The samples were polished using saturated MP mother liquor as a polish.
Chemical Titration: Titration of K + : Sodium tetraphenylboron-quaternary amine salt volumetric method. Determination principle: Potassium ions react with sodium tetraphenolate boron to form potassium tetraphenolate boron deposits, and excess sodium tetraphenolate boron reacts with quaternary amine salt to form insoluble quaternary amine salt sodium tetraphenolate boron double salt.
Titration of Mg 2+ : EDTA complexometric titration. Determination principle: The cation in EDTA complexes with the calcium and magnesium cation in the test solution, so that the color of the solution changed from tartar red to azure blue, which was the endpoint.
Titration of SO 2− 4 : Moore method. Determination principle: Potassium chromate as indicator was titrated directly with silver nitrate standard solution in neutral weak alkaline solution.
Titration of Cl -: Barium chloride volumetric method. Determination principle: In an acidic solution (pH = 2~3), SO 2− 4 and BaCl 2 generated excessive barium salt precipitation and alizarin red~S indicator to generate a yellow complex, titrated with a known standard solution, adding ethanol to improve the sensitivity of the endpoint of the titration.
AAS: Titration of Na + : According to the general rules of atomic absorption spectrometry, the sodium ions in the solution were analyzed by using the German continuous light source atomic absorption spectrometer at the pressure of 0.3 MPa.
Mineral Composition of MP Samples
XRD result in Figure 2 shows that the main components of MP are picromerite (KMg(SO 4 ) 2 ·6H 2 O) and potassium chloride (KCl). In the MLA test results shown in Figure 3, the element Mg:S:K in the red region has a mole ratio of approximately 1:2.03:1.85, indicating that picromerite is the primary mineral, followed by a small amount of magnesium sulfate (MgSO 4 ·7H 2 O). The mole ratio of element K:Cl in the yellow region is about 1.01:1.00, which is expressed as KCl. The mole ratio of the element Na:Cl in blue is about 1.00:1.00, represented by sodium chloride (NaCl). The MLA detection result shows that the MP sample contains a large amount of picromerite and sodium chloride in addition to less potassium sulfate and potassium chloride. However, during sample preparation for the MLA test, the MP sample was partially dissolved due to the requirement to wash and polish the sample simultaneously, despite the saturated MP mother liquor being used as a detergent. As shown in Table 1, 8.18% of the MLA test field is not uniform and could not be measured, which means, 5.37% of the MP sample could not be identified. Therefore, chemical volumetric methods were used to supplement the MLA results. The result of the chemical volumetric test in Figure 3 shows that the mass of potassium ion is 27.18%, a magnesium ion is 4.30%, sulfate ion is 33.67%, chloride ion is 13.57%, and sodium ion is 0.32%. Finally, the composition of the 400 g MP sample can be inferred as follows: picromerite, 65.70%, potassium chloride, 27.50%, magnesium sulfate, 5.97%, sodium chloride, 0.81%, combined with the ionic content data from the chemical titration in Table 2. However, during sample preparation for the MLA test, the MP sample was partially dissolved due to the requirement to wash and polish the sample simultaneously, despite the saturated MP mother liquor being used as a detergent. As shown in Table 1, 8.18% of the MLA test field is not uniform and could not be measured, which means, 5.37% of the MP sample could not be identified. Therefore, chemical volumetric methods were used to supplement the MLA results. The result of the chemical volumetric test in Figure 3 shows that the mass of potassium ion is 27.18%, a magnesium ion is 4.30%, sulfate ion is 33.67%, chloride ion is 13.57%, and sodium ion is 0.32%. Finally, the composition of the 400 g MP sample can be inferred as follows: picromerite, 65.70%, potassium chloride, 27.50%, magnesium sulfate, 5.97%, sodium chloride, 0.81%, combined with the ionic content data from the chemical titration in Table 2. the red area is picromerite, the dark gray area is low counting rate, the yellow area is potassium chloride, the blue area is sodium chloride, and light gray area is an unknown mineral.
However, during sample preparation for the MLA test, the MP sample was partially dissolved due to the requirement to wash and polish the sample simultaneously, despite the saturated MP mother liquor being used as a detergent. As shown in Table 1, 8.18% of the MLA test field is not uniform and could not be measured, which means, 5.37% of the MP sample could not be identified. Therefore, chemical volumetric methods were used to supplement the MLA results. The result of the chemical volumetric test in Figure 3 shows that the mass of potassium ion is 27.18%, a magnesium ion is 4.30%, sulfate ion is 33.67%, chloride ion is 13.57%, and sodium ion is 0.32%. Finally, the composition of the 400 g MP sample can be inferred as follows: picromerite, 65.70%, potassium chloride, 27.50%, magnesium sulfate, 5.97%, sodium chloride, 0.81%, combined with the ionic content data from the chemical titration in Table 2.
Samples Library of MP
As shown in Figure 4a, among the 738 MP samples investigated, the content of picromerite ranged from 30.73% to 76.79%, with an average of 51.20% and a median of 51.19%. In 138 manually configured MP samples, the content parameters of picromerite ranged from 30.46% to 74.49%, with an average of 53.91% and a median of 53.43%. The content distribution of 138 MP samples was similar to that of 738 MP samples data. While Table 3 shows that potassium chloride, magnesium sulfate, and sodium chloride are also similar, which indicates 138 MP samples manually configured can completely meet the needs of field production.
Standardized Processing of MP Samples
The MP samples were then slightly ground and placed in 50 mL centrifuge tubes and mixed using a vortex oscillating mixer at 300 r/min for 6 min. Finally, the MP samples were successively put into a square mold with an inner diameter of 2 cm and pressed for 30 s under a pressure equivalent to 6 t to complete sample preparation.
Hyperspectral Imaging System and Image Acquisition
In this study, a Hyper-Cam hyperspectral imager (Telops, Canada) was used for data acquisition, and its imaging mode was Fourier interference imaging. The spectral range of the instrument is 7.7-11.8 μm, the spectral resolution range is 0.25-150 cm −1 , the Field of View (FOV) (°) is 40, and the imaging field is 320 × 256 array.
Standardized Processing of MP Samples
The MP samples were then slightly ground and placed in 50 mL centrifuge tubes and mixed using a vortex oscillating mixer at 300 r/min for 6 min. Finally, the MP samples were successively put into a square mold with an inner diameter of 2 cm and pressed for 30 s under a pressure equivalent to 6 t to complete sample preparation.
Hyperspectral Imaging System and Image Acquisition
In this study, a Hyper-Cam hyperspectral imager (Telops, Canada) was used for data acquisition, and its imaging mode was Fourier interference imaging. The spectral range of the instrument is 7.7-11.8 µm, the spectral resolution range is 0.25-150 cm −1 , the Field of View (FOV) ( • ) is 40, and the imaging field is 320 × 256 array.
As shown in Figure 5, the Hyper-Cam hyperspectral imaging system was used to collect TIH data from samples and a diffuse reflector (gold-plated plate) in a relatively open environment. The open environment can effectively avoid the interference of other objects in the surrounding environment and reduce the noise of acquiring data. At the same time, the sample was preheated with a heating table, and the heating temperature was set to 50°C. Fluke 54-IIB dual channel contact thermometer was used to record the temperature of the sample and gold foil before and after imaging, and the mean value was taken as the temperature of the sample and gold foil. Then, the absolute value of the difference between the measured temperature and the inverted temperature was used to evaluate the quality of the sample spectral data. It is generally believed that if the absolute value of the temperature difference is less than 1 K, the quality of collected sample data is acceptable and can be used for accurate quantitative analysis and study.
Emissivity Inversion
The method of obtaining sample emissivity in this study refers to the study [33]. Iterative Spectrally Smooth Temperature and Emissivity Separation (ISSTES) algorithm is widely used in remote sensing applications to accurately calculate the emissivity of solid objects from their spectral radiance measurements. The ISSTES takes advantage of the fact that the emissivity spectrum of solid objects is smoother than the characteristics of the atmosphere. ISSTES algorithm defines a group of emissivity curves indexed by surface temperature as follows: where L sensor (λ) is the total radiance reaching the sensor, λ is the central wavelength of each channel (µm), ε(λ) is the emissivity, and E(λ) is environmental radiance measured by the gold-plated plate. τ(λ) and Lu(λ) are atmospheric transmittance and upwelling radiation, respectively, which are simulated by MODTRAN ® 5.2. B(λ,T) is the Planck radiance at panel
Emissivity Inversion
The method of obtaining sample emissivity in this study refers to the study [33]. Iterative Spectrally Smooth Temperature and Emissivity Separation (ISSTES) algorithm is widely used in remote sensing applications to accurately calculate the emissivity of solid objects from their spectral radiance measurements. The ISSTES takes advantage of the fact that the emissivity spectrum of solid objects is smoother than the characteristics of the atmosphere. ISSTES algorithm defines a group of emissivity curves indexed by surface temperature as follows: where Lsensor(λ) is the total radiance reaching the sensor, λ is the central wavelength of each channel (μm), ε(λ) is the emissivity, and E(λ) is environmental radiance measured by the gold-plated plate. τ(λ) and Lu(λ) are atmospheric transmittance and upwelling radiation, respectively, which are simulated by MODTRAN ® 5.2. B(λ,T) is the Planck radiance at panel temperature T. The units for Lsensor(λ), Lu(λ), B(λ, T) and E(λ), are all W/(m²·sr·μm). ε(λ) and τ(λ) are dimensionless quantities.
As can be seen from Equation (1), given the surface temperature and known atmospheric parameters, the corresponding emissivity spectrum can be calculated. Then, if the smoothness criterion of the emissivity curve is determined, the smoothness of a series of emissivity curves at different temperatures near the real surface temperature can be calculated, and the temperature corresponding to the estimated emissivity spectrum is the smoothest result. The smoothness criterion used by ISSTES is designed as follows: where S is the calculated smoothness criterion value, and N is the frequency band number of hyperspectral data.
In this study, the pretreatment of TIH data as well as the CARS and PLSR algorithms were calculated using MATLAB 2019a. As can be seen from Equation (1), given the surface temperature and known atmospheric parameters, the corresponding emissivity spectrum can be calculated. Then, if the smoothness criterion of the emissivity curve is determined, the smoothness of a series of emissivity curves at different temperatures near the real surface temperature can be calculated, and the temperature corresponding to the estimated emissivity spectrum is the smoothest result. The smoothness criterion used by ISSTES is designed as follows: where S is the calculated smoothness criterion value, and N is the frequency band number of hyperspectral data. In this study, the pretreatment of TIH data as well as the CARS and PLSR algorithms were calculated using MATLAB 2019a.
Data Quality Evaluation by Temperature
In this study, the accuracy of the emissivity data was evaluated indirectly by comparing the measured temperature of the sample with the temperature obtained through inverted emissivity data using the algorithm. Since temperature and emissivity are coupled. When the emissivity error is about 0.015, the temperature error is about 1 k [34]. By comparing the measured and inverted temperatures, any discrepancies or errors in the emissivity data could be identified, thereby improving the accuracy of the spectral data and subsequent analysis. The difference between the measured and inverted temperatures was used as an indicator of the quality of the inverted data. This approach is crucial for the successful analysis and interpretation of the TIH data [35]. Figure 6a illustrates that the temperature difference of all samples is within ±2 K. In Figure 6b, 71.0% of the samples are in the range of absolute temperature difference ≤1 K, which indicates that the data collection and data processing process of MP samples is effective and the emissivity data obtained are of high quality. These emissivity results can be used for quantitative analysis and research of MP. and research of MP.
As can be seen from the temperature distribution of some MP samples in Figure 6c, the surface emissivity of MP samples is relatively uniform, indicating that MP samples are fully and evenly mixed during preparation. In addition, the mean emissivity of the 15 × 20 pixel at the center of the MP sample surface is taken as the emissivity of the corresponding sample to further reduce the effect of systematic errors in sample preparation. As can be seen from the temperature distribution of some MP samples in Figure 6c, the surface emissivity of MP samples is relatively uniform, indicating that MP samples are fully and evenly mixed during preparation. In addition, the mean emissivity of the 15 × 20 pixel at the center of the MP sample surface is taken as the emissivity of the corresponding sample to further reduce the effect of systematic errors in sample preparation.
Prediction Model
Firstly, 138 samples were tested for outliers and removed. To avoid some unreliable samples in the modeling calculation [36], the 138 samples were sorted and classified according to their picromerite content and then divided into 5 groups by regular interval sampling. Then, 4 groups of samples were randomly selected as the correction set, and the remaining group of samples was the prediction set. PLSR calculations were performed 5 times. Therefore, each sample had 4 calibration residual errors (CRE) and 1 predicted residual error (PRE). Then, PLSR [37] was used for analysis and calculation, and the CARS [38] method was introduced to choose feature wavelength. The PLSR model and the CARS-PLSR model were constructed separately. CARS were employed to screen out the sensitive bands corresponding to the minerals, while PLSR is utilized to establish a linear relationship between the mineral-sensitive bands and mineral content. The resulting model was then employed to estimate the content of salt ore. The PLSR method, by projection, obtains orthogonal feature vectors for independent and dependent variables, respectively, and then establishes a unitary linear regression relation between the feature vectors. This approach not only resolves the issue of collinearity but also emphasizes the importance of independent variables in explaining and predicting dependent variables during the selection of feature vectors. By selecting several key variables, this method enables the model to achieve the minimum number of variables necessary for optimal performance. For the CARS method, the absolute value of the regression coefficient of the PLSR model is used as the index to evaluate the importance of each wavelength. In each sampling run, a fixed proportion of samples is randomly selected to establish the correction model. The number of samples selected in this study is 80% of the number of calibrations set. The wavelength for selection bands with larger absolute regression coefficients in the PLSR model is defined through adaptive reweighting sampling (ARS) technology. That is, CARS can often find the optimal combination of some key wavelengths that explain the chemical properties of interest.
Model Evaluation
To fully verify the performance of the model, the samples in the MP sample bank were divided into a calibration set and a testing set. The calculated parameters for the calibration set include the correlation coefficient (R 2 c ) and root mean square error (RMSEC). The calculated parameters for the prediction set include the correlation coefficient (R 2 p ), root mean square error (RMSEP), and relative prediction deviation (RPD). The higher R 2 c , R 2 p , and RPD, the lower RMSEC, and RMSEP, the better the predictive effect of the model. If R 2 c is close to R 2 p , or RMSEC is close to RMSEP, the model is robust. In particular, an RPD value between 1.8 and 2.0 indicates a good model, between 2.0 and 2.5 indicates a very good model, and above 2.5 indicates excellent model performance [39].
In Formulas (3)-(5), y i represents the predicted sample mineral content, y i represents the mean value of the actual sample mineral content, y i represents the actual sample mineral content, and n represents the number of samples involved in the calculation.
Outlier Detection
The outlier observation map of the MP sample was established using MCRE with abscissa and PRE with ordinate, as shown in Figure 7. The mean of corrected residual error (MPCE) and predicted residual error (PRE) were taken as the reference, and the larger samples were eliminated. Among them, the points with large MCRE and PRE values are removed. The samples with numbers 108, 84, and 131 are removed with picromerite; samples with numbers 21, 68, 84, 119, and 131 are removed with potassium chloride; samples with number 44 and 55 are removed with magnesium sulfate; samples with number 94 and 106 are removed with sodium chloride. That is, a total of 9 outliers are detected, and the remaining 129 points are used for subsequent model calculation.
larger samples were eliminated. Among them, the points with large MCRE and PRE values are removed. The samples with numbers 108, 84, and 131 are removed with picromerite; samples with numbers 21, 68, 84, 119, and 131 are removed with potassium chloride; samples with number 44 and 55 are removed with magnesium sulfate; samples with number 94 and 106 are removed with sodium chloride. That is, a total of 9 outliers are detected, and the remaining 129 points are used for subsequent model calculation.
Calibration Set and Prediction Set
As shown in Table 4 and Figure 8, a statistical analysis of the mineral composition of the four MP in the prediction and calibration sets is performed in terms of mean, standard deviation, minimum, median, and maximum. It illustrates that the range of sample parameters of the prediction set are all within the range of the calibration set. Moreover, from the two statistical terms mean and median, it can be found that the distribution of
Calibration Set and Prediction Set
As shown in Table 4 and Figure 8, a statistical analysis of the mineral composition of the four MP in the prediction and calibration sets is performed in terms of mean, standard deviation, minimum, median, and maximum. It illustrates that the range of sample parameters of the prediction set are all within the range of the calibration set. Moreover, from the two statistical terms mean and median, it can be found that the distribution of sample parameters of the prediction set and the calibration set is close, which means the results of the prediction set can fully illustrate the model performance of the calibration set.
MP Content Prediction
In the calibration set, PLSR conducts internal validation of the model based on leaveone-out validation, and the calculation results are shown in Table 5 and Figure 9. PLSR is the calculation method of multivariate linear relationship analysis, and the relationship between the percentage content of the four minerals in the MP is not clear. Therefore, univariate PLSR (U-PLSR) and multivariate PLSR (U-PLSR) are used for calculation. From the comparison of RPD values of the prediction set, the prediction accuracy of U-PLSR is higher than that of M-PLSR. The RPD values of four minerals of U-PLSR are 4.59, 4.06, 2.16, and 1.57, respectively, and those of four minerals of M-PLSR are 4.00, 4.06, 2.08, and 1.57, respectively. In the process of PLSR calculation, the components extracted from the joint composition matrix Y of the four minerals cannot represent the various minerals themselves, which deduced that there should be no correlation between the percentage contents of the four minerals. sample parameters of the prediction set and the calibration set is close, which means the results of the prediction set can fully illustrate the model performance of the calibration set.
MP Content Prediction
In the calibration set, PLSR conducts internal validation of the model based on leaveone-out validation, and the calculation results are shown in Table 5 and Figure 9. PLSR is the calculation method of multivariate linear relationship analysis, and the relationship
Sensitive Bands Selection of Pure Mineral
The CARS method is implemented through PLSR calculation of a single dependent variable, which can screen out the respective sensitive wavelengths of each mineral in MP samples. The CARS method could simplify the entire prediction method and enhance the feasibility of application in realistic scenarios of potassium salts. Table 6 shows that there In the calibration set of U-PLSR, the R 2 c of picromerite and potassium chloride is larger, while the R 2 c of magnesium sulfate and sodium chloride is smaller, which may be related to the ratio of four minerals in the MP sample. It means that the content of picromerite and potassium chloride in the calibration set is greater than that of magnesium sulfate and sodium chloride. In MP samples, the signal strength may be more pronounced when the content of a particular mineral is larger, and the final prediction accuracy is higher. In the U-PLSR, the RMSEP values of the four minerals are 2.52%, 3.12%, 1.17%, and 0.35%, respectively, which increase by 0.52%, 0.76%, 0.34%, and 0.14% compared with the RMSEC values. The results indicate that the prediction set is accurate and the PLSR model is robust to the mineral content prediction of MP.
Sensitive Bands Selection of Pure Mineral
The CARS method is implemented through PLSR calculation of a single dependent variable, which can screen out the respective sensitive wavelengths of each mineral in MP samples. The CARS method could simplify the entire prediction method and enhance the feasibility of application in realistic scenarios of potassium salts. Table 6 shows that there are 12 sensitive wavelengths for picromerite, 11 sensitive wavelengths for potassium chloride, 11 sensitive wavelengths for magnesium sulfate, and 8 sensitive wavelengths for sodium chloride. Figure 10 maps and compares the sensitive wavelengths of each mineral, pure mineral, and MP mean emissivity spectrum data. 9.13, 9.53, 9.62, 9.98, 10.17, 11.01 Potassium chloride 11 8.48, 8.72, 8.86, 9.21, 9.53, 9.58, 9.62, 9. 9.84, 9.98, 11.01, 11.30, 11.36 The sensitive wavelength distribution of picromerite is relatively uniform and distributed in the whole wavelength, among which there are four sensitive wavelengths concentrated in the trough of 8.5-9.0 µm. For the sensitive wavelengths of magnesium sulfate, the distribution of sensitive wavelengths is far away from the trough at 9.1 um, except for one near the trough at about 8.9 µm. The emissivity curves of potassium chloride and sodium chloride are similar in shape, with a broad peak between 8.5 and 9.5 µm, but the sensitive wavelengths do not overlap. The sensitive wavelength of potassium chloride is uniformly distributed over the entire thermal infrared band, while the sensitive wavelength of sodium chloride is mainly distributed on both sides of the thermal infrared band.
Since the sensitive wavelengths selected by the CARS method for four minerals in MP overlaps, U-PLSR and M-CARS-PLSR methods are used to establish prediction models for U-CARS-PLSR and M-CARS-PLSR (the input wavelength is the union of the sensitive wavelengths of four minerals, 31 wavelengths), as shown in Figure 11 and 9. 13, 9.53, 9.62, 9.98, 10.17, 11.01 Potassium chloride 11 8.48, 8.72, 8.86, 9.21, 9.53, 9.58, 9.62, 9.66, 10.22, 10.68, 11.07 Magnesium sulfate 11 8.48, 8.51, 8.94, 9.45, 9.62, 9.93, 10.12, 10.42, 10.68, 10.73, 10.84 Sodium chloride 8 8.34, 8.54, 8.58, 9.84, 9.98, 11.01, 11.30, 11.36 Since the sensitive wavelengths selected by the CARS method for four minerals in MP overlaps, U-PLSR and M-CARS-PLSR methods are used to establish prediction models for U-CARS-PLSR and M-CARS-PLSR (the input wavelength is the union of the sensitive wavelengths of four minerals, 31 wavelengths), as shown in Figure 11 and Table 7. In the calibration set, the values of R c 2 and RMSEC of the U-CARS-PLSR model are higher than those of the M-CARS-PLSR for picromerite and potassium chloride, while the results reverse for magnesium sulfate and sodium chloride. In the prediction set, the values of RMSEP and RPD for picromerite are almost the same (RMSEP: 2.72%, 2.78%, and RPD: 4.24, 4.15; RMSEP of sodium chloride: 0.40%, 0.40%, and RPD: 1.37, 1.36), but the results of potassium chloride and magnesium sulfate were significantly different (RMSEP of potassium chloride: 2.86%, 3.16%, and RPD: 4.42, 4.00; RMSEP of magnesium sulfate: 1.45%, 1.29%, and RPD: 1.73, 1.96). Considering that the percentage of magnesium sulfate is much smaller than potassium chloride (standard deviation: potassium chloride, 12.66%; magnesium sulfate: 2.52%), it can be concluded that the performance of U-CARS-PLSR is better than that of M-CARS-PLSR. As Figure 12 shows, four minerals of RPD values of U-PLSR and U-CARS-PLSR are compared: picromerite 4.59, 4.24; potassium chloride, 4.06, 4.42; magnesium sulfate 2.16, 1.73; sodium chloride 1.37, 1.57. The results deduced that the prediction accuracy of U-CARS-PLSR has decreased to a certain extent except for potassium chloride. However, the CARS method reduced the number of selected calculated wavelengths (from 69 to 31 wavelengths), and the RPD values of major minerals in MP samples are both greater than 4.00, indicating that the prediction effect was still acceptable. In other words, CARS have a great role in reducing the cost of TIH technology and then being applied to the production and detection of potassium salt. fate 2.16, 1.73; sodium chloride 1.37, 1.57. The results deduced that the prediction accuracy of U-CARS-PLSR has decreased to a certain extent except for potassium chloride. However, the CARS method reduced the number of selected calculated wavelengths (from 69 to 31 wavelengths), and the RPD values of major minerals in MP samples are both greater than 4.00, indicating that the prediction effect was still acceptable. In other words, CARS have a great role in reducing the cost of TIH technology and then being applied to the production and detection of potassium salt.
Conclusions
To solve the problem of rapid detection in the process of mineral production, this paper introduced the application of TIH technology in the detection of potassium salt samples as an example. The relationship between the potassium salt spectrum and mineral content was constructed, and the potassium salt content was successfully predicted under the PLSR method. The following conclusions are reached: (1) TIH imaging revealed highly prominent emissivity characteristics of the MP samples in the thermal infrared band. Furthermore, the temperature discrepancy between the inverted and actual temperatures of the samples was relatively small, with 71% of the samples exhibiting a temperature difference of less than 1 K. This suggests that the emissivity accuracy of the samples obtained in this experimental process is high and can be approximated as the emissivity spectrum corresponding to potassium salt samples. (2) The CARS-PLSR model, which is based on MP sample emissivity data training, is effective for MP sample prediction. In the U-PLSR model, the RPD values of the four minerals are 4.59, 4.06, 2.16, and 1.57, respectively, indicating that PLSR has a good prediction effect on MP. The calculation results of the U-CARS-PLSR model using the CARS method for sensitive wavelength selection show that the CARS method can effectively reduce the number of wavelengths, which is of great benefit to the practical application of TIH technology. With the CARS method, the number of selected wavelengths for the four minerals is reduced to 12, 11, 11, and 8, with RPD values of 4.24, Figure 12. RPD values of four minerals in U-PLSR and U-PCARS-PLSR models.
Conclusions
To solve the problem of rapid detection in the process of mineral production, this paper introduced the application of TIH technology in the detection of potassium salt samples as an example. The relationship between the potassium salt spectrum and mineral content was constructed, and the potassium salt content was successfully predicted under the PLSR method. The following conclusions are reached: (1) TIH imaging revealed highly prominent emissivity characteristics of the MP samples in the thermal infrared band. Furthermore, the temperature discrepancy between the inverted and actual temperatures of the samples was relatively small, with 71% of the samples exhibiting a temperature difference of less than 1 K. This suggests that the emissivity accuracy of the samples obtained in this experimental process is high and can be approximated as the emissivity spectrum corresponding to potassium salt samples. (2) The CARS-PLSR model, which is based on MP sample emissivity data training, is effective for MP sample prediction. In the U-PLSR model, the RPD values of the four minerals are 4.59, 4.06, 2.16, and 1.57, respectively, indicating that PLSR has a good prediction effect on MP. The calculation results of the U-CARS-PLSR model using the CARS method for sensitive wavelength selection show that the CARS method can effectively reduce the number of wavelengths, which is of great benefit to the practical application of TIH technology. With the CARS method, the number of selected wavelengths for the four minerals is reduced to 12, 11, 11, and 8, with RPD values of 4.24, 4.42, 1.73, and 1.37. The prediction accuracy of major minerals in MP is high (RPD > 4). The model has a good prediction effect on MP.
The study deduces that TIH technology has high accuracy for detecting potassium salts with limited mineral phases. It is reasonable to expect that TIH technology could have potential applications not only in detecting other minerals in production but also in other scenarios where mineral phases are limited, such as in the detection of allotropes.
TIH technology can accurately and rapidly detect mineral phases with limited mineral phases, compared with traditional detection methods. However, it is important to note that in this study, the TIH technology was used to collect data on dry potassium salt samples in a relatively open environment, which may be difficult to replicate under actual production conditions. Therefore, in subsequent studies, two approaches will be taken to address this issue: (1) Construct "shielding conditions" using low emissivity substances to simulate a more realistic environment; (2) Increase the sample size of potassium salt under aqueous conditions and quantitatively investigate the influence of water. These two approaches represent the focal points of follow-up research aimed at bringing the technology closer to practical application.
Data Availability Statement:
The data is unavailable due to privacy restrictions.
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Domain: Agricultural And Food Sciences
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Grape Pomace: Agrifood By-Product with Potential to Enhance Performance, Yolk Quality, Antioxidant Capacity, and Eggshell Ultrastructure in Laying Hens
Simple Summary Grape pomace is an agrifood by-product that is usually thrown away as a waste product, even with its rich content of phytochemicals. The aims of this study were to investigate the effects of dietary inclusion of grape pomace on laying rate, egg quality, yolk lipid profile, oxidative stability, shell quality and ultrastructure, and serum biochemistry in laying hens. Egg production, egg weight, and egg mass were improved due to the addition of grape pomace to the diets of laying hens. A reduction in saturated fatty acids was observed, while monounsaturated fatty acids, polyunsaturated fatty acids, and n-3 fatty acids were increased in the egg yolk of hens fed grape pomace. The dietary inclusion of grape pomace mitigated lipid oxidation and improved the antioxidant capacity of the fresh and stored eggs. The inclusion of grape pomace increased shell weight, thickness, and breaking strength by augmenting the thickness of the palisade layer. To conclude, the dietary inclusion of grape pomace in the diets of layers improved laying performance, enriched the yolk with beneficial fatty acids, augmented the antioxidant potential of yolk lipids, and enhanced shell quality and ultrastructure. Abstract Grape pomace (GP) is an industrial by-product of grape juice making and is commonly discarded as a waste product, even with its large quantity of phytochemicals. Thus, the objectives of this trial were to examine the effects of graded dietary GP on laying rate, egg quality, yolk lipid profile, oxidative stability, shell quality and ultrastructure, and serum biochemistry. Two hundred 35-week-old laying hens were allocated to four dietary treatments with ten replicates each. Four diets were formulated by mixing a standard basal diet with GP at 0 g/kg (control), 30 g/kg (GP3%), 60 g/kg (GP6%), and 90 g/kg (GP9%). Egg production percent, egg weight, and egg mass were linearly improved (p < 0.01) due to adding GP to the diets of laying hens. Eggs obtained from laying hens fed with GP diets had (p < 0.01; linear, p < 0.01) greater Haugh units, yolk color, albumen index, and yolk index than those of the control. The GP9% group had the greatest values (p < 0.05) for shell weight, thickness, and breaking strength. Electron microscopy scanning of eggshells indicated that the incremental dietary level of GP linearly augmented the thickness of the palisade layer but reduced both the mammillary layer and mammillary knob width (p < 0.01). Improved tibia-breaking strength and ash content were shown (p < 0.05) in the GP-fed laying hens. The dietary addition of GP by up to 90 g/kg linearly (p < 0.01) mitigated lipid oxidation and improved the antioxidant capacity in both the serum and stored eggs. A reduction in the percentages of saturated fatty acids was observed, while the contents of monounsaturated fatty acids, polyunsaturated fatty acids, and n-3 fatty acids were augmented because of increasing dietary GP levels (p < 0.001). Additionally, the eggs obtained from laying hens fed on the GP6% and GP9% had lower yolk cholesterol content (p < 0.001); this effect was confirmed by linear and quadratic responses (p < 0.001). Laying hens on GP diets had lower (p < 0.01) serum hepatic enzymes, cholesterol, triglycerides, and low-density lipoprotein but greater high-density lipoprotein compared to the control. To sum up, the addition of GP in the layers’ diets by up to 90 g/kg increased laying performance, enriched the yolk with beneficial fatty acids, enhanced antioxidant potential in yolk lipids, and improved shell quality and ultrastructure.
Introduction
Over the last decade, the continual growth of the human population has raised the requirement for poultry products worldwide, including meat and eggs [1]. Human consumption of hen eggs is progressively rising worldwide, with a rise of 14.1% per capita from 2010 to 2019 [2]. At the same time, the cost of feed ingredients, particularly protein sources and cereal grains, has increased. Feed ingredients present the greatest percentage of animal production costs, and thus observing sustainable and cost-effective practical alternative feedstuffs to replace traditional feedstuffs is very imperative [3]. Agro-industrial by-products are an extraordinary substitution option because these products are produced in considerable quantities yearly, predominantly from the juice and winery industries, causing a great challenge for waste disposal and management [3,4]. Likewise, with their accessibility and low price, these by-products are a valuable source of nutritional components such as fiber, minerals, vitamins, polyphenols, and flavonoids.
Eggs are a useful functional food owing to their constituents of essential amino acids, minerals, vitamins, and bioactive components [5][6][7]. Accordingly, adequate egg intake has been proven to induce health benefits in humans. Still, the nutritional value of the eggs can be improved by enriching them with polyunsaturated fatty acids (PUFA), which have been proven to be associated with a lower prevalence of human health-metabolic problems [8][9][10]. However, the eggs enriched with PUFA are more susceptible to lipid oxidation and deterioration, subsequently shortening the shelf-life of the eggs [11,12]. Lipid oxidation in eggs has conventionally been mitigated with the addition of antioxidant supplements, for instance vitamin E and canthaxanthin, to the diets of laying hens [11]. Despite this, natural alternative components with antioxidant activities can be added to the diets of laying hens to augment the egg's oxidative stability, such as phenolic and flavonoid compounds [12]. However, the application of these extracted components from natural phytogenic plants is believed to be impractical because of the expensive extraction protocols.
Grape pomace (GP) is an industrial by-product of grape juice making and is commonly thrown away in landfills as a waste product, even with its large quantity of phytochemicals [13]. GP disposal can induce environmental pollution; accordingly, unconventional utilizations of GP are required to smooth the appropriate management and use of this by-product [14]. GP consisted of seedless pomace (residual pulp, stem, and skin, approximately 48-62%) and seeds (about 38-52%) [13]. GP is a good source of fundamental bioactive compounds with antioxidant, antibacterial, growth-stimulant, and improved meat quality [5]. Indeed, polyphenols present in grapes, particularly catechins, resveratrol, luteolin, quercetin, kaempferol, and anthocyanins, have been recognized to mitigate the scavenging capacity of free radicals and inhibit oxidation activities [13]. Consequently, its inclusion in poultry diets can beneficially lessen waste disposal, while generating healthier poultry products. Nevertheless, the GP contents of tannins and structural carbohydrates may hinder their nutrient digestibility and utilization by birds [15,16]. Previous studies have shown that dietary supplementation with grape by-products, such as GP, seeds, and grape skins, was efficient in decreasing the meat's lipid peroxidation without impairing growth performance in broiler chickens [13,[15][16][17]. As far as we know, few studies are currently available about the dietary supplementation of GP in layers and its impact on egg quality traits [11,[18][19][20]. These research reports revealed that GPs recommended dietary inclusion rate in poultry ranges from 15 to 60 g/kg [13,15,[17][18][19][20].
To our knowledge, there is a scarcity of research assessing the effect of graded dietary GP on laying rate, yolk lipid peroxidation, fatty acid (FA) profile, shell ultrastructure, and egg shelf-life in laying hens. Therefore, we aimed to explore the effects of graded inclusion of GP in the diets of laying hens on laying performance, egg quality traits, egg yolk lipid oxidation, yolk FA profile, shell quality and ultrastructure, and egg shelf-life. These aims can attribute importance to saving conventional feedstuffs, enriching the research on the nutrition of laying hens, bridging the research gap in GP in poultry, and encouraging the advancement of an environmentally friendly economy. Our hypothesis was that the dietary inclusion of GP could modify the laying rate, egg quality, antioxidant capacity, and shell ultrastructure.
Materials and Methods
The current trial was performed under a protocol accepted by the Institutional Animal Care and Use Committee with oversight by the Faculty of Veterinary Medicine, Sadat City University, Egypt. The ethical approval number is VUSC-021-1-23.
Grape Pomace Analysis
GP originating from red grapes (Vitis vinifera) was collected from the Paste and Juice Company (P & J), Sadat City, Egypt. The proximate chemical composition of GP was performed following AOAC protocols [21]. Dietary phytate phosphorus was measured [22], and available phosphorus was calculated as total phosphorus minus phytate phosphorus. The metabolizable energy of GP has been obtained from the Egyptian Central Laboratory for Food and Feed (Tables of feed composition 2001, Bulletin no. 1,8). Neutral detergent fiber (NDF) and acid detergent fiber (ADF) in GP were measured as described by Van-Soest et al. [23]. Total phenolic content was determined by the Folin-Ciocalteau reagent as described by Al-Farsi et al. [24]. Total flavonoid content was performed according to the methods of Kim et al. [25]. Phenolic acids in GP were measured by high-performance liquid chromatographic (HPLC) using the method of Mattila et al. [26]. The proximate analysis, total phenolic, total flavonoid, phenolic acids, and FA profiles of GP are shown in Table 1.
Trial Design, Diets, and Bird Management
The current study consisted of an eight-week trial designed with four dietary treatments with 10 replicates each in a completely randomized design. Two hundred 35-weekold Lohman Brown Lite laying hens with an initial body weight of 1823 ± 30 g were used. Laying hens were retained in cages (0.44 m × 0.30 m × 0.45 m) offered with nipple drinkers and trough feeders. The birds were vaccinated and managed according to the breeder standards. The light schedule was 16 h light and 8 h darkness daily, and the temperature in the laying hens' house was 24 ± 3 • C during the trial. Feed, which was available in mash form, and water were kept on an ad libitum basis during the trial period. The dietary treatments were as follows: (1) the control diet (no GP, control); (2) a basal diet containing 3% GP (GP 3% ); (3) a basal diet containing 6% GP (GP 6% ); and (4) a basal diet containing 9% GP (GP 9% ). Diets were prepared to be isocaloric and isonitrogenous and to meet the nutrient requirements of the breeders. Experimental diets are shown in Table 2.
Production Performance and Egg Quality
The initial body weight of laying hens before the start of the experiment (35 weeks of age) and the final body weight (43 weeks of age) were recorded. Feed intake (FI) by hens was recorded weekly and then divided by the number of hens per replicate and by 7 to report the daily FI per laying hen. The laying rate and egg weights were determined weekly during the experiment. Egg mass was estimated by multiplying egg weight with laying rate, and the feed conversion ratio (FCR) was documented as g of FI divided by g of egg mass. Egg quality parameters, including albumen and yolk weights, albumen height, yolk height, Haugh unit, specific gravity, shell thickness, and yolk color score, were determined in 60 eggs obtained from each replicate during the last 3 days of week 8 of the experiment. Shell thickness was assessed by micrometer after the removal of shell membranes, and the average value of 3 locations on the egg (at the 2 poles and the middle) was documented. Albumen and yolk heights were measured by a standard tripod micrometer, and the yolk diameter was determined by a caliper. Egg shape index (%), egg yolk index (%), and egg yolk albumen index (%) were accomplished by determining egg width and length using a caliper. Measuring the egg yolk color of freshly laid eggs was performed by the Roche yolk color fan. Haugh units were calculated using the formula described in [27].
Egg Yolk Lipid Profile, Oxidation Stability, and Fatty Acid Composition
On the 2nd day of the last week of the experiment (43 weeks old), 30 freshly laid eggs were obtained from each group (a total of 120 eggs) to assess the egg yolk cholesterol and triglyceride concentrations. The eggs were broken, and the yolks were pooled and separated from the egg white. Yolk cholesterol (mg/g) and triglyceride (mg/g) contents were determined spectrophotometrically using an ultraviolet spectrophotometer UV4802 (Unico Co., Dayton, OH, USA) and commercial kits (Sigma-Aldrich, St. Louis, MO, USA) based on the methods of Hammad et al. [28] and Kaya et al. [29]. On the 3rd day of the last week of the experiment, 10 freshly laid eggs were gathered from each group. The MDA was estimated on the day of egg collection. Moreover, another 30 freshly laid eggs were obtained per group and stored at 4 • C for 25 and 45 days. After the storage time, these eggs were broken and the yolks pooled, then MDA and GPx values were measured to evaluate the degree of yolk lipid peroxidation according to Botsoglou et al. [30], Galobart et al. [31], and Paglia and Valentine [32]. On the 4th day of the last week of the study, 20 freshly laid eggs were obtained from each group and broken, and the yolk was separated from the egg albumen. Then, the collected yolks were pooled and then frozen at −20 • C, freeze-dried, and later used for the measurement of the yolk FA composition using the protocol explained by Yang et al. [33] with a gas chromatograph (Model GC-14A, Shimadzu Corporation, Kyoto, Japan). The FA percentage was calculated as a percent of the total FA in the egg yolk.
Tibia Physical Traits and Chemical Composition
To determine the tibia bone, 10 hens from each group (1 bird/replicate) with the same homogeneity were chosen and euthanized at the end of the trial to gather tibia bones. Meat and other adhering tissue were removed from the tibia. The weight of the tibia (g) was determined by a decimal digital scale, and the tibia's length and width (mm) were measured by a digital micrometer. Tibia-breaking strength was performed and expressed as kilograms' force according to the method of Flemming et al. [34]. The tibia bones were crushed and dried in a hot air oven for 24 h at 105 • C. The samples were defatted by the Soxhlet method using petroleum ether and then dried at 100 • C for 24 h. The dried fat-free tibia was ignited in a muffle furnace at 600 • C overnight, and tibia ash content was represented as a percent of the fat-free dry basis.
Electron Microscope Scanning of Eggshell Ultrastructure
At the end of week 8 of the trial, one egg was randomly collected from each replicate (10 eggs/treatment). Before SEM imaging, the eggs were broken, then the eggshells were washed with distilled water to remove any dirt and dried at room temperature for 48 h [34]. Samples of eggshells (0.5-1 cm 2 ) were arranged for scanning electron microscope analysis. One sample was used to assess the cross-section of the eggshell, and the other was set to evaluate the external surface. Samples were mounted on aluminum stubs, coated with gold in an SPI-Module ™ Vac/Sputter, and then photographed using an electron microscope (JEOL, JSM-5200 LV scanning electron microscope, Japan) at an electron microscope unit at Tanta University, Egypt. The photos were taken to analyze the cross-section of the eggshell at ×100 magnification, and the others were used to assess the external surface of the eggshell at ×35 magnification. The palisade layer thickness (µm), mammillary layer thickness (µm), and total thickness (palisade and mammillary, µm) were determined following Stefanello et al. [35] using Image J software version 1.53t.
Serum Biochemistry
At the end of the trial (43 weeks of age), blood samples were obtained from the wing vein of laying hens (20 samples per treatment) for assessing serum metabolites. Serum was taken by centrifugation at 3000 rpm for 5 min and stored at −20 • C till further analysis. The serum samples were analyzed spectrophotometrically (spectrophotometer UV4802, Unico Co., Dayton, OH, USA) using commercial kits (Bio-diagnostic Co., Cairo, Egypt) for measuring total protein, albumin, total lipids, triglycerides, cholesterol, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels. Serum MDA [36] and GPx [37] levels were measured spectrophotometrically using commercial kits (Biodiagnostic Co., Cairo, Egypt).
Statistical Analysis
The normality of the data was checked by Kolmogorov-Smirnov and Levene's tests. Data were analyzed by One-way ANOVA using IBM SPSS software version 21, and Tukey's test determined significant variations between the treatment groups (p < 0.05). The experimental unit was the replicate for production data and the bird for other measurements. Furthermore, the incremental levels of GP in the diets of laying hens were assessed by orthogonal polynomial contrasts, and the p-value was documented. All values are presented as mean ± SEM.
Laying Performance
The initial body weight (BW) and final BW of laying hens did not differ among the treatment groups (Table 3). Egg production percent during the study period (from week 35 to week 43 of age) was significantly enhanced (p = 0.007) due to feeding GP in layers' diets; this pattern was confirmed by a linear response (p < 0.01) ( Table 3). In hens fed the GP diets, there were significant increases (p < 0.01) in egg weight and egg mass compared to those fed the control diets; this effect was indicated by a linear response only (p < 0.001) ( Table 3). The largest egg weight and egg mass were observed in the laying hens fed the GP 9% diet. Hens fed the GP 6% and GP 9% had lower FI (p < 0.01; linear, p < 0.001; quadratic, p < 0.05) during the trial period (from week 35 to week 43 of age) compared to the control (Table 3). On the contrary, the feed conversion ratio (FCR) was enhanced (p < 0.001) in all the GP-fed groups compared to the control; this response was implied by linear (p < 0.001) and quadratic (p < 0.05) responses (Table 3).
Egg Yolk and Albumen Quality
Dietary modification with GP resulted in greater yolk color scores (p < 0.001; linear, p < 0.001; quadratic, p < 0.01; cubic, p < 0.05) concerning the values recorded in the eggs of the control hens ( Table 4). The GP-fed hens had a lower yolk weight % (p < 0.01) but a higher albumen weight % (p < 0.01) than the control hens ( Table 4). As recorded in Table 4, the indexes of egg yolk and albumen were significantly increased (p < 0.001) in the GP-fed hens as compared to the control ones. The dietary inclusion of GP resulted in a linear increase (p < 0.01) in the Haugh unit, particularly at 90 g/kg, as compared with the control group (Table 4). However, a non-significant effect (p > 0.05) was noticed among treatments for the yolk and albumen pH values (Table 4). Table 5 shows that egg yolk SFA contents linearly (p < 0.001) and quadratically (p < 0.05) decreased in response to GP levels. Laying hens on the GP 9% diets had the lowest yolk SFA contents compared to other treatment groups. On the other hand, laying hens on the control diets had lower egg yolk MUFA (p < 0.001) and PUFA (p < 0.001) con-centrations compared to those on the GP diets (Table 5). Similarly, control diets prompted lower (p < 0.001) n-6 FA than GP diets (linear, p < 0.001, quadratic, p < 0.01; cubic, p < 0.001). Laying hens on the GP diets had greater egg yolk n-3 FA contents compared to those on the control diets; this effect was supported by linear, quadratic, and cubic responses (p < 0.05). The GP 9% group prompted the greatest level of yolk n-3 FA and the lowest n6:n3 FA ratio compared to the other treatment groups (Table 5). Dietary inclusion of GP linearly, quadratically, and cubically (p < 0.05) decreased the ratio of SFA to either PUFA or MUFA (control vs. GP, p< 0.001) in the egg yolk compared to the control diet. Furthermore, the eggs obtained from laying hens fed on the GP 6% and GP 9% had lower yolk cholesterol concentrations (p < 0.001) compared to those obtained from the control and GP 3% groups; this response was confirmed by linear and quadratic effects (p < 0.001). Eggs obtained from all GP-laying hens had a lower yolk triglyceride concentration (p < 0.001) ( Table 5). Table 6 presents the effect of the experimental diets on yolk oxidative stability during storage. There were significant dietary effects on GPx, where freshly laid eggs from laying hens in diet GP 6% and GP 9% had greater yolk GPx contents (p < 0.001) than those from diet control. However, the control diet promoted a similar (p > 0.05) yolk GPx level as diet GP 3% . Similarly, after 25 and 45 days of storage, the eggs from the GP 6% and GP 9% groups had higher (p < 0.01) egg yolk GPx contents; this effect was characterized by a linear response (p < 0.01). Regarding the yolk MDA concentrations of freshly laid eggs, there were non-significant differences among the experimental groups. However, after storage for 25 days, the GP 6% and GP 9% eggs had lower yolk MDA levels (p < 0.001; linear, p < 0.001) when compared to the control and GP 3% ones. For extended storage duration (45 days), all GP groups prompted lower levels of MDA in egg yolk (p < 0.001; linear, p < 0.001; quadratic, p < 0.01) compared to the control group.
Tibia Physical Traits and Chemical Composition
Data on tibia physical morphology and chemical composition are presented in Table 7. Dietary modification with GP significantly did not induce any variations in the weight, length, or width of the tibia. Tibia bone dry matter % did not differ among the four treatments. The present results showed that the tibia bone-breaking strength (p < 0.001) and ash percent (p < 0.05) significantly increased and correlated with increasing GP levels (linear, p < 0.01). Table 8 shows that shell weight percentage, thickness, and breaking strength were linearly improved (p < 0.01) in response to the increased dietary levels of GP. The GP 9% group had the greatest values for shell weight, thickness, and breaking strength (Table 8). Data on the eggshell ultrastructure of laying hens at the end of the trial (43 weeks of age) by scanning electron microscopy are presented in Table 8 and Figure 1a,b. The eggshell is a smooth, hard, calcareous structure that is firmly attached to the outer shell membrane. The mineral crystals on the surface form many tiny pores in the bird's eggshell. The eggshell is formed from an inner layer called the testa and an outer layer called the cuticle. The testa is composed of an organic network of delicate protein fibers and an inorganic interstitial substance of inorganic salts, mainly calcium carbonate. The cuticle is an organic outer layer of eggshell that is composed of a protein matrix lined with mineral crystals, usually calcium carbonate. Most of the eggshell is composed of calcium carbonate crystals (approximately 95%). The mammillary layer is a thin layer of spherolithic calcite crystal aggregates acting as overturned cones, which join to make a compact palisade layer. The palisade layer is the thickest part of the eggshell and combines with the outermost crystalline layer, which is protected by a cuticle. The cuticle contains hydroxyapatite crystals and most of the pigment. The entire eggshell is porous, and pore channels appear between the mammillary cones, spreading radially across the palisade and reaching the exterior. Thus, these channels penetrate all levels of the eggshell, enabling the exchange of water and metabolic gases. The incremental level of GP had linear and quadratic effects (p < 0.01) on the palisade layer thickness compared to the control; the highest thickness was observed in the GP9% eggshell. There was non-significant variation in the mammillary layer thickness among the experimental group (Figure 1). Lower mammillary thickness % was observed in the GP 9% compared to other treatment groups (p < 0.01). Lower mammillary knob width was recognized in the GP-added groups, particularly GP 6% and GP 9% , compared to the control; this effect was characterized by a linear response (p < 0.01).
Serum Biochemistry
Data on serum biochemical constituents are shown in Table 9. Serum total protein and albumin concentrations were linearly (p < 0.001) and cubically (p < 0.05) increased in the GP-fed groups compared to the control ones; the effect was more pronounced for the GP 6% and GP 9% hens (p < 0.001). There was a non-significant difference in serum globulin content among the treatment groups. Laying hens fed the GP diets had lower (p < 0.01) serum total cholesterol, triglycerides, and LDL levels, particularly in the GP 6% and GP 9% hens, than the control (linear, p < 0.001). In contrast, the GP-fed hens had a higher serum HDL concentration than the control group (linear, quadratic, and cubic, p < 0.001). The ALT and AST concentrations were linearly decreased in the serum of laying hens fed the GP diets when compared to those fed the control diet. The GP-fed hens had significantly greater serum levels of GPx (p < 0.001; linear, p < 0.001; cubic, p < 0.001) and lower levels of MDA (p < 0.001; linear, p < 0.001) than the control hens. Table 9. Effect of experimental diets on the blood biochemistry of laying hens (43-week-old).
Treatments
Significance, p-Value (a)
Serum Biochemistry
Data on serum biochemical constituents are shown in Table 9. Serum total protein and albumin concentrations were linearly (p < 0.001) and cubically (p < 0.05) increased in the GP-fed groups compared to the control ones; the effect was more pronounced for the GP6% and GP9% hens (p < 0.001). There was a non-significant difference in serum globulin content among the treatment groups. Laying hens fed the GP diets had lower (p < 0.01) serum total cholesterol, triglycerides, and LDL levels, particularly in the GP6% and GP9% hens, than the control (linear, p < 0.001). In contrast, the GP-fed hens had a higher serum HDL concentration than the control group (linear, quadratic, and cubic, p < 0.001). The ALT and AST concentrations were linearly decreased in the serum of laying hens fed the
Discussion
Grape pomace can possibly be used as a practical feedstuff in poultry nutrition owing to its rich bioactive components (phenolic acids and flavonoids) with favorable antioxidant and antimicrobial activities [13,15]. Nonetheless, the structural carbohydrates and phenolic components present in GP may constrain its utilization in poultry diets [11,20,38]. At the same time, there is a dearth of research investigating the effect of graded dietary GP on laying performance, yolk quality, shell ultrastructure, and egg shelf-life in laying hens. Considering this, it is important to examine the maximum dietary inclusion level of GP to optimize the laying rate, egg quality, antioxidant ability, and health status of layers.
In the current trial, the BW and BW gain of laying hens fed GP, particularly the GP6% and GP9% groups, were increased compared to the control. Similarly, egg production percent, egg weight, and egg mass were also enhanced due to adding GP to the diets of laying hens. Indeed, these enhancements were obvious after 4 weeks of feeding GP diets. Romero et al. [11], Reis et al. [18], and Kara et al. [38] recorded that dietary inclusion of GP at a level of 2% to 6% did not influence the laying rate. Reports on the dietary supplementation of GP in layers are quite scant. The inclusion of GP at 6% and 9% in the diets of laying hens enhanced egg production and egg weight in the current study, which can contribute to the enhancive effect of GP on intestinal probiotic microbiota [39]. Furthermore, the vitellogenin properties of quercetin may have been attributed to the enhanced egg production, egg weight, and egg mass noticed in the current trial. Flavonoids, such as quercetin (a phytoestrogen constituent), induce agonistic and antagonistic effects based on the internal estrogen level [40,41]. Estradiol passively assists the release and function of other reproductive hormones, including FSH, in mature hens [40][41][42]. Thus, the flavonoids present in GP may exhibit estrogenic and vitellogenin activities to improve the laying rate [40,41]. Our results are partially in harmony with Kara et al. [38], who observed that supplementing laying hens' diets with 40 to 60 g of GP/kg of feed increased egg weight without affecting egg production. It is also essential to highlight that the use of GP flour by up to 3% in the diet of laying hens increased egg production, egg weight, and egg mass compared to the control. The inconsistent results may be attributed to different inclusion levels, grape species, diet composition, age, GP polyphenol content, and the length of the trial.
Hens fed the GP 6% and GP 9% diets had lower FI during the trial period (from week 35 to week 43 of age), but FCR was improved in all the GP-fed groups compared to the control. Considering that the dietary inclusion of GP significantly improved egg production, the reduction in FI caused an improvement in the FCR of hens fed the GP diets. These findings may indicate that feed nutrients were utilized more efficiently, as observed from the enhanced FCR. On the other hand, the reduced feed consumption may be attributed to the low acceptance of GP by hens, the elevated dietary crude fiber, NDF, and ADF contents, and anti-nutritional constituents, such as tannins and pectin. The GP diets had greater crude fiber contents (3.37%, 3.81%, and 4.25% for GP 3% , GP 6% , and GP 9% , respectively) than the control diet (2.90%). However, additional research is needed to reveal the GP component(s) that may be accountable for the low acceptance of GP by hens. In quails, Silici et al. [43] observed an improvement in the feed conversion efficiency of birds fed grape seeds. Consistent with our findings, Romero et al. [11] and Kara et al. [38] showed that supplementing layers' diets with GP decreased FI while improving FCR. Adding GP over 6% may decrease FI [44] and fat digestion [41] in broiler chickens. Overall, these results provide additional provision for the use of GP by up to 9% in the diet of laying hens without inducing detrimental effects on laying performance.
Eggs obtained from laying hens fed with GP diets linearly improved Haugh units, yolk color, albumen index, and yolk index with increased GP levels compared to the control, which can be a positive effect of supplementation, since these parameters reflect internal egg quality [18,45]. Little information exists about the impact of supplementing grape by-products on yolk color and Haugh units in layers. Our findings are in harmony with Romero et al. [11], who observed that supplementing laying hens' diets with GP increased egg yolk color score and Haugh units. Similarly, Fróes et al. [46] reported a positive quadratic correlation between yolk coloration and dietary GP concentrations. Moreover, Haugh units were linearly improved by the addition of grape seeds and grape seed extract [19]. Amevor et al. [41] showed that dietary quercetin supplementation enhanced egg quality traits, including yolk index, albumen index, yolk color, Haugh unit, and eggshell thickness. Grapes are considered a natural source of β-carotene and lutein [44], which are frequently used as pigmenting ingredients in Europe to accomplish the most favorable yolk pigmentation anticipated by people [31]. Pigment deposition in egg yolk is determined by its dietary levels and the capability of the hen to digest, absorb, and metabolize it [46]. The improvement in the Haugh unit and yolk color score can be attributed to the flavonoid content of GP. Therefore, the dietary inclusion of GP could be attributed to somewhat reducing the dietary supplementation of synthetic pigments [11,46].
The antioxidant effects of GP, grape seed, and their extracts have been the topic of research, with the emphasis that these products have a high possibility of improving the shelf-life of animal products by mitigating lipid peroxidation [11,13,14,38,45,[47][48][49]. In the present study, it was noticed that the dietary inclusion of GP by up to 90 g/kg mitigated lipid oxidation and improved the antioxidant capacity in serum, freshly laid eggs, and stored eggs. The serum and egg yolk of the GP treatments showed a lower MDA concentration and greater GPx levels than those of the control. Similarly, a reduction in lipid oxidation and enhanced antioxidant capacity were shown in the plasma and egg yolk of laying hens fed with GP [11,18,38]. It was reported that dietary resveratrol linearly decreased the egg yolk MDA concentration of quail-fed diets containing this polyphenol, which is found in red grapes and has antioxidant activity [48]. The antioxidant properties of GP and grape seed may be attributed to the phenolic compounds, which are able to scavenge free radicals, form complexes with metal ions, and hinder or lessen the formation of singlet oxygen [49][50][51]. It was revealed that GP supplementation by up to 1% of the diet was capable of lessening lipid peroxidation in the breast meat of broiler chickens [52]. It is suggested that anthocyanins found in GP may be considered potent antioxidants against lipid peroxidation in tissues by reducing free radicals [51].
The egg yolk fatty acid composition was altered in response to the dietary addition of GP. Specifically, the dietary inclusion of GP at 90 g/kg induced a reduction in the proportions of SFA, while the proportions of MUFA and PUFA improved. The GP9% egg yolk prompted the greatest level of n-3 FA and the lowest n-6 to n-3 FA ratio. Similarly, Romero et al. [11] observed that dietary inclusion of GP at 60 g/kg caused a reduction in the SFA and MUFA contents, but the PUFA content was enhanced. Dietary supplementation of 20 g/kg GP resulted in an increase in the proportion of egg yolk α-linolenic acid and a decrease in that of oleic acid and elaidic acid in quails [52]. Additionally, feeding laying hens a diet containing 30 g/kg of grape seed meal permitted a decrease in yolk contents of SFA and MUFA, while it boosted the content of PUFA [53]. Reis et al. [18] showed that dietary supplementation with GP flour by up to 3% did not affect SFA nor PUFA in egg yolk, but it increased yolk MUFA concentration. These modifications in the egg yolk FA profile of the current study could switch traditional eggs into functional foods since the obtained FA profile could prompt health benefits in humans. These changes in the egg yolk FA profile are desirable, and they can be related to the mitigation of lipid peroxidation and enhanced antioxidant capacity in the egg since lipid oxidation affects the FA profile [18]. Indeed, laying hens directly deposit the ingested dietary lipids into the egg yolk [54]. Thus, the alteration in the yolk FA proportions of laying hens fed diets including GP can be attributed to the different FA provided by GP [11,18], and it may be an associated effect with the dietary incremental levels of vegetable oil. In the research by Çelik et al. [55], the egg yolk FA profile was modified in laying hens that received grape seed oil rather than flaxseed oil. Further research is needed to highlight the mechanism of action beneath this modification in the yolk FA profile in response to dietary GP.
The improved strength of eggshells is an advantageous trait that has economic value in the commercial laying sector. It was observed that shell weight, thickness, and breaking strength were linearly improved in response to the increased dietary levels of GP. The GP9% group had the greatest values for shell weight, thickness, and breaking strength. In support of our findings, we performed scanning electron microscopy of the eggshell, and we found that the incremental dietary level of GP increased the thickness of the palisade layer but decreased both the mammillary layer and mammillary knob width compared to the control. To our knowledge, this is the first report on the effect of feeding GP on the eggshell ultrastructure. Previous studies have demonstrated that eggshell ultrastructure is an important determinant of eggshell quality [56,57]. The enhanced eggshell strength in the current trial because of feeding GP was mainly attributed to lower mammillary thickness as well as increased effective thickness and reduced width of mammillary knobs [35,58]. It was stated that the thickness of the palisade layer and the thickness and width of knobs in the mammillary layer have key roles in breaking strength [35,56,57]. The increased eggshell thickness and strength were mainly a result of the increased effective thickness due to improved calcium utilization. Previous studies have reported that flavonoids enhance eggshell thickness through the regulation of calcium metabolism through their estrogenlike effects [40,59]. However, further studies are required to confirm this mechanism of action. There is currently no research recorded on the effects of GP on the eggshell strength and ultrastructure to compare with the findings recorded herein. This study improved the tibia-breaking strength and ash content in the GP-fed laying hens compared to the control. It seems that polyphenols in GP may enhance calcium absorption and utilization, resulting in an improvement in tibia health. It has been reported that feeding grape products (rich in polyphenols) to ovariectomized rats improved calcium utilization and diminished bone turnover, causing an enhancement in bone health (greater bone calcium retention, cortical thickness, and breaking strength) [55]. Moreover, Hassan et al. [60] observed a strong relationship between an increase in osteocalcin and a rise in blood calcium after the consumption of quercetin, which may indicate an adjustment in bone mineralization [61].
Serum biochemistry is a reliable, practical approach commonly applied to monitor any alteration in response to nutrition or diseases in poultry. In this study, the dietary inclusion of GP decreased serum levels of liver enzymes (ALT and AST) within normal values, demonstrating that feeding GP did not detrimentally affect the hepatic function of hens. Laying hens on GP diets had lower serum cholesterol, triglycerides, and LDL but higher HDL compared to controls. In line with our findings, Khodayari and Shahriar [62] recorded a decrease in plasma cholesterol and triglyceride concentrations in broiler chickens fed diets with Red GP. In contrast, Kara et al. [38] and Reis et al. [18] did not observe any alteration in blood cholesterol levels in birds fed diets containing GP. The current trial obviously indicated that GP reduced yolk cholesterol concentrations. Sun et al. [39] showed that egg yolk cholesterol content was significantly decreased by diets supplemented with grape seed extract. It is well documented that eggs are an excellent source of protein and beneficial nutrients for humans [5][6][7]. However, the elevated cholesterol content is a main limiting factor for the provision of yolk because higher consumption of cholesterol was associated with an increased risk of coronary heart disease [63]. In this study, the decrease in serum and yolk cholesterol contents could be explained by the reduced absorption or synthesis of cholesterol in the intestinal tract and the enhanced bile acid excretion [39]. Polyphenols from grape seeds have been shown to inhibit HMG-CoA synthesis, the key enzyme in cholesterol synthesis, in hens and thus reduce blood and egg cholesterol [39]. Furthermore, the fiber in GP was expected to reduce blood cholesterol levels via the absorption of bile acids and different lipids [13].
Conclusions
Modification of laying hens' diets with GP by up to 90 g/kg did not induce any detrimental effects on laying performance or egg quality traits; however, it enriched egg yolk with beneficial FA such as n-3 FA, reduced yolk cholesterol level, improved yolk color and Haugh units, and extended the egg shelf-life during storage. Moreover, the dietary inclusion of GP increased shell thickness and strength by increasing the thickness of the palisade layer while decreasing both the mammillary layer and mammillary knob width. To sum up, the inclusion of GP in the diet of laying hens by up to 90 g/kg improved laying performance, yolk quality, antioxidant status, shell quality, and shell ultrastructure without affecting laying hen health status. Informed Consent Statement: Not applicable.
Data Availability Statement:
The data presented in this study are available on request from the corresponding author.
Conflicts of Interest:
The authors declare no conflict of interest.
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Domain: Agricultural And Food Sciences
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Study on soil hydraulic properties of slope farmlands with different degrees of erosion degradation in a typical black soil region
In order to explore the impact of soil erosion degradation on soil hydraulic properties of slope farmland in a typical black soil region, typical black soils with three degrees of erosion degradation (light, moderate and heavy) were selected as the research objects. The saturated hydraulic conductivity, water holding capacity and water supply capacity of the soils were analyzed, as well as their correlations with soil physicochemical properties. The results showed that the saturated hydraulic conductivity of black soils in slope farmlands decreased with erosion degradation degree, which was higher in 0–10 cm soil layer than in 10–20 cm soil layer. The water holding capacity and water supplying capacity of typical black soils also decreased with the increase of erosion degradation degree, and both of them were stronger in the upper soil than in the lower soil. With the aggravation of erosion degradation of black soils, soil organic matter content decreased while soil bulk density increased, leading to the decline of soil hydraulic conductivity. The increase of soil bulk density and the decrease of contents of organic matter and >0.25 mm water stable aggregates were the main factors leading to the decrease of soil water holding capacity. These findings provide scientific basis and basic data for rational utilization of soil water, improvement of land productivity and prevention of soil erosion.
INTRODUCTION
Soil hydraulic properties can usually be characterized by soil infiltration performance, soil water characteristic curve and soil water content, which are the basis for evaluating soil water conservation (Huo et al., 2018). Soil saturated hydraulic conductivity (Ks) affects surface water infiltration and runoff and sediment yield (Fares, Aiva & Nkedi-Kizza, 2000;Masís-Meléndez et al., 2014;Wu et al., 2016), which is an important parameter reflecting soil infiltration performance. The higher the saturated hydraulic conductivity, the better the soil infiltration performance. Increasing soil saturated hydraulic conductivity can delay surface runoff caused by precipitation, thus reducing soil erosion. Soil water characteristic erosion and degradation degrees (light, moderate and heavy erosion) in northeast China as the research objects, by determining soil saturated hydraulic conductivity, water holding capacity and water supply capacity, and analyzing their correlations with soil physicochemical properties, to clarify the influence mechanism of black soil erosion and degradation on soil hydraulic properties. We hypothesized that: (1) With the aggravation of soil erosion degradation, soil saturated hydraulic conductivity, water holding capacity and water supply capacity reduce continuously; (2) The aggravation of soil erosion degradation affects soil hydraulic properties mainly through decreasing soil organic matter content and affecting soil texture.
MATERIALS AND METHODS
The study area The study region located in Keshan Experimental Station of Heilongjiang Province Hydraulic Research Institute (125 49′42″E, 48 3′33″N) in Keshan County, Qiqihar City, Heilongjiang Province, China (Fig. 1). The landform of this area is overflowing with rivers and hills, with gentle and long slopes, and hilly terrain accounts for 80% of the total area. It is influenced by cold temperate continental monsoon climate. The annual average temperature is 2.4 C, the frost-free period is about 122 days, and the annual average precipitation is about 500 mm. More than 70% of the rainfall is concentrated between June and September, and the rain and heat are in the same period. The main soil type in this area is typical black soils, and topsoil depth is about 20 cm. The cropping system is one crop a year, soybean and corn rotation.
Selection of sampling plots
Slope farmlands in a back soil region have suffered from soil erosion, which leads to thinning of black soil layer, decrease of soil nutrients and crop yield (He & Xiao, 2022;Liu & Yan, 2009). It has been reported that soil erosion intensity of slope farmlands in black soil region can be categorized according to slope degree (Han & Guo, 2017;Yang, Wang & Xie, 2009). In our study, we further calculated soil loss speed and erosion modulus based on slope degree (Kang, Liu & Liu, 2017;Yan & Tang, 2005), and also investigated black soil layer thickness and crop yield (Wang, Liu & Wang, 2009;Zhang & Liu, 2020), to define soil erosion degree of slope farmlands in the black soil region. Finally, we selected three sampling sites with different degrees of erosion degradation (light, moderate and heavy erosion), based on the comprehensive consideration of slope degree, black soil layer thickness, crop yield, soil loss speed and erosion modulus. The detailed information of the three sampling sites can be seen in Table 1, and the location of these sites can be seen in Fig. 1.
Soil sampling
Field experiments were approved by the Heilongjiang Province Hydraulic Research Institute (12230000414003295L) and after we obtained oral permission from the administrator (Mr. Xujun Liu, the head of Keshan Experimental Station of Heilongjiang Province Hydraulic Research Institute), we collected the soil samples in June of 2022. Soil samples were collected from the lightly, moderately and seriously eroded plots. Three sampling quadrats were randomly selected from each sample plot. In each quadrat, soil samples were collected from 0-10 and 10-20 cm soil layers, respectively, by plum blossom five-point sampling method. Undisturbed soil samples and cutting ring soil samples were also collected from the two soil layers.
Soil properties determination
Soil bulk density was measured by the cutting ring method (Blake & Hartge, 1986). The mechanical composition of soil was measured by the pipette method (Day, 1965). Soil water-stable aggregates were determined by the wet sieve method (ISSAS, 1978). Soil organic matter content was determined by potassium dichromate external heating method (Kononova, 1961). Soil total nitrogen content was determined by the semi-micro Kjeldahl method (Bremner, 1960). Soil available phosphorus was extracted by 0.5 mol/L sodium bicarbonate solution and the concentration in extracts was determined by molybdenum antimony colorimetry method (Olsen et al., 1954). Soil available potassium was extracted by ammonium acetate and the concentration in extracts was determined by flame spectrophotometry method (Pansu & Gautheyrou, 2007). The saturated hydraulic conductivity of soil was measured by constant head method (Klute & Dirksen, 1986).
The characteristic curve of soil moisture was measured by centrifuge method (Soil Moisture Determination Method, 1986).
Fitting model
Due to the wide range of soil texture and high fitting degree of the linear type with measured data (Van Genuchten, 1980), the Van Genuchten (VG) model has been widely used for estimating soil water characteristic curve, especially in black soil region (Gao, Gu & Li, 2018;Wang et al., 2018). Therefore, in this study, the VG model was adopted, and its expression formula (Lei, Yang & Xie, 1988) is as follows: In the above formula, θ is the volume moisture content of soil under suction(h); h r is the permanent wilting point; h s is the saturated volume moisture content; a is the suction value related to the inlet air value, which is equal to the reciprocal of the inlet air value, and the inlet air value of soil is related to the soil texture. Generally, the inlet air value of heavy clay soil is larger, while that of light soil or well-structured soil is smaller; h is soil water suction; n and m are curve shape parameters, n reflects the change of soil moisture content with soil water suction, and the value of n determines the slope of soil water characteristic curve.
The larger the value of n, the slower the slope of the curve, taking m ¼ 1 À 1 n .
The formula of specific water capacity is:
Data processing and analysis
Soil water characteristic curve was fitted by RETC software ( [URL] differences in soil properties (e.g., soil bulk density, soil mechanical composition, soil organic matter content and saturated hydraulic conductivity) among sloped farmlands with different degree of erosion and degradation were analyzed by one-way ANOVA analysis, and the correlations between soil physicochemical properties (soil organic matter content, soil bulk density, sand, silt, clay) and water characteristic parameters (a, n, C (100), Ks) were analyzed by Pearson correlation analysis, using SPSS 17.0 software (SPSS Inc, Chicago, IL, USA).
Saturated hydraulic conductivity of black soils
Soil saturated hydraulic conductivity is an important parameter reflecting soil infiltration performance. The greater the infiltration performance of soils, the greater its water retention potential. As shown in Fig. 2, the saturated hydraulic conductivity of lightly eroded (L) slope farmland soils was between 0.04-0.11mm/min, which was higher than those of moderately eroded (M) (0.02-0.05 mm/min) and heavily eroded (H) slope farmland soils (0.01-0.04 mm/min), with a decrease range of 63.6-75%. The saturated hydraulic conductivity of soil decreased with the increase of depth, 0.04-0.11mm/min in 0-10 cm soil and 0.01-0.05mm/min in 10-20 cm soil, with a decrease range of 54.5-75%.
The saturated hydraulic conductivity of lightly, moderately and heavily eroded slope farmland soils decreased by 63.6%, 60% and 75%, respectively, with the increase of depth.
With the aggravation of soil erosion and degradation, soil permeability and hydraulic conductivity decreased.
Water holding capacity and water supply capacity of black soils
The centrifuge method was used to measure the water content of black soils in slope farmlands with different degrees of erosion degradation after natural water absorption saturation and soil water balance under different rotating speed (suction value). Then, VG equation was used to fit it. The parameter values are shown in Table 2. The correlation coefficient R 2 was above 0.7594. The VG equation can well simulate the water characteristic curves of black soils with different degradation degrees, as shown in Fig. 3. The difference between saturated water content h s and permanent wilting point h r can characterize the water holding capacity of soil. The greater the difference, the stronger the water-holding capacity of the soil. The differences of saturated water content and permanent wilting point of 0-10 and 10-20 cm soil layers were 0.4418 and 0.4245 respectively in lightly eroded sampling plot (L), 0.4076 and 0.3880 respectively in moderately eroded sampling plot (M), and 0.3783 and 0.3662 respectively in heavily eroded sampling plot (H). It can be seen that the water holding capacity of lightly eroded farmland soil was the strongest, followed by moderately eroded farmland soil, and the water holding capacity of the upper soil was stronger than that of the lower layer. Therefore, with the aggravation of erosion degradation, the water holding capacity of black soils decreased.
Table 2 and Fig. 3 indicated that the parameter n characterizing the shape of water characteristic curve gradually decreased with the aggravation of black soil erosion and degradation, and the slope of water characteristic curve of heavily eroded farmland black soils was the steepest, followed by moderately eroded soil and finally lightly eroded soil. The a value of black soils listed as lightly eroded farmland < moderately eroded farmland < heavily eroded farmland. It can also be seen that with the aggravation of erosion, the content of soil clay gradually decreased, and the content of soil sand increased, which reduces the water-holding capacity of soil (Table 3).
The results showed that under the same soil water suction, the specific water capacity of 0-10 cm soil layer was larger than that of 10-20 cm soil layer, and the specific water capacity of the same soil layer list as L > M > H (Fig. 4). The specific water capacity of 0-10 and 10-20 cm soil layer in M were 7.52% and 10% lower than those in L, and the specific water capacity of 0-10 and 10-20 cm soil layer in H were 7.75% and 5.73% lower than those in M, respectively (Fig. 4). Therefore, soil erosion and degradation reduce the water supply capacity of soil.
Correlations between soil physicochemical properties and water characteristic parameters
The relationship between soil physicochemical properties and soil erodibility was not specifically analyzed in this study. However, our results showed that with the intensification of soil erosion and degradation of slope farmlands, the contents of soil organic matter, >0.25 mm water-stable aggregates, silt and clay decreased, while soil bulk density and sand content increased, as shown in Table 3. These results indicated the close relations between soil erodibility and soil physicochemical properties for slope farmlands in black soil region. Soil hydraulic properties are further affected by soil physicochemical properties. The correlations between the physicochemical properties and water characteristic parameters of surface soil in slope farmlands with different erosion and degradation degrees were analyzed (Table 4).
Parameter a was significantly negatively correlated with soil organic matter and clay content (P < 0.05), which was extremely significantly negatively correlated with >0.25 mm water-stable aggregates and silt content (P < 0.01), while it was significantly positively correlated with bulk density (P < 0.05), and extremely significantly positively correlated with sand content (P < 0.01) (Table 4). Parameter n was negatively correlated with soil bulk density and sand content (P < 0.01), and positively correlated with >0.25 mm water-stable aggregates and silt content (P < 0.01), but it was not correlated with organic matter and clay content (Table 4). The correlation between specific water capacity and soil bulk density and silt content were very significant. The specific water capacity of soil decreased with the increase of soil bulk density and the decrease of silt content (Table 4). In addition, soil specific water capacity was significantly positively correlated with soil organic matter while negatively correlated with sand content (P < 0.05). There was a significant negative correlation between saturated hydraulic conductivity and soil bulk density (P < 0.05), but no significant correlation was found between saturated hydraulic conductivity and soil organic matter, sand, silt, clay and >0.25 mm water-stable aggregates content.
DISCUSSION
Soil erodibility is closely related to soil physicochemical properties (Jiang, Pan & Yang, 2004;Yang, Yang & Ma, 2014). A large number of studies have shown that soil erodibility is negatively correlated with the contents of organic matter and >0.25 mm water-stable aggregates in soil, and positively correlated with soil bulk density (Fan, Zhu & Shangguan, 2023;Lu, 2022;Lv, 2021;Wang, Cui & Zhao, 2017). Soil physicochemical properties, such as soil organic matter content, mechanical composition, bulk density, pore distribution, greatly changed with the intensification of soil erosion and degradation, which could have significant effects on soil saturated hydraulic conductivity and soil erodibility. With the aggravation of erosion degree, soil sand content increased, clay content and organic matter content decreased, soil aggregate particles were broken, and aggregate stability decreased (Ai, 2013;Gao, Gu & Li, 2018). The saturated hydraulic conductivity of soil increased with the increase of soil organic matter and total porosity, but decreased with the increase of soil bulk density (Mao, Huang & Shao, 2019;Wang et al., 2016;Zhang, Zhao & Hua, 2009).
Consistent with our first hypothesis, with the aggravation of black soils erosion and degradation, the saturated hydraulic conductivity of soil decreased, because soil organic matter and >0.25 mm water-stable aggregates content gradually decreased with soil erosion and degradation, which increased soil bulk density and led to the decrease of soil water permeability. Our results were consistent with the findings by Zhang et al. (2015) and Jing, Liu & Ren (2008). In addition, previous studies have shown that the destruction of soil structure will lead to the decrease of soil infiltration rate and present a significant positive correlation (Yang, Zhao & Lei, 2006;Yang, Wu & Zhao, 2009). We found that the saturated hydraulic conductivity of lightly eroded topsoil was significantly higher than that of moderately eroded topsoil, while there was no significant difference between the saturated hydraulic conductivity of moderately eroded topsoil and that of heavily eroded topsoil. This may be due to the significant destruction of soil structure from light to moderate erosion, resulting in a significant decrease in soil infiltration performance to a very low level. From moderate to heavy erosion, the damage degree of soil structure is reduced, so that the soil infiltration performance is not significantly reduced.
Previous results have shown that compared with other models, the VG model has the highest accuracy for simulating soil water characteristic curve (Deng et al., 2016;Wang et al., 2018;Zhang et al., 2022). In this study, the VG model was used to simulate the water characteristic curve of black soils, and the fitting correlation coefficients (R 2 ) were all between 0.7594 and 0.9939. Therefore, this model can be effective in fitting the relationship between water content and water suction of black soils in slope farmlands with different erosion and degradation degrees. Compared with the VG model of lightly and moderately eroded soil, the R 2 value of the heavily eroded soil VG model was much lower. The reason may be that the sand content of heavily eroded soil is significantly higher than that of lightly and moderately eroded soil, so that the water holding capacity of heavily eroded soil is lower. The soil moisture content decreased significantly with the increase of water suction, resulting in a small change of soil moisture content with water suction in the middle and late centrifugation period. Therefore, the VG model R 2 value of heavily eroded soil with higher sediment content is smaller.
With the aggravation of soil erosion and degradation degree, the difference between soil saturated water content h s and permanent wilting point h r decreased, as well as shape parameter n, indicating that soil water holding capacity was weakened. That might be because with the aggravation of soil erosion, the contents of soil organic matter and clay decrease and the content of sand increases, which eventually leads to the decrease of soil water holding capacity (Zhai et al., 2016). Ma, Fu & Luo (2017) indicated that the difference between soil saturated water content h s and permanent wilting point h r could characterize the water holding capacity of soil, with greater difference reflecting stronger water holding capacity of the soil. Dong et al. (2017) found that the larger the fitting parameter n of the VG model, the better the soil water retention capacity. Therefore, the water holding capacity of typical black soils decreases with the aggravation of black soils erosion and degradation.
It has been found that the parameters a and n of VG model water characteristic curve can reflect the water holding capacity of soil, and the smaller the a value and the larger the n value, the better the water holding capacity of soil (Ma, Fu & Luo (2017); Pan, Lei & Zhang, 2007;Wang et al., 2018). Soil water holding capacity is mainly affected by soil basic physicochemical properties such as soil bulk density, organic matter content, soil texture, soil porosity and so on. Soil water holding capacity positively correlated with soil texture and porosity, and negatively correlated with soil bulk density (Liu et al., 2017a;Zhao, Zhou & Wu, 2002). The results of this study showed that the parameter a was negatively correlated with the contents of organic matter, silt, clay and >0.25 mm water-stable aggregates in soil (P < 0.05), but positively correlated with soil bulk density and sand content (P < 0.05). Parameter n was negatively correlated with soil bulk density and sand content (P < 0.01), and positively correlated with silt and >0.25 mm water-stable aggregates content (P < 0.01), but did not correlate with soil organic matter and clay contents. Our results provided evidence that soil erosion and degradation led to the decreases of the contents of soil organic matter and >0.25 mm water-stable aggregates, while resulted in the increase of soil bulk density, which consequently decreased soil water holding capacity. Therefore, soil bulk density and the contents of organic matter and >0.25 mm water-stable aggregates were the main factors affecting soil water holding capacity. In Table 3, in H erosion degradation class silt content was lower than L&M in two depths of samples. The reason may be that soil erosion will lead to the fragmentation of soil aggregate particles, and the small particles generated after the fragmentation of micro-aggregates are carried away by rain and wind, resulting in the imbalance of soil aggregates. The decrease of aggregate stability in turn resulted in the intensification of surface runoff and soil erosion, the decrease of soil particle content and coarser texture (Ai, 2013). Earlier studies have also showed that the clay and silt contents of black soils decreased with the increase of erosion degree (Zhai et al., 2016;Gao, Gu & Li, 2018), which supported our results.
The specific water capacity when the soil water suction is 100 kPa (C (100)) can well measure the water supply capacity of soil (Liu et al., 2019). There is research indicated that specific water capacity is a useful index to measure the amount of water that can be released by soil to supply plant absorption (Liu et al., 2017a). The greater the specific water capacity, the stronger the soil water supply capacity and drought resistance. In this study, the specific water capacity of soil decreased with soil erosion and degradation, which indicated that soil erosion and degradation reduced the water supply capacity of soil, mainly due to the fact that soil with low degree of erosion and degradation has higher organic matter content, better soil structure and higher water absorption capacity, thus making the water supply capacity stronger (Ma et al., 2005).
Finally, it should be noted that the accuracy of the VG model varies with changes in soil texture and physicochemical properties. For example, when the sand content in the soil is high (more than 50%), the VG model has poor fitting effect (Zhan, Li & Yu, 2022). Therefore, although our results have demonstrated that the VG model can be effective in simulating soil water characteristic curves of black soils in slope farmlands with different erosion and degradation degrees, caution is needed in applying and extending the conclusions drawn from this model.
CONCLUSIONS
The water characteristics of black soils in sloping farmlands with different degrees of erosion degradation have seldom reported in the past. Our study investigated the saturated hydraulic conductivity, water holding capacity and water supply capacity of black soils in lightly, moderately and seriously eroded slope farmlands, fitted them by the VG model, and explored their correlations with soil physicochemical properties. The results support our hypotheses that the aggravation of erosion and degradation of black soil in slope farmlands coarses soil texture, reduces the contents of organic matter and >0.25 mm water-stable aggregates, and increases soil bulk density, which leads to the decrease of soil saturated hydraulic conductivity and weakens soil water holding capacity and water supply capacity. These findings provide scientific basis and basic data for rational utilization of soil water, improvement of land productivity and prevention of soil erosion. Therefore, improving soil water characteristics of sloping farmland in black soil region can not only increase soil infiltration, reduce surface runoff and erosion, enhance water storage and moisture conservation capacity, but also provide theoretical basis for efficient use of agricultural water resources, which is of great significance for agricultural sustainable development in black.
Figure 2
Figure 2 Saturated hydraulic conductivity of soils in slope farmlands with different erosion and degradation degrees. Note: L, lightly eroded soils; M, moderately eroded soils; H, heavily eroded soils. Values are means of three replicates ± SD and different lowercase letters indicate significant differences (Duncan's multiple range test, p < 0.05). Full-size DOI: 10.7717/peerj.15930/fig-2
Figure 4
Figure 4 Specific water capacity of soil in slope farmlands with different erosion and degradation degrees. Note: L, lightly eroded soils; M, moderately eroded soils; H, heavily eroded soils. Values are means of three replicates ± SD and different lowercase letters indicate significant differences (Duncan's multiple range test, p < 0.05). Full-size DOI: 10.7717/peerj.15930/fig-4
Table 1
Basic information of sampling sites.
Table 2
Fitting parameters of VG model of water characteristic curve.
Note:L, lightly eroded soils; M, moderately eroded soils; H, heavily eroded soils. Values are means of three replicates ± SD and different lowercase letters indicate significant differences (Duncan's multiple range test, p < 0.05).
Table 4
Pearson correlation coefficient between soil physicochemical properties and water characteristic parameters.
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Domain: Agricultural And Food Sciences
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Effects of calcination temperature of eggshell-derived CaO as a catalyst for biodiesel production from waste cooking oil
Biodiesel is considered to be more friendly to the environment than petroleum-based fuels, cheaper and capable for producing greener energy which contributed positively in boosting bio-economy. In this work, waste cooking oil (WCO) is converted into biodiesel utilizing a waste eggshell (CaO) nano-catalyst in an effort to discover environmentally beneficial and economically viable processes for social and economic development. The eggshell-based CaO catalyst developed for the production of ecologically friendly biodiesel at a reduced price is calcined at temperatures between 600 and 1100 °C. The synthesized catalysts were assessed in terms of their physical and chemical qualities via BET, TGA and XRD analysis. This revealed that, besides displaying exceptional transesterification activity, the catalyst synthesised at 950 °C also offered the greatest biodiesel yield. Transesterification, used in biodiesel generation, was used to evaluate the catalytic performance of manufactured catalysts under several reaction circumstances. Under prime reaction conditions i.e., a reaction time of 3 hours, an ethanol-oil molar ratio of 9:1, and a catalyst amount of 4 wt.%, it was ascertained that a catalyst which had calcined at 950 °C demonstrated excellent transesterification activity and delivered a ceiling yield of 88% fatty acid ethyl esters. The production of FAME was confirmed by using gas chromatography-mass spectroscopy (GC–MS). Fuel properties of fatty acid ethyl ester complied with ASTM D 6751 which indicated that it would be an appropriate alternative form of fuel.
INTRODUCTION
Energy is an important foundation for each country's economy and society. Presently, over 78% of the world's energy consumption is met by non-renewable sources. As a result of their rapid consumption, their supply is dwindling in the modern world. 1 Anthropogenic activities produce vast quantities of carbon dioxide (CO 2 ) and greenhouse gases (GHGs), which in turn cause pollution, degradation, and global warming. 2,3 Furthermore, climate change is caused by these trace gases. Therefore, it is essential to reduce these emissions; this may be accomplished by concentrating on mitigation techniques, such as the use of renewable energy sources. A renewable, maintainable, economically viable, and environmentally friendly alternative to a fossil fuel-based energy system must be conceived. One potential product is biodiesel: a liquid biofuel currently under consideration as a carbon-efficient alleviation solution. Replacing traditional fossil fuels with a product such as biodiesel is a credible means of reducing greenhouse gas (GHG) emissions and the build-up of CO 2 . This is of particular significance to the transportation sector, which is viewed as playing a significant role in the reduction of global warming and climate change. 4 Biodiesel production costs and the cost of raw materials used in the manufacturing of biodiesel are the key obstacles to commercialization and market competitiveness. 2,5 For biodiesel to compete with gasoline, it's essential to find inexpensive feedstocks, alcohols, and catalysts that are both easily available and inexpensive. There is a viable option for the manufacturing of low-cost and ecologically sustainable goods such as biodiesel from waste cooking oil (WCO). 6,7 The production of biodiesel requires various procedures which include micro-emulsion, 8 blending, pyrolysis, and transesterification (defined as the reaction between a fat/oil triglyceride and alcohol, to produce esters and glycerol). Transesterification is a rescindable procedure and one which requires a surplus of alcohol to impel the equilibrium to the product side. Theoretically, the stoichiometry for this process requires a ratio of 3:1 alcohol to oil but, empirically, this ratio has been seen to fluctuate. When it comes to biodiesel manufacturing, transesterification is the most generally utilized technology due to its low price point, efficiency, and compatibility with diesel oil in any ratio. 9 The manufacture of biodiesel from vegetable oils frequently makes use of homogeneous catalysis. Soap formation, excessive wastewater generation, reactor corrosion, and other process problems can occur with homogeneous catalysts, despite the fact that they provide high yields in a short period of time. 10 Biodiesel technology is urged to use heterogeneous catalysts to overcome the challenges of homogeneous catalysis and lower the cost of biodiesel production. Among the many advantages of heterogeneous catalysts are environmental friendliness, ease of recyclability, minimal reactor corrosion, ease of separation, and increased purity in the ester and glycerol products. 11 The use of low-cost and environmentally favorable solid waste sources for sustainable biodiesel production has recently gained promising scope.
The use of CaO as a catalyst in the transesterification process has been well documented by many previous publications. Originating from naturally occurring shells, an exceptionally untainted version of CaO (obtained from the shells of mussels under specific experimental conditions) created biodiesel from soybean oil, with a yield of 94.1%, as reported by Rezaei et al. 12 Other methods, such as those employed by Chen et al., manufactured CaO from ostrich eggshells, by implementing a technique involving ultrasound, which yielded 93% biodiesel from palm oil. Another research team, Gupta et al., obtained a 96% biodiesel output from soybean oil, using CaO catalysts based on snail shells. One team demonstrated the feasibility of using waste chicken eggshells and soybean oil to generate high yield and highquality biodiesel synthesis of over 97%. 13 In previous research, it was demonstrated that the transesterification
RESEARCH ARTICLE
Raiedhah A. Alsaiari, Esraa M. Musa and Moustafa A. Rizk 31 S. Afr. J. Chem., 2023, 77, 30-35 [URL]/ of high-grade vegetable oil is possible when combined with the use of a naturally occurring CaO catalyst. This use of vegetable oil is, however, not viewed as economically viable and, consequently, the use of this process to enter the biodiesel market is particularly challenging. To overcome this issue, there is a great deal of current research exploring alternate, renewable, feedstock that is enduring, economically feasible and environmentally benevolent. This research involves an investigation into the use of waste cooking oil and inedible plant oils, such as jatropha, castor, tobacco and linseed which are essential feedstocks, crucial to transesterification. When considering the production of biodiesel, the use of surplus cooking oil and eggshells has two advantages: a reduction in pollution (caused by the disposal of these two products) and a reduction in production expenditure.
To obtain improved biodiesel yields, CaO's catalytic activity can be boosted through increased basicity and surface area, fabrication of a nanoparticle can greatly enhance the catalytic performance of a heterogenous catalyst via a reduction in crystal size. Biodiesel made from used cooking oil has been extensively studied, although there are still drawbacks such as high levels of free fatty acids and contaminants. For it to be deemed a potential contender for traditional homogenously catalyzed biodiesel production, these constraints must be addressed or reduced. 14 A number of research papers on the subject found that biodiesel produced from waste cooking oil using eggshell catalysts yielded between 91% and 100% depending on the reaction conditions. Due to differences in reaction time, heterogeneously catalyzed transesterification processes were slower than those mediated by homogeneous catalysts. In the three-phase systems (oil, alcohol, and catalyst), the mixing difficulty caused this. 15 CaO's lack of basicity and surface area may restrict its ability to catalyze. Transesterification can be complicated by the need for more catalysts and a longer reaction time, both of which increase manufacturing costs. To obtain improved biodiesel yields, CaO's catalytic activity can be boosted through increased basicity and surface area.
Currently, no work has been reported studying different calcination temperature and application of green nano particles of CaO derived from waste eggshells as efficient catalyst for synthesizing biodiesel via waste cooking oil that doesn't lead to food competition. This is innovative research, the catalysts engineered were investigated using X-ray diffraction (XRD), TGA and Brunauer-Emmett-Teller (BET) techniques. The ASTM6751 reference standards were used to judge the suitability of the biodiesel product for use as a fuel. Biodiesel production from date seed oil is cost-effective and has no negative impact on food security. It contributes to GHG reduction while also providing a cost-effective alternative to fossil fuels. As a result, our work herein aims to identify the economic benefits associated with conversion of waste material into a value-added product.
Preparation of the waste cooking oil sample (WCO)
This WCO was originally gathered from surrounding eateries that used sunflower oil in their cooking. After being heated at 110 °C for roughly half an hour in an oven to eliminate the water contained in the WCO, the oil was filtered to get rid of any remaining food particles. Density, acid value and free fatty acid (FFA) value, were all calculated for WCO in accordance with industry standards. 16
Preparation of CaO nanocatalyst from eggshell
Eggshell wastes were gathered from surrounding restaurants and treated in boiling water to harden the gelatinous components sticking to the eggshell's inner wall, allowing for simple removal. It was then oven-dried at 120 °C for 16 hours after being cleaned many times with tap water and rinsing with distilled water to eliminate contaminants. It was ground after drying. The powdered eggshell is placed in a crucible and calcined in a muffle furnace for 3 hours at temperatures of 600, 700, 800, 900, 1000 and 1100 °C.
The GC-MS for produced biodiesel and eggshell-derived catalysts were subjected to an analysis, including BET, in order to find one that would work well in the manufacture of biodiesel.
Transesterification of waste cooking oil (WCO)
A 100 mL round-bottom flask was used for the transesterification procedure, the -bottom flask sitting in a dish containing an oil bath to control the reaction temperature on the hot plate. The catalyst was weighed and dissolved in the requisite amount of alcohol before being added to the round-bottom flask containing the measured and heated waste cooking oil for the reaction. By adjusting the catalyst loading, alcohol/oil molar ratio, reaction temperature, and reaction duration, a high biodiesel yield was achieved by the transesterification process. The following equation was used to calculate an expected yield of biodiesel: Yield % = Weight of biodiesel produced Weight of sample oil used × 100 (1) Different experimental runs were performed to examine and optimize the impact of catalyst loading, alcohol to oil molar ratio, reaction temperature, and reaction time. The effect of catalyst loading was studied by varying the loading amount from 2 to 6 wt% in each run (the mass of catalyst was calculated based on the weight of waste cooking oil). A molar ratio of 1:9 was chosen for the oil to ethanol, and 75 °C and 3 hours reaction time were applied. The next step of the experiment was to maintain a steady catalyst loading. A study was conducted to assess the impact of factors such as reaction temperature, reaction duration, and catalyst loading. A study was conducted to assess the impact of oil to ethanol molar ratio. Variations in the oil-to-ethanol molar ratio (1:3, 1:6, 1:9, and 1:12) were tested, and the value with the greatest biodiesel output was chosen. To determine the best temperature range for the reaction, temperatures of 50-80 °C were tested. As the optimal value, the reaction temperature with the maximum biodiesel yield was selected.
Lastly, to study the effect of reaction time, the other values for catalyst loading, oil to alcohol molar ratio, and reaction temperature were held constant while reaction times of 30, 60, 90, 120, and 180 minutes were tested to see which one resulted in the maximum biodiesel production. The solution was then put into a separate funnel when the reaction was completed. The catalyst, Glycerol and the ethyl ester all formed distinct layers. Overnight, the product was left standing to separate effectively. As can be seen in Figure 1, after an overnight stand, the three phases
RESEARCH ARTICLE
Raiedhah A. Alsaiari, Esraa M. Musa and Moustafa A. Rizk 32 S. Afr. J. Chem., 2023, 77, 30-35 [URL]/ are clearly separated. After that, the biodiesel layer was mixed with 15 mL of distilled water and then shaken on a hotplate for 15 minutes, and then transferred to a separating funnel and left for 24 hours to end up with two clear layers. The lower layer was discarded, and the biodiesel layer was mixed with 0.05 g of sodium sulfate and shaken for 10 min, then separated to measure the weight of the biodiesel layer.
The calcined samples underwent X-ray Diffraction analysis (XRD) using a Brucker AXS-D8 Advance diffractometer (Germany). This diffractometer is outfitted with a copper anode that produces Nifiltered CuKa radiation (k = 1.5406) from a generator running at 40 kV and 40 mA, in the 2 range between 20 and 80. The instrument is maintained by interfaces of DIFFRAC plus SEARCH and DIFFRAC plus EVA to enable an automatic search and match of the crystalline phases for identification. For BET, 1 g of catalyst samples were degassed for 50 minutes at 120 °C in a sample tube to eliminate moisture and other surface contaminants. The tube was allowed to cool to ambient temperature before being connected to a gas intake (liquid N 2 at -196 °C) that was running parallel to an empty reference tube. Both tubes were immersed in liquid nitrogen in a Dewar. For TEM, Sample preparation was as follows: the catalyst powder was dispersed in high purity ethanol, then a drop of the suspension was allowed to evaporate on a holey carbon film supported on a TEM grid. Images were acquired in transmission mode and particle size distributions were calculated using Image J software.
TGA analysis
TGA studies were conducted to determine the best calcination temperature for eggshells CaO derived catalyst in order to build an effective catalyst for biodiesel synthesis from date seed oil. The findings of a thermal experiment on uncalcined eggshell are shown in Figure 2. The results revealed a modest loss of mass, which was most likely caused by water evaporation and the burning of some organic elements. The temperature range of 600-1000 °C, on the other hand, was linked to considerable weight loss. This weight loss at high temperatures might be attributed to CaCO 3 breakdown into CaO. Catalysts were made from wasted eggshell powder in a muffle furnace at three different temperatures, 800 °C, 950 °C, and 1000 °C, as measured by thermogravimetric analysis.
BET analysis
C950's BET surface area and pore volume were determined to be much larger ( Table 1). Because of the increased surface area and pore volume, the catalyst displayed enhanced catalytic activity in the transesterification of date seed oil for biodiesel production. As a result, the C950 catalyst was chosen to optimize biodiesel properties.
Characteristics of waste cooking oil
The density, acid value and free fatty acid value of waste cooking oil were evaluated after filtering and separation of the biodiesel layer; the findings are shown in Table 2.
Effects of calcination temperature on the catalyst activity
For selected feedstocks, the influence of activation temperature on transesterification activity was studied in the range of (600-1100 °C) as shown in Table 3. The results revealed that as the activation temperature for eggshell-derived material was raised, the biodiesel conversion rose linearly. In comparison to other catalysts, the 950 °C calcined catalyst had the highest catalytic activity. Catalysts calcined at 950 °C (C950) showed strong catalytic activity which may be due to the catalyst's surface containing an optimal number of active sites. In comparison to catalysts activated at different temperature, the BET surface area and pore volume of C950 were found to be considerably greater ( Table 1). As a result of the increased surface area and pore volume, the catalyst demonstrated greater catalytic activity in the transesterification process of waste cooking oil (WCO) for the manufacture of biodiesel. Because of this, the C950 catalyst was selected for optimizing biodiesel characteristics.
Effect of reaction temperature
Biodiesel production is very temperature dependent. Figure 3 demonstrates that the highest biodiesel yield was achieved at 75 °C. Because ethanol continuously vaporizes at temperatures above 75 °C, the concentration of ethanol in the reaction medium decreases because of the redux, resulting in a lower biodiesel yield. 3 At an ideal temperature of 75 °C for producing biodiesel, a maximum yield of 88% was achieved.
Effect of different catalyst loading
One of the most important aspects of a successful transesterification reaction is the amount of catalyst used. In Figure 4, we see how changing the catalyst loading affects the biodiesel yield. Increasing the catalyst loading from 1% to 4% wt resulted in a greater biodiesel production. This study's findings suggest that increasing catalyst loading can increase the biodiesel yield by increasing the active surface area of the catalyst involved in the transesterification process. This process has, however, negatively impacted the biodiesel yield, which declined by 4 to 6 wt.%. This may be due to the transesterification reaction product becoming stickier, due to the larger catalyst quantities, which inhibits the mass transfer process taking place in the liquid (oil/ alcohol/catalyst) structure, resulting in a reduced biodiesel yield once the optimal amount is attained. The decrease in biodiesel production with low catalyst loading is likely attributable to the insufficiency of the catalyst for complete conversion and the creation of methyl ester. This research found that a catalyst loading of 4% wt resulted in an 88% biodiesel yield. Figure 5 depicts the influence of reaction time on the transesterification process. The highest biodiesel production was achieved after three hours of reaction. After the optimal reaction time, the biodiesel yield declines significantly due to the transesterification process's reversible nature, which results in product loss with longer reaction times. Longer reaction times may also cause the hydrolysis of esters and the production of more fatty acids, which lowers the amount of biodiesel that can be made. 17
Effect of oil to ethanol molar ratio
Another factor that has a significant influence on biodiesel yield, is the oil-to-ethanol ratio. As observed in Figure 6, an increase in the molar ratio of oil to ethanol from 1:3 to 1:12 creates a comparative growth in biodiesel production. When the ratio exceeds 1:12, biodiesel production decreases which can be ascribed to the high molar ratio of oil to ethanol impeding the separation of glycerin, as the solubility of glycerol, in surplus ethanol, escalates. It is necessary to keep the glycerin in solution, to reduce the production of esters and assist the formation of mono-, di-, and triglycerides. In this investigation, the optimal molar ratio of oil to ethanol for a maximum biodiesel yield of 89% was determined to be 1:12.
Reusability test
An extremely useful method of determining a catalyst's long-term viability from an economic standpoint is to examine its reusability in the biodiesel synthesis process. Experiments on the CaO-1000 catalyst's reusability were conducted using fresh reactants and improved reaction conditions as shown in Table 4. Used catalyst was Oil:Ethanol molar ratio centrifuged out of the reaction mixture, washed in n-hexane to remove adsorbed materials, and then dried in an oven at 110 °C for 16 hours after each run. Biodiesel yields of over 80% were recorded for as many as two separate cycles. Once the catalyst was reused more than three times, however, the biodiesel yield began to drop. The accumulation of organic contaminants on the surface of the catalyst may account for its loss of transesterification activity.
Comparison with previous studies
A comparison has been made between previous studies and what has been studied in this study as shown in Table 5. In this work the focus was on the effect of calcination temperature of the catalyst whereas in previous studies one calcination temperature was selected. Also, in this study, this catalyst was compared with pure calcium oxide under the same reaction conditions to be close to the same effectiveness as the eggshell catalyst, while this comparison was not made in previous studies.
Characteristics of synthesized biodiesel
CaO nano-catalyst was synthesized by calcination under optimum reaction circumstances, and the fuel qualities of the resulting biodiesel were analyzed using the American Society for Testing and Materials' technique (ASTM). Table 6 shows that the produced biodiesel had high-quality fuel attributes that were within the range of the biodiesel standard and were generally consistent with earlier results. 22 Fatty acid ethyl esters (FAMEs) in biodiesel were identified using GC-MS analysis. Table 7 described the fatty acid ethyl esters and other products in more details. All the fatty acid ethyl esters expected to appear and responsible for biodiesel appeared in the analysis (Figure 7).
CONCLUSION
Biodiesel has been successfully manufactured via a combination of low-cost, waste cooking oil and a financially viable, high-performance, low-impact CaO nano-catalyst created from the waste eggshell. Under ideal conditions, of 4 wt.% catalyst loading, 9:1 ethanol to oil molar ratio, 75 °C reaction temperature, and 3 h reaction time, the C950 catalyst functioned commendably, yielding a maximum biodiesel yield of 88%. The high BET surface area, and optimal pore volume of this catalyst, created increased transesterification activity in the surplus cooking oil. However, following many reuses, this activity was observed to diminish because of two factors: active sites on the surface of the catalyst becoming covered by glycerol and other organic molecules and agglomeration of the catalyst particles. In conclusion, the use of a catalyst created from surplus eggshells, combined with low-cost, waste cooking oil, is a commercially viable and ecologically sound alternative to traditional fossil fuels.
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Domain: Agricultural And Food Sciences
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Analysis of greenhouse gas generation models at household waste landfills for ecosystem applications
. The control and minimization of greenhouse gas emissions is an important task of modern ecology. One of the sources of greenhouse gases is landfills of household waste (LHW). A special feature of LHWs, as a source of greenhouse gases, is the complexity of estimating emissions. The fact is that the production of greenhouse gases (mainly methane) at LHW is a long process, time-consuming and dependent on many factors. In particular, the rate of putrefaction of organic waste depends on environmental parameters, such as temperature, humidity, and precipitation patterns. Knowing the estimates of greenhouse gas emissions, it is possible to develop an appropriate technology for their disposal, taking into account the regional features of the location of landfills. A mathematical model of gas formation on LHWs is required to solve the problem of predicting greenhouse gas emissions from these landfills. Currently, there are several generally accepted models of LHW. This paper reviews the three main models used in world practice: LandGEM, EPER-Germany, and TNO in terms of their universality and applicability for describing LHW from Siberia region. It was shown that the most promising model is LandGEM.
Introduction
The impact of greenhouse gases on climate change is an urgent environmental problem. Significant sources of greenhouse gases are landfills for household waste (LHW). When organic waste rotts, various gases are released, of which methane is the most dangerous in terms of the greenhouse effect. Since methane is 21 times higher than CO 2 in terms of the greenhouse effect [1], one of the most common ways to minimize the consequences of gas formation at PBW is to collect landfill gas and then use it as fuel [2][3]. However, in the case of Siberia, such a method of disposal may have problems with economic feasibility due to climate conditions. An alternative approach to the problem of landfill gas is the reclamation of landfills using green spaces [4][5].
Closed artificial ecosystems, such as experimental biotechnical life support systems [6][7], can also be used as a basis for developing technologies for the disposal of gaseous waste [8] from landfills.
Mathematical modelling of the system reduces either to the selection of a function from the variables of the system that best describes the experimental data, or to the identification of key mechanisms of the process and their mathematical description [9]. In both cases, the resulting model needs to be verified -to check the possibility of describing a real system and select parameters for describing a specific system. Not all parameters of the system and its mathematical model can be obtained by direct measurement. A number of parameters, so-called "fitting" parameters [10], can be determined only by trying to describe the dynamics of a real system using a model. One of the problems of modern mathematical modelling is the fact that in case of a sufficiently large number of fitting parameters, the model can describe any dynamics, but only in the section used for validation without a guarantee of correct prediction of future dynamics.
The aim of this work was to review three popular mathematical models of gas formation on the LHW for the number of fitting parameters and their applicability to the description of LHW for Siberia conditions.
Materials and methods
Various mathematical models are used to describe the process of generating greenhouse gases from LHW. The LandGEM model [11][12] recommended by the US Department of Environmental Protection, is widely used. Other common models of gas formation on LHW are EPER-Germany [11][12][13][14] and TNO [11,14].
The LandGEM Model. The Land GEM model is described in detail in [11] and is based on extensive empirical material from landfills in the USA and Canada. The model equation has the form: Where is the amount of methane released per year (cubic meters per year, ), is the gas generation constant, is the year number, is the number of the tenth part of the year (i.e. approximately a month ), is the maximum gas generation, is the rate of garbage delivery to the landfill, is the time. Carbon dioxide emissions are calculated from methane emissions obtained in the model using an empirical proportionality coefficient. In addition to methane and carbon dioxide, the emissions of another 50 pollutants are calculated. The coefficients of the model can be empirically estimated, and the model is widely used in the United States and around the world. There is a free software implementation of the model, which is a Microsoft Excel workbook.
As can be seen from (1), the model is based on the assumption that the decay of organic matter is described by a simple exponential law. Fitting parameters include and . An example of how the LandGEM model works is shown in figure 1. The data about Krasnoyarsk LHWs from Krasnoyarsk officials [15] was used. In 2012 waste input to LHW was reduced from 280000 tons/year to 200000 tons/year due to starts of garbage recycling. As can we seen from figure 2, in scenario with no garbage recycling LHW may produce 220000 tons of landfill gases in contrast to 165000 tons in scenario with garbage recycling.
The LandGEM model is widely used in PBW modeling in various countries [11-12;14;16-18]. In the context of this work, it is particularly worth noting the work [14] in which 35 landfills in Canada were successfully modeled using the LandGEM model, which means that the model is fundamentally applicable in Siberia. The EPER-Germany model. The EPER-Germany model was created and is used in Germany and is the so-called zero-order model. This is a simple balance equation that describes only the current landfill, but not the landfill that has stopped working. Model equation: (2) Where and correspond to model (1), is the share of carbon-containing waste in the total mass, is the share of available to methane-synthesizing bacteria, is the share of methane in landfill gas, and is the efficiency of gas collection (for incineration). The model's fitting parameters . , and can be measured. The EPER-Germany model is also widely used for modeling landfills [14;19-20]. In [14], an attempt was made to use the model to describe landfills in Canada, but the result was significantly worse than that of LandGEM.
The TNO Model. The TNO model is similar to the LandGEM model, but instead of a discrete equation, a differential equation is used. This model is used in Denmark. The model equation has the form: The designations are identical to (1) and (2). The difference from the LandGEM model is the use of explicit parameters for the proportion of carbon in total biomass and the proportion of carbon available for decomposition instead of the maximum decomposition rate.
Results and Discussion
The authors of the three main modern models of gas formation at solid waste landfills minimized the number of adjustment parameters. In the EPER-Germany model, it is only one -the fraction of degradable carbon. However, this is achieved at the cost of refusing to describe the closed dump. The LandGEM and TNO models use two adjustment parameters each.
As can be seen from (1) and (3), the LandGEM and TNO models actually differ in the name of the parameters and the level of sampling. Indeed, it is easy to get (1) from (3) by replacing to . Thus, when choosing between LandGEM and TNO, the choice is actually reduced to the availability of a ready-made implementation in the public domain, available to LandGEM, but not to TNO.
The simplicity and number of fitting parameters for EPER-Germany are achieved at the cost of describing only the stationary case. In the case of Siberia, it is not landfill gas collection that is relevant, but landfill remediation, and the ability to model the case of a decrease in the gas production intensity after the landfill is closed is important, which the EPER model lacks.
Conclusion
The LandGEM model seems to be a fairly effective modeling tool tested on a large number of landfills in conditions close to the Siberian region. Having a ready-made implementation of the open source model simplifies both the use of the model and its refinement if necessary.
In the course of the work, the presence of an isomorphism between the LandGEM and TNO models of gas formation at landfills was shown. These models can be used in assessing greenhouse gas emissions at landfills in the Siberian region with the aim of further developing technologies for the utilization of these gases and land reclamation on the basis of closed artificial ecosystems.
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Domain: Agricultural And Food Sciences
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Nixtamal techniques for different maize races prepared as tortillas and tostadas by women of Chiapas, Mexico
Nixtamalization, which means cooking maize in alkaline water, is the central technique for the culinary use of maize in Mexico and Central America. Without this procedure, relying on maize as the basic starch staple is inadequate because of nutriment deficiencies. Mexico has more than 50 principal racial types of maize, and these differ in grain qualities that can require the adjustment of the nixtamalization process. Properties such as hardness and grain composition influence nixtamalization because they are related to the absorption of water that occurs during cooking and steeping. Some maize preparations, like tortillas and tostadas, can also require the adjustment of nixtamalization to obtain a high-quality foodstuff. We studied how women in three regions of the state of Chiapas, which differ in the prevalent maize race available, prepare their nixtamal and whether they make changes according to the type of food they prepare. Interviews of 30 women follow the measure of relevant variables when the women prepared nixtamal. We found that nixtamalization is adjusted for different grain hardnesses and for environmental conditions. Variations were found in the cooking time of the nixtamal, in the amount of time the nixtamal was steeped, and in a special process of double boiling of the nixtamal performed by some women for tostadas. Women that specialize in production for the market have developed variations preferred by consumers. As practiced by women in Chiapas, nixtamalization is a flexible technique that is adjusted for maize type and for food preparations.
About 60 native races and hundreds of landraces of maize are grown in Mexico [4,5]; these have important variations in their grain qualities and nutritional characteristics and also in their culinary and gastronomic characteristics [6,7]. In Mexico, the central technique that links maize and its culinary use is nixtamalization [1,8.]. Tortillas are the main foodstuff derived from nixtamal and the basic component of the daily diet of Mexicans; these Mexican cuisines have been recognized as intangible heritage of humanity [9]. Inside of Mexico the tortilla is recognized as an ethnic food, and in Central America and southern USA it is a common foodstuff [10].
Nixtamalization and its variation at the household level and for specific preparations, however, have been scarcely studied ethnographically [11]. The women of Ixtlahuaca and Tlaxiaco (regions of the State of Mexico and Oaxaca, respectively) make tortillas for their own consumption and sale in public squares and markets. They cook hybrid and native varieties of maize, but they prefer the native grains by the shorter cooking time and better organoleptic characteristics of the tortillas [12,13]. The discovery of nixtamalization was essential for developing a food culture around maize. Without nixtamalization, the nutritional deficiencies of this kernel would have prevented a diet based on this grain [8,14]. Nixtamalization increases the calcium content and efficiency in the assimilation of essential amino acids, releases the available niacin and removes the kernel coating making the masa (dough) less fibrous and more elastic [15].
Despite the importance of fresh nixtamal in the Mexican diet, practically all scientific attention on nixtamalization has been focused on the production of industrial nixtamal [16][17][18][19]. Since it is a relatively simple process, formal research regarding homemade nixtamalization has been neglected. There is, however, a complexity hidden in its apparent simplicity that can be relevant for high-quality maize products.
In their simplified form, the maize kernels are cooked in alkaline water until the pericarp comes off [20]. The nixtamal, as the maize is called once cooked this way, can cool in the cooking liquid for several hours, commonly overnight. Next, it is washed one or more times in water and milled into a dough known as masa [21]. It is thought that early nixtamalized maize was done with wood or seashell ashes [11,14]. Currently, the predominant form of alkaline used is calcium hydroxide (Ca (OH) 2 or lime) [22][23][24][25]. The cooking time of the nixtamal is commonly between 30 and 45 min, but it may be longer than 1 h or may be only steeped in boiling water but with a larger concentration of lime [25,26]. After cooking, the nixtamal can be left to soak in its water from less than 30 min to 1 day [20].
Exploratory work has suggested the variation of interest in all steps of nixtamalization. Some nixtamalization processes are associated with a particular product, such as very short steeping for totopos (a tortilla-type food dehydrated with infrared radiation in a bottomless clay oven called comixcal) in the state of Oaxaca [27]. It may also be important to modify nixtamalization for some characteristics of the kernel, such as hardness and the predominant type of endosperm [28,29].
Hardness and starch composition are characteristics that affect nixtamalization because they are related to water absorption when cooking and steeping the grain [29,30]. Starch granules can be polygonal with a rigid protein matrix or spherical with a weak protein matrix; the former has smaller spaces [31]. Softer grains with larger spaces between starch granules enable faster water absorption.
In Mexico, women have been directly responsible for nixtamalization and have inherited the knowledge of how to nixtamalize from their families [32]. This work is of an ethnographic nature and examines how women in three regions of the state of Chiapas perform and use nixtamalization, as well as focusing on the variation of the process for three types of maize and two important food uses: tortillas and tostadas.
The quality of the tortillas was studied using two nixtamalization times [33] and the quality of the toasts through two cooking processes (in press); both are important products in most regions of Mexico. Artisanal tortillas and tostadas are highly demanded and appreciated; many women in need of income produce these for sale in markets and locally [34]. We expected that women distinguish between different types of maize and adjust the nixtamalization depending on the hardness of the kernel, while increasing the boiling time for the hardest grain for tortillas and tostadas. We also expected that women modify nixtamalization based on the type of food product prepared.
Study regions
The research was performed in 10 rural communities of 7 municipalities (Table 1, Fig. 1). We chose to work in three regions of the state of Chiapas, Mexico, with distinct altitudinal ranges that correlate neatly with the presence of the three maize races included in the study. In the three regions, women produce tortillas and tostadas for home consumption and some also for the market.
Native maize types
More than 20 races of maize have been reported for Chiapas [35], but only about 10 are common. In addition, the three studied, Tuxpeño, Comiteco and Oloton, stand out in abundance throughout Chiapas [36]. Maize races are a widely used informal taxonomic level for maize diversity; these commonly present subracial and interracial variants where they are prevalent [37].
Tuxpeño is a race with widespread distribution in warm regions of Mexico below 1,200 m.a.s.l. and is distinguished by medium-to-long cobs (15 to 20 cm) with a cylindrical shape. Their kernels are long and thin, commonly with a pronounced depression at the distal of the kernel. The Comiteco race has long cobs (sometimes more than 35 cm), is conical in shape and is the most important maize race in the Meseta Comiteca region (subsequently Comiteca). Oloton is the race that predominates in the temperate elevations above 2,000 m.a.s.l. [35,36]. Its cobs are also conical in shape and commonly have disordered basal rows. The kernels tend to be spherical and short in length [38]. The Altos or highland region is between 1900 and 2400 m.a.s.l. and has a temperate humid climate, with Oloton as the dominant maize race. The Altos region is characterized by having a predominantly population of indigenous people (68%). The Metropolitana and Comiteca regions' population is mostly mestizo, but indigenous communities are also present (Fig. 2).
These three races have been reported to have different kernel hardness [39]. In anecdotal observations, the Oloton has a harder kernel than Tuxpeño and Comiteco, which appear to be of intermediate hardness.
In the literature, it is reported that Tuxpeño is harder than the Oloton [39]. In measuring the hardness and the compaction of the kernel associated with this research, we found that the Oloton and Comiteco tend to be harder than the Tuxpeño, but this was not systematic for the three independent samples collected for each race. Hardness, measured by the flotation index, results in 41 grains of 100 floating for Oloton, 36 for Comiteco and 35 for Tuxpeño. Test weight measurements as an indicator of hardness range between 76 and 77 kg/hL for the three races of corn. On the other hand, the hardness as a puncture force measured in Newtons (N) presents values of 123 N for Oloton, 124 N for Comiteco and 110 N for Tuxpeño. Since a significant variation was found within of each race, this measurement must be taken with a larger independent sample.
Interviews with women
To access the communities, we introduced ourselves to the local authorities, explained the purposes of the study and requested permission to work. We individually asked 30 women whether they wanted to collaborate in the project and for permission to be interviewed. We sought those that belonged to different neighborhoods and family nuclei to reduce kin relationships. Women were shown samples of kernels corresponding to maize of the three races studied to discuss their knowledge of each type of maize. The interview guide applied was structured on their knowledge about maize races, differences between of grain types and colors when nixtamalizing, how they learned and at what age about the techniques of nixtamalization, and tortilla and tostada preparations.
In the Metropolitana region, five of the women sell tortillas for a living. Some of them also sell dough (masa) for pozol, and the other 5 are recognized for making good tortillas, although they do not produce them for market. No commercial tostada producers were found in this region, but all women produce these for household consumption. In the Comiteca region, all women prepare tortillas and tostadas for home consumption, and the five women of Yalumá are dedicated to the sale of these foods. In the Altos region, the women make tortillas for family consumption, and all but two make tostadas for sale.
Participant observation of nixtamalization
We participated with each of the women when they performed the nixtamalization of maize, as well as the subsequent making of their tortillas and tostadas. For this purpose, a participant observation guide with specific questions was used to identify how they perform the nixtamalization technique, how they acquired the knowledge and what they know of nixtamalization with respect to the race and hardness of the kernel, as well as its relationship with the type of food preparations and its characteristics. We also measured several relevant variables of the process: amount of corn, water and lime used; temperatures and cooking time of the nixtamal for tortillas and tostadas; resting time of nixtamal; washing; size and weight of raw and cooked tortillas and tostadas.
Nixtamalization
The average age of women was 48.1 years (SD 13.7), varying between an average of 46.1 years in Altos and 55.7 years in Comiteca.
All the women interviewed learned to nixtamalize and make tortillas and tostadas from other women. They learn at a young age, and the practice is transmitted informally by adult's women. Same situation as in the case of Malawian girls who make "nsima", a kind of thick porridge prepared with corn flour [40].
Almost all (93%) learned from their mother or grandmother, and the rest from their mothers-in-law. The way they learned is through imitation, and they began with preparing tortillas. When mothers or grandmothers prepare the tortillas of the day, they provide a small portion of masa for young girls to participate. As one woman stated "leaving school they would make me make my tortilla … they gave me my little ball of masa to learn how to make my tortilla…".
No women stated that men prepare nixtamal or participate in preparing tortillas or other foods because it is considered a female activity [41]. If they require help to For nixtamalization, the women interviewed did not give us a specific description of how they learned to do it. Apparently, it is learned by imitation and without specific recommendations regarding the amounts of maize, water, or lime. Common practice is to add enough water to cover the kernels, so when the nixtamal boils and the water is absorbed by the grain, nixtamal will still be in solution. A small unmeasured quantity of lime is added to the water, and the maize is brought to a boil and cooked until the pericarp comes off when rubbed with the fingers.
The boiling temperature at the Metropolitana region is 5 degrees higher (average 97.5 °C) than in the other two regions (92.7 and 91.0 °C for Comiteca and Altos, respectively). The boiling time in the three regions ranged from 35 to 110 min, with a trend to shorter times in the Metropolitana region ( Table 2). The average cooking time was 51.4 min in the Metropolitana region (ranging from 35 to 65), 72.1 min for Comiteca and 80.0 for Altos (ranging from 60 to 85 and 45 to 110, respectively).
Only one-third of women identified problems with nixtamalization that are associated with the quality of food preparations. This may be because not all associate poor nixtamalization with poor quality characteristics in their food. The women who do manage to relate the technique to the properties say that overcooking of the nixtamal during the nixtamalization, or an incomplete cooling of the nixtamal after boiling, will produce sticky masas that produces a poor texture in tortillas and tostadas.
Once the pericarp can be removed from the kernel, the nixtamal is left to rest for a variable amount of time. In the Altos and Comiteca regions, the nixtamal is usually prepared in the afternoon and left to soak overnight. In Metropolitana, the common practice is to perform the nixtamal in the morning and steep it for no more than 1 h ( Table 2). The women stated that if they soak the nixtamal for longer the masa acquires an acidic aroma and flavor, possibly related to the much warmer climate in this region.
Once the nixtamal has been soaked, it is washed and rinsed with clean water two or three times to remove lime residue, and the kernels are rubbed to remove the skin. The first residue of lime water in which the nixtamal is soaked is known as nejayote. The washed nixtamal is ground between two grooved stones in electric mills to obtain the masa, now known as masa, or it is milled between two grooved metal plates in manual mills.
Women who make pozol in the Metropolitana region stated that they perform the same nixtamalization process, but the nixtamal is coarsely ground. In the Altos region, women mentioned that to make atoles or tamales it is necessary to cook the nixtamal for a longer time.
Nixtamalization with "double boiling" for tostadas
In the Altos region, most the of tostada producers (85%) use the technique known as double boiling for the nixtamal, while less than a third (29%) in Comiteca and no one in the Metropolitana regions practice this procedure. Women associate this technique with softer tostadas, and its origin is uncertain. Apparently, it was unknown before they became producers for the market. In this technique, the nixtamal is first prepared in the conventional way: boiled in lime water, soaked and rinsed. After washing, they boil the nixtamal again in clean water, without lime, until the kernel bursts. This boiling requires a long period of time. Thus, it is common that the second boiling takes place during the night, for which they ensure there is sufficient wood in the stove. In the first boiling of the nixtamal, the kernels are still intact; if the boiling is too prolonged, some could burst, and the lime water would penetrate the grain, imparting an unpleasant flavor to the tortilla or tostada. The next morning the burst grains are rinsed and milled to obtain the masa. Some women described two stages of bursting the kernel: one with the kernel slightly burst, or starting to burst, and the other as "completely" burst (Fig. 3). The masa for the doubledboiled nixtamal is described as fluffier than the common nixtamal and sticky, which is not a characteristic of common nixtamal. Thus, double-boiled nixtamal is more difficult to work with, but the softer tostada that is produced has a larger demand.
In the Metropolitana region, double boiling is not practiced for tostadas but several women that produce pozol for sale practice a similar technique. These women sometimes keep washed nixtamal without grinding it for one day, after which they boil it again with a small amount of lime until it bursts slightly. They stated that this is needed because their very hot climate spoils the nixtamal quicker, and boiling it again reduces the problem, as does using lime.
Maize race, kernel hardness and grain color
The three maize races can be found in white and yellow grains. Oloton and Comiteco can be also found in blue/ purple and red shades, although the latter are very scarce. The women interviewed in the three regions stated that they prefer their local maize race of yellow grain for household consumption and deemed that these offer a better appearance, flavor and consistency to food. They also indicate that it is easier to wash the nixtamal for yellow maize; thus, they use less water with this grain color. When washing the nixtamal, the white maize requires two or more rinses in water so that the yellow pigmentation caused by the lime does not prevail in tortillas, while a yellow grain nixtamal can be used with only one rinse. In the Altos region, the Tuxpeño are preferred for the tostadas prepared for the market because they make softer tostadas. These maize varieties are not produced in this region, but they are sold in local markets.
All women of the Altos expressed that they recognize the hardness of maize grains (Table 3), though only a third of them do so in both the Comiteca and Metropolitana regions. This difference is possibly related to the fact that in the Altos the Oloton and Tuxpeño maize can be acquired locally or regionally, while the Oloton and Comiteco are not marketed in the Metropolitana region because Tuxpeño is abundant. In the Comiteca region, however, the Comiteco and Tuxpeño are available, although not all women distinguish them. The women of the Altos stated that the Oloton maize is harder than the Tuxpeño.
Only 13.3% of the participants have noticed a difference in the cooking time of the maize from the same race but of different colors. They stated that blue and purple grains cook faster compared with yellow or white.
Preparation of tortillas
Women over 50 years of age reported that there were no tortilla presses before, and they only used their hands to shape the masa into tortillas. In the Metropolitana region, all women use tall wooden stands, known as palmeadores or torteadores (Fig. 4), which they use to form the tortillas. These women use a plastic rectangle Fig. 3 From the Yalumá community in Comitán in the Comiteca region, the yellow maize nixtamal from the Comiteco race that has been double-boiled until the grain looks "burst. " Table 3 Relative frequency (%) of the women's perception of maize grain attributes in three regions of Chiapas that they put on the wooden stand to facilitate the circular movement of the masa, and with the tips of the fingers the masa is spread until a circular tortilla is formed. On the one hand, the contour of the tortilla is shaped, and on the other hand pressure is exercised in such a way that it thins the disk without breaking it.
In the Altos and the Comiteca region, women put the masa between two plastic rectangles in the center of a wooden or metal press and flatten it to shape the tortilla. They press more than once when the tortilla is not even in thickness or shape. The size of the tortilla in the Comiteca and Altos regions is around 12 cm, which is partly determined by the size of the press. In the Metropolitana region, tortillas are larger than 15 cm because it is easy to manually mold more masa on the palmeadores. When the tortillas are flattened, they are placed on a metal griddle known as a comal. Presently, most are made of iron, but a few people still use clay comals. It is very common for women to cover the surface of the griddle with a paste of water with lime or wood ash, so that the tortillas stick less and are easier to turn.
Tortillas are baked similarly in these regions and consist of three cooking phases. First, the tortillas are placed on the comal at about 250 °C and given about 20 s to seal the face ("cara") or the front side of the tortilla. Tortillas are then turned over and cooked for a longer time: 50 to 90 s, to form the back ("espalda") of the tortilla. Tortillas are turned again to the face and cooked for an additional 20 to 40 s until the formation of a puffed or inflated tortilla, generated by water vapor trapped between the face and the back, creates a thin layer in the face.
Preparation of tostadas
When tostadas are made, the women emphasized that they are not prepared in the same way as tortillas. Instead of the three phases described above, the tostadas are done without flipping the tortilla in one cooking phase. The tortilla is left on the comal until it becomes dehydrated, which is determined when the size shrinks, and the surface appears cooked. Done in this way, the inflation is avoided, and a smooth texture is obtained on both surfaces. Once the tortilla is baked, it is dehydrated by toasting it on both sides by placing it on a perpendicular surface close to the fire (Fig. 5), so the infrared heat of the stove dries and toasts the tortilla, giving a brittle tan appearance. Some women use a grilling basket to hold the tortillas flat during the drying.
The tostadas of the three regions show variations. In the Metropolitana region, women use the same nixtamal prepared for tortillas; none of them practiced or knew of double-boiling nixtamal. To prepare tostadas, they prefer to fry the usual tortillas but make them smaller. These tostadas are sturdy, even tough and crisp. In Comiteca and the Altos, tostadas are made mostly with doubleboiled nixtamal masa by all women producing them for sale.
Tostadas prepared with the just burst nixtamal are sturdier and less fragile, while the ones with the completely burst nixtamal are more fragile and easier to chew. Some women described that tostadas with slightly burst kernels are better for frying because they absorb less oil. In addition, those with completely burst kernels are the most fragile and better for dry roasting in the oven or comal; these seem to absorb more oil if fried.
Conclusions
Our study of nixtamalization in Chiapas suggests that there are sufficient variations in the process to warrant further research. Nixtamalization is a simple process that can be customized to maize types, environmental conditions and preparations. Despite the simplicity of nixtamalization, making high quality tortillas or tostadas We found that the length of the nixtamal 's boiling and steeping times vary from just more than 30 min to almost 2 h. Apparently, this is associated with grain type and with a warmer climate but also with the temperature at which water boils in the regions studied. In lower elevations with warmer environments, women boil the nixtamal for less time and do a short 1-h steeping, the later associated with the much quicker fermentation and decomposition processes that produce off-flavors in this climate. It is believed that the steeping creates conditions for gelatinization, but women from Metropolitana did not comment that their masa had any problem with the short steeping. In the Comiteca and Altos regions, with cooler climates in the mid-elevations and the highlands, maize is steeped overnight without problems with off flavors.
In the Altos region, women have also developed a particular process for the preparation of tostadas known as double boiling. With this technique, crunchier and softer tostadas are produced. Apparently, this was not transmitted from the women's mothers and was developed locally for sale.
All women perceive that nixtamalization and steeping times are related to a good quality tortilla. Women who are engaged in preparing these for sale state that the excessive use of lime, the overcooking of the nixtamal, or an excessive steeping time in a warm climate all produce poor quality tortillas and tostadas.
In the three regions, women identified and stated that they prefer their local maize types when making tortillas for their families because they say these were more satisfying and tasted better, but they also use other maize varieties if available commercially in their regions. In these regions, there is a preference for yellow grain varieties, although in the Altos the white grain of lowland varieties is favored for tostadas intended for sale.
Only the women of the Altos have sufficient experience with local maize and maize introduced from warmer regions; thus, they were the only group that expressed that the hardest grains require more time to nixtamalize.
We did not find the specific transmission of knowledge of the nixtamalization process, maybe because women mention that they learn the technique by watching other persons do it and that the essential aspect is to recognize the consistency of the nixtamal when it is ready to withdraw from the heat. In all cases, women learned indirectly from their family by being in the environment where tortillas are made. In all cases, only women are involved in nixtamal production and tortilla and tostada making. This contrasts with tortilla and tostada production in Mexican cities, where men operate the automatic machinery used in industrial-style production [42]. Industrial-style tortillas and tostadas are not considered ideal as a culinary product in Mexican society, while the artisanal ones described in this article are deemed the archetype of high quality [33,43,44].
Nixtamalization is a flexible process that can be adjusted for different maize types and food preparations. The women in Chiapas, who produce for the market, have developed modifications for high-quality foods. Mexican culinary culture is centered on maize products, and therefore, these innovations in nixtamalization are fundamental for this dynamic and exuberant cuisine with worldwide recognition.
This study demonstrates the enduring importance of native corn nixtamalization in regional and local diets. Future studies on other native races of Mexico can be carried out to assess whether these changes in nixtamalization are due to the structural properties of the grain or there are other important variables to consider.
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Domain: Agricultural And Food Sciences
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Uptake of Soil-Residual Diazinon by Rotational Lettuce under Greenhouse Conditions
Pesticide residue is an increasing concern in rotational crop practices. The pesticide used for the primary crop may re-enter the secondary crop, thus exceeding pesticide levels set by the positive list system (PLS). As such, evaluation of pesticide residue translocated into rotational crops is required for ensuring pesticide safety. In this study, we investigated the residue pattern of diazinon translocated into lettuce as a typical rotational crop in Korea. Diazinon was used to treat greenhouse soil at the maximum annual application rate before crop planting. Diazinon residues in soil and lettuce were investigated using liquid chromatography/tandem mass spectroscopy and a modified quick, easy, cheap, effective, rugged, safe (QuEChERS) method. The limit of quantitation (LOQ) of diazinon was found as 0.005 mg/kg for the plant and soil samples. The recovery of diazinon at the LOQ and 10× the LOQ ranged from 100.2% to 108.7%. The matrix calibration curve showed linearity, with R2 values > 0.998. Diazinon residue in soil dissipated over time after the initial treatment, generating first-order kinetics (R2 = 0.9534) and having a half-life of about 22 days. The uptake ratio (UTR) of diazinon from the soil to the plant ranged from 0.002 to 0.026 over the harvest period. Considering the UTRs, diazinon residue in the edible leaf could exceed the PLS level (0.01 mg/kg) if lettuce is rotated in soil containing >0.357 mg/kg of diazinon. Based on our findings, to comply with the PLS, a 3-month plant-back interval is required following diazinon treatment and/or setting the maximum residue limit of diazinon for lettuce.
Introduction
Monitoring pesticide residue is especially important for fresh leafy vegetables, as they are widely consumed food items. A variety of vegetable crops are being used as greenhouse cultivation crops to meet the demand imposed by the growing human population [1]. In Korea, lettuce is cultivated as a typical rotational plant consumed throughout the year. The National Agricultural Products Quality Management Service of Korea has demonstrated that, among all crops on the market, lettuce ranks as the top crop in terms of the content of unregistered pesticides [2]. The unregistered pesticides in lettuce are transported to the plant from the soil after being used for the primary crop. Thus, managing pesticides remaining in soil is necessary to prevent pesticide contamination of secondary crops with unregistered pesticides. To ensure the safety of rotational crops, the positive list system (PLS), a pesticide safety system, was implemented in Korea for all agricultural products. Under PLS regulations, agricultural products containing unregistered pesticides for which the maximum residue limit (MRL) has not been established can be sold only when pesticides levels are <0.01 mg/kg. However, amounts in excess of this threshold may enter rotational crops through an unintentional route, i.e., even if the pesticides are not sprayed directly onto the secondary crops. In Korea, a cropping system in which different crops with short growing periods are rotationally cultivated in a greenhouse is commonly used; as such, pesticides used for primary crops could remain in the soil, thus contaminating Foods 2022, 11, 3510 2 of 10 secondary crops. For soil-residual pesticides used for primary crops that are not registered for use in secondary crops and remain at levels >0.01 mg/kg, products derived from the secondary crops cannot be sold under the PLS system. Thus, methods are required to prevent unintentional contamination with unregistered pesticides when cultivating secondary crops. To address this issue, the Rural Development Administration (RDA) of Korea requires the registration of pesticides for use with secondary crops, to decrease the possibility that soil-residual pesticides may contaminate secondary crops and violate the PLS. The RDA also applies the plant-back interval (PBI) as an alternative method for preventing unregistered pesticide contamination. However, in rotational cultivation systems, this requires information on the uptake and residue patterns of pesticides remaining in soil that have been used for primary crops, to avoid violation of the PLS.
Diazinon is an organophosphorus insecticide widely used for pest control in Korea. The World Health Organization (WHO) has categorized diazinon as a moderately hazardous pollutant of Class II [3]. The number of studies have demonstrated the toxicity of diazinon in aquatic organisms, including potential acute toxicity [4,5], body length shortening and endothelial cell changes [6], enzyme reaction and gene expression changes [7], lipid and protein oxidative damage [8] and adaptation adverse effects [9]. The reduction of intestinal microorganism, involving in the production of fatty acids, and the induction of bile acid disorder, by the exposure of diazinon have been reported in mice [10,11]. Moreover, the toxicological effects of diazinon on histophysiological and biochemical parameters in mammalian animals, particularly in the liver and kidney, suggest that diazinon residue cannot be ignored in life systems [12]. Taken from these studies, monitoring diazinon residue in food products has become increasingly important to ensure the safety of human health. According to the Institute of Public Health and Environment of Korea, diazinon ranks first among the top pesticides found in agricultural products on the market in the last 3 years [13]. Their report states that diazinon residue must be monitored continuously in leafy vegetable products, as it is mainly detected in vegetables in which diazinon is not registered for use. In this study, we aimed to investigate the magnitude of soil-residual diazinon translocated into lettuce as a representative rotational crop in Korea. The acceptable soil residue of diazinon when growing lettuce (<0.01 mg/kg) was estimated on the basis of the uptake ratio between the soil and crop. In turn, the PBI of diazinon was evaluated based on this threshold and the dissipation kinetics of diazinon in soil.
Chemicals and Reagents
Diazinon standard (98.2%) was purchased from Sigma-Aldrich Corp. (St. Louis, MO, USA) and its analytical standard (1000 mg/L) was obtained from Kemidas Corp. (Gunpo, Gyeonggi-do, Korea). Organic solvents used in this study were of HPLC grade, obtained from J. T. Baker (Phillipsburg, NJ, USA). Other chemicals were of analytical grade, obtained from Sigma-Aldrich Corp. (St. Louis, MO, USA), unless otherwise stated. Sample extraction and purification were performed using Agilent QuEChERS kits (San Francisco, CA, USA). A granular diazinon (3%) was kindly provided by Sungbo Chemicals Co., Ltd. (Seoul, Korea).
Diazionon Application
A granular formulation of diazinon (3%) was mixed thoroughly with soil (1:4 (g/g) in a stainless serum bottle and applied evenly onto each plot of soil at a rate of 50 kg/10a. The applied rate was determined based on the diazinon level used in greenhouse soil consecutively for five years. The soils of each plot were mixed by using a land management machine (Dongyang Tech., Daegu, Korea), as previously described [14].
Greenhouse Conditions and Experiments
The experiments were performed at an agricultural greenhouse (Damyang, Jeonnam, Korea). The soil composition was found as sand (50.4%), silt (37.6%) and clay (12.0%), 95.08 g kg −1 organic matter, 31.63 cmolc kg −1 cation exchange capacity and pH 6.8 by the method described previously [15]. The soil was investigated as a loam texture based on its composition data. The experimental plots were designed as prepared previously [5]. The plot size was 30 m 2 with triplicates of each 10 m 2 . Lettuce was planted in the soil with the distance of 20 × 20 cm, 7 days after diazinon application. The plots were prepared to have a buffer zone (1.0 m) between each plot in order to prevent sample contamination. The greenhouse temperature and the humidity were monitored daily by a digital thermo-hydrometer during the experiment. The average temperature was 24.8 • C with the maximum 30.0 • C and the minimum 16.4 • C. The relative humidity was from about 48 to 88% during the experiments. The light was natural conditions during the experiment.
Sample Preparation
The soils were sampled by a stainless auger (Shinill Sci., INC., Paju, Korea) at a depth of 0-20 cm from eight points in each plot after diazinon treatment. The soil samples were dried overnight under dark shadow and subjected to pass through a 2 mm sieve. For the plant samples, lettuces (1 kg per plot) were collected from each plot 32,36,40,44,48,51 and 56 days after treatment (DAT) with diazinon. The samples were put in polyethylene bags with ice and immediately transported to the laboratory. The plant root and leaf samples were prepared into small cakes after washed the debris with running water. The samples were then blended using a homogenizer and stored at −20 • C until used for the experiments.
For the determination of diazinon, the samples were prepared by methods modified from QuEChERS [16,17]. The methods were optimized to meet the requirements of the Organization for Economic Cooperation and Development (OECD) that has guided pesticide residue analysis. A 10 g soil sample was mixed with 10 mL distilled water in a 50 mL centrifuge tube for 15 min. The sample was then extracted with 10 mL of acetonitrile for 2 min and 4 g anhydrous MgSO 4 and 1 g MgCl 2 was added, followed by mixing thoroughly (2 min) and centrifugation at 3500 rpm (5 min). The supernatant (1 mL aliquot) was added with 150 mg MgSO 4 , 25 mg C18 and 25 mg PSA in a centrifuge tube and mixed for 2 min before centrifugation at 8000 rpm for 3 min. The supernatant was then subjected to passing through a 0.2 µm syringe membrane filter (PTFE-H) and used for liquid chromatography/tandem mass spectroscopy analysis (LC/MS/MS). For clean-up of the plant samples, the samples were prepared as described above, replacing C18 by graphitized carbon black (GCB, 2.5 mg).
Instrumentals
A Waters model Xevo TQ-XS triple quadrupole LC/MS/MS equipped with a Waters model ACQUITY TM UPLC system was used for the sample analysis. The analytical column was a C18 stainless column (Osaka Soda CAPCELL CORE, 150 × 2.1 mm length, 2.7 µm particle size, 90 Å pore size). A solvent mixture of acetonitrile and water with 0.1% (v/v) formic acid was used as the mobile phase and flowed as: isocratic flow with 60% acetonitrile for 0.5 min, flow rate 0.3 mL min −1 , gradient flow with 95% acetonitrile for 2.5 min, isocratic flow with 95% acetonitrile for 2 min. The collision energy values were 23 eV and 38 eV for quantitative and qualitative ions of diazinon, respectively. The electron spray ionization (ESI) method at positive ion mode was used for acquiring LC/MS/MS spectra with optimized conditions as follows: capillary voltage 3 KV, de-solvation N 2 flow 650 L h −1 , ion source temperature 150 • C, cone gas flow 50 L h −1 , de-solvation temperature 350 • C and de-clustering potential value 31 eV. For optimizing LC/MS/MS, instrumental validation was conducted as guided by SANTE/11312/2021 [18]. The tolerances of ion ratio was permitted absolutely within ±30% by considering the relativity to the ratio of standard calibration. The diazinon MS ions were m/z 305.2 and m/z 169.1 for quantitative detection and m/z 305.2 and m/z 153.2 for qualitative detection, respectively. For quantitative analysis of diazinon in the samples, the matrix-matched calibration curve was applied in the range of 5 to 250 µg L −1 in the working solutions that had been diluted with the control extracts from the stock solutions (100 mg L −1 ). The limit of quantification (LOQ) at the signal-to-noise (S/N) ratio of 10:1 was calculated. The recovery tests at levels of LOQ and 10× the LOQ were conducted in triplicate.
Validation and Establishment of Methods
For quantitative and qualitative analysis of diazinon, the methods used in the current study were established and validated based on the Organization of Economic Co-operation and Development (OECD) guidelines. The quick, easy, cheap, effective, rugged, safe (QuEChERS) method for sample extraction and clean-up was modified based on trial and error. Liquid chromatography/tandem mass spectrometry (LC-MS/MS) indicated high sensitivity and selectivity of the method (Table 1). Using established methods, standard calibration of diazinon achieved good linearity (0.005-0.25 mg L −1 ) for soil and plant samples. The coefficient of determination (R 2 ) of the calibration linearity was 0.998-0.999 for all sample solutions, similar to neat organic solvent. The LOQ of diazinon in all samples was 0.005 mg kg −1 . The matrix effects for the plant samples ranged from −8.21 to −7.10, while the matrix effect was 18.44 for the soil samples. The sample matrix generally affects quantitative measurements of pesticides when the matrix effect is >±10%. Thus, the matrixmatched standard calibration should be considered to improve method accuracy. In this study, we applied the matrix-matched standard calibration to all soil samples, given that the matrix effect was >±10%. The ion ratio tolerances in all samples (relative to the ratio for solvent standard calibration) ranged from −2.21 to 0.68, with ratios within ±30% of the guidelines for pesticide analysis set by the European Commission (SANTE/11312/2021) being considered acceptable [19]. Our method confirmed the presence of diazinon in all samples. Recovery tests were performed for samples with 1× and 10× the LOQ for diazinon to investigate method reliability. The recovery of diazinon ranged from 100.2% to 108.7% ( Table 2). The relative standard deviation was <11.04%. These results met the guidelines of SANTE/11312/2021, thus validating our approach for determining diazinon levels in soil samples. (1) Data are means ± SD of triplicate; (2) Limit of quantification.
Residue and Uptake Patterns of Diazinon
Diazinon residue in soil was investigated over time to determine plant uptake patterns. Soil samples were obtained on each sampling day after treatment (DAT) and subjected to LC-MS/MS analyses. Diazinon residues decreased dramatically from the initial concentration to approximately 25% at 7 DAT, 7% at 45 DAT, and <1% at 180 DAT, as presented in Figure 1. The regression equation (C = 50.974e −0.032t ; R 2 = 0.9442) well described the first-order diazinon dissipation kinetics, where diazinon exhibited a half-life (DT 50 ) of approximately 22 days. Diazinon appeared to dissipate rapidly after treatment, even when the level exceeded that recommended in Korea.
Residue and Uptake Patterns of Diazinon
Diazinon residue in soil was investigated over time to determine plant uptake patterns. Soil samples were obtained on each sampling day after treatment (DAT) and subjected to LC-MS/MS analyses. Diazinon residues decreased dramatically from the initial concentration to approximately 25% at 7 DAT, 7% at 45 DAT, and <1% at 180 DAT, as presented in Figure 1. The regression equation (C = 50.974e −0.032t ; R 2 = 0.9442) well described the first-order diazinon dissipation kinetics, where diazinon exhibited a half-life (DT50) of approximately 22 days. Diazinon appeared to dissipate rapidly after treatment, even when the level exceeded that recommended in Korea. Diazinon residue was quantified in lettuce leaf and root over time; the residues ranged from 0.009 to 0.117 mg kg −1 in leaf samples and 0.250 to 1.573 mg kg −1 in root samples ( Table 3). The residue levels in leaf and root samples appeared high at early harvest stage, 32 DAT and 36 DAT. The residue in the leaf sample decreased continuously from the initial concentration (0.093 mg kg −1 ) to 0.032, 0.024, and 0.009 mg kg −1 at 40, 48, and 56 DAT, respectively. The residue amount in the root samples was 1.020 mg kg −1 at 32 DAT, with a peak of 1.578 mg kg −1 occurring at 36 DAT; thus, the residue fluctuated over the growth period. The residue in the root samples on the last harvest day accounted for approximately 32.1% of that in the soil on that day, which suggests that diazinon from the soil was consistently absorbed by the roots over the course of the experiment. Table 3. Diazinon residues in leaf and root samples during the harvest.
Harvest Numbers (DAT)
Residues (mg kg −1 ) * Leaf Root 1 (32) 0.093 ± 0.012 b 1.020 ± 0.033 b 2 (36) 0.117 ± 0.003 a 1.578 ± 0.0071 a 3 (40) 0.032 ± 0.017 c 0.250 ± 0.022 d 4 (44) 0 Diazinon residue was quantified in lettuce leaf and root over time; the residues ranged from 0.009 to 0.117 mg kg −1 in leaf samples and 0.250 to 1.573 mg kg −1 in root samples ( Table 3). The residue levels in leaf and root samples appeared high at early harvest stage, 32 DAT and 36 DAT. The residue in the leaf sample decreased continuously from the initial concentration (0.093 mg kg −1 ) to 0.032, 0.024, and 0.009 mg kg −1 at 40, 48, and 56 DAT, respectively. The residue amount in the root samples was 1.020 mg kg −1 at 32 DAT, with a peak of 1.578 mg kg −1 occurring at 36 DAT; thus, the residue fluctuated over the growth period. The residue in the root samples on the last harvest day accounted for approximately 32.1% of that in the soil on that day, which suggests that diazinon from the soil was consistently absorbed by the roots over the course of the experiment. Table 3. Diazinon residues in leaf and root samples during the harvest.
The uptake pattern of diazinon was investigated based on the residue in the plant relative to soil. The uptake ratio (UTR) of diazinon was calculated as UTR = A × B −1 , where A is the residue in plant parts and B is the residue in soil before planting. The UTR of diazinon over the growth period is presented in Table 5. The UTR in the leaf sample was 0.026 at 32 DAT, with a peak of 0.028 at 36 DAT followed by a steady decrease to 0.008 and 0.002 at 40 and 56 DAT, respectively (R 2 = 0.8828). The UTRs of the root samples were higher than those of the leaf samples, ranging from 0.039 to 0.389. The UTR of the root samples peaked at 36 DAT; notably R 2 = 0.3266 for the UTR, which was significantly lower than that of the leaf samples. The UTR of the root samples fluctuated during the harvest period, suggesting that roots take up diazinon continuously. The different UTR patterns between the leaf and root samples imply that diazinon accumulates in roots and is partially translocated into leaves.
Plant Back Interval of Diazinon
The PBI of diazinon was estimated to investigate when lettuce, as a secondary crop, may be safely planted in greenhouse soil containing diazinon. The highest UTRs among the calculated values were subjected to compare with the PLS level (0.01 mg kg −1 ) to determine the maximum soil residue (MSR), where MSR = 0.01 mg kg −1 × UTR −1 . The MSR represents the diazinon residue transferable to lettuce at a concentration lower than the PLS level. The PLS level was applied to estimate the MSR, because the MRL of diazinon has not yet been set for lettuce in Korea. The MSR was then applied to the diazinon dissipation equation in soil (Figure 1), where MSR = 50.974e −0.032T ; T refers to the PBI. The MSR value was 0.357 and 0.026 mg kg −1 for the leaf and root, respectively ( Table 6). The uptake of diazinon generated a PBI of 93.9 and 177.7 days for the leaf and root, respectively. These results suggest that, when the primary crop is treated with diazinon, a >3-month interval after harvesting of the primary crop is necessary before lettuce can be cultivated in the same soil, given the MSR level. Our study suggest that guidelines for the safe use of diazinon in lettuce are required, given that lettuce is usually rotated into cultivation 7-14 days after the harvesting of primary crops in Korea. (1) The highest UTRs are used from Table 5; (2) positive list system level; (3) maximum soil residues taken by the plants lower than 0.01 mg kg −1 ; (4) plant-back intervals.
Discussion
Lettuce is usually rotated into cultivation within a few weeks after primary crop cultivation in greenhouses in Korea. Lettuce is an important income crop for farmers because it is consumed throughout the year. However, unregistered pesticide levels in lettuce are among the highest for all crops. Unregistered pesticides may violate the PLS threshold for agricultural products; only crops with levels <0.01 mg/kg can be brought to market. Diazinon is one of the top 10 unregistered pesticides in crops on the market. It is mostly found in vegetables, such as lettuce and spinach. Thus, managing the residual diazinon in soil after its application to primary crops is required for safe rotational cultivation of vegetables in greenhouses. We studied the uptake of soil-residual diazinon in lettuce, as a typical rotational crop. LC-MS/MS methods were validated and developed for this purpose, in accordance with OECD guidelines. The methods are capable of quantitatively and qualitatively detecting diazinon without interfering with the samples, as evidenced by the matrix effects and ion ratio tolerance ratios.
Diazinon dissipated rapidly in soil after treatment, exhibiting a half-life of 22 days. Previous studies demonstrated rapid dissipation of diazinon in soil after treatment by microbial oxidation and hydrolysis [20][21][22][23]. Adsorption and volatilization are also important for the rapid dissipation of diazinon in agricultural soil [24,25]. Based on our data and the results of previous studies, the accumulation of diazinon in soil is not significant.
Diazinon residues in lettuce fluctuated during the harvest period, different from the residue patterns in soil. Diazinon uptake is likely greatest in the initial period after treatment, where the amounts in soil were low during the harvest. Diazinon uptake by carrot was high in the early growth stage [26], which is related to the high residue in soil in that stage. In this study, diazinon levels differed significantly between leaf and root, such that transport of diazinon from root to leaf may not be concentration-dependent. The peak UTR of diazinon in leaf was 0.028, while that of root was 0.389. These results suggest that the root took up diazinon continuously as the plant grew during the experiments. Moreover, diazinon dilution appeared to occur during plant growth, as in other studies [27,28]. The dilution effect was higher in leaf than root, probably due to leaf growth. Diazinon has a water solubility of 40 mg L −1 and octanol-water (log K ow ) partition coefficient of 3.81 [29], indicating high sorption to soil [30]. There is a positive relationship between K ow and the UTR [31]. High sorption of diazinon to soil could contribute to its rapid dissipation therein. Meanwhile, lettuce root hair would contact soil organics containing diazinon and affect the UTR. This hypothesis could explain approximately 32-42%, of the diazinon in soil, accumulated in lettuce root, relatively higher than the levels in lettuce leaf. Diazinon uptake by carrot was found higher on the root outer layer than the inside root body, meaning that direct contact of root with soil residue may contribute to the uptake [32]. The translocation of 14 C-ring-labeled diazinon by bean plants documented the presence of diazinon only in the primary leaves by two days but not thereafter, persisting mostly in the roots [33]. Leaf vegetables such as lettuce spinach have been known to be a typical plant that takes pesticide moderately [34,35], but dissipation of pesticide is generally faster in lettuce than in other plants [36]. The residue behavior of methoxyfenozide and pymetrozine in Chinese cabbage was conducted for their risk assessment, demonstrating temperature-dependent dissipation, leading to low health risk [37]. The uptake of total soil-residual dinotefuran by lettuce has recently demonstrated that about a 24-28% level of initial concentration was translocated into leaves 30 and 60 days after treatment [38]. This high uptake ratio was explained by high water solubility and lower sorption to soil organics [39,40]. Thus, the evaluation of soil-residual pesticide in leaf vegetables is important for pesticide safety in agricultural products. In this study, diazinon in soil was taken up continuously by lettuce during the experiment, and the uptake was dependent on the soil-residual amount. Thus, managing diazinon residue in treated soil is necessary for safe rotation of lettuce in the greenhouse setting.
We aimed to identify an MSR resulting in lettuce diazinon uptake amounts <0.01 mg/kg, as stipulated by the PLS; the MSR satisfying this threshold was estimated as 0.357 mg kg −1 for lettuce leaf and 0.026 mg kg −1 for lettuce root. Considering the dissipation kinetics, a diazinon residence time in soil of 93.9 days for leaf and 177.7 days for root would be needed to achieve this MSR in soil; thus, a PBI of ≥3 months is needed to comply with the PLS. Efforts should also be made to reduce diazinon residue in soil to below the MSR before cultivating lettuce. An MRL for diazinon is required for lettuce. According to the OECD calculator [41], the MRL of diazinon for edible leaf parts was 0.3 mg kg −1 . However, governmental input is needed for setting the MRL. According to the OECD guidelines [42], the PBI should be studied over a 7-30 day period for lettuce, given that it is a rotational crop. Following OECD guidelines, the RDA of Korea recommends conducting PBI studies over 30 and 60 days for lettuce and spinach, respectively [43,44]. Based on soil dissipation and UTR values for diazinon, we estimated a PBI of diazinon for lettuce complying with the PLS threshold.
The PLS was implemented in Korea in 2020 to promote safe pesticide use for all agricultural products intended for the market. However, the threshold of 0.01 mg kg −1 may be exceeded in rotational crops due to the uptake of residual pesticides in soil used for treating primary crops, as stated above. This may be especially common in Korea, where farmers cultivate a variety of rotational crops in greenhouses. Thus, studies on the uptake patterns of pesticides by secondary crops are needed to satisfy the PLS threshold. Here, we examined plant uptake of diazinon, as a typical unregistered pesticide that can accumulate in lettuce. Diazinon dissipated rapidly in the soil after treatment, and was taken up by lettuce over the growth period. To comply with the PLS threshold, a PBI of ≥3 months is needed for lettuce grown in greenhouse soil containing diazinon in an amount equivalent to the MSR. An MRL for diazinon should be set for lettuce grown in greenhouses, as an alternative to application of the PBI. Furthermore, a strategy for accelerating the dissipation of diazinon in soil [45] or suppressing diazinon uptake by the plant [46] would be helpful to satisfy the PLS threshold.
Conclusions
Diazinon in soil dissipated through first-order degradation kinetics and had a half-life of approximately 22 days. Diazinon was taken up continuously by lettuce during the growth period, and uptake was higher by root than leaf. The peak UTR was 0.028 for leaf and 0.389 for root. The UTRs were used to estimate the MSR that would prevent the PLS threshold (0.01 mg kg −1 ) for lettuce being exceeded; the estimated MSR was 0.357 mg kg −1 for leaf and 0.026 mg kg −1 for root. The PBI was calculated as 93.9 days for leaf and 177.7 days for root. Although diazinon dissipated rapidly in soil, continuous uptake throughout the harvest period suggests that soil-residual diazinon should be monitored carefully to comply with the PLS threshold, and we suggest a PBI of ≥3 months for rotational cultivation of lettuce in greenhouse soil. Methods to accelerate the degradation of diazinon in soil or decrease uptake by the plant would also be helpful, to ensure that lettuce planted after primary crops have been treated with diazinon is safe for consumption. An MRL of diazinon for lettuce should also be set.
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Domain: Agricultural And Food Sciences
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Structure and properties of flat cocoon silk after silk reeling
Silk is obtained mostly from oval cocoons. In this paper, the flat cocoons were obtained by changing the silking environment of Bombyx mori silkworms. Then the appropriate method was used to reel the flat cocoons. The structure, thermal and mechanical properties of flat cocoon silk (FCS) after silk reeling and degumming were studied. The experimental results have shown that flat cocoon silk has the same main composition and similar thermal performance as that of common cocoon silk (CCS), but the sericin distribution on the surface of FCS is more uniform, the crystallinity degree of the FCS (53.77%) is slightly higher than that of the CCS (50.02%), and the cross-sectional areas of the FCS before and after degumming are smaller than those of the CCS. Before degumming, the stress of FCS is about 1% higher than that of CCS, the initial modulus is about 4.7% higher, and the strain is about 10.7% lower. After degumming, the stress of FCS is about 2.7% higher than that of CCS, the initial modulus is about 7.8% higher, and the strain is about 31.3% lower. The results have shown that FCS after silk reeling has application performance close to or even better than that of CCS.
Introduction
Beside the traditional textile industry, silk has become a new material that can be used in many high-tech industries [1][2][3][4][5]. Results of proteomic studies show that silk is a complicated protein complex, and contains many biologically active protein components besides fibroin and sericin. Natural sericin protein has good biocompatibility, and has been used in beauty, skin care, anti-inflammatory and health care products. Sericin films, tissue engineering scaffold materials, etc made from sericin protein have also been used in the field of biomedicine [6]. Modification of sericin can improve the properties of sericin films and further increase their applicability [7][8][9][10][11].
Fibroin, of which is in high concentration in silk, also has a wide range of applications. Fibroin protein has long been used in the field of cosmetics. Fibroin protein is also a good optical material, and its immobilized enzyme can be used to make enzyme sensors. Fibroin can be widely used in the field of medicine and the preparation of biological materials [12,13]. Fibroin protein can also inhibit the growth of microorganisms [14].
Mature Bombyx mori silkworms spin silk in a three-dimensional space, forming oval cocoons. Silk is obtained mostly from oval cocoons. However, due to the differences in varieties of Bombyx mori silkworms, the amount of silk production will be different. The way of body movement and the change of place during silk spinning will have an impact on the shape and the properties of cocoons [15][16][17][18]. If the silking place is limited to two-dimensional space, mature Bombyx mori silkworms can hardly find the best place of cocooning and will spin out a piece of silk on a flat surface, which is the so-called flat cocoon. After silk spinning, Bombyx mori silkworms will transform into pupa above the flat cocoons. Van Der Kloot, W G et al systematically studied the rule of silk spinning of the Cecropia silkworms and found that the silkworms spin silk into outer, middle and inner layers, and the amount of silk spinning and non-repeatability of each layer of flat cocoons were the same as those of oval cocoons [19]. Bin Zhou et al verified that flat cocoons had the multi-layer structure and characteristics similar to those of common oval cocoons. The fiber characteristics and performance change rules of the flat cocoon silk from the outer layer to the inner layer were completely consistent with those of common oval cocoons. They believed that flat cocoons were also constructed by the silkworm according to the same 'programmed' process as common oval cocoons [20]. Zongpu Xu et al combined flat cocoons with resin to form films as flexible and transparent reinforcing materials for substrates on electronic devices, with a significant increase in tensile strength and modulus compared with pure resin, while maintaining flexibility and transparency [21].
In a traditional silk production process, such methods as cocoon drying, cocoon boiling, silk reeling and skein finishing are used to obtain raw silk from dry cocoons [22]. However, this process is complicated. Therefore, a fresh cocoon reeling process is developed, that is, fresh cocoons are directly reeled after vacuum hot water osmotic treatment without pupae killing and drying, and then processed into raw silk [23,24]. If the fresh cocoons can't be reeled immediately, they need to be stored or frozen in the cold storage. Therefore, the fresh cocoon reeling process has high demands on the the cold storage [25][26][27][28]. If flat cocoons could be used for silk reeling, processes such as cocoon drying, cocoon boiling and cold storage will be eliminated.
There have been no previous studies on silk reeling of flat cocoons. In this paper, flat cocoons with uniformly distributed silk were obtained through experiments, and were reeled using improved traditional silk reeling method. The microstructure, and mechanical and thermal properties of the FCS were tested and compared with those of CCS, which will provide theoretical support for further development and utilization of FCS. The method of flat cocoon reeling in this study can also provide a new way to obtain and use other kinds of cocoons that cannot be reeled, such as Eri-silkworm cocoons.
2. Experiments 2.1. Materials 100 Bombyx mori silkworms (Sericultural Research Institute, Chinese Academy of Agricultural Sciences), 40 smooth-surfaced round disks with a diameter of 8 cm, and a wood cocooning frame.
Preparation of flat cocoons and common cocoons
The mature Bombyx mori silkworms were divided equally into two groups, one group was placed on the wood cocooning frame for normal silk spinning and cocooning, and the other group was placed on round disks, with one mature Bombyx mori silkworm on each disk to make flat cocoons. A plastic case was placed below each disk, so that the disk was about 15 cm from the table, and a mature Bombyx mori silkworm was placed on each disk after urination. After 3 to 4 days, the mature Bombyx mori silkworms finished spinning. Then the pupae on surfaces of flat cocoons were taken away, and the flat cocoons were reserved. The processes of silk spinning for making flat cocoons and common cocoons are shown in figure 1.
Preparation of silk fibers 2.3.1. Silk reeling
Flat cocoons and common cocoons were placed in hot water at about 85°C simultaneously. 30 min later, the flat cocoons were fully soaked, and the common cocoons could be reeled smoothly. Silk reeling of flat cocoons in water will result in intertwined silk, so that the fully soaked flat cocoons need to be taken out of the water bath environment, placed on the disks upside-down, and reeled, with the help of a magnifying glass, by extracting a strand of silk from the top layer. In order to ensure that the CCS and the FCS were always in the same environment, when the flat cocoons were taken out of the water bath environment, the common cocoons were also taken out for silk reeling. The two kinds of silk were wrapped on a bottle with the diameter of 5 cm respectively. Repeat this experiment, 40 groups of flat cocoons and common cocoons were reeled into silk fibers for later use. The processe of silk reeling is shown in figure 2.
Degumming
10 meters silk from each group of FCS and CCS obtained by reeling were placed in a beaker respectively, and then were treated with 5 g l −1 Na 2 CO 3 solution at 100°C for 3 times, 30 min each time, during which the solution was unceasingly stirred with a glass rod, and then the silk was rinsed with distilled water and placed on absorbent paper until it was completely dried [29][30][31][32][33].
Property tests 2.4.1. Cocoon and silk specifications
Twenty common cocoons that had pupae removed and twenty flat cocoons were taken and tested for thickness using a fabric thickness instrument (YG(B)141D, Wenzhou Darong Textile Instrument Co., Ltd.) in accordance with GB/T 3820-1997 Determination of Thickness of Textiles and Textile Products, with pressure weights of 25 cN and pressing time of 10 s. An electronic balance (ESJ30-5 A, Shanghai Precision Instrument Co., Ltd.) was used to measure the weight of flat cocoons and common cocoons. A microscope equipped with CU fiber fineness software was used to obtain the cross-sectional area data of 200 silk fibers from different samples.
Scanning electron microscope
A scanning electron microscope (SEM, Japan/SU8010) was used to observe the microscopic morphology of gold-sprayed common cocoon, flat cocoon and dried degummed cocoon silk at a voltage of 5 kV.
Thermogravimetric analysis
A thermogravimetric analyzer (NETZSCH STA 449F3) was used to test the thermogravimetric properties of the two kinds of cocoon silk at a heating rate of 10°C min −1 and a nitrogen flow of 20 ml min −1 .
Infrared spectra
A US Nicolet iS5 Fourier Transform Infrared Spectrometer (FT-IR) was used to test the two kinds of cocoon silk samples under the following test conditions: room temperature, ATR test method, wave number range of 500-4000 cm −1 , scanning per acquisition of 32 and spectral resolution of 4 cm −1 . Absorption spectra were obtained by transformation using OMNIC 6.0 (Nicolet Instrument Co., USA) software.
X-ray diffraction
The two kinds of degummed cocoon silk samples were cut into powder and tested using an x-ray diffractometer
Mechanical property test
A fiber stretcher (YG004, Changzhou Dahua Electronic Instrument Co., Ltd.) was used to test the mechanical properties of FCS and CCS under the following test conditions: environment temperature of 22°C, and relative humidity of 50%. Before the test, the FCS and CCS both before and after degumming were balanced in the test environment for 24 h. The tensile speed was 10 mm min −1 and the gauge length was 20 mm. Samples were taken from 40 groups of silk for testing. SPSS software was used to test the abnormal value and analyze the coefficient of variation of the test data.
Results and discussion
3.1. Structure comparison of flat cocoons and common cocoons The appearance comparison of flat cocoon and common cocoon is shown in figure 3, and the specification comparison is shown in table 1. It can be seen from figure 3 that there is an obvious difference in shape between the flat cocoon and the common cocoon. The common cocoon is an ellipsoid, while the flat cocoon is a circular flat. The comparative data in table 1 show that the thickness of the flat cocoon is about one-third of that of the common cocoon, and its weight is slightly lighter. This is because the Bombyx mori silkworms were not placed on the disks until the urination was completed. At this time, the Bombyx mori silkworms had spun out some or even all of the outer layer cocoon silk. The common cocoons are relatively hard and difficult to deform, while the flat cocoons are soft and easy to bend, but they also have enough strength to keep circular. The microstructure comparison of a flat cocoon and a common cocoon is shown in figures 4(a) and (b). It can be seen from the SEM image that the silk of both the flat cocoon and the common cocoon is stacked in a regular cross-layer shape. The comparison shows that the silk of common cocoon is more closely connected. The cross angle of FCS is smaller than that of CCS, and the straightness is higher than that of CCS, which is due to larger movement area when the Bombyx mori silkworms make flat cocoons. Both the FCS and CCS are formed by two parallel fibroins wrapped by outer sericin. The sericin on the FCS is evenly distributed, while there is multiple obvious sericin protrusions on the CCS. Figures 4(c) and (d) show the microstructures of FCS and CCS after degumming. It can be seen from the figures that both FCS and CCS after degumming are free of sericin bond and are in a good monofilament state. The comparative data in table 1 show that the cross-sectional areas of FCS before and after degumming are both smaller than those of CCS, which may be due to the large cocooning space and the large swing amplitude of the head when the silkworm is cocooning the flat cocoon, so that the silk is subject to greater stretching, and the silkworm can maintain such a spinning posture for most of the cocooning time, so that the stretching force of the FCS is more uniform, and the silk has a better straight state. However, during the formation of common cocoons, due to the influence of the internal structure of cocoons, the swing amplitude of silk is not uniform, resulting in a large difference in silk elongation. Figure 5 shows the thermodynamic analysis curves of FCS and CCS. The thermal decomposition can be roughly divided into three stages along the temperature axis: in the first stage (0°C-100°C), the termination temperatures of the two kinds of silk fibers are both 100°C, and the weight loss rate is about 5% for CCS and about 10% for FCS. The weight loss rate in this stage may be caused by the release of the water bound by physical adsorption in the silk fibers. In the second stage (100°C-320°C), the decomposition rates of both silk fibers are the highest in the range of 250°C to 320°C, which is of great significance for evaluating the heat resistance and thermal stability of the silk fibers. At the end of this stage, the weight loss rate of FCS is about 18%, while that of CCS is about 20%, indicating that there was no significant difference between the two fibers. Compared with FCS fibers, CCS fibers have slightly poor arrangement and stacking structure between macromolecular bonds, therefore, the thermal stability of FCS is slightly better than that of CCS. The extrapolated onset temperature of weight loss rate is related to the β-sheets structure of protein. According to figure 5, the extrapolated onset temperature of weight loss rate is about 293°C for CCS and 301°C for FCS. Therefore, it can be inferred that the β-sheets structure of protein of CCS is less than that of FCS. In the third stage (320°C-620°C), the decomposition rates of both silk fibers are slowed down. Figure 6 shows that the infrared spectra of FCS and CCS are similar in peak shapes and peak positions on the whole, both have some typical characteristic peaks, and no characteristic peak displacement has occurred, indicating that basic structures of the two kinds of silk have not changed. Both of the infrared spectra have characteristic absorption peaks at 1620 cm −1 , 1508 cm −1 and 1226 cm −1 . The absorption peak near 1620 cm −1 is an amide I α-helix structure caused by C=O vibration, the absorption peak near 1508 cm −1 is a protein amide II β-sheets structure caused by C-N stretching vibration and N-N vibration, and the protein amide III band absorption peak near 1226 cm −1 is caused by N-H and O-C-O vibration in the protein peptide bond. Figure 7(a) shows the x-ray diffraction curves of FCS and CCS of Bombyx mori. It can be seen from figure 7 that the diffraction angles of the principal peaks of the FCS and CCS are very close, which are respectively 20.496°and 20.438°, indicating that the main structures of the two are similar without significant changes, but the diffraction intensity of FCS is higher than that of CCS. Software Jade was used for full spectrum fitting of diffraction peaks within the test range, as shown in figures 6(c) and (d), pseudo-Voigt function was used to describe diffraction peaks, and finally the integral area values of crystalline peaks and non-crystalline peaks were obtained and the crystallinity degrees were calculated. The crystallinity degree of FCS is 53.77% and that of CCS is 50.02%, as shown in figure 6(b). The calculation results show that the crystallinity degree of FCS is slightly higher than that of CCS, but there is little difference. The reason for the difference may be that the silk fibers of the flat cocoon have a higher relative content of β-sheets and a lower relative content of α-helix, thus affecting the regularity of macromolecular arrangement.
Mechanical properties
The stress-strain curves are shown in figure 8, and the tensile property comparison of FCS and CCS before and after degumming is shown in table 2. Compared with those of the CCS, the average stress of FCS before degumming is about 1% higher, the average initial modulus is about 4.7% higher and the average strain is about 10.7% lower. The stress difference between FCS and CCS is not obvious, and the variations range of stress error of FCS is smaller than that of CCS. Presumably, the main reason is that when a Bombyx mori silkworm spins silk on a flat surface, the space becomes larger and the cocoon thickness decreases, silk of the cocoon layers is subjected to a more uniform stretching force, and silk straightness is higher; or the sericin on the FCS is more evenly distributed, reducing the weak link phenomenon during the stretching. Before degumming, there is no significant difference in the strain of FCS and CCS, and the variations of strain of FCS is still smaller than that of CCS. After degumming, the average stress of FCS is about 2.7% higher than that of CCS, the average initial modulus is about 7.8% higher and the average strain is about 31.3% lower. The stress and initial modulus of degummed FCS are higher than those of CCS, and the strain is lower than that of the CCS. This is because the crystallinity degree of fibroin part of FCS is slightly higher, the molecular arrangement is more regular, the bond between molecules is stronger, and molecular chain segment is not easy to slide when stretched by external force. In addition, the cross-sectional area of single FCS after degumming is smaller than that of the CCS, which also leads to an increase in its stress.
Conclusion
After the environment in which Bombyx mori silkworms spin silk is changed, the properties of silk will be affected. In this paper, Bombyx mori silkworms were placed on disks with smooth surfaces to obtain flat cocoons. Through SEM observation, it was found that the silk of both flat cocoons and common cocoons was interlaced and layered, and the silk fibers were evenly distributed; the cross angle of FCS is smaller than that of CCS, and the straightness is higher than that of CCS; the sericin on the surface of FCS was evenly distributed, while there were some unevenly distributed sericin on the CCS. The flat cocoons and common cocoons were reeled and degummed in the same way, and the properties of the two cocoons before and after degumming were compared.
The thermogravimetry experiment showed that the thermal stability of FCS was similar to that of CCS. The infrared spectrum and x-ray diffraction experiments showed that the main components of FCS were the same as those of CCS, but the crystallinity degree of FCS was slightly higher than that of CCS. The results of mechanical experiments showed that FCS showed higher stress and initial modulus and lower strain compared with CCS after degumming. The results of this study have shown that FCS after silk reeling has application performance close to or even better than that of CCS. In the later research, a more suitable method can be attempted to reel the flat cocoons, or silk membrane with a wider range of area and thickness can be obtained by changing the area of silk spinning place, increasing the number of mature Bombyx mori silkworms in the silk spinning place. This study may provide a new way for industrial development and utilization of silkworm cocoons that have structural defects and can't be continuously reeled silk to manufacture silk products, such as Eri-silkworm cocoons.
Data availability statement
All data that support the findings of this study are included within the article (and any supplementary files).
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Domain: Agricultural And Food Sciences
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Comparative epidemiology of porcine circovirus type 3 in pigs with different clinical presentations
Porcine circovirus type 3 (PCV3), as an emerging circovirus species, was reported to be widely circulating in the United States, China, South Korea and Poland. Previous studies revealed that PCV3 was mainly concentrated in sick animals with respiratory disease, skin disease, reproductive disorders and so on. However, the circulating status of PCV3 in pigs with other clinical presentations (especilly asymptomatic or diarrhea) was not well established. In this study, to conduct a comparative epidemiological survey of PCV3, 80 weaned pig serum samples with severe respiratory disease (SRD), 175 weaned pig serum samples with mild respiratory disease (MRD), 216 asymptomatic weaned pig serum samples, 35 diarrheal weaned pig samples and 35 non-diarrheal weaned pig samples were collected from eight provinces of China. Via qPCR testing, PCV3 was circulating in all sampling provinces, with total positive rates varying from 1.04% to 100%. Interestingly, the PCV3-positive rate was significantly higher in weaned pigs with SRD (63.75%, 51/80) than in those weaned pigs with MRD (13.14%, 23/175) and asymptomatic pigs (1.85%, 4/216) (P < 0.01). Similarly, the PCV3-positive rate was significantly higher in diarrheal weaned pigs (17.14%, 6/35) than in non-diarrheal weaned pigs (2.86%, 1/35) (P < 0.05). Moreover, the lower Ct values of qPCR were frequently found in those weaned pigs or fattening pigs with respiratory disease and diarrhea rather than that in asymptomatic pigs. Sequence analysis showed that low genetic diversity existed among those PCV3 sequences collected from pigs with different clinical presentations. The present study further extends evidence that newly described PCV3 widely circulates in six additional provinces of Southern and Northern China and has high similarity to previously reported isolates. As an emerging virus of swine, although the present case-control study reveals that PCV3 has a potential association with swine respiratory disease and diarrhea, further investigations into the pathogenesis are needed to ascertain the role of PCV3 in swine health.
Background
At present, small non-enveloped DNA circoviruses of concern to animal and human health are classified in two genera (Circovirus and Cyclovirus) in the Circoviridae family. The genus Circovirus consists of 27 species, while the genus Cyclovirus has 43 species [1]. Porcine circoviruses are members of the genus Circovirus with two recognized species, porcine circovirus type 1 (PCV1) and porcine circovirus type 2 (PCV2). PCV1 can infect and replicate in swine, but is not known to cause any obvious disease [2]. While PCV2 infection can result in significant production and economic losses to the worldwide swine industry [3,4]. Clinically, PCV2 can cause porcine circovirus disease (PCVD) or porcine circovirusassociated disease (PCVAD), which is characterized by postweaning multisystemic wasting syndrome (PMWS), porcine dermatitis and nephrotic syndrome (PDNS), interstitial pneumonia, and reproductive disorders [5,6].
Recently, a novel circovirus significantly divergent from PCV1 and PCV2, provisionally designated porcine circovirus type 3 (PCV3), was identified in U. S. swine herds [7,8]. The full-length genome sequence of newly found PCV3 was 2000 nucleotides, which was considerably larger than those of PCV1 and PCV2 (~1760 and 1780 nucleotides, respectively) [9]. Actually, prior to identification of PCV3, PCV3-like sequences were also reported in different farmed animals several years ago, which revealed possible early distribution of PCV3 in animal species [10,11]. It is interesting that PCV3, similar to PCV2, has a potential association with multisystemic disease, PDNS and reproductive failure in pigs [7,8]. At present, PCV3 also has been reported in China, South Korea and Poland, accompanying with widely geographical distribution [12][13][14][15][16][17]. Despite good progress in PCV3 epidemiology, the circulating status of PCV3 in pigs with different clinical presentations (especilly asymptomatic or diarrhea) was not well established. Therefore, the present study aims to perform comparative epidemiology of PCV3 in pigs with different clinical presentations.
Methods
In 2016, two small-scale fattening pig farms (about 200 or 300 American Landrace pigs in total), locating in Guangdong province (southern China) and Jilin province (northern China) separated by more than 3, 000 km in distance ( Fig. 1), suffered from severe respiratory disease (SRD). Pigs (2-3 months old) on both farms have received immunizations against PCV2, pseudorabies virus (PRV), classical swine fever virus (CSFV) and type 2 porcine reproductive and respiratory syndrome virus (PRRSV). However, the morbidity rate of pigs on the two farms was approximately 60%, the mortality in affected pigs was about 80%. From autopsy results of 18 individual dead pigs (n = 8 for farm A, n = 10 for farm B) (Additional file 1: Table S1), the similar macroscopic lesions were concentrated in the lungs and lymph nodes, which was characterized by PRRSV-or PCV2-like lesions including pulmonary interstitial widening, congestion and lymphadenopathy bleeding. These 18 pig lung samples were defined as the samples with SRD. To compare the detection results of PCV3 based on the same Table S1) were collected from Shandong province (n = 26), Gansu province (n = 120), Guangxi zhuang autonomous region (n = 34), Guangdong province (n = 130), Sichuan province (n = 65) and Yunnan province (n = 96) (Fig. 1). Moreover, 35 diarrheal weaned pig (6-7 weeks old) samples and 35 non-diarrheal weaned pig (6-7 weeks old) samples (Additional file 1: Table S1) were collected from Gansu province (n = 40) and Neimenggu autonomous region (n = 30) (Fig. 1). The above-mentioned samples were stored −80°C until further use.
Prior to quantitative PCR (qPCR), 200 μL tissue supernatants or serum samples were used to perform viral DNA extraction according to the manufacturer's instructions (TIANGEN Biotech Co., Ltd. Beijing, China). Viral DNA samples were stored at −80°C until use. A previously established qPCR protocol was used, consisting of two specific primers (Forward, 5′-AGTGCTCCCCATT GAACG-3′; Reverse, 5′-ACACAGCCGTTACTTCAC-3′) and one modified probe (5′-FAM-ACCCCATG GCTCAACACATATGACC-BHQ1-3′) [8]. Moreover, the detection of PRRSV was performed according to a previous method [18]. The full-length genome sequence of PCV3 was amplified using the two pairs of overlapping PCR primers according to a previous description [13]. These two PCR fragments were cloned and sequenced. The corresponding sequencing results were spliced using SeqMan program (DNAStar software version 7). Sequence alignment and phylogenetic analysis based on three species of PCV sequences were performed using Clustal W program implemented in DNAStar software and MEGA 5.1 software, respectively. In addtion, qPCR detection results in pigs with different clinical presentations were analyzed by chisquare (χ 2 ) test (Ziyue software), the value of P < 0.05 and P < 0.01 was considered significant and very significant, respectively.
To further genetically characterize PCV3 in those positive samples with low Ct values (< 22), two representative genome sequences (PCV3-CHN/GD2016 and PCV3-CHN/CC2016) were obtained from south China and north China, respectively, and were deposited into GenBank database under accession numbers KY421347-KY421348. Like previously reported PCV3 sequences, their genomes were 2000 nucleotides in length. Multiple sequence alignment results showed that the two current PCV3 genome sequences shared > 97% nucleotide similarity with other known PCV3 sequences, revealing low levels of genetic variation among PCV3 isolates. Online Blastn alignment results showed that they mainly differed in ORF2 gene that encodes viral capsid protein (Data not shown). In addition, phylogenetic analysis showed that PCV3-CHN/GD2016 and PCV3-CHN/ CC2016 clustered with those PCV3 isolates from the United States and Korea, and were distantly related to PCV1 and PCV2 (Fig. 3).
Discussion
Previous studies suggested that PCV3 was common in PDNS cases and that it might play a role in reproductive failure and multi-systemic inflammation in U. S swine herds [7,8]. Although there were other swine pathogens (including torque teno sus virus 1, TTSuV1; porcine hemagglutinating encephalomyelitis virus, PHEV; porcine astrovirus 4, PAstV4) present in PCV3-infected tissues, high numbers of PCV3 sequence reads by metagenomic sequencing suggested that PCV3 might play a potentially pathogenic role in those clinical cases [7,8]. Similarly, immunohistochemistry localized PCV3 in typical PDNS lesions in the absence of PCV2 [8]. However, in four latest studies from China, single PCV3 infection and/or co-infection with PCV2 were reported in clinical cases [12,13,15,16]. Surprisingly, during one of four studies, PCV3 had an abnormally high positive rate (85.7%, 12/14) in pig samples with productive failure, but PCV2, PRRSV and PRV were negative in these pigs [15]. In this study, we identified co-infection of PCV3 with PRRSV in SRD pigs, not in other pigs. Coinfection of pigs with PCV2 and PRRSV is known to exacerbate disease severity [19,20]. A possible synergy between PCV3 and PRRSV or PCV2 co-infection with disease severity warrants further investigation. Additionally, low Ct values of PCV3 were frequently found in Fig. 3 Phylogenetic analysis based on complete genome sequences of PCV1, PCV2 and PCV3. The phylogenetic tree was constructed by the Maximum Likelihood method using MEGA 5.1 software. One thousand bootstrap replicates (1000 times) were used to assess tree topology. Only bootstrap scores of at least 50 were retained. Scale bar indicates 10% nucleotide sequence divergence. The PCV3 isolates of PCV3-CHN/GD2016 and PCV3-CHN/CC2016 obtained in this study are indicated by gray shading diseased pigs, not in asymptomatic pigs (Fig. 2b), which revealed that the high titers of PCV3, similar to PCV2, could contribute to the occurrence of clinical diseases in pigs [21]. Another interesting finding was that PCV3 was detected in fecal samples, which may suggest for a fecal-oral transmission by PCV3.
Conclusions
To conclude, the present study further extends evidence that newly described PCV3 widely circulates in six additional provinces of Southern and Northern China and has high similarity to previously reported isolates. As an emerging virus of swine, although the present case-control study reveals that PCV3 has a potential association with swine respiratory disease and diarrhea, further investigations into the pathogenesis are needed to ascertain the role of PCV3 in swine health. Similar to PCV2 [22], the usage of viral infectious clone accompanying by clinical and histological methods could resolve this scientific issue.
Additional file
Additional file 1: Table S1.\===
Domain: Agricultural And Food Sciences. The above document has 2 sentences that start with 'As an emerging virus of',
2 sentences that start with ' The full-length genome sequence',
2 sentences that end with 'diarrhea) was not well established',
2 sentences that end with 'similarity to previously reported isolates',
2 paragraphs that end with 'pigs with different clinical presentations'. It has approximately 1623 words, 75 sentences, and 15 paragraph(s).
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Deciphering bacteria associated with a pre-parasitic stage of the root-knot nematode Meloidogyne hapla in nemato-suppressive and nemato-conducive soils
bacteria
Introduction
Plant-parasitic nematodes (PPN) are very important pests of many cultural and natural plants (Wilschut and Geisen, 2020). A recent estimation of the yield losses caused by PPN worldwide is lacking, but it has been reported to reach billions of US dollars (Bernard et al., 2017). The root-knot nematodes (RKN) form a very important group of PPN due to their ubiquitous nature and wide host range, being able to reproduce sexually (amphimixis) and asexually (mitotic and meiotic parthenogenesis). Apart from the mature adult male, the infective second-stage juvenile (J2) of RKN is the only stage that resides in soil upon hatching (pre-parasitic stage). When J2 start feeding in the vascular cylinder of the host roots, they indulge in a sedentary lifestyle without the ability to move. During the sedentary phase, juveniles grow into a swollen appearance. Adult males, if present, regain a vermiform shape and mobility, whereas adult females remain swollen and sedentary and produce a large number of offspring. Although PPN are obligate biotrophs that cannot survive without the plant, they spend an extended amount of time in soil before migrating to the roots (the exophytic phase) (Vestergård, 2019). In this case, the subsequent development of the RKN population strongly relies on the capacity of the pre-parasitic J2 to overcome the adverse biological conditions in soil (predators, parasites, hyperparasites) prior to infecting the plant. Thus, the exophytic phase of RKN is important from the aspect of biological control, as various bacteria and fungi have been reported to antagonize J2 while residing in soil (Topalović et al., 2020b). The fungi parasitizing nematodes use different forms of traps (adhesive networks, hyphae and rings) or produce conidia and zoospores that attach to the nematode surface and germinate inside the nematode body (Moosavi and Zare, 2012). Some examples are the fungal genera Arthrobotrys, which forms adhesive networks, Dactylellina, which forms adhesive knobs and nonconstricting rings, and Drechslerella, which forms constricting rings that trap nematodes (Moosavi and Zare, 2012). The most studied bacteria parasitizing nematodes belong to the genus Pasteuria. They attach to the nematode surface in soil using endospores and proliferate inside the nematode body when nematodes enter the plant roots (Chen and Dickson, 1998). However, other bacteria have also been reported to antagonize nematodes by producing toxins (Pseudomonas spp., Rhizobium spp., Bacillus spp., Streptomyces spp., and Lysobacter spp.), by inducing systemic resistance in plants (Bacillus spp., Rhizobium spp., and Microbacterium spp.), and by producing volatile organic compounds (Arthrobacter spp. and Variovorax spp.) (Tian et al., 2007;Topalović et al., 2020a;Topalović et al., 2020b).
Soils comprising microbiomes that antagonize nematode performance in soil and on plants are referred to as nematode-suppressive (Raaijmakers and Mazzola, 2016). Stenberg et al. (2021) have proposed that soil suppressiveness, which establishes spontaneously and as a result of untargeted cultural practices, can be defined as natural biological control. Suppressive soils have been detected for various PPN species, including cyst-forming nematodes (Westphal and Becker, 1999;Westphal and Becker, 2001;Olatinwo et al., 2006;Westphal et al., 2011;Hamid et al., 2017) and RKN (Pyrowolakis et al., 2002;Klein et al., 2012;Adam et al., 2014b;Topalović et al., 2019b). The use of amplicon sequencing in recent studies has revealed that nematode suppression is not always related to the presence and high abundance of only one antagonistic microbial species. Rather, a consortium of several microbial species can contribute to the decline of nematode populations in soil (Eberlein et al., 2016a;Castillo et al., 2017;Mwaheb et al., 2017;Hussain et al., 2018;Eberlein et al., 2020;Silva et al., 2021). For instance, Castillo et al. (2017) reported that a negative correlation exists between the abundance of root-lesion nematode, Pratylenchus penetrans, and RKN, Meloidogyne chitwoodi, and bacterial genera such as Bacillus, Arthrobacter, and Lysobacter in potato agricultural soils. More in-depth studies on interactions between PPN and soil microorganisms have shown that soil-dwelling nematode stages attach a limited range of microorganisms to their surface (Adam et al., 2014b;Elhady et al., 2017;Topalović et al., 2019a). The microbial attachment to PPN depends on the nematode species and the soil origin (Elhady et al., 2017), but plant exudation also plays a role in these interactions Mohan et al., 2020;Elhady et al., 2021). Recently, Topalović et al. (2019b) have studied the suppressive ability of the microbiomes from different soils against the northern RKN species Meloidogyne hapla, which attacks almost all temperate vegetables and legume crops (CABI, 2021). Interestingly, the suppressive microbiomes impaired M. hapla infection and reproduction both via direct interactions and by inducing systemic resistance in plants. Additionally, some of the isolated bacterial strains attaching to M. hapla J2 in different soils antagonized J2 in vitro and in the greenhouse (Topalović et al., 2019a), while the J2-attached Microbacterium sp. strain triggered a different expression of pattern-triggered immunity (PTI)-responsive genes in plants upon nematode invasion of the roots (Topalović et al., 2020a). However, it remains elusive which microbial characteristics really differentiate RKN-suppressive from RKN-conducive soils. More in-depth understanding of the differences between microbial consortia attaching to RKN in suppressive and conducive soils could potentially aid the identification of agricultural soils that are at low or high risk, respectively, of devastating infection levels to susceptible crop species.
In the current study, we aimed to elucidate the effects of the microbiomes from nine different soils on the invasion of M. hapla J2 in tomato roots and on plant performance. In addition, we used amplicon sequencing to decipher the composition of bacteria attached to the J2 cuticle when incubated in microbial suspensions originating from the different soils. We hypothesized that the composition of J2-attached bacteria reflects their biological potential to suppress nematodes (in suppressive soils) or assist them during the protection from the antagonists and invasion into the roots (in conducive soils). Our study gives an insight into the nemato-microbial interactions in different soils and helps understand the role of nematode-attached bacteria in nematode suppression and survival, which would be of a benefit to the sustainable nematode control.
Nematode extraction and plant growth for the glasshouse experiment
We extracted eggs of M. hapla from tomato roots and placed them on a modified Baermann tray for J2 hatching as described previously (Hooper et al., 2005). After hatching, we surface-sterilized J2s using 0.02% HgCl 2 for 3 min and a mixture of 10 mg l − 1 rifampicin, 25 mg l − 1 streptomycin-sulphate, and 1× CellCultureGuard (AppliChem, Darmstadt, Germany) for 4 h on a rotary shaker at 100 rpm. Nematodes were extensively washed on a sterile 5-μm sieve with sterile tap water to remove the traces of the chemical compounds after sterilization. We surface-sterilized seeds of tomato plants (Solanum lycopersicum L.) using 70% ethanol for 1 min and 3% NaOCl for 3 min. After sterilization, the seeds were extensively washed with sterile tap water and air-dried under sterile conditions. We planted one seed per 0.6 l pot containing autoclaved sand and clay pellets in a ratio of 10:1, and placed them in the glasshouse cabinet at 20 • C with 16 h photoperiod. The plants were watered as needed with fertilizer solution, (WUXAL Super NPK fertilizer, 8-8-6 with micronutrients, AGLUKON, Düsseldorf, Germany). The sand/ clay blend was autoclaved at 134 • C for 10 min to kill the indigenous microbes and nematodes, followed by a 20-min dry cycle.
Preparation of soil microbial suspensions for the J2 invasion assay
We used the soils from a previous study (Topalović et al., 2019a) for preparing soil suspensions for J2 incubation (Table 1). We used Bodenatlas Deutschland ( [URL]) to determine the WRB types of the soils and World Geodetic System 1984 ( [URL]) to determine the coordinates. We sieved the soils through a 0.5-cm sieve and suspended 300 g of soil in 3 l of sterile tap water in 5 l glass bottles containing 1 mm metal beads. To release microorganisms from the soil particles, soil suspensions were shaken for 1 h at 120 rpm. After shaking, large soil particles were allowed to settle for 10 min and the supernatants were sieved through a series of 150-μm and 20-μm sieves. We centrifuged the flow-through at 4000 ×g for 10 min (Sorvall Lynx 6000 Centrifuge, Fisher Scientific GmbH, Schwerte, Germany) and resuspended the pellet in 350 ml of sterile tap water. We drenched the rhizospheres of 3-week old tomato plants by evenly distributing 30 ml of soil suspensions around the roots (10 replicate pots for each soil suspension). One week later, 2 ml of sterile tap water containing 1000 surface-sterilized J2 of M. hapla were added to four holes around the stem (each hole receiving approx. 250 J2 in 500 μl of water). We arranged the pots in a randomized block design (10 replicate blocks × 9 soil treatments) in a glass house cabinet at 20 • C with 16 h photoperiod. Pots were watered and fertilized as needed.
After seven days, we removed the plants from the pots, rinsed the root systems and measured the fresh weight of roots and shoots. We measured the dry weight of shoots after drying in the oven at 100 • C overnight. We stained J2 inside the weighed roots with acid-fuchsin (Hooper et al., 2005) and counted the number of stained J2 per root under a stereomicroscope.
The J2 baiting in soil suspensions
Based on the data on root invasion by J2 in the glasshouse, we selected six soils (three suppressive and three conducive soils) for the J2 baiting experiment. We considered the soils as suppressive when the number of invaded J2 per root system was not significantly different from the soil with the lowest J2 invasion (soils S10 (mean 5 J2/root), BS1 (mean 23 J2/root), and G (mean 30 J2/root); see abbreviations in Table 1). We considered the soils as non-suppressive or conducive when the number of invaded J2 per root system was not significantly different from the soil with the highest J2 invasion (soils JKI (mean 92 J2/root), KWS (mean 65 J2/root), and E (mean 44 J2/root); see abbreviations in Table 1). The soils were sieved through a 1-mm sieve and 10 g of sieved soil was blended with 2 × 20 ml of sterile tap water for 1 min at a high speed (Stomacher®80, Seward, London, UK). We centrifuged the supernatant containing the released soil microorganisms for 5 min at 500 ×g to remove soil particles, after which we sieved the supernatant through a sterile 5-μm sieve to exclude indigenous nematodes. We used the flow-through as a microbial suspension for nematode incubation.
Around 2000 surface-sterilized J2 were incubated in glass jars containing 30 ml of soil suspensions overnight. The incubations were performed using an incubator (Brunswick Scientific, Edison, New York, USA) at 30 rpm at room temperature. We prepared four biological replicates of each soil suspension for the baiting experiment. After incubation, we transferred nematodes to handmade 5-μm pore sieves, washed with 50 ml of sterile tap water to remove loosely attached microbes and transferred the nematodes to bead-beating tubes for DNA extraction.
DNA extraction and PCR amplification
We extracted total DNA from J2 of M. hapla and their attached microorganisms with the FastDNA Spin Kit for Soil (MP Bio, Heidelberg, Germany). To lyse the cells mechanically, the Fastprep FP120 bead beating system (MP Bio, California, USA) was used for 30 s at a high speed. For the high throughput sequencing of the J2-associated microorganisms, we amplified a fragment spanning the hypervariable regions V3-V4 of the 16S rRNA gene with an initial PCR step using primers Uni341F (5 ′ -CCTAYGGGRBGCASCAG-3 ′ ) and Uni806R (5 ′ -GGAC-TACNNGGGTATCTAAT-3 ′ ) originally published by Yu et al. (2005) and modified as described in Sundberg et al. (2013). The PCR conditions consisted of an initial denaturation step at 95 • C for 5 min, 30 cycles of denaturation at 95 • C for 30 s, annealing at 56 • C for 20 s, and elongation at 72 • C for 1 min. The final extension step was performed at 72 • C for 10 min. In a second PCR reaction using the same cycling conditions but only 15 cycles, the primers additionally included Illumina specific sequencing adapters and a unique dual index combination for each sample. After each PCR reaction, amplicon products were purified using HighPrep™ PCR Clean Up System (AC-60500, MagBio Genomics Inc., USA) paramagnetic beads using a 0.65:1 (beads: PCR reaction) volumetric ratio to remove DNA fragments below 100 bp in size and primers. Samples were normalized using the SequalPrep Normalization Plate (96) Kit (Invitrogen, Maryland, MD, USA) and pooled using a 5 μl volume for each sample. The pooled samples library was concentrated using DNA Clean and Concentrator™-5 kit (Zymo Research, Irvine, CA, USA). The pooled library concentration was determined using the Quant-iT™ High-Sensitivity DNA Assay Kit (Life Technologies). Before library denaturation and sequencing, the final pool concentration was adjusted to 4 nM before library denaturation and loading. Amplicon sequencing was performed on an Illumina MiSeq platform using Reagent Kit v2 [2 × 250 cycles] (Illumina Inc., CA, US). Raw sequencing data are deposited to the NCBI's Sequence Read Archive under the BioProject PRJNA752946.
Bioinformatic analysis
The DADA2 pipeline based on amplicon sequence variants (ASVs) was used for 16S rRNA gene amplicon sequence analysis (Callahan et al., 2016). Briefly, filtration and trimming (filterAndTrim -maxN = 0, maxEE = 2, truncQ = 2) were performed to clean raw sequences, which then went through error learning (learnErrors), de-replication (der-epFastq), and merging. By discriminating biological sequences from sequencing errors, ASVs were then inferred (dada). We merged the forward and reverse reads (mergePairs) for the construction of the sequence table (makeSequenceTable) and further removed chimera sequences (removeBimeraDenovo). Taxonomy classification of chimera-free ASVs was with the naïve Bayesian RDP Classifier (Wang et al., 2007) with a bootstrap threshold of 80, by searching against the SILVA nonredundant database release 138 (Quast et al., 2013). ASV sequences identified as singletons were removed. The generated sample-wise ASV abundance table was used for further analysis.
Statistical analysis
For the plant growth parameters and J2 invasion, the data were logtransformed and analyzed in SAS 9.4 using GENMOD procedure with scale parameter Pearson and assuming a generalized linear model at alpha level p < 0.05. The multiple pairwise treatment effects were tested using Tukey-Kramer adjustments with the Least Square Means.
The statistical analyses of the sequencing data were conducted in the R Environment version 4.0.0 (R Core Team, 2020). We produced rarefaction curves of the observed 16S ASVs using the "rarecurve" function of the package vegan on non-rarefied counts per sample. Barplots of the soil-ASVs relative abundance versus J2-associated ASVs were built with vegan package (Oksanen et al., 2020). Alpha diversity measures of J2associated microbial assemblages were calculated per sample with vegan package, based on randomly subsampled read count data, to compensate for variation in read numbers across samples. We tested the effect of soil origin on alpha diversity measures with a one-way ANOVA followed by Tukey's Honest Significant Difference (HSD) test for pairwise comparisons. To visualize the effect of soil suppressiveness on the J2-attached microbiome we performed canonical analysis of principal coordinates (CAP) on normalized ASV counts (variance stabilization -DESeq2 package; Love et al., 2014), with the "capscale" function of the vegan package. We assessed the statistical significance using the "permutes" function in the vegan package with 10 4 permutations. Additionally, soil origin and suppressiveness category was further tested by permutational analysis of variance (PERMANOVA) using vegan package, with 10 4 permutations.
To identify indicator ASVs of the J2-associated bacteria, indicator species analysis (indicspecies package; de Cáceres and Legendre, 2009) was used to calculate the point-biserial correlation coefficient (r) of an ASV's positive association to one or a combination of soils. The analysis was conducted with 10 4 permutations and considered significant at p < 0.05. We used bipartite networks to visualize the significant (p < 0.05) indicator ASVs associations to one or more of the different soils in study. The networks were constructed using the Fruchterman-Reingold layout with 10 4 permutations as implemented in the R package igraph (v. 1.2.5; Csárdi and Nepusz, 2006). To visualize the abundance distribution of the indicator ASVs across the different samples, we constructed a heatmap using the "heatmap.2" function in gplots package (Warnes et al., 2020).
The soil microbiomes also affected growth of tomato plants differently (Fig. S1). At 7 DPI, the highest values for the dry shoot weight and fresh root weight were recorded for plants drenched with the KWS soil microbiome (mean 0.15 dry shoot weight; mean 0.58 g fresh root weight, respectively), which significantly differed from all the other treatments in this study. The lowest dry shoot weight was measured for the treatments BS1 and G (mean 0.044 g; mean 0.041 g), but this was significantly different from the treatments KWS, JKI and E (p < 0.05). In addition, fresh root weight was also low for the BS1 treatment (mean 0.1 g; p < 0.05), which was followed by the treatment B (mean 0.18 g; p < 0.05).
To see if the root weight affected nematode invasion into the roots, we also calculated the number of invaded J2 per g of fresh root weight (Fig. S2). The lowest nematode invasion per g of root was seen for the S10 treatment (mean 16 J2/g of root), while these mean values ranged from 120 J2 to 197 J2 per g of root for treatments E, K, B, G, and S5, respectively. Interestingly, while the fresh root weight was lowest for BS1 treatment, it showed the highest number of J2 per g of root (mean 248 J2) and did not differ significantly from the treatments D2 and JKI. However, as the J2 root invasion was not determined by the root mass, we decided to use the number of invaded J2 per root system as the measure for nematode suppression by microbiomes in this study.
Composition and comparison of M. hapla J2-associated bacterial communities in different soils
Sequencing of the 16S rRNA amplicon library resulted in 1602 ASVs in 30 samples (6 microbial suspensions × 4 replicates plus sequencing of the original 6 soil samples). Overall, 65,728 16S rRNA gene sequences (2191 ± 213; average ± standard error of the mean across all samples) were obtained with an average read length of 415 bp. Rarefaction curves evaluating the ASV richness per sample showed that bacterial variation was not covered completely in our sampling strategy for some samples (Fig. S3). When looking at the dataset of the J2-attached microbiome, samples recovered 54,940 16S rRNA gene sequences (2289 ± 261) that corresponded to 1213 ASVs.
The alpha diversity of bacterial ASVs, i.e. the number of observed ASVs and Shannon Index, attached to J2 of M. hapla varied for the different treatments (Fig. 2). The highest alpha diversity was found in J2 samples from two suppressive soils, BS1 and G, with significant differences observed for the Shannon index, when compared to the bacteria attached to the J2 inoculated with the conducive JKI soil microbiome (Fig. 2).
Comparative analysis of the J2-attached microbiomes with the bacterial soil origin revealed that only the suppressive soils G and BS1 clustered together with their respective J2-attached microbiomes (Fig. 3A). On the other hand, the non-suppressive soils (E, JKI and KWS) plus the S10 suppressive soil clustered together and separated from the J2 microbiomes (Fig. 3A). Across all samples, the most abundant taxa corresponded to six bacterial classes, i.e. Acidimicrobiia, Actinobacteria, Alphaproteobacteria, Anaerolinaeae, Chloroflexi, and Gammaproteobacteria. In all microbiome suspensions, the J2 were predominantly colonized by Alphaproteobacteria, followed by Actinobacteria, except for the J2 incubated with the soil E microbiome, where a significant Fig. 1. Invasion of M. hapla J2 in tomato roots as affected by the microbiomes from nine different soils. Different letters above standard error bars represent statistical differences between the treatments at p < 0.05 (Tukey HSD test).
decrease of Alphaproteobacteria was compensated by the enrichment of Actinobacteria (ANOVA, p < 0.05, Benjamini-Hochberg FDR). Acidimicrobiia displayed a significantly higher relative abundance on J2 exposed to the conducive microbiomes from JKI and KWS soils, while Chloroflexi were significantly more enriched in samples associated with the suppressive G soil (ANOVA, p < 0.05, Benjamini-Hochberg FDR).
Canonical analysis of principal coordinates (CAP) highlighted that the attachment of bacteria to the J2 cuticle was very specific for the individual soil origins based on the clear grouping of replicates for each soil, although there was some overlap between replicates from KWS, S10 and JKI treatments (Fig. 3B). Moreover, the J2-attached microbiomes of the BS1 and G treatments were more dissimilar and dispersed when compared with the other assemblages. PERMANOVA confirmed the significant effect of microbial suspensions on J2-attached microbiomes (Fig. 3B). However, there was no obvious pattern of sample grouping according to the degree of suppressiveness.
Indicator species analysis of J2-attached bacteria in different soils
Discriminant analysis was used to produce a network with M. hapla J2-attached ASVs that differed significantly across different soil microbiome treatments, by implementing indicator species analysis. A total of 40 ASVs that corresponded to 3.3% of the total ASVs, were identified as indicator taxa (Fig. 4A). The network shows that at a higher taxonomic resolution, the J2-attached microbiomes from S10 and G do not share indicator ASVs with any of the other treatments, while the other treatments do share a few indicator ASVs. In addition, BS1 and G samples have mostly Alphaproteobacteria and Actinobacteria as indicator species, while the indicator species in other treatments were mostly assigned to Proteobacteria and Gammaproteobacteria. Among these, 11 ASVs were specific to J2 in JKI treatment, 4 in KWS treatment, 15 in BS1 treatment, 1 in S10 treatment, and 12 in G treatment, while no indicator taxa were specific to J2 in E treatment.
To compare the relative abundances of different genera between the different treatments, the indicator taxa were further summarized at genus level in a heatmap of centered and scaled counts, showing the very specific attachment of bacteria to the J2 cuticle in each treatment (Fig. 4B). The most numerous indicator ASVs were associated with J2 from two nematode-suppressive soils, G and BS1, with one shared ASV from the genus Sphingomonas. The J2 from the G treatment were colonized by Alphaproteobacteria (genera Qipengyuania, Sphingomonas and Altererythrobacter, and families Devosiaceae and Sphingomonadaceae) and Actinobacteria (genus Nocardioides and two Actinoplanes species, Actinoplanes digitatus and Actinoplanes italicus). In the BS1 treatment, the J2-attached ASVs from the phylum Alphaproteobacteria were assigned to Sphingomonas and Methyloligellaceae, while the members of Actinobacteria were more abundant and identified as Crossiella, Streptomycetaceae, Pseudarthrobacter, Micrococcaceae, Streptomyces, and Nocardia. In addition, two ASVs associated with M. hapla in the BS1 treatment were assigned to Chloroflexi and Clostridia. A low number of ASVs that were detected as attached to J2 after incubation in the S10 treatment was assigned to the genus Rhodococcus. In two non-suppressive soil microbiome treatments, KWS and JKI, two genera, Rhizobium and Devosia, attached to the cuticle of J2. In addition, the ASV corresponding to the order Burkholderiales was only found on the J2 from the JKI treatment.
Discussion
In this study we measured suppressive effects of microbiomes from nine different soils against the RKN species M. hapla by following J2 invasion in tomato roots. To make sure that only the microbial moiety of soils was tested against the nematode and to exclude the effects of varying physicochemical characteristics of different soils (Prot and van Gundy, 1981), we drenched the rhizospheres of tomato plants grown in sand and clay pellets with microbial suspensions extracted from different soils prior to nematode inoculation. We used this approach as it was shown that establishment of RKN was better in carrots grown in sand as compared to its dilutions with bed-soil (Kim et al., 2017). An enhanced soil aeration and low accumulation of plant growth inhibitory substances in sandy soils were considered important factors for successful nematode invasion and reproduction. Our results showed a distinct capability of microbiomes originating from different soils to suppress nematode performance. The tomato roots drenched with microbiome from soil S10 had the lowest number of invaded M. hapla J2, which was followed by BS1, B and G soil microbiomes. In addition, our results indicate that microbiomes from soil JKI were least suppressive against J2 invasion in roots, followed by soils KWS, D2, E, and S5. J2 invasion of the roots did not depend on the size of the root system, as there was no indication that bigger roots hosted more nematodes than the smaller roots. Hence, we ascribe differences in J2 invasion of the whole root system between treatments to differences in the microbial suppression of the J2. In addition, a seven-day period used to assess J2 invasion was not long enough for observing significant nematode effects on the plant growth parameters in our study; thus, the differences in the plant growth between microbiome treatments should only be ascribed to different effects of the soil microbiomes. Indeed, the importance of soil bacteria in aiding the plant to uptake nutrients from soil and fight diseases, and in de novo synthesis of essential compounds for the plant growth has been repetitively reported (Hayat et al., 2010;Bakker et al., 2018).
It has previously been shown that the nematode surface can be an important source of nemato-antagonistic microorganisms in different soils (Adam et al., 2014b;Elhady et al., 2017;Orr et al., 2019;Topalović et al., 2019a). On the other hand, we know very little about the microorganisms that soil-dwelling stages of PPN carry on their surface for protection purposes (Topalović and Vestergård, 2021). So far, studies point to the surface coat, the carbohydrate-rich protein layer over the nematode epicuticle, as the main area for microbial attachment (Davies and Curtis, 2011). In the present study, we were able to decipher bacterial communities on the surface of M. hapla J2 that were incubated in microbial suspensions of three suppressive (BS1, G, and S10) and three conducive (JKI, KWS, and E) soils. This was done in order to reveal if microbial attachment to the J2 surface in soil is determined by the soil origin and if it can reflect the degree of suppressiveness of soil microbiomes against the nematode. At phylum level, the J2 attached similar bacteria in all soils that corresponded to Acidimicrobiia, Actinobacteria, Alphaproteobacteria, Anaerolinaeae, Chloroflexi, and Gammaproteobacteria. These phyla have been commonly found in association with different life stages and species of PPN (Adam et al., 2014b;Cao et al., 2015;Tian et al., 2015;Castillo et al., 2017;Elhady et al., 2017;Hussain et al., 2018;Masson et al., 2020;Yergaliyev et al., 2020). However, digging deeper into the analysis of J2-attached bacteria using CAP based on Bray-Curtis distance, we saw a treatment-dependent clustering of bacterial ASVs, where least differences were found between the bacteria attached to J2 from conducive JKI and KWS soils and suppressive S10 A) The relative abundance of bacterial ASVs associated with the different soils and J2-attached microbiomes, at class level. The labels below the barplots represent biological replicates of each treatment. The arrows next to the taxa show significant changes of their abundance for specific treatments (ANOVA, p < 0.05, Benjamini-Hochberg FDR). B) Bacterial communities attached to M. hapla J2 in microbial suspensions from six soils as analyzed by constrained analysis of principal coordinates (CAP) using Bray-Curtis distance. The principal coordinates 1 (CAP1) and 2 (CAP2) were plotted based on the soil origin. The statistical difference was determined using PERMANOVA assessed with 10 4 permutations. Percentage of variation given on each axis refers to the explained fraction of total variation. soil. We believe that the geographical position of the soil sites might have partly contributed to this effect, as soils JKI, KWS and S10 were geographically closest to each other. Notably, we observed a higher bacterial diversity and richness, even though not significant, on J2 recovered from two suppressive soils, BS1 and G, in comparison to other soils, while these alpha diversity parameters were lowest for the J2attached bacteria from conducive JKI soil. The presence of more diverse bacterial assemblages on nematodes from suppressive soils could be correlated with the fact that the low occurrence rate of plant pathogens and parasites in soil is usually linked with a high microbial diversity (Workneh and van Bruggen, 1994;Garbeva et al., 2004;Zhou et al., 2019). When considering a higher taxonomic level, a very low number of commonly shared ASVs between J2 from different treatments suggests that the surface-sterilization of J2 prior to their incubation in soil suspensions successfully removed most of the bacteria that were already present on the J2. In addition, we found the most numerous indicator ASVs on the surface of J2 from suppressive G and BS1 soils. Although the majority of these taxa belonged to Actinobacteria and Alphaproteobacteria, very few of the ASVs were common for these two treatments. Nevertheless, some of the G and BS1 originating J2-attached ASVs, including members of Sphingomonadaceae, Nocardioides, Devosiaceae, Micrococcaceae, Actinoplanes, Streptomyces, Clostridium, and Nocardia, have been previously reported in association with different PPN species in soils with nematode-suppressive characteristics (Adam et al., 2014b;Eberlein et al., 2016b;Castillo et al., 2017;Elhady et al., 2017;Hu et al., 2017;Hussain et al., 2018). Members of Streptomyces and Clostridium produce compounds with nematicidal effects (Siddiqui and Mahmood, 1999), but there is no clear evidence as to if and how the rest of these bacteria can suppress nematodes.
The bacteria attached to J2 from conducive soils, KWS and JKI, including Devosia, Clostridium, Rhizobium, and Burkholderiales, have also been detected in studies on microbial attachment to Meloidogyne spp. (Adam et al., 2014b;Elhady et al., 2017). Clostridium, Rhizobium and Burkholderia have been reported as nematode antagonists (Reitz et al., 2000;Meyer et al., 2001;Adam et al., 2014a), but as microbiomes from KWS and JKI soils were conducive to J2 root invasion, we speculate whether bacteria attaching to the J2 could have protected the J2 rather than being only antagonists. Devosia, as such, has often been detected in cyst nematode-suppressive soils using amplicon sequencing (Eberlein et al., 2016b;Hu et al., 2017;Hussain et al., 2018), but it has never been tested as a nematode antagonist in vitro. On the other hand, both Devosia and Sphingomonadaceae have been associated with different life stages of M. incognita isolated from heavily infested tomato roots . As these bacteria have role in nitrogen fixation and cellulose degradation, it has been suggested that they may form a symbiotic association with nematodes and aid them during the plant root parasitism Tian et al., 2015).
It thus appears that J2 exposed to microbiomes from soils with varying suppressiveness carry both putatively nemato-suppressive bacteria (e.g. Burkholderiales and Clostridium) as well as bacteria that may facilitate J2 root invasion. This is an interesting phenomenon which should not come as a surprise, as nemato-parasites have a strong ability to attract nematodes (Jansson, 1987;Davies and Curtis, 2011), and here we show that they attached to J2 even in conducive soils. However, whether the attachment of bacteria that protect J2 against antagonists or facilitate their root invasion played a role for the high J2 root invasion in pots treated with conducive soil microbiomes is an intriguing question that warrants further investigation of the potential J2 protective role of microorganisms attached to the surface of infective stages of PPN. The application of nemato-antagonistic microbial strains has been proposed as a sustainable strategy for the management of PPN. However, the efficiency of a range of microbial control agents has been insufficient when applied in real agricultural soils. We propose that the attachment of indigenous nemato-protective microorganisms can partly explain the low efficacy of applied biocontrol strains (Topalović and Vestergård, 2021). It is important to note that Topalović et al. (2019a) have previously isolated bacteria attached to M. hapla J2 that were incubated in the suspensions extracted from the same soils used in the current study. The study reported a very high attachment rate of the strain Microbacterium sp. K6 in the re-attachment experiments with purified isolates, but no indicator ASV was assigned to this genus in our results. Thus, this confirms that nemato-bacterial interactions in different soils are very complex, and the estimation that only 1% of soil bacteria are culturable (Amann et al., 1995), adds up to this complexity.
Taken together, J2 of M. hapla, recovered from microbial suspensions with a varying potential to suppress the nematode, attached a specialized subset of bacteria, and their composition and abundance is mainly affected by the soil origin. In addition, bacterial colonizers on J2 from two suppressive soils were the most numerous and diverse, but further studies on nematode associations with microorganisms in conducive soils are needed in order to determine their function and possible role in nematode protection. This might give an explanation as to why we still lack microbial control agents with high and consistent efficiency against RKN.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Domain: Agricultural And Food Sciences
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Food Safety Practice and Its Associated Factors Among Food Handlers in Public Food Establishments of Godey Town, Somali Region, Eastern Ethiopia
Food borne illness is more common in both developed and developing country. In developing countries up to an estimated 70% of cases of diarrheal disease are associated with the Consumption of contaminated foods. Approximately 10 to 20% of food-borne disease outbreaks are due to contamination by the food handler. Nevertheless, data regarding food safety practice and associated factors in low-income countries like Ethiopia are very minimal, including the study area. The purpose of this study was to determine the magnitude of food safety practice and associated factors among food Handlers in public food establishments of Godey town, Somali region. To address the stated objective, institutional based cross sectional study design was used, on 390 food handlers working in all 109 public food establishments in Godey town. Data collection was done by four diploma nurse by using structured pretested questionnaire and institutional observation checklist. Data were entered on to Epi Data version 3.0 computer software and exported to SPSS version 20 computer software for analyzes. Accordingly, descriptive statistics was used to describe the independent variables in relation to the outcome variable. Bivariate, logistic regression analyses were done to see the association between each independent variable and the outcome variable. All variables with p-value <0.25 during bivariate were entered in to multiple logistic regression models to control for all possible confounders and to identify factors associated with the outcome variable. Odds ratio along with 95% CI were estimated to measure the strength of the association. Finally, level of statistical significant was declared at p-value <0.05. As a result, the study has revealed that the prevalence of satisfactory food safety practice of food handlers was 20.9% [95% CI: 16.7, 24.8]. 95%CI: (2.7, 15, 3)] and presence of supervision [AOR=3.08, 95%CI: (1.3, 7.12)] were statistically significant factors associated with food safety practice. Along with this, the prevalence of satisfactory food safety practice among food handlers was low in this study, knowledge about food safety, hand washing facility, and supervision were factors associated with food safety practice. Thus, strong supportive supervision, awareness on knowledge of food handlers on food safety practice and maintaining and establishing hand washing facility in kitchen area have to be done to solve the problem.
Introduction
Safety is defined as the condition of being safe from undergoing or causing hurt, injury or loss (Webster's, 1990). Food safety was defined by the world health organization as assurance that when food is consumed in usual manner does not cause harm to human health and wellbeing (WHO, 2002).
Food is a fundamental human need and basic necessity to good health, Source of energy, vitamins, and minerals. If the hygienic condition of the food is not kept, it may cause an adverse effect on human health; this may result due to lack of knowledge, wrong attitude and improper practices by food producers or handlers at food catering establishments and consumers. Food safety still remains a major public health challenge and concern globally. Because of this Food borne diseases are known to be responsible for large proportion of illness, deaths and source of diarrheal diseases (Nagga Baraki, 2006).
Food can be subjected to contamination with toxic substances and pathogenic organisms during production, transportation, preparation, storage and service. The consumption of contaminated food that contains sufficient quantities of pathogenic organisms and toxic substances will result in food borne disease. It may due to lack of knowledge in part of food handlers and negligence in safe food handling. It is estimated that in developing countries up to 70% of cases of diarrheal disease may be caused by contaminated food. Food prepared in large quantity is liable to contamination and to the rise of food borne diseases if the strictest principles of hygiene are not maintained (WHO, 2006).
The study conducted by WHO in Geneva by the year 1989 showed that food handling personal play important role in ensuring food safety throughout the chain of food production and storage. Mishandling and disregard of hygienic measure on the part of food handlers may enable pathogenic bacteria to come in to contact with food and in some case survive and multiply in sufficient number to cause illness in consumers (WHO, 1989). Other evidence in University campus by the year 1988 indicated that poor sanitary practice in food distributions, storage, handling and preparation can create an environment in which bacteria and other infectious agent are more easily transmitted (Gent R. ,etal, 1999).
Food handler are anyone who works in a food and drink establishments and who handles food, or contact with any equipment or utensils that are likely to be in contact with food, such as cutlery, plates bowls, or chopping boards (Scallan E.et al, 2011).
Food borne diseases can be defined as diseases commonly transmitted through food. Food borne diseases comprise a broad group of illnesses caused by microbial pathogens, parasites; chemical contaminants and bio toxins (WHO, 2002). Food borne diseases are major health problems in developed and developing countries. The World Health Organization (WHO) estimated that in developed countries, up to 30% of the populations suffer from food borne diseases each year, whereas in developing countries up to 2million deaths are estimated per year (Havelaar A. et al, 2013).
Statement of the Problem
Food-borne related illnesses have increased over the years, and negatively affected the health and economic well-being of many developing countries (WHO, 2008). The World Health Organization (WHO) stated that about 1.8 million persons died from diarrheal diseases in 2005, mainly due to the ingestion of contaminated food and drinking water.
Food poisoning can occurs as a result of consuming food contaminated with microorganisms or their toxins, the contamination arising from inadequate preservation methods, unhygienic handling practices, crosscontamination from food contact surfaces, or from persons harboring the microorganisms in their nares and on the skin (Barrie D., 1996).
According to CDC report, each year as many as 600 million, almost one in ten people in the world ill after consuming contaminated food, of this 420000 people die and from this, 125000 are under five, also CDC estimates that each year roughly 1 in 6 Americans (or 48 million people) gets sick, 128,000 are hospitalized, and 3,000 die of food borne diseases (CDC, 2001). According to WHO report 2009, say that fifty children under five die every hour in South East Asia due to diarrhea caused by food born disease (WHO, 2009).
Evidence indicates that in developing country Illness and death from diseases caused by contaminated food are a constant threat to public health and a significant impediment to socio-economic development worldwide. Food borne disease (FBD) outbreaks are common and often cause considerable morbidity and mortality (Havelaar A. et al, 2015). Including Ethiopia around 70% of the diarrhea disease is associated with consumption of contaminated food (WHO, 2010). Approximately 10 to 20% of food-borne disease outbreaks are due to contamination by the food handler (Maizun M. and Nye N., 2002).
Practice of food safety among food handlers is not satisfactory in the world, even though it varies from country to country. For instance the study conducted in Turkey by the year 2004 on the evaluation of food hygiene knowledge , attitudes and practice of food handlers in food business among 764 food handler indicate that mean food safety practice score was only 43.4 % + or -16.3. The study demonstrated that food handlers in Turkish food businesses often have lack of knowledge regarding the basic food hygiene (critical temperatures of hot or cold ready-to-eat foods, acceptable refrigerator temperature ranges, and cross-contamination (Azmi Safak Ersun et al, 2004).
Other evidence indicate by the year between November 2010 and January 2011 in Switzerland on 100 food handlers in Restaurant showed that mean knowledge score of the participating food handlers was 71%. None of the food handlers knew the correct temperatures for cooking chicken and holding potentially hazardous hot foods, and the range of temperatures for pathogen growth (Palak K.et al, 2013). The study conducted in Jamaica by 2014, identified that factors like gender, education, job position, training and experience in the food industry were associated with the practice level of food handlers (Thelwell M., 2014).
Data regarding food borne diseases in African Region are still minimal (WHO, 2000). However, as per some studies conducted in the region, food safety practice of food handlers is not satisfactory. Study conducted in Nigeria by the year 2013 indicated that 37% of food handlers were directly engaged in cross contamination practices that are potential to cause food borne illness. Education and training on food safety were among the factors responsible for poor food preparation practice (Mokhtar A., 2013). Other evidence showed that lack of accesses to potable water; poor government structural arrangements and incontinent environmental condition were notable reason (Dewaal C. and Robert N., 2005).
In Ethiopia also the practice of food safety is not satisfactory with different factors. An evidence indicate that prevailing poor food handling and sanitation Practices, inadequate food safety laws, weak regulatory systems, lack of financial resources to invest safer equipment, and lack of education for food Handlers are the main contribution factor for food contaminations in public food catering establishments (Mulgeta K and Bahay A, 2012). Recent study conducted in Northern parts of Ethiopia in Gondar Town only 30.3% of food handlers Research on Humanities and Social Sciences www.iiste.org ISSN 2224-5766 (Paper) ISSN 2225-0484 (Online) Vol.11, No.7, 2021 had good food handling practice and socio demographic characteristics , level of knowledge, attitude of food handler were identified factors for food safety practice ( Gizaw Z. , et al, 2014).
Other study in Dangla Town in northern part of Ethiopia indicate that only 52.5% of food handlers had good food handling practices and presence of insects and rodents were among the factors identified as having significant associations with food safety practice (Tessema G.et al, 2014).
Therefore conducting other study in order to strengthen the privies finding in areas where not previously done is very important. In Godey Town Somali Region there is no studies conducted on food safety practice and factors that shows the local context, regardless of some influencing factors. Those influencing factors include the existing large number of food establishments and food handlers serving large consumers as well as hot weather condition in the area. As per daily observations, the hot weather makes both cooked and non-cooked foods out of use easily unless safely handled. Therefore, this study was assess the status of food safety practice and associated factors among food handlers in public food establishments of Godey Town.
Objectives of the Study General objective of the Study
The overall objective of the study was to determine the magnitude of food safety practice and associated factors among food handlers in public food establishments at Godey Town Somali Region.
Specific objectives of the Study
To estimate the magnitude of food safety practice among food handlers.
To identify factors associated with food safety practice among food handlers.
Research Methodology
In order to achieve the study objectives quantitative research approach was used. Specifically survey method was employed.
Study Design
Institutional based cross-sectional study design was used.
Research Participants
All food handlers who were working in Godey town public food establishments during study period. In this regard, while food handlers who were working in public food establishment during data collection were included from the study, food handlers who were unable to respond to interview during data collection were excluded in the study.
Sample size determination
The required sample size for this study was determined using single population formula with the following assumptions. Prevalence of satisfactory food safety practice to be 30.30 % (Gizaw z. et al, 2014). It has 95% confidence level, margin of error d= 5% and 10% non-response rate, the sample size was calculated as follows. n= (zα/2) 2 p (1-p) where z α /2 at 95% confidence level =1.96 and p=0.303 as given above. To this effect, the total sample size is n=324 and considering 10% for non-response=356.
In line with the above sample size determination logic, in Godey town there were 390 food handlers in public food establishments. As a result, the final sample size for this study was all food handlers who were working in public food establishments taken to increase the power of the study.
Data collection methods Data collection instrument
The study has employed structured questioner to address the specific objectives of the study. The questioners contain socio demographic factor and other variables. The questioner was first prepared in English then translated in to Amharic and local language Somali then again translated to English by other person in order to check its appropriateness.
Data Processing and Analysis
Once the data was collected and cleaned, the data were entered into Epi data version 3.0 computer software and exported to SPSS version 20 computer software for analysis. Descriptive statistics was run to check for any missing values. Summary of descriptive statistics such as frequencies, percentages, means, standard deviation and median were used to describe socio demographic characteristics. Narration was used to report frequency of socio demographic characteristics of food handlers, Knowledge on Food Safety Practice of food handlers and attitude on Food Safety Practice of Food handlers. After that, the status of food safety knowledge, attitude and Research on Humanities and Social Sciences www.iiste.org ISSN 2224-5766 (Paper) ISSN 2225-0484 (Online) Vol.11, No.7, 2021 36 practice of food handlers were determined based on their score. To determine the status of knowledge based on 9 knowledge related question which contained three options, correct, incorrect and I don't know, the appropriate answer was given score one and the remaining given score of zero. The score was rang (0-9). The respondents who score 7 or 77% and above from total of nine where considered as adequate knowledge, food handlers score 6 and below 6 were considered as in adequate knowledge. food safety attitude of food handlers was assessed based on attitude related five question, correct answer was given score of 2, Neutral answer was given one, incorrect answer was given zero, where total range became (0-10).
After that respondents score range 6-10 were considered as positive attitude, range 4-5were considered as neutral attitude and rang 0-3 were considered as negative attitude,. Finally food safety practice was assessed based on 12 food safety practice related questions which contain three options always, sometimes and never. Correct answer was given 2, sometime was given one and incorrect answer was given zero. Total score was range from (0-24). Food handlers score 17 and above were considered as good, whereas food handlers score 16 and below 16 were considered as poor practice. During bivariate analysis, crude odds ratio along with 95% CI was used to see the association between each independent variable and the outcome variable by using binary logistic regression model. Independent variables with p-value of ≤ 0.25 were included in multi-variable analysis to control for all possible confounders and identify factors associated with food safety practice. Then outliers and influential cases were checked by standardized residuals and cook's distance respectively. Cases with standardized residuals out of the interval (-3, 3) and cook's distance above 1 were excluded from the multivariable analysis. Multi-co linearity was also checked to see the linear correlation among the independent variables by using standard error and variance inflation factor. Variables with standard error of >2 and variance inflation factor >5 were dropped from the multivariable analysis.
Hosmer Leme show goodness of fit tests was used to check for model fitness by looking cut of point> 0.05. The continuous variables such as food handlers' age was tested using the normal curve with a histogram. Adjusted odd ratios along with 95% confidence interval was estimated to measure the strength of association between dependent and independent variable . In this study level of statistical significance was declared at p value <0.05.
Ethical Considerations
The study protocol was approved by Haramaya University College of health and medical science intuitional health research and ethics review committee (IHRERC) of Harar campus. Official letter of cooperation was written from Haramaya University College of health and medical science to all concerned bodies of Godey town and Somali regional health bureau. The study participant ware clearly informed about the purpose of study. Benefit of the study was explained for the study participants. It was explained that the participation was voluntary. The issue of confidentiality and privacy of their information were clearly explained for the participants. The written informed voluntary and signed consent was obtained from the manager of the food establishment and each study participants. In order to protect the confidentiality of the information the name of participant was not included in the questioners. As a result, the identification was only coded by numerical numbers.
Socio demographic characteristics
A total of 390 food handlers in all (109) public food establishments were responded to the questionnaire yielding 98.2% response rate. Out of the total (n=383) participant majority 140 (36.6%) of study participants were from restaurant. Regarding gender, (n=383), 209 (54.6%) were males and 174 (45.4%) were females. The mean age of the respondents was 26.4 ± 8 years. About their educational status majority of them 297, (77.5%) have no formal education. In the case of Ethnicity 276 (72.1%) of the participants were Somali in their ethnicity. Looking marital status, around 282 (73.6%) of participants were singles. In case of food safety training, three hundred five (77.2%) of food handlers were not attend food safety training.
Knowledge of food handlers about food safety
Food safety knowledge of food handlers was assessed based on 9 food safety knowledge questions. Each question has three options (correct, incorrect and don't know). The appropriate answer for question number 6 and number 8 from the given option was incorrect, the remaining 7 questions, was option correct. Based on the result of knowledge assessments, from the total (n=383) food handlers, 94 (24.5%) food handlers had adequate knowledge and 289 (75.5%) had inadequate knowledge. Mean score value of food safety knowledge of the respondents was 4.54.
Attitude of food handlers towards food safety practice
Attitude on food safety practice of food handlers was assessed based on 5 attitude questions. From the total (383) study participants only 53(13.2%) of food handlers had positive attitude.
Research on Humanities and Social Sciences www.iiste.org ISSN 2224-5766 (Paper) ISSN 2225-0484 (Online) Vol.11, No.7, 2021 Food safety practice among food handlers Current study indicated that only 80 (20.9%) of the study participants had satisfactory food safety practice whereas 303 (79.1) of the study participants had not satisfactory food safety practice. However majority of the participants 225(58.7%) reported that always wash their hands before starting their work and 114 (29.8%) of them do it sometimes.
The study also showed that only few of the participants 38 (9.9%) they didn't use separate utensil when they are preparing raw and cooked foods. To ward checking expire date of product, only 33 (8.6%) they never checked expire date of the products.
About smoking status, 103 (26.9%) of participant reported that always smoke cigarette and 132 (46.8%) of them smoke cigarette during normal work. From the total participant majority of them 300 (78.3%) said that came to work when they have diarrhea. Furthermore 150 (39.2%) participants reported that they always cover head during food serving and 210 (54.8%) of the participants do it sometimes. Besides, majority 290 (75.7%) participants reported that they have habit of making their nail long and 93 (24.3) of participants never do it. In addition from the total only few of them 35 (9.1%) were reported that never disinfect cutting boards after each use.
Observation of Institutional facilities
Observation was conducted on 107 public food establishments21 hotel, 39 restaurants, 26 cafeterias and 21 kurs bet. Two establishments were involuntary for participation (one from cafeteria, the other from kurs bet). Almost all 97(90.6%) had no food safety guideline. More than half (78.5%) institution had no hand washing facility for food handlers.
In the multivariable logistic regression analysis secondary education, having food safety knowledge, presence of hand washing facility for food handlers and presence of supervision were statistically significant factors food safety practice
Discussion
Current study showed that there was poor practice of food handling in the majority of food handlers 303(79.1). Factors associated with this poor finding were, lack of knowledge about food safety practice, lack of hand washing facility for food handlers and lack of supportive supervision from the regulatory body.
Looking the status of current study finding, the prevalence of good practice was only 20.9% this figure is markedly lower than the study conducted in Jordan (89.43%) (Labib Sharif et al, 2013). This difference may be due to variation of socio demographic characteristics, regulatory system of food establishments and accesses difference in facility. However this study finding (20.9) was higher than the study conducted in Bangkok (15.2%) (Cuprasitrut. T et al, 2011). This may due to difference in socio demographic characteristics and the number of sample size variation.
While looking knowledge about cross-contamination status of current study participants, 32.6% of food handlers reported that always come to work when they have diarrhea and 47.9% of participants do it sometimes, and only 18.2 of food handlers never wear jewelry during food preparation, these mentioned figures were not consistent with study conducted in Jamaica ,which showed that only 19%of food handlers came to work with illness like diarrhea, and 71% of food handlers were never use jewelry during food preparation. This possible variation may be due to; current study food handlers may have Lack of awareness on such type of risk activities to food born disease on food safety practice.
Finding of this study (good practice (20.9%) also not consistent with study conducted in Sudan (33.21%) (Abdelrazig A. et al, 2017). This difference may be due to study setting because; the study conducted in Sudan was by sample size of 40 food handlers and conducted in restaurants only.
Current study also showed that the prevalence of good practice was lower than study conducted in Addis Ababa university cafeterias by the year 2014 on 302 food handlers (52.3%), the study conducted in Arba Minch 32.6%. This difference may be due to variation of geographical area and regulatory system. However the study conducted in ambo town on sanitary survey of food and drinking establishments, showed that the prevalence of not hand washing before starting their work was higher (5.7%) (Dugassa Guteta, 2007) than current study (1.3%) much lower (1.1%) than smoking cigarette for current study (27.7%). This possible reason may be due to hot environmental condition of current study area made food handlers better conscious to wash their hands to protract food spoilage and more cultural acceptance of smoking cigarette in current study area.
About knowledge on food safety practice, food handlers those who had good food safety knowledge on food safety practice were 10.4 times more good practice than those who had no adequate knowledge. Knowledge also as identified factor with the study conducted in, Kuching city. (Mizanur Rahmanet al, 2016). This possible explanation may be presence of knowledge about food safety enable/support food handlers to have satisfactory food safety practice.
While looking the other givens variables for the current study, presence of hand washing facility for food handlers also one of the identified factor, means that ,those who had hand washing facility in their kitchen area were 6.5 times more good practice than those who had not hand washing facility and when looking the other literatures this factor also as identified factors .for instance the study conducted in the study conducted in Mekele town (Lalit I. et al 2015) ,this possible reason may be that presences of hand washing facility may help the food handles to keep their personal hygiene like hand washing and to clean their utensil as time they wants, Current study also identify that lack of supervision as gap for good safety practice, mean that those food handlers who were doing in facility where supervision held were 3 times had good safety practice than those who were doing in where there is not supervision held. This finding is supported with study conducted Cassino, Italy (Elisa Langianoet al, 2011) and in Arba Minch (Legesse D et al). Really the presence of supportive supervisors improve the food handlers, food handling practice by giving practical support and feedback on food handling.
Conclusion and Recommendations Conclusion
The magnitude of satisfactory food safety practice is low in this study. Variables like knowledge about food safety practice, hand washing facility for food handlers and presence of supervision were identified as factors significantly associated with food safety practice.
Recommendations
Based on major findings of the study important recommendations are listed below.
Godey Zonal as well as Godey warada Health bureau together with cultural and truism bureau is expected to work better in making strong supportive supervision for food establishments and it is better to Godey warada environmental health professions give awareness on food safety practice and food safety knowledge.
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Domain: Agricultural And Food Sciences
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Design and Analysis of The Strength of Rice Transport Vehicle Frames
. Merauke Regency is one of the largest rice producers in Papua Province with a total production of 344,192.32 tons in 2020, a harvested area of 61,584 ha and a rice productivity of 5.59 tons/ha. Agricultural development in Merauke Regency is supported by the availability of agricultural land and the modernization of agricultural equipment. The post-harvest process is the final phase that is key to success, so it must be handled properly to achieve maximum results once the post-harvest rice begins with the rice harvest. The rice harvest must be supported by a robust transport vehicle in wet and muddy fields. Vehicles with caterpillar drive wheels are compatible because the ground pressure is lower. The design of the rice transport vehicle selects the track wheel type as the drive wheel so that it can be used on wet and muddy surfaces. The vehicle chassis is designed for the transport of 1000-1500 kg of rice. The construction and analysis are simulated with Autodesk Inventor software; the Chasis model is analyzed for strength using the finite element method.
Introduction
Rice is a plant that is easy to live with in almost every region of Indonesia. Rice is resistant to dry or rainy weather, resistant to pests, easy to grow (one rice stalk can produce eight rice stalks), and relatively quick (four months old). Almost every province in Indonesia has a rice harvesting area that caters to the needs of the population [1].
Merauke Regency is one of the largest rice producers in the Papua Province with a total production of 344,192.32 tons in 2020, a harvested area of 61,584 ha and a rice productivity of 5.59 t / ha [2]. The amount of rice production is increasing from year to year according to the New land clearing in% continues. Agricultural development in Merauke Regency is supported by the availability of agricultural land and the modernization of agricultural tools. The farmers in Merauke currently cultivate rice fields with agricultural machines, from pressure areas for planting, planting, tending to harvesting and post-harvest [3]. The use of agricultural machinery is one way of increasing the productivity and efficiency of agriculture, increasing the quality and added value of products, and empowering farmers. In essence, the use of machines in agriculture consists in increasing the human labor force in the agricultural production process, whereby agricultural tools and machines can be used at any stage of the production process [4]. Therefore, the mechanization of agriculture * Corresponding authoris expected to increase the efficiency of human labor, the degree and standard of living of farmers, the quantity and quality ofagricultural production, enable the growth of subsistence agriculture to commercial agriculture, and accelerate the transition of economic forms. Indonesia from agricultural to industrial nature [5].
The post-harvest process is the final phase that is the key to success. Therefore, the handling must be done well. In order to achieve maximum results, post-harvest rice begins with the rice harvest, the implementation of which is based on the age of the plant and which is influenced by various factors, namely variety, climate and altitude. Place it so that the age of the rice harvest varies, and the difference is between 5 and 10 days. The characteristics of rice ready to be harvested are when 90-95% of the grains are pithy or have changed color from yellow to golden yellow. The harvest age is 30-35 days after uniform flowering or after 135-145 days after planting, with the moisture content of the grain in the summer between 22-23% and 24-26% in the rainy season [6]. When harvest time comes, farmers will use agricultural tools and machinery that are classified as conventional and modern. Conventional rice harvesters and machines include ani-ani and sickle. Modern rice harvesting tools and machinery include a reaper, a reaper binder, and a combine harvester. In addition to using a rice harvester, a transport vehicle in the form of a hand tractor is also used when transporting rice, with which rice carts are pulled.
Hand tractor is the most common vehicle used to transport rice. However, since the drive wheel is a tire wheel type, it is less difficult for the hand tractor to carry rice in the rain, resulting in wet and muddy rice fields. A vehicle that is suitable for transporting rice in the fields is a vehicle with a caterpillar wheel because the pre-ground insurance is less than that of the tire, which allows the vehicle to move well in wet and muddy areas without rice immersion / bedding. The rice transport vehicle design chooses the crwler wheel type as the drive wheel so that it can operate on land with wet and muddy surfaces. The vehicle chassis is designed for 1000-1500 kg of rice. Design and analysis are simulated using the Autodesk Inventor software. The strength of the Chasis model is analyzed using the finite element method.
Material Chassis
Steel is a metal that is widely used in industry. When choosing the chassis material, steel is used for several advantages such as wear resistance, ductility and toughness. Steel is a type of metal that is widely used with the element carbon as one of the basic compounds. According to Ahmed et al. (2017: 431), steel has a good value in terms of yield point and ultimate strength, namely with careful management and processing. The steel used is AISI 1018 steel [7]. stated that the AISI 1018 steel material has good toughness, strength, ductility and weldability. The physical properties of the AISI 1018 steel material from design data in Autodesk Inventor Professional software are shown in Mass density = The relationship between the mass of a substance and its volume (density).
Welding
The assembly process between parts in chassis modeling uses welding and bolt simulations. The welding takes place on a permanent connection. The weld joint used is a fillet joint. This type of weld joint is used for connections between frames and multiple connections between frames and brackets. Welding has various advantages in the production world, such as economy, dimensional accuracy and variations in the shape of the weld structure. However, welding can also have adverse effects such as: B. Changes in the microstructure, decrease in strength and toughness of the material, deformation and residual stress [9].
Autodesk Inventor Professional Software
Autodesk Inventor Professional 2017 is a type of Computer Aided Drawing (CAD) software that emphasizes solid modeling [11,12]. Autodesk Inventor is a parametric 3D modeling software. The term parametric refers to the use of design parameters to create and control the designed 3D model. That is, in order to start creating a design, it is necessary to make a basic sketch with dimensions. These dimensions are used as parameters to control the length and width of the sketchsimulations.
Finite Element Analysis
Finite element analysis (FEA) was used for the modified design and a comparative analysis was performed to check the stress and displacement values [13,14]. FEA is also known as finite element analysis or finite element method. The way FEA works is to break down a structural object to be tested into finite elements that are interconnected and managed by the software with special calculations. In Autodesk Inventor Professional, the analysis is performed using stress analysis tools. Stress Analysis is a structural test tool in Autodesk Inventor that applies the FEA concept. Stress analysis on the vehicle chassis aims to determine the stress that occurs when the chassis receives a load [15]. country.
Design Process
The design process consists of the steps that must be followed in order to manufacture a product. Different or reduced steps lead to different product yields. The design process in designing and analyzing the strength of rice transporting vehicles is computationally performed using Autodesk Inventor software.
The steps to be taken to create the design and strength analysis results on the chassis of the rice transport vehicle are as follows: a) Literary studies Literature studies come from previous journals that relate to the research to be carried out. A literature review examines the strengths and weaknesses of existing research in order to be taken into account in the research to be carried out. b) Design model The design model is used as a reference before the software is modeled. The design model in the chassis design uses the Pahl and Beitz design models. The design model begins with planning and explaining the product, designing product concepts, designing product shapes, and designing product details. c) Model Use Autodesk Inventor Professional 2017 software to design a chassis with a given geometry and determine the type of connection using welding and bolting simulation.
d) Data and material input
This phase is the input o f material data, the determination of restrictions, contacts, meshes and the determination of charging points. Material data is entered in the Autodesk Inventor Professional 2017 software via the material tool. The edge area is determined on the seat, which is directly related to the suspension. It is believed that this seat is rigid with suspension and does not experience displacement due to loading.
Results and Discussion
The results of the structural analysis when tested with Autodesk Inventor Professional software in the form of von Mises stress, displacement and factor of safety. The report data of this simulation is a computational calculation using the finite element method in stress analysis. Conclusions on structural analysis must correspond to the feasibility standard, the results of the von Mises stress analysis must be below the yield strength value [16]. and the safety factor must be" 4" [10]. The data obtained from software processing in the form of numerical data, graphs and simulations of von Mises stress, displacement and safety factors found in every geometry from the smallest to the largest. Descriptive analysis is performed to determine the feasibility of a design by ensuring that the design stress does not exceed the allowable stress of the material. The analyzed data is numbers obtained from stress analysis tests in the form of von Mises stress, displacement, and safety factors from Autodesk Inventor Professional software (FEA)
Chassis Strength Analysis Results
The chassis simulation of the transport vehicle is carried out with a total load of 15,000 N. The load analysis is done by determining the weight of each load, which is assumed to be a total weight of 15,000 N on each side of the vehicle chassis. The weld connection used is a fillet weld type. Weld joints of this type are used for connections between frames and some connections between frames and brackets.
Conclusions
Chassis design with specifications chassis length 6000mm, chassis width 2500mm, using AISI 1018 steel material, rectangular model with dimensions 120x80x3mm. The Von Mises stress value for AISI 1018 106 HR steel material is 29.06 MPa for the standard mesh, 28.6 MPa for the 10 mm control mesh and 28.15 MPa. The displacement value for AISI 1018 106 HR steel material is 0.3643 mm for the standard grid, 0.3704 mm for the 10 mm control grid and 0.3764 mm for the 5 mm control grid. The safety factor for AISI 1018 106 HR steel material is 9.32 for the standard fabric, 9.45 for the 10 mm control fabric and 9.58 for the control fabric.\===
Domain: Agricultural And Food Sciences. The above document has
* 2 sentences that start with 'Agricultural development in Merauke Regency',
* 2 sentences that start with 'The vehicle chassis is designed',
* 2 sentences that start with 'The design model',
* 2 sentences that end with 'wet and muddy surfaces',
* 2 sentences that end with '1000-1500 kg of rice',
* 2 sentences that end with 'research to be carried out',
* 2 paragraphs that start with 'Autodesk Inventor Professional',
* 2 paragraphs that end with 'using the finite element method'. It has approximately 1872 words, 91 sentences, and 26 paragraph(s).
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Contact Toxicity Effects of Selected Organic Leaf Extracts of Tithonia diversifolia (Hemsl.) A. Gray and Vernonia lasiopus (O. Hoffman) against Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae)
Maize weevil (Sitophilus zeamais) infestation results in a substantial reduction in the quantity and deterioration of the quality of stored maize. Most farmers control weevils using conventional pesticides which are usually associated with several human health risks as well as intoxication of the fauna and flora. However, bioinsecticides form an alternative intervention since they possess fewer side effects on human health, are ecofriendly, and are readily available. 'is study sought to validate and document, in a systematic way, the pesticidal properties of the species Tithonia diversifolia and Vernonia lasiopus used for many years by many people of the world on S. zeamais. 'e plant leaf samples were obtained from Embu County, Kenya. Dichloromethane and ethyl acetate solvents were used to extract active phytochemicals from the dried plant sample powder. 'e GC-MS analysis of the obtained extracts was performed at ICIPE laboratories to identify their phytochemical compositions. Twenty grams of maize grains were put in 50ml plastic vials and admixed with different treatments. 'e positive control group was treated with Actellic SuperTM, while the negative control was treated with the respective extracting solvent only. 'e experimental groups were separately treated with the plant leaf extracts at doses of 25, 50, 75, and 100%. After treatment, each of the six groups was infested with 10 male S. zeamais and weevil mortality as a result of contact toxicity of the treatments was assessed at 6, 24, 48, 72, and 96 hours after the insects were exposed to the extracts. Results of the study indicate that the selected organic leaf extracts of T. diversifolia and V. lasiopus possessed significant contact insecticidal effects that ranged between 1.67 to 99.98%. Furthermore, the GC-MS analysis revealed several active biocompounds in T. diversifolia and V. lasiopus extracts, which are known for their considerable insecticidal effects. Our data suggest that the organic leaf extracts of T. diversifolia and V. lasiopus have considerable insecticidal properties and would, therefore, be a valuable bioprotective agent for stored maize grains against S. zeamais.
Introduction
Postharvest losses due to storage pests have been recognized as an increasingly important constraint to maize production. In spite of the great value of maize, its availability and utilization have been impaired due to grain damage caused by notorious postharvest insect pests in developing countries. Maize weevil, S. zeamais (Coleoptera: Curculionidae), is a small agricultural insect pest in the beetle family Curculionidae (snout beetles). It is the single most important primary pest that attacks stored maize grains, among others insect pests such as the larger grain borer Prostephanus truncatus Horn (Coleoptera: Bostrychidae) [1,2]. Weevil infestation causes an estimated annual loss of 30-50% of stored maize grains in tropical Africa [3].
Farmers normally control insect pests using synthetic insecticides. However, these chemicals are expensive and are arguably associated with deleterious side effects on the environment. e synthetic pesticides invoke resistance over time. Insecticide resistance among strains of maize weevil has been found to different registered synthetic grain protectants such as deltamethrin, Primiphos-methyl, permethrin, and Lindane and may become a much more serious problem in the future [4,5].
e toxicity effects of pesticides on insects such as weevils have different possible physiological end points which practically impose toxic effects that kill the targeted pests [6][7][8]. Pesticides can be inhaled (fumigants), ingested, or absorbed via the insect body surface due to the abrasive effect on the pest cuticle as contact toxicants [9]. Although with some exceptions, an ingested insecticide will induce a more severe response than the same amount of insecticide encountered by an insect through direct contact or fumigation [10]. e nonconventional methods employed to control weevils on stored maize include the use of inert dusts, sanitary pest control methods involving consistent cleaning and disinfestation of storage structures, freezing, and use of ionizing radiation, as well as the use of hermetic techniques [11][12][13].
Different plant materials of Vernonia lasiopus have also exhibited antifungal and antimalarial activities among others [1]. It is applied on cattle bodies to control livestock ticks (Boophilus microplus) in pastoralist communities in Kenya [23]. e leaves and stem decoction of V. lasiopus is used by herbalists in Eastern Province, Kenya, to treat malaria, helminths, and nonbacterial infections [24]. Farmers in Embu County, Kenya, use the leaves of T. diversifolia and V. lasiopus on stored maize cobs to protect them against weevil infestation. However, no scientific research has been conducted to evaluate this described effect. It is against this background that this study was designed to explore and provide information on the contact toxicity effects of the selected organic extracts from T. diversifolia and V. lasiopus against adult S. zeamais.
Plant Sample Collection.
e plants used in this study, T. diversifolia and V. lasiopus, were collected from their natural habitat in Makunguru Village, Nthawa Location, Siakago division, Mbeere North subcounty, Embu County, Kenya. e GPS locations for T. diversifolia and V. lasiopus specimens were 0°35′39″S, 37°38′10″E and 0°35′39.51″S, 37°38′23.62″E, respectively. e fresh leaves were identified and collected from mature plants with the help of local herbalists. e folklore information obtained included the local name of the plants, part of plants harvested, season of harvesting, method of preparation, and other medicinal importance of the plants. Samples were properly sorted out, cleaned, and transported in bags to Kenyatta University, in the Biochemistry, Microbiology, and Biotechnology departmental laboratories. e plant samples were provided to an acknowledged taxonomist for botanical authentication and voucher specimens deposited at the Kenyatta University Pharmacy and Complementary/Alternative Medicine research herbaria.
Sample Preparation and Extraction.
e leaves of T. diversifolia and V. lasiopus were air-dried separately under shade and at room temperature for a period of two weeks. e leaves were separately ground into fine powder using a grinding electric mill and sieved using a 300 µm mesh.
e powder was used for extraction following the guideline used by Singh [25]. Extraction was separately conducted with dichloromethane (DCM) and ethyl acetate to ensure maximum extraction of a wide variety of compounds [26].
Two hundred grams of each plant leaf powder was separately soaked in 200 ml of the respective solvents for 12 hours. e extracts were decanted and 200 ml of solvent was added and set for 24 hours. After 24 hours, filtration was carried out again and 200 ml of the respective solvent was added for the final extraction until 48 hours when the last filtrate was obtained. Occasional swirling was performed to ensure thorough extraction. Aluminum foil and cotton wool were always used to cover the flasks to prevent escape of solvent. Muslin cloth and Whatman No. 1 papers were used for the filtration of the extracts. e extract filtrates were then concentrated in vacuum using the Heidolph rotary evaporator, and the solvent was recovered. e concentrates were further allowed to dry to remove traces of the solvents and yield dry extracts. All extracts were later kept in sample bottles and refrigerated (4°C) awaiting use in pesticidal bioassays. e percent extraction yields of the DCM and EtOAc leaf extracts of the two plants were determined using the following formula: Percent (%) extract yield � mass of extract obtained (g) mass of sample(g) × 100. (1)
Preparation of Extract
Concentrations. e plant extract concentrates were diluted with the respective solvents at a concentration of 1 gml −1 , and this was termed as the stock solution (100% v/v concentration) as described by Deshmukh and Borie [27] with limited modifications. e concentrations used were 25% and 100% (v/v). ese extract concentrations were prepared as follows: the 25% (v/v) concentration was prepared by diluting 1 ml of the stock solution with 3 ml of solvent to make up 4 ml. e 50% (v/v) concentration was prepared by diluting 2 ml of the stock solution with 2 ml of the solvent to make up 4 ml, while for the 75% (v/v) concentration, 1 ml of the solvent was added to 3 ml of stock solution to make up 4 ml.
Preparation of Maize Grains.
To eliminate the effect of varietal resistance to S. zeamais infestation, a susceptible maize variety was obtained as a test variety for use in this study [21]. e experimental grains were cleaned and standardized using the method of Sulherie et al. [28]. e damaged kernels were sorted out and the clean ones were put in a deep freezer at −20°C for three days to eliminate any eggs, larvae, pupae, or adult weevils. e dead weevils were sieved out and grain aired for 72 hours prior to use. is acclimatization of the maize grains stabilized the moisture content at 12-13%, thereby ensuring its suitability for feeding by weevils [16].
Rearing and Sexing of Maize Weevil (Sitophilus zeamais).
A stock culture of the maize weevil, S. zeamais, was initiated by collecting adult weevils from infested maize grains and cultured in their food media (susceptible whole maize grains) under fluctuating ambient temperature and relative humidity. Two hundred unsexed adult weevils were introduced into five two 2 l bottles with 500 g of maize. e insects were allowed to oviposit for seven days after which they were sieved out and subsequently used for the bioassay experiments. e insect stock culture was further maintained in glass bottles of 2 l capacity containing maize grains. e weevils were reared subsequently by replacing devoured and infested grains with fresh, clean, uninfected grains in containers covered with muslin cloth to allow for air circulation and prevent escape of insects. e muslin cloths covering the containers were held in place with rubber bands. e maize dust was periodically sieved to prevent the growth of mould, which may lead to the caking of grains and ultimate death of the insects. Sitophilus zeamais breeding and experiments were conducted at an ambient temperature of 27 ± 2°C, relative humidity of 75 ± 5.5%, and suitable photoperiod (LD 12 : 12). e culture maintained was used throughout the period of this study. e weevils were sexed morphologically under a dissecting microscope using the methods of Ojo and Owoloye [29] by examining the weevil's rostrum and abdominal shape of the insects. Male S. zeamais were identified with a rough, distinctly shorter, and wider rostrum, while the female was identified with a smooth, shiny, distinctly longer, and narrower rostrum than that of the male. e male and female weevils were, hence, separated into different insect stock jars.
Gas Chromatography-Mass Spectrometry (GC-MS)
Analysis. Gas Chromatography-Mass Spectrometry (GC-MS) analysis of the DCM and ethyl acetate leaf extracts of T. diversifolia and V. lasiopus was performed using the procedure previously used by Dar et al. [30]. Analysis of the sample was carried out using GC-MS (7890/5975, Agilent Technologies, Inc., Beijing, China) consisting of a gas chromatograph interfaced to a mass spectrometer. e GC-MS was equipped with an HP-5 MS (5% phenyl methyl siloxane) low-bleed capillary column of 30 m length, 0.25 mm diameter, and 0.25 µm film thickness. For GC-MS detection, an electron ionization system with an ionization energy of 70 Ev was used. e carrier gas used was helium (99.99%) at a constant flow rate of 1.25 ml/min in the split mode. e injector and mass transfer line temperature were set at 250°C and 200°C, respectively, and an injection volume of 1 µl was employed. e oven temperature was programmed from 35°C for 5 minutes, with an increase of 10°C/ minute to 280°C for 10.5 minutes and then 50°C/minute to 285°C for 29.9 minutes with a run time of 70 minutes. e MS operating parameters were ionization energy: 70 eV; ion source temperature: 230°C, solvent cut time: 3.3 minutes, scan speed: 1666 µ/second; scan range: 40-550 m/z; and interface temperature: 250°C. Interpretation of mass spectrum from GC-MS analysis was performed using the central database of the National Institute of Standard and Technology (NIST), which contains more than 62,000 patterns. As for the unknown components, their spectrum was compared with those which are known from the NIST library [30].
Experimental Design.
e determination of contact toxicity experiments adopted a randomized controlled study design (RCD) with four replications. e experiments were set up into six independent treatment groups ( Table 1) with four replicates (n � 4) per treatment group. In the negative control, maize grains were treated with the respective solvent only, while for the positive control group, the grains were treated with Actellic Super ™ at a recommended dose of 50 g/ 90 kg grains.
Determination of contact toxicity tests was carried out as follows: twenty grams of maize grains were weighed and put into 50 ml plastic vials. 1.0 ml of each plant extract at predetermined concentrations of 25, 50, 75, and 100% was added. e mixture was shaken gently to ensure uniform coating of grains. After the grains and extracts were thoroughly mixed, the setups were air-dried for 2 hours to evaporate all traces of solvents. Twenty male adult S. zeamais were introduced into each plastic vial and then tightly covered with a lid. Several tiny openings were made on the lid of the plastic vials to ensure ventilation.
Weevil mortality as a result of fumigant and contact toxicity was assessed 6, 24, 48, 72, and 96 hours after the insects were exposed to the extracts. After these test observation periods, the plastic vials were opened and the weevils transferred into an open recovery tray for five minutes before mortality was assessed.
e insects were confirmed dead if they could not move their appendages when probed with a sharp pin on the abdomen [31]. Corrected mortality percentages were then computed using Abbort formula [32]: where P r � corrected mortality.
Data Management and Statistical Analysis.
e number of dead weevils (D n ) was obtained from the different groups for each of the two plant extracts at the five test durations. e data obtained were recorded and later tabulated on a broad sheet. Corrected percent weevil mortalities (Pr) were formulated and computed using Ms Excel program. e data were checked for normality using the Kolmogorov-Smirnov test and then analyzed through descriptive statistics and presented as mean ± SEM. e data from different treatment groups were also subjected to inferential statistics using oneway ANOVA followed by Tukey's post hoc test for separation and pairwise comparisons of means. e significant difference between the treatment groups was reported at p ≤ 0.005. e resulting data of this study were presented in the form of tables and bar graphs. Unpaired Student's t-test was used for pairwise separation and comparison of means between different treatment groups for the two plants. e analyses were conducted using Minitab version 17 software as the statistical tool.
Quantitative Phytochemical Analysis of the Selected Organic Leaf Extract of T. diversifolia and V. lasiopus.
e GC-MS analysis of the organic leaf extract of T. diversifolia and V. lasiopus revealed the presence of several phytocompounds as presented in Tables 2 and 3. Results of percentage (%) extract yields applied in determining the concentration (ng/g) of the phytochemical revealed in the organic leaf extracts of the two are tabulated in Table 4. e dichloromethanolic extracts of T. diversifolia had the highest yield of 1.69% followed by ethyl acetate extracts of T. diversifolia (1.44%) ( Table 4). e dichloromethanolic and ethyl acetate extracts of V. lasiopus had the lowest yield of 0.56 and 0.54%, respectively (Table 4). e GC-MS results of the present study showed the presence of active insecticidal compounds in the organic leaf extracts of T. diversifolia and V. lasiopus. ese compounds include lipids (fatty acid esters and phytosterols), terpenoids (monoterpenes, diterpenes, triterpenes, and sesquiterpenoids), and phenolic compounds (Tables 2 and 3). Tables 3 and 5 show, the DCM leaf extracts of T. diversifolia and V. lasiopus generally caused remarkable weevil mortality upon contact. It was observed that the two plants manifested an increase in weevil mortality with an increase in exposure time to weevils throughout the experimental period. In this study, the solvent (dichloromethane) was reported to have no weevil-killing potential throughout the experimental period (Tables 5 and 6). e T. diversifolia extract caused dose-dependent effects, except in the first and second observation times of 6 and 24 hours after exposure to weevils. Six hours after exposure to weevils, the T. diversifolia extract dose of 75% evoked the highest weevil mortality of 36.25%. However, this was not significantly different from the effects caused by the rest of the extract concentrations (p > 0.005; Table 5).
Contact Toxicity Effects of DCM Leaf Extracts of T. diversifolia and V. lasiopus against S. zeamais. As
Twenty-four hours after exposure to weevils, the T. diversifolia extract dose of 75% caused the least weevil mortality (72.47%), which was significantly lower than the effects caused by the other dosages (p < 0.005; Table 5). At the same time, the T. diversifolia extract doses of 25, 50, and 100% evoked statistically similar weevil-killing abilities, which also matched the effects caused by Actellic Super ™ (p > 0.005; Table 5).
Following 48, 72, and 96 hours of exposure to weevils, the contact toxicity effect of the T. diversifolia extract at all concentrations was comparable to each other (p > 0.005; Table 5). Furthermore, the effects caused by the T. diversifolia extract concentrations were found to be statistically comparable to the effects of the standard pesticide, Actellic Super ™ , after these long durations of exposure to S. zeamais (p > 0.005; Table 5).
On the other hand, the DCM leaf extracts of V. lasiopus also demonstrated considerable dose-dependent contactinduced weevil mortality. However, it was apparent that none of the V. lasiopus extracts caused weevil mortality in a comparable fashion to that caused by the standard pesticide, Actellic Super ™ (p < 0.005; Table 6). e V. lasiopus extract concentrations of 25 and 50% caused comparable weevil mortality throughout the experimental period (p > 0.005; Table 6). e two highest Actellic Super ™ � 50 g/90 kg grain; solvents � 1 ml DCM/EtOAc. International Journal of Zoology 5 extract concentrations (75 and 100%) caused significantly different weevil mortalities upon contact (p < 0.005; Table 6). is was only in exception of the observation noted after 72 hours of exposure to weevils, when the two dosages caused statistically similar mortalities of 43.7 and 57.45%, respectively (p > 0.005; Table 6). However, these effects were significantly lower than the effects of the reference pesticide, Actellic Super ™ (p < 0.005; Table 6).
In comparison, it was observed that the DCM leaf extract of T. diversifolia generally evoked a more effective weevilkilling potential as compared to the V. lasiopus extract ( Figure 1). Nevertheless, following 6 hours of exposure to weevils, the extracts of both T. diversifolia and V. lasiopus, at the doses of 75 and 100%, showed no significant difference in their effectiveness (p > 0.005; Figure 1). However, during the rest of the experimental period, the T. diversifolia extract remained significantly the most potent plant against S. zeamais (p < 0.005; Figure 1).
Contact Toxicity Effects of the Ethyl Acetate Leaf Extract of T. diversifolia and V. lasiopus against S. zeamais.
Overall, the ethyl acetate leaf extracts of T. diversifolia and V. lasiopus demonstrated weevil-killing ability, which increased with the increase in extract dosage (Tables 7 and 8).
e effectiveness of these plant extracts was also found to increase with an increase in exposure time to maize weevils. e weevils in the negative control group were found alive, showing zero percent mortality (Tables 7 and 8). is study demonstrated that, apart from the T. diversifolia extract dose of 100%, none of the other dosages showed weevil mortality comparable to that caused by Actellic Super ™ following a short duration (six hours) of exposure to weevils (p ≤ 0.005; Table 7). In the rest of the experimental period, it was found that the T. diversifolia extract doses of 75 and 100% were as effective as the standard pesticide, Actellic Super ™ (p > 0.005; Table 7).
After 48 and 72 hours of exposure to weevils, the effectiveness of the T. diversifolia extract doses of 25 and 50% was found to be comparable to each other (p > 0.005) although significantly lower than that of the rest of the treatments (p ≤ 0.005; Table 7). At the last observation time (96 hours after exposure), the T. diversifolia extract dose of 50% was found to be equally effective as the extract doses of 75 and 100% as well as the reference pesticide, Actellic Super ™ (p > 0.005; Table 7).
Similarly, the ethyl acetate leaf extract of V. lasiopus also caused dose-dependent weevil mortality, which increased with an increase in exposure time. Six hours after exposure to weevils, the V. lasiopus extract evoked weevil mortalities of 12.50, 23.75, 32.50, and 41.25% at doses of 25, 50, 75, and 100%, respectively. ese effects were significantly different from those reported by both positive and unprotected grain samples (p < 0.005; Table 8).
It was apparent that the effectiveness of the V. lasiopus extract at low doses of 25 and 50% was not significantly different from each other (p > 0.005) except after 48 hours of exposure. Likewise, the high extract doses (75 and 100%) evoked statistically similar weevil mortality except after 24 hours of the V. lasiopus extract exposure to weevils (p > 0.005; Table 8).
is study further demonstrated that the effect of the V. lasiopus extract did not match the effectiveness of the synthetic pesticides after a short duration of exposure to weevils (<48 hours). However, the higher extract dosages of V. lasiopus (75 and 100%) evoked mortalities which were comparable to each other as well to the effect caused by Actellic Super ™ following a long duration of exposure to weevils (72 and 96 hours) (p > 0.005; Table 8). It was also evident that, after long durations of exposure to weevils (72 and 96 hours), the V. lasiopus extract doses of 25 and 50% remained equally effective (p > 0.005) but significantly lower than other treatments (p ≤ 0.005; Table 8).
Upon comparison, the ethyl acetate leaf extract of T. diversifolia generally demonstrated more potent weevilkilling ability as compared to the V. lasiopus extract (Figure 2). All concentrations of the T. diversifolia extract showed significantly higher weevil mortality after 6, 24, and 48 hours of exposure to the weevils than the effects of the V. lasiopus extract (p ≤ 0.005; Figure 2). However, following 72 hours of exposure to weevils, the 100% dose of the two plants showed no significant statistical difference in their effectiveness against S. zeamais (p > 0.005; Figure 2). At the observation time of 96 hours, the two extracts, at extract concentrations of 25, 75, and 100%, were equally effective against S. zeamais (p > 0.005; Figure 2). Values are expressed as mean ± SEM for four replicates per group (n � 4). Statistical comparisons were made within a column, and values followed by the same superscripts along the column are not significantly different by one-way ANOVA (p ≥ 0.005) followed by Tukey's post hoc test. Actellic Super ™ � 50 g/90 kg of maize grains; solvents � 1 ml DCM/EtOAc. 6 International Journal of Zoology Probit analysis was performed to obtain the 50% lethal dose of the four selected organic leaf extracts. e concentration of the selected organic leaf extracts of T. diversifolia and V. lasopus that killed 50% of the 20 weevils exposed to extracts every 24 hours for a period of 96 hours was recorded. e LD 50 revealed DCM leaf extract of T. diversifolia to be the most effective biopesticide, while DCM leaf extract of V. lasopus was reported as the least effective of the tested extracts (Table 9).
Discussion
e present study was designed to assess the toxicity effects of organic leaf extracts of T. diversifolia and V. lasiopus against S. zeamais. It was apparent that the two plants possess contact toxicity properties on adult weevils. e extracts showed toxicity ratings that ranged between a moderately low toxicity of 31.57% and a very high toxicity of 99.93% after 96 hours of exposure to weevils. International Journal of Zoology 7 e insecticidal findings of the present study are in accordance with many other studies that reported botanicals as effective controls against major stored grain pest species.
ere is immense scientific literature on both crude extracts of plants and isolated phytochemicals with insecticidal effects against storage pests [33]. For instance, according to Ikbal and Pavela [34], O. basilicum, M. piperita, P. anisum, M. pulegium, A. indica, and F. vulgare, among others plant species, have shown outstanding effectiveness against insects [34]. e essential oils of cinnamon, clove, rosemary, bergamot, and Japanese mint also showed effective fumigant toxicity against pulse beetle [35]. Similarly, the present findings support the results of Stoll [36], who reported that organic leaf extracts of various plants have effective toxicity against insect pests of various crops in the field and in stores. e insecticidal nature of essential oils of P. angolensis and P. quadrifolia was also manifested by contact action on adult insects of S. cerealella [36].
To evaluate the contact toxicity effects of the alcoholic leaf extracts of T. diversifolia on termites, Oyedokun et al. [37] used similar test dosages used in this study and demonstrated equally high toxicity effects of T. diversifolia on termites. Similar laboratory-based tests were carried out to determine the toxicities of methanolic, hexane, and methanolic: hexane blend extracts of Allium sativum on maize weevils using four concentration levels of 25, 50, 75, and 100% by Ouko et al. [39]. e results of this study showed a direct relationship between the level at which the plant extract treatments were applied and their effectiveness on S. zeamais . e effects of the treatments at different extract concentration levels on the S. zeamais were notably different from each other. In general, the bioactivities of DCM and EtOAc leaf extracts of T. diversifolia and V. lasiopus were directly proportional to the extract concentrations. e higher the plant extract concentration, the more potent the extract.
at the number of dead weevils increased with the increasing concentration could be due to the increase in bioactive components as the concentration of the extract increases such that it is likely that, at the lower dose, there was no sufficient concentration of the active principle(s).
is variability can also be explained by the fact that the probability of feeding on the botanical insecticidal compounds along with the extract particles increases with the increase in concentration.
is correlation suggests International Journal of Zoology that the organic extracts of the two plants can best be applied at 100% v/v concentration to have a better kill of maize weevils. According to Ouko et al. [39], this may be due to the fact that the combination of the active phytocompounds was in the best proportional mixture for optimum insecticidal activity at 100% v/v extract concentration. at the higher dose such as that of 100% was not as effective as at the lower dose level of 75% may be due to the fact that the high dose takes longer to be absorbed across the insect cuticle to the targeted site. at the insecticidal effectiveness increased with extract concentration and exposure time in this study is consistent with previous findings on the effects of organic plant extracts on various pest insects including S. zeamais, A. obtectus, B. brassicae, and T. castaneum [39][40][41][42][43][44][45][46][47]. e extracts manifested a higher mortality with an increased exposure time of the weevils to the treated maize grains.
is observation could be explained by the fact that an increase in exposure time allows for more contact time with the target pest and, hence, permits an increase in uptake of active constituents, hence the observed higher mortality with longer exposure span.
is is consistent with other previous studies carried out using Citrullus colocynthis, Cannabis indica, and Artemisia argyi extracts against insect pests. ese extracts exerted adverse effects against insect pests such as Brevicoryne brassicae L. at increasing concentrations and prolonged exposure periods [48]. e trend was also consistent with the findings in [49,50] that showed a positive concentrationdependent correlation of A. sativum versus mortality in pulse beetle and maize weevils, respectively. e toxicity activities of the two plant extracts on the weevils varied relatively according to the solvent used during extraction. e content and activity of the extracted phytochemicals depend on the polarity of the solvent and the solubility of the bioactive compounds in the mother solvent. erefore, the extracting solvent plays an important role in the biocidal potency of plant crude extracts [48,51,52], and this was evident in the present study.
Previous studies have shown that nonpolar organic solvents such as ethyl acetate extract, pesticidal nonpolar compounds such as terpenoids and phytosterols [53], and medium-polar solvents such as dichloromethane effectively extract flavonoids, terpenoids, phytosterols, fatty acids, alkaloids, and phenols [53,54] which also exhibit pesticidal properties. Polar organic solvents such as methanol usually extract polar compounds such as amino acids, sugars, and glycosides, which are not particularly associated with pesticidal activities [54,55]. e variation in the toxicity effect of the extracts in this study can, therefore, be attributed to the varying phytochemical composition of the extracts. e higher mortality exhibited by the ethyl acetate leaf extracts indicated that this organic solvent extracted more active compounds with insecticidal activity than the DCM leaf extracts. erefore, in this study, the contact insecticide activities of EtOAc and DCM leaf extracts exhibited no significant difference, which suggests that using either of the two extraction solvents renders no difference. e GC-MS analysis revealed that the organic leaf extracts of T. diversifolia and V. lasiopus contain phytochemical compounds which are toxic to insect pests and parasites. ese compounds include phytosterols, fatty acids, α-pinene, citronellol, 1,8-cineole, limonene, linalool, α-terpineol, caryophyllene oxide, sabinene, and eugenol among others [56,57]. When absorbed through the insect body surface, these compounds interfere with the basic metabolic, biochemical, physiological, and behavioral functions of the target insects. Insecticidal properties may be linked to the main phytochemicals extracted, reportedly acting alone or in synergy with others including minor constituents, thus potentiating its contact toxicity effects on weevils [58,59].
Fatty acids identified by GC-MS analysis of the selected organic leaf extracts of T. diversifolia and V. lasiopus have previously been demonstrated to have insecticidal effectiveness against S. zeamais among other insect pests [60,61]. It is, therefore, not strange that the extracts killed the adult weevils in the present assay. Furthermore, the insecticidal effects of these fatty acids have been suggested to enhance the efficacy of microbial insecticides such as Bacillus thuringiensis [62]. e observed contact toxicity on weevils may be due to nonanoic acid, which is a naturally occurring saturated fatty acid also found in the studied extracts. Usually, ammonium salt, which is a form of nonanoic acid, is used as a herbicide that works by stripping the waxy cuticle of the plant, thereby causing cell disruption, cell leakage, and death of plants by desiccation. Similarly, the chemical might have stripped off the insects' cuticles causing cell leakage and eventual mortality of the weevils [63].
Major phytosterols also revealed in the GC-MS analysis of the organic leaf extracts of T. diversifolia and V. lasiopus can be associated with the extract toxicity effects on the weevils. Stigmasterol is among the phytosterol compounds whose accumulation in the body leads to cardiac injury and, hence, promotes mortality [64].
Para-xylene may cause death of organisms through affecting the central nervous system if swallowed or causing chemical pneumonitis when breathed into the lungs [65].
is suggests that p-xylene found in the organic leaf extracts of T. diversifolia and V. lasiopus could be responsible for toxicity effects of the extracts on weevils in the present study. Furthermore, previous studies have suggested that p-xylene could cause damage to development and reproductive systems [65]. e pesticidal effects of the selected organic leaf extracts of T. diversifolia and V. lasiopus could also be due to the presence of α-pinene in these extracts. Benelli et al. [66] reported that α-pinene contained in the organic leaf extract of C. sativa contributed to 98.20% insect mortality. Insecticidal properties of α-pinene have been demonstrated against Tribolium confusum, Tribolium castaneum, Sitophilus zeamais, Callosobruchus maculatus, and Rhyzopertha dominica. Furthermore, the results of Benelli et al. [67] also indicated a similarly high mortality of M. persicae, also associated with the presence of α-pinene in the organic extracts of Aulacorthum solani.
International Journal of Zoology Uptake of eugenol from the plant extracts may also have contributed to the high mortality of adult insects in this study. Eugenol has been reported to have effective toxicity effects against insects such as aphids, houseflies, and cockroaches [68,69]. e insecticidal activities of various plant species such as C. cinnamomum and C. cymbopogon against houseflies (M. domestica) have also been largely associated with the predominance of eugenol phytochemicals in plant essential oils [69].
According to the GC-MS analysis, the organic leaf extracts of T. diversifolia and V. lasiopus contained limonene whose insecticidal activities have been extensively reported against various insects such as C. maculatus, C. subinnotatus, B. brassicae, fleas, and ticks among others [70][71][72]. Similarly, it is probable that the death of weevils in this study was as a result of their exposure to limonene. e toxicity effects of these extracts could also be as a result of the presence of linalool. Insecticidal properties of linalool have been demonstrated against Sitophilus zeamais, Tribolium confusum, Tribolium castaneum, Callosobruchus maculatus, and Rhyzopertha dominica. Few reports have been published regarding the mode of action of linalool in insects. However, similar to limonene, linalool is thought to cause the death of insects by affecting the activity of nerves in insects [73][74][75].
e insecticidal activity of the organic leaf extracts of M. lucida has previously been attributed to sabinene among other known major components of oxygenated monoterpenes in the extract [76]. It is, therefore, likely that the toxicity effect of organic leaf extracts of T. diversifolia and V. lasiopus on adult weevils in this study was contributed by sabinene, which was also identified during phytochemical analysis of these extracts. e toxicity of the extracts on adult weevils in the present study could also be linked to the presence of α-bulnesene in the organic leaf extracts of T. diversifolia and V. lasiopus. According to Albuquerque et al. [77], α-bulnesene extracted from Pogostemon cablin exhibits insecticidal activities against various urban ant species.
Additionally present in the studied extracts is caryophyllene oxide, which is an insecticidal sesquiterpene and, hence, probably responsible for the toxicity of the organic leaf extracts of T. diversifolia and V. lasiopus on weevils. According to the work in [78], sesquiterpenes such as (E)caryophyllene oxide are naturally pesticidal. Caryophyllene oxide identified in the organic extracts of Melaleuca styphelioides was found to exhibit strong insecticidal properties against Aphis spiraecola, Aphis gossypii, and M. persicae [79].
Caryophyllene in the root bark of Chinese bittersweet, Celastrus angulatus Max., was largely associated with the toxicity effects of the plant extract against insects such as Mythimna separate [78]. Furthermore, a closely similar (E)caryophyllene, myrecene, that was extracted from C. sativa, was reported to exhibit effective insect-killing potential on A. solani and M. persicae [66,67]. e insecticidal activity of organic leaf extracts of T. diversifolia and V. lasiopuscould be as a result of other terpenoids such as 1,8-cineole ?-terpineol, terpinen-4-ol, and linalool that were found to be highly present in the studied extracts.
As much as the extracts of V. lasiopus showed the presence of several insecticidal phytochemicals (terpenoids, phenolics, phytosterols, fatty acids, and alkaloids), their concentration levels were notably low to induce an effective weevil mortality in comparison to the effectiveness of T. diversifolia extracts. erefore, that the organic leaf extracts of V. lasiopus had lower toxicity against maize weevils could be attributed to the presence of these potent compounds in lower concentrations than the concentrations in the organic leaf extracts of T. diversifolia. e standard insecticide used in this study, Actellic, is a persistent broad-spectrum insecticide. Actellic has fumigant, stomach, and contact activity against insect pests. It is conventionally used for the control of storage pests in bulk stored grains, bagged grains, and storage surfaces. It effectively controls weevils, large grain borers, and other insects and mites on stored grains and pulses. It contains permethrin (3 g/kg) and pirimiphos-methyl (16 g/kg) as its active ingredients, which gives Actellic an effective control against storage pests. Pirimiphos-methyl is taken by the insect through its respiratory system and affects the pests through its fumigant and repellence effects. On the other hand, permethrin is able to penetrate the insect cuticle and, hence, effect its contact and stomach actions on pests [85].
It is worth noting that, during the 48 hours of the test observation time, the fumigant activity of EtOAc leaf extract of T. diversifolia at the highest tested extract concentration of 100% was marginally more effective (97.47% and 91.22%, respectively) than Actellic (82.47%). is suggests a possibly better insecticidal mechanism of the extracts or mimicry of the Actellic mode of action by the active phytochemicals in the studied extracts. It is also possible that the EtOAc and DCM leaf extract of T. diversifolia was efficiently inhibiting alternative mechanisms for killing weevils. e possible cause of toxicity of these extracts on weevils is through inhibition of acetylcholinesterase enzyme. Many phytochemicals affect neurotransmission and signal transduction in organisms [86]. Binding of these antagonists to acetylcholinesterase receptors causes physiological and biochemical disturbances and blockage. e subsequently observed effects include restlessness, lack of coordination, unconsciousness, and eventual death of the insect as similarly observed in the present study [86].
ese observed effects as well as the rapid action of the extracts against weevils were suggested as indicative of a neurotoxic mode of action and interference of the neuromodulator (acetylcholine or octopamine) or the GABA-gated chloride channels [87].
Nevertheless, the observed toxicity of the studied extracts on weevils could also be due to that the active constituents in these extracts targeted voltage-gated sodium channels. ese channels are vital for electrical signaling in most excitable cells. Pesticidal alkaloids from sabadilla, pyrethrins, and Tanacetum cinerariae folium target these channels and bind to the specific receptors on them, hence altering their gating functions [90]. Likewise, the pesticidal phytocompounds in this study could have acted by blocking the sodium channel pores and altered their functions. is may have resulted in the cell being reexcited, inhibiting the generation of action potentials, leading to paralysis and ultimate death of the weevils [91].
Other probable mechanisms that caused the death of adult weevils in this study could include DNA intercalation, interference of protein biosynthesis, antagonistic activity of the GABA receptor chloride channel, and disruption of membrane stability in the insect by phytochemicals. ere is a positive correlation between the degree of DNA intercalation and inhibition of DNA polymerase I, reverse transcriptase, and translation at the molecular level and with toxicity against insects at the organismic level [86]. Gammaaminobutyrate (GABA) is a main inhibitory neurotransmitter in both vertebrates and invertebrates. In insects, although inhibitory transmission relies mainly on gammaaminobutyrate (GABA) [87,92,93], unlike in mammals, GABA receptors of insects have a regulatory function not only in the central nervous system but also in the peripheral one [87,93]. e terpenoids present in star anise (Illicium sp.) were found to show an antagonist activity on the GABA receptor of Musca domestica [92].
Conclusions
e present study demonstrates that the organic leaf extracts of T. diversifolia and V. lasiopus have phytochemicals endowed with considerable insecticidal effects via insects' body contact toxicity on S. zeamais. e studies, hence, reveals the possible potency of the extracts in the management of the S. zeamais population on stored grains.
Data Availability
All data used in this study are included in this research paper.
Conflicts of Interest
e authors declare no conflicts of interest.
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Domain: Agricultural And Food Sciences
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Acidification Effects on In Situ Ammonia Emissions and Cereal Yields Depending on Slurry Type and Application Method
: Field application of organic slurries contributes considerably to emissions of ammonia (NH 3 ) which causes sever environmental damage and can result in lower nitrogen (N) fertilizer efficiency. In recent years, field acidification systems have been introduced to reduce such NH 3 emissions. However, combined field data on ammonia emissions and N use efficiency of acidified slurries, in particular by practical acidification systems, are scarce. Here, we present for the first time a simultaneous in situ assessment of the effects of acidification of five different organic slurries with a commercial acidifications system combined with different application techniques. The analysis was performed in randomized plot trials in winter wheat and spring barley after two applications to each crop (before tillering and after flag leave emergence) in year 2014 in Denmark. Slurry types included cattle slurry, mink slurry, pig slurry, anaerobic digestate, and the liquid phase of anaerobic digestate. Tested application techniques were trail hose application with and without slurry acidification in winter wheat and slurry injection and incorporation compared to trail hose application with and without acidification in spring barley. Slurries were applied on 9 m × 9 m plots separated by buffer areas of the same dimension. Ammonia emission was determined by a combination of semi-quantitative acid traps scaled by absolute emissions obtained from Draeger Tube Method dynamic chamber measurements. Experimental results were analysed by mixed effects models and HSD post hoc test ( p < 0.05). Significant and almost quantitative NH 3 emission reduction compared to trail hose application was observed in the barley trial by slurry incorporation of acidified slurry (89% reduction) and closed slot injection (96% reduction), while incorporation alone decreased emissions by 60%. In the two applications to winter wheat, compared to trail hose application of non-acidified slurry, acidification reduced NH 3 emissions by 61% and 67% in cattle slurry, in anaerobic digestate by 45% and 57% and liquid phase of anaerobic digestate by 58%, respectively. Similar effects but on a lower emission level were observed in mink slurry, while acidification showed almost no effect in pig slurry. Acidifying animal manure with a commercial system was confirmed to consistently reduce NH 3 emissions of most slurry types, and emission reductions were similar as from experimental acidification systems. However, failure to reduce ammonia emissions in pig slurry hint to technical limitations of such systems. Winter wheat and spring barley yields were only partly significantly increased by use of ammonia emission mitigation measures, while there were significant positive effects on apparent nitrogen use efficiency (+17–28%). The assessment of the agronomic effects of acidification requires further investigations.
Introduction
Atmospheric nitrogen (N 2 ) is transferred into reactive forms (Nr), e.g., through industrial fixation into ammonia (NH 3 ) (~80 Mt N yr-1). The primary purpose of this nitrogen (N) conversion is to support food production through fertiliser use. About 50% of the current human population depends on synthetic nitrogen fertilisers [1] for food. Nr not taken up by the crop is lost to the environment. The side effects of this Nr in the environment include global warming, acidification of soil, eutrophication of habitats, and water quality deterioration, as well as formation of atmospheric micro-particles [2]. In particular, agricultural NH 3 emissions (90% of total European Union NH 3 emissions) cause about 45% of airborne eutrophication, 31% of soil acidification, and 12% of fine dust formation within the EU 15 [3]. NH 3 emissions also mean a considerable loss of fertiliser nitrogen for the crop [1]. Emissions of NH 3 are accountable for the acidification and eutrophication of nitrogen-limited ecosystems [3]. About 40-50% of the global anthropogenic NH 3 emissions are related to manure from livestock production [4]. Additionally, less than 50% of the N input in agriculture is utilized in agronomic outputs [5]. A better understanding of the use of organic fertilisers is required to reduce Nr emission. Petersen et al. [6] stressed that farmers have to consider new strategies for manure management to minimise environmental impact and increase fertiliser value.
Ammonia volatilization is influenced by type and composition of slurry, application technique, pH level of soil and manure, as well as environmental conditions, such as temperature, wind and rain [7][8][9]. Trailing hose application is considered as environmentally friendly application system in many European countries and is applicable in growing crops [10]. However, emissions can still be high, and this calls for further reduction [7]. Further emission reduction can classically be attained by incorporation systems as slurry injection [11] or mixing slurry with surface soil. Arable closed slot injectors use a strong tine to inject slurry at about 0.1 m depth and cover applied slurry with soil immediately after application. Injection has become a common application method in countries with strong environmental regulations on manure use (such as the Netherlands and Denmark) [10], and strong emission reduction was proven in many field trials [7]. In addition, pre-treatment of slurries on-farm can help to reduce ammonia emissions from field applied slurries. Among those are additives (clay minerals, humic acids), solid-liquid separation or manure aeration [12,13]. However, for some of the pretreatments, it is still uncertain whether they can reduce ammonia or other trace gas emissions for the whole slurry life cycle.
As a new approach for emission reduction, slurry acidification was introduced to manipulate slurry pH, which shifts the NH 4 + /NH 3 equilibrium and thereby reduces ammonia emissions. All else being equal, a one unit reduction in pH reduces NH 3 concentration by a factor of ten [9,10]. In practice, mainly highly concentrated sulphuric acid is used for pH adjustment, thereby adding sulphur as a major plant nutrient. There exist two main approaches: on-farm acidification [14] with higher acid demand and stronger pH stabilization and single point field acidification [15]. The latter adjusts slurry pH to one specific level immediately before application. Commercial suppliers of single point field acidification systems recommend the adjustment of the pH value to 6-6.5 pH to have an NH 3 emission reduction of around 50%. The amount of acid needed to reach the target pH value varies depending on slurry properties [16]. Slurries may react differently to acidification due to variable pH buffer capacity [17], initial pH value, and specific composition (e.g., dry matter concentration). Farmers may be motivated to use slurry acidification because of its reduction of NH 3 emission while sustaining high manure application efficiency [10], potentially increasing fertiliser N efficiency with lower soil compaction compared to slurry injection [18].
However, mainly laboratory systems and experimental systems with acidification procedures differing from commercially available systems were used to derive ammonia emission reduction factors for acidification and its agronomic effects. While experimental systems adjust slurry pH in the tank some time before it is pumped to the application tubes, acid is dosed instantaneously before slurry release in commercial systems. Slurry pH is A straightforward comparison and assessment of acidification systems requires a better understanding of effects of fertiliser type and application technologies under same experimental conditions [19]. Due to methodological limitations, effects of treatments on ammonia emissions are usually assessed for a specific emission source only [6]. Standard quantitative NH 3 loss measuring methods require large field areas, expensive equipment, or an electrical supply. Their application in replicated field trials is limited [19] and statistical assessment of agronomic effects are scarce. Generally, four replicates per treatment are chosen in agronomic trials to allow statistical testing, which is usually not achieved in applying standard quantitative methods. Statistical assessments are then made across trials, sites and years. In the present study, the requirement of simultaneous tests of slurries and application systems was considered by quantitative ammonia loss measurement in sufficiently replicated field plots. The same approach was successfully applied by Seidel et al. [15]. However, such a simultaneous assessment of a wide range of slurries and commercial application systems under field conditions was performed for the first time in the present study compared to earlier research.
Manure processing by anaerobic digestion creates new slurry types (anaerobic digestate and its separated liquid fraction), that vary from untreated manure, and it can also bring changes or increases in NH 3 and GHG (greenhouse gas) emissions [20]. Manure processing as, e.g., solid-liquid separation, is also increasingly standard in various countries [21]. There exists no published information on slurry acidification effects on ammonia losses and yield performance from such substrates. Due to high pH buffering capacities and initial pH, it is discussed whether acidification is practically feasible applying biogas digestates regarding acid requirements and robustness of the pH reduction. Similarly, there exists no information on how slurry incorporation systems interact with slurry acidification with respect to ammonia emissions and slurry yield effects.
The treatments for this experiment were designed to represent commonly used organic slurries applied to winter wheat and spring barley in Denmark and other northwestern European regions. Five organic liquid fertilisers (dairy cattle, mink, and pig slurry, as well anaerobic digestate and separated anaerobic digestate) were applied evenly by four application methods and their combinations (band spreader, incorporation with rotary cultivator, shallow closed slot injection and single point field acidification) to 9 m × 9 m plots on two locations in four trials. Loss of NH 3 was determined under different canopy conditions, i.e., crop heights and leaf areas.
We investigated, for the first time in a single trial design, how slurry acidification in interaction with slurry application techniques and slurry type influence NH 3 emissions and slurry N use efficiency. This was performed to give a proper insight in slurry acidification as a NH 3 reduction measure and to identify emission mitigation approaches that deliver the highest ammonia emission reduction efficiency. The objectives were to quantify acid addition requirements of the five different slurries for emission reduction and mitigation potentials of combined application methods. Crop yields were determined to assess the plant nutrition effect of reduced ammonia emission by acidification. Guiding hypotheses were: Ammonia loss reduction effects of the commercial system are similar to experimental systems; Effectiveness of a fixed acid dose on slurry pH and ammonia emission reductions varies among slurry types; Ammonia loss reduction significantly translates in higher yields and N use efficiency; Combining slurry acidification with slurry incorporation systems for NH 3 emission reduction yield stronger NH 3 loss reductions and thereby more pronounced yield effects.
Experimental Sites
Four slurry application trials were carried out in 2014: two trials at the beginning of April and two at the beginning of May. Within each experiment, three to ten treatments were tested. The experiments were performed with two applications to spring barley (Hordeum vulgare L.) on the first trial site and two applications to winter wheat (Triticum aestivum L.) on separate plot areas on the second trial site. Two slurry applications to spring barley were performed on the same yield trial, resulting in altogether 3 trials on yield effects of slurry types and management. Winter wheat was sown in September 2013. The two fields were located close to the Research Centre Foulum, Central Jutland, Denmark. The podzol soils (World reference base) in spring barley and winter wheat had a loamy sand texture with no crop residues (Table 1) and no tillage less than 1 week before slurry application. Soil textures did not vary significantly within fields due to a flat terrain with equally distributed soil conditions and properties (~5 ha for each experiment). Both study areas were located within a distance of~1.8 km, and climate is characterised as a temperate coastal maritime climate with mean annual precipitation of~704 mm [22,23]. Due to cool temperatures and regular rainfall events before application, soil surfaces were moist at slurry spreading.
Experimental Set-Up
Slurry fertilizer effects on crops and ammonia volatilization losses were quantified simultaneously across treatments using a randomized block design (n = 4). Experimental plots were 9 × 9 m each, arranged with an interspace of 9 m to each other. (Figure 1). Four slurry application trials were carried out in 2014: two trials at the beginning of April and two at the beginning of May. Within each experiment, three to ten treatments were tested. The experiments were performed with two applications to spring barley (Hordeum vulgare L.) on the first trial site and two applications to winter wheat (Triticum aestivum L.) on separate plot areas on the second trial site. Two slurry applications to spring barley were performed on the same yield trial, resulting in altogether 3 trials on yield effects of slurry types and management. Winter wheat was sown in September 2013. The two fields were located close to the Research Centre Foulum, Central Jutland, Denmark. The podzol soils (World reference base) in spring barley and winter wheat had a loamy sand texture with no crop residues (Table 1) and no tillage less than 1 week before slurry application. Soil textures did not vary significantly within fields due to a flat terrain with equally distributed soil conditions and properties (~5 ha for each experiment). Both study areas were located within a distance of ~1.8 km, and climate is characterised as a temperate coastal maritime climate with mean annual precipitation of ~704 mm [22,23]. Due to cool temperatures and regular rainfall events before application, soil surfaces were moist at slurry spreading.
Experimental Set-Up
Slurry fertilizer effects on crops and ammonia volatilization losses were quantified simultaneously across treatments using a randomized block design (n = 4). Experimental plots were 9 ×⋅9 m each, arranged with an interspace of 9 m to each other. (Figure 1). Figure 1. Experimental design of one block, used for multi-plot NH3 loss measurements with passive samplers by square treatment plots (9 m × 9 m), Plots were separated by 9 m non-fertilised buffers. Treat. = treatment; Check = control plot with background measurement; 100/150 N = 100/150 kg N ha −1 synthetic CAN fertilizer; arrows = 9 m distance. Figure 1. Experimental design of one block, used for multi-plot NH 3 loss measurements with passive samplers by square treatment plots (9 m × 9 m), Plots were separated by 9 m non-fertilised buffers. Treat. = treatment; Check = control plot with background measurement; 100/150 N = 100/150 kg N ha −1 synthetic CAN fertilizer; arrows = 9 m distance.
Slurry Types
On the spring barley field, a single cattle slurry was investigated with five application methods, whereas on the winter wheat field only trail hose application was used, applying five slurries both with and without acidification (Tables 2 and 3). Slurry applications were based on the same total ammoniacal N (TAN) application rates. In winter wheat the following slurries were included: dairy cattle slurry (CS), cofermented anaerobic digestate (AD), liquid phase separated anaerobic digestate (AS), mink (MS) and pig (PS) slurry. Due to higher TAN concentrations compared do CS and digestates, mink and pig slurry were applied with smaller volumes. The latter two slurries were also characterized by low DM and viscosity compared to the other slurries. The slurries were similar to other liquid manures in Denmark and were produced at the Foulum Experimental Centre, sourced from farmers close to the research area and the Foulum biogas plant. The biogas slurry (non-and separated anaerobic digestate) was a co-fermented liquid manure, fermented with cattle solid manure, chopped straw and pasture grass.
Slurry Fertilization and Application Methods
Five strategies for CS application ( Table 2) were investigated at two application dates in spring barley: before sowing (1 April 2014) and at 4-leafs stage (1 May 2014): (1) Trail hose application followed by incorporation within 4 h by power harrow (inc), before sowing; (2) Trail hose application of acidified CS, followed by incorporation within 4 h by power harrow (inc ac) before sowing; (3) Shallow closed slot injection (inj) before sowing; (4) Trail hose application (th) at EC 22; (5) Trail hose application + acidification (ac) at EC 22.
For the NH 3 measurements before sowing, 2 plots (9 m × 9 m) with trail hose applied CS were added for the derivation of the ammonia emission transfer factor [24] and as reference for emission reduction by mitigation techniques. Slurry application rate was the same as in the other CS treatments. These two plots were not included in yield evaluation.
In winter wheat, two different slurry application dates were tested: 3rd and 30th of April. Both trials were located on the same field. The first application was performed at the end of stem elongation stage, while the second application was performed at flag leaf emergence. Altogether 10 slurry treatments (5 slurries × 2 acidification levels) were tested ( Table 2). Sulphuric acid dosage was determined from titration measurements performed prior to field application, but the resulting pH in the field was often different from the target of 6.0.
All slurry treatments also received a second N dosage of Sulphur amended Calcium Ammonium Nitrate (CAN 24-0-0-6), 25 kg N/ha in spring barley and 30 kg N/ha in winter wheat. CAN was applied when slurry was fertilized in the respective other barley or wheat trial. As a result, in all slurry treatments, about 110 kg/ha of mineral N was applied, mainly as ammoniacal nitrogen.
In both, barley and winter wheat, two N levels of Sulphur amended CAN (0, 100 and 150 kg N/ha) were included as a reference and for evaluation of nitrogen use efficiency of tested slurries. Plots with no N fertilisation were included for N control, NUE and NH 3 background concentration measurements.
Trail hose application was performed with a commercial system (Samson, SB 16-24, folded at 16 m), reduced to the operating width of 9 m. The closed slot injection machine had a width between the tines of 0.06 m and an injection depth set between 0.10-0.13 m.
In-field slurry acidification was performed with a commercial single point acidification system (Gødningsudstyr, Kyndestoft Maskinfabrik ApS, Vesterled 38 A, 7830 Vinderup, Denmark), mixing slurry with 50% sulphuric acid. The acid was pumped from a tank to the application tubes. The mixture was then directly applied to the soil.
For slurry analysis, samples of all slurries were taken at every application at trail hose openings. These samples were analysed for TAN. (Tables 2 and 3).
The application rates of slurry were based on slurry ammonium N concentrations and standard slurry application rates in Denmark.
Ammonia Emissions
For determination of NH 3 loss, the plot centres were equipped with passive flux samplers, first applied in the standard comparison method (SCM) [25] but used here in combination with a calibrated dynamic chamber method (Dräger Tube Method (DTM), [26] for scaling of the semi-quantitative loss obtained by the passive flux samplers with a transfer factor derived from the DTM to absolute losses [15,27,28]. Transfer coefficients were obtained by the simultaneous measurement with passive sampler and DTM on 2-4 treatment plots with trail hose application and 2 unfertilized control plots by simultaneous measurements with both methods. The measurements on the unfertilized plots are used for the quantification of NH 3 background concentrations and identification of eventual drift of emitted ammonia between treatment plots. Areas dedicated for harvest within each plot were not to be touched by the chamber and passive sampler measurement procedures.
Emission measurements started immediately after application. In each experiment, slurry treatments were applied sequentially, each slurry type after another, with slurry application finalized before afternoon. Plots receiving CAN were not included in the measurements, due to the low emissions potential connected with this fertilizer [29,30]. Emission reduction effects are expressed in relation to emissions from the respective reference treatment, which was cattle slurry applied by trail hoses for the barley trial, and the respective unacidified slurry in the winter wheat trials.
The passive sampler was located in the centre of a square plot at the height of 0.15 m above soil or canopy, directly after slurry application and contained 20 mL of 0.05 M sulphuric acid for NH 3 absorption. The solution in the samplers was exchanged every 3 to 4 h and was later analysed for ammonia concentrations with an ammonia-electrode (Thermo Scientific, Beverly, MA, USA). Samples were directly moved to the lab and kept frozen (−18 • C) until measurement. Measurements with DTM were made at least at two locations within a plot per measurement date. In detail, stainless steel rings were placed into the upper soil level of one plot for each treatment immediately after slurry application. Two were placed in the slurry application and two between the slurry strips to gain representative slurry coverage. By experience, band applied slurries cover about 50% of the treated area [28]. Each time four chambers were inserted and connected to an NH 3 indicator tube and an automatic pump to ensure a defined flow rate through the dynamic chambers. Raw data obtained from dynamic chambers measurements were corrected to account for ambient wind conditions by a calibration formula [26]. Ammonia emission measurements lasted until no fluxes could be detected, between 72-96 h.
The resulting NH 3 fluxes of the calibration plots allowed the calculation of cumulative N-loss for each treatment plot. The transfer coefficient is derived as average from 2 (barley trials)-4 (winter wheat trials) plots. Due to the large set of ammonia data only cumulative losses are presented. Emission dynamics are shown in the Supplementary Material.
Meteorological Measurements
A local weather station was placed in the field throughout the entire trial period. Following data was recorded: air temperature, wind speed, wind direction, and relative humidity. The weather station was fitted at the experimental site, which included a 2Daxis ultrasonic anemometer at the height of 2 m, providing wind speeds (0-60 m s −1 ) and wind direction data (WindSonic4 Gill Ultrasonic Anemometer, model: SDI12 OPT4, Gill Instruments Limited, Hampshire, United Kingdom). Further, a thermo-hygro sensor (CS215 Temperature and RH Probe, Campbell Scientific, Logan, Utah, United States of America) was set at 1 m height for air temperature and air humidity.
Precipitation was not measured in the fields. Additional rainfall data were obtained from Foulum weather station.
Yield and Nitrogen Use Efficiency
Cereal yields were determined by harvest of 13.5 m 2 with a plot scale combine harvester (Haldrup C-85, InotecGmbH, DK 9670 Løgstør). Cereal yields are reported on a basis of 14% water content (t ha −1 ). Nitrogen yield is quantified by grain protein concentration (% of DM) and N uptake by grain (kg N ha −1 ). The plant samples were dried at 80 • C for 24 h to provide the dry matter (DM) yield. The total plant N content was analysed from the oven-dried material after burning the material at 900 • C, where the N-oxides and molecular N was determined by LECO TruSpec CN (St. Joseph, Michigan, MI, USA) as described in [31].
N use efficiency is quantified and assessed by the calculation of apparent nitrogen recovery efficiency (ANRE, [32], Equation (1)) N F = sum of N uptake by grain and stem (kg N ha −1 ) of fertilized treatment; N control = sum of N uptake by grain and stem (kg N ha −1 ) of unfertilized control; N fert = N applied by fertilizer (kg N ha −1 ).
Statistics
Ammonia emission data were analysed by a mixed effects model and HSD post hoc test, separately for each slurry application campaign. Variables included in the models differed between summer barley and winter wheat, generally "block" was treated as random effect, while treatment (combination different factors e.g., slurry type +/− acidification), slurry type, acidification and application date were included as fixed effects. The response variable was plot-level total NH 3 emission for the complete trial duration. Yield data were analysed by a stratified statistical approach. For both, winter wheat and summer barley, as the first, step a one-way mixed effects model including all fertilizers and treatments as fixed factor and block as random factor were applied. In case of a significant effect of a fixed factor, a Tukey post hoc test to differentiate treatment levels was carried out with an alpha <0.05. As the study design was not balanced, data subsets were created to analyse the effects of slurry application date, slurry type, and acidification as fixed factors in a multi-factorial mixed effects model for the winter wheat trials. For this analysis only slurry treatments, i.e., 5 slurries with and without acidification at the two application dates were selected. In the case of summer barley, two subsets were created. First, to test the effect of acidification in interaction with application technique, only treatments with and without acidification were included in a 2-way mixed effects model analysis, which were a trail hose application and harrow incorporation. To check for the effect of slurry application techniques, only different slurry application techniques treatments without acidification were selected for a one-way mixed effects model. In all analyses, "block" was the single random effect in the models. Tukey post hoc test was used to differentiate between treatment levels. Statistical calculations were performed with the program R (version R-3.0.1) with the package "agricolae" (version 1. [2][3]. For mixed effects model analysis and following post hoc tests, the R-packages "nlme" and "emmeans" were used (R package version 3.1-152).
NH 3 Emissions
Average wind speed during all NH 3 measurement campaigns was about 3.3 m s −1 in April and 3.0 m s −1 in May. Throughout the experiments, an average temperature of 6.7 • C was measured (see also Supplementary Material). No precipitation occurred within the first days of experimental periods, a part of a 1 h rain (1 mm) event at the beginning of the first barley trial (data Foulum weather station). Emissions in both winter wheat and the second barley trial were by on-setting rainy periods on the third day of emission measurements.
Summer Barley Trials
In summer barley all abatement treatments significantly reduced NH 3 emissions compared to trail hose application ( Figure 2, NH 3 emission dynamics Figure S1). Incorporation reduced NH 3 emissions by 59%, incorporation with acidification by 89%, while closed slot injection yielded the highest reduction effect of 96%. Setting the incorporation treatment as a reference point, emissions were further reduced by additional acidification by 72% and were not significantly different from the closed slot injection emissions. In the second barley trial acidification reduced NH 3 loss of applied CS by 74% compared to the non-acidified variant. In summer barley all abatement treatments significantly reduced NH3 emissions compared to trail hose application ( Figure 2, NH3 emission dynamics Figure S1). Incorporation reduced NH3 emissions by 59%, incorporation with acidification by 89%, while closed slot injection yielded the highest reduction effect of 96%. Setting the incorporation treatment as a reference point, emissions were further reduced by additional acidification by 72% and were not significantly different from the closed slot injection emissions. In the second barley trial acidification reduced NH3 loss of applied CS by 74% compared to the non-acidified variant. Lowercase letters indicate significant differences between treatments at p < 0.05 (n = 4 except n = 2 for CS th 1st trial; mixed effects model, HSS test p < 0.05; lowercase letters indicate significant differences between treatments; CS, cattle slurry; th, trail hoses; inc, harrow incorporation; inj, closed slot injection; ac, acidification).
Winter Wheat Trials
Comparing the emissions of the two winter wheat trials, a significantly higher emission level (test not shown) was observed in the first trial, although overall conditionsapart from canopy height-did not differ between trial periods. Lowercase letters indicate significant differences between treatments at p < 0.05 (n = 4 except n = 2 for CS th 1st trial; mixed effects model, HSS test p < 0.05; lowercase letters indicate significant differences between treatments; CS, cattle slurry; th, trail hoses; inc, harrow incorporation; inj, closed slot injection; ac, acidification).
Winter Wheat Trials
Comparing the emissions of the two winter wheat trials, a significantly higher emission level (test not shown) was observed in the first trial, although overall conditions-apart from canopy height-did not differ between trial periods.
In the first winter wheat trial, NH 3 emissions from all slurry types were reduced by acidification except for PS (Figure 3, NH 3 emission dynamics Figure S2). The multi-factorial statistical test thus resulted in a significant main effect of slurry acidification in interaction with slurry type. Slurry type was also a highly significant factor in the analysis with higher relative ammonia emissions for cattle slurry and anaerobic digestate. Significantly, acidification reduced emissions of CS by 61%, AD by 57%, MS by 74%, and AS by 58%, considering all slurry types individually. In the second winter wheat trial (Figure 4), the same main effects were observed in the multivariate model. Losses from MS and PS, as well as AS, were not significantly reduced by acidification when considering separate paired comparisons. However, across all tested slurries there existed a significant main effect of acidification and slurry type. However, there was also a significant interaction between acid and slurry type.
Acid Requirements
On average, separated anaerobic digestate had the highest acid requirement of 4.9 kg H 2 SO 4 per pH unit per t slurry, followed by cattle slurry (4 kg), mink slurry (3.5 kg), anaerobic digestate (3.3 kg) and pig slurry (2.0 kg), the latter with a rather low acid requirement ( Figure 5). Although the target pH value was pH of 6, measured pH values at the trail hose outlet differed considerably from the target value. However, emission reduction values were neither correlated with measured pH values after acidification nor with pH change between acidified and un-acidified slurry or slurry dry matter concentrations. When omitting separated digestate slurries with specifically high acid demand from the analysis, NH 3 emission reduction effects of acidification on the remaining four slurries were closely (r 2 = 0.98) related to sulphuric acid addition (including separated digestate r 2 = 0.63).
Acid Requirements
On average, separated anaerobic digestate had the highest acid requirement of 4.9 kg H2SO4 per pH unit per t slurry, followed by cattle slurry (4 kg), mink slurry (3.5 kg), anaerobic digestate (3.3 kg) and pig slurry (2.0 kg), the latter with a rather low acid requirement ( Figure 5). Although the target pH value was pH of 6, measured pH values at the trail hose outlet differed considerably from the target value. However, emission reduction values were neither correlated with measured pH values after acidification nor with pH with pH change between acidified and un-acidified slurry or slurry dry matter concentrations. When omitting separated digestate slurries with specifically high acid demand from the analysis, NH3 emission reduction effects of acidification on the remaining four slurries were closely (r 2 = 0.98) related to sulphuric acid addition (including separated digestate r 2 0.63).
Yield Variables
In both crops, yields (Figures were low compared to average grain yield levels in the region, in particular for summer barley. N application levels were chosen based on these yield expectations which probably resulted in excess fertilization. With respect to protein concentrations, summer barley concentrations were high (>10%), indicating low economic value for use of brewing barley, while protein concentration in wheat were low (~10%), indicating poor economic return due to poor grain quality.
Neither in barley nor in the two winter wheat trials did single fertilizer treatments show significant effects on yield compared to the other fertilizer treatments, with exception of incorporation of acidified slurry by harrow in summer barley (Figures 6 and 7). In addition, the CAN treatments resulted in no significantly higher yields. However, Figure 5. pH values before and after single point acidification and acid requirements averaged across both winter wheat trials 2014. Sulphuric acid (50%) was used for pH level reduction, target pH level of 6. PS, pig slurry; MS, mink slurry; AS, liquid phase separated anaerobic digestate; AD, anaerobic digestate; CS, cattle slurry.
Yield Variables
In both crops, yields (Figures were low compared to average grain yield levels in the region, in particular for summer barley. N application levels were chosen based on these yield expectations which probably resulted in excess fertilization. With respect to protein concentrations, summer barley concentrations were high (>10%), indicating low economic value for use of brewing barley, while protein concentration in wheat were low (~10%), indicating poor economic return due to poor grain quality.
Neither in barley nor in the two winter wheat trials did single fertilizer treatments show significant effects on yield compared to the other fertilizer treatments, with exception of incorporation of acidified slurry by harrow in summer barley (Figures 6 and 7). In addition, the CAN treatments resulted in no significantly higher yields. However, when analysing the data by multi-factorial models, in particular, acidification showed significant main factor effects on yield variables (Tables 4 and 5, all data in Supplementary Table S1). §: *, significant factor; ns, nonsignificant; acid, acidification (+/−); fert, slurry type (M, mink; P, pic; AS, liquid phase anaerobic digestate; A, anaerobic digestate; C, cattle; date, application date (early, late).
Barley Trials
In the summer barley trial, acidification resulted in a significant main factor effect with higher values in grain yield (+28%), N grain uptake (+9%), total N uptake (+10%) and ANRE (+9%). Only protein concentration was not significantly influenced (Tab 4). The multifactorial analysis of the three application methods in summer barley yielded significantly higher total N uptake, protein concentration and ANRE, while grain yield and grain N uptake remained unaffected. In particular, injection of slurry was more efficient than trail hose application, while there was only a trend for higher values for slurry incorporation with harrow. Lowercase letters indicate significant differences between treatments; ac, acidification; CS, cattle slurry; th, trail hose; inj, closed slot injection; inc, incorporation with harrow; 100/150, kg N/ha applied as CAN. §: *, significant factor; ns, nonsignificant; acid, acidification (+/−); fert, slurry type (M, mink; P, pic; AS, liquid phase anaerobic digestate; A, anaerobic digestate; C, cattle; date, application date (early, late).
Barley Trials
In the summer barley trial, acidification resulted in a significant main factor effect with higher values in grain yield (+28%), N grain uptake (+9%), total N uptake (+10%) and ANRE (+9%). Only protein concentration was not significantly influenced (Tab 4). The multifactorial analysis of the three application methods in summer barley yielded significantly higher total N uptake, protein concentration and ANRE, while grain yield and grain N uptake remained unaffected. In particular, injection of slurry was more efficient than trail hose application, while there was only a trend for higher values for slurry incorporation with harrow. Application methods without acid treatment § acid = acidification (ac+, with acid; ac−, without acid); tec = application technique (th, trail hose; inc, incorporation by harrow; inj, closed slot injection). Table 5. Yield effects of 5 slurry types applied with and without acidification (sulphuric acid) to winter wheat at two different application dates. Mixed effects models with HSD post hoc test (p < 0.05), * = significant main and interaction effects, ":" between factors indicate interaction effects, different letters indicate significance levels (values level "a" > values level "b").
Barley Trials
In the summer barley trial, acidification resulted in a significant main factor effect with higher values in grain yield (+28%), N grain uptake (+9%), total N uptake (+10%) and ANRE (+9%). Only protein concentration was not significantly influenced ( Table 4). The multifactorial analysis of the three application methods in summer barley yielded significantly higher total N uptake, protein concentration and ANRE, while grain yield and grain N uptake remained unaffected. In particular, injection of slurry was more efficient than trail hose application, while there was only a trend for higher values for slurry incorporation with harrow.
Winter Wheat Trials
In the winter wheat trial, timing of slurry and CAN application had a significant effect on yield levels ( Table 5) with higher yields with the second slurry application. After multivariate analysis of the effects of slurry types and acidification, both showed significant main factor effects on all yield variables excluded grain yield (Figure 8). Acidification resulted in +9% grain N uptake, +9% total N uptake, +7%, protein and +27% ANRE (Table 5, Figure 9). However, there existed interaction effects on grain N uptake between slurry type and acidification and between slurry type and application date. Acidification showed pronounced effects in PS, CS and AD, while only minor effects were observed for mink and, although not significant, negative effect in AS.
When considering ANRE as the main N efficiency measure applied in this study, acidification showed a consistent significant positive effect across both crops and in both wheat trials (Figure 9, Tables 4 and 5).
Winter Wheat Trials
In the winter wheat trial, timing of slurry and CAN application had a significant effect on yield levels ( Table 5) with higher yields with the second slurry application. After multivariate analysis of the effects of slurry types and acidification, both showed significant main factor effects on all yield variables excluded grain yield (Figure 8). Acidification resulted in +9% grain N uptake, +9% total N uptake, +7%, protein and +27% ANRE (Table 5, Figure 9). However, there existed interaction effects on grain N uptake between slurry type and acidification and between slurry type and application date. Acidification showed pronounced effects in PS, CS and AD, while only minor effects were observed for mink and, although not significant, negative effect in AS.
When considering ANRE as the main N efficiency measure applied in this study, acidification showed a consistent significant positive effect across both crops and in both wheat trials (Figure 9, Tables 4 and 5).
NH3 Emissions
The study compared the efficacy of different technological measures to reduce ammonia emissions from field application of several slurry types. The application systems used could all be used with the same operational quality because the sandy soils allowed easy handling of the systems. In contrast to many other slurry acidification trials, a commercial field acidification system was used. Thus, trial performance was technically much closer to farmer's practice and trial results more closely linked to effects potentially observed under practical farming compared to other emission studies.
Ammonia emission measurements had limitations. In between experimental campaigns, generally, transfer factors may change due to effects of environmental conditions on NH3 uptake by the samplers. It therefore has to be determined for each campaign as given in the original study [25]. However, with respect to the derivation of the transfer factor, replicate factors obtained from single plots were not always consistent within an experimental campaign. This can be explained by the uncertainty and variability of fertilizer application at the small scale (<0.1 m 2 ) for DTM dynamic chamber method and within the larger areas used for passive sampling (81 m 2 ). In some cases, the small sampling area was eventually not representative for the whole plot. Therefore, replicate plots were used to determine average transfer factors. Nevertheless, this variation is a source of uncertainty and the number of replicate measurements for derivation of the transfer coefficient was limited. It requires further investigation to which number of replicate microscale measurements are needed to obtain a robust transfer factor.
Overall levels of cumulative ammonia emissions from cattle slurry were within the generally observed range [7]. The measurement approach has been quantitatively validated compared to micrometeorological methods in earlier studies [26][27][28]. Nevertheless, being a non-standard measurement approach, observed cumulative ammonia emissions from trail hose applied CS of the four emission trials were cross checked with results calculated with the ALFAM2 model [33]. In three of the four trials, measured emissions were close to emissions calculated with the model. However, emissions in the first winter wheat trials measurements deviated strongly from model calculations. These high values were due to high ammonia concentrations in the measurement system and not due to the calibration approach for post-processing for ammonia loss raw data. Nevertheless, emission
NH 3 Emissions
The study compared the efficacy of different technological measures to reduce ammonia emissions from field application of several slurry types. The application systems used could all be used with the same operational quality because the sandy soils allowed easy handling of the systems. In contrast to many other slurry acidification trials, a commercial field acidification system was used. Thus, trial performance was technically much closer to farmer's practice and trial results more closely linked to effects potentially observed under practical farming compared to other emission studies.
Ammonia emission measurements had limitations. In between experimental campaigns, generally, transfer factors may change due to effects of environmental conditions on NH 3 uptake by the samplers. It therefore has to be determined for each campaign as given in the original study [25]. However, with respect to the derivation of the transfer factor, replicate factors obtained from single plots were not always consistent within an experimental campaign. This can be explained by the uncertainty and variability of fertilizer application at the small scale (<0.1 m 2 ) for DTM dynamic chamber method and within the larger areas used for passive sampling (81 m 2 ). In some cases, the small sampling area was eventually not representative for the whole plot. Therefore, replicate plots were used to determine average transfer factors. Nevertheless, this variation is a source of uncertainty and the number of replicate measurements for derivation of the transfer coefficient was limited. It requires further investigation to which number of replicate microscale measurements are needed to obtain a robust transfer factor.
Overall levels of cumulative ammonia emissions from cattle slurry were within the generally observed range [7]. The measurement approach has been quantitatively validated compared to micrometeorological methods in earlier studies [26][27][28]. Nevertheless, being a non-standard measurement approach, observed cumulative ammonia emissions from trail hose applied CS of the four emission trials were cross checked with results calculated with the ALFAM2 model [33]. In three of the four trials, measured emissions were close to emissions calculated with the model. However, emissions in the first winter wheat trials measurements deviated strongly from model calculations. These high values were due to high ammonia concentrations in the measurement system and not due to the calibration approach for post-processing for ammonia loss raw data. Nevertheless, emission data are indirectly in agreement with observed yield level differences between the first and the second wheat trials, with higher yield levels in the later application characterized by lower ammonia emissions. ALFAM2 model calculations can also deviate strongly from emission data measured with standard, i.e., micro-meteorological methods [33].
In the barley trial, cumulative values of the NH 3 emissions (Figure 2) of incorporated cattle slurry were significantly higher than the emissions of the same treatment with acidified slurry and closed slot injection. This was probably due to the typical 2 h delay of incorporation after trail hose application. Emissions would have been on the same level, if the slurry was incorporated immediately after application. Following Sommer et al. [10], NH 3 emissions would be efficiently decreased by 80% with incorporation directly after surface application.
Injectors significantly lower threat of ammonia loss, with reduction efficiencies of 49-97% compared with 41-48% for band spreading, both relative to surface application [34]. This was also confirmed in our study with simultaneous measurements. Closed slot injectors have drawbacks, the working width is 2-8 m, and the injection is much more energy demanding. For growing crops, the damage from the wheels is higher than when using trailing hoses, and the cutting of roots by the open-slot injection discs can also cause crop damage. Therefore, deep injection is never, and open-slot injection is hardly ever, used in winter cereals. For bare soil, closed-slot injection is often applied while open-slot injection in typical for grassland applications [10,11]. The results showed that emissions from acidified incorporated slurry and closed slot injection were low and not significantly different ( Figure 2). However, the cost of acidification and incorporation can be much cheaper for the farmer, than deep injection. Therefore, acidification could play an essential role in NH 3 abatement when slurry is applied to bare soil. When surface application is performed in growing cereal crops, open slot injection is costly, due to reasons as earlier described. Field acidification with trail hoses, can be one of the technological alternatives to reduce NH 3 loss. Although, acidification increases costs compared to simple trail hose application, due to the requirement for additional equipment and specialized staff handling concentrated acid [10,16]. Conversely, due to cost-effective sulphur (S) fertilization, ease of application, and possible positive yield effects, acidification can be a practical and cost-efficient alternative to injection. Moreover, the reduction effect can be increased by subsequent incorporation, as demonstrated in our study.
The NH 3 emissions after trail hose application, incorporation, shallow closed slot injection and single point field acidification varied. Application of slurry with band spreading on the soil beneath a crop canopy can decrease NH 3 volatilisation by~50% compared to surface broadcast application, the efficiency of this technique increases with greater leaf area and height of crop [10,35]. Soil water content, solar radiation, crop height and leaf area significantly influence the potential reduction efficiency of the trail hose technique, with the most significant effect at low soil water content, high solar radiation and great leaf area. [10]. Nevertheless, trail hose application in the second trial ( Figure 2), with higher spring barley canopy and a loss of 14% ammonium N applied, was higher compared to trail hose application in the first trial (12%). The soil water content, due to some rain, appears to have affected the results of the first trial of the barley field. As mentioned, rain (1 mm) was observed at the beginning of the first trial. NH 3 emissions are at their highest directly after application. Thus, a potential canopy effect was masked by other environmental factors in this trial. For future tests of canopy effects on emissions, doing measurements in manipulated canopies might present better insights.
In general, in both winter wheat trials acidification of slurries showed similar reduction effects on NH 3 emissions. However, only small or no reduction effect were observed for PS. Furthermore, acidifying dairy cattle slurry in the barley trial and the early and late winter wheat trials showed a similar reduction effect of 61%, 67% and 74% reduction of NH 3 emission, respectively.
Emissions of CS and AD were significantly higher compared to those from other slurries and acidification resulted in significant reduction of losses for both slurries. MS, PS and AS showed no significant differences between each other. This is probably due the low DM concentration compared to the former slurries which were on a similar level. Higher TAN concentrations may also have played a role (Table 2), as lower volumes of slurry had to be applied and the fraction of infiltrated slurry is higher when the same amount of ammonium N is applied with a smaller volume of slurry. While acidification reduced emissions by about 50% for AS and MS, the effect was almost negligible for PS.
It had to be expected that acidified pig slurry showed stronger reduction effects of about 67% of NH 3 emission at a pH of 5.5 [14]. However, in the cited study, on-farm acidification systems were tested. Differences between acidified and unacidified treatments were smallest in PS and emissions were low compared to CS and AD. PS was characterized by the lowest initial pH, low DM concentration and lowest acid demand to reach target pH. Fast infiltration of both acidified and unacidified PS may have dominated the emission process compared to acidification. However, DM concentrations were even low in MS and AS connected with high acidification efficiencies. Hypothetically, the small acid demand entailing eventual fast pH buffer reactions in PS after application may have influenced the effectiveness of acidification. This is supported by the close relationship between acid dosage and reduction effects for the non-digestate slurries. Although, generally, single point acidification seemed to have worked well in four of the five tested slurries, this result may hint to limitations of this acidification approach. On this background, our first hypothesis on the consistent effectiveness of commercial systems across slurry types has to be rejected. More detailed investigation of pH buffer reactions of different slurries may shed more light on this open question. In this context, the high acid demand for pH adjustment for digestate slurries may pose further limitations for the acidification approach due to the high risk of sulphur oversupply.
Regarding sulphur fertilization, crops on to which animal manure is applied often show a lack of S supply because of low concentrations of readily plant-available S. Sulphate in slurry, when stored, is potentially reduced during storage and lost as hydrogen sulphide (H 2 S). This loss could be reduced by farm acidification [36], and most of the slurry would be still plant available at the time of application [37]. Nevertheless, high demand of sulphuric acid addition, e.g., for anaerobic digestate slurries in this study, may entail the risk of sulphur overfertilization [15] and subsequent sulphate leaching losses. Thus, slurry acidification by sulphuric acid cannot be considered a general solution for reducing ammonia emissions from field applied slurries-keeping sulphur fertilization balances in mind. While injection and taking advantage of cold application conditions in early spring could be a viable mitigation option for small canopies, slurry acidification could be recommended for slurry application later in the vegetation period and in taller canopies.
For all mitigation measures for specific trace gases, there exists the risk that emissions of other trace gases may be concomitantly increased ("emission swapping"). For example, special NH 3 mitigation measures during storage of manure can increase N 2 O emissions [38,39]. However, for single point acidification no general negative effect on N 2 O [40] and CH 4 emissions were observed [41] in contrast to higher N 2 O emissions found in many cases for slurry injection [40].
However, as part of the risk of excess S fertilization, slurry acidification can mobilize other nutrients and ions which could also have detrimental effects. The beneficial effect of acidification on crop P nutrition is well known [42], but this could potentially also mobilize P in water leaving the root zone, or nickel and zinc, which are used as feed additives transferred to the slurries. These potentially negative side effects of slurry acidification need more attention in research.
The fourth hypothesis is supported by the trial results, as combined mitigation measures resulted in improved NH 3 loss abatement in the barley trial and emission reduction in low DM slurries MS and AS in winter wheat. However, considering the PS treatment, the low NH 3 emission level of untreated slurry (probably due to low DM) was not further decreased by acidification. The cause for this was probably rooted in unsustained pH decrease, i.e., inappropriate acidification treatment by the used application system.
Acid Requirements
In contrast to on-farm acidification, single point slurry acidification lowers the pH to a target pH value with subsequent pH increase by buffer processes within the slurry [16]. This may entail the risk of an insufficient acid dosage when pH reaction and pH buffer systems are fast as occurred in pig slurry in this trial. Soil texture influence on the result was not covered by this study as all trials were performed on similar soils in the same agro-region. Buffering capacities of slurries are variable, and a variable amount of acid was needed to reduce pH by a certain level (Table 2 and Figure 5), in order to reach the target pH 6 value. The results show that the target 6 pH value was achieved only for MS, while other acidified slurries differed from the target value. A further detailed analysis of slurry properties, with their buffer potential, may give further explanations for the variable acid requirements. DM concentration ( Table 2) and slurry processing by biogas production may play a major role. For future trials, it would be advantageous to know more precisely how to adjust the pH value for a particular slurry type, to assure that the acidification system is operating correctly. Therefore, the pH treatment of commercial acidification system needs more attention with respect to in how far this approach is robust enough to guarantee a specific pH level of slurries after leaving the system to the field surface.
The second hypothesis is supported by the results, as the different slurries were characterized by different acid requirements for pH decrease. However, a specific single point pH value at application did not guarantee a specific ammonia emission reduction, as was demonstrated by the pig slurry acidification results in this study. The closest relationship between emission reduction and acidification treatment was to the amount of acid added. Thus, for single point acidification amount of acid addition seems to be eventually more appropriate control measure than target pH value of acidified slurry.
Yield Variables
Emission reduction did not translate in higher grain yields but into significantly higher values for most of the four other tested yield variables. This can be partly explained by the high fertilization level of the trials compared to the realized yields. However, in the treatments with the strongest quantitative reduction of emissions (expressed as kg N per ha emission reduction), CS and AD in the winter wheat and injected CS in the summer barley trial, the increase in yield variables was more pronounced than for the other tested slurries. This may hint to a direct relationship between ammonia emission reduction and increased N uptake by the crop which was also observed for wheat and synthetic fertilizers [19]. Contrastingly, a stronger effect was also observed in PS. In addition to higher N availability after acidification, which did not exist in PS treatment, higher S and P availability [42] can promote crop growth and thereby indirectly cop N uptake. Across all trials, acidification had the most robust and pronounced effects of all application techniques. The specific effect of acidification on yield and N uptake can hardly be generalized as it depends on crop type, fertilization level and soil nutrient supply. Mixed effects were also observed in practical trials around the Baltic Acidification Project [43], but higher winter wheat yields after acidification were particularly observed in Northern Germany close to the sites of this study. Generally, clear NUE effects were observed in Danish trials [18]. The third hypothesis can thus only partly be confirmed, as yield was mainly unaffected by ammonia mitigation measures for single treatments. Nevertheless, a generally positive main effect by acidification on grain yield was confirmed for summer barley and was also found in earlier studies [18].
Conclusions
The experimental approach used in this work (small replicated plots with a large number of experimental treatments) provided a means for simultaneous comparison of ammonia emissions depending on multiple slurry application technologies under identical conditions. Such a broad approach of simultaneous comparison of application systems and slurry types was performed for the first time in this study. In general, results confirmed that in-field slurry acidification, slurry injection, and rotary incorporation all significantly reduced NH 3 emissions from the field-applied slurry. Furthermore, incorporation plus acidification showed nearly the same reduction in emission as closed slot injection, supporting the hypothesis that a combination of mitigation measures can further reduce NH 3 emission. Acidification may be a cost-effective approach for reducing NH 3 emission and an alternative to injection depending on slurry type. The results hint to limitations of commercial single point acidification techniques with slurry pH as management variable. Alternatively, baseline acid addition levels seem to be needed to obtain robust emission reduction. Further trials may give further insight into the acid requirements for a significant reduction of NH 3 emissions combined, taking into consideration reasonable sulphur fertilisation levels. Results give clear evidence that particular consideration has to be taken concerning acid requirements of different slurry types. From a fertiliser management perspective, it is necessary to use the appropriate amount of organic fertiliser at the right time, to minimise emissions and to be sufficient for crop growth. As in other studies, the yield effect was more pronounced with respect to N uptake and NUE expressed as ANRE. There still exists a gap of published data on yield and NUE effects by slurry acidification in field studies, which call for further investigations.
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Domain: Agricultural And Food Sciences
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Effects of Cleaning Procedures on the Concentration of Pesticide Residues on Crisp Fresh-Cut Lettuce (cv. Vera)
: Decontamination procedures are a need when talking about ready-to-eat foods, especially vegetables. In this work particularly, we are focusing on the effects of four cleaning solutions and ultrasound baths on the amount of pesticide residues left on lettuces. Five pesticides were applied to lettuces grown in controlled conditions. The residues were analyzed with an acetate QuEChERS method and a HPLC-MS/MS system. All tested methods shown diminution of residues without significant differences among each other. Out of 16 pesticides analyzed in commercial samples, only five were found on seven of them, without exceeding MRLs.
Introduction
Consumption of fresh fruits and vegetables are part of a healthy lifestyle as they are a source of vitamins, fibers and many nutrients. Food safety is a major issue when talking about fresh produce as many are eaten raw to maintain more of their benefits, but this may lead to foodborne illnesses if not washed properly [1]. Regarding raw vegetables, ready-to-eat foods have increased in popularity as they present an easier way to get already washed and cut produce.
To prepare vegetables for consumption several parameters need to be taken into consideration, this work will focus on pesticide residues, which, for Uruguay, the maximum residue limits (MRL) are set by the Codex Alimentarius [2]. During production, farmers use pesticides to avoid plagues, to improve production and to prevent diseases that could affect their crop [3]. When applied using good agricultural practices, pesticides should leave residues beneath the established MRLs, furthermore, these residues can be lowered by different cleaning procedures.
Ultrasound baths are an environmentally friendly decontamination method used widely to reduce microorganisms and residues in different industries [4]. Cavitation bubbles formed by the ultrasonic waves can detach residues from surfaces and when they burst, they have the ability to break molecules [5]. This last capacity has proven to be effective to affect pesticides [6], therefore the intention is to study whether or not the different frequencies applied and different lengths of application have different effects on the residues, without damaging the leaves as to preserve the fresh look of the lettuces.
Comparing and contrasting some of the methods used in the industries nowadays in vegetables is the main objective of this paper.
Materials and Equipment
Work mixes were prepared from pesticide stock solutions that had been made by dissolving high purity standards in the appropriate solvent and were kept at −40°. HPLC grade acetonitrile (MeCN) and methanol (MeOH) as well as deionized water from a Mil-liQ system were used. Sodium acetate (NaOAc), ammonium formate, formic acid 88%, sodium chloride (NaCl) and glacial acetic acid (HAc) were also employed during this work.
The analysis was performed in an Agilent 1200 series HPLC system, coupled to a 4000 QTRAP ® mass spectrometer system from Applied Biosystems SCIEX™. The column employed was a ZORBAX Eclipse XDB-RP-C18 (150 mm × 4.6 mm, 5 µ m) from Agilent. The spectrometer was working in Multi Reaction Monitoring (MRM) mode with nitrogen as a collision gas. Mobile phase solutions were A: deionized water with 2% MeOH, 0.1 % formic acid and 5 mM ammonium formate and B: MeOH with 2% deionized water, 0.1% formic acid and 5 mM ammonium formate. The gradient started with 30% of mobile phase B for a minute, then increased to 100% after 11 min, it was kept constant for two minutes and then reduced back to 30% in two minutes. It remained there until the 21 min of runtime were up. A flow of 0.6 mL/min was kept throughout the analysis. The software employed was the Analyst Software (version 1.8).
Lettuce Acquirenment
This study was performed using two groups of lettuces. On one hand, commercial lettuces were purchased from local points. One the other hand, lettuces were grown in a greenhouse in controlled conditions and obtained at ripe stage. Both groups were analyzed for pesticide residues with their own blanks associated.
Commercial Samples and Processing
All in all, 22 lettuces were bought from different local producers and shops in a two months period. Three of those lettuces were obtained from an organic producer, which were used as blank samples for the validation procedure and for calibration curves.
Each head of lettuce was cut into stripes and milled with liquid nitrogen to a fine dust as soon as it got to the laboratory, and was kept frozen until analysis.
Lettuce Production and Pre-Harvest Treatments
In order to obtain lettuces with similar levels of pesticides, an experiment in controlled conditions was carried out. Crisp lettuce (Lactuca sativa, cv Vera) was grown in a greenhouse with daily watering in Estación Experimental Dr. M. A. Cassinoni, near Paysandú, Uruguay. A total of 70 lettuces were cultivated following Good Agricultural Practices during September and October 2020.
From the pesticide pool available for use on lettuce in Uruguay, acetamiprid, boscalid, carbendazim, chlorpyrifos ethyl and methyl, cyromazine, dimethoate, fluvalinate, imidacloprid, iprodione, methomyl, pyraclostrobin, pyrimethanil, pirimicarb, propamocarb and spynosad were chosen for this study after consulting with lettuce producers from the north-west region. Five of these products were chosen to be used during the controlled conditions experiment, the selected pesticides, chlorpyrifos ethyl, pirimicarb, imidacloprid, boscalid and pyraclostrobin. The application was performed following each label recommendations, using a hand spray applicator.
Lettuce Harvest and Post-Harvest Processing
Lettuce heads were harvested at ripe stage at four to six-week-old and immediately processed. Applied (A) and non-applied (NA) heads were shredded manually with a stainless-steel knife to obtain homogenous batches.
NA-samples were processed with liquid nitrogen and kept frozen until analysis. Additionally, an A-sample was taken to generate positive controls, while the rest of the batch was used for different decontamination procedures.
Chemical Treatments
Three disinfectant solutions were tested simulating domestic conditions, 100 ppm of sodium hypochlorite, 80 ppm of peracetic acid and 40,000 ppm acetic acid (4%), together with tap water. For this purpose, six liters of each solution were placed in ten-liter tubs with leaves of the equivalent of half a lettuce from the A-samples. They were kept submerged for ten minutes and stirred mid-way. Once the time was up, the excess liquid was removed with a domestic salad spinner, each sample was milled into a fine dust with liquid nitrogen and kept frozen until analysis.
Ultrasound Treatments
Two stainless steel ultrasound units (Elma, Germany) Transsonic TI-H (25 kHz, 45 kHz) and Elmasonic P (37 kHz, 80 kHz) with operating powers of 100-120 W were used. Ultrasound power dissipation (P) was determined calorimetrically, recording temperature of the bath throughout the different procedures.
For each of the four frequencies, 70 g of chopped lettuce and three liters of cold distilled water were placed in the ultrasound baths to be treated for two time periods, ten or fifteen minutes. Each combination was tested twice.
After the application of treatments, excess of water was eliminated using a domestic salad spinner, then, each sample was milled into a fine dust with liquid nitrogen and kept frozen until analysis.
Development and Validation of Extraction Method
After testing the three traditional QuEChERS methods (original, acetate and citrate), the acetate version without clean-up was validated according to the SANTE guidelines [7] for the 16 pesticides selected. It begun with 5 g of lettuce in 50 mL Falcon tubes in which 10 mL of 1% HAc in MeCN were added. The mixture was shaken manually for a minute and then 4 g of MgSO4 and 1 g of AcONa were added, after three minutes of manual shaking, the tube was centrifuged for 5 min at 3500 rpm. The extract was filtered through a 0.45 µ m pore syringe filter into 2 mL glass vials for HPLC-MS/MS analysis.
Method Validation
The acetate buffered QuEChERS method without clean-up was chosen for this analysis after testing its performance against the original and citrate buffered methods [8][9][10], and then against itself with a clean-up procedure. Once testing was done, SANTE guidelines were followed in order to validate the selected methodology [7]. Three levels of concentration with five replicates each were put to the test, achieving limits of quantitation of 10 μg/kg for 12 pesticides, 25 μg/kg for carbendazim, chlorpyrifos methyl and pyraclostrobin, and 50 μg/kg for iprodione. This implies recoveries between 70-120% and standard deviations below 20%. The matrix effect was below 20% for all pesticides except for carbendazim, therefore there's the advantage that this method can be used without a matrix-matched calibration curve. Details of the validation parameters are shown in Table 1.
Commercial Lettuce Samples
Once the method was validated, it was challenged through the analysis of 22 commercial samples. Only seven of those lettuces showed pesticides residues at quantifiable levels for five pesticides (acetamiprid, boscalid, iprodione, propamocarb and pyraclostrobin). These results are presented in Table 2 together with the maximum residue levels (MRL) from the Codex Alimentarius [2] and the European Union [11]. As it stands, all the samples were below the stablished regulation for Uruguay but iprodione failed EU [11] standards.
Decontamination Procedures
Regarding the cleaning solutions used, all four showed a reduction in concentration of the applied pesticides when comparing with the positive control. Chlorpyrifos proved to be the most resilient with reductions as little as 5% while pyraclostrobin was the easiest to remove with a maximum decrease of 90%. Still, no significant difference was found between the selected solutions according to the ANAVA test Pillai Bartlett with alfa 0.05.
Ultrasound baths on their part also demonstrated to be an effective method of pesticide residue reduction. Each combination time-frequency managed to lower the selected pesticides where, again, chlorpyrifos was a though contestant with an average diminution of just 20%. On the other hand, pyraclostrobin had an average of 58%, with a maximum of 70%. Once more, despite the differences among pesticides, the combinations did not showed differences when analyzed with the ANAVA test Pillai Bartlett with alfa 0.05.
All in all, though vastly different in mode of action and cost, both the ultrasound and the cleaning solutions managed to achieve what was expected and, amazingly, there was no significant differences among the 12 methodologies when using the ANAVA test Pillai Bartlett with alfa 0.05 as the p/value was 0.28. All results are on Figure 1.
Conclusions
All in all, a fit for purpose methodology based on the QuEChERS approach, for the determination of pesticides residues in lettuce was developed and validated for 16 compounds. Said method had its applicability tested in the analysis of 22 commercial samples, where seven showed pesticide residues, below the corresponding MRL.
Both the ultrasound and the cleaning solutions managed to reduce pesticide residues without significant differences among each other. Chlorpyrifos proved to be the most resilient while pyraclostrobin was the easiest to remove.
Author Contributions:
Funding: This research was funded by CSIC through the PAIE program.
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Domain: Agricultural And Food Sciences
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Aphid-infested beans divert ant attendance from the rosy apple aphid in apple-bean intercropping
Ecological intensification of cropping systems aims at restoring multi-functionality while supporting current productivity levels. Intercropping is a form of ecological intensification involving ecological processes beneficial to farmers that do not take place in monocultures. Thus, it represents a practical approach to decrease the use of synthetic inputs such as insecticides in cultivated systems. Whereas insecticide reduction via intercropping-facilitated suppression of aphids is reported in literature, the majority of published studies focussed on herbaceous crops. Thus, the effect of intercropping on aphid populations of cultivated trees remains largely unaddressed. In this study we hypothesized that intercropping a specific companion plant within perennial crops would divert ant attendance from an aphid attacking the crop to another aphid feeding on the newly introduced plant, reducing aphid damage on the crop. We tested our hypothesis in the system of apple (Malus domestica Borkhausen), the rosy apple aphid (Dysaphis plantaginea Passerini) and the black garden ant (Lasius niger L.). Bean plants (Vicia faba) with the black bean aphid (Aphis fabae Scopoli) were intercropped within apple trees inoculated with D. plantaginea. We measured ant attendance, aphid development and survival as well as honeydew composition on both plant species through semi-field and field experiments. The majority of ants chose to attend A. fabae over D. plantaginea in the semi-field experiment with potted plants. In the orchard, a larger majority of scouts were scored on A. fabae over D. plantaginea. A higher number of D. plantaginea colonies remained active in the apple control, whilst they were almost eradicated by intercropping. Although chemical analyses of honeydew disclosed differences in the carbohydrate and amino acid profiles between aphid species, the difference in honeydew composition did not explain the preference for A. fabae. Ants did not discriminate between the two honeydew mimics both in laboratory and field bioassays. Our results showed the potential of intercropping apple trees with beans as a method to reduce ant attendance and thus colony survival. We propose that intercropping represents a bottom-up approach towards ecological intensification of perennial crops. Together with other ecosystem-based measures such as habitat management, intercropping should be considered when planning ecosystem redesign to increase biological control of pests.
www.nature.com/scientificreports www.nature.com/scientificreports/ resources, deterrence of pests and pathogens, and attraction of beneficial organisms 8 . For example, intercropping cereals with grain legumes promotes yield stability while it substantially reduces weed infestation and increases protein yield per hectare. In addition, an improved use of abiotic resources according to species complementarities for light interception and use of both soil mineral nitrogen and atmospheric nitrogen is documented 9,10 . Intercropping is also proposed as an approach to decrease pest damage through mechanisms like a reduced host finding, trap crop effects, the presence of deterrent plants, and the increased recruitment and survival of generalist natural enemies 11 . In this regard, there is very limited information on intercropping-mediated disruptions of mutualistic relationships of pests (i.e. ant-Hemiptera mutualism), resulting on a negative situation for the herbivores, and a potential pest damage reduction.
The use of companion plants in intercropped systems to reduce pest infestation was recently reviewed by Ben-Issa et al. 12 who pointed out that in order to achieve long-term results, companion plant strategies need to be combined with other approaches against sucking pests such as aphids. However, intercropping alone reduced also aphid infestation in cotton, wheat and other crops [13][14][15] .
Although intercropping-mediated suppression of aphids is reported in literature, the majority of these studies focussed on herbaceous crops. Thus, the effect of intercropping on aphid populations of cultivated fruit trees remains largely unaddressed. A higher degree of trophic complexity, due to both longer longevity of the main crop and co-occurrence of non-crop species in the alleys in comparison with annual crops, may explain the lower number of studies in perennial systems. Among interactions, interspecific relations between ants and tree infesting aphids are often of mutualistic nature 16 . Plasticity in behaviour is found in some ant species, with plant chemical defence indirectly mediating aphid performance via interactions with tending ants 17 . Whereas ants harvest honeydew from the aphid colony as a source of carbohydrates and amino acids, aphids are protected by ants from consumption by natural enemies. The suppression of aphid populations via intercropping should thus not only consider effects such as dilution and spatial diversification of the crop, trap crop or attraction of antagonists, but also other effects such as ant diversion from the target aphid by dedicated intercropped plants. Mechanisms behind diversion include preferential attraction of ants towards the honeydew of an aphid pest, which attacks the specific intercropped plant. Such a behavioural preference may be driven by chemistry, with compounds such as trisaccharide sugars or amino acids triggering a higher attraction to the honeydew of the intercropped plant in comparison with that of the main crop. However, factors such as the size of aphid colonies and the related amount of produced honeydew as well as plant architecture and the distance of the aphid colony from the ant nest may also play a role.
In perennial cultivated systems such as apple orchards, several species of aphids inflict serious injury, requiring specific interventions with systemic aphicides like neonicotinoids. Although pesticides could be replaced by native natural enemies to keep aphid population at bay 18 , attendance by ants has been shown to push efficient predators away from aphid colonies 19 .
In this study, we hypothesized that introducing a specific plant within a tree crop would divert ant attendance from an aphid attacking the tree main crop to another aphid feeding on the newly added plant, contributing to an aphid reduction in the crop. We tested our hypothesis in the perennial system of apple (Malus domestica Borkhusen), where the rosy apple aphid Dysaphis plantaginea Passerini is a major pest 20 . Bean plants (Vicia faba L.) were inoculated with the black bean aphid (Aphis fabae Scopoli) and intercropped within apple trees inoculated with D. plantaginea. Bean and black bean aphid were chosen because of their phenological co-occurrence in the field with rosy apple aphid in this region. Apple as a sole crop was used as untreated control.
Methods
In order to assess the effect of intercropping on ant-aphid interactions we carried out a series of sequential complementary experiments. Firstly, we tested in a semi-field setup whether A. fabae on bean could outcompete D. plantaginea on apple for ant attendance (Choice experiment in semi-field condition). Following this experiment, a field trial was carried out to corroborate our semi-field observations in the field and determine if there was an increased biological control of D. plantaginea (Field experiment). Additionally, we tested if the differences in attraction observed in the semi-and field experiments could be explained through differences in honeydew chemical composition, collecting and analysing the honeydew from both aphids (Chemical analyses), and testing the choice of ants to honeydew mimics (Laboratory and field choice test with honeydew mimic).
Choice experiment in semi-field condition. Single faba beans cv. Gloria were sown into 2 l plastic containers filled with a vegetable substrate (Hasselfors Garden organic-certified, Sweden). A. fabae colonies originated from their winter host Euonymus europaeus L.. The migration of A. fabae from its winter host coincides with apple bloom and approximately the time when D. plantaginea colonies begin to develop in Sweden. Branches from three different plants of E. europaeus with A. fabae individuals were brought into contact with five-week-old V. faba plants to obtain new colonies. A. fabae colonized the bean plants after two weeks. Following the removal of any predator from the bean plants, a single A. fabae female was transferred to the top of newly potted beans to create an aphid colony per plant on a total of 30 plants. The main stem of each plant including the newly established colony was covered with a perforated plastic bag as a protection measure against predators. Plants were placed in a net-house to prevent aphid predation and used in behavioural experiments seven days after infestation.
Forty two-year-old potted apple trees (cv. Aroma) were purchased from Stångby Plantskola (AB, Lund, Sweden) in the spring of 2014 and maintained in 15 l pots. Trees were fertilized and pruned once a year. Pests were controlled by removing the insects manually after visual inspection. No disease control was required. Whereas a first batch of 20 trees was kept in a net-house (to avoid ant nesting), a second batch of 50 trees was placed in different apple orchards within the Skåne region to allow L. niger to nest inside the pot at the base of the trees. Worker www.nature.com/scientificreports www.nature.com/scientificreports/ ants were collected from each nest and observed under stereomicroscope to ascertain that the nest belonged to the species L. niger.
Only the rooting system of trees exposed in the orchards was used in further experiments. After cutting off the tree canopy at 10 cm from the ground, the presence or absence of an active nest with a queen and eggs was verified by inspecting the soil of each pot in the spring 2015. The root system with the ant nest was then removed in a block from the pot and transferred to an ant-secured starving-cardboard box (57.6 × 34.6 × 40.7 cm). Ants were kept without food and water during 14 hours before each run of the experiment. The potted trees that were not exposed in orchards, and therefore had no ant nests, were treated with Loxiran Myr (natural Pyrethrin extract, Neudorf, Emmerthal, Germany) in order to avoid the presence of any undetected ants.
A single D. plantaginea apterous virginoparae adult was collected from a field colony (Alnarp, SLU) and inoculated on a shoot of a potted tree using a clipcage (see Porcel et al. 18 for details). Bean and apple plants were inoculated with the respective aphid on the same day. At day seven after inoculation, a V. faba plant with an established A. fabae colony was removed from its protective bag and planted into the same pot as the apple tree, avoiding a direct contact between the canopy of the apple tree and the bean. The clipcage around D. plantaginea was removed after planting the bean. Aphid colonies with similar size were selected on the paired plants. In order to prevent uncontrolled ant intrusion from outside, the pot with the two plants was placed inside a masonry bucket with water. At 8:00, ant nests were removed from the starving box and placed inside pots. This pot was then moved into a masonry bucket with water to avoid unwanted ant dispersal in the greenhouse. At 10:00 a.m., the two pots were connected with a wooden bridge, allowing the ants to freely access the pot hosting the two plants. The bridge was situated equidistantly between the apple tree and the bean plant (Fig. 1).
The number of D. plantaginea aphids on apple, A. fabae on bean, and ants tending colonies were counted six times in 2 h intervals from 10.00 a.m. to 8.00 p.m. Ants observed inside and around the aphid colonies were considered tending ants. Ten replicates were run simultaneously each day for three consecutive days using ten different L. niger nests. Each apple and bean plant was used once and each ant nest was used three times on different days. After each run of the experiment, nests were placed back into the starving boxes until the following day. Ants that had established aphid attendance were not returned to the nests. As a total of seven D. plantaginea colonies failed to establish in the first three days, a fourth run was carried out with the same seven sets of plants for a total of 30 replicates.
The number of ants attending D. plantaginea and A. fabae was analysed with a generalized mixed model (GLMM) with a log link and a Poisson error distribution using the R package "lmer4". Aphid species and the interaction between Aphid species and Time were included as fixed factors. The interaction was dropped from the final model based on AIC goodness of fit. Ant nest and Day of the experiment were added as random effects. The replicate was included as a random effect to account for the dependency structure derived from repeated counts on the same colony over time. The probability of ant presence in D. plantaginea colonies was analysed with a binomial GLMM with the same fixed and random effects. The significance of the fixed factors was tested with Wald tests for both models. Final models were checked for overdispersion and the assumptions were verified by representing graphically the residuals against the fitted values, the fixed factors and the random effects. All statistical analyses described herein were carried out with R v. 3.5.2. www.nature.com/scientificreports www.nature.com/scientificreports/ Field experiment. Four square plots (30 × 30 m) were established in an apple orchard in the Skåne region (Sweden). Plots included seven apple rows and were spaced a minimum of 25 m apart. The 12 th of June 2015, twenty-seven trees in the centre of each plot were artificially infested with a single apterous virginoparae of D. plantaginea using clipcages as described above. Experimental trees were inspected for naturally occurring D. plantaginea colonies (at an early stage of development at the time) that were removed if found to avoid interference with the established colonies. After seven days, the cages were removed. Five of these colonies per plot were covered by a mesh bag (30 × 70 cm, mesh of 300 μm, Megaview Science, Taichung, Taiwan) to exclude predators as a control treatment. At the same time, in two of the plots, 57 bean plants infested with A. fabae were planted underneath the trees with D. plantaginea colonies in a spatial arrangement in which each D. plantaginea colony was surrounded by three bean plants (Fig. 2). Beans were kept in the net-house and prepared following the same protocol as described previously. The number of aphids and ants associated to the established aphid colonies was recorded weekly per colony during a four-week period.
Because not all A. fabae survived the first week of exposure in the orchard, the uncolonized beans were used to evaluate whether ants preferred infested over uninfested bean plant. Preference was analysed using a GLM with a binomial distribution and a log link with Ants presence as response variable and A. fabae presence and Week as fixed factor. D. plantaginea and A. fabae colonies that did not establish in the first week were excluded from subsequent analyses. The number of ants around D. plantaginea colonies was analysed with a negative binomial GLM (after detecting overdispersion with a Poisson distribution) using Ant presence as response variable and Treatment and Week as fixed factors. D. plantaginea colony survival over time was analysed with a Cox proportional hazards regression model. Because the model tested the risk of colony predation over time, treatment was included as fixed factor and the event of colony suppression as response variable. The significance of the treatment was checked with a Wald test. The Cox model was carried out using the R package "survival". The number of D. plantaginea aphids per colony was analysed using a GLMM with a negative binomial distribution (due to overdispersion) and a log link. Treatment, Week, and their first level interaction were used as fixed factors and Plot as random effect. The colony ID was nested in Plot to account for repeated aphid counts on the same colony. Pairwise comparisons of treatments in each date were performed using Tukey's test with R package "emmeans". Models were validated graphically as described previously.
Chemical analyses. In June 2017, 10 apple trees and bean plants were artificially infested with D. plantaginea and A. fabae following the methodology described in the choice experiment in semi-field condition. Mesh bags were placed over the branches bearing D. plantaginea colonies to exclude natural enemies and ants. Aphid honeydew (1-5 μl; N = 6) was collected with microcapillary tubes from A. fabae and D. plantaginea active colonies by folding aluminium foil around the leaf hosting the colony for 6 hr. Collections were stored at −18 °C until analysis. The sugar analysis was performed via Ion Chromatography -Pulsed Amperometric Detection -Charged Aerosol Detection (IC-PAD-CAD), while the amino acid content was analysed via high precision liquid chromatography with fluorescence and diode-array detectors (HPLC-FLD-DAD). The detailed analytical protocol is presented in Appendix A. The honeydew composition of A. fabae and D. plantaginea was compared using a Willcoxon test. Because the amount of collected honeydew varied between samples, sugar and amino acids contents were normalised within each sample before the test. Compounds occurring only once were removed from the analysis. www.nature.com/scientificreports www.nature.com/scientificreports/ were purchased from Antdealer Antshop (Erfurt, Germany) and maintained in the laboratory. Ten colonies were tested twice in two consecutive weeks and 9 colonies were tested once. Colonies were kept in a climate chamber at 25 °C and 12:12 light:dark cycle and were starved for 48-50 hours before the experiment. They were kept in Petri dishes (Ø = 55 mm) with a moist charcoal-plaster bottom and a small hole in the lid to allow workers to move in and out from the nest. Each dish with a single colony was placed in a plastic box (15 × 15 × 15 cm) which served as the foraging arena. All tested stimuli were formulated at a concentration of 4% sugars and 13 nmol/ml amino acids and prepared shortly before the experiments. Twohundred µl of each solution were presented to the ants in an Eppendorf lid (Ø = 10 mm) randomly placed in a Petri dish (Ø = 55 mm) with a distance of 15 mm between solutions. The composition of honeydew mimics is reported in Table 1. The number of ants feeding from each solution was counted every ten minutes for 250 min. In addition, a cafeteria-setting experiment was conducted in the field. Seventeen ant nests were located by visual inspection in two apple orchards (and the area surrounding the orchards) situated in the Swedish University of Agricultural Sciences at Alnarp campus (Alnarp, Sweden). Nests were presented with 200 µl of each of the sugar solutions as previously described. Ants feeding from each solution were counted every five minutes for 300 min in orchard 1 (10 nests) and for 120 min in orchard 2 (7 nests). Ant count data from both experiments was pooled over time for analyses and submitted to two GLMs. The models used a negative binomial error distribution (due to overdispersion) and a log-link and included total cumulative ant sum as response variable and Treatment as factor. Multiple comparisons between treatments were conducted with Tukey's test and model validation was carried out visually as described previously.
Results
Choice experiment in semi-field condition. In the greenhouse, the number of ants attending A. fabae was higher than for D. plantaginea from 10:00 until 20:00, where 1.84 ± 0.39 (mean ± SE) ants were recorded attending A. fabae against 0.06 ± 0.05 associated to D. plantaginea (Fig. 3A and Table A1). Both aphid colonies recorded an increase in ant attendance over time ( Fig. 3A and Table A1). A rather stable number of ants were attending D. plantaginea while a considerably more pronounced increase was recorded for A. fabae (Fig. 3A). A similar trend was observed for the proportion of attended colonies (Fig. 3B), which increased over time with differences between species (Table A1). At the final check of the experiment, 60.0% of the A. fabae colonies and 6.6% of the D. plantaginea colonies were ant-attended. Field experiment. All observed ants were identified as L. niger and were almost exclusively found on the infested bean plants (Fig. 4). Out of the total 114 beans planted, A. fabae established successfully in 73 (64.0%). Ants visited a significantly higher proportion of infested bean plants (41.0 vs 14.6%, GLM, χ 2 = 112.8, P < 0.001, Table A1).
Forty-one and 39 D. plantaginea colonies out of 54 established adequately in the apple + bean and apple treatment, respectively. In plots without beans, 0.13 ± 0.05 (mean ± SE) ants per tree attended the D. plantaginea colonies. In the intercropping plots, very few ants attended D. plantaginea (0.01 ± 0.01) while a significantly higher number (Table A1) Most D. plantaginea colonies were predated during the first week of exposure. Only D. plantaginea colonies in the apple alone treatment survived to the end of the experiment, while no colonies in the apple + bean treatment survived past the third week (Fig. 5A). The number of D. plantaginea individuals in the established colonies decreased over time with no difference in aphid survival between treatments (Table A1, Fig. 5A,B). However, the number of aphids per colony initially established was lower in the apple + bean treatment as compared to apple alone in the last two dates of the experiment (Fig. 5B). www.nature.com/scientificreports www.nature.com/scientificreports/ Chemical analysis of aphid honeydew. The analysis of the honeydew disclosed differences between species (Fig. 6). The monosaccharide glucose was the dominating sugar of both species, followed by the monosaccharide fructose (Fig. 6A). Among trisaccharides, raffinose was detected exclusively in D. plantaginea's honeydew, and the honeydew-specific melezitose, although found in both species, showed a higher content in the D. plantaginea honeydew. Other sugars such as those coming from hemicellulose breakdown or conjugated in other molecules, i.e. the monosaccharides arabinose, galactose, mannose, rhamnose, xylose and the disaccharides turanose and trehalose were minor components of the honeydew of both species. The sugar alcohol sorbitol was found in significantly higher proportion in D. plantaginea (Fig. 6A). Myo-inositol was the only carbocyclic sugar detected in the honeydew of both aphids. www.nature.com/scientificreports www.nature.com/scientificreports/ Glutamate was the most common amino acid found in both species (Fig. 6B). Asparagine showed a higher content in the A. fabae in comparison to the D. plantaginea honeydew. The normalized content of ammonium was instead higher in the honeydew from D. plantaginea, although not significantly different (Table A1). The content of serine, aspartate, glutamate, threonine and valine tended to be higher but not significantly different in the bean aphid, while the opposite was measured for isoleucine (Fig. 6B). Lysine and histidine tended to be higher but not different for the rosy apple aphid. Alanine showed a low content in both species.
Laboratory and field choice test with honeydew mimic. L. niger did not discriminate between honeydew mimics of A. fabae and D. plantaginea in both the laboratory and field choice assays (Fig. 7). Sucrose was less preferred than any mimic, while water attracted only a few ants with very similar results in the laboratory and the field (Fig. 7).
Discussion
The possibility of exploiting differential ant attendance to generate new intercropping or selected plants combinations represents a practical opportunity to increase the resilience of cultivated systems. In this study we confirmed the initial prediction, i.e. that the supplement of a specific plant within a perennial cropping system would divert ant attendance from an aphid attacking the perennial crop to an aphid feeding on the newly introduced plant. The effect of intercropping on ant was initially measured in the greenhouse and subsequently confirmed in a full field www.nature.com/scientificreports www.nature.com/scientificreports/ setting. In a previous study, intercropping was associated with season-long reductions in ant activity in a pecan tree orchard 21 , although influence on a specific pest was not shown.
Previous studies showed a relationship between reduction of ant attendance, increase of antagonists in colonies, and drop in aphid populations in apple and other cropping systems. Nagy et al. 38 used different artificial feeders and sugars attaining a reduction of D. plantaginea by reducing L. niger attendance in all cases. They reported the highest ant diversion and aphid reduction for sucrose feeders attached to the tree trunk and argued www.nature.com/scientificreports www.nature.com/scientificreports/ that proximity to the ant nest, as opposed to feeders on the branches, may increase diversion. A similar effect was observed for the mutualism between Aphis spiraecola Patch and Lasius grandis Forel 39 . A solution comprising different sugars decreased attendance and aphid populations. However, an increase in antagonists was only noticeable when feeders were placed on branches. Our results, using a sentinel colony methodology, did not evidence a significantly higher biological control in terms of colony reduction over time. Nonetheless, colonies remained active in the control treatment the last two weeks of assessment whilst they were almost eradicated in the presence of bean plants (Fig. 5). The same active colonies grew larger over time under ant-attendance. A pronounced drop in colonies during the first two weeks in both treatments can probably explain the lack of differences observed. A high predator population, in particular of Anthocoris nemorum (L.), that peaks at this time of the year, could have outcompeted L. niger in the location of the small aphid colonies after clipcage removal. This could have partially prevented the establishment of mutualism in the control treatment in our field setting. Porcel et al. 18 showed the efficiency of this natural enemy to quickly locate D. plantaginea colonies that are not under ant-attendance protection. Additionally, it is possible that ants had already established trails to track naturally occurring colonies at the time of year the experiment was carried out. Such trails could have deterred the presence of antagonists in the apple + bean treatment diluting the treatment effect. Given the complexity at the field level, further research should evaluate the population of natural enemies, the effect of temperature and the possible influence of already established non-inoculated aphids on aphid-ant-natural enemies interaction.
Fischer et al. 22 showed that there is a competition for the mutualistic services of L. niger between the aphid A. fabae, Metopeurum fuscoviride Stroyan and Brachycaudus cardui (L.) utilizing the same plant Tanacetum vulgare. While M. fuscoviride was the most attended species, A. fabae was the least intensively attended. Authors argued that qualitative and quantitative differences in honeydew determine the aphid's selective attractiveness to ants, with the least competitive species being predated by L. niger. Although in our experiments with sentinel colonies we did not observe predation by ants neither upon A. fabae nor upon D. plantaginea (data not shown), the spatial www.nature.com/scientificreports www.nature.com/scientificreports/ isolation of the species may have played a role in moderating such competition. Probably, L. niger simply visited more intensively A. fabae to optimize the rate of honeydew harvest, made possible by a shorter distance from the nest compared to D. plantaginea 23 . As an alternative explanation, L. niger may prefer bean over apple due to the presence of extra floral nectaries.
Offenberg 24 observed an increased predation on A. fabae when artificial nectaries were offered to L. niger, whereas alternative prey had no significant effect. Consequently, a higher density of V. faba in the orchard or the addition of artificial nectaries may restore the balance. The shift of ants from extrafloral nectaries to aphid colonies seems to occur when the total reward from aphids will exceed that from extrafloral nectaries 25 .
The chemical analysis of the honeydew highlighted a rather specific profile for the two aphid species, with a higher content of the trisaccharides melezitose and raffinose but a lower presence of 1 out of 17 amino acids (asparagine) in D. plantaginea's honeydew. This result is in contrast with Woodring et al. 26 , who found that aphid species with the highest total amino acid concentration in the honeydew always had the highest concentration of sugars. It seems however, that the content of specific saccharides plays a major role in ant attraction. Woodring et al. 27 discussed that the sugar composition of the honeydew of the ant-attended M. fuscoviride indicated a rapid digestion of sucrose into glucose and fructose, and the simultaneous synthesis of considerable amounts of melezitose and some trehalose. Melezitose, a trisaccharide synthetized by aphids, has been reported to be used by ant scouts as a cue indicative of a long-lasting productive resource for collective exploitation and defence against competitors or aphid predators 28 . Trail mark laying was exclusively triggered by raffinose, sucrose and melezitose. A plant-specific honeydew production seems to be common in polyphagous species such as A. fabae, where the quality of the plant directly affects honeydew composition and indirectly ant attendance 30 . In our experiment, an increased preference for A. fabae could perhaps have been achieved by selecting plants with a higher release of melezitose, because A. fabae from E. europaeus produces a honeydew low in this compound 29,30 . However, A. fabae was more tended than D. plantaginea in both greenhouse and field experiments in spite of releasing less melezitose than D. plantaginea. The role of melezitose in the establishment of the mutualism is not entirely clear for A. fabae, because low-producing clones manage to attain high frequency of attendance 31 . Perhaps also the quality and the density of extrafloral nectaries on V. faba as well as the size of the colony and the related amount of produced honeydew need to be taken into account when evaluating the efficacy of ant diversion in apple-bean intercropping 32 .
It is nonetheless intriguing that in both our greenhouse and field experiments, A. fabae attracted a large majority of L. niger, disregarding the lower content of raffinose and sucrose and the complete absence of melezitose. The higher level of the sugar alcohol sorbitol in D. plantaginea's honeydew is somehow expected, as it is often found in the apple phloem. The carbocyclic sugar myo-inositol has not previously been retrieved from aphid honeydew and it seems to be related to glucose metabolism and cold tolerance in hemipterans 33,34 .
The amino acid composition is reported as a relevant factor in the establishment of ant-aphid mutualism 35 . Whilst amino acid analyses of A. fabae honeydew are available in the literature, no information could be found on D. plantaginea's honeydew profile. In our study we retrieved 6 major, 5 minor and 6 "in traces" amino acids. Two of the major ones, asparagine and isoleucine, differed substantially between the aphid species. Schillewaert et al. 29 reported arginine, asparagine and glycine as major amino acids in A. fabae, whereas isoleucine and 13 other amino acids were detected at an intermediate or lower content. Although the lack of information on the possible effect of specific amino acids such as asparagine and isoleucine on ant preference does not allow us to interpret further our result, it appears that ant preference falls under the category of context-dependent behaviours. Because L. niger did not discriminate between A. fabae and D. plantaginea honeydew mimics in our laboratory and field assays, we argue that the result observed in the intercropping experiment is mainly driven by other factors than honeydew contents. It is possible that a combination of factors such as honeydew profile, aphid colony growth and distance of the colony from the ant nest may affect the final outcome of the mutualism. In addition, plant architecture may shape the distance between colonies, which could in turn affect the foraging activity of ants 36 . Because of plant quality in deciduous trees may change with phenological development, the ant-aphid interaction observed in our study could be differentially shaped at a later stage in the season.
Recent studies showed that L. niger scouts were attracted not only to the complete plant system and honeydew, but also to the microorganisms in the absence of plant or honeydew; more specifically to a bacterium from A. fabae's honeydew. Staphylococcus xylosus emits a blend of volatiles that attract ant scouts 37 . In the present study we did not examine the possible effect of honeydew volatiles on ant attendance. However, it might be relevant to measure such attraction in order to shed additional light on the factors regulating the increased preference of L. niger towards A. fabae.
An aspect to consider is that the intensity of attendance reduction observed in Nagy et al. 38 and Wackers et al. 39 , by using artificial sucrose feeders, is comparable to what we report in this study (Fig. 4). This leads us to infer that, under certain circumstances, equivalent biological control increases may be obtained with the natural system that we present here.
In this study we demonstrated the potential of intercropping an aphid-bearing plant in orchards as a method to reduce ant attendance in aphid colonies in order to increase biological control. Future studies should clarify whether the same effect can be achieved by only sowing beans without inoculating the aphid. Additionally, alternative companion plants and aphids would be needed to increase diversity and provide a more robust system as aphid population can vary between years. We conclude that the concept of using a plant capable of diverting ant attendance from the main cultivated crops holds the potential to be included in conservation biological control of horticultural crops as a bottom-up approach to enhance the action of natural enemies. Together with other ecosystem-based measures, intercropping should be thus evaluated when planning ecosystem redesign to decrease the use of synthetic inputs such as pesticides.
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Domain: Agricultural And Food Sciences
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An intensive study plot to investigate chestnut tree reproduction
Pollination is a key step for fruit production. To provide a tool for future in-depth analysis of pollination in chestnut, we describe in detail a chestnut orchard (location, genotype, phenotype and seed-set of all trees). Chestnuts, which are insect-pollinated trees, have been massively planted around the world for nut production. Orchards are planted with clonal varieties selected from crosses between the European chestnuts (Castanea sativa) and Japanese chestnuts (C. crenata) or Chinese chestnuts (C. mollissima) because these two last species are tolerant to blight and ink diseases. To characterize chestnut genetic resources and accurately model male and female fitness as well as pollen exchanges in orchards, we characterized all chestnuts of the INRAE chestnut germplasm collection located near Bordeaux (France). All chestnut trees were geolocated and genotyped using 79 SNP and 98 SSR loci. We scored their flowering phenology using chestnut BBCH scale and precisely described their phenotype (height, diameter a breast height (DBH), canopy diameter…), their capacity to produce pollen (flower type, catkins length…) and their fruit production (number of burrs, seed-set…). We geolocated 275 trees and genotyped 273 of them. We identified 115 unique genotypes and assigned each genotype to species. To assess phenology, we evaluated 244 trees twice a week, for 6 weeks from early June to mid-July. We also described tree phenotypes with 11 variables, pollen production with 5 variables and fruit production with 3 variables. All measures were recorded in 2018 except seed set that was measured two consecutive years, in 2018 and 2019. The data collected is very detailed and allows modelling precisely pollen exchanges between trees. Parts of this data have been successfully published in scientific articles. Data are available at: [URL] Associated metadata are available at: [URL] INRAE chestnut germplasm collection is located in Villenave d'Ornon near Bordeaux (Gironde, France). This collection consists of two experimental plots called "A" and "E" composed of respectively 29 and 215 chestnut trees from three species: the European chestnut (Castanea sativa), the Japanese chestnut (Castanea crenata), and the Chinese chestnut (Castanea mollissima), as well as their hybrids. We characterized the chestnut trees from these study plots, other chestnut trees planted across the INRAE experimental station, and all remaining chestnut trees found within a radius of 1 km around the chestnut collection (Fig. 1). We genotyped all these trees with SNP markers, identified 113 genotypes ("Multilocus matches" function from GenAlEx, Peakall and Smouse 2012) and assigned them to chestnut species (STRU CTU RE analysis, Pritchard et al. 2000;Larue et al. 2021b). We further described the architecture, male catkins and fruit production of all trees in 2018, and repeated seed set measurements in 2019.
Identification and geolocation of chestnut trees
We identified 275 chestnuts and geolocated them with a Garmin 64st. Tree positions were verified and corrected using QGIS Software (Qgis Desktop 3.16.4) with satellite photos from IGN BdOrtho. Tree coordinates are expressed in Lambert 93. Each tree received a unique identifier according to its position and this ID is used as reference across all files. There is an introduction register of INRAE chestnut germplasm established since 1950, but for this paper, with some few exceptions for illustration purposes, no attempt was made to systematically use common names for the varieties.
Genotyping
Leaves were sampled from all identified trees and stored at − 20 °C until analysis. DNA isolation was performed with a CTAB custom protocol (Larue et al. 2021b). Samples were characterized using 120 Single Nucleotide Polymorphism markers (SNPs) using Agena MassARRAY Platform (Larue et al. 2021b). We identified all samples having the same multilocus genotype using "Multilocus Matches" function from Genalex 6.503 (Peakall and Smouse 2012) and carefully inspected the results manually. We also computed "Multilocus near matches" to verify that different genotypes differ at multiple markers.
When the unique multilocus genotypes were identified (the genets), we obtained the consensus genotypes by summarizing genotypic data from all ramets of each genet. Finally, we used STRU CTU RE software (Pritchard et al. 2000) to assign each ramet to species, as explained in Larue et al. (2021b).
Phenotyping
The architecture of each ramet was described using the diameter at breast height (at 1.3 m) for all stems > 1 cm, total height and canopy average diameter (in meter). We then calculated the basal surface area (in square meter). We measured the density of male flowers of unisexual catkins Fig. 1 Map of INRAE chestnut genetic collection and of all isolated chestnuts found within a radius of 1 km around the collection (number of flowers per square meter) to estimate the capacity of each ramet to produce pollen. We identified flower type ( Fig. 2) according to Solignat and Chapa (1975), measured catkins length (in centimeter) and diameter (in millimeter), and estimated relative stamen density. The phenology of all trees was recorded twice a week in late spring of 2018 (from June to mid-July) using a specifically developed standardized scale (Larue et al. 2021c). Briefly, at each visit, each tree receives three scores, one for male flowers of unisexual male catkins, one for female flowers and one for male flowers of bisexual catkins. We estimated burr production (burr number per square meter) in July by counting the number of burrs in the canopy or on the ground underneath each tree. Finally, we collected burrs in the fall and estimated seed set by counting the number of developed nuts per burr (female inflorescences of chestnut trees are composed of three female flowers located side by side). Each flower, if pollinated, produces a fruit surrounded by the pericarp; if pollination fails, the pericarp is still present but remains empty. If the three flowers of an inflorescence are not pollinated, the burr contains three empty nuts. This dataset is composed of 17 Excel files: 1 file describing all variables entitled "0_0_Read_Me.xlsx" and 16 data files, described below:
Access to the data and metadata description
We labeled and mapped all chestnut trees located inside and outside the INRAE plantations: -1_1_List_Chestnuts.xlsx contains a unique identifier for each chestnut tree. -1_2_List_INRAE_Chestnuts_Germplasm_Collection.
xlsx is a list of all chestnut trees that are part of the two plantations, making-up the INRAE germplasm collection (excluding isolated trees that were not planted as part of this germplasm collection).
We genotyped all these chestnut trees at SNP markers: -2_1_Genotypes.xlsx is the corresponding raw data.
-2_2_Genotypes_Genalex_Input.xlsx includes the SNP genotypes in Genalex format. We identified trees having the same multilocus genotype (clones):
-3_1_Clonal identification.xlsx
We compiled a list of all unique multilocus genotypes (the genets): -4_1_Consensus_genotypes_Genets.xlsx We then attributed a genet to each ramet (several ramets of the same genet are grafted on different rootstocks). -5_1_Genotypes_Ramets.xlsx Using a Bayesian approach (Structure), we assigned each genet to the different gene pools corresponding to different chestnut species.
-6_1_Species_Identification_Genets.xlsx We listed 275 chestnut trees: 244 adult trees in the INRAE germplasm collection (A plot = 29 trees/E plot = 215 trees), 24 small trees in the nursery, and 7 adult trees outside INRAE campus. All trees are geolocated, but all the young trees of the nursery are represented by a single GPS point. Of the 275 trees identified, two died before collecting leaves for DNA isolation, so we have the genotypes of 273 individuals. We identified 113 unique genotypes (genet), with an average of 2,4 ramets/genet. All this information is summarized in: -8_1_Summary. xlsx All chestnuts are located on a map: -8_2_Map. xlsx
Technical validation
We validated the dataset first by hand and then using numerical and graphical analyses with R software (R software v4.0.4). Laboratory and measure equipment were regularly calibrated, and standards were used for each analysis. Genotyping errors with SNPs using MassArray platform are extremely rare (Guichoux et al. 2011;Larue et al. 2021b), and it is therefore possible to quickly and reliably characterize a large number of samples at low cost. The genetic characterization of this collection is a first step for the creation of a database to describe chestnut cultivars. Users will be able to genotype their samples with the same markers (or a subset of them) and compare their results with the database.
Reuse potential and limits
The reuse of the data presented here is simple. The Excel files can be easily imported into R by saving them as.txt or.csv files with minor modifications. Parts of the data were used successfully in previous studies, demonstrating their usefulness and portability. For instance, we successfully performed Structure analyses (Pritchard et al. 2000) with 68 SNPs and 94 SSRs (Larue et al. 2021b), showing that the SNP markers are very reliable to identify clones, species and interspecific hybrids, including advanced hybrids.
The collected phenology data are also very detailed, allowing inter-varietal and interspecific comparisons, as performed in Larue et al. (2021c). In Larue et al. (2021a), we describe in detail the phenology of two ramets for each of eight genets. We show that whereas the phenology of the different genets can vary greatly, it is very repeatable among ramets of the same genet. Seed set measurements also provide valuable data that allow us to highlight differences in probability of fecundation according to the flower types. In particular, we have shown that astaminate trees have a higher see-set than staminate tree (results not shown).
A limitation of the present work is that we have not attempted to provide common names for all accessions studied. This would require a lot of curation, which is under way. Indeed, by genotyping the chestnut collection, we have highlighted problems of varietal identification. In some cases, a single genet has been designated with several cultivar names, a case of synonymy. In other cases, different genets have received the same cultivar name, a case of homonymy. At this point, trees are therefore named only according to their position in the plot.
In the literature, male catkins are classified in four categories according to the length of stamen filaments: astaminate (no stamens emerging from the flowers), brachystaminate (stamens 1-3 mm), mesostaminate (stamens 3-5 mm) and longistaminate (stamens > 5 mm), with pollen production of the tree strongly depending on flower type. However, variation of pollen production across trees is a continuous trait and these categories have limits.
Note also that when we calculated the seed set, we measured the number of fruits per burr, i.e. the number of flowers in each female inflorescence that give a fruit, but not burr set, i.e. the percentage of female inflorescences that give burrs. The probability of fecundity is therefore overestimated. To better estimate pollination success, it would be necessary to measure both burr set and seed set, which would be very labor-intensive.\===
Domain: Agricultural And Food Sciences. The above document has 4 sentences that end with '(Larue et al', 2 sentences that end with '(Pritchard et al', 2 sentences that end with 'in Larue et al'. It has approximately 1758 words, 99 sentences, and 25 paragraph(s).
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Characteristics of forest honey from several areas in Riau Province, Indonesia
Honey quality is influenced by several factors, including transportation conditions and length of storage. This study aimed to investigate the composition, characteristics, and quality of honey from several regions in Riau and Riau honey sent to Java Island. Honey samples were obtained from five districts in Riau Province, namely, Inderagiri Hulu, Kuantan Singingi, Pelalawan, Bengkalis, and Kampar Regencies. The honey parameters observed were based on the Indonesia National Standard (SNI) of honey. Data were analyzed descriptively by comparing the characteristics of honey samples from Riau Province. Results showed a significant difference between honey sent and those not sent between islands. Significant differences were mainly observed in hydroxymethylfurfural (HMF) levels. Almost all honey samples sent to Java Island had HMF levels above 50 mg/kg. Meanwhile, all Riau honey samples from the five regions had HMF levels below 50 mg/kg. The diastase enzyme activity was slightly higher in the honey samples from the five regions. Land transportation to the island decreased the quality of honey as indicated by the high levels of HMF and decreased diastase enzyme activity. Therefore, mileage and storage conditions must be considered in the delivery of Riau honey to other regions.
Introduction
Honey is a natural product with a sweet taste produced by honeybees from flower nectar and consumed due to its high nutritional value and health benefits, such as antioxidants, anti-inflammatory, antimicrobial, and wound healing. The composition of honey depends on the type of flower, season, environmental factors, and postharvest treatment by beekeepers (1,2).
Riau Province is one of the largest honey producers in Indonesia. Honeybee cultivation is prospective enough to be developed in Riau Province because of the gap between supply and demand for honey production. The supply of honey is about 8,000 tons/year, and the demand for honey is 20,000 tons/year. Honey shortage is addressed by importing from other countries and domestic industries. Problems often faced by honeybee farmers include simple technology, unsustainable honey harvesting, and inability of the product to meet the standards or criteria set by the market (3).
Land transportation is a necessary route for the delivery of honey outside Riau Province. Mileage that takes days, especially when shipping between the islands of Sumatra and Java, can reduce the quality of honey. Packing and high temperatures during land trip can also damage the composition of honey, thereby reducing its quality and consequently its health efficacy. For instance, hydroxymethylfurfural (HMF) and diastase activity are commonly used as parameters of honey quality, and both are greatly affected by temperature and storage conditions (4.5).
No data are available on the quality of Riau honey samples and the differences in the quality and composition of honey from Riau Province sent by land transportation to islands in Sumatra and Java with those of honey that only circulates in Riau Province. Therefore, this study aimed to determine the characteristics and quality of Riau honey samples, and compare the composition of honey from several regions in Riau Province with that of honey sent to Java Island.
Materials and Methods
A descriptive method was used to determine the characteristics of Riau honey and the effect of inter-island transportation on the composition of honey samples from five districts in Riau Province, namely, Indragiri Hulu (Inhu), Kuantan Singingi (Kuansing), Pelalawan, Bengkalis, and Kampar. This research was conducted from March to June 2019.
Forest honey samples consisted of one from Indragiri Hulu (Inhu) District, one from Kuantan Singingi (Kuansing), one from Bengkalis, two from Pelalawan, and one from honey farms in Kampar (kelulut honey). The honey sample from Pelalawan consisted of one sample from the Sorek area and one commercial honey sample.
In the first phase, honey samples from five districts in Riau Province were packaged in plastic bottles and sent to the Riau Provincial Trade Office for quality analysis. Testing parameters were adopted from SNI (Indonesia National Standard) 3545:2013.
In the second phase, honey samples from the five districts in Riau Province were sent to Java Island using land expedition services for 4 days. Honey was packaged in plastic bottles and then in boxes made of pieces of wood. Honey testing was conducted at the Agro-Industry Center (BBIA), Bogor. Testing for diastase activity, HMF, water, and acidity was conducted following SNI 3545:2013. Analysis of reducing sugar, sucrose sugar, total insoluble solids, and ash content was performed as per SNI 01-2892-1992. For metal contamination, MU/MO/10 (AAS) was adopted for lead and cadmium, MU/MO/12 (AAS) for mercury, MU/MO/13 (AAS) for arsenic, AOAC.999.11 ( The honey samples were examined in terms of 13 parameters such as diastase activity, HMF, water content, reducing sugar (glucose), sucrose, acidity, total insoluble solids, ash, metal contamination (Pb and Cd), microbial contamination (total plate count, coliform, mold, and yeast), and calcium levels tested at BBIA using SNI Parameter in 2013. Each sample was measured twice to ensure the validity and reproducibility of the data. The results were qualitatively analyzed to describe the characteristics of several honey samples in Riau and to determine the changes in HMF levels and diastase activity after the honey was sent to Java.
Characteristics of Riau Forest Honey
Riau is a province in Indonesia and is located on Sumatra Island. The climate is tropical with a maximum temperature of 35.1 °C and a minimum temperature of 21.8 °C. The average annual rainfall ranges between 1,700 and 4,000 mm (6).
The honey samples were analyzed at the Riau Provincial Trade Office using SNI 2013 parameters. The characteristics of some Riau honey samples are presented in Table I. The highest diastase activity was found in the Kuansing honey sample (8.16), and an average of 0 was obtained for the honey samples from other regions. The requirement for diastase activity according to SNI is a minimum of 3 DN. The diastase enzyme activity of the honey in this study was lower than that of the honey from India and Ethiopia varying from 36.7 DN to 57.5 DN and from 3.91 DN to 13.6 DN, respectively (7,8) but was higher than that of the honey from Malaysia ranging between 0 and 0.75 DN (9). The variation of diastase activity could be caused by the honey's floral origin. 1.0 X 10 6 < 3.0 2.8 X 10 2 2.5 X 10 3 < 3.0 3.0 X 10 1 6.2 X 10 2 < 3.0 2.0 X 10 1 2.8 X 10 3 < 3.0 1.0 X 10 2 6.9 X 10 3 < 3.0 7.0 X 10 1 3.7 X 10 3 < 3.0 2.0 X 10 1 The diastase activity in honey is affected by several factors. The temperature and heating process may decrease the diastase content. Biological differences among species of bees also affect the diastase content of honey (10).
The enzyme content in honey is one of the characteristics that are considered beneficial for health. The main enzymes found in honey are invertase (saccharase), diastase (amylase), and glucose oxidase. Diastase activity is an essential factor that determines the quality of honey. Although enzymes are a small part of honey's composition, their presence is associated with health advantages, including nutritional benefits, carbohydrate digestion, and antimicrobial activity (11,12).
For HMF level parameters, all Riau honey samples met SNI requirement of below 50 mg/kg (from 0.49 mg/kg to 27.84 mg/kg). The lowest HMF level was found in Kuansing honey sample at 0.49 mg/kg. The average HMF level in this study was lower than that of Tunisian honey (12.07 mg/kg to 27.43 mg/kg) (13) and higher than that of Ethiopian honey (0 to 3.37 mg/kg) (8). The high water content of honey could increase its HMF level.
HMF is a cyclic aldehyde produced from the breakdown of sugar through the Maillard reaction (a non-enzymatic browning reaction) during food processing or long storage. The content of simple sugars (glucose and fructose), acidic compounds, and minerals can increase the production of HMF. HMF affects the freshness of honey because freshly harvested honey contain minimal and even no HMF. HMF concentrations tend to increase during processing or storage (4). High acid content, moisture content, sugars, amino acids, and minerals could increase HMF level (14).
The moisture content of Riau honey samples ranged from 19.4% to >25%. The maximum water content according to SNI is 22. The honey samples from Bengkalis had a moisture content of 20.6, and commercial honey had a water content of 19.4. The Bengkalis honey sample has undergone dehumidification, a process of decreasing water content. Commercial honey is also suspected to have undergone this procedure.
The moisture content of Riau honey samples was higher than that of Tunisia honey (17.27% to 19.80%) and Turkish honey (15.1% and 20.4%) (13,15). The high moisture content in Riau honey samples can be caused by honey harvesting in the rainy season.
Honey contains water, fructose, and acidic compounds. Mold can grow in honey when the water content of honey is high. Fermentation is a problem in honey. If the water content increases, then fermentation and decomposition could rapidly occur (16). Water content in honey is affected by plant species, geographical origin, season at harvest time, and postharvest processing, such as honey extraction, processing, and storage conditions (14).
The highest reducing sugar content was detected in Sorek honey samples at 67.14 (minimum SNI requirement of 65). The honey samples from other regions had reducing sugar levels below 65. These values were lower than the reducing sugar content of Saudi honey (72.36 ± 0.32 g/100 g) (1) and Croatian honey with an average of 67.69 ± 7.05 g/100 g for acacia honey and 77.82 ± 12.25 g/100 g for chestnut honey (17). The reducing sugar content is determined by the duration of storage and honey collection time (18).
Honey is rich in reducing sugars, notably fructose (38%) and glucose (31%). Both types of sugar do not require hydrolysis by enzymes in the digestive tract to directly be absorbed in the small intestine. Fructose may lower hyperglycemia or sugar levels in experimental mice, healthy subjects, and patients with diabetes. Therefore, fructose does not enhance blood glucose. Furthermore, its metabolism does not require insulin. Glucose also increases fructose absorption in the gut (11).
The requirement for sucrose content in honey is a maximum of 5% according to SNI. The honey from Kuansing, Inhu, Kampar, and Sorek achieved this requirement. However, the honey from Bengkalis and Pelalawan (commercial) did not reach the SNI standard and had sucrose contents of 6.38% and 3.14%, respectively. Tunisian honey has a sucrose level below 5% (0.20% to 4.60%) (13). Multifloral honey from Poland and Slovakia has a sucrose level of 4.40% ± 1.95% and 4.47% ± 2.15%, respectively (19). Source of plant, immaturity of honey, and artificial feeding of bees affect the sucrose content in honey (14).
The sucrose in honey is turned into glucose and fructose. High levels of sucrose indicate premature honey harvesting. Hence, invertase cannot fragment sucrose into glucose and fructose. Sugar content in honey is affected by the ratio of fructose-glucose and sucrose content. Crystallized honey suggests a high level of glucose. Therefore, the glucose in honey is hardly soluble in water. Honey also contains other types of sugar that can impede crystallization (13,20).
The maximum acidity level in honey is 50 N/Kg according to SNI 2013. Bengkalis, Kampar, and Commercial honey samples had a high acidity above 50 N/kg. Sudan honey has an acidity of 51.80 ± 1.95 meq/kg for Apis melifera honey and 98.40 ± 1.82 meq/kg for Apis florea honey (21). Meanwhile, Tunisian honey has a low acidity ranging from 0.0071 N/kg to 0.0272 N/kg. Different levels of acidity in honey may be caused by the varied botanical origin or the difference in harvest season (13).
The characteristics of flower nectar sucked by bees affect the acidity in honey. Low acidity indicates freshness, and high acidity indicates the fermentation of glucose into organic acids. The consistency of honey also affects its acidity. Liquid texture has a higher acidity than solid texture because the production of free acid from fermentation easily occurs in liquid honey texture. In addition, acidity is affected by the length of storage. Free acids produced by fermentation during storage will increase the acidity of honey (20).
The total insoluble solids in this study ranged from 0.37% to 1.90%. SNI 3545:2013 imposed a maximum of 0.5%, which was only achieved by Bengkalis honey. By contrast, Turkish honey has a weak total insoluble solid content between 0.001% and 0.080% (22), and Ethiopian honey has a total insoluble solid content of 0.005%-0.22%. Honey requires a proper procedure to avoid contamination with insoluble solids (23). A high number of insoluble solids in honey, such as impurities or other particles, could indicate poor hygiene during postharvest honey process.
All honey samples met the maximum ash content according to SNI (not more than 0.5%), except for Bengkalis honey that had a slightly high ash content (0.54%). Sudan honey contains 0.26% (Apis melifera) and 1.16% (Apis florea) ash content (21), and Brazil honey has an ash content between 0.11% and 0.95% (24).
Ash levels indicate mineral content and are affected by honey extraction methods and bee food (21,25). Other factors can influence ash content in honey, such as environment, geography, and vegetation (24).
For metal contamination, all Riau honey samples met the SNI requirements (<2.0 mg/kg for lead and <0.2 mg/kg for cadmium). Turkey honey has low lead (mean of 0.04 ± 0.09) and cadmium (mean of 0.0002 ± 0 contents. In Chines honey, the average contents of lead and cadmium are 1.34 and 33.98 µg/kg, respectively (26,27). Most of Riau honey samples were derived from multifloral honey or forest honey distant from industrial areas. For this reason, the concentration of heavy metals was low in Riau honey samples.
Bees can fly up to a radius of 4 km from the hive, allowing them to access an area of 50 km 2 . Contact of bees with air, soil, and water cause their honey to contain heavy metals. The level of heavy metals in honey can indicate the number of heavy metals found in the environment. Contaminated air, water, and soil and honey processing influence the composition of heavy metals in honey (11,28).
Although heavy metals constitute a small part of honey, they are crucial in the quality of honey. Honey can contain heavy metals such as lead and cadmium that can damage health (11). Furthermore, heavy metals such as Pb, Cd, Hg, Cr, Cu, Mn, Ni, and Zn are nonbiodegradable substance that can accumulate in the human body and cause health problems, including metabolic and respiratory disorders, headaches, nausea, and vomiting (28).
TPC indicates the number of microorganisms (pathogenic and nonpathogenic) in honey. For example, Bacillus sp., Clostridium sp., Micrococcus sp., lactic acid bacteria, yeast, and fungi are present in honey. These microorganisms could originate from the air, soil, water, dust, pollen, and nectar. In addition, unhygienic conditions during honey extraction, processing, and packaging may cause microorganism contamination in honey (30,31).
Honey can load microorganisms, such as bacteria, mold, and yeast. Contamination in honey can occur either through primary sources (pollen, flower nectar, dust, soil, body, and digestive tract of bees) or secondary sources during postharvest processing, such as humans and equipment (32,33).
All honey samples fulfilled coliform requirements i.e.,., <3 APM/g but failed to meet the requirements for mold and yeast because they exceeded SNI requirements, i.e., <1 x 10 1 APM/g. Similarly, the amounts of mold and yeast found in Croatian honey are above the accepted standard for mold at 18-182 cfu/g and for yeast at 18-1,300 cfu/g. The molds in Croatian honey originated from primary sources such as the digestive tract of bees (34). Microorganisms are found in honey because they can survive in high sugar solutions and acid conditions (29).
Most microorganisms in honey are not harmful to health. The antimicrobial properties in honey can inhibit the growth of microorganisms. However, honey may contain Clostridium botulinum, which leads to infant botulism. Consequently, honey is not recommended for children under 1-year-old (31). Table II shows the honey quality test results with 13 parameters based on SNI 3545:2013. None of the Riau honey samples met all the honey requirements based on SNI in 3545:2013. Honey samples from Kuansing, Inhu, and Sorek met eight SNI requirements, and honey samples from Bengkalis, Kampar, and commercial honey samples met only seven SNI 3545:2013 requirements. Each of the three honey samples that achieved the eight SNI requirements had priorities. Kuansing honey samples showed high diastase activity, Sorek honey samples had high levels of reducing sugar, and Inhu honey samples contained low total plate numbers.
Changes in Riau Honey Composition after Inter-Island Shipping
The honey samples sent to Java were analyzed at BBIA, Bogor. Changes in the composition of honey samples were observed, primarily in the level of diastase activity and HMF levels. These two parameters are affected by the heating process and have a negative correlation. Diastase activity tends to decrease when the heating process is prolonged, and HMF level tends to increase with heating time (7). Table III provides the changes in the composition of Riau honey sent by land transportation to Java Island. Table 3 shows a significant decrease in the quality of honey after inter-island delivery, especially in the diastase activity. Almost all honey samples had 0 (zero) activity of diastase, except for the commercial honey from Pelalawan with a diastase level of 1.83 DN. This value is below the SNI requirement, that is, a minimum of 3 DN.
Diastase activity is a measurement of α-amylase and β-amylase activities and is often used as a quality parameter of honey. Diastase activity decreases due to heating (9). A decreased diastase activity can be due to transportation between the islands of Sumatra and Java. The storage conditions of honey samples prior to transport might have caused heating in honey during transport for 4 days.
HMF levels increased significantly (>50 mg/kg), except in Bengkalis honey samples and commercial honey samples with HMF 0 levels. This phenomenon occurred because HMF broke down into levulinic acid and formic acid. Hence, HMF was not detected.
The determination of HMF in honey samples aims to find out the freshness of honey. Increased HMF is associated with prolonged storage at high temperatures or excessive heating of honey. The HMF level acceptance limit varies by country and is high in the tropics at 80 mg/kg (4,18). According to SNI 3545: 2013, HMF levels in honey must not be more than 50 mg/kg.
Factors that can affect the formation of HMF include high temperature, low pH, prolonged storage, high water content, and use of metal box (4). Honey samples sent by land transportation can increase HMF levels due to storage conditions that cause the heating of honey during a 4-day expedition. The high water content in four honey samples (Kuansing, Inhu, Kampar, and Sorek) can also induce the increase in their HMF levels.
HMF has negative effects on human health, such as cytotoxicity on mucous membranes, skin, upper respiratory tract, chromosomal aberrations, and carcinogenic effects on humans and animals. However, recent research showed that HMF has positive effects such as antioxidants, anti-allergies, anti-inflammatory, and anti-carcinogens. These results were obtained at the preclinical stage and therefore require further research (4).
For other parameters, no significant changes were observed in the honey sent to Java. Calcium levels were only measured in BBIA Bogor, and the highest of 270 mg/kg was found in Bengkalis honey. The calcium level in this study was higher than that in honey from natural hives in Nigeria that ranges between 37,76 and 40,90 mg/kg (35) and honey from Tunisia that ranges between 221,07 and 113,85 mg/kg honey (13).
The predominant minerals in honey are potassium, sodium, calcium, and magnesium (14). The mineral content of honey is manifested in its color, that is, dark honey has more minerals than light honey (35). Consumption of honey provides calcium that is easily absorbed and could strengthen bone mass. This mineral could reduce the risk of osteoporosis or low bone mass, a cause of fractures especially in the elderly (36).
Conclusions
None of the analyzed Riau's honey samples fulfilled all SNI 3545:2013 requirements. Only three honey samples, namely Kuansing, Inhu, and Sorek honey samples, could fulfill 8 out of 13 SNI requirements, and another three honey samples could meet 7 out of 13 SNI 3545:2013 requirements. A decrease in diastase activity and an increase in HMF were observed in the honey sent to Java. Therefore, distance and storage conditions must be considered in the land transportation of honey out of Riau Province to maintain honey quality.
Institutional Review Board Statement
This study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of the Health Research Ethics Committee, Faculty of Public Health, Universitas Indonesia, Indonesia (protocol code 332/UN2. F10/PPM.00.02/2019, 16 May 2019).
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Domain: Agricultural And Food Sciences
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Enhancement of the antioxidant and skin permeation properties of eugenol by the esterification of eugenol to new derivatives
The aim of the study was to determine the antioxidant activity and assess the lipophilicity and skin penetration of eugenyl chloroacetate (EChA), eugenyl dichloroacetate (EDChA), and eugenyl trichloroacetate (ETChA). Identification of the obtained products was based on gas chromatography (GC), infrared spectroscopy (FTIR/ATR), gas chromatography coupled with mass spectrometry (GC-MS), and the analysis of 13C-NMR and 1H-NMR spectra. The antioxidative capacity of the derivatives obtained was determined by the DPPH free radical reduction method, while the octanol/water partition coefficient (shake-flask method) was tested to determine the lipophilicity of these compounds. In the next stage of testing EDChA and ETChA–(compounds characterized by the highest degree of free radical scavenging), the penetration of DPPH through pig skin and its accumulation in the skin were evaluated. For comparison, penetration studies of eugenol alone as well as dichloroacetic acid (DChAA) and trichloroacetic acid (TChAA) were also carried out. The antioxidant activity (DPPH, ABTS, and Folin–Ciocalteu methods) of the fluid that penetrated through pig skin was also evaluated. The in vitro pig skin penetration study showed that eugenol derivatives are particularly relevant for topical application. The obtained derivatives were characterized by a high level of antioxidant activity estimated after 24 h of conducting the experiment, which indicates long-term protection against reactive oxygen species (ROS) in the deeper layers of the skin.
Introduction
Reactive oxygen species (ROS) are important factors in the ageing process that are formed during incomplete reduction of oxygen molecules in the respiratory chain. When there is an imbalance between reactive oxygen species and the body's antioxidant potential, oxidative stress occurs. It is widely recognized that reactive oxygen species (ROS) contribute to the aging of the skin, which is the external barrier of our body. However, many tissues inside our body are also subjected to ROS. In fact, the human body is exposed to both endogenous and exogenous ROS effects. These compounds, which cause oxidative stress, are responsible for oxidative modifications of polyunsaturated fatty acids and nucleic acids (as a consequence, this leads to structural changes in cell membranes as well as to DNA damage). Antioxidants are compounds characterized by the ability to deactivate free radicals responsible for the ageing process of the body (Dhale et al. 2007;Michalak et al. 2014;Igielska-Kalwat et al. 2015;Agati et al. 2012;Zhao 2015;Suvarnakuta et al. 2011;Li and Seeram 2010;Janiuk et al. 2013). To assess their antioxidant properties, in vitro methods are mainly used, and these are based on two types of reactions: the HAT (hydrogen atom transfer) technique and the SET (single electron transfer) method. The first method is related to the transfer of a hydrogen atom derived from an antioxidant, while the second method involves the transfer of a single electron from an antioxidant molecule (Zheng 2017;Makuch et al. 2019). The most commonly used methods for assessing the antioxidant properties of compounds include the ferric ion reducing antioxidant parameter (FRAP) method, the method using the ABTS reagent (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), determination of total polyphenol content using the Folin-Ciocalteu reagent, and the method for determining the antioxidant activity using the DPPH radical (2,2-diphenyl-1-picrylhydrazyl) (Gulcin 2011;Molyneux 2004;Li et al. 2011;Benzie and Strain 1996). In spectroscopic methods, the quantitative analysis of antioxidant capacity is based on the change in absorbance of the test solution (Gulcin 2011;Molyneux 2004;Li et al. 2011;Benzie et al. 1996).
The DPPH radical is a dark purple color and has a maximum absorbance at λ = 515-517 nm. The method of measuring the antioxidant capacity of compounds using the DPPH technique is based on a spectrophotometrically recorded change in the color of the ethanol solution of the DPPH radical. The reaction of the DPPH radical with an antioxidant occurs on one of the nitrogen atoms present in the DPPH molecule (on the so-called nitrogen bridge). When the DPPH radical is transferred to the hydrogen atom present at the antioxidant hydroxyl group, the dark violet color of the DPPH ethanol solution changes to light yellow or the solution completely discolors; thus, the absorbance of the tested solution decreases (Gulcin 2011;Molyneux 2004;Li et al. 2011).
Literature reports indicate that clove oil, eugenol, and esters obtained by esterifying eugenol with acetic anhydride or benzoic acid (eugenyl acetate and eugenyl benzoate) are characterized by the ability to deactivate free radicals (Horchani et al. 2010;Vanin et al. 2014;Sá et al. 2017). Besides, eugenol, eugenyl acetate, eugenyl propionate, eugenyl butyrate and eugenyl 4-ethyl, 4-fluoro, 4-chloro and 4-bromobenzoate are also characterized by antimicrobial activity (Rahim 2017;Chaibakhsh et al. 2012;Cichorek et al. 2013). Other literature reports indicate that eugenol and eugenyl acetate are also characterized by anti-tumour activity against the B16 melanoma cell line, as assessed by the method described by Arung et al. (2007Arung et al. ( , 2011. The results of our previous preliminary studies related to the assessment of antioxidant activity showed that products obtained by the esterification of eugenol with the appropriate carboxylic acid chloride compounds are characterized by their ability to react with the free radical DPPH (Makuch et al. 2019). The natural consequence of this trend is the synthesis and evaluation of antioxidant activity of the chloro-, dichloro-, and trichloroacetate derivatives. In addition to antioxidant activity, antioxidants should be characterized by an adequate level of penetration through the stratum corneum of the skin into its inner deeper layers. The indicator of the hydrophilicity and hydrophobicity of compounds is the octanol/water partition coefficient (log P). By increasing the lipophilicity of eugenol through its esterification, the penetration of obtained ester derivatives through cell membranes is facilitated (Malinowska et al. 2013). The stratum corneum is a physical, environmental, and microbiological barrier that protects the body against external factors. It is mainly made of lipid substances such as ceramides, cholesterol, fatty acids, cholesterol esters, and phospholipids present in the stratum corneum in small amounts. These substances can significantly inhibit the penetration of exogenous compounds (both therapeutic and cosmetic) into the deeper layers of the skin. Also, the nature of the outer layer means that lipophilic substances penetrate it much more easily than the hydrophilic compounds that accumulate in it (Jaworska et al. 2011). By giving active substances adequate lipophilicity, their penetration is increased while their accumulation is limited. This phenomenon is particularly important in the case of active substances such as added antioxidants that are characterized by high antioxidant activity in both the stratum corneum of the skin and in its deeper layers (IIntarakumhaeng and Li 2014;Zhang et al. 2016). Therefore, the use of eugenol ester derivatives as active substances with high antioxidant activity and higher lipophilicity (compared to eugenol and the acids from which these derivatives were obtained) can be an alternative for obtaining cosmetic preparations characterized by longlasting protection against free radicals (ROS).
As part of the research, eugenyl chloro-, dichloro-, and trichloroacetate were obtained by reacting eugenol with chloro-, dichloro-, and trichloroacetic acid chlorides. Esters were synthesized as described in our previous publication (Makuch et al. 2019). The selectivity of the conversion to EChA, EDChA, and ETChA as well as the conversion of eugenol were determined by the gas chromatography (GC) method, while the molar masses of the obtained products were confirmed based on the mass spectrum (GC-MS). The most important band associated with the presence of an ester group in the structure of the obtained products was identified by infrared spectroscopy. The unequivocal confirmation of the structure of new eugenol ester derivatives not yet described in the literature was carried out by NMR. The antioxidative activity and the octanol/water partition coefficient of eugenol and its esters were evaluated by the spectrophotometric method.
The penetration through pig skin using the Franz diffusion cell, accumulation of two derivatives (EDChA and ETChA) in the skin, eugenol content, as well as DChAA and TChAA contents were evaluated. Moreover, the antioxidant potential of solutions applied to the skin and obtained after 24 h of penetration through the skin as well as the activity of the skin after the test were assessed.
Synthesis and characterization of new esters
First, EChA, EDChA, and ETChA were obtained by the method described in our previous publication (Makuch et al. 2019). After synthesis, the obtained products were identified by mass spectrometry coupled with gas chromatography (GC-MS). Chromatographic analyses were performed with a TRACE GC series apparatus with a VOYAGER mass detector using a DB5 capillary column (30 m × 0.25 µm × 0.5 µm). The following separation parameters were used for the analysis: helium flow of 1.0 ml/min, sample chamber temperature of 240 °C, and detector voltage of 350 V. The thermostat temperature increased according to the following program: isothermal at 50 °C for 1 min, increase at a rate of 8 °C/min, isothermal at 260 °C for 5 min, and then cooled to 50 °C. The sample partition coefficient in the dispenser was 20, the volume of dispensed sample was 0.1 µl, and the ion mass range was 25-350 mV/z.
The degree of conversion of eugenol and the purity of the obtained products were determined by gas chromatography (GC). Chromatographic analyses were performed on a FOCUS apparatus (Thermo Electron) with a flame ionization detector (FID) and a RESTEK RTX-5 capillary column (0.53 mm × 30 m × 1.5 µm). Infrared spectroscopy (FTIR/ATR) was characterized by functional groups present in the structures of the products obtained. Analyses were performed on a THERMO NICOLED 380 apparatus using a measuring range of 4000-400 cm −1 . The same method also used eugenol for comparative purposes.
The structures of the obtained esters (dissolved in deuterated chloroform (CDCl 3 )) were confirmed based on the analysis of nuclear magnetic resonance (NMR) spectroscopy spectra, which was performed with a Bruker DPX-400 spectrometer. The conditions for recording 13 C-NMR spectra were as follows: 100.62 MHz, a spectrum width of 24 kHz, 65.5 K data points, a resolution of 1.46 Hz/point, a data acquisition time of 1.37 s, a repetition time of 1 s, a pulse width of 9.2 µs, and 1-8 scans. In addition, 1 H-NMR spectra were recorded under the following conditions: 400.13 MHz, a 12 kHz spectrum width, 65.5 K data points, a 0.488 Hz/point resolution, a data acquisition time of 4.09 s, a repetition time of 1 s, a 7.8 µs pulse width, and 16-32 scans.
On the 1 H-NMR spectrum, which is presented in Fig. 1, the presence of clear peaks indicating the presence of certain groups of protons in the structure of the tested ester was observed. The proton signals recorded as intense peaks corresponded to hydrogen atoms from groups belonging to hydrocarbon chains, indicating the presence of an aromatic system in the molecule of the compound tested. The analysis of the 13 C-NMR spectrum presented in Fig. 2 supplemented the information obtained based on the interpretation of the 1 H-NMR spectrum and additionally confirmed the structure of the obtained ester. The chemical shift values of carbon atoms and protons as well as the signals assigned to atoms 13 C and 1 H were as follows: 13 C-NMR (101 MHz, CDCl 3 ) δ 160. 24, 150.51, 140.43, 137.71, 136.75, 121.45, 120.77, 116.50, 116.46, 89.54, 56.04, 40.09; 1 H NMR (400 MHz, CDCl 3 ) δ 6.98 (d, J = 8.0 Hz, 1H), 6.80-6.67 (m, 2H), 5.97-5.81 (m, 1H), 5.04 (dtd, J = 14.7, 3.4, 1.7 Hz, 2H), 3.76 (s, 3H), 3.32 (dt, J = 6.7, 1.5 Hz, 2H).
Measurement of lipophilicity of eugenol and new esters
To determine the lipophilicity of eugenol and its ester derivatives, the values of the n-octanol/water partition coefficient (P) were examined. Determining the lipophilicity of a substance involves determining its partition coefficient between two immiscible liquids: n-octanol and water (which model the properties of cell structures well). The partition coefficient was expressed as the logarithm ratio of substance concentrations in both phases (Piwowarczyk et al. 2017): where P is the partition coefficient, C n-octanol is the concentration of the compound in the octanol phase, and log P = log C n-octanol − log C water ,
Fig. 1 1 H-NMR spectrum of ETChA
C water is the concentration of the compound in the aqueous phase.
N-octanol was mixed with water in a 1:1 ratio containing the test compound at a concentration of 32.00-178.00 mg/100 ml solution. The mixture was then shaken on a shaker (TS-2 Orbital Shaker) for 24 h at a constant temperature of 25 °C, which was controlled by an immersion thermostat. Concentrations of substances in the analyzed samples were determined by spectrophotometry at the following wavelengths: 279 nm (in the case of eugenol), 272 nm (in the case of EChA), 277 nm (in the case of EDChA), and 280 nm (in the case of ETChA). For comparison purposes, log P values for DChAA and TChAA were also determined by potentiometric method. Furthermore, blanks were performed for each compound tested. For this purpose, n-octanol was mixed with water in a 1:1 ratio, and then the mixture was shaken for 24 h under constant temperature conditions, after which the aqueous layers were analyzed by a spectrophotometric method using appropriate wavelengths λ (Piwowarczyk et al. 2017).
Furthermore, compounds contained in aqueous solutions were identified by thin-layer chromatography (TLC). Based on the obtained chromatograms, the retention factor (R f ) values for the corresponding ester and pure eugenol were determined. The absence of eugenol in aqueous solutions of the esters tested indicated a lack of the hydrolysis of these compounds (Waszczuk and Makuch et al. 2020).
Measurement of the antioxidant capacity using DPPH, ABTS and Folin-Ciocalteu methods
Studies on the antioxidant activity of eugenol and its esters were carried out by free radical reduction (DPPH) (Brand-Williams et al. 1995;Nowak et al. 2017), ABTS , and the Folin-Ciocalteu method (Nowak et al. 2019). The ABTS assay is based on the generation of a blue/green ABTS, which is applicable to both hydrophilic and lipophilic antioxidant systems; whereas DPPH assay uses a radical dissolved in organic media and is, therefore, applicable to hydrophobic systems (Floegel et al. 2011).
The analyses were performed on a Merck Spectroquant Pharo 300 apparatus at the following wavelengths λ: 517 nm (in the case of the DPPH method), 734 nm (in the case of the ABTS method), and 765 nm (in the case of the Folin-Ciocalteu method). Trolox was used as a reference substance in the DPPH and ABTS methods, while gallic acid was used as a standard to assess the polyphenol contents in the sample tested by the Folin-Ciocalteu method. The antioxidant activity results obtained by these methods are expressed in mmol/dm 3 .
The antioxidant activity of eugenol and its ester derivatives was measured as follows: 2850 µl of an ethanol solution with the DPPH radical was introduced into the tube, and its absorbance at λ = 517 nm was about 1.000 ± 0.020 with 150 µl of the ethanol solution containing the tested antioxidant. The tube was wrapped in aluminum foil and its contents were sealed with a stopper and then incubated for 10 min at room temperature. After this time, spectrophotometric measurements were carried out at the appropriate wavelength and in triplicate.
First, an aqueous solution of potassium persulfate (2.45 mM) was prepared, in which an appropriate amount of ABTS reagent was introduced to obtain a 7 mM solution of ABTS in an aqueous solution of potassium persulfate. The solution prepared in this way was incubated at 4 °C for 24 h and then diluted with methanol (50% v/v) to obtain an absorbance of approximately 1.000 ± 0.020.
The antioxidant activity of eugenol and its ester derivatives was measured as follows: 2500 µl of prepared ABTS solution and 25 µl of an ethanol solution with the tested antioxidant were introduced into the spectrophotometric cuvette. The cuvette was sealed with a stopper and then incubated for 6 min at room temperature. After this time, the spectrophotometric measurement was carried out at the appropriate wavelength and in triplicate.
This method is based on the use of the Folin-Ciocalteu reagent (takes place in an alkaline medium), which is used to determine the total content of phenolic compounds found in the tested samples. The reaction is based on the spectrophotometrically recorded color change of the test solution from yellow to blue.
Two hundred microliters of Folin-Ciocalteu reagent in 1800 µl of water was dissolved in a dark bottle. The solution prepared in this way was incubated at room temperature for 60 min. The antioxidant activity of eugenol and its ester derivatives was measured as follows: 1350 µl of distilled water and 1350 µl of sodium carbonate solution (0.01 mol/dm 3 ) were introduced into the spectrophotometric cuvette with 150 µl of the prepared Folin-Ciocalteu solution and 150 µl of an ethanol solution containing the tested antioxidant. The cuvette was sealed with a stopper and then incubated for 15 min at room temperature. After this time, spectrophotometric measurements were carried out at the appropriate wavelength and in triplicate.
Skin permeation studies of eugenol and new esters
Porcine skin was used for the study due to its similar properties permeability to human skin (Čuříková et al. 2017;Janus et al. 2020). The skin came from a local slaughterhouse. A fresh portion of skin from the abdomen was washed several times with a solution of PBS at pH 7.4. Skin with a thickness of 0.5 mm was cut with a dermatome, and then it was wrapped in aluminum foil and frozen at − 20 °C for a maximum of 3 months. This freezing time ensured the stability of the skin barrier properties (Badran et al. 2009). Before the examination, the skin was thawed at room temperature for about 30 min, and then it was soaked in a PBS solution for 15 min to hydrate it (Haq et al. 2018;Kuntsche et al. 2008;Simon et al. 2016). In the next stage, the skin was mounted in Franz diffusion cells.
The integrity of skin was checked 1 h after its installation in the Franz diffusion chamber (SES GmbH Analyze Systeme, Germany). Skin impedance was measured using an LCR 4080 meter (Conrad Electronic, Germany) operating in parallel mode at 120 Hz (kΩ error < 0.5%). To make the measurement, the tips of the probes were immersed in the donor and acceptor chambers filled with the PBS solution (Kopečná et al. 2017). Membranes with an electrical resistance of > 3 kΩ, corresponding to the resistance measured for human skin, were used in the study (Davies et al. 2004).
The penetration of eugenol and its ester derivatives was assessed in a Franz diffusion chamber consisting of a 2 ml donor chamber and an 8 ml acceptor chamber.
The area through which the tested active ingredients permeated was 1 cm 2 . The acceptor fluid, mixed with a magnetic stirrer, was a PBS solution that maintained the physiological pH. The acceptor chamber was kept at a constant temperature of 37 ± 0.5 °C with the VEB MLW Prüfgeräte-Werk type 3280 thermostat. Before starting the test, Franz diffusion cells were allowed to equilibrate at 37 °C for 15 min. After this time, ethanol solutions of test compounds (at a concentration of 1% w/v) were placed in the donor chamber. For the study, 500 µL of the ethanol solution of the test compound (at a concentration of 1% w/v) was applied to the outer layer of the skin in each donor chamber to ensure continuous delivery of the active substance during the experiment. All donor chambers were closed with a plastic stopper to prevent excessive evaporation of the solution. The described tests were carried out for 24 h, while 0.3 ml of the solution located in the acceptor chamber was taken at specified intervals (30 min, 1 h, 2 h, 3 h, 4 h, 5 h, 8 h and 24 h), and then supplemented with a fresh portion buffer at the same pH (Kopečná et al. 2017). The samples were analyzed by high-performance liquid chromatography (HPLC) with a UV spectrophotometric detector (Knauer, Berlin, Germany). The components tested were separated on a 125 × 4 mm column containing Hyperisil ODS; particle size 5 µm. The flow rate of the mobile phase, consisted of acetonitrile, water, and MeOH (28:64:8, by vol) was 1 ml/min. Twenty microliters of each analyzed sample was injected onto the column.
After the experiment was carried out, the skin was extracted to estimate the residual volume of tested active ingredients accumulated in it. The antioxidant activity of the obtained extracts was also tested using modified methods described in (Brand-Williams et al. 1995;Nowak et al. 2017;Nowak et al. 2019). Extraction was carried out as follows: after the experiment was completed, the Franz diffusion chambers were dismantled, while the skin surface was washed three times with an aqueous solution of sodium lauryl sulfate (at a concentration of 0.5% w/w) to elute the ethanol solution of the test compound. A patch (1 cm 2 diffusion surface) was cut from the skin prepared in this way, dried at room temperature, and then weighed and cut into smaller pieces. Then, 2 ml of concentrated methanol was added to it, and extraction was carried out for 24 h at 4 °C. After 24 h of incubation, the skin was homogenized (for 3 min) using a homogenizer (IKA ® T18 digital ULTRA TURRAX, Germany). The extracts obtained were then centrifuged at 3500 rpm for 5 min. The supernatant was analyzed by HPLC to determine the content of active ingredients, while to evaluate the antioxidant activity of the obtained extracts the DPPH, Folin-Ciocalteau, and ABTS methods were applied.
The cumulative mass of active substance (µg) permeating into the receptor chamber was calculated based on the concentrations of compounds determined by HPLC. The permeation rate was determined based on the amount of permeation of a compound over a given period (µg/cm 2 /h). The accumulation of compounds in the skin was calculated by determination of remaining ingredients in the liquid obtained after skin extraction; the results are given in µg/cm 2 of skin.
The antioxidant activity of solutions of test compounds applied to the skin, acceptor fluid taken after 24 h of penetration, and solutions obtained after skin extraction taken at the end of the experiment was determined using the DPPH, Folin-Ciocalteau, and ABTS methods, as described in sections: measurement of the antioxidant capacity of eugenol and new esters using the DPPH, the ABTS and the Folin-Ciocalteu methods.
Statistical calculations were done using Statistica 13 PL software (StatSoft, Polska). The results were evaluated using one-way analysis of variance (ANOVA). Significant differences between the permeation of individual compounds were evaluated using Tukey post-hoc test. Probabilities < 0.05 were considered to be statistically significant. Results are presented as the mean ± standard deviation (SD).
Results
Research by the GC method showed that the process yielded eugenol esters as the main products with 100% selectivity, with eugenol conversion of 99.7% (in the case of EChA and ETChA) and 99.8% (in the case of EDChA).
The IR ETChA spectrum, which is shown in Fig. 4, has an absorption band characteristic of the ester group at a wavelength of about 1775 cm −1 . Also, there is no wideband at a wavelength of about 3500 cm −1 , which is attributed to the stretching vibration of O-H bonds. However, this band occurs in the eugenol molecule. Besides, absorption bands were observed at a wavelength of about 3010 cm −1 (derived from CH carbon atoms with sp 2 hybridization) and at a wavelength of about 1637 cm −1 (associated with the presence of C= C carbon atoms), which occur in both the allyl group as well as in the aromatic ring of eugenol and its ester. In the IR spectrum of eugenol and ETChA, absorption bands were measured at wavelengths of about 2976 cm −1 (attributed to CH carbon atoms with sp 3 hybridization) and about 1300-1118 cm −1 (found on carbon in the aromatic ring), derived from the methoxy group (Kuo et al. 2009;Ginting et al. 2019). In the case of the remaining esters (EChA and EDChA), the same functional groups that were present in the structure of ETChA were observed. Table 1 presents a comparison of octanol/water partition coefficient values determined by the experimental method and calculated in the MestReNova program.
Each compound's lipophilicity is represented as the decimal logarithm of the partition coefficient (Piwowarczyk et al. 2017). Results are presented as the mean ± standard deviation (SD). The partition coefficient (log P) values for eugenol and its ester derivatives, determined using the theoretical calculation method, were slightly higher than the log P values obtained by the spectrophotometric method (Table 1).
The log P values for dichloroacetic acid and trichloroacetic acid (DChAA 0.80 and 0.95 ± 0.002, TChAA 1.42 and 1.51 ± 0.002-- Table 1) were similar to the log P values described in the literature. However, by comparing the literature data describing the partition coefficient values determined by the experimental and theoretical methods, we found that depending on the method used, log P values ranged from 2.13 to 2.66 (in the case of eugenol), from 0.92 to 1.06 (in the case of dichloroacetic acid), and from 1.17 to 1.53 (in the case of trichloroacetic acid). There is no data in the literature describing the partition coefficient values that have been determined for ester derivatives such as eugenyl chloroacetate (EChA), eugenyl dichloroacetate (EDChA), and eugenyl trichloroacetate (ETChA). Eugenol ester derivatives are considered nonionized substances. Due to the neutral nature of these compounds, their solubility is not dependent on the pH of the environment. Under the conditions of the experiment, there is no dissociation of esters to ionized forms, which would significantly disturb the solubility profiles of the derivatives obtained (Kuo et al. 2009;Ginting et al. 2019;Pernin et al. 2019;Sangster 1993Sangster , 1997Sangster , 2009Hansch 1996;Howard and Meylan 1997).
The values of the antioxidant activity of the tested compounds (at a concentration of 1% w/v) were 1.23 ± 0.01 mmol TE/dm 3 (for eugenol), 0.32 ± 0.01 mmol TE/dm 3 (for EChA), 1.08 ± 0.02 mmol TE/dm 3 (for EDChA), and 1.04 ± 0.01 mmol TE/dm 3 (for ETChA), respectively- Table 2. Both eugenol and its ester derivatives with the highest values of antioxidant activity (i.e., EDChA and ETChA) were assessed for penetration through pig skin using the Franz diffusion chamber. Table 2 presents the results for the antioxidant activity of solutions of the tested compounds, carried out by the DPPH method. Table 3 presents the results for the antioxidant activity of the solutions of the tested compounds, carried out using the ABTS method. Table 4 shows the total polyphenol content in solutions of the tested compounds, carried out using the Folin-Ciocalteu method.
The test results, presented in Tables 2, 3 and 4, show that the initial solutions of the tested compounds (eugenol, EDChA, ETChA) applied to the skin, solutions of acceptor liquids, and solutions obtained after skin extraction were characterized by high antioxidant activity.
In the case of studies carried out for pure TChAA and DChAA, no antioxidant activity was shown.
The results of the studies on the antioxidant activity of acceptor fluid solutions (collected after 24 h of permeation) showed that the tested solution were characterized by antioxidant activity due to of eugenol and its esters. The degree of reduction of the DPPH free radical increased in the following order: 0.08 ± 0.01 mmol Table 2). The antioxidant activity (determined by the ABTS method) of the compound solutions (eugenol, EDChA, ETChA) tested prior to application to the skin changed as follows: 4.74 ± 0.01 mmol TE/ dm 3 (for eugenol) > 4.71 ± 0.01 mmol TE/dm 3 (for ETChA) > 4.70 ± 0.02 mmol TE/dm 3 (for EDChA) ( Table 3). The results of studies on the antioxidant activity of acceptor fluid solutions (collected after 24 h of permeation) showed that the eugenol solutions tested had the highest antioxidant activity (0.25 ± 0.03 mmol TE/dm 3 ). Lower antioxidant activity was observed for the ETChA and EDChA solutions (0.19 ± 0.03 and 0.20 ± 0.07 mmol of TE/dm 3 ) (Table 3).
Test results obtained by the Folin-Ciocalteu method showed that the polyphenol contents of the initial solutions applied to the skin changed as follows: 3.84 ± 0.05 mmol of gallic acid/dm 3 (for eugenol) > 3.35 ± 0.06 mmol of gallic acid/dm 3 (for ETChA) > 3.27 ± 0.10 mmol of gallic acid/dm 3 (for EDChA) ( Table 4). The results of tests for antioxidant activity of acceptor fluid solutions (collected after 24 h of permeation) showed that the tested eugenol solutions had the highest polyphenol content (0.27 ± 0.01 mmol gallic acid/dm 3 ). Lower concentrations of 0.25 ± 0.01 and 0.22 ± 0.01 mmol of gallic acid/dm 3 , respectively, were measured for solutions of ETChA and EDChA (Table 4).
The results of studies on the antioxidant activity of solutions obtained after skin extraction taken after the experiment showed that both eugenol and its ester derivatives were characterized by high antioxidant activity, as estimated by the three techniques mentioned: DPPH, ABTS, and Folin-Ciocalteu. The degree of DPPH free radical reduction for these compounds increased in the following order: EDChA (0.25 ± 0.01 mmol TE/ dm 3 ) > Eugenol (0.22 ± 0.02 mmol TE/dm 3 ) > ETChA (0.21 ± 0.01 mmol TE/dm 3 ) ( Table 2).
In contrast, the antioxidant activity (ABTS method) of the solutions obtained after skin extraction changed as follows: 1.14 ± 0.02 mmol TE/ dm 3 (for EDChA) > 1.03 ± 0.07 mmol TE/dm 3 (for ETChA) > 0.91 ± 0.02 mmol of TE/dm 3 (for eugenol) ( Table 3). The research results obtained by the Folin-Ciocalteu method showed that the values of antioxidant activity of solutions obtained after skin extraction (ETChA and EDChA) were higher (0.55 ± 0.01 and 0.58 ± 0.04 mmol of gallic acid/dm 3 ) than the values of antioxidant activity of eugenol (0.41 ± 0.03 mmol gallic acid/dm 3 ) (Table 4). Table 5 presents the results of studies on the penetration of active substances through pig skin and the amounts of extracted active ingredients accumulated in the skin. Figure 5 shows the results of studies on the permeation of active substances through pig skin during the 24-h experiment.
In our own research conducted in vitro, the penetration of eugenol and its new ester derivatives (EDChA, ETChA) through pig skin was assessed. For comparative purposes, tests were also carried out for pure acids (DChAA, TChAA). The experiment was carried out using a Franz diffusion chamber, in which the donor phase consisted of ethanol solutions of the compounds tested. The acceptor phase was PBS solution, because it corresponds to systemic conditions, is isotonic in nature, and allows conditions corresponding to the conditions prevailing in the deeper layers of the skin to be maintained (Alonso et al. 2014). Permeation of test substances through pig skin into the acceptor fluid increased in the following order: EDChA > ETChA > Eugenol > DChAA > TChAA. After conducting the experiment for 24 h, the highest average cumulative mass was observed in the case of EDChA (302.77 ± 1.90 µg). The mass was slightly lower in the case of ETChA (297.62 ± 24.97 µg) and for eugenol (272.89 ± 54.64 µg). In addition, the study showed that amount of ETChA penetration differed significantly from that of TChAA (210.54 ± 16.45 µg). The highest increase in the penetration rate of EDChA to the acceptor fluid (µg/cm 2 /h) was observed between 2 and 3 h, while for ETChA and eugenol, it was between 3 and 4 h (Fig. 5).
After the experiment was carried out, the skin was extracted in order to extract the tested active ingredients accumulated in it. The obtained test results showed that the concentration of tested substances in the analyzed extracts (µg/cm 2 skin) decreased in the following order: TChAA (799.41 ± 39.99 µg/ cm 2 skin) > DChAA (750.82 ± 44.62 µg/ cm 2 skin) > eugenol (566.93 ± 33.34 µg/cm 2 skin) > EDChA (555.09 ± 53.22 µg/cm 2 skin) > ETChA (539.14 ± 40.53 µg/cm 2 skin). Pure TChAA and DChAA acids were accumulated in the skin, as evidenced by the high concentrations of compounds found in the analyzed extracts: TChAA (799.41 ± 39.99 µg/cm 2 skin) and DChAA (750.82 ± 44.62 µg/cm 2 skin) ( Table 5). The factor significantly affecting the transport of active substances is the lipophilicity of the test compound (Yang et al. 2008;Srinivas et al. 2019;Ichihashi et al. 2003;Casagrande et al. 2007). The optimal log P coefficient (which is an indicator of the lipophilicity of the active substance) is in the range of 2 to 3 (Janus et al. 2020;Haq et al. 2018;Simon et al. 2016). This was also confirmed in our own research, which showed that both eugenol and its ester derivatives were characterized by good permeability through the skin (log P: Eugenol 2.20 ± 0.001, EDChA 2.65 ± 0.001, ETChA 2.75 ± 0.002, Table 1). Lipophilic compounds penetrate much more easily through the skin, because the skin consist mainly of lipid substances which, at the same time, limits the penetration of hydrophilic substances (log P: DChAA 0.95 ± 0.002, TChAA 1.51 ± 0.002, Table 1) commonly used in dermatology or cosmetology (Jaworska et al. 2011). The lower lipophilicity of the compound (log P < 2) is associated with its worse penetration the skin (Simon et al. 2016). This relationship was also confirmed in our own research; the average masses accumulated in the acceptor fluid after 24 h were 247.63 ± 16.45 (in the case of DChAA) and 210.54 ± 16.45 (in the case of TChAA), as shown in Table 5, while the average cumulative masses for these compounds at 0.5; 1; 2; 3; 4; 5; 8, and 24 h are shown in Fig. 5.
Discussion
The antioxidant activity of eugenol and EDChA depends on the concentration of antioxidant in the test sample. As it has been shown in our previous studiy (Makuch et al. 2019), the antioxidant activity of the sample increased as from 76% (for 0.25 µg/ml) to 88% RSA (for 5 µg/ml). The antioxidant activity of eugenol increases with an increase of this compound concentration in the tested sample due to a reduced electron density on the oxygen atom of the phenolic group (i.e. the -OH group associated with carbon of the aromatic ring). The hydrogen bonding energy is much lower, which makes it easier to give it to the DPPH radical (through the reaction of the radical and antioxidant molecule with the formation of the adduct).
Other studies have shown that the values of the parameter determining the concentration reducing 50% of free radicals (IC 50 ) for eugenol are inversely proportional to its antioxidant activity. The lower the IC 50 , the higher the antioxidant activity (Makuch et al. 2019).
The results of EDChA antioxidant activity presented in Table 2, showed that the antioxidant activity may be strongly influenced by the kinetic behavior of this compound. As our previous research has shown (Makuch et al. 2019), by increasing the concentration of EDChA in the tested sample, a decrease in antioxidant activity was observed: from 93% (at 0.25 µg/ml ester concentration) to 89% RSA (at 5 µg/ml ester concentration). The reason for under-activation is that the reaction time (10 min) between DPPH and EDChA is too short. As a result, this time prevents the end of the reaction between radical and antioxidant. This phenomenon is most often observed in the case of antioxidants (essential oils, compounds isolated from plant materials or plant extracts) characterized by a slow reaction with DPPH radical (Cenobio-Galindo et al. 2019;Fadda et al. 2014;Magalhaes et al. 2012;Ahmad et al. 2012).
Eugenol has a hydroxyl group (-OH) associated with an aromatic ring with acidic properties, which could lead to antioxidant activity. Its free radicals scavenging activity could lead to form phenolic radicals. These radicals are stable due to resonance caused charge transfer and are not able to detach hydrogen from lipid or protein molecules (and to decrease the oxidation).
Replacement of hydrogen atoms in the aliphatic chain EChA, EDChA and ETChA by heteroatoms (in this case, chlorine atoms) enhances the antioxidative properties. Eugenol esters containing chlorine atoms in the structure easily trap free radicals, giving up the H atom in the aliphatic chain. The reason is a change in the shape of the molecule, i.e. a change in length, direction, range and polarization of the bonds and a change in the symmetry of the particles. Introduction of chlorine atoms into the structure, causes polarization of bonds between carbon-chlorine atoms. The polarization of bonds between the carbon-chlorine atoms reduces the density of the electron cloud in the whole molecule and causes polarization of all close bonds present in the structure. As a result of this bond between the carbon-hydrogen atoms in EChA, EDChA and ETChA molecules, they change their length and polarity. In addition, the presence of chlorine atoms in the structure of these compounds changes the electro-neutrality of carbon atoms. Additionally, the presence of the methoxyl group (-OCH 3 ) in the eugenol molecule and the EChA, EDChA and ETChA molecules increases the antioxidant properties of these compounds (Rice-Evans et al. 1996).
We demonstrated that new eugenol derivatives (EDChA and ETChA) containing ester groups, penetrate more readily through biological membranes. They are characterised by higher partition coefficient compared to the parent output eugenol and acids (DChAA and TChAA), which can have a positive impact on enhance active substance transport through biological membranes. Eugenol is a terpene compound classified as an absorption promoter that is characterized by high antibacterial (Makuch et al. 2016;Pavithra 2014) as well as antioxidant activity (Hamed et al. 2012;Promod et al. 2010. Terpenes, which are a group of substances that are commonly considered safe from the point of view of dermal toxicity, are often used in preparations applied to the outer layer of the skin Ahad et al. 2016;Pavithra 2014).
The transport of the active substance the skin also depends on the molecular weight of the active substance itself. Overcoming the lipophilic barrier, which is the skin, is possible for non-polar-new esters of eugenol, which have molecular weights of < 600 Da (Malinowska et al. 2013;Tan et al. 2015;Thi and Hwang 2014). Besides better absorption of active substance by penetrating faster, the presented esters can provide endogenous action against free radicals, which is their superiority to the used in cosmetology acids (α-and β-hydroxy acids, TChAA), for which the skin is a barrier limiting their penetration. Data in the literature indicate that after a single application of trichloroacetic acid, complete epidermal necrolysis occurs, resulting in a decrease in capillary permeability. Therefore, after application of TChAA, no irritation or inflammation of the skin was observed (Sarkar 2012;Pathan and Setty 2009). In contrast, these symptoms occur after the application of commonly used α-and β-hydroxy acids (AHA and BHA). EDChA and ETChA are alternatives to AHA, BHA, and TChAA, which are active substances commonly used in problem skin care that have a tendency to cause imperfections (Karolak et al. 2017;Pathan and Setty 2009).
In addition, the good permeability of EDChA and ETChA through the skin and their proper accumulation in the skin (Table 5; Fig. 5) as well as their antioxidant capacity (Tables 2, 3 and 4) can limit also the exogenous effects of free radicals. Free radicals are highly reactive, toxic molecules due to the presence of one or more impaired electrons. Within tissue they damage DNA, proteins, lipids and carbohydrates (Dhale et al. 2007). The reactivity of new esters of eugenol by donating their electrons to the free radicals suggested use EDChA and ETChA as antioxidant.
In recent years, antioxidants have increasingly been used as active ingredients in cosmetic and pharmaceutical preparations, because they act as ROS blockers. Among the huge group of antioxidants, clove oil and eugenol (the main component of clove oil) can be distinguished as having confirmed antioxidant and antimicrobial effects. Although eugenol, as a biologically active substance, is already used in many cosmetic and pharmaceutical preparations the antioxidant effect of eugenol after crossing the skin barrier has not previously been studied. In addition, the use of new eugenol derivatives (EDChA, ETChA) as biologically active substances increases their penetration (as confirmed in our own research) of the skin and could decrease the toxic effect of exogenous and endogenous ROS. The obtained derivatives were characterized by high antioxidant activity, which was estimated after 24 h of conducting the experiment, which indicates long-term protection against ROS in the deeper layers of the skin. In the presented studies, the relationship between the lipophilicity of each tested active substance and its antioxidant capacity was estimated. The research presented in this publication thus provides new knowledge to this area of research (Li et al. 2011;Makuch et al. 2016;Makuch et al. 2015;Makuch and Kądziołka 2018;Makuch et al. 2017;Makuch and Wróblewska 2014;Pavithra 2014;Hamed et al. 2012).
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Domain: Agricultural And Food Sciences
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Drying kinetics of RDF : Experimental investigation and modeling
An experimental study was performed to determine the drying characteristics of an oversized fraction of RDF alternative fuel using a laboratory scale hot air dryer at a variety air temperatures and a constant air velocity. For this research the industrial RDF was derived from a Regional Municipal Waste Treatment Facility near the city of Kraków, Poland. The samples of RDF were prepared in two forms: ovesized (unmodified condition) and shreded in a two-drum crusher. In addition, the RDF was sorted into three groups of samples: paper, plastic, textiles. Each form of RDF and each group of samples were dried in hot air dryer at temperatures of 50, 70 i 90 °C and a constant air velocity of 1,5 [m·s]. The loss of the the samples mass were measured in a continues manner until the equilibrum moisture content was reached. The effective moisture diffusivity [m·s] and activation energies [kJ·mol] was amounted. The analysis of the course of moisture content change concludes that that the drying of the RDF alternative fuel occured mainly in the II period of the process during which the transport of water content was carried out by diffusion. And, to a lesser extent, with the surface heat transfer in II period. Based on the calculated data there was a model determined which presented the best possible matching of the course of moisture
Introduction
RDF alternative fuel is a combustible fraction of municipal or industrial waste obtained from the separation of the biodegradable fraction. It is typically produced in the Regional Waste Water Treatment Plant (RIPOK). RDF is a heterogeneous fuel whose main components are paper (including cardboard), plastic and textiles [1]. RDF can also be found in admixtures of inert components: glass, wood, organic parts and metals. Their presence is due to an imperfection of the municipal waste screening process. The mass fraction of individual fractions varies, depending on the installation, source of waste: Municipal Solid Waste (MSW), Commercial and Industrial Waste (CIW), Construction and Demolition Waste (CDW) and collection sites: urban and rural [2,3,4]. Typically, RDF is dominated by paper: 50-70%, plastic: 30-50%, textiles (<10%) and inert ingredients (<5%). An example of RDF composition according to the source of waste is presented in the Table 1.
The RDF calorific value varies between MJ·kg -1 [4]. RDF humidity varies, ranging between 5-23% [3,4]. This depends on the origin of the waste, the type of screening plant and the time of year for municipal waste collection [6,7]. The RDF fuel surplus fraction consists of particles greater than 5 cm [8]. It is generated by screening a mechanical waste stream of municipal waste on sieve screens (drum sieves). The particle size depends on the mesh size and typical sieve sizes are 5, 8, 10 cm [9].
RDF can be utilized thermally in combustion, pyrolysis and gasification. Most often it is a product intended for cement kilns, lime plants, waste incineration plants and power plants as well as heating plants [10]. RDF is also subjected to the process of pelleting or briquetting [11]. The moisture content parameter plays an essential role in the design and process optimisation of thermal ultilisation or compaction of the RDF fuel. The presence of moisture has a great impact on the fuel's calorific value and, consequently, on the possibilities of thermal processing. For example, for a cement kiln, humidity cannot exceed 15% [12]. On the other hand, RDF with low moisture content is difficult to handle during transportation within facilities due to dust and blockages on conveyor belts. Moisture also plays a key role in the agglomeration process. Water molecules are involved in the physical-chemical reactions which occur during bonding of fuel elements (adhesion, formation of solid bridges) [13]. However, the water molecules are uncompressible, which at the same time makes the compaction process quite difficult. Too high water content will result in a high relaxation coefficient [14], but too low will increase the energy efficency of the shredding process [15] and increase the risk of spontaneous combustion as well [16]. Determining the required humidity ought to be a compromise between the Thermal drying to reduce water content has been proved to be an effective method [17]. In many branches of industry, drying has a crucial role: food industry, agriculture, paper industry. There are many methods of drying available: contact, convection, microwave, radiation, dielectric and others [18]. Drying consists by removing moisture from the material through evaporating water, with the share of heat supplied to this process. The most common and simplest method is drying by convection using gas, usually warm air, as a drying medium. In this process, the transport of heat and mass from the interior of the material to its surface is carried out by diffusion, and further on into the surrounding atmosphere by convection. Drying also can be a part of the process, taking part in the preparation of the raw material for the compaction process of solid biofuels [19], and yet is a very energy consuming process.
Since RDF is a heterogeneous material composed of many different components, it contains different types of moisture. The paper and textiles would propably be the main water binding materials in alternative fuel [20]. The water contained there would be primarily capillary bounded, while in the plastics the moisture would be collected as a film on the surface. The RDF is a lightweight, porous and bulky material, so convective drying would have a more practical effect due to the ease of flow of the drying medium between the RDF elements. Knowing the drying kinetics has a key role in designing and optimization for the agglomeration or thermochemical processing of raw materials [21]. There are articles concerning drying of paper, paper sludge [i.e. 22,23,24], textiles [25] or food waste [26]. These research studies focused on drying kinetics analysis, drying curves analysis, the Effective moisture diffusivity (D eff ) and Activation energies (E a ) determinations and calculations the best equation for the drying procces under variable factors (i.e. temperature of drying, air velocity, initial moisture content of the sample). However very little is said in the literature concerning RDF drying. The purpose of this study is to observe the effect of various temperatures at convection drying on the drying kinetics of RDF and it's main fractions (plastic, textiles and paper) in separation.
Material and methods
RDF was collected from the RIPOK industrial plant located in Krakow, which was produced from municipal solid waste sorted out of the Krakow area. The analysed fraction was formed on drum sieve with a 10 cm mesh screen installed. Because of that the RDF is mainly composed of large particles (over 3 cm). There were five types of samples prepared for the experiment: -RDF0primary fine fraction gained directly from RIPOK -RDF1 -primary fraction, shredded in a two-drum crusher on the RDF pelletizing line.
In addition, three groups of raw materials were selected from RDF0: paper, plastic and textiles. There were samples of 12 g (± 5 g) prepared from all raw materials for drying. Samples were dried by convection in the laboratory drier Elkon KBC 65G. The measurement stand diagram is show in Fig. 2. The drying experiments were performed at 50, 70 i 90 °C air temperatures. The drying air velocity was at a constant 1.5 m·s -1 . All the experiments were replicated five times at each temperature value for each samle type. The weight loss was measured by Radwag AS-160. R2 analytical balance (d=0,01 mg). The measurement was recorded continuously of at 5 s interval and saved by the Radwag "Pomiar-Win" software each time. The temperature was measured with two NiCrNiAl thermocouples that were placed inside dryer. With a thermometer that Works in connection with the YC-747UD meter the temperature of the ambient environment-the inside of the dryer (T1) and the temperature of the sample (T2) was measured. The measurements were recorded continuously at 1 s intervals by Temp Monitor_S2 (ver. 1.0.16) software. The drying proces proceeded until the moisture content reached an equilibrum value (until there were no significant variations in the moisture lost). The mean drying time was 25 minutes. A Pol-Eko SLW-53 TOP dryer was used for the samples initial moisture content measurment according to the PN-EN 15414-3:2011 standard [28]. The dry matter calculations were done according to the PN-EN ISO 638:2008 standard [29].
The moisture content (U τ ) was calculated from the following equation: Where, m τ is the mass of the sample at any given time τ, [kg]; m db the mass of the dry basis of the sample, [kg]. The unit of the moisture content is(U τ ) kg water/kg dry basis.
The drying rate (dU/dt) [kg water/·kg d.b.·s -1 ] was obtained from the following equation [18]: The three common models were used to quantify drying kinetics of RDF0 and RDF1. The models are described with simplified equations respectively [18]: -Henderson-Pabis: -Lewis: -Page: Where, MR is the moisture ratio (dimensionless), U τ is the moisture content at Any given time τ [kg water/kg d.b.], U i is the initial moisture content [kg water/kg d.b.], U e is the equilibrium moisture content [kg water/kg d.b.], k is the drying rate constant [s -1 ]. N and a are the empirical constants.
Taking the natural log of both sides of the equations 3-5 is a way to determine the empirical constants. The form of the normalized equations of the moisture ratio versus time is: -Henderson-Pabis: -Lewis: -Page: The Effective moisture diffusivity (D eff ) [m 2 ·s -1 ] can be determined from the slope of the normalized plot of the unaccomplished moisture ratio, ln(MR) vs time, using the following equation [31]: (9) Where, L is the thickness of the sample (slab) of 0,0045m [m], k is the drying rate constant [s -1 ].
The Activation energies (E a ) [kJ·mol -1 ] was obtained from the reliance of the effective moisture diffusivity D eff on the temperature T. The reliance can be described by an Arrhenius type equasion [31]: (10) Where the D eff is effective moisture diffusivity [m 2 ·s -1 ]; D 0 is the pre-exponential factor of the Arrhenius equation [m 2 ·s -1 ], R is the universal gas constant (8.3145 kJ·mol -1 ·K -1 ) and T is the absolute air temperature [K]. Taking natural logarithm of both sides of Eq. (5) the result can be written as: (11) The activation energy (E a ) is determined by plotting the natural logarithm of D eff (lnD eff ) versus reciprocal of the absolute temperature T [K].
The experimental drying data was tested to find the most suitable model among the above mentioned (3)(4)(5). The different constants in the considered models were determined using a linear regression procedure. The adjusted coeficient of determination (R 2 ), reduced chisquared (χ 2 ) and root mean square error (RMSE) were used to inspect the goodness of fit. [18] Where MR P is the predicted moisture ratio at any time, MR E is the experimental moisture ratio at any time, ̅̅̅̅̅ is the average experimental moisture ratio, N is the number of observations, n is the number of constants in the drying model.
The calculations and statistical data analysis were performed using R Core Team (2016) software (R Foundation for Statistical Computing, Vienna, Austria. URL [URL]/) with the packages: ggpolt, dplyr, stats.
Results and discussion
The initial moisture content of all samples were determined using PN-EN 15414-3:2011 standard [29]. As expected the highest average value of moisture content was obtained for paper (~ 41%) and textiles (~25 %). The plastics, that were the main component of the RDF had a moisture content of approximately 10%. There was no significant differnence in the moisture content values between RDF0 and the RDF1 samples. It is clear that the mechanical comminution at the pellet production line had little impact on moisture loss in the material. (Table 3). The shapes of the drying curves versus time for the samples resembled the exponential function (U τ ). The steeper the curve was, the quicker the moisture loss took place. It is cleary evident that these curves were influenced by various temperatures (Fig. 3, 4). The deviations were related to the individual characters of particular samples which could be also noticed in the shapes of the moisture ratio curves (Fig. 3.bottom plots). There was no I period of drying process in the paper and textiles. In these samples the drying process began in the second period in which the diffusion mechanism is predominant, and which is mostly common for porous matter. The drying rate was going slow at the temperature of 50 °C in the paper, however at the temperature of 70 and 90 °C the rate of changes were faster (Fig. 3A, the bottom plot). The maximum drying rate of the paper was 0.06 x10 -2 kg water/kg d.b. at 90 °C. Considering the textiles, the drying curves are also noticeably influenced by the various temperatures. With the decreasement of water content, the drying curves are less steep. (Fig. 3B). The paper and textiles were dryed completely at the U = 0 at the temperature of 90 °C after 20 minutes (1250 s). With the decreasment of the temperature the final water content in the both of samples was equal to equilibrium moisture content. The maximum drying rate of the textiles was 0,088 x10 -2 kg water/kg d.b. at 90 °C.
Different kind of curve shapes can be observed in plastisc (Fig. 3C). With the decreasement of water content, the drying curves are less steep, and more flat and paralel to the x axis. There are two periods of drying process in plastic, where I period is mild and long, and the II one is dynamic and short (especially at the temperature of 90 °C). This is characteristic for porouscapillary and porous materials. The maximum drying rate in plastic is 0,085 x10 -2 kg water/kg d.b. at 90 °C. The time of drying of 20-25 minutes is too short to remove the water completely from the samples above at 50 °C, in particular for paper and textiles. The plastic and paper exhibit characteristics of hygroscopic material at the lower temperature values, however at 90 °C the samples exhibit the characteristics close to nonhygroscopic material [32].
Based on the shapes of the drying RDF0 and RDF1curves it can be stated that the samples resemble capillary-porous and porous materials. The shape of the curves exhibit the characteristic of paper and textiles drying curves, although the total percentege of them didn't exceed 15 %. However the drying rate was twice more dynamic in RDF0 and RDF1 than in paper and textiles. The first period of drying, related to the constant drying rate occured in both of RDF samples, but it lasted a short time at the temperature 50 and 70 °C. At the 90 °C the first drying period occured slightly in RDF1, but hardy in RDF1 (Fig. 4bottom plots of A and B). The first drying period was specific to the plastics olny (Fig. 3C), which is the main component of the RDF (ok. 70 %). The drying rate of RDF was faster in the shredded fraction (RDF1), where the area of of evaporation was larger due to reduction of particie size. At the 90 °C both of RDF samples were dried completely untill the moisture content of U=0 (Fig 4, bottom plots of A and B). At the lower temperatures the RDF resembled more party-hygroscopic material [9], it might contain the areas of a different moisture component. At lower temperatures RDF was dried to an eqiulibrum moisture content, which was 0.110 kg water/kg d.b. at T=50 °C and 0.001 kg water/kg d.b. at T=70 °C for RDF0, and 0.041 kg water/kg d.b. T=50 °C i 0.010 kg water/kg d.b. T=70 °C for RDF1 respectively. Based on the results of the experiment the three methematical drying models were fit to the experimental data. The calculations are reveled in Table 5 and Table 6. All of the models provided are a very good fit to the experimental data of drying RDF samples at various temperatures. Of all the models tested, the Page model offered the highest value for R 2 . However, the Henderson-Pabis and Levis models had a great fit at the temperatures of 50 i 70 °C as well. At the temperatures of 50-70 °C the value of R 2 parameter with the Levis model reached above 0,98 for RDF0 i RDF1 samples (Table 5). The χ 2 test values reflect to the goodness of model fit and are low (less than 0.02), but quite varied depending on samples types and the temperature of process in all three models ( Table 6). The lowest χ 2 test values were obtained from the Page model. The highest values of the χ 2 test were related to the lowest values of R 2 parameter and concerned the Henderson-Pabis and Levis models for modeling of drying RDF0 and RDF1 at 90 °C.
The highest values of %E parameter were obtained at the temperature 90 °C, where they reached even 62% ( Table 6). The drying ratio curve of RDF1 and RDF0 at 90 °C was more linear (Fig. 4 A,B) and it's deviation from values of lower temperatures propably was caused by describing it with exponential equations. Compared to RDF0, the values of %E were lower in the RDF1 sample. Maybe from the comminuted sample, which RDF1 was, more homogeneous samples were aqcuired. The raise in effective moisture diffusivity D eff was related to increasement of the temperature and decreasement of the paticle size of the samples. At 50 °C in RDF1 was almost two times higher than in RDF0 and was about 10.0707×10 -7 [m 2 ·s -1 ] ( Table 7). The activation energy (E a ) for diffusion calculated from the slopes of normalized equation of D eff (10) was found to be 52.07 kJ·mol -1 for RDF0 and 28.26 kJ·mol -1 for RDF1. Comminution of the RDF resulted in a decrease in activation energy.
Conclusions
1) The paper and textiles had the highest moisture content in RDF composition of 41% and 22% respectively. Moisture content of the plastic did nor exceed 10 %. The comminution of RDF caused insignificant difference in the moisture content between RDF0 and it's shredded form of RDF1.
2) Based on the analysis of the drying kinetics of the RDF0 and RDF1 it could be stated that RDF has more features of porous material than porous-capillary. The first period of drying occured only in plastic and slightly in RDF0 and RDF1 at lower drying temperatures of 50 and 70 °C. The drying process begun with second period of drying in paper and textiles. The moisture and mass movement was mainly by diffusion and less by capipillary for ces.
3) Of all of the three drying kinetics models of RDF tested, the Levis model had the best fit to the experimental data. The obtained values for R 2 was greater than 0.98 and χ 2 test values were in the range of 0.3 -2,4 × 10 -3 . None of the mathematical models were able to satisfactory describe the performance of drying RDF at the temperature of 90 °C.
4) The Effective moisture diffusivity (D eff ) values were affected by increasing temperature. The highest values of 33.6521 ×10 -7 m 2 ·s -1 were obtained at 90 °C, and the lowest of 4.0457 ×10 -7 m 2 ·s -1 were obtained at 50 °C for RDF0. The Activation energy (E a ) varied from 28.26 kJ·mol -1 to 52.07 kJ·mol -1 for RDF1 and RDF0 respectively. The lower energy is needed to remove water from comminuted RDF. 5) Drying process of the RDF using hot air at the temperature of 90 RDF °C allows for removal of the moisture content completely, until U = 0. At lower temperatures of 50 °C and 70 °C the RDF could be dried untill the equillibrium moisture content.
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Domain: Agricultural And Food Sciences
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Effects of β-glucan with vitamin E supplementation on the growth performance, blood profiles, immune response, pork quality, pork flavor, and economic benefit in growing and finishing pigs
Objective This study was conducted to evaluate the effects of β-glucan with vitamin E supplementation on the growth performance, blood profiles, immune response, pork quality, pork flavor, and economic benefit in growing and finishing pigs. Methods A total of 140 growing pigs ([Yorkshire×Landrace]×Duroc) were assigned to five treatments considering sex and initial body weight (BW) in 4 replications with 7 pigs per pen in a randomized complete block design. The experimental diets included a corn-soybean meal-based basal diet with or without 0.05% or 0.1% β-glucan and 0.02% vitamin E. The pigs were fed the diets for 12 weeks (phase I, 0 to 3; phase II, 3 to 6; phase III, 6 to 9; phase IV, 9 to 12). The BW and feed intake were measured at the end of each phase. Blood samples were collected at the end of each phase. Four pigs from each treatment were selected and slaughtered for meat quality. Economic benefit was calculated considering the total feed intake and feed price. Pork flavor was analyzed through inosine monophosphate analysis. Results The average daily gain and feed efficiency were improved compared to the control when β-glucan or vitamin E was added. Supplementing 0.05% β-glucan significantly increased the lymphocyte concentration compared to the addition of 0.1% β-glucan and the content of vitamin E in the blood increased when 0.02% vitamin E was added. The treatment with 0.1% β-glucan and 0.02% vitamin E showed the most economic effect because it had the shortest days to market weight and the lowest total feed cost. The addition of β-glucan or vitamin E had a positive role in improving the flavor of pork when considering that the content of inosine monophosphate was increased. However, carcass traits and meat quality were not affected by β-glucan or vitamin E. Conclusion The addition of 0.1% β-glucan with 0.02% vitamin E in growing and finishing pig diets showed great growth performance and economic effects by supplying vitamin E efficiently and by improving the health condition of pigs due to β-glucan.
INTRODUCTION
Antibiotics have been widely used to improve growth performance and prevent disease in livestock environments for a long time. However, the use of antibiotics is harmful to animal and human and causes serious problems, such as bacterial resistance to antibiotics, presence of drug residues in pork products, and environmental pollution [1]. Therefore, the European Union and Korea banned the use of antibiotics as feed additives for growth promotion in 2006 and 2011, respectively. For this reason, research on various antibiotic substitutes, such as plant extracts, probiotics, and β-glucan, has been actively conducted [2]. β-Glucan is a type of functional polysaccharide and is a component contained in mushrooms, grain seeds (oat, rye, barley, etc.), and the cell walls of yeast. It has various biological functions, such as improving immune function, preventing disease, and controlling blood glucose [3]. β-Glucan can stimulate a series of pathways that strengthen the immune system and enhance both innate and acquired immunity [4]. An active immune system can help animals fight diseasecausing organisms and maintain clinical infection control and growth processes. In addition, β-glucan has beneficial effects on improving growth performance, nutrient digestibility, and carcass traits when it is added to growing and finishing pig feed [5].
Vitamin E, which acts as an antioxidant at the cell membrane level, has a structural function and performs several functions related to reproduction [6]. Adding a high vitamin E content in the growing and finishing pig feed increases the immune response [7]. Vitamin E can prevent oxidized phospholipids in cell membranes and fats in feed, including unsaturated fatty acids [8]. In addition, vitamin E mainly maintains cells and helps to minimize the damage caused by oxidative reactions in cells [9].
There have been many previous studies evaluating the effects of β-glucan with vitamin E on growing and finishing pigs, but there is insufficient evidence to verify the synergistic effect of β-glucan with vitamin E on growing and finishing pigs. Therefore, this study was conducted to evaluate the effects of β-glucan with vitamin E on the growth performance, blood profiles, immune response, pork quality, pork flavor, and economic benefit in growing and finishing pigs.
MATERIALS AND METHODS
All experimental procedures involving animals were conducted in accordance with the Animal Experimental Guidelines provided by the Seoul National University Institutional Animal Care and Use Committee (SNUIACUC; SNU-200209-2)
Experimental animals and management
A total of 140 growing pigs ([Yorkshire×Landrace]×Duroc) with an initial body weight (BW) of 34.43±2.362 kg were assigned to one of five treatments considering sex and initial BW in four replicates with seven pigs per pen in a randomized complete block design. Pigs were randomly allotted to their respective treatments by the experimental animal allotment program (EAAP) [10]. Pigs were housed in an environmentally controlled facility. The pens were fully concrete floored (2.60×2.84 m 2 ) and equipped with a feeder and water nipple. The experimental period was 12 weeks (phase I, 0 to 3; phase II, 3 to 6; phase III, 6 to 9; phase IV, 9 to 12).
Experimental design and diet
Dietary treatments included i) CON, corn-soybean meal (SBM)-based diet; ii) LB, corn-SBM-based diet + 0.05% β-glucan; iii) LBE, corn-SBM-based diet + 0.05% β-glucan + 0.02% vitamin E; iv) HB, corn-SBM-based diet + 0.1% β-glucan; and v) HBE, corn-SBM-based diet + 0.1% β-glucan + 0.02% vitamin E. A corn-SBM-based diet was used as feed in this experiment, and all nutrients in the experimental diet except crude protein (CP) met or exceeded the nutrient requirements of the National Research Council (NRC) [11] for growing and finishing pigs. The CP was set to 6.25 times more than the standard total nitrogen in the requirement of NRC [12]. In the present study, β-glucan and vitamin E products were provided by E&T Company (E&T CO., Ltd, Daejeon, Korea). β-Glucan consisted of (1,3)-(1,6)-β-Dglucan and mannan, and vitamin E was in the form of vitamin E-acetate. In the case of vitamin E, 35 IU/kg was present in the vitamin premix, and 110 IU/kg of vitamin E was additionally supplemented to the LBE and HBE treatments. All nutrient contents in the feed were formulated equally, and the formula and chemical composition of the experimental diet are presented in Table 1 to 4.
Growth performance
Body weight and feed intake were measured at the end of each phase to calculate the average daily gain (ADG), average daily feed intake (ADFI), and gain:feed ratio (G:F ratio). In addition, feed given to all growing and finishing pigs was recorded each day, and feed waste in the feeder was recorded at the end of each phase.
pH and pork color
At the end of the experiment, four finishing pigs from each treatment were selected and slaughtered for pork quality analysis. Pork samples were collected from the nearby 10th rib on the right side of the carcass. Because of the chilling procedure, 30 min after slaughter was regarded as the initial time. The pH and pork color were measured at 0, 3, 6, 12, and 24 h, respectively. The pH was measured using a pH meter (Model 720; Thermo, Orion, Waltham, MA, USA) and pork color was determined by CIE color L*, a*, and b* values using a CM-M6 (Minolta Camera Co., Tokyo, Japan).
Carcass traits and physiochemical properties
The pig carcass grading was judged using the data determined to be grade 5 according to the criterion for grades for pork carcass (scalding) after slaughter at the slaughterhouse. Only results judged to be grades 1+, 1, 2, and 3 were used, and outside grades (grade E) were not included in the grade. The carcass weight was measured by the hot carcass weight of the half carcass. For the back fat thickness, the thickness of the fat layer was measured by cutting the last rib of the carcass, which was precooled to 5 degrees or less at a right angle. Water holding capacity (WHC) was measured by the centrifuge method [13]. Longissimus muscles were ground and sampled in filter tubes, heated in a water bath at 80°C for 20 min and centrifuged for 10 min at 2,000 rpm and 4°C (Eppendorf centrifuge 5810R, Germany). After that, to calculate the cooking loss, longissimus muscles were packed with polyethylene bags, heated in a water bath until the core temperature reached 70°C and weighed before and after cooking. After heating, the samples were cored (0.5 inch diameter) parallel to muscle fiber and the cores were used to measure the shear force using a Warner-Bratzler meat shearing machine (Salter 235; GR, USA). The shear force, cooking loss and WHC of pork were analyzed by animal origin food science, Seoul National University.
Pork flavor
For analysis of inosine monophosphate (IMP), which is an indicator to infer the pork flavor, the samples were thawed and centrifuged at 10,000 rpm for 5 min at 4°C (Eppendorf centrifuge 5417R), and the supernatants were transferred to cold HPLC vials and placed in a thermostatted autosampler (1°C to 2°C). Analysis of IMP was performed by high-performance liquid chromatography (HPLC) (Hewlett-Packard HPLC system series 1100; Waldbronn, Germany) using UV detection (210 nm).
Economic benefit
As the experimental pigs were reared in the same environmental conditions, economic efficiency was calculated using only the feed cost without considering other factors. The total feed cost and feed cost (won) per body weight gain (kg) were calculated using the amount of the total feed intake and the feed price. The days to reach market weight (115 kg) were estimated from the BW at the end of the feeding trial and ADG of 10 to 11 weeks.
Statistical analysis
All obtained data were first processed by Excel 2010, and then analyzed by one-way analysis of variance using Statistical Analysis System 9.4 TS1M7 (SAS Inst. Inc., Cary, NC, USA). Each pen was used as an experimental unit for growth performance and economic benefit, while individual pigs were used as experimental units for blood profiles, immune response, and pork quality. Orthogonal polynomial contrasts were used to determine the effects of diet (β-glucan and vitamin E against the control), β-glucan, vitamin E, and the interaction between β -glucan and vitamin E. Data are presented as the means and their pooled standard errors. The differences were considered statistically significant when p<0.05, while 0.05≤p<0.10 was considered to indicate a trend in the data.
Growth performance
The effects of β-glucan with vitamin E supplementation in the growing and finishing pig diets on growth performance are presented in Table 5. As a result of the experiment, ADG was significantly higher in the early finishing period (Diet, p<0.01) and showed a higher trend in the total finishing period (Diet, p = 0.06) in the treatments in which β-glucan or vitamin E was added compared to the control. A significant difference in the late finishing period (BG×VE, p<0.05) was found in ADFI by the interaction between β-glucan and vitamin E. The G:F ratio was significantly higher in the early finishing period (Diet, p<0.05) and showed a higher trend in the total finishing period (Diet, p = 0.05) when β-glucan or vitamin E was added compared to the control. The treatments supplemented with 0.02% vitamin E showed a lower trend in the early growing period (VE, p = 0.05) but a higher trend in the early finishing period (VE, p = 0.07) compared to the treatments without additional vitamin E. In addition, a significant difference in the late finishing period (BG×VE, p<0.05) and a trend in the total finishing period (BG×VE, p = 0.09) were observed in the G:F ratio by the interaction between β-glucan and vitamin E. In a previous study by Tran et al [14], supplementation with 0.2% β-glucan increased ADG significantly in the growing, finishing, and growing-finishing periods compared to the control when 0.2% β-glucan or 0.4% vitamin E was added to growing and finishing pig feed (p<0.05). In addition, the feed conversion ratio was significantly lower in the treatment where 0.2% β-glucan was added compared to the control (p<0.05). Cueno et al [15] studied the effects on growth performance and carcass traits when β-glucan was added to the feed from weaning pigs to growing and finishing pigs. Weaning pigs were assigned to one of four treatments considering sex and initial BW in a 2×2 factorial design with two levels of carbadox supplementation (0%, 0.25%) and two levels of a product containing β-glucan (0%, 0.2%). As a result, the final body weight tended to be higher in the treatments to which 0.2% β-glucan was added (BG, p = 0.09). According to Luo et al [5], 0.01% β-glucan significantly increased ADG and improved the G:F ratio in 50 to 75 kg and 25 to 110 kg sections (p<0.05) when β-glucan was added by level (0.005%, 0.01%, 0.02%) to the growing and finishing pig feed. In addition, supplementation with 0.01% β-glucan significantly increased the ADG and G:F ratio in the 75 to 110 kg section compared to the control (p<0.05). Luo et al [5] explained that this was because the digestibility of dry matter, total energy, and CP significantly increased with the addition of 0.01% β-glucan, but the exact mechanism for the improvement in growth performance of growing and finishing pigs was not known [16]. However, β-glucan could have a positive effect on growth performance as a result of improving the intestinal microflora of pigs and promoting the absorption of nutrients in the intestine through improved immunity when β-glucan, an immune enhancer, was added to the feed [16]. There was no significant difference in the growth performance of growing and finishing pigs when vitamin E was added to the growing and finishing pig feed [17,18]. However, Hasty et al [19] reported that the ADFI of finishing pigs increased linearly when β-glucan was added by level (0.005%, 0.01%, 0.02%) to the growing and finishing pig feed. Considering previous studies, it is considered that ADG and feed efficiency of the treatment with β-glucan or vitamin E were higher than those of the control because the immunity and health status of the growing and finishing pigs improved.
Consequently, the addition of β-glucan or vitamin E to the growing and finishing pig feed had a positive effect on the growth performance compared to the control.
Blood profiles and immune response
The effects of β-glucan with vitamin E supplementation in the growing and finishing pig diet on blood profiles and immune response are presented in Table 6. The concentration of vitamin E in the blood was significantly higher in the LBE and HBE treatments supplemented with 0.02% vitamin E (VE, p<0.01) at the 3rd and 12th weeks and showed higher trends at the 6th and 9th weeks (VE, p = 0.07; 0.09). In addition, the concentration of vitamin E in the blood was significantly higher in the treatment where β-glucan and vitamin E were added at the 3rd and 9th weeks compared to the control (Diet, p<0.05), and showed a higher trend at the 6th week (Diet, p = 0.07). In addition, the TNF-α concentration showed a lower trend in the treatments to which β-glucan or vitamin E was added compared to the control at week 9 (Diet, p = 0.07). Supplementation with 0.05% β-glucan was significantly higher than the treatment with 0.1% β-glucan at 9 and 12 weeks in lymphocyte concentration (Diet, p<0.01). There was no significant difference between treatments in selenium and IL-6 concentrations.
In the present experiment, the lymphocyte concentration was increased when 0.05% β-glucan was added to the feed of growing and finishing pigs. Lymphocytes are part of the adaptive immune system, comprising 20% to 40% of the white blood cell count [20]. Hahn et al [21] conducted an experiment by dividing treatments into 4 groups (control, 0.02% β-glucan, antibiotics, and 0.02% β-glucan + antibiotics) to investigate the effect of β-glucan on immunity in weaning pigs. As a result, a subset of the pig lymphocyte population, major histocompatibility complex-II (week 4), CD-4, and CD-8 (week 8) were found to be higher in the diet supplemented with β-glucan compared to weaning pigs fed other diets. According to Kim et al [22], there was no significant difference between treatments on Day 0 before Escherichia coli inoculation when β-glucan was added at each level (0.0054%, 0.0108%) in weaning pig feed. However, the ratio of CD4+ T cells was significantly increased in the treatment where 0.0054% β-glucan was added after 2 and 5 days of E. coli inoculation compared to the control. On the other hand, in the experiments of Lee et al [23] and Mao et al [24], there was no significant difference in lymphocytes even when β-glucan was added to the weaning pig feed. Regarding the different effects of β-glucan addition on lymphocytes, Bohn and Bemiller [25] suggested that it may be due to differences in molecular weight, branching degrees, morphology, and intermolecular linkages that can affect the bioactive activity of β-glucan. In the present experiment, adding 0.02% vitamin E to growing and finishing pig diets increased the concentration of vitamin E in the blood. In particular, these results are important for growing and finishing pigs. The reason is that the main cause of pork quality deterioration is lipid oxidation, which also increases the occurrence of oxidative rancidity and unpleasant odor. These changes eventually shorten the shelf life of pork. Therefore, antioxidants such as vitamin E are often used to reduce the oxidation of pork and improve shelf life and quality. The results of the present experiment suggest that vitamin E was additionally well delivered to growing and finishing pigs, and it can be expected to have a positive effect on the oxidation and quality of pork in finishing pigs in the future.
pH of pork
The effects of β-glucan with vitamin E supplementation in the growing and finishing pig diets on the pH of pork are presented in Table 7. As a result, the pH of pork was significantly higher in the LBE and HBE treatments with the addition of 0.02% vitamin E than in the treatments without vitamin E treatment 3 hours after slaughter (VE, p<0.05). In addition, treatments with β-glucan and vitamin E were significantly lower than the control (Diet, p<0.01). The treatment with β-glucan and vitamin E was significantly higher than the control 24 hours after slaughter (Diet, p<0.05). In addition, there was a significant difference in the pH of pork 24 hours after slaughter due to the interaction of β-glucan and vitamin E (BG×VE, p = 0.09).
The change in the pH of pork after slaughter is an important factor in determining the quality of pork and affects the freshness, WHC, softness, color, and storage of the pork [26]. Additionally, Park et al [27] reported that the lower the postmortem pH is, the higher the protein content. Additionally, as the pH increased, cooking loss and drip loss decreased, and the WHC increased. The initial pH and final pH after slaughter are used as standards in judging the quality of pork. The initial pH is the predicted value of pale, soft, exudative (PSE) meat, and the final pH is the predicted value of dry, firm, dark (DFD) meat. When blood supply to the muscle is stopped after death, lactic acid production increases due to the anaerobic glycolysis of glycogen stored in the muscle, and the pH of the muscle decreases. This decrease in pH is affected by the handling conditions before and after slaughter, the genetic capacity of the individual, and the rate of anaerobic glycolysis.
The sudden decrease in the pH of pork promotes the outflow of the juice by modifying the protein structure of the muscle, and the outflow of the juice on the surface scatters light to make the pork look pale, resulting in the generation of PSE meat.
According to Luo et al [5], the pH of pork was significantly higher, and the drip loss could be reduced in the treatment with 0.01% β-glucan than those in the control 45 minutes after slaughter when β-glucan was added by level (0.005%, 0.01%, 0.02%) in the feed for growing and finishing pigs. According to the experiment of He et al [28], the pH of pork was significantly the highest and the drip loss was the lowest 45 minutes after slaughter with a reduced lactic acid content and glycolytic potential in the treatments supplemented with 0.02% β-glucan when β-glucan was added by level (0%, 0.005%, 0.01%, 0.02%, 0.04%) in the feed for growing and finishing pigs. This means that the possibility for pork to develop PSE is low. Additionally, no significant difference in the pH of pork was found when β-glucan was added by level in the feed for growing and finishing pigs [29]. Moreover, no significant difference in the pH of pork was observed between the treatments when vitamin E was supplemented [17][18][19]30]. In the present experiment, since the pH was not out of the normal range (pH 5.3 to 6.8), there was no negative effect on pork even though it was affected by β-glucan and vitamin E.
In summary, the addition of β-glucan and vitamin E to the feed of growing and finishing pigs does not negatively affect the pH of pigs after slaughter.
Color of pork
The effects of β-glucan with vitamin E supplementation in the growing and finishing pig diets on the color of pork are presented in Table 8. As a result of the experiment, there was no significant difference in the color of pork between the treatments.
The first thing consumers see when purchasing pork at a store is the color of the meat. Because of these characteristics, the color of the meat has the greatest influence on consumers' understanding of the quality of pork and making a purchase decision. The color of pork is an important indicator for evaluating its muscular appearance. It is influenced by several factors, including the rate of postmortem glycolysis, intramuscular fat, pigment level and the oxidation state of the pigment [31]. According to a study by Luo et al [5], treatment with 0.01% β-glucan 45 minutes after slaughter showed significantly higher redness compared to the control (p<0.05) when β-glucan was added by level (0.005%, 0.01%, 0.02%) in the feed for growing and finishing pigs. In addition, the yellowness 45 minutes after slaughter was significantly lower than that of the control (p<0.05) in all the treatments where β-glucan was added. According to an experiment by He et al [28], when β-glucan was added by level (0%, 0.005%, 0.01%, 0.02%, 0.04%) in the feed for finishing pigs, the redness significantly increased (linear, p<0.05), and the whiteness significantly decreased 45 minutes after slaughter (linear, p<0.05). When 0.01% [17], 10 and 210 IU/kg [18], and 0.04% [30] vitamin E were added to growing and finishing pig feed, respectively, there was no significant difference in the color of pork between the treatments.
Bendall and Wismer-pederson [32] reported that an increase in yellowness and a decrease in the redness of pork were the result of a decrease in the freshness of the pork. Since there is no negative effect on the redness and yellowness of the pork when supplemented with β-glucan and vitamin E, it does not affect the freshness of the pork. In addition, Joo et al [33] said that if the L value is 58 or more when 24 hours have elapsed after slaughter, it is PSE pork. However, since all treatments showed an ideal value lower than what Joo et al [33] suggested, it was determined that there was no negative effect on pork in the present experiment.
As a result, the addition of β-glucan and vitamin E to the growing and finishing pig feed does not have a negative effect on the color of pork.
Carcass traits and physiochemical properties
The effects of β-glucan with vitamin E supplementation in the growing and finishing pig diets on carcass traits and physiochemical properties are presented in Table 9. As a result, there was no significant difference between treatments in carcass traits including carcass weight, carcass yield, grade, and back fat thickness, or in physicochemical properties including cooking loss, shear force, and WHC.
There are standards for pork grading. Carcass weight and back fat thickness are the criteria for the first grade, and appearance, meat quality, and defective items are the secondary grade. In particular, the most important items for grading are carcass weight and back fat thickness, which are the firstgrade criteria. Kim and In [34] analyzed the characteristics of carcass traits by classifying them into 5 levels (less than 69 kg; 70 to 80 kg; 81 to 90 kg; 91 to 96 kg; 97 kg or more) according to carcass weight. As a result, back fat thickness increased significantly with increasing carcass weight (p<0.05). In addition, the thickness of back fat was classified into 6 levels Cooking loss, which is generally known to have an inverse correlation with WHC, is an indirect indicator of WHC. Shear force is a mechanical measure of the toughness of meat and is known to be highly related to WHC [35]. WHC is a measure of the moisture in meat according to internal and external environmental changes and is determined by the microstructure of meat or the change in moisture content during shredding. Additionally, it is known to be closely related to changes in the pH of meat. WHC is an important factor in the quality of pork. As the WHC increases, the quality of pork improves, but when the WHC decreases, the shear force gets higher.
According to a study by Luo et al [5], there were no significant differences in carcass weight, back fat, and carcass yield among treatments when β-glucan was added by level (0.005%, 0.01%, 0.02%) in the feed for growing and finishing pigs. There were no significant differences among the treatments in the cooking loss and shear force. The drip loss was rapidly reduced in the treatment where 0.01% β-glucan was added (p<0.05), which meant that the WHC of the muscles could be improved. Sampath et al [29] reported no significant differences in cooking loss and WHC when β-glucan extracted from Saccharomyces cerevisiae was added by level (0%, 0.05%, 0.1%) to the feed for growing and finishing pigs. According to the experiment by He et al [28], there were no significant differences in carcass yield and average back fat thickness when β-glucan was added by level (0%, 0.005%, 0.01%, 0.02%, 0.04%) in the feed for finishing pigs. When 0.02% β-glucan was added to the treatment, the cooking loss was significantly decreased (linear, p<0.05), but there was no significant difference in shear force. According to Li et al [30], when vitamin E (0%, 0.04%) and ferulic acid (0%, 0.01%) were added to the feed for growing and finishing pigs, there were no significant differences in back fat thickness, lean percentage, and shear force by vitamin E. Cannon et al [17] reported that there were no significant differences in carcass yield, back fat thickness, drip loss and cooking loss among treatments when 0.01% vitamin E was added to feed for growing and finishing pigs. Wang et al [18] conducted an experiment to add DDGS (0%, 15%, 30%) and vitamin E (10 and 210 IU/kg) to feed for growing and finishing pigs, but no significant differences were observed in carcass weight, carcass yield, and back fat thickness. In addition, shear force and drip loss were significantly reduced when 210 IU/kg vitamin E was added (p<0.05).
Therefore, the addition of β-glucan and vitamin E to the feed for growing and finishing pigs did not have any effect on carcass characteristics or physicochemical properties.
Pork flavor
The effects of β-glucan with vitamin E supplementation in the growing and finishing pig diets on pork flavor are presented in Table 10. As a result of the experiment, the treatments with β-glucan and vitamin E had a significantly higher content of IMP than the control (Diet, p<0.05). Additionally, there was a trend in the IMP content (BG×VE, p<0.05) due to the interaction between β-glucan and vitamin E.
IMP is an important indicator to infer the flavor of pork and is particularly related to umami. According to a previous study, supplementing 0.005% and 0.01% β-glucan increased the IMP content in pork when β-glucan was added by level (0.005%, 0.01%. 0.02%) to the growing and finishing pig feed [5]. Usually, after slaughter, the oxygen supply to the muscle tissue is stopped, and the energy supplied by phosphocreatine and glycolysis is used for adenosine triphosphate (ATP) synthesis [36]. As phosphocreatine and glycolysis decrease, ATP synthesis stops and begins to be degraded, which was thought to increase the contents of IMP in the present
experiment.
As a consequence, the addition of β-glucan with vitamin E in growing and finishing pig feed had a positive role in improving the flavor of pork when considering that the content of IMP was increased.
Economic benefit
The effects of β-glucan with vitamin E supplementation in the growing and finishing pig diet on economic benefit are presented in Table 11. In the case of feed cost per weight gain, LBE and HBE treatments with the addition of 0.02% vitamin E showed a high trend in the early growing phase (VE; p = 0.06). Supplementing β-glucan or vitamin E showed significantly lower feed cost per weight gain compared to the control in the early finishing phase (Diet, p<0.05). The treatments supplemented with β-glucan or vitamin E showed significantly lower total feed cost compared to the control in the late finishing phase (Diet, p<0.05). No significant difference was found in days to market weight. However, the treatment HBE with 0.1% β-glucan and 0.02% vitamin E showed the shortest days to market weight among treatments.
Tran et al [14] conducted an experiment on the effect on economic benefit when 0.2% β-glucan and 0.4% vitamin E were added to the growing and finishing feed. As a result, the treatment with 0.2% β-glucan had a higher feed price compared to the control. However, the treatment supplemented with β-glucan showed a better effect of 118.98% based on 100% of the control due to the high ADG and low cost of veterinary medicines.
Consequently, since the HBE treatment with 0.1% β-glucan and 0.02% vitamin E had the shortest days to market weight and the lowest total feed cost, a positive effect on economic efficiency can be expected.
CONCLUSION
The ADG and feed efficiency were improved compared to the control when β-glucan or vitamin E was added. Supplementing 0.05% β-glucan significantly increased the lymphocyte concentration compared to the addition of 0.1% β-glucan, and the content of vitamin E in the blood increased when 0.02% vitamin E was added. The HBE treatment with 0.1% β-glucan and 0.02% vitamin E showed the most economic effect because it had the shortest days to market weight and the lowest total feed cost. However, carcass traits and meat quality were not affected by β-glucan or vitamin E.
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Domain: Agricultural And Food Sciences
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Development of an IgY-Based Treatment to Control Bovine Coronavirus Diarrhea in Dairy Calves
Bovine Coronavirus (BCoV) is a major pathogen associated with neonatal calf diarrhea. Standard practice dictates that to prevent BCoV diarrhea, dams should be immunized in the last stage of pregnancy to increase BCoV-specific antibody (Ab) titers in serum and colostrum. For the prevention to be effective, calves need to suck maternal colostrum within the first six to twelve hours of life before gut closure to ensure a good level of passive immunity. The high rate of maternal Ab transfer failure resulting from this process posed the need to develop alternative local passive immunity strategies to strengthen the prevention and treatment of BCoV diarrhea. Immunoglobulin Y technology represents a promising tool to address this gap. In this study, 200 laying hens were immunized with BCoV to obtain spray-dried egg powder enriched in specific IgY Abs to BCoV on a large production scale. To ensure batch-to-batch product consistency, a potency assay was statistically validated. With a sample size of 241, the BCoV-specific IgY ELISA showed a sensitivity and specificity of 97.7% and 98.2%, respectively. ELISA IgY Abs to BCoV correlated with virus-neutralizing Ab titers (Pearson correlation, R2 = 0.92, p < 0.001). Most importantly, a pilot efficacy study in newborn calves showed a significant delay and shorter duration of BCoV-associated diarrhea and shedding in IgY-treated colostrum-deprived calves. Calves were treated with milk supplemented with egg powder (final IgY Ab titer to BCoV ELISA = 512; VN = 32) for 14 days as a passive treatment before a challenge with BCoV and were compared to calves fed milk with no supplementation. This is the first study with proof of efficacy of a product based on egg powder manufactured at a scale that successfully prevents BCoV-associated neonatal calf diarrhea.
Introduction
Neonatal calf diarrhea (NCD) is a multifactorial disease in newborn calves on farms worldwide [1]. Bovine coronavirus (BCoV) associated with NCD has been detected in beef and dairy herds on all continents causing large economic losses to the dairy industry [2,3]. This enteric disease affects calves between 24 h and 30 days of life, although cases as late as 5 months of age have been reported [4][5][6]. The peak incidence occurs between days 7 and 10 [5,7,8]. The strains detected in calves with diarrhea have been labeled as BCoV-induced calf diarrhea strains (BCoV-CD) and belong to the bovine enteric or enteropathogenic coronaviruses (BECoV) group.
Worldwide, BCoV prevalence varies between 15 and 70% in naturally occurring outbreaks [9][10][11], but antibody (Ab)-prevalence is over 90% in adult cattle, suggesting that most of the cattle are exposed to the virus at least once in their lifetime [2]. However, the rate of fecal detection of BCoV ranges from 5.95% [12] to 10.52% [7] in herds from Argentina and is at 7.8% in herds from Uruguay [5]. Studies show that BCoV infection rates are significantly higher in dairy than in beef herds in Argentina, while the prevalence is higher in beef herds in Uruguay [5].
BCoV belongs to the Betacoronavirus genus within the Coronaviridae family. Infection is mainly induced by fecal-oral and respiratory transmission routes with varying viral tropisms depending on the BCoV spike protein [13]. Calves become infected early after birth through fecal exposure from carrier dams. BCoV diarrhea is detected mainly in artificially reared dairy calves. Once infected, a calf can shed high amounts of the virus (e.g., 1 × 10 9 virus particles per mL of feces). The pathology of BCoV is more severe than that of bovine group A rotavirus (RVA), resulting in mucohemorrhagic enterocolitis [14]. BCoV causes severe diarrhea, sometimes fatal, in young animals destroying epithelial cells from the gut's intestinal villi, causing malabsorption syndrome [15]. Virus replication leads to the destruction of the absorptive intestinal villous epithelial cells in the entire small intestine and eventually spreads throughout the large intestine, causing atrophy of colonic ridges and malabsorptive diarrhea. Undigested nutrients are fermented in the large intestine, promoting bacterial overgrowth and production of organic acids, especially D-lactate, contributing to electrolyte loss and leading to dehydration and metabolic acidosis. As a rule, the severity of the disease increases while the incubation period decreases in younger calves, especially those with failure of passive immune transfer (FPT). The majority of calves recover, but a few may experience pyrexia, recumb, cardiovascular collapse, coma, and death [4,16].
BCoV is also associated with winter dysentery in adult cattle [17] and respiratory tract disorders in cattle of all ages [18,19]. Some BCoV strains behave as pneumoenteric pathogens, also replicating in the upper respiratory tract. Infected calves may develop both diarrhea and respiratory disease, shedding the virus in feces and nasal secretions [4,16].
Calves acquire passive maternal protective Abs against common pathogens via colostrum intake. For a successful passive transfer from mother to calf, the calf needs to suck maternal colostrum within the first six to twelve hours of life before gut closure, so that maternal Abs and other macromolecules can be transferred massively into the bloodstream [20]. Systemic maternal Abs are then transferred back to the gut lumen by active transport via the neonatal Fc receptor [21,22].
Although dams may be vaccinated against BCoV to control diarrhea in calves, the frequency of FPT poses the need to develop alternative local passive immune strategies to enhance prevention and, most importantly, as a specific treatment method to control BCoV diarrhea in infected calves. Milk supplements studies have been conducted to prevent diarrhea caused by other viruses such as RVA. Prevention and treatment are based on specific Abs from colostrum (homologous IgG) [23] and egg yolk Abs (heterologous IgY) as passive immune therapies [24][25][26]. Moreover, IgY Abs successfully treated SARS-CoV-2 infection when given intranasally to animals and humans [27,28].
IgY Abs transference from chicken serum to the egg after immunization was initially described in 1893 [29]. IgY Abs are the only Ab isotype present in chicken egg yolk, simplifying processing and purification, and approximately 1500 mg of IgY can be harvested each month from each laying hen (5-25 mg/egg yolk), while 2 to 10% of total Ab are antigen-specific IgY [30]. These properties make IgY production a fast and economic method for polyclonal Ab production [31,32]. It is also advantageous to use avian IgY instead of mammalian IgG based on animal welfare [30]. Our studies have previously described that prophylactic or therapeutic administration of hyperimmune egg yolk to newborn calves during the first days of life significantly reduced the severity of diarrhea after a challenge with virulent bovine RVA [25,26]. In contrast, there are just a few studies on BCoV prevention strategies for bovine and porcine species using IgY Abs [33][34][35]. There is only one study that reported that the administration of IgY Abs against BCoV in calves was efficacious against diarrhea [36]. Additionally, every new biological measure needs to be developed together with standardized manufacturing methods and suitable laboratory techniques for chemistry manufacturing and control (CMC) standards that adhere to regulatory authorities' requirements. This study also describes the technology used to achieve this goal. The specific aims of this study are (i) to produce on a large-scale spray-dried egg yolk powder enriched in IgY Abs against BCoV; (ii) to evaluate batch-to-batch consistency using a statistically validated potency assay; and (iii) to conduct a proof of efficacy study where IgY to BCoV powder was administered as a prophylactic treatment to colostrum-deprived calves experimentally infected with BCoV vs. animals fed milk without IgY supplementation.
Egg Powder Enriched with IgY Abs to BCoV
Batches of egg powder used in this study were obtained from BCoV hyperimmunized hens. Two hundred White Leghorn laying hens were housed in groups of eight animals per cage at the laying hen facility of Bioinnovo S. A., Buenos Aires, Argentina. Room temperature, relative humidity, and light/dark cycles were controlled. Hens were fed a laying hen diet and water ad libitum, and eggs were collected daily starting at the first immunization. The vaccine contained 10 8 Fluorescence Focus Forming Units (FFU)/mL of live attenuated BCoV (Mebus reference strain) mixed in a 1:1 ratio with ISA 71VG adjuvant (Seppic, Courbevoie, France). For the emulsification process, oil and water components were mixed using a T25 digital Ultraturrax (IKA, Baden-Württemberg, Germany). This strain was selected following regulations from the Argentinean animal health service authority (SENASA), which requested that future batches of BCoV IgY be produced with commercially approved BCoV vaccines since this development is planned to be scaled up to register a commercial product. Commercial BCoV vaccines licensed in Argentina are designed for bovines and formulated based on the Mebus strain. Thus, in anticipation of eventually immunizing with a commercial BCoV vaccine, the hen vaccine was formulated with the same strain, the Mebus strain. However, the treated and untreated calves were subsequently challenged with the Arg95 BCoV strain during the efficacy study to evaluate the cross-protection to the strain currently circulating in Argentina.
Hens were immunized intramuscularly in the breasts with 0.5 mL of the immunogen at 0, 15, 30, 90, 120, 180, and 195 days. BCoV-specific IgY Abs were measured in sera from ten randomly selected hens to track the elicited immune response to the immunogen. Additional booster doses were administered when a decrease in the IgY Ab titer was detected in order to maintain high BCoV-specific IgY titers throughout the study.
To obtain egg powder batches, whole eggs from immunized hens were processed using an egg breaker (Pelbo, Brugherio, Italy) and then spray-dried (FlexPump, Galaxie S. A., Buenos Aires, Argentina). IgY Ab titers were determined by ELISA. Batches with the highest BCoV IgY Ab titers were tested by virus neutralization (VN) assay and maintained at a controlled room temperature (18-24 • C) until use. The product quality and stability were studied over 2 years and the physicochemical and microbiological properties were evaluated as previously reported [26].
BCoV IgY Specific Antibody ELISA
IgY Ab titers to BCoV were measured in samples of egg powder, calf sera, calf feces, and supplemented milk using a double-antibody sandwich ELISA. Briefly, 96 well ELISA plates (Maxisorp, NUNC, Thermo Fisher, Waltham, MA, USA) were coated with a BCoV hyperimmune antiserum (ELISA BCoV-IgG titer of 16384) prepared in guinea pigs at a 1:5000 dilution in carbonate/bicarbonate buffer pH 9.6. After a blocking step with 10% non-fat milk (La Serenísima, Mastellone Hnos, Buenos Aires, Argentina), the supernatant of cell culture lysate BCoV-infected or mock-infected HRT-18 cells was added, followed by serial four-fold dilutions of the samples. The reaction was developed using a peroxidaselabeled polyclonal goat IgG anti-chicken IgY Ab (Sigma-Aldrich, Burlington, MA, USA) as conjugate and hydrogen peroxide and ABTS (2,2 -Azino-bis (3-ethylbenz-thiazoline- 6-sulfonate)) as substrate/chromogen system. This assay was statistically validated to enable a robust tool for quality control of drug substance lots. For this objective, a positive and negative reference sample population (chicken serum and egg yolk) was obtained from BCoV-immunized and non-immunized hens, respectively (n = 241 samples). Furthermore, parameters of analytic and diagnostic validation were assessed following WOAH recommendations [37].
Fluorescent Focus Reduction virus Neutralization Test
Virus-neutralizing Ab titers to Mebus and Arg95 BCoV in hens' sera and egg yolk pools, supplemented milk, and calf sera were measured with a fluorescent VN test as previously described [12]. Briefly, serial 4-fold dilutions from samples were pre-incubated with 100 TCID of BCoV Mebus or Arg95 strain for 1 h at 37 • C. Sample and virus mixtures were added to HRT-18 cell monolayers and incubated for 48 h at 37 • C and 5% CO 2 . Finally, monolayers were fixed with 70% acetone and incubated with an anti-BCoV guinea pig serum FITC-labeled (1:100 in 0.1% in PBS Evan's blue solution) for 1 h at 37 • C. Fluorescence foci (representing the infected cells) were observed under a fluorescence microscope. The Ab VN titer was expressed as the reciprocal of the highest sample dilution that resulted in a >80% reduction in the number of fluorescent foci.
Virus and Inoculum Production
BCoV Mebus and Arg95 strains were replicated in HRT-18 cells in D-MEM (Gibco, Thermo Fisher, Waltham, MA, USA) plus 2 µg/mL of bovine trypsin (Sigma-Aldrich, Burlington, MA, USA) and antibiotics during 48-72 h at 37 • C and 5% CO 2 atmosphere. After observation of the cytopathic effect, cells and virus were frozen and thawed followed by a clarification step of 3500 rpm for 20 min. Supernatants containing viral strains were stored at −80 • C until use.
The challenge stock was obtained from one seven-day-old colostrum-deprived calf that had been infected orally with 50 mL of the BCoV Arg95 strain (10 5 FFU/mL). Once BCoV shedding was confirmed, 72 h after virus inoculation, the calf was euthanized and different aliquots of intestinal content were titrated by antigen ELISA, cell culture immunofluorescence assay (CCIF), and RT-qPCR. To confirm the infectivity of the challenge stock, a second calf was inoculated with 20 mL of the first calf's fecal fraction diluted in D-MEM with antibiotics and filtered by a 0.2 µm syringe filter. Microbiological controls and back titration of the inoculum were performed to confirm its identity. Twenty mL of the fecal fraction containing 10 6 FFU of BCoV were used to challenge calves in the efficacy study.
Experimental Design to Test the Efficacy of Egg Yolk Powder to Prevent BCoV Diarrhea in Calves
The experimental design to test the efficacy of egg powder against BCoV is summarized in Figure 1. Eight newborn Holstein male calves procured from the same dairy farm were separated from their mothers at birth before suckling and moved into the isolation facilities within the first 4 h of life. The animals were housed in individual isolation rooms under a strict management protocol as previously described [38]. All calves were confirmed to be negative for BCoV-specific IgG by ELISA at 48 h of life. All animals received 2 L of Abfree milk twice a day as regular feeding. The milk used in the experiment was commercially sterilized 3% fat bovine milk apt for human consumption (La Serenísima, Mastellone Hnos, Buenos Aires, Argentina). Calves were randomly assigned to one of the two following experimental feeding groups: Gp 1 = calves fed with milk supplemented with 40 g of BCoV-specific egg powder with a final ELISA BCoV IgY Ab titer of 512 and VN of 32, twice a day (n = 4); Gp 2 = calves fed milk without supplementation (n = 4). IgY Ab titers in milk were determined by ELISA and VN. All animals were inoculated orally with 10 6 FFU of virulent BCoV Arg95 strain approximately one week after birth [0 post-inoculation day (PID)]. This viral dose was previously confirmed to cause diarrhea and virus shedding in 100% of inoculated colostrum-deprived calves (control calves). Animals assigned to the IgY passive treatment group (Gp 1) started the treatment 24 h before the virus inoculation day (−1PID). From PID 15 onwards, all calves in both groups were fed with milk without supplemental Abs (end of treatment window).
Calves were examined daily for signs of diarrhea and virus shedding after BCoV inoculation. The presence of elevated rectal temperatures was recorded. To estimate the severity of diarrhea, fecal consistency was scored as follows: 0: normal; 1: pasty; 2: semiliquid; and 3: liquid. A score equal to or greater than 2 was considered diarrhea. The scoring was done blindly by qualified technicians. Before and after BCoV inoculation, fecal samples were collected daily to assess virus shedding. Serum samples were collected on the day of birth, at inoculation, and then weekly (7,14,21 PID). Serum Abs to BCoV were evaluated by ELISA and VN assays. The presence of Abs in feces was assessed by ELISA.
Mastellone Hnos, Buenos Aires, Argentina). Calves were randomly assigned to one of the two following experimental feeding groups: Gp 1 = calves fed with milk supplemented with 40 g of BCoV-specific egg powder with a final ELISA BCoV IgY Ab titer of 512 and VN of 32, twice a day (n = 4); Gp 2 = calves fed milk without supplementation (n = 4). IgY Ab titers in milk were determined by ELISA and VN. All animals were inoculated orally with 10 6 FFU of virulent BCoV Arg95 strain approximately one week after birth [0 postinoculation day (PID)]. This viral dose was previously confirmed to cause diarrhea and virus shedding in 100% of inoculated colostrum-deprived calves (control calves). Animals assigned to the IgY passive treatment group (Gp 1) started the treatment 24 h before the virus inoculation day (−1PID). From PID 15 onwards, all calves in both groups were fed with milk without supplemental Abs (end of treatment window).
Calves were examined daily for signs of diarrhea and virus shedding after BCoV inoculation. The presence of elevated rectal temperatures was recorded. To estimate the severity of diarrhea, fecal consistency was scored as follows: 0: normal; 1: pasty; 2: semiliquid; and 3: liquid. A score equal to or greater than 2 was considered diarrhea. The scoring was done blindly by qualified technicians. Before and after BCoV inoculation, fecal samples were collected daily to assess virus shedding. Serum samples were collected on the day of birth, at inoculation, and then weekly (7,14,21 PID). Serum Abs to BCoV were evaluated by ELISA and VN assays. The presence of Abs in feces was assessed by ELISA.
Coronavirus Antigen Detection
BCoV shedding was detected in fecal samples using an antigen capture ELISA as described previously [39]. The genotype and molecular identity of BCoV were confirmed by RT-PCR followed by DNA sequence analysis as described elsewhere [12].
Quantitative Real-Time BCoV PCR
Viral RNA was extracted using QIAamp ® Viral RNA Mini Kit (Qiagen, Germantown, MD, USA), following the manufacturer's instructions. Reverse transcription (RT) was carried out with MML-V (Promega, Madison, WI, USA) and random hexamers primers (Thermo Fisher, Waltham, MA, USA). Five microliters of RNA were used as a template and cDNA was stored at −20 °C. Quantitative polymerase chain reactions (qPCR) were performed with TaqMan ® technology on an ABI 7500 instrument (Applied Biosystems, Thermo Fisher, Waltham, MA, USA); cDNA from fecal samples was analyzed in duplicate. To quantify BCoV in the samples, a standard curve was generated by using ten-fold dilutions (10 7 to 10 2 FFU/mL) of a tissue-cultured Mebus BCoV strain. A fragment of N
Coronavirus Antigen Detection
BCoV shedding was detected in fecal samples using an antigen capture ELISA as described previously [39]. The genotype and molecular identity of BCoV were confirmed by RT-PCR followed by DNA sequence analysis as described elsewhere [12].
Quantitative Real-Time BCoV PCR
Viral RNA was extracted using QIAamp ® Viral RNA Mini Kit (Qiagen, Germantown, MD, USA), following the manufacturer's instructions. Reverse transcription (RT) was carried out with MML-V (Promega, Madison, WI, USA) and random hexamers primers (Thermo Fisher, Waltham, MA, USA). Five microliters of RNA were used as a template and cDNA was stored at −20 • C. Quantitative polymerase chain reactions (qPCR) were performed with TaqMan ® technology on an ABI 7500 instrument (Applied Biosystems, Thermo Fisher, Waltham, MA, USA); cDNA from fecal samples was analyzed in duplicate. To quantify BCoV in the samples, a standard curve was generated by using ten-fold dilutions (10 7 to 10 2 FFU/mL) of a tissue-cultured Mebus BCoV strain. A fragment of N gene, which is highly conserved among strains, was amplified. As was described elsewhere, five microliters of cDNA were used as the template, 2× MasterMix™ (Applied Biosystems, Thermo Fisher, Waltham, MA, USA), and primers and probes with a final concentration of 0.4 µM and 0.2 µM, respectively, were also used [40]. DNase/RNase-free water to a final volume of 25 µL completed the reaction mix.
Cell Culture Immunofluorescence Assay (CCIF)
The virus infectious titer was assessed with a cell culture immunofluorescence (CCIF) assay [12]. Fluorescent foci within the infected well were visualized using a FITC-labeled hyperimmune guinea pig antiserum to BCoV, and fluorescent foci-forming cells were counted using a fluorescence microscope. Titers were expressed as the number of FFU/mL and log-transformed for area under the curve (AUC) calculation.
Bovine Isotype-Specific Antibody ELISA
The IgM, IgA, and IgG1 Ab titers to BCoV were quantitated in calf sera and feces. Specific IgG1 Abs were detected by a double-sandwich ELISA using the reagents and protocol described previously [8]. Specific IgM and IgA Abs were measured by capture-ELISAs standardized in our laboratory following previous studies [38] and using antibovine IgM mAb (kindly supplied by Dr. L. J. Saif, The Ohio State University, Wooster, OH, USA) and affinity-purified sheep anti-bovine IgA polyclonal antibody (Bethyl Laboratories INC., Montgomery, TX, USA). Briefly, 96-well plates (Maxisorp, NUNC, Thermo Fisher, Waltham, MA, USA) were coated overnight at 4 • C with anti-IgA and anti-IgM Abs in a dilution 1/500 in a carbonate-bicarbonate buffer (pH 9.6) and blocked with 10% nonfat milk (La Serenísima, Mastellone Hnos, Buenos Aires, Argentina) in PBS. Plates were washed four times with 0.5% Tween 20 in PBS, pH 7.4, before adding 100 µL of the four-fold dilution of each sample per well and incubating for 1 h at 37 • C. Clarified Mebus BCoV and mock-infected HRT-18 cell supernatants were added in volumes of 100 µL/well. As detector Ab, a hyperimmune guinea pig serum to BCoV was added at a dilution of 1/5000 and incubated for 1 h at 37 • C. Finally, the reaction was developed using a commercial HRP-conjugated anti-guinea pig IgG Ab in a dilution of 1/5000 (Seracare, Milford, MA, USA) and hydrogen peroxide and ABTS as substrate/chromogen system. The reaction was stopped with 50 µL of 5% sodium dodecyl sulfate (SDS) (Sigma-Aldrich, Burlington, MA, USA). The absorbance at 405 nm was measured using an ELISA plate reader (Thermo, Marsiling Industrial Estate, Singapore). The ELISA Ab titer of each sample was expressed as the reciprocal of the highest dilution that had a corrected absorbance value (absorbance in the virus-coated well minus absorbance in the mock antigen-coated well for each sample and dilution) greater than the cut-off value (mean corrected absorbance of positive capture of blank wells + 3 standard deviations (SD)). Samples negative at a dilution of 1:4 were assigned a titer of 2 for the calculation of geometric mean titers (GMTs).
Statistical Analysis
The cut-off value of the ELISA assay to measure anti-BCoV IgY Abs was obtained after performing the Receiver Operating Curve (ROC) analysis of the corrected optical densities (ODc) measured at 405 nm. The ODc frequency distribution from 241 samples classified 94 as negative and 147 as positive, tested at 1/256 dilution (reference population). Diagnostic sensitivity and specificity of the IgY ELISA were estimated following the Greiner and Gardner recommendations and validation parameters of The WOAH Manual of terrestrial animals [41]. Concordance analysis between the classification of reference samples and its results obtained by the ELISA was conducted using the Kappa statistic [42]. To estimate the intermediate precision of the ELISA, ODc results from the positive control were recorded for a period of four years (2012-2015). The result was expressed as the coefficient of variation (CV). The correlation between log-transformed VN and ELISA IgY Ab titer was analyzed by linear regression and Pearson's correlation test. Statistical analyses were conducted using MedCalc Software (Ostend, Belgium), Version 19.0.5, and Infostat (Córdoba, Argentina), Version 2020.
Statistical analysis of the efficacy study in calves was conducted as follows. Cumulative titers of virus shedding were expressed as AUC. The AUC of diarrhea score and virus shedding was calculated in RStudio (Boston, MA, USA) using the AUC command of the DescTools package and the spline approach. The mean day of onset, duration of virus shedding and diarrhea, and mean AUC of virus shedding and diarrhea among the treatment groups were compared using the Student t test or Wilcoxon rank sum test when the normality and homoscedasticity assumptions were not met. Neutralizing and isotypespecific Ab titers in feces and serum were log10-transformed and serum negative samples at a dilution of 1:2 were assigned an arbitrary Ab titer of 2, log = 0.3, for the calculation of geometric mean titers (GMTs) in the case of the inverse of the maximum positive dilutions and arithmetic mean in the case of the log-transformed values. The IgM, IgA, and IgG antibody titers in serum from PID 0 to PID 14 and the virus shedding titer and diarrhea score from PID 1 to 14 were analyzed by a two-way ANOVA of repeated measures through time. Statistical significance was assessed at p < 0.05. Statistical analyses were performed using Infostat with a link to R or RStudio Version 1.4.1717 from RStudio, PBC.
Development of a Product Based on IgY Abs to BCoV
Laying hens were immunized with a vaccine formulated with the BCoV Mebus reference strain in an avian-specific adjuvant as described in the M&M section. This vaccine was highly immunogenic in hens reaching ELISA IgY Ab titers to BCoV in the serum of 18,820 (GMT). The egg powder batches reached a peak of ELISA IgY Ab titer to BCoV of 1024 measured in a suspension of 10 mg/mL ( Figure 2). Eggs from 200 hyperimmunized hens were collected daily and were crashed and dried every two weeks at the Bioinnovo manufacturing plant generating two DS (Drug Substance) batches with a total of 74.2 kg of dried egg-based products. IgY Ab titers from all DS batches are detailed in Table 1. Additionally, we evaluated the immune response against several antigens, independently, when we formulated polyvalent vaccines for hens, and we observed no negative effect (decrease in overall Ab titer) in either IgY to BCoV response or IgY response to other antigens as RVA when both antigens were formulated together.
Quality Control of Egg Yolk Powder DS Batches Enriched in IgY to BCoV.
IgY Ab neutralizing activity against Mebus and Arg95 BCoV strains and binding IgY Ab titers in egg powder batches and supplemented milk are shown in Table 1. VN Ab titers against the Mebus and Arg95 strains were equal. As expected, VN Ab titers were lower than binding IgY titers in the produced batches (64 vs. 1024, respectively) as well as in the supplemented milk (32 vs. 512 respectively). This result predicted that IgY Abs might serve as a potential tool to neutralize BCoV infection when administered in vivo.
BCoV IgY-Specific Antibody ELISA Validation
A summary of all diagnostic validation results is depicted in Table 2. The assay was successfully validated according to WOAH recommendations, giving assay specificity and sensitivity values of 98.2% and 97.7%, respectively.
Parameter
Result Acceptance Criteria
Quality Control of Egg Yolk Powder DS Batches Enriched in IgY to BCoV
IgY Ab neutralizing activity against Mebus and Arg95 BCoV strains and binding IgY Ab titers in egg powder batches and supplemented milk are shown in Table 1. VN Ab titers against the Mebus and Arg95 strains were equal. As expected, VN Ab titers were lower than binding IgY titers in the produced batches (64 vs. 1024, respectively) as well as in the supplemented milk (32 vs. 512 respectively). This result predicted that IgY Abs might serve as a potential tool to neutralize BCoV infection when administered in vivo.
BCoV IgY-Specific Antibody ELISA Validation
A summary of all diagnostic validation results is depicted in Table 2. The assay was successfully validated according to WOAH recommendations, giving assay specificity and sensitivity values of 98.2% and 97.7%, respectively. Figure 3A).
To determine the admission range of the positive control, samples were run 22 times in a 1/1024 working dilution resulting in an ODc of 0.518 (0.378-0.658; arithmetic mean ± 1 SD). For an individual assay result to be characterized within the expected parameters, the ODc of the positive control had to fall within this admission range, while the negative control and the blank had to measure below the cut-off of the assay ( Figure 3B).
The linearity of the positive control was determined by running serial four-fold dilutions of the positive control in eight independent assays during four consecutive years. A linear decrease of ODc vs. dilution factor of the positive control allowed for adjusting the linear regression in the dilution range tested ( Figure 3C). in a 1/1024 working dilution resulting in an ODc of 0.518 (0.378-0.658; arithmetic mean ± 1 SD). For an individual assay result to be characterized within the expected parameters, the ODc of the positive control had to fall within this admission range, while the negative control and the blank had to measure below the cut-off of the assay ( Figure 3B).
The linearity of the positive control was determined by running serial four-fold dilutions of the positive control in eight independent assays during four consecutive years. A linear decrease of ODc vs. dilution factor of the positive control allowed for adjusting the linear regression in the dilution range tested ( Figure 3C).
ROC Curve: Cut-Off Value and Associated Sensitivity and Specificity
The cut-off value of the assay was determined after ROC analysis on the frequency distribution of ELISA ODc from 241 samples. A total of 94 samples were classified as negatives (serum, fluid egg yolk, and dried egg powder from non-immunized hens or hens
ROC Curve: Cut-Off Value and Associated Sensitivity and Specificity
The cut-off value of the assay was determined after ROC analysis on the frequency distribution of ELISA ODc from 241 samples. A total of 94 samples were classified as negatives (serum, fluid egg yolk, and dried egg powder from non-immunized hens or hens immunized with other antigens including Rotavirus, Salmonella, and E. coli) and 147 were classified as positive (serum, egg yolk, and dried egg powder from BCoV immunized hens) constituting the reference population. Samples were tested by ELISA in 1/256 dilution ( Figure 4B). The 1/256 dilution was selected for the validation analysis because this was the minimum dilution that showed significant differences between the OD obtained in virus-coated and mock-coated wells.
Results were expressed in percentage of positivity (P%) from the ODc of the positive control run in each plate in a 1/1024 dilution which was assumed as 100 P%. The ROC analysis indicated that at a cut-off value of 18.68% from the ODc of positive control (tested in each plate in a 1/1024 dilution), the sample to be tested will be properly classified 95 out of 100 times. With this 18.68 P% cut-off value, the assay showed a diagnosis sensitivity (DSe) and specificity (DSp) of 97.66% and 98.23%, respectively ( Figure 4B). The assay could detect the two different positive and negative populations independently of the sample dilution used. The cut-off value measured in ODc was 0.110. immunized with other antigens including Rotavirus, Salmonella, and E. coli) and 147 were classified as positive (serum, egg yolk, and dried egg powder from BCoV immunized hens) constituting the reference population. Samples were tested by ELISA in 1/256 dilution ( Figure 4B). The 1/256 dilution was selected for the validation analysis because this was the minimum dilution that showed significant differences between the OD obtained in virus-coated and mock-coated wells. Results were expressed in percentage of positivity (P%) from the ODc of the positive control run in each plate in a 1/1024 dilution which was assumed as 100 P%. The ROC analysis indicated that at a cut-off value of 18.68% from the ODc of positive control (tested in each plate in a 1/1024 dilution), the sample to be tested will be properly classified 95 out of 100 times. With this 18.68 P% cut-off value, the assay showed a diagnosis sensitivity (DSe) and specificity (DSp) of 97.66% and 98.23%, respectively ( Figure 4B). The assay could detect the two different positive and negative populations independently of the sample dilution used. The cut-off value measured in ODc was 0.110. A concordance analysis between IgY to BCoV ELISA results and the actual classification of the samples included in the reference population considering an 18.68 P% cutoff value showed a Kappa value of 0.93 corresponding to an almost perfect agreement (Table 3). A concordance analysis between IgY to BCoV ELISA results and the actual classification of the samples included in the reference population considering an 18.68 P% cut-off value showed a Kappa value of 0.93 corresponding to an almost perfect agreement (Table 3).
Assay Intermediate Precision
The CV for the IgY to BCoV ELISA resulted in 27%, which is less than the 30% admitted by WOAH [37]. This analysis included intra-plate repeatability and reproducibility in separate assays.
Correlation between the IgY ELISA Ab Titers and Neutralizing Ab Titers
A total of 35 samples (4 hen serum samples, and 31 IgY batches of fluid and spraydried powder) were tested with ELISA and VN. There was a significant correlation between the Ab titers (R 2 = 0.92, p < 0.001) indicating that the ELISA for IgY quantification might be used as a reference to estimate VN batch-to-batch protective Ab titer ( Figure 5).
Assay Intermediate Precision
The CV for the IgY to BCoV ELISA resulted in 27%, which is less than the 30% admitted by WOAH [37]. This analysis included intra-plate repeatability and reproducibility in separate assays.
Correlation between the IgY ELISA Ab Titers and Neutralizing Ab Titers
A total of 35 samples (4 hen serum samples, and 31 IgY batches of fluid and spraydried powder) were tested with ELISA and VN. There was a significant correlation between the Ab titers (R 2 = 0.92, p < 0.001) indicating that the ELISA for IgY quantification might be used as a reference to estimate VN batch-to-batch protective Ab titer ( Figure 5).
Reproduction of BCoV Infection and Diarrhea in Colostrum-Deprived Calves
One colostrum-deprived calf was used to produce the virulent BCoV inoculum for further studies. As mentioned in M&M, this calf was infected with 50 mL of BCoV Arg95 strain with a tissue culture infection titer of 10 5 FFU/mL at 7 days of age. The calf developed diarrhea the day after inoculation. Once BCoV shedding was confirmed, 72 h after
Reproduction of BCoV Infection and Diarrhea in Colostrum-Deprived Calves
One colostrum-deprived calf was used to produce the virulent BCoV inoculum for further studies. As mentioned in M&M, this calf was infected with 50 mL of BCoV Arg95 strain with a tissue culture infection titer of 10 5 FFU/mL at 7 days of age. The calf developed diarrhea the day after inoculation. Once BCoV shedding was confirmed, 72 h after virus inoculation, the calf was euthanized and different aliquots of intestinal content were titrated by antigen ELISA, CCIF, and RT-qPCR. All collected fractions were positive for infective BCoV and those titers were much greater than inoculum (Table 4). All fractions were negative for Rotavirus, E. coli, and Salmonella. A second calf was challenged using 20 mL of the first fecal fraction diluted in D-MEM with antibiotics and filtered by a 0.2 µm syringe filter. This animal received 10 6 FFU of BCoV which resulted in 6 days of virus shedding and 7 days of diarrhea confirming that the inoculum was able to induce BCoV infection and disease. Microbiological controls and back titration of the inoculum were performed to confirm its identity. Twenty mL of the fecal fraction containing 10 6 FFU of BCoV was used to challenge calves in the efficacy experiment.
Egg Powder Containing BCoV IgY Abs Reduced Diarrhea Duration and Severity in a Colostrum-Deprived Calf Model
A proof of principle study was conducted to evaluate whether the egg powder enriched in BCoV IgY Abs could prevent BCoV diarrhea in colostrum-deprived calves. As it was detailed in M&M, eight colostrum-deprived calves were randomly assigned to one of the following feeding groups: group 1: calves fed with 2 L of milk supplemented with 40 g of egg powder with a final ELISA BCoV IgY Ab titer of 512 and VN titer of 32, twice a day (n = 4) for 14 days; group 2: calves were fed with milk without supplementation (n = 4). All animals were challenged orally with 10 6 FFU of virulent BCoV Arg95 strain (PID 0, 7 days of age). Diarrhea and virus-shedding measurements associated with BCoV infection and disease are summarized in Table 5. Table 5. Diarrhea and virus shedding parameters in colostrum-deprived calves fed 2 L of milk supplemented with 40 g of egg powder twice a day for 14 days (group 1: BCoV IgY) or Ab-free milk (group 2: control) experimentally infected with 10 6 FFU of BCoV Arg95. All calves developed diarrhea after inoculation with BCoV. However, calves receiving IgY showed a significant delay (p = 0.0019) in the onset of diarrhea (4 days); the diarrhea was significantly less severe (p = 0.0036) and significantly shorter in duration (p = 0.0003) (50% less duration) than the diarrhea observed in the control group (Table 5, Figure 6). Diarrhea severity (AUC) was also significantly reduced (p = 0.0036) in treated calves (Table 5).
All the animals also showed signs of infection and shed BCoV after the challenge. However, the IgY group of calves (Gp 1) showed a significant delay (p = 0.0041) in the onset of infectious virus shedding and significantly shorter (p = 0.0104) duration (only three days on average) compared with the control group that shed the infectious virus for an average of 6 days ( Table 5, Figures 6 and S1). The magnitude of virus shedding (AUC) was reduced compared with the group of animals receiving Ab-free milk, but not significantly (p= 0.103) ( Table 5).
When studying the isotype-specific Ab responses to BCoV in feces we observed that fecal-IgM and IgA Ab responses were associated with viral clearance and diarrhea resolution ( Figure 6). The peak of IgM responses occurred at 7 PID in the control group compared to 14 PID in the IgY-treated group, in concordance with the delay in the onset of the infection and disease. The peaks of IgA responses were detected in both groups at 14 PID, while higher titers were observed in the calves receiving IgY than in the control animals. No copro-IgG1 Ab or IgG2 responses were detected. In serum, IgA Ab response was higher in the IgY-treated group compared to the control group (p = 0.021 at 21 PID) ( Figure 7). The peak of IgM Ab response was detected at 7 PID in the serum of the control group compared to 14 PID in the IgY group of calves following the delay of the shedding and disease (Figure 7). IgG1 and VN Ab responses were similar between groups. Seric IgG2 was not detected.
We also evaluated the presence of IgY Ab to BCoV in fecal samples from calves fed with milk supplemented with egg powder enriched in BCoV IgY Abs. We detected IgY Ab in fecal samples of calves from the treated group (Gp 1). As shown in Figure 6, IgY Abs were not detectable in feces during most of the treatment or while shedding was present. IgY Abs to BCoV were detected in calves from Gp 1 between days 10 and 15 once virus clearance was achieved. Even though IgY titers in calves' feces were low, IgY was specific to BCoV in an ELISA assay, demonstrating that IgY Ab to BCoV is able to travel intact through the gastrointestinal tract to remain detectable until one day after the end of treatment ( Figure 6).
Hyperthermia was the last clinical parameter evaluated. Rectal temperature was measured daily in all the calves in this study. Control calves (Gp 2) showed an average of 4.3 days of hyperthermia compared with 1.5 days in calves treated with egg powder enriched in BCoV IgY Ab (Tables 5 and S1).
virus clearance was achieved. Even though IgY titers in calves' feces were low, IgY was specific to BCoV in an ELISA assay, demonstrating that IgY Ab to BCoV is able to travel intact through the gastrointestinal tract to remain detectable until one day after the end of treatment ( Figure 6).
Hyperthermia was the last clinical parameter evaluated. Rectal temperature was measured daily in all the calves in this study. Control calves (Gp 2) showed an average of 4.3 days of hyperthermia compared with 1.5 days in calves treated with egg powder enriched in BCoV IgY Ab (Table 5, Table S1).
Discussion
There is increasing evidence that all human CoVs currently known might have an animal origin. Controlling BCoV infection in calves is of public health importance since BCoV belongs to the same phylogenetic group as the pandemic SARS-CoV-2 [43]. In addition, very important economic losses are associated with NCD [44] and new strategies are needed to control viral diseases in order to decrease the unnecessary use of antibiotics
Discussion
There is increasing evidence that all human CoVs currently known might have an animal origin. Controlling BCoV infection in calves is of public health importance since BCoV belongs to the same phylogenetic group as the pandemic SARS-CoV-2 [43]. In addition, very important economic losses are associated with NCD [44] and new strategies are needed to control viral diseases in order to decrease the unnecessary use of antibiotics by farmers. IgY technology is a sustainable source of polyclonal Abs and is aligned with animal welfare because Abs are collected directly from eggs.
In the present study, we describe the development and scaling up of a product based on IgY Ab to control BCoV diarrhea in dairy calves. The ability of IgY to neutralize BCoV infection was measured in vitro. In addition, a binding assay was standardized and statistically validated as a tool to test batch-to-batch consistency.
The binding assay effectively measured IgY Abs to BCoV in serum, fluid egg, and egg powder from BCoV-immunized hens, in feeding milk, and in fecal samples from calves fed with IgY powder. The statistical validation of the assay included the estimation of diagnostic sensitivity and specificity of 97.66% and 98.23%, respectively. During the validation process, five batches of capture polyclonal antibodies, three BCoV antigen batches, and one control set were used. An intermediate precision value of 27% demonstrates the robustness of the assay [37]. As expected, the VN IgY Ab titers to BCoV were lower than ELISA titers. However, there was a significant correlation between the assays. It is important to highlight that even though these VN titers were measured against the Mebus strain and calves were infected with the Arg95 strain, we had already established that Mebus and the local Arg95 strain belonged to the same serotype [12,14].
Although the VN assay might be more precise when detecting antibodies with an effector function, there are many reasons for developing a binding assay to measure IgY antibodies in an egg-based product. For example, egg samples are usually toxic to cell monolayers, and neutralization assays depend on maintaining the integrity of the cell culture. Neutralization assays are also laborious, time-consuming, and need an expert technician to run, read, and interpret the assay. On the other hand, a binding (ELISA) is by far more accessible to most laboratories, gives an objective result, is fast, easy to perform, and has low equipment requirements. Additionally, to confirm a correlation between VN titers and ELISA BCoV-specific IgY titers we performed a regression analysis with log−10 transformed titers resulting in an R 2 value of 0.92 for a linear regression analysis and 0.97 for the quadratic regression analysis (Supplementary File S1). These results are very optimistic compared to similar studies performed with a correlation analysis between GenScript SARS-CoV-2 ELISA Ab titers and pseudo-VN titers with an R 2 value of 0.552 [45]. This is the first BCoV-specific IgY ELISA assay to be statistically validated. The assay was transferred to Bioinnovo, a biotechnology firm developing IgY products, and to the National Health Service (SENASA), the local regulatory authority, to control future commercial batches.
The efficacy of the product was tested in a pilot study using a colostrum-deprived neonatal calf model of BCoV infection and disease, specifically standardized for this purpose. Milk supplemented with egg powder enriched in IgY Ab to BCoV was administered to four colostrum-deprived calves and then challenged with 10 6 FFU of BCoV [18,46,47]. BCoV Arg95 strain was used as the challenge pool because it is a local isolate that genetically represents the strains currently circulating in the field in Argentina and Uruguay [5,12]. We observed that all control calves infected with BCoV showed viral shedding and developed diarrhea for 7.8 days on average starting at 48 h post-inoculation, which was similar to that shown in other studies [18,46,47]. Calves fed with IgY Abs to BCoV with a final ELISA Ab titer of 512 and VN titer of 32 for 14 days showed a significant delay in the onset of diarrhea and virus shedding in contrast to control animals. Moreover, the clinical episodes in the IgY-treated calves were of significantly shorter duration and severity, as was the duration of hyperthermia. This shedding and severity of disease results observed after administering this amount of passive IgY Ab treatment (40 g of egg powder in 2 L of milk, twice a day for 14 days with a final VN titer of 32) are comparable to Ikemori et al.'s results [36]. Ikemori challenged colostrum-deprived calves with 10 9 TCID50 of Kakegawa BCoV strain and after 6 h calves received 0.5 g of powder egg yolk with a neutralizing titer of IgY Ab to BCoV of 5120 for 7 days, which is equivalent to IgY neutralizing Ab titer in the milk of 12.8 [36]. Other studies performed to evaluate non-specific Ab as passive immunity against BCoV diarrhea show that calves treated with a milk replacement supplemented with commercial serum proteins (APC Lifeline with 10% immunoglobulins, 40% proteins, and 0.5% fat) resulted in no differences in diarrhea severity between the control and treated groups [48]. Finally, several researchers are studying IgY technology against CoV, but they did not evaluate the product in animal models [35,49].
Another aspect to consider is the dose of product administered in each meal. In this study, 40 g in each 2 L milk feeding was the maximum amount of powder that was properly dissolved in the milk. Increasing the Ab titer in the egg powder batches will increase the titer administered in each dose, thus increasing the efficacy of the product to protect against BCoV diarrhea. This could be achieved by optimizing the vaccine formulation containing not only a higher titer of the Mebus reference strain (that grows in proper titers in tissue culture) but also a BCoV strain more closely related genetically to the ones circulating in the field in Argentina, Uruguay, and Brazil [5,50].
It is important to highlight that the efficacy of the product was tested in colostrumdeprived calves representing the worst-case scenario compared to natural conditions with probably lower infectious doses. In previous studies, we observed that calves with BCoV IgG1 passive maternal Abs titers in serum of ≥1024 were mostly protected from BCoV infection compared to calves receiving BCoV IgG1 passive maternal Abs with titers of ≤ 256 [8]. Thus, vaccination of dams with BCoV vaccines followed by proper colostrum intake might result in an optimal level of passive maternal antibody (≥1024). The supplementation of milk with IgY during the susceptible immunological window also represents a double strategy to minimize damage by FPT (colostrum and IgY intake/treatment).
Additionally, we observed that BCoV-specific copro IgM and IgA Ab responses were delayed in the IgY-treated group compared to the control animals. This was correlated with the delay in the onset of diarrhea and virus shedding. Similarly, the serum IgM, IgA, and IgG1 responses were delayed and had a higher magnitude in the treated group compared to the control group. This immunomodulation was also observed in calves experimentally infected with bovine RVA and treated with rotavirus-specific IgY [25] as well as in mice treated with some components of egg yolk [51]. It has been demonstrated that low molecular mass substances associated with chicken IgY stimulated the production of cytokines and nitric oxide from macrophages [52]. Furthermore, the clearance of viral infection and resolution of clinical symptoms was associated with the development of a mucosal immune response characterized by high titers of secretory IgA in the gut.
IgY technology has been successfully used for the development of many potential therapeutics [53] and many of them are being tested in human clinical trials [54]. The development of an IgY-based product to prevent and treat BCoV diarrhea in calves is, to our knowledge, an advance in the field. Although BCoV has been detected with low prevalence in Argentina, BCoV causes diarrhea that complicates clinical symptoms and sometimes leads to the death of the calf [2]. Vaccination is not 100% effective in local dairy production systems, so additional measures might need to be implemented to prevent neonatal diarrhea caused by BCoV. Even if immunization is properly implemented with potency-tested vaccines, colostrum management is still problematic, and calves might succumb to diarrhea. The development of this product might contribute to minimizing the passive immunity shortage and positively modulate gut mucosal immune responses that will protect newborn-treated calves from future exposures to the antigen [25]. Overall, the passive oral administration of BCoV IgY Abs might help reduce the antigen load in farms reducing the risk of diarrhea, while providing a tool to control this viral disease for which antibiotic therapy is not applicable. In addition, a product can be designed to include other pathogens that cause NCD like RVA, E. coli, Salmonella, etc., to control the syndrome more efficiently or prevent new infections. To our knowledge, this is the first study describing the efficacy of scaled-up DS batches of a spray-dried product based on IgY Abs to BCoV in the prevention of NCD caused by BCoV under controlled conditions.
Conclusions
Egg powder enriched in IgY to BCoV was successfully developed and produced at an industrial scale obtaining a product to be used in NCD prevention. BCoV infection was reproduced in controlled conditions using a local circulating strain isolated in a dairy farm in Argentina in 1995. Finally, the administration of IgY Ab to BCoV at a final ELISA Ab titer in the milk of 512 and VN Ab titer of 32 as passive treatment significantly delayed the onset and duration of virus shedding and diarrhea in colostrum-deprived calves experimentally challenged with a field strain. Finally, an ELISA assay was developed and statistically validated to control batch-to-batch potency showing high sensitivity and specificity. This study sets the stage to provide an efficient tool to control BCoV diarrhea in dairy farms.
Supplementary Materials:
The following supporting information can be downloaded at: [URL]. mdpi.com/article/10.3390/v15030708/s1, File S1: Regression analysis from ELISA vs VN Ab titers; Figure S1: Diarrhea evolution in each calf from the IgY-treated group and control group. Table S1: Fecal scores and rectal temperatures from calves.
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Domain: Agricultural And Food Sciences
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Salt-affected soils in Tanzanian agricultural lands Type of soils and extent of the problem
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The estimates predict that 50% of arable land around the world will become impacted by salt-affected soils by 2050, consequently increasing food insecurity (Butcher et al., 2016), hence making soil salinization increase a serious global threat to agricultural production (Butcher et al., 2016;Corwin & Scudiero, 2019). The prevailing climate change is likely to intensify the effect of salt-affected soils (Corwin & Scudiero, 2019;Eswar et al., 2021;Wen et al., 2021), leading to dramatic impacts on crop growth and productivity and consequently reducing yield by more than 50%, especially in arid and semi-arid regions (Anami et al., 2020;Ivushkin et al., 2019). Thus, in light of the expected enormous growth in the global population, salt-affected soils are one of the key challenges to food production (Chen & Mueller, 2018;Egal, 2020;Wen et al., 2021;Zörb et al., 2019).
In sub-Saharan Africa, soil salinization affects 19 million ha of land (Tully et al., 2015), whereas in Tanzania, over 3 million ha of land are affected (FAO, 2000). Research conducted by Kashenge-Killenga et al. (2016) in some irrigation schemes indicated that 7-15 percent of the schemes had salt-affected soils and that about 2-10 percent of rice fields were abandoned. Furthermore, Kashenge-Killenga et al. (2016) and Meliyo et al. (2016) reported high values of electrical conductivity (EC) ranging from 14 to 19 dSm −1 in various irrigation schemes. Consequently, the average yield losses ranged from 5 to 70 percent (Kashenge-Killenga et al., 2016), while in extreme cases the yield losses were up to 100 percent. To address the effect of salt-affected soils on cash and food crop production, stakeholders' awareness of the problem and the most effective management options deserve global attention.
To date, different approaches have been proposed for the prevention, mitigation, and reclamation of saltaffected soils, including the use of organic and microbial soil remediation (Amini et al., 2016;Gunarathne et al., 2020;H. Sun et al., 2017;Leogrande & Vitti, 2019;Saifullah Dahlawi et al., 2017;U. B. Singh et al., 2021); breeding for salt-tolerant varieties for different crops (Dehnavi et al., 2020;Kamran et al., 2020;Sunita et al., 2020), engineering and water serving technologies (Mohanavelu et al., 2021), precision application of chemicals and fertilizers (El Hasini et al., 2019;G. Qadir et al., 2017;Gangwar et al., 2019), and phytoremediation (A. Kumar et al., 2020;Nouri et al., 2017). However, most of these technologies are quite expensive and unaffordable for farmers in rural areas. Hence, in order to effectively manage salt-affected soils, a combination of technologies is required (Butcher et al., 2016), so that farmers can choose the technology that best suits their needs.
Though salt-affected soils have significant negative impacts on agricultural production by turning productive lands into barren grounds and spoiling water quality and ecosystem services, research results show that if such soils are properly managed, they are highly productive with significant economic potential (G. Qadir et al., 2017;Stavi et al., 2021;Wicke et al., 2011). The economic potential of salt-affected soils can only be realized if the extent and characteristics of such soils are well established to allow the proper selection of technologies for their effective management options. However, in Tanzania in particular, the information on the extent and characteristics of saltaffected soils is scanty and scattered (Butcher et al., 2016;Ivushkin et al., 2019), thus posing a challenge to how to effectively manage such soils for sustainable agricultural production. Therefore, this systematic literature review was conducted to explore the currently available information on salt-affected soils in Tanzania, including their extent, types, origin, and distribution, and what have been the coping strategies for sustainable farming on such soils in both irrigated and rainfed agro-ecologies.
Rational of the review
Soil salinization has become a serious challenge in sustainable agriculture for food and nutritional security in developing countries (A. Singh, 2021;Butcher et al., 2016). The global reports estimate the extent of saltaffected soils to be around 1 billion ha, whereas the information down to individual countries is not well documented (Ivushkin et al., 2019;Omuto et al., 2020). Tanzania inclusive, the data is more significant for planning and management strategies. The problem of saltaffected soils is an increasing concern in Tanzania, like in other parts of the world, especially in rice-growing areas (Kashenge-Killenga et al., 2013, 2016;Makoi & Ndakidemi, 2007;Meliyo et al., 2016). Although the negative impacts of salt-affected soils on farmers fields have been reported, including loss of crop yields and the abandonment of arable land in some areas after becoming unproductive, the information is not well documented (Kashenge-Killenga et al., 2016). Thus, the need to meet increasing food demand for the growing population under condition of declining agricultural land necessitates prioritizatio of research on salt-affected soils (P. Kumar & Sharma, 2020) and effective management options for increasing crop production.
Knowledge and a comprehensive understanding of the current information are the way forward toward the alleviation of this challenge, thereby increasing productivity and food security (Shokat & Großkinsky, 2019). Therefore, it is very important to have real-time data about the extent, distribution, and types of salt-affected soils to support and guide informed decision-making to improve agricultural production in Tanzania. This review presents the current status of the available information and existing gaps and proposes a way forward that guides research priorities targeting the development of salt-affected soil management options for improved crop production, specifically in rice irrigation schemes. In this regard, conducting a review of the pertinent scholarly literature is crucial for assessing existing knowledge and identifying research gaps in a particular area of research interest, which helping to expand the knowledge base (Snyder, 2019).
Search strategy, keywords and criteria of selection
The work adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, an approach that demonstrates a clear path, guarantees scientific quality, and ensures transparency for conducting a systematic review (Grant & Booth, 2009;Page et al., 2021). Several systematic review flow charts have been developed and adopted to conduct systematic review and meta-analysis, including SALSA (search, appraisal, synthesis, analysis) by Grant and Booth (2009), the Protocol, Search, Appraisal, Synthesis, Analysis, and Report (PSALSAR) framework by Mengist et al. (2020), and the PRISMA approach by Moher et al. (2010). This review opted to follow a modified PRISMA flowchart, which is a widely accepted checklist designed to improve the reporting standards of comprehensive literature reviews and meta-analyses (Jafarzadeh et al., 2021). As shown in Figure 1, it involves four phases: identification, screening, eligibility, and inclusion. The paper used nine (9) search engines, namely Elsevier, MDPI, Frontiers, Global Science, Springer, Wiley, Taylor & Francis, PubMed, and Web Research Gate, to download and collect published articles from peer-reviewed journals. In areas with limited published works, unpublished reports that had relevant information were also considered. Keywords were used in searching papers to minimize unwanted papers and avoid the risk of missing relevant papers. Broad themes were also used, covering aspects such as the origin of salt-affected soils, the extent of salt-affected soils, the distribution of salt-affected soils, management options for salt-affected soils, the challenges and opportunities of salt-affected soils, and the economic implications of salt-affected soils. Generally, the search identified a total of 419 journal papers listed in search engines and 5 reports. Out of 419 articles collected, 56 were duplicates and were removed. Further screening was done for the remaining 363 papers, and the 173 papers were rejected because the titles, abstracts, and texts of the articles did not directly match the target of the review. Further screening was done, and 57 articles out of the remaining 190 were removed for having no direct relevant information in the main text. Finally, 133 articles and one report were used to examine and discuss various aspects of salt-affected soils in Tanzania. Figure 1 illustrates the flow of the review from search sites to the final decision for articles used in this review using the PRISMA approach (Grant & Booth, 2009;Page et al., 2021).
Origin of salt-affected soils
The genesis of salt-affected soils occurs through natural processes influenced by salty parent materials, mineralogy, groundwater, windblown salt particles, and floods (Omuto et al., 2020;Stavi et al., 2017). While humaninduced activities such as irrigation (with poor drainage or irrigation with saline water), inappropriate fertilizer application, improper waste disposal, inappropriate use of wastewater, misuse of soil amendments, inappropriate soil-water management, and land-use change (Amini et al., 2016;Shahid et al., 2018;Stavi et al., 2021). Whether natural or human-induced soil salinization emerges as a major environmental constraint impeding soil productivity, agricultural sustainability, and food security, particularly in arid and semi-arid regions of the world (Chiconato et al., 2019;Corwin & Scudiero, 2019;Mukhopadhyay et al., 2021;Shrivastava & Kumar, 2015).
Spatial distribution, extent, types, and the causes of salt-affected soils in Tanzania
Spatial distribution, extent, and types of salt-affected soils in Tanzania were reported by Mnkeni (1996), who indicated that 3.6 million ha of land had salt problems, of which 83% were saline and 16% were sodic. The occurrence of these soils is most extensive in areas with arid and semi-arid climates and in coastal regions where there is an incursion of sea water through estuaries and rivers. Additionally, in inland areas, shallow groundwater influences are also present. On the other hand, FAO (2000) estimated that over 1.7 million ha were saline, whereas 300,000 ha were sodic. According to Mnkeni (1996), salt-affected soils mainly occur in alluvial plains and valleys that receive soils influenced by the nature of the parent materials eroded by surface runoff or colluvial from highland areas. In the northern highlands, water sources of the Pangani river run within and over the volcanic lava and ashes of Kilimanjaro and Meru mountains, eroding salt materials and overflowing in flat areas (Mnkeni, 1996). Salt-affected soils in the internal drainage basin and swamps like those in the central zone regions and within the rift valley were due to long-term collection of water, poor drainage (Mnkeni, 1996), and higher evapotranspiration than precipitation.
Recently, climate change has been perceived as one of the contributing factor that accelerates the problem of salt-affected soils in Tanzania (Kashenge-Killenga et al., 2016). This is evidenced by the experiences of increasing drought and the decreasing length of the growing seasons caused by poor distribution of rainfall patterns where evapotranspiration exceeds precipitation (Kashenge-Killenga et al., 2016). Besides natural factors, the problem of saltaffected soils is being intensified by management factors, including inadequate irrigation infrastructure and poor agricultural practices (Meliyo et al., 2016;Omar et al., 2022). For example, there is a lack of farm inlets and outlet canals that encourage farmers to share irrigation water across farm boundaries. While both natural and management factors are contributing to intensifying salt-affected soils, the current extent and spatial distribution of saltaffected soils remain a challenge due to a lack of upto-date information (Kashenge-Killenga et al., 2014).
Figure 2 indicates the distribution of salt-affected soils in Tanzania (De Pauw, 1984).
Classification and general properties of salt-affected soils
Salt-affected soils are classified as saline, sodic, and saline-sodic soils based on their chemical and physical properties (Table 1), which are the electrical conductivity of saturated paste extract (ECe), pH, the calculated exchangeable sodium percentage (ESP), and the sodium adsorption ratio (SAR) (Wallender & Kenneth, 2012). The saline soils are the ones with excess accumulation of soluble salts in the root zone and have high ECe values (>4 dSm −1 ). Sodic soils, on the other hand, are characterized by the accumulation of high levels of exchangeable sodium relative to other cations, hence with SAR>13 and/or ESP>15% (Cuevas et al., 2019;Hassani et al., 2020). On the other hand, saline-sodic soils are characterized by having both highly soluble salts and exchangeable sodium, ECe>4 dSm −1 , SAR>13, and ESP>15% (Wallender & Kenneth, 2012).
Saline soils
Saline soils contain high levels of soluble salts in the soil solution, enough to cause adverse effects on the growth of most crops. The dominant cations in saline soils are calcium (Ca 2+ ), magnesium (Mg 2+ ) and/or potassium (K + ), as well as anions of chlorides (Cl − ), sulphates (SO 4 2− ), and carbonates (CO 2− ) and bicarbonates (HCO 3 − ) (Richards & USDA, 1954;Wallender & Kenneth, 2012). Although NaCl dominates, nitrates may be present on a few occasions (Osman, 2018). An accumulation of soluble salts in the root zone alters the pH and composition of soil solution and interferes with plant absorption processes (osmosis/osmotic pressure) of water and essential nutrients, causing imbalances and deficiencies (Akhatar, 2019;C. Zhao et al., 2020). Plants growing on saline soils are forced to activate different physiological and biochemical mechanisms that help them cope with the resulting stress, including changes in morphology, anatomy, photosynthesis, water relations, toxic ion distribution, and biochemical adaptation (A. Kumar & Bandhu, 2005;Rahneshan et al., 2018). The primary effect induced in plants by excessive soluble salts is to limit the ability of plant roots to absorb soil water, even under wet soil conditions (Munns et al., 2020). Soil water flows from a higher osmotic potential (low salt concentration) in plant cells to a low osmotic potential (high salt concentration) in the soil solution, causing symptoms like a drought effect (Munns et al., 2020). With the high concentration of soluble salts, the ratio of Na + to the major dominant ions, Cl − and SO 4 2− is less than 1 (Table 2). The preponderance of chloride and sulphate ions gives saline soils a brownish-white appearance (Wallender & Kenneth, 2012).
Saline soils have a good soil structure because excess soluble salts keep the clay particles in a flocculated state, which helps the particles cling together and initiate binding into aggregates that are usually porous and permeable (Wallender & Kenneth, 2012). Saline soils are the dominant salt-affectesoil class in Tanzania, although their curent extent and distribution are not very clear
Sodic soils
Sodic soils are denoted by a high concentration of exchangeable sodium ions (Na + ) in the soil exchange complex, where sodium ions (Na + ) compete with calcium (Ca 2 + ), potassium (K + ), and other cations and occupy more than 15% of the soil cation exchange capacity (CEC) (Richards & USDA, 1954). Sodium replaces other cations in the exchange complex, causing the dispersion of soil particles (Wallender & Kenneth, 2012), because the monovalent sodium cation has a weaker binding force compared to the divalent cations of calcium (Ca 2+ ) and magnesium (Mg 2+ ). The dominant cations in sodic soils are sodium (Na+), and the dominant anions are carbonate (CO 3 ) (Richards & USDA, 1954). The major challenge caused by excessive sodium is damage to the soil structure, accompanied by an increase in the compactness of soils and a decrease in infiltration, hydraulic conductivity, and oxygen availability in the root zone (Wallender & Kenneth, 2012). A high concentration of sodium increases soil pH (alkalization) through the presence of HCO 3 − and CO 3 2− (Leogrande & Vitti, 2019;Shahid et al., 2018). The forces that bind clay particles together are greatly weakened when excessive sodium comes between them, causing clay particles to expand, swell, and disperse (Wallender & Kenneth, 2012). The soil dispersion reduces the stability of soil aggregates, with the consequence of accelerating soil erosion (Gangwar et al., 2019). Sometimes sodicity is formed as a secondary effect where leaching has washed away soluble salts into the subsoil and left sodium bound to the negative charges of the clay (Wallender & Kenneth, 2012). Soil sodicity has detrimental effects on water permeability and soil aeration, water holding capacity, root penetration, seedling emergence, and microbial communities and their stable soil structure due to flocculation; usually porous and permeable (Chhabra, 2005;Osman, 2018;Wallender & Kenneth, 2012) Saline-sodic stable soil structure; good physical conditions of the soils (Chhabra, 2005) unstable soil structure; dispersed soil organic matter (Chhabra, 2005;Osman, 2018;Wallender & Kenneth, 2012) activity (Akhatar, 2019;Irakoze et al., 2021;Sheoran et al., 2021). Due to low soluble salts but high exchangeable sodium, the ratio of sodium ions to the sum of major anions is greater than 1 in sodic soils (Chhabra, 2005).
The extent of salt-affected soils reported by Mnkeni (1996) and FAO (2000) indicated a lower proportion of saline-sodic soil compared to saline and sodic soils in Tanzania. This is most likely because saline-sodic soils can turn into sodic soils after washing or leaching of soluble salts if sodium amendments are not made, thereby increasing the extent of sodic soils (Abate et al., 2021;C. Zhao et al., 2020).
Saline-sodic soils
Saline-sodic soils are the group of salt-affected soils having a combined effect of both salinity and sodicity (Alcívar et al., 2018;Wallender & Kenneth, 2012). These are considered to be highly degraded in terms of soil physical, chemical, and biological properties and hence least productive (Chaganti et al., 2015). Saline-sodic soils are more challenging in reclamation because separate treatments are required for both salinity and sodicity (Alcívar et al., 2018;Osman, 2018). The dominant cations in saline-sodic soils are sodium (Na + ), calcium (Ca 2+ ), magnesium (Mg 2+ ), and/or potassium (K + ), while dominant anions are chloride (Cl − ), sulphate (SO 4 2− ), bicarbonate (HCO 3 − ) and nitrate (NO 3 − ) (Richards & USDA, 1954). The proportionally high concentration of soluble salts (saline-sodic soil) keeps the colloids flocculated and well aggregated, but careless leaching of saline-sodic soils may cause dispersion, accompanied by degradation of soil structure and loss of water permeability (Osman, 2018), and the turning of saline-sodic soil into sodic soil. These soils are reported to be of limited extent in Tanzania, but they are also difficult to distinguish from sodic and saline soils by most soil users. This justifies the need to update the characterization of salt-affected soils in Tanzania.
Management of salt-affected soils
In order to ensure the sustainable reclamation of saltaffected soils, management options should be developed based on the type of salt-affected soil, degree of effect, and availability of site-specific amendment materials that are affordable by the farmers. Several advocated best-bet options can reverse salinity, sodicity, and saline-sodic effects in soils. However, most of the options take time to address the problems, and in every case, they are expensive. The best solutions to be used are dictated by the type of salt-affected soils and their gravity. The choice also depends on whether one is working in irrigation schemes with canals or on non-irrigated soils without canals. Depending on the situation, improving the efficiency of irrigation canals and drainage canals, capturing and treating salty drained water, and increasing the amount of water that gets into aquifers are prerequisites for the effective management of salt-affected soils. Use of soil amendments that improve infiltration and mulching to save soil water from evaporation losses can also help to manage the detrimental effects of salt-affected soils on crops. Details of best-bet options for the management of salt-affected soil are presented below.
Organic remediation
Research in various parts of the world shows that various forms of organic soil amendments, such as biochar, green manure compost, and municipal solid waste compost, improve the physical, biochemical, and microbial properties of salt-affected soils. These amendments can be used individually or in combination for the reclamation of degraded soils, especially salt-affected soils (El Hasini et al., 2019;M. Huang et al., 2019;Sheoran et al., 2021). Other researchers reported the combined application of green waste compost, sugarcane compost, and gypsum to reclaim saline soils (Diacono & Montemurro, 2015;El Hasini et al., 2019;Leogrande & Vitti, 2019).
The literature further shows that organic matters stimulate nitrogen mineralization in salt-affected soils by increasing organic matter solubilization (X. W. Wang et al., 2019). For example, Y. P. Singh, Mishra, et al. (2019) reported that the application of vermicompost at 10 t ha −1 saved 25% N without a significant reduction in the grain yield of rice and wheat in sodic soils.
In recent years, the application of biochar as an amendment for salt-affected soils has been reported and has attracted considerable attention from several researchers (A. Yang et al., 2020;Bin Yousaf et al., 2022;Kul et al., 2021;M. Singh et al., 2022;Phuong et al., 2020;Saifullah Dahlawi et al., 2017;Y. Sun et al., 2022), with emphasis on the improvement of the physical, chemical, and biological properties of salt-affected soils. Though numerous researchers reported positive results using biochar as an amendment for salt-affected soils, the efficacy is controlled by various factors such as temperature, feedstock, soil salt types, and biotic interactions (Almutairi et al., 2023;Freitas et al., 2020;H. Huang et al., 2021;Ippolito et al., 2020). The combined effects of these factors have an impact on the quality and performance of biochar (Kavitha et al., 2018). The high cost of production and high application rate are among the major constraints of using biochars for the amelioration of salt-affected soils (Saifullah Dahlawi et al., 2017). Organic amendments are therefore the solution for organic farming to improve soil physicochemical properties, enhance crop yield, and reduce greenhouse gas emissions (Amini et al., 2016;Fidel et al., 2019;Gunarathne et al., 2020;Kammann et al., 2017;Kubaczyński et al., 2020). Moreover, organic amendments help to improve soil aggregate formation and stability by binding the small particles in salinesodic and sodic soils to form large, water-stable aggregates (Diacono & Montemurro, 2015). Table 3 summarizes some of the reported amendment materials and their application rates across several countries.
Regardless of the good results reported on the use of organic amendments in the management of saltaffected soil, there is limited information available for Tanzania. Meliyo et al. (2016) recommended 3-8 tons/ha of farmyard manure (FYM) to boost soil organic matter and improve the infiltration rate, thereby accelerating the leaching of soluble salts down the root zone on clay soil. According to Makoi and Ndakidemi (2007), the use of FYM at 25 t ha −1 was adequate to improve the infiltration rate and available water capacity of sodic soils. However, the majority of small-scale farmers may not be able to obtain recommended quantities of FYM for salt-affected soil management unless alternative organic sources are considered (Makoi & Ndakidemi, 2007). Moreover, research results (Meliyo et al., 2016), at Ndungu Irrigation Scheme, Same District, show that locally available organic amendments like rice husk, rice straw, and sawdust incorporated in salt-affected soils 45 days before flashing are effective in improving soil infiltration, ECe, and yield comparable to gypsum. It was found that ECe dropped from 14 dS/m to less than 4 dS/m, which is appropriate for rice and many other crops, and this was attributed to improved infiltration that allowed proper flashing out of salts from the root zone.
Irrigation water quality and drainage infrastructure
The quality of irrigation water plays a vital role in sustaining the productivity of agricultural land (Awan et al., 2021;Prasad et al., 2022). It is common for irrigation water to contain some amount of salts; thus, depending on the frequency of irrigation and drainage conditions, salts brought into the field with irrigation water can accumulate over the soil surface with time (Mohanavelu et al., 2021). Based on global estimates, more than 20% of the irrigated area is affected by salinization induced by irrigation practices (M. Qadir et al., 2014). Numerous resources and strategies, including the use of non-saline or less-saline water for irrigation and the development of proper drainage facilities (artificial drainage), have been highlighted to reduce soil salinization in irrigation schemes (Liu et al., 2019;Mohanavelu et al., 2021). In most cases, the source of irrigation water is surface water, which along the pathway can dissolve salts from parent materials and transfer them to accumulate in the irrigation schemes (Shouse et al., 2010). Soluble salts can accumulate over the soil surface if the internal drainage is insufficient to drain the salts that are brought in with irrigation water (Connor et al., 2012). Among the management options for removing access salts from the topsoil layer is leaching with non-saline water. But if the water table is near the surface, like in humid and sub-humid areas, the leached salts can percolate below the plant root zone and lead to contamination of groundwater (Shahid et al., 2018).
In many cases, irrigation water in Tanzania is of good quality either without or with little dissolved salts at acceptable levels (Kashenge-Killenga et al., 2016). However, most irrigation schemes are found on the foot slopes of the Rift Valley Escarpment, which are characterized by high temperatures, most often on leeward sides, and hence unreliable or low precipitations. This is the case for all irrigation schemes in the Usangu plains, Lake Rukwa valley, Korogwe district in Tanga region, and Kilimanjaro region. Other areas are hinterland depressions or valleys equally characterized by high temperatures and low precipitation, including the Singida, Tabora, and Shinyanga irrigation schemes. These areas are characterized by poor leaching due to high water tables just near the soil surface, making salts accumulate over the surface. The problems are aggravated by poor irrigation infrastructure (canals without lining) and old canals without adequate renovation and close supervision (Meliyo et al., 2016). Nearly 90 percent of irrigation schemes had inadequate irrigation infrastructures, which increases the possibility of spreading salt concentration (Kashenge-Killenga et al., 2016).
Unfortunately, the country lacks up-to-date information on the extent of salt-affected soils in irrigated areas, so one can hardly specify the actual contribution of poor irrigation water quality and drainage infrastructures on soil salinization.
Planting salt tolerant crops
In salt-affected soil environments, salt-tolerant crops are an alternative coping mechanism. The ability of plants to grow and complete their life cycle in a harsh environment containing high concentrations of soluble salt is one of the ways to manage salt-affected soils (Irakoze et al., 2021;Manuel et al., 2017). Salt-tolerant crop varieties have been developed to sustain growth under osmotic effects, ion toxicities, and nutrient imbalance conditions (Manuel et al., 2017;Zhang & Dai, 2019).
The osmotic effect induces metabolic changes in the plant like those caused by water stress 'wilting' induced by drought (Chiconato et al., 2019;Munns & Gilliham, 2015). Some important sereal crops varieties (Table 4) tolerant to various levels of salt concentration, have been released but their tolerance varies with weather growth stages and crop species (Farooq et al., 2017; Figure 3. Systematic mechanisms of biochar interaction in salt-affected soil environment. Liang et al., 2017;Phogat et al., 2018). Maas (1993) developed a linear model to estimate a yield loss under the unit-increased salinity level beyond the threshold. The model explained that for any given crop, the relative yield loss (Y t ) for soil salinities exceeding the threshold can be estimated using the following equation: Where Y t is the relative yield; a is the salinity threshold expressed in (dS/m); b is the slope that represents the percentage of yield expected to be reduced for each unit of added salinity above the threshold; and ECe is the mean electrical conductivity of a saturated soil extract taken from the root zone.
Crop plants are more sensitive to salts during the early growth stages (at germination and seedling stages), but the degree of sensitivity differs critically between species and is more similar among the cultivars within similar species (Farooq et al., 2017). Crops naturally develop a large number of physiological and biochemical strategies to cope with salt stresses (Sharma et al., 2016;W. Wang et al., 2003;Zörb et al., 2019), but differ in their threshold levels (C. Zhao et al., 2020). Table 4 shows some cereal crops released for salt tolerance along with their tolerance level.
Salt-tolerant rice varieties, such as SATO 1 and SATO 9 (Kashenge-Killenga et al., 2016), were developed and released in 2016 as part of a soil salinity management strategy and can grow in a salt-affected soil environment. However, seed availability and adoption by the farmer are still slow because, although the variety is high yielding and grows well under salinity, it is a non-aromatic one, which is not in high demand in local markets. Additionally, the majority of farmers in Tanzania prefer rice varieties with high yield, early maturity, aromatic flavor, and hence high market value (Suvi et al., 2020). Thus, a rice breeding program must focus on meeting farmers' preferred traits to accelerate the adoption rate of newly released varieties. It is also important to caution that even salt-tolerant rice varieties have a threshold that they can cross, and hence the development of salt-affected soil reclamation technologies and/or integrated management options remains an important undertaking.
Inorganic amendments
Inorganic (chemical) amendments such as gypsum (CaSO 4 ) which provide a source of calcium (Ca 2+ ) that replaces the exchangeable sodium (Na + ) on the exchangeable sites, are commonly used to reclaim alkaline (sodic) soils. Gypsum application is one of the best-known methods for the reclamation of alkaline (sodic) soils (Bello et al., 2021;Lastiri-Hernández et al., 2019). In alkaline soil, Ca 2+ can replace a substantial amount of the exchangeable Na + from the exchange site, and subsequently, Na + combine with SO 4 2-to generate soluble salts that are leached out of the root zone via an irrigation water system (Sarwar et al., 2011). The ionic exchange reaction at the soil exchange site in alkaline soil is shown in Eq. ( 1). This reaction improves soil stability and permeability (i.e.increases soil porosity, oxygen availability, and infiltration capacity) while decreasing soil pH, EC, and ESP (Alcívar et al., 2018;Sarwar et al., 2011;Y. P. Singh, Mishra, et al., 2019). It also stimulates soil microbial activity and increases nutrient availability (Kim et al., 2018). For gypsum to be effective in the amelioration of saltaffected soil, adequate water should be available to irrigate the soil after gypsum application to enhance the quick leaching out of displaced Na + from the rhizosphere (Bello et al., 2021).(Hailu et al., 2020) Note: The tolerance level depends much on weather conditions, especially temperature and relative humidity.
Soil colloids at exchange site net
(2) Globally, several reclamation techniques have been recommended to reduce the negative impact of saltaffected soils by improving physical, chemical, and biological soil properties. However, limited information is available in Tanzania, where little research has been conducted to develop area-specific recommendations on the application rates for inorganic amendments.
The study conducted by Makoi and Ndakidemi (2007) revealed that the combination of farmyard manure (FYM) and gypsum at rates of 25 t ha −1 and 12.5 t ha −1 significantly reduced EC, ESP, and increased infiltration rate compared to the treatment of FYM and gypsum alone in sodic soil. Furthermore, it has been demonstrated that the integrated use of gypsum and various organic amendments improved the quality and productivity of alkaline (sodic) and saline-sodic soils through changes in soil properties (Alcívar et al., 2018;Bello et al., 2021).
Salt scraping
The scraping method involves removing the salt crust that has accumulated on the soil surface, particularly in saline-affected land (Endo & Kang, 2015). Salt scraping can be used to remediate saline soils if the dynamics of salt precipitation are taken into account (Shaygan & Baumgartl, 2022). Evaporation is the main factor influencing the upward movement of saltwater to the surface of the soil, while high rainfall events can leach salts deep into the soil profile (Shaygan & Baumgartl, 2022). The effectiveness of this method requires that the leaching process be followed to remove the remaining soluble salts (Endo & Kang, 2015).
Soil ripping
In most cases, sodic and saline-sodic soils have dispersive behavior (Shaygan & Baumgartl, 2022), which results in low soil porosity with massive structure and high soil strength, especially when dry, which prevents root extension; a low infiltration rate, resulting in waterlogging or perched water tables, which drowns roots; and poor movement of air into the subsoil, resulting in low oxygen availability to growing plants. In this situation, ripping technology can be used as a means to reduce soil compaction and accelerate salt leaching (Mageshen et al., 2022). It is, however, recommended to combine ripping with organic and inorganic amendments for long-term improvements in soil physical conditions (Endo & Kang, 2015).
Salt leaching
For the prevention of salt accumulation on the soil surface and in the root zone caused by evaporation and evapotranspiration, a significant amount of fresh water is required to overcome the rate of evaporation and evapotranspiration. A fraction of the applied water flow through the root zone and flush away the excess salts (Ebrahim Yahya et al., 2022). Therefore, the amount of water applied must be optimized to allow leaching without a water-table rise (Ebrahim Yahya et al., 2022). However, poor soil properties, such as low permeability, make this process ineffective (Xu et al., 2020). Without leaching, salts accumulate at the soil surface (Shaygan & Baumgartl, 2022) and can limit plant establishment.
Economic implications in reclamation of salt-affected soils
Estimation of the costs attributed to the reclamation of salt-affected soils is very heterogeneous due to different methodologies used in the assessment process, differences in soil types, the intensity of salinization, and the type of reclamation required (Munns & Gilliham, 2015). Yield loss is the most detrimental factor used to assess damage induced by salt-affected soils on a local scale (Thimmappa et al., 2016). The major economic cost of soil salinization is the reduced income to farmers caused by the reduced yield (Munns & Gilliham, 2015), which differs from one country to another and is largely influenced by the costs of inputs against the profit farmers can make in the seasons with average rainfall (Munns & Gilliham, 2015). At the farm level, net income decreases sharply with increasing salinity, which increases the cost of production (Thimmappa et al., 2016).
Consistent losses of crop yield caused by soil salinization as a result of climate change or the rising water table may alter the cropping system and make it impossible for crop production; ultimately, the land usage may revert to pasture production using salt-tolerant grasses or other species, including halophytes (Munns & Gilliham, 2015). Not only that, but farmers in saltaffected areas are also affected by food insecurity due to the devastating consequences of salt-induced costs in crop production (Haider & Hossain, 2013;P. Kumar & Sharma, 2020). According to M. Qadir et al. (2014), the global estimate of salt-induced costs due to crop failure in irrigated areas could reach US $27.3 billion, with an estimated cost of US $441 per ha of land (M. Qadir et al., 2014), and economic loss could be as high as the estimated values if the salinity levels increase without proper management (M. Qadir et al., 2014).
In Tanzania, low yields have been reported in most rice-producing irrigation schemes (Kashenge-Killenga et al., 2013;Makoi & Ndakidemi, 2007), and some of the farms have even been abandoned (Meliyo et al., 2016). The estimated area loss by salt-affected soils in irrigation schemes ranges from 5 to 25% for more than 70% of the schemes surveyed (Kashenge-Killenga et al., 2016). Similarly, the study conducted by Omar et al. (2022) based on farmers' views indicated that about 25% of the land in the surveyed irrigation schemes was salt-affected. On the other hand, yield losses in salt-affected areas range from 5-100% depending on severity levels and irrigation water availability (Kashenge-Killenga et al., 2016). Unfortunately, the cost induced by salt-affected soils has not been reported for Tanzania as a case study because the current extent of salt-affected soils is not well established and no cost estimations have been done. Nevertheless, despite the negative impact of saltaffected soils on agricultural systems, it was established that if successfully managed, land with salt-affected soils becomes productive again and can hence be used for crop production (M. Qadir et al., 2014).
Based on a few reviewed case studies for Tanzania, salt-affected soils have been reported to exist in different agro-ecologies but are more alarming in rainfed lowlands and irrigated areas. Climate change is becoming a critical factor that has a significant impact on soil salinity (Corwin, 2021). Climate change is expected to increase the frequency of extreme weather events, with unusually low precipitation, higher temperatures, higher potential evapotranspiration, and more frequent droughts in parts of the world (Malhi et al., 2021).
Similarly, to other Sub-Saharan African countries, climate change and population growth rates are major factors influencing food insecurity in Tanzania (Bjornlund et al., 2020). The challenge of climate change is expected to worsen the situation of food insecurity (Ires, 2021;Randell et al., 2022). For instance, the central and some parts of the northern highlands of Tanzania experienced moderate to severe drought (Mdemu, 2021;Verhoeve et al., 2021), which caused serious threats to water availability, food security, and local livelihoods (Mdemu, 2021). There is a potential for climate change to exacerbate the hazards of soil salinity, especially in arid and semi-arid regions (Eswar et al., 2021).
Climate change could accelerate the hazards of soil salinity, especially in arid and semi-arid regions, and has the potential to spread the problem in the near future to currently unaffected areas (Eswar et al., 2021). Under this scenario, areas affected by salt contamination become worse, and it needs attention for the future of agriculture and its ability to satisfy the growing food demand for the fast-growing population (Mukhopadhyay et al., 2021). Therefore, it is important to address the challenges caused by salt-affected soils (i.e.high osmotic stress, nutritional disorders, toxicities, poor physical soil conditions, and reduced crop productivity) promptly. Minimizing the negative effects of climate change and reclamation of salt-affected soils are among the critical solutions to future food security (Corwin, 2021). Thus, research focusing on the extent, types, and management options of salt-affected soils is critically important. Thus, understanding the salt-affected soils aerial extent, types, and severity for a specific area is of critical importance for developing effective management options.
Conclusion and the way forward
Salt-affected soils are a challenge to agricultural land and have a substantial impact on the sustainability of food and nutritional security. In the face of its severe impact in some parts of the world, it calls for intervention to ensure food sustainability. Thus, to fulfill the demand for food security at regional and national levels, appropriate information is a key factor in lessening salt stress on agricultural land and improving crop sustainability. This review aimed to explore the currently available data on salt-affected soils in Tanzania, including the distribution extent, types, origin, and what have been the coping strategies for sustainable farming under both irrigated and rainfed agro-ecologies. Soil salinity affects plant physicochemical properties, including increasing osmotic pressure and oxidative stresses, which adversely affect crop growth, yield, and quality. There have been various mitigation techniques developed to manage saltaffected soils around the world, such as the use of organic and inorganic amendments, phytoremediation, salt-tolerant microbes, land-shaping techniques, and salt-tolerant crops. It is imperative to note, however, that the effectiveness of each technique varies based on the soil's physicochemical properties, water availability, and the climatic conditions of a particular location. Additionally, the integration of leaching techniques and salt-tolerant varieties could be the most effective way to overcome salt stress challenges in Tanzania. In light of the conclusions above, it is recommended that comprehensive soil characterization studies be conducted to determine the extent (coverage) and the severity of the problem. In irrigated and lowland rainfed riceproducing areas, soil types should be classified and sources of salinization identified. Data from the above studies will be useful for guiding future research regarding the management options of salt-affected soils for the improvement of crop production. The information will also be used to predict the future impact of climate change on salt-affected soils as well as to develop affordable soil management options for reclaiming saltaffected soils.
Table 1 .
Classification of salt-affected soils based on ECe, ESP, SAR and pH values Saltand Kenneth (2012). Agricultural Salinity Assessment and Management.
Table 2 .
Characterization of salt-affected soils based on exchangeable ions
Table 3 .
Summary of reviewed amendments used to manage salt-affected soils in different countries
Table 4 .
Selected cereal crops released for salt-tolerance
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Domain: Agricultural And Food Sciences
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The Use of Image Analysis and Sensory Analysis for the Evaluation of Cultivar Differentiation of Freeze-Dried and Lacto-Fermented Beetroot (Beta vulgaris L.)
The aim of the research was to compare the possibility of distinguishing the cultivars of processed beetroots using image analysis technique and sensory evaluation. The differentiation of processed samples was tested for freeze-dried beetroot ‘Czerwona Kula’ and ‘Cylindra’, lacto-fermented beetroot ‘Czerwona Kula’ and ‘Cylindra’, freeze-dried lacto-fermented beetroot ‘Czerwona Kula’ and ‘Cylindra’. The textures from the images of quarters of root slices, as well as sensory attributes evaluated by expert sensory assessors, were determined. The differences in the means of selected textures from color spaces Lab, RGB and XYZ for different cultivars of raw and processed beetroots were observed. The raw beetroots ‘Czerwona Kula’ and ‘Cylindra’ were discriminated with the accuracy of up to 94.5% for models built based on selected texture from color space RGB. In the case of processed beetroots ‘Czerwona Kula’ and ‘Cylindra’, the accuracy reached 96% (color space Lab) for freeze-dried beetroots, 99% (color space Lab) for lacto-fermented beetroots, 98.5% (color space Lab) for freeze-dried lacto-fermented beetroots. In the case of sensory attributes, no statistically significant differences were observed between the beetroot samples.
Introduction
The beetroot (Beta vulgaris L. var. esculenta) is a very popular vegetable, not only in Eastern Europe but also all over the world (Sawicki et al., 2016). The beetroots have many uses in human nutrition. Particularly, it can be used in various forms, like a boiled in soup (traditionally borsch), fermented products especially juice and natural red colorants, e.g. to improve the color of sauces, tomato paste, desserts, jellies, jams, ice cream, cereals, sweets (Kaur and Singh 2014), as well as in dried forms like chips, powder in bakery and food supplements. In last year, the root of Beta vulgaris L. plant was considered as a functional health-promoting food (Chhikara et al. 2019;Clifford et al. 2015). The beetroot has active compounds such as betalains, carotenoids, polyphenols and flavonoids, and saponins (Kaur and Singh, 2014;Kowalski and Łechtańska 2015).
Freeze-drying is one of the methods of food preservation, the main goal of which is to inhibit the growth of microorganisms and significantly reduce any changes at the cellular level. It is extremely important to choose the right method of drying food products. In order to maintain high sensory properties of dried products, attention should be paid to the process conditions, i.e. temperature, humidity, air flow velocity, and the properties of the dried products (thermal resistance, structural and mechanical properties) and water diffusion capacity (Jayaraman and Das Gupta 2007;Figiel 2010;Kowalski and Szadzinska 2014). According to many authors, relatively the smallest losses of substances responsible for the sensory quality of the product, in particular aromatic compounds, both in terms of aroma typical and intensity, occur during freeze-drying (Rząca and Witrowa-Rajchert 2007;Kondratowicz and Burczyk 2010). Hoffmann (2007) used the high temperature of drying selected species of spice vegetables using the conventional method, and, through their freeze-drying, both methods caused undesirable changes in the sensory profile, including oxidation of aromatic compounds and the formation of foreign smell notes referred to as 'hay, dust'.
Freeze-drying is mainly used for processing fruit and vegetables due to the much better quality of the product compared to convection drying of these raw materials. On an industrial scale, this technique has found application in the production of instant coffee and spices. The main obstacles to its dissemination in the industry are economic reasons (high costs and long process time) (Piotrowski et al. 2008;Rząca and Witrowa-Rajchert 2007). In numerous publications, the authors inform about the laboratory use of freezedrying, among others for drying strawberries (Hammami and Rene 1997;Piotrowski et al. 2008), apples (Hammami et al. 1999), tomatoes (Georgé et al. 2011) or celery (Kozak and Lis 1999). Freeze-dried products are used as flavor additives and ingredients of such dishes as sweets, yogurts, sauces, dressings, instant soups. Color and flavor in the case of dried red beetroot are very attributes of quality affecting the degree of the product acceptability by the consumers (Sorour and El-Mesery 2014).
The aim of this study was to compare the possibility of distinguishing the cultivars of processed beetroots using objective image analysis technique and descriptive sensory evaluation. The study was carried out to determine the presence of textures from the images of quarters of root slices, which allow for cultivar discrimination of beetroot. The sensor attributes that differentiate beetroot cultivars were assessed.
Material
The beetroots belonging to cultivars 'Czerwona Kula' and 'Cylindra' were used in the experiments. The beetroots were purchased from the manufacturer in central Poland. The beetroots 'Czerwona Kula' were characterized by the round shape, whereas the beetroots 'Cylindra' were cylindrical and elongated.
The raw, freeze-dried, lacto-fermented and freeze-dried lacto-fermented beetroots were tested. In the case of tests involving the raw and freeze-dried samples, the roots were washed and peeled and then were cut into slices about 5 mm thick. Additionally, each slice was cut into quarters. The one hundred samples of each cultivar prepared in this way were immediately subjected to the research using image analysis. And part of the material was intended for freezedrying. Firstly, the quarters of root slices were frozen in the laboratory freezer at a temperature of − 29 ± 2 °C for 3 days. The freeze-drying was carried out for 53 h including 24 h without heating, 24 h at a temperature of 0 °C and 5 h at a temperature of 30 °C. The final pressure was 0.030 mBar.
The other part of beetroots was subjected to lacto-fermentation. The beetroots were washed, peeled and then cut into slices and put into 1300-ml sterile glass jars with standard spices used in fermentation (garlic, horseradish, dill). The jars were filled with potable water. The table salt was added to the final concentration of NaCl in 3.5% brine. The lactic fermentation process was carried out in agreement with the current standard procedures. Elkner (2004) reported that a temperature of about 20 °C was recommended for the initial phase of fermentation. At this temperature, bacteria peptize (protein breakdown), and bacteria of the genus Aerogenes develop, and then lactic acid bacteria acidify the environment. The fermentation process may be slowed down by gradual lowering of temperature-the temperature of 11 °C ± 1 °C is recommended for this stage. The carbon dioxide can dissolve more easily in the brine at this temperature. The fermentation process should proceed slowly, to be correct, and the lactic acid content in products should reach 0.7% after 30-40 days. To fulfill these requirements, in the experiment, fermentation was conducted for 3 days at a temperature of 20 °C, then for the next 10 days at 13.5 °C ± 1.5 °C and finally at 5 °C for 30 days. After stopping fermentation, part of the samples was subjected to tests, and others were used for freeze-drying using the parameters which were applied for the raw material.
Image Analysis
The quarters of slices of raw, freeze-dried, lacto-fermented and freeze-dried lacto-fermented beetroots belonging to different cultivars 'Czerwona Kula' and 'Cylindra' were imaged using a flatbed scanner. Before placing on the scanner scene, the samples were drained of excess water using a paper towel, if necessary. The scans were obtained on the black background at a resolution of 800 dpi and saved in TIFF format. The tests were performed in one hundred repetitions for each cultivar (800 samples in total). These were acquired: -one hundred images of quarters of slices of raw beetroot 'Czerwona Kula', -one hundred images of quarters of slices of raw beetroot 'Cylindra', -one hundred images of quarters of slices of freeze-dried beetroot 'Czerwona Kula', -one hundred images of quarters of slices of freeze-dried beetroot 'Cylindra', -one hundred images of quarters of slices of lacto-fermented beetroot 'Czerwona Kula', -one hundred images of quarters of slices of lacto-fermented beetroot 'Cylindra', -one hundred images of quarters of slices of freeze-dried lacto-fermented beetroot 'Czerwona Kula', -one hundred images of quarters of slices of freeze-dried lacto-fermented beetroot 'Cylindra'.
The images of beetroot samples were analyzed using the Mazda software (Łódź University of Technology, Institute of Electronics, Poland) (Szczypiński et al. 2009). The color conversion of images to channels L, a, b, R, G, B, X, Y and Z was performed. Afterward, the region of interest (ROI) including the surface of the quarter of the slice for each sample was determined. Then, approximately two hundred texture parameters of the outer surface of the quarter of the slice based on the run-length matrix, co-occurrence matrix, histogram, autoregressive model and gradient map were calculated for each ROI (Szczypiński et al. 2009).
Sensory Evaluation
Sensory assessment of freeze-dried, lacto-fermented and freeze-dried lacto-fermented beetroots was carried out in the (c) Fig. 1 The means of selected textures from color space Lab including (a) texture from color channel L, (b) texture from color channel a, (c) texture from color channel b for images of quarters of slices of raw beetroot 'Czerwona Kula' and 'Cylindra'. SEM standard error of the mean sensory laboratory, which met all the requirements set out in the standard PN-ISO 8589 (Sensory analysis-General guidelines for designing a laboratory for sensory analysis). At all stages of the sensory analysis, the individual evaluation stations were used equipped with the specialized software-program ANALSENS designed for preparing tests, recording individual scores and statistical processing of the results. The sensory evaluation is performed by a 10-person panelist whose members have obtained a certificate of completion of training in the field of sensory sensitivity verification and methods used in the sensory analysis of food products. The certificate was issued by a company dealing with training in the field of sensory analysis of food and water products-J. S. Hamilton Ltd. using the quantitative description analysis (QDA), conducted in accordance with the procedure included in the standard Sensory Profiling ISO 13299:2016. Due to the sensory properties of raw samples of tested beetroot cultivars, which were unacceptable to consumers, the sensory evaluation for raw beetroots was not performed. The sensory quality of products was evaluated for odor, color, texture and taste. Firstly, the brainstorming sessions were run to select attributes for the beetroot products. The assessments for each descriptor were marked on unanchored lines, with anchoring points (low-high intensity of impression). Results were presented in numerical values (0-10), where the starting point of the line was assigned the value zero and the ten centimeters (end of the line) (Table 1).
Each analysis was carried out in two sessions, so the results represent the mean of these sessions.
Statistical Analysis
The statistical analysis for texture parameters was performed with the use of the STATISTICA (StatSoft Inc., Tulsa, USA) software and the WEKA (University of Waikato) (Bouckaert et al. 2016). The STATISTICA (StatSoft Inc., Tulsa, USA) software was used to visualize differences in selected textures between beetroot cultivars. The graphs including the means with standard error of each mean (SEM) were prepared. The discriminant analysis was performed using the WEKA application to develop the models for the cultivar differentiation of beetroots. The analyses were performed separately for (i) raw beetroot 'Czerwona Kula' and 'Cylindra', (ii) freeze-dried beetroot 'Czerwona Kula' and 'Cylindra', (iii) lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra', (iv) freeze-dried lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra'. The models including the sets of selected textures from color spaces Lab, RGB and XYZ were developed. Firstly, the attribute selection using the Best First with the CFS subset evaluator was carried out separately for individual color spaces. Due to this step, the texture parameters with the highest discriminative power were selected for building the discrimination models. The beetroots belonging to cultivars 'Czerwona Kula' and 'Cylindra' were discriminated using tenfold crossvalidation mode and the Random Forest classifier from the group of Decision Trees, Logistic from Functions and PART from Rules (Witten and Frank 2005). The average accuracies and accuracies for each cultivar were determined. The ANALSENS software was used to analyze the results of the sensory evaluation. The significance of differences between results was estimated using a nonparametric Mann-Whitney U test (p = 0.05). The medians were calculated.
Raw Beetroot
The mean with SEM (standard error of the mean) was determined for selected textures from color spaces Lab, RGB and XYZ. The results are presented in the form of graphs comparing the values for two beetroot cultivars. Only exemplary texture parameters were included in the figures, but the differences in the means were determined for many other textures. The means with SEM for selected textures from each color channel from the color space Lab are shown in Fig. 1. The cultivar differentiation is noticeable for each presented texture. The samples of raw beetroot 'Czerwona Kula' were characterized by the lower values of texture LHMean from color channel L (Fig. 1a), aHMean from color channel a (Fig. 1b) and bHMean from color channel b (Fig. 1c), whereas the higher values were observed for beetroot 'Cylindra'. In the case of images of quarters of slices of raw beetroot 'Czerwona Kula', the lower means of selected textures from color space RGB including texture RHMean from color channel R (Fig. 2a), GHMean from color channel G (Fig. 2b) and BHMean from color channel B (Fig. 2c) were noted. Figure 3a) The raw beetroot 'Czerwona Kula' was also characterized by the lower means that 'Cylindra' of selected textures from color space XYZ: texture XHMean from color channel X (Fig. 3a), YHMean from color channel Y (Fig. 3b) and ZHMean from color channel Z (Fig. 3c). The differences in texture parameters between beetroot cultivars allowed for the discrimination of 'Czerwona Kula' and 'Cylindra' with very satisfactory accuracies. In the case of raw beetroot for all developed models, the average accuracies were above 90% ( Table 2). The highest correctness equal to 94.5% was observed for the model built based on textures from color space RGB for the PART classifier. The images of quarters of slices of beetroot 'Czerwona Kula' were correctly classified in 96% and 'Cylindra'-93%. It indicated that 96 from 100 cases (quarters of slices) 'Czerwona Kula' were included in the class 'Czerwona Kula' and 4 cases in the class 'Cylindra', whereas 93 cases of 'Cylindra' were classified as 'Cylindra' and 7 cases-as 'Czerwona Kula'. The values of TP Rate, Precision, F-Measure, ROC Area and PRC Area were also very high and were above 0.9. In the case of color space RGB, the high results were also obtained for the Random Forest. The average accuracy was equal to 94% and accuracies for individual cultivar 96% for 'Czerwona Kula' and 92% for 'Cylindra'. The average accuracy of 94% was also determined for the model built based on textures selected from color space Lab for the Random Forest. In this case, the accuracy for 'Czerwona Kula' was equal to 97% and for 'Cylindra' was 91%. The lowest average accuracies of up to 93% (95% for 'Czerwona Kula', 91% for 'Cylindra') were observed in the case of models built for color space XYZ.
Freeze-Dried Beetroot
The means of one selected texture for each color space are presented in Fig. 4. The differences between cultivars of freeze-dried beetroot were determined. Freezedried beetroot 'Czerwona Kula' had the lower values of texture LHMean from color channel L from color space Lab (Fig. 4a), texture RHMean from color channel R from color space RGB (Fig. 4b) and texture XHMean from color channel X from color space XYZ (Fig. 4c). The freeze-dried beetroot 'Cylindra' was characterized by the higher means of these textures. Data not presented in the graphs indicated that also there were differences between the cultivars for other textures.
The presence of textures with different means between freeze-dried beetroot 'Czerwona Kula' and 'Cylindra' resulted in high accuracies of cultivar discrimination. The average accuracies were very high and reached 96% for color space Lab and the Random Forest classifier (Table 3). The freeze-dried beetroot 'Czerwona Kula' was correctly classified in 97%, and 'Cylindra' was correctly included in class 'Cylindra' in 95%. Also, the values of TP Rate, Precision, F-Measure, ROC Area and PRC Area were the discrimination performed using the selected textures from color space Lab and Random Forest. Slightly lower results were obtained for the models built based on textures from color spaces RGB and XYZ. In the case of color space RGB, the average accuracy reached 93% for Random Forest (95% for 'Czerwona Kula', 91% for 'Cylindra') and 93% for Logistic (93% for 'Czerwona Kula', 93% for 'Cylindra'). For color spaces XYZ, the average accuracy was equal up to 94% for Random Forest (96% for 'Czerwona Kula', 92% for 'Cylindra').
Lacto-Fermented Beetroot
The means of textures of images of quarters of slices were different between lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra', for example, for LHMean from color space Lab (Fig. 6a), RHMean from color space RGB (Fig. 6b) and XHMean from color space XYZ (Fig. 6c). The values of these textures were lower for 'Czerwona Kula' than for 'Cylindra'.
The discriminant analysis of the lacto-fermented beetroot revealed very high accuracies. The cases of beetroot 'Czerwona Kula' and 'Cylindra' were distinguished with the correctness of up to 99% in the case of models built based on textures selected from color space Lab for the Random Forest and Logistic classifiers (Table 5). In the case of the Random Forest, the lacto-fermented beetroot 'Czerwona Kula' was discriminated with an accuracy of 100%. It means that all cases of beetroot 'Czerwona Kula' were correctly classified as 'Czerwona Kula'. The accuracy for beetroot 'Cylindra' was equal to 98%. The values of TP Rate for 'Czerwona Kula', Precision for 'Cylindra', as well as ROC Area and PRC Area for 'Czerwona Kula' and 'Cylindra' reached 1.000. In the case of the Logistic classifier, both cultivars were classified with accuracies of 99%. It means that 99% of cases of 'Czerwona Kula' were included in class 'Czerwona Kula' and 1% in class 'Cylindra', and 99% of cases of 'Cylindra' were classified as 'Cylindra' and 1% as 'Czerwona Kula'. The values of the ROC Area and PRC Area were equal to 1.000. The average accuracies for color spaces RGB and XYZ were slightly lower and reached 95% (Random Forest, PART) and 93% (Random Forest, PART), respectively.
The results of the sensory quality of the lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra' are presented in Fig. 7 and Table 6. The beetroot smell, beetroot fermented smell, sweet smell, off-odor, beetroot color, color attractiveness, hardness, crunchiness, beetroot taste, fermented beetroot taste, sweet taste, bitter taste, off-flavor taste and overall quality were evaluated. There were no significant differences between samples.
Freeze-Dried Lacto-Fermented Beetroot
The values of selected textures from color spaces Lab, RGB and XYZ were different between freeze-dried lactofermented beetroot 'Czerwona Kula' and 'Cylindra'. The means of LHMean from color space Lab (Fig. 8a), RHMean from color space RGB (Fig. 8b) and XHMean from color space XYZ (Fig. 6c) were lower for 'Czerwona Kula'. The freeze-dried lacto-fermented beetroot 'Cylindra' was characterized by the higher values of these texture parameters. The samples of freeze-dried lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra' were distinguished with an average accuracy of up to 98.5% in the case of textures of images of quarters of slices from color space Lab for the Random Forest and Logistic (Table 7). In the case of both classifiers, the accuracies for individual cultivars were equal to 99% for 'Czerwona Kula' and 98% for 'Cylindra'. The average accuracy for the models built based on textures selected from color space RGB reached 93.5% for the Random Forest classifier. In the case of color space XYZ, the Table 6 The results of the sensory evaluation of lacto-fermented beetroot and freeze-dried lacto-fermented beetroot (a scale of 0 to 10 points) Medians (Me) in the column for cultivars and treatments are not different according to the Mann-Whitney U quarters of slices of freeze-dried lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra' discriminated with the correctness of up to 93% for the Random Forest. The sensory profiling based on beetroot smell, beetroot fermented smell, sweet smell, off-odor, beetroot color, color attractiveness, hardness, crunchiness, beetroot taste, fermented beetroot taste, sweet taste, bitter taste, off-flavor taste and overall quality of freeze-dried lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra' is shown in Fig. 9 and presented in Table 6. The sensory assessment of beetroot showed no significant differences between cultivars and treatments.
The consumer's visual sensory perception of food can influence other sensory perceptions such as taste, smell and texture. Literature data confirm that when assessing the taste and smell of a product, the consumer is suggested by its appearance, e.g. color, and its loss or unfavorable change is associated with the deterioration of other sensory features (Walkowiak-Tomczak and Czapski 2007;Walkowiak-Tomczak et al. 2016;Herbach et al. 2007). Several factors directly determine the appearance of the product-the raw material, the used technology and the storage conditions. The effect of processing on the physicochemical and sensory properties of beetroot was reported by Nistor et al. (2017) and Tomic et al. (2020). In our study, the effect of cultivar on raw and processed beetroots was evaluated. The different processing techniques may affect beetroots differently depending on the cultivar. Cultivar differentiation may be more or less evident in different parameters of beetroots. Therefore, the appropriate technique for distinguishing the cultivars of beetroots should be chosen. The image analysis based on textures was useful for the discrimination of cultivars of raw and processed beetroots with a high probability. The (c) Fig. 8 The means of selected textures from color space Lab for color channel L (a), color space RGB for color channel R (b), color space XYZ for color channel X (c) for images of quarters of slices of freeze-dried lacto-fermented beetroot 'Czerwona Kula' and 'Cylindra'. SEM standard error of the mean sensory evaluation provided only small differences in attributes of processed beetroots. Therefore, the objective procedure, for example, using image analysis may be more desirable for distinguishing the cultivars of processed beetroots than descriptive sensory evaluation.
Conclusions
The cultivar differentiation of beetroots was studied using image analysis and descriptive sensory evaluation. The possibility of distinguishing the beetroot cultivars based on texture parameters of images of raw and processed samples and sensory attributes of processed beetroots was compared. The presence of textures from the images of quarters of root slices allowing for cultivar discrimination of beetroot was proved. The models built based on selected textures provided a very high discrimination accuracy of up to 99%. The differences in sensory attributes were very small, and their usefulness for distinguishing the beetroot cultivars may be minimal. Therefore, the objective techniques may be more useful in practice for the cultivar discrimination of raw and processed beetroots.
Data Availability Not applicable.
Code Availability Not applicable.
Declarations
Ethics Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Consent to Participate
Informed consent was obtained from all individual participants included in the study.
Conflict of Interest
Ewa Ropelewska declares that she has no conflict of interest. Anna Wrzodak declares that she has no conflict of interest.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [URL]:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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Domain: Agricultural And Food Sciences
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DEVELOPMENT OF RESEARCH-BASED BIOLOGICAL MODULES ON CHARACTERISTICS OF LEAVES EPIDERMIS AND ITS DERIVATIVES OF Solanum lycopersicum var. Cerasiforme and Solanum lycopersicum cv. Ranti FOR HIGH SCHOOL STUDENTS
The study aimed to determine the feasibility of the modules developed for class XI learning on the structure and function of plant tissues based on the results of research on the characteristics of the epidermis and epidermal derivatives of cherry tomato leaves and rose tomato leaves. The research was carried out in two stages. The first was exploratory research carried out by taking samples in the form of cherry tomato leaf organs and rose tomato leaves. Preparation of cherry tomato leaf and rose tomato leaf preparations using the leaf clearing method, observation with optilab-raster image application. Research data were analyzed descriptively. The second stage was preparing modules on the structure and function of plant tissue as biology teaching materials for class XI using the ADDIE development model, which was limited to ADD. Module quality data was collected using a data collection instrument in the form of a product assessment questionnaire. The average result of product evaluation by material experts is 82.14%, and media experts are 84.37%. Based on the results of this assessment, the module on the structure and function of plant tissue is feasible to be used for testing as high school biology teaching materials.
INTRODUCTION
Biology is a branch of science with the object of studying living things and covering all aspects of life.
Biology as a subject with special aspects and characteristics requires unique methods and strategies to achieve learning objectives (Sari & Ma'rifah, 2020). Learning is a process of teaching and learning activities that occur between students and teachers. In the learning process, there is intense interaction between students and teachers. Students are the main actors (subjects) of learning, while the teacher is a facilitator who accompanies students in achieving the desired learning goals.
The main problem that is often faced by education in schools is the weak mastery of the material by students, including in biology subjects and the lack of teaching material facilities that contain real images as learning media that can assist teachers in conveying material. Success in the learning process is supported by several factors, namely the availability of teaching materials, methods and approaches used by the teacher in learning (Hala et al., 2015). The teacher is not the only source of knowledge for students but rather as an indispensable facilitator, namely by creating a learning environment that is able to encourage students to be happy and excited to learn. One way that teachers can do this is by varying teaching materials as learning materials that can attract students' attention to read them (Yusa et al., 2023) .
Teaching materials are a collection of various learning resources that are systematically arranged for learning purposes (Nuryasana & Desiningrum, 2020). Teaching materials are an important part in determining the quality of learning. The design of developing teaching materials needs to pay attention to the development model to ensure the quality of teaching materials in supporting the effectiveness of learning, because the development of teaching materials is basically a linear process with the learning process (Cahyadi, 2019). Teaching materials developed effectively to improve student learning outcomes (Wulandari et al., 2017). The function of teaching materials for educators is to improve the learning process to be more effective and interactive. The role of teaching materials for students is that they can learn at their own pace (Prastowo, 2015). Teaching materials are needed in all subjects in school, especially biology.
Based on the interview conducted by researchers with teachers at Muhammadiyah 4 Yogyakarta High School, information was obtained that there was still a lack of additional references to accompany textbooks in learning biology. The books used do not present many pictures of the anatomical structures of tissues in plants, so they are not varied enough to provide explanations to students. Studies related to the characteristics of the epidermis and epidermal derivatives from cherry tomato and rose tomato leaves can be used to add information regarding the importance of knowledge of plant tissue material. The teaching materials were less varied, especially biology teaching materials.
Regarding the difficulties in learning plant tissue material at Muhammadiyah 4 Yogyakarta High School, the teacher stated that there was still a lack of pictures in the textbook, especially plant tissue material, to provide a real example to students. There were limited facilities from laboratories in schools, so students could not do practical work on plant tissue material. There are no module teaching materials regarding plant tissue material other than textbooks that can help the in-class learning to improve understanding and learning outcomes by using teaching materials. Well, one of the teaching materials that can be developed is modules. Learning using modules aims to increase the efficiency and effectiveness of learning in schools. Modules are printed teaching materials designed so students can study them independently (Ariana et al., 2020).
One way to improve understanding and student learning outcomes namely by developing teaching materials Good. One of the teaching materials that can be developed is a module (Setiyadi et al., 2017). Learning modules are teaching materials that are arranged in a systematic and interesting manner that include content, methods and evaluations that can be used independently to achieve the expected competencies (Nafaida et al., 2015). In the world of education today, there are two types of modules that are currently being developed, namely electronic modules and printed modules. Each of these module types has its advantages and disadvantages (Puspitasari, 2019). The modules are structured to be supplementary teaching material equipped with attractive pictures and clear information to complete a high school biology textbook for class XI. One of the goals of preparing modules is to provide teaching materials that are following the demands of the curriculum by taking into account the needs of students, namely teaching materials that are under the characteristics of teaching materials and the characteristics of students .
The field of study aspects listed in the 2013 curriculum in KD 3.3 with plant tissue sub-material. The research results are adapted to KD 3.3 class XI, namely analyzing the relationship between cell structure in plant tissues and organ functions in plants and KI 4.3 presenting data from observations of the structure of tissues and organs in plants.
METHODS
The research was carried out through the first two stages: an exploratory analysis by taking samples from cherry tomato leaf organs and rose tomato leaves. Preparation of cherry tomato leaves and rose tomato leaves using the leaf-clearing method. Observations were performed using optilab, through the image raster application. Research data were analyzed descriptively. The second stage was the preparation of teaching materials based on the research results, then studying their potential as a source of biology learning and arranging into biology teaching materials in the form of modules.
Time and Location of Research
This research was conducted in the Salam Garden Gg. Mayang V Pringgolayaan, Banguntapan, Bantul, DIY. The cherry tomato and rose tomato leaf samples were observed at the Laboratory of Campus 4 of Ahmad Dahlan University.
Data Collection Technique
Data collection techniques used in this research are documentation, observation, unstructured interviews, and product validation instruments. Documentation using the instrument is a document guide containing the required data categories. Observations were made to discover the physical condition and potential of the cherry tomato and rose tomato plants. Interviews were conducted with biology teachers to obtain in-depth information regarding the unknown problems and needs of the school. The validator validated the questionnaire sheet to determine the feasibility of the module product that the researcher had designed.
Tools and Materials
The tools and materials used in exploratory research were scissors, a camera, dropper, brush, object glass, cover glass, flacon bottles, optilab, bunsen, tweezers, binocular microscope, tweezers, and stationery, laptops, and editing applications (Canva). Samples used in this study were taken from cherry tomato and rose tomato leaves, chloralhydrate and distilled water (5: 2).
Research Procedure
The working procedure in this research are: 1. Exploration Research Stage a. Preparation for observing the location of the research site b. Leaf samples were taken in 2-3 pieces, and the leaves were taken by counting from the top to the 4th leaf. Leaf samples were cut 1 cm in length (tip of leaf, edge of leaf and middle of leaf).c. The observed morphological characteristics of the cherry tomato and rose tomato plants were plant length, leaf length, and leaf width.d. Leaf preparation e. Observation of preparations was observed using optilab, at 100x and 400x magnification with a specific field of view, then the structures of the epidermis, stomata and trichomes were seen.
Module Development Stage
The research results were arranged into teaching materials in modules. The analysis of the potential of teaching materials refers to books (Suhardi, 2012)
Development
The teaching material products that have been printed are then validated by experts, namely material experts and media experts. Module assessment is done by filling in the validation instrument that the researcher has prepared. The results of teaching material validation are used as product improvements assessed by the validator so that these modules can be used as biology teaching materials for plant tissue material Data Analysis Technique 1. Descriptive Analysis Data were analyzed descriptively by interpreting or describing essential elements, such as the shape of the epidermis, the number of epidermal cells, the length and width of the epidermis, the type of stomata, the length and width of stomata, stomata index, the number of stomata, the shape of trichomes, the type trichomes, length and width of trichomes and a number of trichomes in cherry tomato and rose tomato leaf organs.
Analysis of Module Product Validation Data by Material Experts and Media Experts
The assessment of teaching material uses a Likert scale to measure the validator's opinion of teaching materials.
RESULTS AND DISCUSSION Exploratory Research
This study focused on leaf organs to observe their morphology and anatomy. The leaf morphology section measured the length and width of the leaf. After being observed as a whole, the leaves of cherry tomatoes and rose tomatoes have similar similarities, namely, green leaves fluffy. The leaf edges are notched pinnate (pinnatilobus), which follow the pinnate arrangement of the bones, with the tip of the leaf being pointed (acutus) and the base of the leaf being blunt (obtusus) and flat (truncatus). The foliolum of tomato includes pinnate compound leaves with an odd number of children, compound leaves where the children are on the right and left of the mother petiole and one leaf covering the tip of the mother stalk (Tjitrosoepomo, 2013). The following is a morphological picture of the cherry tomato and rose tomato leaflet. The epidermis on the leaves has several modified appendages; the leaf epidermis's derivatives include stomata and trichomes. Stomata are pores or holes in the epidermis, each of which is bounded by two guard cells or covering cells (Sutrian, 2011). Based on the results of research on the shape of the stomata on the leaflets of cherry tomatoes and rose tomatoes, they belong to the anisocytic type, with the characteristic of guard cells being surrounded by three neighboring cells, one of which is smaller than the other two cells. This research is important to do to broaden students' insights in learning about the structure and function of plant tissues, especially the epidermis and epidermal derivatives. The needs of students are analyzed before determining the teaching materials to be made, aiming to see the possible causes of existing problems and the student's basic needs. Otilia (2020) reveals that needs analysis is the foundation for developing curriculum content, teaching materials and teaching methods that can increase student motivation and success. The results of the analysis of the needs of students are that they need practical teaching materials that contain solid, concise and clear material coverage so that they motivate students to study in class or study independently.
The next stage enters the Design stage. The researcher collected references and pictures taken from class XI high school plant tissue material at this stage. References for b a the material were from journals, textbooks on plant anatomy, textbooks for class XI high schools, results from research on the epidermis and epidermal derivatives of cherry tomato leaves and rose tomato leaves and biology websites in preparing the module using the Canva application, because the Canva application is a graphic design platform that can be used for free and easily The Canva application has a variety of attractive designs. It is able to increase teacher creativity in designing learning media because many features are provided, saves time in practical learning media, and is easy to develop attractive materials without device limitations (Tanjung & Faiza, 2019). The results of the module arrangement are then printed using 210 gr glossy side paper as the cover and 100 gr glossy side paper as the module's contents by finishing the middle staples module. The following shows a module design display using Canva (Figure 5). At this stage, it is the process of printing the module teaching materials that have been designed. The results of the modules that have been designed are developed based on existing references (Neno et al., 2022). This stage also assessed the module product, which aims to see its feasibility as a class XI biology teaching material on plant tissue material. The module assessment instrument is prepared based on the criteria for evaluating teaching materials by the National Education Standards Agency (BSNP), which is adjusted to the characteristics of the module. The aspects assessed are content feasibility, content presentation, language feasibility, and graphic feasibility. This module is assessed by two validators, material experts and media experts, by providing the assessment parameters on the instrument sheet. Based on table 1, the results of the assessment by experts material for the module, there are two aspects: the feasibility of the content and language. The feasibility aspect of the content gets an assessment percentage of 87.5% in the excellent category. The linguistic element gets a rating percentage of 75% in the outstanding category. The items for assessing the linguistic aspect are the readability of the language, the consistency and accuracy of writing terms/scientific names/symbols and words/sentences used following excellent and correct grammar per EYD. The opinion supports this (Nurlaili, 2011) the use of clear sentence structures can make it easier for students to understand messages from teaching materials. The results of the media expert's assessment are as follows (table 2). Based on table 2, the assessment results by media experts on the module, there are two aspects: the feasibility of presentation and graphics. The presentation feasibility aspect gets a rating percentage of 91.67% in the excellent category. The graphical element gets a rating percentage of 80% in the excellent category. The following is the result of a recapitulation of the results of the assessment of material and media expert namely as follows (table 3).
Table 3. Expert recapitulation results materials and media experts
Recapitulating the assessment results of material experts and media experts, the module teaching material products get an average score of 83.25% in the excellent category with revisions. According to Darmawan & Nawawi (2020), 81% -100% is categorized as very suitable for testing with revisions. The action taken by the researcher after getting an assessment and input from the validator was to improve the module teaching material product. Biological module products for plant tissue material that have been designed need revision to perfect the final results of the module to produce a better module product than before (Lubis et al., 2015).
Developed module each has special characteristics activities are highly stressed group collaboration and internal discussion find concept. This agrees with (Budiono & Susanto, 2006) which posited that the most way good at using the module is students actively learn together with friends in a group, temporarily the teacher checks intensive and provide assistance to students who have difficulty in learning module individually. Following are some of the results of the module product which has been revised (Sawitri & Ambarwati, 2014). Figure 6. Some parts of the resulting module.
CONCLUSION AND SUGGESTIONS
Module teaching materials compiled based on the results of research on the characteristics of the epidermis and epidermal derivatives of cherry tomato leaves and rose tomato leaves were declared suitable for testing as biology teaching materials for class XI on plant tissue material.
Suggestions for further research because the module only reaches the development stage, it is necessary to implement or try out the use of plant tissue material modules for class XI high school students in several different schools.
Figure 2 .
Figure 2. a. Epidermal form cherry tomato leaves.b. Form epidermis of rose tomato leaves.
Figure 5 .
Figure 5. Display of module design using the canva app
Table 1 .
Results of material expert assessment
Table 2 .
Media expert assessment result
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Domain: Agricultural And Food Sciences
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Design and Development of Self-Made Cost-Effective Microsoft Excel Visual Basic Application for Livestock Ration Formulation
One of the most important aspects of the livestock sector is ration cost optimization, which results in profit and ideal animal health. Manually preparing rations is time consuming and unsafe. Whereas computers can quickly formulate a ration that meets all of the nutritional requirements, after giving standard data on feeds. However, the existence of the ideal computer programme is questionable; if it exists, it is more expensive, less user-friendly, exclude local feeds, be limited to a particular region/country, feed composition may differ. As a result, in this chapter, the user will learn how to create and develop a self-made least-cost ration formulation using the locally available feeds, so that user may easily build their computer Programme using Visual Basic application of Microsoft Excel. There are three phases to ration formulation for any animal (ruminant or non-ruminant). The first phase requires the user to know the available feeds and their nutrient composition. The second part involves determining which nutrients are important for animals and creating nutrient equations. The third phase involves the creation of a linear programming model. Finally, the interface is being designed. Each phase is thoroughly explained in excel, with suitable data and reference coding.
Introduction
The primary goal of ration formulation in animal production is to offer a balanced diet that supports physiological functions such as growth, maintenance, reproduction, and lactation while also providing energy for physical and metabolic activity [1]. A standard and efficient feed formulation must include all the classes of feedstuffs (Animal Nutrition Group, India) [2] as provided in Figure 1.
A concentrate is a feed or feed mixture that provides increased levels of primary nutrients (protein, carbohydrates, and fat) while containing less than 18 percent crude fiber (CF) and low moisture. These are high in nitrogen-free extract (NFE) and Total Digestible Nutrients (TDN) and low in crude fiber [3]. There are classified into two categories: energy-rich concentrates and protein-rich concentrates, based on the content of crude protein (CP). When the crude protein content of dry concentrates is less than 18 percent, they are categorized as energy-rich concentrates, and when the CP value is greater than 18 percent, they are defined as protein-rich concentrates [4,5].
Roughages are heavy foods that contain substantially less digestible material, such as crude fiber greater than 18% and a low TDN content (about 60%) on a dry basis. Roughages differ in the level of protein, mineral, and vitamin composition. Some roughages, particularly legumes, are good suppliers of calcium and magnesium [6]. The phosphorus concentration is likely to be moderate to low, whereas the potassium content is likely to be high, these concentrations are affected by the plant species, soil, and fertilization strategies all have an impact on trace minerals. Roughages are categorized into two classes based on moisture content: dry and green or succulent roughages [7]. Green roughages often have 60-90 percent moisture, while dry roughages have just 10-15 percent moisture. Green roughages are divided into several types for ease of use, including pasture, produced fodder crops, tree leaves, and roots. Based on the nutritional content and preparation methods, dry roughages have been further categorized as hay and straw [8]. Minerals available in the feeds are of different types i.e., Micro minerals, macro minerals and chelated minerals. Microminerals, also known as trace minerals, are needed in milligrams (mg) or microgram (g) quantities [9]. They're found in trace amounts in animal tissues and feeds. They're frequently found in enzyme cofactors and hormones. Cobalt, iodine, zinc, copper, manganese, and selenium are examples of micro or trace minerals. Macro-minerals play a specific role in the formation and function of the animal's body. Animals require the following seven macro-minerals: calcium (Ca), phosphorus (P), sodium (Na), magnesium (Mg), potassium (K), sulfur (S), chlorine (Cl) [10]. Chelated minerals are a class of organic minerals that are divided into proteinates, chelates, and other complexes based on their molecular structure [11]. A chelated mineral is one that has two or more chemical interactions with peptides or amino acids, such as copper or zinc. Each one has a different level of absorption and effectiveness.
The National Research Council has studied nutrient requirements based on several criteria such as dry matter intake (DMI), total digestible nutrients (TDN), crude protein (CP), metabolic energy (ME), calcium (Ca), phosphorus (P), and other elements that affect intake and techniques of prediction [12]. The entire weight of feed minus the weight of water in the feed is expressed as a percentage and is known as dry matter. In feeding studies, dry matter intake is determined by weighing the whole ration supplied and the amount of feed left by the animal [13]. The term "total digestible nutrients" stems from an old system of calculating available energy in feeds and animal energy requirements using a complex calculation of measured nutrients. The whole amount of protein present, determined from the total nitrogen available, is referred to as a crude protein. The percent nitrogen is multiplied by 6.25 to get the percent protein. The digestible energy intake minus the energy in the urine minus the energy in the gaseous result of digestion equals the metabolizable energy. Calcium is required for bone formation, neuron function, and the production of milk and eggs in animals. Phosphorus is also included in a wide range of co-enzymes, nucleic acids, proteins and amino acids [14].
It is essential to know the significance of these nutrients in animal feed. Animal disease control, as well as feed and fodder shortages, are the most pressing issues in animal husbandry. Farmers frequently encounter the following issues.
1. Nutrient requirement for the livestock animal, 2. The amount of feed that must be supplied every day to boost productivity, 3. Feed ingredient costs must be kept under control.
Animal nutrition is necessary for livestock production to be effective. Animal feed efficiency and growth rate can both benefit from good nutrition. Diets that meet the demands of animals must be provided.
This work used goats to fully understand nutritional needs and feed composition through the use of a visual basic application. The three phases of the study are explained in this chapter, the first phase is the selection of feeds and understanding their nutrient composition. The second part involves determining which nutrients are important for animals and creating nutrient equations. The third phase entails the establishment of a linear programming model, followed by the design of the interface.
Data collection
Goats can grow well and produce maximum milk if balanced and nutritious food is fed [15]. A balanced ration should contain digestible nutrients, vitamins, and minerals, including concentrate feeds and green and dry roughages. The feed list was created based on the most commonly used feeds, fodders and its nutrient composition was used as per ICAR (2013) given in Table 1.
Nutrient requirements and estimation of nutrient requirements
Nutrient requirements are estimated based on the Indian Council of Agricultural Research (ICAR) (2013) and it was programmed in Excel VBA. A balanced ration should meet the nutrient requirement. If the growing goat does not get the nutrients, it will affect milk yield and weight at the time of slaughter [16,17]. The nutrient requirements for the growing goats are given in Table 2. There are three major factors of balanced ration: DMI, CP and TDN.
Dry Matter Intake (DMI)(kg/d): Dry matter intake is dependent upon many factors like fodder quality and quantity, climate condition, and nutrient requirement of goat. The DM requirements of goats for different body weights and growth rate functions are different [18]. The dry matter requirement is calculated based on body weight and average daily gain as per the Indian standard [19]. The total DMI intake calculated is in terms of 'kg' and the formula used in VBA code is given below:
Dim a As Integer
Dim z As Integer Dim y As Integer Energy: Energy is expressed as "Total Digestible Nutrients" (TDN). Energy allows doing physical reproductivity. It also provides for the development, lactation, reproduction, and other physiological functions such as feed digestion [20]. The TDN is calculated based on metabolic body weight and average daily gain as per the Indian standard (ICAR 2013).
From the Table 1. Will find CF1 (common factor 1) for 5, 10, 15, 20, 25, 30 kg with respective metabolic body weight (BW^0.75). the formula of CF1 is given below in eq (1) 15 kg are taken as 30.04 (average), for more than 15 kg can be taken as 30.13 (average of 3). Then we find CF2 (common factor 2) with respective average daily gain (ADG) by the following formula (eq (2)) CF2 values are found to be 1.6. Therefore (see eq (3)) ME (Mcal/d) can be found by using the following formula (eq (4)) Where 0.28 is the common factor. Protein: Protein is expressed as crude protein (CP). It is one of the major nutrients in terms of nutrition and cost. CP represents the percentage of protein present in feedstuff. CP is essential for maintenance, increasing the forage intake [21,22]. It varies for every stage of goat life. Therefore, setting CP level is very important. If the balanced ration does not meet the CP requirement, protein supplies are to be used at a greater cost [23]. At the same time, they were producing a balanced ration for these four requirements to be met compulsorily with the least cost [24]. Then the production will be more and farmers will be benefitted. The CP is calculated based on metabolic body weight and average daily gain as per the Indian standard (ICAR 2013).
CF1
CF2 values are 0.46 for less than 10 kg and 0.44 for greater than 10 kg. Therefore (see eq (7)
Research design
The developed tool (RBT) uses VBA (Visual Basic Application) as front end and back end as excel. It is a simple excel file that is saved as .xlsm form and integrated with VBA code [25]. The user form or first page asks for input data, mainly body weight (BW) in kg and expected average daily gain (ADG) in g, depending upon which, it will calculate the minimum nutrient requirements, i.e., total DMI in 'Kg', CP in 'g', TDN in 'g'. Then should be selected from the list on the second page from roughages, concentrate, and minerals. Once this information is fed, tool RBT will solve for minimization of cost with DMI, TDN, CP as constraints. The tool RBT followed the following linear programming model [26]. (see eq (8)) Objective Function: Where c i is the cost of each feed ingredient, x j represents the number of feeds, a i represents the composition of DM, TDN and CP in all feeds, b min and b max are the minimum and maximum requirement of DMI, TDN and CP, c max is the maximum limit for each feed.
Results and discussion
Ration balancing tool for growing goata Microsoft Excel VBA based software can calculate the nutritional requirements for animals, such as dry matter intake (DMI), crude protein (CP), total digestible nutrient (TDN), and metabolizable energy (ME), for which equations are derived by using common factor method based on the data of ICAR ( Once the nutrients requirements are found, the application asks the user to select the available feeds which are listed in the application. Then it will provide a balanced ration using LP model [27]. The expert nutritionist has examined the created application in NIANP, and the results of some specific animal categories (Goat 1 and Goat 2) are given in Table 3. The developed RBT will find the least-cost ration with the consumer selected feed without breaching the nutrient requirement shown in the sixth column of Table 3. Table 3, It is observed that two different categories of goat listed for validation, DMI, CP, TDN and ME criteria, are determined depending on both the weight and average daily gain as in the second column of Table 3. The developed RBT will find the least-cost ration with the consumer selected feed without breaching the nutrient requirement shown in the fifth column. To find the optimal solution, the RBT uses the Excel solver. The Excel Solver is efficient in obtaining feasible solutions nonlinear model for goats and increased daily gain and milk yield [28]. The nutrients TDN and CP required for growing goat according to Mandal, 2005 [29] for goat 1 with the body weight of 20 kg and an ADG of 75 g are 351 g and 79 g, respectively, for goat 2 with the body weight of 20 kg and 100 g of ADG, the requirements are 446 g and 100 g respectively. The nutrients TDN and CP calculated by developed application for Goat 1 are 349.5 g and 77.74, and for Goat 2 are 444.7 g and 99.51 g. There is a very small difference 1.5 g (0.4%) and 1.26 g (0.3%) in TDN and CP for goat 1, for goat 2 TDN and CP difference is 1.3 g (1.6%) and 0.49 g (0.49%) between RBT and Mandal et al. (2017). The required nutrients for two different goat categories and calculated by balanced ration are shown in Figures 5 and 6 for goat1 and 2, respectively. From the above studies and evaluation, it can be confirmed that the calculated values for DMI, TDN and CP are almost equal to the values of ICAR (2013). A Ration Balancing Tool (RBT)" is developed using Excel VBA, which gives a balanced ration for the goats with the available ingredients that satisfy all the nutrient requirements. Many software programs are available to customize ration for the lowest cost [30]. However, scanty applications are available for goat least-cost ration formulation. This study explains how the application is exceptional and more efficient and convenient compared to all other software programs, most of which are not user-friendly, and farmers must rely on expert assistance to implement it. For the commercial business reason, many software programs are developed for the client, wherein small dairy farmers still have to rely on specialists for optimized rationing. This tool is very simple to execute and user friendly. It is designed to determine the nutritional requirement of goats, depending on their weight and daily gain and to optimize goat ration at least cost.
Steps followed for formulation
Step1: once the excel sheet is open, page 1 of the user form will appear as shown in Figure 7. This page contains three tabs 'Introduction', 'Methodology' and 'Help'. Detailed information on goat feed formulation is given in the 'Introduction' tab. The procedure to use the application is given step by step in the 'Methodology' tab. How to add excel options to the applications is mentioned in the 'help' tab.
Step2: Clicking the NEXT button, page 2 will be displayed as shown in (Figure 8) where users are required to enter input data such as body weight (kg), expected average daily gain (g) of goat. Depending on the input data, the tool RBT calculates the DMI, TDN and CP required for a particular goat. Step3: Users must select feeds from roughages, concentrate and minerals on page 3 as shown in (Figure 9). The option is given to fix the minimum and maximum feed selected. If not, it will take standard values set by the tool. Users can also add new feeds depending on the availability in the subpage shown in (Figure 10a).
Step4: After the selection of feed has been completed, the tool RBT will provide an optimized ration cost to satisfy all nutrients at the minimum cost. If any nutrient requirement has not been met, the app will ask for feed refining where the user has to reselect the feed, this case is shown in (Figure 10b).
Step5: For the final output, the user must click on the 'Go to Result'. It opens excel sheet where the user can find.
2. Cost of 100 kg ration on dry matter basis.
Ration cost for the number of goats available.
Printouts can be taken for all the results. The features of the developed application are as follows, firstly Data Maintenance; if no feed is listed, the feed with nutrient composition can be uploaded by the consumer while selecting the feed. It allows the consumer to reasonably apply the feed available locally and reduce the cost. Consumers can get optimized ration in maximum effective steps by selecting the animal data and picking the feeds and then tapping on the "Solve" icon to get the result as it is user-friendly. For Display and printing, after the solution is found, there is an option for the result to be printed on a fed basis with feed quantity and total DM intake per kg. System requirements are also minimal as All MS Office versions can be used, and no special hardware or RAM is needed. The macros and solver options in VBA reference need to be enabled. The application provides the result in three ways: cost of single goat ration: Here, the total DMI is provided for one goat. This will help the consumer get an optimized ration and provide the right amount of roughage, concentrate, and minerals to be included in the ration. Finally, the price of each feed is given in the result. Cost of 100 kg ration on dry matter basis: Here, it estimates 100 kg at a time, which can be fed to goats at periodic intervals. The amount of roughage, concentrates, and minerals to be added to make 100 kg and its cost will be shown. Ration cost for the number of goats available: Here, the ration will be estimated on a dry matter basis for the number of available goats. The output is given in Figure 11.
Conclusions
This study showed that how the excel VBA can be used to analyzing the nutrient requirement and producing a balanced ration for livestock (goat) are fundamental aspects of reducing goats' feeding cost. Hence Excel Visual Basic Application (VBA) has been developed. Developed 'RBT' for beneficial for dairy farmers, which is based on a linear programming model. The ICAR (2013) table values for nutrients and the software-calculated values have high R2 values (DMI-0.989; TDN-1; CP-0.999). It can be confirmed from the aforementioned studies and evaluations that the computed values for DMI, TDN, and CP are nearly identical to the ICAR (2013) values. Just by giving the goat's minimum input, the application will calculate the nutrient requirement and the balanced ration at the lowest cost. Adding extra feed allows the user to add the feed available, which can lower the cost. The answer produced by the application is verified by a nutritionist at the National Institute of Animal Nutrition and Physiology (NIANP), Bangalore. Hence, it is concluded that even this application could be used quite effectively by dairy farmers. By understanding the nutrient requirements, the same can be developed for other livestock animals such as cattle, buffalo, and pigs.
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Domain: Agricultural And Food Sciences
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Temporal expression of avian β defensin 10 and cathelicidins in the yolk sac tissue of broiler and layer embryos
The yolk sac is a multifunctional organ, which not only participates in nutrient absorption, but also plays an important role in immune function. The objective of this study was to compare the mRNA abundance of avian β-defensin 10 (AvBD10) and 3 cathelicidins (CATH1, CATH2, and CATH3) in the yolk sac tissue (YST) of commercial broilers and white egg and brown egg commercial layers. AvBD10 and CATH mRNA abundance was analyzed using two-way ANOVA and Tukey's test, with P < 0.05 being considered significant. AvBD10 and CATH mRNA showed similar temporal expression patterns in the YST of both broiler and layers, with an increase from embryonic day (E) 7 to E9 through E13 followed by a decrease to day of hatch. AvBD10 mRNA showed a breed × age interaction with greater expression in the YST of both layers compared to broilers at E9 and E11. CATH1 mRNA was greater in the YST of brown egg layers than broilers. CATH2 mRNA showed a breed × age interaction, with greater expression in the YST of brown egg layers than broilers at E11. CATH3 mRNA showed no difference in the YST between layers and broilers. Because broilers and brown egg layers are genetically related, these results show that selection for production parameters (broiler vs. layer) and not genetic relatedness (white egg layer vs. brown egg layer and broilers) is the basis for the differences in AvBD10, CATH1, and CATH2 mRNA in the YST of broilers and layers. The yolk-free body weights of broiler embryos were greater than that of both brown and white egg layers from E9 to 17. One possible explanation is that the reduced expression of AvBD10, CATH1 and CATH2 mRNA in the YST of broilers compared to layers at E9 and 11 may be due to faster embryonic growth at the expense of host defense peptide expression in broilers compared to layers.
INTRODUCTION
The yolk sac tissue (YST) is an extra-embryonic membrane that surrounds the egg yolk and provides essential functions for the embryo, while its organs are developing (Wong and Uni, 2021). One of the key functions of the YST is immunity. The YST transports IgY in the yolk to the blood circulation of the embryo (Hincke et al., 2019) and also expresses high mRNA levels of the host defense peptide (HDP) avian b-defensin (AvBD) 10 (Zhang and Wong, 2019). Transfer of IgY and expression of a HDP in the YST would provide immunity for the newly hatched chick before its own immune system matures.
There are 14 AvBD genes in chickens, which are clustered on chromosome 3 (Cheng et al., 2015). All AvBD peptides show antimicrobial activity, with AvBD5,8,10,and 12 showing the greatest activity (Lee et al., 2016). In the YST of chicks, AvBD10 mRNA was the most abundantly expressed and was localized to endodermal epithelial cells by in situ hybridization (Zhang and Wong, 2019). AvBD10 mRNA in the YST increased from embryonic day (E) 7 to E9, remained elevated from E9 to E13 and then declined from E13 to E19.
The cathelicidins (CATH) are another major family of HDP that are expressed in mammals and avians and show antimicrobial activity against a wide spectrum of bacteria (Van Harten et al., 2018;Wang et al., 2020). In chickens, there are four cathelicidins: CATH 1, 2, 3, and B1, which are clustered on chromosome 2 (Xiao et al., 2006;Cuperus et al., 2013). CATH1 and CATH3 are the most closely related with greater than 90% sequence identity (Zhang and Sunkara, 2014). CATHB1 is expressed predominantly in the bursa. CATH1, CATH2 and CATH3 mRNA were expressed in whole embryos and showed similar expression patterns with increases from E3 to E6 and E9 (Meade et al., 2009). All CATH peptides show similar antimicrobial activity against pathogens (Xiao et al., 2006;Lee et al., 2016). Expression of CATH mRNA in the YST, however, has not been reported.
It is often assumed that differences in gene expression between broilers and layers are due to the different selection parameters for these chickens: rapid growth rate of broilers vs. high egg production rate of layers. However, this assumption is potentially confounded by breed differences as broilers and white egg layers were developed from very different breeds. Commercial broilers were originally developed from multiple heavy dual-purpose breeds (brown shell eggs), which included the White Plymouth Rock (Crawford, 1990). The genetic basis of commercial brown egg layers includes some breeds in common with broiler origins. In contrast, commercial white egg layers are produced solely by the White Leghorn breed. Genetic diversity studies confirmed the close relationship between broilers and brown egg layers and the greater genetic distance of White Leghorns (Malomane et al., 2019). Van der Most et al. (2011) investigated a potential tradeoff between growth and immune function in poultry that had been divergently selected for growth. Their meta-analysis showed that selection for growth compromised immune function. The objective of this study was to compare the temporal expression patterns of CATH1, CATH2, CATH3, and AvBD10 mRNA in the YST of embryos from broilers and layers. This study utilized 3 distinct types of chickens, broilers, and both white and brown egg layers. Differences between broilers vs. layers would implicate the impact of different selection parameters, while differences between a white egg breed vs. a brown egg breed would imply that they are influenced primarily by breed differences.
Egg Incubation and Tissue Collection
Seventy-five broiler eggs (Cobb 500) were obtained from a commercial hatchery in Harrisonburg, VA.
Seventy-five eggs from brown egg layers (HYB, Rhode Island Red £ White Plymouth Rock) and 75 eggs from white egg layers (W36, White Leghorn) were obtained from a commercial Hy-Line hatchery (Elizabethtown, PA). Eggs were randomly placed and incubated simultaneously in 3 OvaEasy 190 incubators set at 37.5°C (Brinsea Products Inc, Titusville, FL). At embryonic age E7, E9, E11, E13, E15, E17, and E19, 6 viable eggs from each breed were randomly selected. Embryos were euthanized by cervical dislocation and yolk-free body weights (YFBW) of embryos were measured. At DOH, 6 chicks from each breed were weighed and euthanized. Two small pieces of YST were collected from each embryo, rinsed with cold 1 Â PBS, minced, and placed into cryotubes, snap frozen in liquid nitrogen, and stored at À80°C for relative gene expression analysis. All animal procedures were approved by the Virginia Tech Institutional Animal Care and Use Committee.
RNA Isolation and Relative Gene Expression Analysis
Approximately 25 mg of YST were homogenized in TRI Reagent (Molecular Research Center, Inc. Cincinnati, OH) using a tissue lyser. Total RNA was isolated using the Direct-zol RNA MiniPrep kit (Zymo Research, Irvine, CA). The concentration and purity of the RNA samples were analyzed using a Nanodrop-1000 (Thermo Fisher Scientific, Waltham, MA). One mg of total RNA was used to synthesize cDNA using the High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific). cDNA was diluted 1:20 and used for real-time quantitative PCR (qPCR). Each sample was run in duplicate. Each well consisted of 5 mL SYBR green master mix (Thermo Fisher Scientific), 1 mL forward and reverse primers (5 mM), and 1.5 mL diluted cDNA and DEPC water. qPCR was performed with an Applied Biosystems 7500 Fast Real-time PCR system (Thermo Fisher Scientific) using the default fast program: 95°C for 20 s, 40 cycles of 90°C for 3 s and 60°C for 30 s. Primers for qPCR for AvBD10, CATH1, CATH2, CATH3, and CATHB1 are listed in Table 1. The stability of mRNA expression of 5 reference genes for all YST samples from all 3 types of chicks was tested using RefFinder (Xie et al., 2012). The five reference genes included 2 ribosomal proteins (RPLP0 and RPLP1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), b-actin (ACTB), and TATA-box binding protein associated factor 4 (TAF4). Only RPLP0, ACTB, and TAF4 were selected to be used for relative gene expression analysis due to their greater expression stability. The geometric mean of the Ct values of RPLP0, ACTB, and TAF4 was used to calculate DCt. The average DCt for broilers at E7 was used as the calibrator. Relative gene expression was determined by the 2 ÀDDCt method (Schmittgen and Livak, 2008).
Statistical Analysis
Differences in weight of yolk-free embryos or day of hatch chicks between breeds for each embryonic day were analyzed by one-way ANOVA and Tukey's test. Differences in relative gene expression between breeds and ages were analyzed by two-way ANOVA and Tukey's test using JMP Pro 15 (SAS Institute Inc., Cary, NC).
Body Weight of Layer and Broiler Embryos
The growth of broiler and layer chicks was assessed by measuring YFBW of embryos from E7 to E19 and BW of chicks at DOH (Figure 1). Egg weights at the start of incubation were: broiler eggs (60.7 § 0.5 g), brown eggs layer (58.6 § 0.5 g), and white eggs layer (63.8 § 0.5 g). One-way ANOVA showed that the weights of white eggs layer > broiler eggs > brown eggs layer, consistent with the pre-incubation egg weight distribution. At E7, there was no difference in YFBW between broiler and layer embryos. At E9, E11, E13, E15, and E17, the YFBW of broiler embryos were greater than both layer embryos. The YFBW of layers were the same except for at E17 when brown egg layers had greater YFBW than white egg layers. By E19 and DOH the YFBW and BW, respectively, of the layers and broilers were not different, likely because egg size restricted further growth. Consistent with this idea, brown eggs had the lowest egg weights and numerically lower BW at E19 and DOH.
AvBD10 and CATH mRNA Expression in the Yolk Sac Tissue of Broilers and Layers
Expression of AvBD10, CATH1, CATH2, and CATH3 mRNA were analyzed by two-way ANOVA for age, breed, and breed  age interaction (Table 2). When there was an interaction (AvBD10 and CATH2), the results were also displayed as a graph. AvBD10 mRNA in the YST of broilers, brown egg and white egg layers all showed similar temporal patterns with low levels at E7, a peak at E9/11 and a low level at DOH (Figure 2). There was a breed  age interaction (P < 0.001) for AvBD10 mRNA with all 3 chick types showing different levels of expression (Table 2). For broilers, AvBD10 mRNA increased from E7 to E9 and E11, decreased from E11 to E17 and was unchanged from E17 to DOH. By contrast, AvBD10 mRNA for both brown egg and white egg layers increased from E7 to E9 and E11, decreased from E11 to E13 and from E13 to DOH. At E9, AvBD10 mRNA in the YST was not different between the 2 layers; whereas at E11, AvBD10 mRNA Figure 1. Body weights of embryos and chicks at day of hatch for broilers, brown egg layers and white egg layers. Yolk free body weights at embryonic day (E) 7 to E19 and body weight of chicks at day of hatch (DOH) were recorded. Bars show mean § individual SE (n = 6). Statistical analysis used one-way ANOVA and Tukey's test. Different letters (a-c) indicate differences between breeds within an age (P < 0.05). Table 2. Expression of avian b-defensin 10 (AvBD10) and cathelicidin (CATH 1-3) mRNA in the yolk sac tissue of broilers and layers from embryonic day 7 (E7) to day of hatch (DOH). was greater in brown egg layers than white egg layers ( Figure 1). Overall, AvBD10 mRNA in the YST was greater in both layers compared to broilers (Table 2).
For CATH1 mRNA, there was no breed  age interaction, but there were main effects of age and breed (Table 2). CATH1 mRNA showed a similar pattern of change across all 3 types of chicks, starting at a low level at E7 that increased to E11, no change from E11 to E19, and then a decrease from E19 to DOH. CATH1 mRNA was greater in the YST of brown egg layers compared to broilers, with white egg layers intermediate.
CATH2 mRNA showed a similar temporal pattern of an increase from E7 to E11 and a decrease from E11 to DOH (Table 2). There was a breed  age interaction (P = 0.002) for CATH2 mRNA (Figure 3). CATH2 mRNA in the YST of broilers increased from E7 to E13 and then decreased from E13 to E19 and DOH. By contrast, CATH2 mRNA in the YST of brown egg layers increased from E7 to E11, decreased from E11 to E13 and from E13 to DOH; while CATH2 mRNA for white egg layers increased from E7 to E11 and E13 and then decreased from E13 to E17 and from E17 to DOH. At E11, CATH2 mRNA was greater in the YST of brown egg layers than broilers, with white egg layers intermediate. There was no difference for CATH2 mRNA between broilers and layers at any other time points. Overall, CATH2 mRNA was greater in the YST of both layers compared to broilers (Table 2).
For CATH3 mRNA there was no breed  age interaction, but there was a main effect of age (Table 2). CATH3 mRNA similarly showed the same temporal expression pattern with an increase from E7 to E9 and E11, no change from E11 to E17, and a decrease from E17 to DOH. CATHB1 mRNA was not detected in the YST of either broiler or layer embryos at any age (data not shown).
DISCUSSION
The egg contents must provide not only nutrition but also protection from pathogens for the developing embryo. The egg white contains ovotransferrin and lysozyme, both of which have antimicrobial properties; while the yolk contains hen-derived antibodies (Wong and Uni, 2021). Zhang and Wong (2019) had previously shown that AvBD10 mRNA was expressed in the YST. The current study confirmed AvBD10 mRNA expression in the YST and additionally showed that CATH1, CATH2, and CATH3 mRNA were also expressed in the YST. The combined antimicrobial action of biomolecules in the egg white, yolk, and YST creates a protective environment for the developing embryo.
The profiles of AvBD10 and CATH mRNA all showed peak expression during mid embryogenesis (E9 to E13) in the YST of both broilers and layers. The decline in AvBD10 and CATH mRNA during late incubation would be consistent with the beginning of degradation of the YST prior to internalization. Peak expression during mid incubation would provide protection for the developing embryo from any pathogens that may be present in the egg yolk while the immune organs of the embryo are in the process of developing and maturing. It is unknown what the trigger might be for this increase in AvBD10 and CATH mRNA, but it is unlikely due to contamination in the eggs because this induction occurred consistently with a previous trial using broilers (Zhang and Wong, 2019) and the current trial using both broiler and brown and white egg layers from different commercial hatcheries. This is most likely a genetically programmed event. Meade et al. (2009) reported the temporal expression patterns for AvBDs and CATHs in whole Cobb embryos at E3, E6, and E9. AvBD5, AvBD9, and AvBD10 mRNA increased 25-, 164-and 87-fold, respectively, from E3 to E9 in whole embryos while CATH1, CATH2, and CATH3 mRNA increased 7-, 6-, and 9-fold, respectively, from E3 to E6 (Meade et al., 2009). Thus, in the developing embryo, immune protection is from a combination of AvBD and CATH expression by the embryo during early incubation (E3 to E9) and by the YST during mid incubation (E9 to E13).
Genetic distance analysis showed that brown layers are genetically more closely related to commercial broilers than to commercial White Leghorns (Malomane et al., 2019). This is consistent with the known origin of commercial brown egg layers, being derived from some of the same breeds used to develop the commercial broiler (Crawford, 1990). The brown and white egg layers both had AvBD10, CATH1, and CATH2 mRNA levels greater than broilers, and were more similar to each other than to broilers. This suggests that the differences observed in this study were not due to genetic differences per se (brown egg layers and broiler breeds vs. White Leghorn breed), but were more likely due to the selection for specific performance traits, that is, rapid early growth rate for broilers vs. high egg numbers and extended egg production for layers.
The difference in HDP mRNA expression profiles in the YST between broilers and layers may be due to selection for rapid growth. In this study, broiler embryos had greater YFBW than layer embryos between E9 and E17, which was also reported by Ohta et al. (2004). AvBD10, CATH1, and CATH2 mRNA, however, were lower in the YST of broiler embryos compared with layer embryos during this period. One possible explanation is that the increased early growth rate of broilers may come at a cost of decreased expression of HDPs in the YST. Because there is a finite amount of nutrients in an egg, energy may be directed towards growth instead of host defense for broiler embryos. This hypothesis, however, needs further investigation.
There was elevated expression of CATH1 and CATH2 mRNA in the YST of layers compared to broilers; whereas CATH3 mRNA showed no difference. Expression of CATHB1 mRNA was not found in the YST (data not shown), confirming that it is predominantly expressed in the bursa (Achanta et al., 2012). The CATH genes are organized as a cluster on chromosome 2 in the order of CATH1-CATHB1-CATH2-CATH3, with CATH3 transcribed from the opposite strand as the other CATH genes (Cuperus et al., 2013;Cheng et al., 2015). CATH1 and CATH 3 showed the greatest sequence identity (>90%) and are thought to have arisen by gene duplication (Xiao et al., 2006;Zhang and Sunkara, 2014). One possible explanation for the difference between CATH1/CATH2 and CATH3 mRNA expression in the YST of broilers and layers may be because CATH1 and CATH3 have similar amino acid sequences and induced expression of both would be redundant. A second possibility is that there may have been a change in the regulatory elements of the CATH1 and CATH3 genes during gene duplication.
In conclusion, the temporal expression patterns for AvBD10 and CATH1, CATH2, and CATH3 mRNA were similar in the YST of broiler and layer embryos, with an increase from E7 to E9/E11, followed by a decline to DOH. The peak HDP expression during mid embryogenesis would protect the embryo from pathogens present in the egg, while the immune organs of the embryo are in the process of maturing. However, layers, especially brown egg layers, had greater AvBD10, CATH1, and CATH2 mRNA in the YST compared to broilers. The increased early expression of AVBD10, CATH1, and CATH2 mRNA in the YST of layer compared to broiler embryos was inversely related to the lower YFBW of layer compared to broiler embryos. This suggests that during mid embryogenesis, energy may be directed towards growth at the expense of host defense for broilers. These results further indicate that differences between expression levels of HDPs in the YST of layer and broiler embryos are more likely due to the different selection parameters of growth (broilers) vs. egg production (layers) rather than breed differences (broilers and brown egg layers vs. White Leghorn). The unique design using broilers and brown and white egg layers would allow future studies to also dissect differences due to genetics or selection.
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Domain: Agricultural And Food Sciences
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Analysis and Optimization of a Synthetic Milkweed Floral Attractant for Mosquitoes
A pentane extract of flowers of common milkweed, Asclepias syriaca (Asclepiadaceae), elicited significant orientation from both male and female Culex pipiens in a dual-port flight olfactometer. Analysis of the extract by gas chromatography–mass spectrometry revealed six major constituents in order of relative abundance: benzaldehyde, (E)-β-ocimene, phenylacetaldehyde, benzyl alcohol, nonanal, and (E)-2-nonenal. Although not all were collected from the headspace profile of live flowers, a synthetic blend of these six compounds, when presented to mosquitoes in the same levels and proportions that occur in the extract, elicited a response comparable to the extract. Subtractive behavioral bioassays demonstrated that a three-component blend consisting of benzaldehyde, phenylacetaldehyde, and (E)-2-nonenal was as attractive as the full blend. These findings suggest the potential use of synthetic floral-odor blends for monitoring or control of both male and female disease-vectoring mosquitoes.
Introduction
The northern house mosquito, Culex pipiens L. (Diptera: Culicidae), is a member of a species complex that includes vectors of lymphatic filariasis and several arboviral diseases, such as St. Louis encephalitis (SLE), Rift Valley fever (RFV), and West Nile virus (WNV). In the northeastern quadrant of the United States, C. pipiens recently has become important because of its role in the transmission of WNV. The virus was introduced into New York City in 1999 and is currently the most widespread arboviral disease in the U. S. (CDC, 2010). The blood-feeding pattern of C. pipiens (shifting from avian to human feeding within the transmission season) (Edman and Taylor, 1968;Kilpatrick et al., 2006), coupled with its high vector competence (Turell et al., 2005) and ability to carry WNV through the winter, has allowed the virus to spread from its point of origin and maintain transmission throughout the mosquito's range. Thus, C. pipiens is one of the major targets for mosquito vector control and surveillance in the U. S. Current methods of monitoring by abatement districts and health departments include Centers for Disease Control (CDC) light traps and CO 2 -baited traps, which mainly trap blood-seeking females, along with gravid traps, which target gravid females.
Plant-derived attractants have the potential to act as surveillance-trap lures and, when combined with poisonlaced sugar solutions (Müller et al., 2010), to control mosquito populations. Mosquitoes are attracted to various plant species, from which they obtain nectar and other juices. Sugar feeding by mosquitoes has a significant influence on dispersal (Hocking, 1953;Magnarelli, 1977) and vectorial capacity (Gary and Foster, 2001;Gu et al., 2011), and, contrary to long-held conjecture, is required by both males and females throughout the adult stage (Downes, 1958;Yuval, 1992;Foster, 1995). Both sexes typically first visit plants soon after emergence. Males then require sugar at frequent intervals to maintain their energy reserves in order to join nightly mating swarms . Females take sugar between blood meals, when they are digesting blood, or when they are gravid (Clements, 1999;Foster, 2008). Furthermore, females of most temperate-climate Culex and Anopheles species enter reproductive diapause in late summer, after which they no longer are attracted to blood hosts, but engage heavily in plant-sugar feeding (Bowen, 1992a).
The potential for plant volatiles to lure mosquitoes has been demonstrated in several laboratory behavioral assays that have used stimuli such as natural plant extracts (Vargo and Foster, 1982;Jepson and Healy, 1988;Mauer and Rowley, 1999) or single floral compounds (Jhumur et al., 2006). In field studies, Bates (1949) reported the successful trapping of anopheline mosquitoes with plant and fruit baits; fruit also proved to be an effective attractant in CDC traps for C. tarsalis (Reisen et al., 1986). Sandholm and Price (1962) observed that mosquitoes in the field were attracted to light-colored flowers with distinct fragrances; odor appears to be primarily responsible for long-range attraction, with visual cues playing a role at shorter range (Thorsteinson and Brust, 1962;Healy and Jepson, 1988;Jepson and Healy, 1988). Orientation to commercially obtained floral extracts and honey has been demonstrated for various mosquito species (Thorsteinson and Brust, 1962;Hancock and Foster, 1997;Foster and Takken, 2004). Schlein and Müller (2008) and Müller et al. (2008Müller et al. ( , 2010 reported dramatic population reductions of C. pipiens and other mosquito species by spraying a fruit-based sugar bait containing insecticide on vegetation surrounding larval habitats. Light-less CDC traps baited with the blossoms of Tamarix jordanis were highly effective in trapping C. pipiens, and populations were reduced where these blossoms were treated with spinosad insecticide . Flower species that elicit the highest attraction probably vary by region. During mid-summer in the U. S., mosquitoes have been observed probing blossoms of common milkweed, Asclepias syriaca, at rates disproportionate to their abundance relative to other flowering plants, with one study reporting 54 species occurring in the study area that did not serve as nectar sources (Grimstad and Defoliart, 1974). Another study collected 25 Aedes vexans from one milkweed cluster in just 15 min (Sandholm and Price, 1962). The observed preference of insects for milkweed flowers, both day and night, possibly is due to its strong and distinctive fragrance, lighter-colored flowers, and greater nectar production (Sandholm and Price, 1962). Common milkweed is indigenous to eastern and midwestern North America, where its principal native pollinators are mainly large Hymenoptera and Lepidoptera (e.g., Jennersten and Morse, 1991). Mosquitoes are incapable of transferring milkweed pollinia and therefore function as nectar thieves, appearing to co-opt the attractive properties used by the pollinators to locate the flowers (Foster, 1995).
Solvent extracts of common milkweed flowers also are attractive to mosquitoes (Vargo and Foster, 1982;Mauer and Rowley, 1999), confirming that volatile chemicals are at least partly responsible for that attraction. Mauer and Rowley (1999) determined the headspace profile of common milkweed flower to be predominantly 2-phenylethanol and benzyl alcohol; however, they found that a synthetic blend of these two compounds was not attractive to C. pipiens. Due to the multiple demonstrations of C. pipiens attraction to milkweed, both in the laboratory and the field, we used a solvent extract of the flower as a potential model for synthetic mosquito lures.
Methods and Materials
Mosquitoes Experiments were conducted with C. pipiens from a colony established in 2009 from larvae collected near Columbus, OH, USA. Larvae were identified at L4 by siphonal hair tufts (Vinogradova, 2000). Adults were maintained in 41-l clear acrylic cages on a diet of 10 % sucrose, water, and weekly blood meals from the legs of a rooster (ILACUC permit No. 2005A0054). Oviposition water was prepared by soaking grass clippings in aged tap water and allowing fermentation over a 3-d period. Three days after each blood meal, oviposition cups were placed with caged adults, and eggs were collected the following day. Two hundred first-instar larvae were placed into 22.8× 33.0 cm aluminum pans with 450 ml of aged tap water. The larvae were provided finely ground TetraMin® flakes, increasing the quantity daily from 50 mg for first instars to 500 mg for final instars until pupae appeared on the 8th and 9th day post-hatching. Pupae then were counted and transferred to plastic cups and placed in a 41-l cage supplied with water wicks. Emerging adults were given ad libitum access to water, but were deprived of sugar. Experiments were conducted 36±12 h after emergence. The mosquito rearing and maintenance conditions were 27±1°C, 85±5 % RH, and 16:8 (L:D), with 30-min gradual crepuscular transitions between photophase and scotophase.
Extract Preparation Flowers of common milkweed, A. syriaca, were collected in early summer from The Ohio State University campus in Columbus (40º00′18.95" N, 83º02′47.11" W), placed in an ice cooler, and transported 10-min to the laboratory. Single florets were plucked from the main milkweed umbel and separated from the calyx and other green parts of the flower, weighed, and placed into a 500 ml narrow-mouth glass Erlenmeyer flask. Milkweed florets were submerged in HPLC-grade n-pentane (Fisher Scientific) in a 1:8 ratio (w/v) for a total solvent volume of 480 ml and held for 24 h at room temperature, at which time the extract was decanted into 21-ml borosilicate glass vials, capped with Teflon-lined screw caps and stored at -20°C.
Headspace Analysis The volatile profile of milkweed flower was characterized by placing a single floret into a 21-ml borosilicate glass vial with a Teflon-lined rubber septum. Volatiles were allowed to equilibrate in the vial headspace at 30°C for 10 min before collections were made. Volatiles were collected by using a divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) (50/30 μm) solid phase micro-extraction (SPME) fiber (Supelco, Bellefonte, PA, USA). This mixed-chemistry fiber provides affinity for chemicals with a far broader range of polarity and volatility than PDMS alone. The fiber was introduced to the vial through the septum and exposed for 30 min. The collected volatiles were analyzed immediately by using an Agilent Technologies 6890 series gas chromatograph interfaced to an Agilent Technologies 5973 quadrupole mass selective detector (GC-MS). The SPME fiber was desorbed at 275°C for 3 min with a splitless injection onto a Zebron™ ZB-1 ms column (30 m×0.25 mm, 0.25 μm film thickness) (Phenomenex, Torrance, CA, USA). The oven temperature was held at 25°C for 3 min, then ramped at 15°C/min to 250°C, where it was held for 2 min. The carrier gas was helium at a flow rate of 1 ml/min. The mass selective detector was operated in EI mode at 70 eV, scanning 19-350m/z with a quadrupole temperature of 180°C and source temperature of 240°C.
Extract Analysis To guide the construction of a synthetic floral blend, pentane extracts of milkweed florets were analyzed by GC-MS on a Zebron™ ZB-50 column (15 m× 0.25 mm, 0.25 μm film thickness) (Phenomenex), with a 1-μl splitless injection at 210°C. The temperature program began at 25°C for 3 min and increased at 13°C/min to 200°C, followed by a 25°C/min increase to 280°C to remove high-boiling lipids. Other parameters were as described above. Peak identities were validated by re-injection on a Finnegan Trace GC/MS (Thermo Fisher Scientific Inc., Waltham, MA, USA), with a 1:10 split at 180°C and a Rtx®-5MS column (30 m×0.25 mm, 0.25 μm film thickness) (Restek, Bellefonte, PA, USA). The helium flow was 1 ml/min, and temperature program was 40°C for 1 min, ramped at 15°C/min to 275°C, with a 2-min final hold time. Retention indices (RI) of compounds were determined on both columns relative to n-alkanes (C 8 -C 20 ). Components of floral headspace and extract were identified by matching their mass spectra to NIST/ EPA/NIH Mass Spectral Library 2005 and comparison of retention indices to published values (Adams, 1995). Identity of major components was confirmed by comparison of spectra and retention times to authentic standards. Peak purity was determined by using AMDIS deconvolution software (NIST, Gaithersburg, MD, USA) to assure the absence of any coeluting components. A synthetic mimic of the extract was constructed by blending authentic standards of the major components identified in the extract. Quantities of each component were individually adjusted until the overall concentration and component proportions closely approximated those of the floral extract (Fig. 1a).
Behavioral Assays All behavioral assays were conducted in a clear acrylic dual-port flight olfactometer, modified from Hancock and Foster (1993), with three main parts: an introduction/release chamber, flight chamber, and trapping ports. The introduction/release chamber was located at the downwind end, measuring 30×40 cm wide and 30 cm long. A sliding gate separated the release chamber from the main flight chamber (30×40 cm wide, 90 cm long), which had two cylindrical glass jar trapping ports (15 cm long by 7 cm diameter) on its upwind end. Ports were fitted with borosilicate glass funnels, with the wide end opening into the flight chamber and the narrower (3 mm diam) end pointing into a glass jar. Thus, mosquitoes entering the wide end of the funnel from the flight chamber were channeled into the jar, where they were retained. Trapping ports were located 11 cm above the flight chamber floor and were separated by 21 cm. The funnel and glass jar were held together by Parafilm ® sealing film (Pechiney Plastic Company, Menasha, WI, USA), which was replaced between treatments. We recognized the pitfalls associated with the use of Parafilm ® in solvent-based behavioral assays (Millar and Haynes, 1998), and we ensured that this sealant would not come in contact with any chemicals in the olfactometer. A 7.5-mm diam hole in the upwind end of each jar allowed the introduction of purified/humidified air after it had passed from an oil-free air pump through an activated carbon canister, and then through a water column. Air flow was maintained at 50 ml/s into each port, providing a velocity of 72 mm/s in the center of the flight chamber. A black cotton cloth, covering a dampened layer of cotton wool, covered the entire floor of the flight chamber, to maintain a level of humidity similar to that within the choice ports. Data loggers (HOBO®, Onset Computer Corporation, Bourne, MA, USA) recorded temperature and humidity in the olfactometer, which was 25.0-27.5°C and 75-95 % RH. An exhaust duct, connected at the downwind end of the release chamber, directed the effluent air out of the building through an exhaust hood. To test for positional bias of the ports, mosquitoes were released into the chamber after either baiting both ports with honey or leaving both empty. Mosquitoes were divided equally between left and right ports when baited with honey and were found rarely in ports when both were empty.
Response to whole milkweed flowers was determined in the flight olfactometer with 2 g of florets placed in an aluminum weighing boat in one of the trapping jars, and compared with an empty control jar. Extracts and synthetic chemicals were applied to 15-cm long cotton wicks (TIDI Products, Neenah, WI, USA) and compared to a pentane control. The positions of the treatment and control ports were alternated between bioassays as a further safeguard against positional bias. The olfactometer parts were cleaned with 70 % ethanol followed by water after each experiment; gloves were used at all times to avoid contamination with human-related kairomones. The 16:8 (L:D) light cycle used for mosquito rearing was maintained in the bioassay room. At 2 h prior to scotophase, approximately 200-300 mosquitoes of both sexes in similar numbers were released through a sleeve connection, directly from an acrylic plastic cage (30×30×30 cm) into the holding/release chamber, where they were held for 15 min to acclimatize before the release gate was opened. After 12 h, the numbers of mosquitoes in the treatment port, the control port, and remaining in the flight chamber were recorded. Use of a 12-h period captured the bimodal nocturnal-crepuscular sugar-feeding rhythm of C. pipiens, which includes some sugar feeding throughout the night (Yee and Foster, 1992).
Video Recording Mosquito flight behavior was recorded by using three infrared RCA closed-circuit video cameras (Lancaster, PA, USA) onto which was mounted a TC1824B wide-angle ES 25 mm 1:1.4 lens for flight-chamber recordings or a TC1874C ES 75 mm 1:1.8 lens for each of the choice ports. The cameras were controlled in series with a Burle Security Products TC8108 (Lancaster, PA, USA) eight-channel switcher, with video output to two RCA TC1109 video monitors. Video output was recorded with an Emerson EWV404 VCR (Parsippany, NJ, USA) onto VHS tape in time-lapse mode, 20 s each min.
Statistical Analysis Mosquito response in the flight olfactometer was analyzed by comparing numbers caught in the two ports by a goodness-of-fit chi-squared test with SPSS v. 17 (SPSS Inc, Chicago, IL, USA). The threshold for significance was α00.05. In the dose-response experiment, a regression model of mosquito response to log-transformed blend dose was determined by using the Fitted Line Plot module of Minitab v. 16 (Minitab Inc., State College, PA, USA).
Results
Chemical Identification Six compounds comprised >90 % of the relative abundance of the milkweed floret components in the pentane extract: (E)-β-ocimene, benzaldehyde, nonanal, benzyl alcohol, phenylacetaldehyde, and (E)-2-nonenal ( Fig. 1a, Table 1). The volatile profile collected by DVB/ CAR/PDMS SPME directly from fresh florets was dominated by three of these compounds: (E)-β-ocimene, benzaldehyde, and phenylacetaldehyde (>75 % of the total), but there were also substantial differences compared to the pentane extract (Fig. 1b). Most notably, (E,Z)-and (E,E)-alloocimene were collected from the flower headspace, but were almost completely absent from the extract, whereas nonanal, a major constituent of floret extract, was missing in the headspace sample. These disparities can be explained partly by variation in volatility among the components, but also likely reflect differences between the chemical composition in flower tissue and what is released. The extract also contained higher-boiling hydrocarbons and fatty acids, but due to their low volatility, they were not included in behavioral studies. Based on the quantities of synthetic standards used to mimic the extract GC profile (Table 1), the total floral concentration of the six major volatiles was estimated at 32 μg/g floret fresh weight.
Flight Olfactometer Response Infrared video recordings showed C. pipiens in the flight chamber engaged in a zigzagging flight that was directed upwind towards ports baited with florets, extracts, or synthetic blends. The angle of the turns progressively decreased as the mosquitoes approached the target. In most cases, mosquitoes flew into the ports, but in a few cases they landed on the entrance of the port and walked in. There was no observed oriented flight towards the control port.
In the first behavioral assay, mosquitoes showed a significant response to whole milkweed florets, where 67 % of released mosquitoes were captured in the floret-baited port, compared to only 6 % in the control port ( Fig. 2a; χ 2 0515.02 df01, P<0.001). Despite the chemical differences measured between the headspace and extract profiles of milkweed florets, mosquitoes showed a similarly strong response to a pentane extract of milkweed florets (52 %) compared to pentane alone (11 %) ( Fig. 2b; χ 2 061.44, df01, P<0.001). Moreover, mosquitoes were observed in video recordings to probe the extract-treated cotton wick during the early scotophase and early photophase, suggesting that the extract also stimulated a feeding response. This behavior was never observed on control wicks. Based on the positive response to the milkweed floret extract, a six-component synthetic blend was formulated to simulate the concentrations and relative proportions of major constituents of the pentane extract (Fig. 1a). One discrepancy in the GC profiles was caused by the presence of the (Z)-isomer in synthetic (E)-β-ocimene, resulting in a synthetic blend that exceeded the levels of this isomer in the floret extract. In the olfactometer, the synthetic floret blend performed similarly to the natural extract, with 48 % of released mosquitoes trapped, compared to 16 % for the control (Fig. 2c; χ 2 0120.6, df01, P <0.001). Again, video-recordings showed a directed upwind flight response to ports containing the synthetic blend, accompanied by vigorous probing of the treated wicks, but not to the controls. Males and females responded to milkweed floret odors in similar numbers in all three experiments as the sex ratio of mosquitoes captured in either the treatment or control ports did not deviate significantly from 1:1.
Because quantity as well as quality can determine the intensity of chemically mediated behavior, C. pipiens Relative response shows the proportional response to the reducted (gray bars) and full (black bars) blends. Numbers in bars indicate the mean number of C. pipiens responding (N04-6). Asterisks denote significant differences in mean response to reducted versus full blend by chi-squared test (* P<0.05, ** P<0.005) response was measured in the flight olfactometer to different doses of the three-component blend compared to a solvent control. There was a significant positive quadratic response [log(dose) (y0-20.527x 2 +73.476x-43.709; R 2 057.6 %], with a response maximum predicted at 62 μg (Fig. 5). The response flattened out at both the lowest and highest doses; removal of the two most extreme doses produced a strongerfitting regression model (R 2 093.3 %), but with a similar predicted optimal dose of 65 μg.
Discussion
A positive upwind orientation by C. pipiens to floret volatiles of A. syriaca was demonstrated in this study, suggesting a new potential source of attractants for use in the field as lures. Males and females showed significant response to milkweed florets, a pentane extract, and a synthetic blend of the extract's six major constituents: benzaldehyde, (E)-β-ocimene, benzyl alcohol, phenylacetaldehyde, nonanal, and (E)-2-nonenal. The first three of these compounds are among the most common floral odor constituents in plants (Knudsen et al., 2006). Subsequent subtractive bioassays of the synthetic blend demonstrated that only three of its components contributed to attraction: benzaldehyde, phenylacetaldehyde, and (E)-2-nonenal.
The attraction of mosquitoes to plant odors has been demonstrated in numerous field and laboratory studies, but few studies have shown significant attraction to synthetics. Mauer and Rowley (1999) observed orientation of C. pipiens to a methylene chloride extract of A. syriaca in a dual port olfactometer. However, a synthetic blend of the two dominant compounds in the extract headspace, benzyl alcohol and 2phenylethanol, failed to attract the mosquitoes. We did not test 2-phenylethanol, but benzyl alcohol was not active in our flight olfactometer bioassays. Jhumur et al. (2007) also found benzyl alcohol to not be very attractive to C. pipiens var. molestus, although Puri et al. (2006) recorded significant upwind response by C. quinquefasciatus to the compound.
Flowers of Tanacetum vulgare also attract Culex species in the field (Andersson and Jaenson, 1987), and Bowen (1992b) discovered a high proportion of both broadly-and narrowlytuned antennal receptor neurons of C. pipiens sensitive to thujone, the primary constituent of T. vulgare fragrance. However, thujone only elicited a close-range dose-dependent probing response in C. pipiens; it did not stimulate upwind flight in a wind-tunnel olfactometer (Bowen, 1992b). The only previous flower-based synthetic blend causing mosquito orientation was developed from Silene otites, whose flowers attract mosquitoes in the field (Brantjes and Leemans, 1976). The synthetic blend mimic consisted of phenylacetaldehyde, veratrole, and 2-methoxyphenol, the first of which elicited the strongest attraction in C. pipiens var. molestus when presented individually (Jhumur et al., 2006). Phenylacetaldehyde also was a prominent component of our A. syriaca headspace and solvent extract, and it was essential for maximum attraction to the synthetic blend.
Although nonanal was a major component of A. syriaca floret extract, we saw no evidence that it played a role in attraction in our bioassays. In contrast, from single-cell recordings, Syed and Leal (2009) determined that ca. 40 % of all antennal olfactory receptors of C. quinquefasciatus were acutely sensitive to nonanal, and it produced a synergistic effect on trap catch when presented with CO 2 . This apparent discrepancy likely is explained by differences in mosquito physiological state. Nonanal is a major skin odorant of birds and mammals, including humans, resulting from the oxidation of sebaceous fatty acids (Haze et al., 2001). This fact, along with the significant behavioral interaction with CO 2 , suggests that nonanal may play an important role in mediating Culex host-finding, but does not attract sugar-seeking mosquitoes.
We found notable differences between profiles of the pentane extract and the SPME-collected headspace of A. syriaca florets. Pentane extracts were dominated by phenylacetaldehyde, (E)-β-ocimene, and nonanal, whereas the headspace profile contained primarily benzaldehyde, ocimene isomers, and phenylacetaldehyde. Disparities between extracts and chemicals collected in the headspace might be explained by differences in the physico-chemical properties of the constituents, deep penetration by solvents to extract compounds that are not normally released by the tissue, and/or selective trapping of chemicals by SPME. In this study, differences between the methods are largely consistent with chemical differences in vapor pressure. Benzaldehyde, β-ocimene, and alloocimene have the highest vapor pressures of all the chemicals identified from milkweed, and they make up most of the volatile profile. The vapor pressure of benzaldehyde is almost twice that of nonanal, almost four times that of (E)-2-nonenal, and more than six times that of benzyl alcohol. The latter three compounds were either absent or found in very low levels in the headspace analysis. Phenylacetaldehyde is intermediate in its volatility, but was also the component found in the highest levels in the pentane extract.
Volatile collection analyses can produce misleading results, as they may not accurately reflect the actual proportionality of constituents in the headspace. We do not believe that this was a major factor for explaining the differences in the headspace and extract profiles of milkweed due to our choice of SPME phase. Although PDMS has been the most widely used SPME phase, it is actually a poor choice for characterizing plant volatile profiles that contain constituents with a range of volatilities and functional groups. In preliminary studies (not shown), we found a broader array of volatile compounds was trapped from various flowers by DVB/CAR/PDMS compared to PDMS alone. This mixed-bed fiber not only employs a broader range of phase polarity, but also incorporates both adsorption and partitioning as mechanisms of collection (Koziel and Novak, 2002). A number of recent studies have demonstrated the higher recovery efficiency and linearity by DVB/CAR/PDMS compared to other SPME phases for all of the compound classes that we identified from milkweed (Cui et al., 2009;Ferreira et al., 2009;Zhang et al., 2009). For example, Zhang et al. (2009) found that volatile profiles of longan fruit extracted by a 50/30 μm DVB/CAR/PDMS fiber were 3x higher in terpenes, 5x higher in alcohols, and 14x higher in esters than those produced by a 100 μm PDMS fiber, and revealed volatile carbonyls and acids, which were completely absent from PDMS profiles.
This study points to floral odors as a potential new model for chemical lures useful for mosquito sampling or control. If similar attraction can be demonstrated at the field level, as has already been demonstrated with human kairomone blends (Mukabana et al., 2012), synthetic floral blends could potentially be used in trapping devices to sample adult populations. Relative to animal-derived odors (Mukabana et al., 2012), floral odors have the advantage of attracting both sexes of mosquitoes in proportional numbers, and females in all gonotrophic states and in reproductive diapause. Given that C. pipiens visits a variety of flowers for nectar-feeding, the three compounds identified here are likely not the only floral components attractive to them, and more effective blends may remain to be discovered. It also remains to be seen whether different mosquito species use similar chemical cues. Future research should seek additional attractants and determine optimal blend release rates, delivery systems, and trap designs for maximizing capture in the field.
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Domain: Agricultural And Food Sciences
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Performance of Push–Pull Technology in Low-Fertility Soils under Conventional and Conservation Agriculture Farming Systems in Malawi
: Push–pull technology (PPT) is one of the most viable low-cost agroecological practices that reduces the effects of insect pest infestations (e.g., stemborer) and parasitic weeds (e.g., Striga ) in croplands. PPT was evaluated in low-fertility soils and two farming practices, minimum-tilled conservation agriculture practice (CA), and conventionally tilled practice (CP), in contrasting agroecological zones at the Chitedze, Mbawa, and Chitala stations in Malawi. Stemborer and Striga infestations were also investigated and the suitability levels of two Desmodium species. Farmers’ perceptions of PPT were gathered through a focus group discussion. The performance of PPT varied significantly between treatments, sites, and years on grain yields and the number of cobs that could be assigned to soil attributes. Significant variations were found in the number of exit holes, stemborer damage severity, and the number of Striga -affected plants with severe infestation. In Chitedze, CP recorded significantly shorter maize plants by 14.1, 11.6, and 5.8 cm than CP–PP, CA, and CA–PP, respectively, in 2016–2017. There were no significant differences in plant height between CP–PP, CA, and CA–PP. Similar results were also found in 2017–2018. Focus group discussions among farmers attested to up to 70% reductions in Striga weed and stemborer pests under PPT over the two seasons. Farmers who used push–pull technology reported a 45–50% yield increase. Push–pull was also perceived as a technology that improves soil fertility and controls soil erosion. The study presented the importance of soil physicochemical properties in the performance of the technology, as supported by the high occurrence of Striga asiatica in the country and the low suitability of Greenleaf Desmodium . Results reaffirmed the technology’s agronomic benefits in productivity, pest management, plant vigour, and Striga control. The cost of labour was described as a challenge, and research to identify more suitable Desmodium species is needed. The current study suggests the release of the technology in Malawi, emphasizing the inclusion of Desmodium and Brachiaria as animal fodder for the adoption of the technology.
Introduction
Maize Zea mays L. is the staple crop in Malawi and a major source of carbohydrates for over 80% of the Malawian population [1]. Approximately 70% of the land area under cultivation is under maize production each year [2]. Unfortunately, maize production in of Desmodium species and Striga to guide PPT scaling, and (iii) to understand the socioeconomic drivers that may influence the adoption of the technology.
Materials and Methods
Field experiments were conducted using on-station research sites in Chitala, Chitedze, and Mbawa under unimodal rainfed conditions for three growing seasons between 2016 and 2019, in different contrasting agro-ecologies. On-farm co-validation activities were conducted in Lilongwe, Salima, Nkhotakota, and Mzimba. Figure 1 shows the four agroecological regions in Malawi considered in this study. The objectives of this study were (i) to investigate the performance of PPT under current farming practices in various agroecological zones; and (ii) to evaluate the suitability of Desmodium species and Striga to guide PPT scaling, and (iii) to understand the socio-economic drivers that may influence the adoption of the technology.
Materials and Methods
Field experiments were conducted using on-station research sites in Chitala, Chitedze, and Mbawa under unimodal rainfed conditions for three growing seasons between 2016 and 2019, in different contrasting agro-ecologies. On-farm co-validation activities were conducted in Lilongwe, Salima, Nkhotakota, and Mzimba. Figure 1 shows the four agro-ecological regions in Malawi considered in this study. In Malawi, the rainfall season starts in November-December, which coincides with the planting season of most of the annual crops. The end of the rainfall season is between In Malawi, the rainfall season starts in November-December, which coincides with the planting season of most of the annual crops. The end of the rainfall season is between April and May, which initiates most of the harvesting activities of most crops. Figure 2 shows the rainfall patterns during the three maize growing seasons considered in this study. April and May, which initiates most of the harvesting activities of most crops. Figure 2 shows the rainfall patterns during the three maize growing seasons considered in this study.
Soil Characterisation
Soil properties are critical for the propagation of Striga and the success of the companion crops in a PPT [31]. The physical and chemical soil properties from the topsoil profile (0-20 cm) were analysed from the Chitedze Agricultural Research Station laboratory. Soil samples were analysed for total soil organic carbon (SOC) using the Walkley and Black method described by Anderson and Ingrams [32]. Thesoil organic matter (SOM) and mineralisable N were derived from the SOC and SOM, respectively, by multiplying the percentage concentration with a factor. Phosphorus and exchangeable base cations of K, Ca, and Mg were analysed using the Mehlich 3 method as described in [33]. The results of the analysis are detailed in Table 1. Rainfall (mm)
Soil Characterisation
Soil properties are critical for the propagation of Striga and the success of the companion crops in a PPT [31]. The physical and chemical soil properties from the topsoil profile (0-20 cm) were analysed from the Chitedze Agricultural Research Station laboratory. Soil samples were analysed for total soil organic carbon (SOC) using the Walkley and Black method described by Anderson and Ingrams [32]. Thesoil organic matter (SOM) and mineralisable N were derived from the SOC and SOM, respectively, by multiplying the percentage concentration with a factor. Phosphorus and exchangeable base cations of K, Ca, and Mg were analysed using the Mehlich 3 method as described in [33]. The results of the analysis are detailed in Table 1.
Design, Treatments, and Field Layout
A set of four plots or treatments shown in Figure 3 were arranged in a randomised complete block design and replicated three times at every site. The plot size was 10 m long × 10 m wide, with 0.75 m between rows. Two of the four plots were sown with maize/Desmodium intercropping under CA (CA-PP) and CP (CP-PP), with grass planted at the perimeter of each plot (Figure 3). A 1 m buffer separated the plots from each other. The other two plots were sown with maize mono-cropping under CA and CP. The maize mono-cropping plots were established 5 m away from the maize/Desmodium intercropping plots ( Figure 3). The intercropping treatments and their corresponding monocrops were sown at a similar maize sowing density to compare them. maize/Desmodium intercropping under CA (CA-PP) and CP (CP-PP), with grass planted at the perimeter of each plot ( Figure 3). A 1 m buffer separated the plots from each other. The other two plots were sown with maize mono-cropping under CA and CP. The maize mono-cropping plots were established 5 m away from the maize/Desmodium intercropping plots ( Figure 3). The intercropping treatments and their corresponding monocrops were sown at a similar maize sowing density to compare them.
Land Preparation
During the first year, the land was ploughed and harrowed in the conventional plots under dry conditions to achieve a fine soil tilth, ensuring good germination of smallseeded legumes such as Desmodium. The untilled CA-based plots were mulched with maize stalks at the recommended 2-3 t/ha [34]. The CP-based plots were not mulched to mimic the farmers' CP. In the second and third years, crop residues were removed in the CP plots as per the farmer's practice and retained in the CA plots.
Planting and Crop Management
Maize was used as a test crop and was sown on flat soil surfaces with a dibble stick and ridges in the CA and CP plots, respectively. The rows were spaced at 75 cm apart, with seeds sown at 25 cm apart within each row. Two maize seeds were initially sown and later thinned to one plant per planting station, two weeks after emergence, to maintain an optimum plant population of 53,000 per hectare [35]. The same plots and their respective treatments were consistently maintained for three years.
Two rows of Brachiaria were planted around the maize/Desmodium intercropping plots. Desmodium intortum was planted between the two rows of maize in all the intercropping plots at a spacing of 37.5 cm from the maize row to protect maize from
Land Preparation
During the first year, the land was ploughed and harrowed in the conventional plots under dry conditions to achieve a fine soil tilth, ensuring good germination of small-seeded legumes such as Desmodium. The untilled CA-based plots were mulched with maize stalks at the recommended 2-3 t/ha [34]. The CP-based plots were not mulched to mimic the farmers' CP. In the second and third years, crop residues were removed in the CP plots as per the farmer's practice and retained in the CA plots.
Planting and Crop Management
Maize was used as a test crop and was sown on flat soil surfaces with a dibble stick and ridges in the CA and CP plots, respectively. The rows were spaced at 75 cm apart, with seeds sown at 25 cm apart within each row. Two maize seeds were initially sown and later thinned to one plant per planting station, two weeks after emergence, to maintain an optimum plant population of 53,000 per hectare [35]. The same plots and their respective treatments were consistently maintained for three years.
Two rows of Brachiaria were planted around the maize/Desmodium intercropping plots. Desmodium intortum was planted between the two rows of maize in all the intercropping plots at a spacing of 37.5 cm from the maize row to protect maize from outside Striga infestation ( Figure 3). The seeds were mixed with dry sand in the ratio of one part of seeds to three parts of dry sand to ensure the uniform distribution of Desmodium within a row. The seeds were broadcasted into the shallow grooves at an average soil depth of 1 to 2 cm under adequate soil moisture conditions to enhance good germination [36].
Weed Management
At planting, glyphosate was applied in CA plots at a rate of 2.5 L ha −1 as a general spray, and careful superficial manual (hand pulling, where necessary light hoe) weeding was performed within the cropping season. Weeding in CP plots was carefully carried out at 3 and 5 weeks after planting (WAP) to avoid uprooting Desmodium intercrop plants. The missing gaps were filled using root splits/cuttings or vines to optimize the Desmodium plant population. Desmodium has very aggressive growth habits; if sown as an intercrop and left untrimmed, it can overshadow or smother the maize companion crop. Therefore, Desmodium was continuously trimmed until the maize crop reached knee height before it was left to cover the soil. This activity was performed at 3 and 6 WAP, as recommended by Khan et al. [36].
2.6. Data Collection 2.6.1. Maize Yield Maize yield data was determined according to an area of 3 m × 3 m within each plot to avoid border effect errors. The fresh weights of the cobs at harvest were recorded from each quadrant. Composite samples from each treatment (about 5 cobs) were taken for dry cob weight, grain weight, and grain moisture at harvest. Samples were sundried, and grain moisture content was measured and adjusted to 13% using a handheld grain moisture meter (Dickey-John USA Grain Moisture Tester, Minigac GAC 2500_US, R. K. Enterprises, New Delhi, India) as stipulated in Lark et al. [37]. The grain moisture adjustment was performed to help standardise the yield performance of different treatments and eliminate experimental error sources due to differences in drying methods.
Plant height was recorded at harvest by recording the maize height of 10 plants per plot, from the ground level to the first split of the tassels.
Striga Infestation and Stemborer Damage
The
Striga and Desmodium Mapping
Striga suitability analysis was performed using a GIS multicriteria decision-making approach. A literature review, expert opinions, and information collected in the field guided the variables to be incorporated in the Striga suitability analysis. The variables included annual mean rainfall, annual mean temperature, soil pH, soil organic concentration, and soil nitrogen and sand content. The raster datasets on each of these indicators were assembled, resampled to a resolution of 1 km, and processed from several sources for the Malawi region. The Striga-suitable areas were obtained by overlaying all the thematic layers in terms of weighted overlay methods, using the spatial analysis tool in ArcGIS 10.3 [40].
These layers were reclassified to a common suitability scale of 1 to 9, where class '9 represented the highest value. The evaluation scale was chosen following [41]. The reclassified layers were then weighted by assigning an equal percentage influence value. This is achieved by multiplying each raster cell's reclassified value by its layer weight and totaling the values to derive a suitability value. Both weight and rating values were assigned through expert knowledge and field observations. The output was compiled to produce a map indicating Striga suitability levels in Malawi.
In situ data retrieved from the Global Biodiversity Information Facility (GBIF: [URL]: //www.gbif.org/: accessed 2 November 2021) was used to develop ecological niche models of D. uncinatum (Silverleaf Desmodium) (n = 43) and D. intortum (Greenleaf Desmodium) (n = 36), which are the species favourable for the conventional and climate-smart PPT systems, respectively [27]. Presence records of the two species were combined with 19 bioclimatic variables to assess habitat suitability of the forage legume by using maximum entropy modelling (MaxEnt) in the MaxEnt tool package, version 3.4.0 k, which performs well for modelling presence-only data. This machine learning algorithm estimates a species distribution closest to uniform based on the environmental conditions at known occurrence sites [42]. The 19 bioclimatic layers contain grids of temperature and rainfall variables that interpolate observed data at a spatial resolution of 1 km. The layers were sourced from the Worldclim data repository ( [URL]/: accessed 2 November 2021). The variance inflation factor method was applied to eliminate collinear variables [43]. This exercise was performed using R software's 'usdm' package [44,45]. Out of the 19 bioclimatic variables, 8 were considered for the modelling experiment. Response curves and jack-knife graphs were used to assess variable importance following [43].
Seventy percent of the 'presence only' data was used as training data, while 30% was used to validate the model [46,47]. The threshold independent area under the curve (AUC) of the receiver operating characteristic (ROC) was used to assess the accuracy of the model [48].
Focus Group Discussion
Focus group discussions (FGDs) were used to understand the socio-economic profiles of the targeted villages/communities, the main economic activities, crop and livestock production constraints, and how these constraints are tackled locally [49]. Farmers' perceptions of the technology's benefits and possible adoption challenges were investigated, and an emphasis was placed on maize production constraints. Further, the FGDs elicited information on the sources of agricultural extension information. Eight FGDs were conducted in four of the five project districts (i.e., two FGDs in each district), where PPT was being validated for scaling-up. The four districts covered were Lilongwe, Salima, Nkhotakota, and Mzimba. The FGDs each constituted a group of about 9-25 key informants of both genders. Informants were assembled in a central place in a village. These key informants came from different villages. A prepared checklist was used to guide the discussions, which an economist moderated. An interpreter who was fluent in the local language facilitated the interview. Following the PPT demonstration, the host farmers were asked to enumerate some of the potential benefits they had experienced in the last season when they hosted the demonstrations.
Data Analysis
The data were subjected to the general analysis of variance (ANOVA) model using Genstat (Version 15.1, VSN International Ltd., Hemel Hempstead, UK). Statistical comparisons of the treatment means at a 5% probability level were conducted using the least significant differences (LSD).
Effect on Grain Yields and Number of Cobs
Overall, there were significant decreases over the years (p < 0.001) and between the various sites (p < 0.001), and the interactions between the years and the sites were also significant (p < 0.001). Overall, the treatment effect was not significant; however, the interaction between the sites and the treatment was marginally significant (p = 0.045). The interaction between treatment and year was not significant, and the combined interaction between treatment, year, and site were also not significant (p = 0.082).
Effect of Push-Pull Technology on Grain Yields at Chitedze, Mbawa, and Chitala Research Stations
In Chitedze, the treatments had a significant effect (p < 0.01) on the grain yield. In 2016-2017, maize grain yields were significantly higher in CP by 1001, 1967, and 1691 kg Sustainability 2022, 14, 2162 9 of 21 than CP-PP, CA, and CA-PP, respectively. The yield in CP-PP was significantly higher by 690 kg and 966 kg than those in CA and CA-PP, respectively. In 2017-2018, maize grain yield was significantly higher in CA than CP, CA-PP, and CP-PP by 1031, 1975, and 2761 kg, respectively. There was also a significant difference between CP on the one hand and CA-PP and CP-PP on the other. In 2018-19, CP treatments again recorded the highest yields, but no significant differences were found between the other treatments.
In Mbawa, there was a significant seasonal effect (p < 0.001) on the grain yield. Season 2016-2017 recorded the highest grain yield. In 2016-2017, sole maize treatments in CP and CA had higher grain yields by 2376 and 2316 kg than in CA-PP. However, no significant differences were found between CA, CP, and CP-PP. In 2017-2018, no significant differences were found between the treatments. In the 2018-2019 season, CP-PP recorded significantly higher maize grain yield by 1227 kg and 1269 kg than CA and CP and was not significantly different from CA-PP (Table 2). (Table 2).
Effect of Push-Pull Technology on the Number of Maize Cobs at Chitedze, Mbawa and Chitala Research Stations
In Chitedze, there was a significant effect (p < 0.001) of the season and the treatments on the number of maize cobs harvested (Table 3). In 2016-2017, CP and CP-PP plots had significantly higher numbers of maize cobs by 11.7, 15.7, and 8.7, 12.7 than CA and CA-PP, respectively. However, in 2017-2018, CP, CA, and CP-PP had a significantly higher number of cobs, respectively, by 12.6, 12.3, and 9.0 than CA-PP. In the 2018-2019 season, CP recorded a significantly higher number of cobs by 4.7, 7.7, and 10.0 than CP-PP, CA-PP, and CA (Table 3). There were significant differences between CA and CP but no differences between CA-PP and CA (Table 4). (Table 4).
Effect on the Damage Level: Number of Stemborer Exit Holes
The season and the treatment significantly affected the number of exit holes. During the 2016-2017 growing season, CP had more exit holes than CP-PP, CA, and CA-PP (respectively by 0.44, 1.10, and 1.13). There were significant differences between CP-PP on the one hand and CA and CA-PP on the other, but no significant differences were recorded between CA and CA-PP. Stemborer severity in CP was significantly higher by 1.3 and 1.6 than CA and CA-PP, respectively. There were also significant differences between CP, CA and CP-PP. However, there were no significant differences between CP and CP-PP and between CA and CA-PP (Table 4).
In the 2017-2018 season, CA-PP and CP-PP recorded significantly fewer numbers of stemborer exit holes than (CA-PP: 1.52 and 1.47 for CA and CP, respectively, and CP-PP: 1.24 and 1.19 for CA and CP, respectively). Stemborer severity showed a similar trend to that of the previous year (Table 4).
Striga Severity and Number of Plants Affected by Striga
Striga severity was significantly affected by the seasons and treatments. The 2018-2019 season recorded significantly higher Striga severity than 2017-2018 (Table 5). In 2017-2018 the Striga severity was significantly higher by 0.6, 0.7, and 1 than CP-PP-CA and CA-PP. The number of plants affected by Striga reflected a similar trend as the severity score. The 2018-2019 season had the highest infestation of Striga (Table 5). CP-PP and CP recorded a higher severity than CA (2.0 and 1.7) and CA-PP (2.3 and 2.0), respectively. The number of plants affected by Striga also reflected a similar trend as the severity score (Table 5). (Table 6). There were no significant differences in plant height between CP-PP, CA, and CA-PP. Similarly, in 2017-2018, CP also recorded significantly shorter maize plants by 19.2, 23.9, and 24.9 cm than CP-PP, CA, and CA-PP, respectively (Table 6).
Striga Mapping
The output map showed regions with high to low suitability for Striga occurrence in the whole country ( Figure 4). The model predicted a very high Striga asiatica suitability in areas around the Mbawa and Chitedze Research Stations, whereas it was moderate to low in the Chitala Research Station area.
Desmodium Climate Suitability Model
The AUC values were all higher than 0.5, indicating an optimal occurrence area in all the species (Figure 5). This shows that the model successfully predicted the suitable habitat area for the two Desmodium species.
Desmodium Climate Suitability Model
The AUC values were all higher than 0.5, indicating an optimal occurrence area in all the species (Figure 5). This shows that the model successfully predicted the suitable habitat area for the two Desmodium species. Sustainability 2022, 14, x FOR PEER REVIEW 14 of 22 The jack-knife test demonstrated that precipitation of the warmest quarter (Bio_18) is the most important variable in determining the suitability of the two Desmodium species ( Figure 6). The response of Desmodium performance to the four most important bioclimatic variables is illustrated. The response curves of the four variables in the Silverleaf Desmodium model (Figure 7) indicated that Silverleaf Desmodium performs optimally at the precipitation of 400-600 mm in the warmest quarter ( Figure 7A) and up to 1200 mm in the wettest month ( Figure 7C). The forage legume thrives in a mean temperature of 20 °C in the wettest quarter ( Figure 7B) and a mean diurnal temperature range of 6-10 °C ( Figure 7D). The jack-knife test demonstrated that precipitation of the warmest quarter (Bio_18) is the most important variable in determining the suitability of the two Desmodium species ( Figure 6). The jack-knife test demonstrated that precipitation of the warmest quarter (Bio_18) is the most important variable in determining the suitability of the two Desmodium species ( Figure 6). The response of Desmodium performance to the four most important bioclimatic variables is illustrated. The response curves of the four variables in the Silverleaf Desmodium model (Figure 7) indicated that Silverleaf Desmodium performs optimally at the precipitation of 400-600 mm in the warmest quarter ( Figure 7A) and up to 1200 mm in the wettest month ( Figure 7C). The forage legume thrives in a mean temperature of 20 °C in the wettest quarter ( Figure 7B) and a mean diurnal temperature range of 6-10 °C ( Figure 7D). The response of Desmodium performance to the four most important bioclimatic variables is illustrated. The response curves of the four variables in the Silverleaf Desmodium model (Figure 7) indicated that Silverleaf Desmodium performs optimally at the precipitation of 400-600 mm in the warmest quarter ( Figure 7A) and up to 1200 mm in the wettest month ( Figure 7C). The forage legume thrives in a mean temperature of 20 • C in the wettest quarter ( Figure 7B) and a mean diurnal temperature range of 6-10 • C ( Figure 7D).
The response curves of the four variables in the Greenleaf Desmodium model (Figure 8) indicated that Greenleaf Desmodium performs optimally at the precipitation of 400-1400 mm in the warmest quarter ( Figure 8A) and between 20-160 mm in the driest month ( Figure 8C). It thrives well even with a high temperature seasonality ( Figure 8B) and a mean diurnal temperature range of 6-8 • C ( Figure 8D). The response curves of the four variables in the Greenleaf Desmodium model ( Figure 8) indicated that Greenleaf Desmodium performs optimally at the precipitation of 400-1400 mm in the warmest quarter ( Figure 8A) and between 20-160 mm in the driest month ( Figure 8C). It thrives well even with a high temperature seasonality ( Figure 8B) and a mean diurnal temperature range of 6-8 °C ( Figure 8D). The response curves of the four variables in the Greenleaf Desmodium model ( Figure 8) indicated that Greenleaf Desmodium performs optimally at the precipitation of 400-1400 mm in the warmest quarter ( Figure 8A) and between 20-160 mm in the driest month ( Figure 8C). It thrives well even with a high temperature seasonality ( Figure 8B) and a mean diurnal temperature range of 6-8 °C ( Figure 8D). A comparison of the two models indicated that Silverleaf Desmodium generally has higher suitability than Greenleaf Desmodium across all the districts in Malawi (Figure 9). The suitability of Greenleaf Desmodium used in this study in the target districts was found to be very low (Figure 9). A comparison of the two models indicated that Silverleaf Desmodium generally has higher suitability than Greenleaf Desmodium across all the districts in Malawi (Figure 9). The suitability of Greenleaf Desmodium used in this study in the target districts was found to be very low (Figure 9).
Focus Group Discussions
After introducing PPT, farmers showed much enthusiasm in taking up the technology since they noticed that it could significantly reduce Striga weed and stemborer pests by up to 70%. They also attested that they had seen a significant increase in maize yield (Table 7). However, the cost of labour in terms of ploughing,planting, weeding, harvesting, and threshing was higher in PPT-based treatments.
Focus Group Discussions
After introducing PPT, farmers showed much enthusiasm in taking up the technology since they noticed that it could significantly reduce Striga weed and stemborer pests by up to 70%. They also attested that they had seen a significant increase in maize yield (Table 7). However, the cost of labour in terms of ploughing, planting, weeding, harvesting, and threshing was higher in PPT-based treatments.
Discussion
Despite deficient soils and erratic rainfall patterns, the expected agronomic benefits in yield, pest management, and plant features were achieved under CA and CP. The [1,2]. Crop performance in terms of yield was related to soil physicochemical properties (Table 8). Soil analysis results showed an excess of potassium in all samples. Mbawa soils are acidic and deficient in nutrients, including nitrogen, essential for maize growth. Chitedze soils are also acidic and deficient in nitrogen and phosphorus, and their pH is moderately acidic. Chitala soils are less acidic than others, often with an excess of phosphorus. Areas with high deficiency seemed more favourable for sole maize due to interspecific competition between maize, Desmodium, and Brachiaria. PPT seemed to be more compatible with CP in low-fertility soils. Desmodium is a perennial plant that expands its root system in subsequent seasons [50]. CP supports ploughing, and the disturbance caused to the roots prevents competition for nutrients between maize and the companion plants (Desmodium and Brachiaria). PPT was only compatible with CA in Chitala, where soil nutrients were balanced. Results on grain yield and the number of cobs in that region testified to the agronomic performance of PPT under CA. In addition to these variabilities, the rainfall pattern may interfere with a crop's agronomic performance [51]. CA and CP had the lowest exit holes. These results confirm previous findings of the superiority of PPT over convention practice in reducing lepidopteran pests, as described by Midega et al. [24], Hailu et al. [27], and Ndayisaba et al. [52]. These findings imply that maize under PPT produces better yields and has less ear rot, and hence fewer chances of Aflatoxin contamination, as reflected in the severity scores [53]. Both PPT and CA promote the presence of natural enemies, which support a more efficient control of the pest in subsequent seasons. In that regard, a spillover effect in adjacent control plots can be envisaged; hence, agronomic attributes in terms of plant vigour and height are the discriminating factors between treatments.
Both PPT and CA are soil-fertility-increasing technologies. CA is designed to increase biological diversity, reduce runoff and erosion, improve soil organic carbon, and improve crop yield [54][55][56]. Likewise, PPT improves soil moisture and nitrogen fixation, and Desmodium suppresses Striga through root exudates, mainly Isoschaftoside, a C-glycosylflavonoid, leading to suicidal germination of Striga seeds [57]. This has been confirmed in many earlier studies [52,58,59]. Additional attributes of PPT can be observed in Chitedze, whereby PPT maize plants in CP (2016-2017) and PPT maize plants under CA 2017-2018 were taller than the plants in the other treatments. It can be concluded that the application of PPT or CA contributes to a drastic reduction in Striga through soil fertility improvement.
Desmodium Greenleaf has very low suitability in the target sites. Desmodium Greenleaf originates from South America and requires neutral soils (pH < 7) [60]. Its optimal temperature ranges between 25 and 30 • C, and it performs better between 500 and 2500 m in the tropics where annual rainfall is above 900 mm and up to 3000 mm [60]. In that regard, Desmodium Silverleaf showed a much higher coverage and suitability in the country.
PPT is a sustainable and low-input production system that relies on household labour for ploughing, planting, weeding, harvesting, and threshing. PPT does not require external inputs such as chemical pesticides to reduce incidences of stemborer and Striga in maize. Farmers involved in the FGDs reported increased productivity between 45-50% and improved arthropod abundance, soil biota and soil organic matter, and overall environmental health. Recently, PPT was found to control FAW, a serious invasive pest of cereal crops in Africa [24,27]. Therefore, dissemination and outreach campaigns need to emphasize the multiple benefits of the technology, including the use of Brachiaria and Desmodium and fodder crops [61,62].
The FGDs showed that farmers considered PPT as a yield-increasing technology. However, the initial establishment and planting of PPT requires ploughing and harrowing the land to a fine tilth for the sowing of Desmodium seeds and the general layout of the plot. Several studies have demonstrated that the cost of the initial establishment might be high, but it is reduced over time.
Conclusions
This study is the first to investigate PPT's performance in various agroecological zones in Malawi under two farming practices. The study confirmed the classical benefits of technology in terms of stemborer and Striga control. However, PPT was more compatible with CP in low-soil-fertility areas, probably due to below-ground competition under CA. The combination of PPT and CA can only occur in areas of moderate soil fertility. Root pruning is therefore compulsory to avoid plant stunting in subsequent seasons. The combination of PPT and CA was very effective in controlling Striga. Desmodium Silverleaf is more suitable in Malawi than Greenleaf is. While further research is needed to identify indigenous Desmodium, the current study supports the release of the technology in Malawi. Desmodium and Brachiaria as animal fodder can offer a comparative advantage for adopting the technology.
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Domain: Agricultural And Food Sciences
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Acute and 28-Day Repeated-Dose Oral Toxicity of the Herbal Formula Guixiong Yimu San in Mice and Sprague–Dawley Rats
Simple Summary Postpartum uterine diseases of dairy cows include retained placenta (RP) and puerperal metritis (PM). Cows suffering from a retained placenta are at an increased danger of developing puerperal metritis or endometritis, and subsequent decreased fertility. The dominant approach to a retained placenta in cows is the local or systemic administration of antibiotics; however, current reports point to the low efficacy of intrauterine and systemic antibiotics in accelerating the separation and removal of the retained placenta. Therefore, substitute approaches to cope with these two disorders in postpartum cows should be developed. Herbal medicines are considered good alternatives to allopathic medicine, and some ethno-veterinary medicines are often used to treat the RP in cows. GYS is primarily used to treat postpartum blood stasis syndrome caused by retained placenta. It was designed based on the therapeutic role of enhancing the blood flow and removing blood stasis, maintaining the qi movement, and releasingthe pain. It can create a very promising state for prior placental detachment and the spontaneous discharge of the RP, but its toxicity has not been completely assessed. In the present study, we demonstrated that GYS did not have any therapeutic side effects in rats, thus providing a practical approach for the clinical control of a retained placenta. Abstract To evaluate the acute and chronic 28-day repeated-dose oral toxicity of Guixiong Yimu San (GYS) in mice and rats, high-performance liquid chromatography (HPLC) was used to determine the stachydrine hydrochloride in GYS as the quality control. In the acute toxicity trial, the mice were administered orally at a dose rate of 30.0 g GYS/kg body weight (BW) three times a day. The general behavior, side effects, and death rate were noticed for 14 days following treatment. In the subacute toxicity trial, the rats were administered orally at a dose rates of30.0, 15.0, and 7.5 g GYS/kg BW once a day for 28 days. The rats were monitored every day for clinical signs and deaths; changes in body weight and relative organ weights (ROW) were recorded every week, hematological, biochemical, and pathological parameters were also examined at the end of treatment. The results showed that the level of stachydrine hydrochloride in GYS was 2.272 mg/g. In the acute toxicity trial, the maximum-tolerated dose of GYS was more than 90.0 g/kg BW, and no adverse effects or mortalities were noticed during the 14 days in the mice. At the given dose, there were no death or toxicity signs all through the 28-day subacute toxicity trial. The oral administration of GYS at a dose rate of 30.0 g/kg/day BW had no substantial effects on BW, ROW, blood hematology, gross pathology, histopathology, and biochemistry (except glucose), so 30.0 g/kg BW/day was determined as the no-observed-adverse-effect dosage.
Introduction
A retained placenta (RP) is a frequent uterine disorder in first postpartum cattle [1,2]. Cows with an RP have an increased danger of developing puerperal metritis, and the Vet. Sci.2023, 10, 615 2 of 17 consequences of an RP on farm productivity partially depend on the occurrence of metritis [3][4][5]. Thus, the medical therapy for a retained placenta is an ideal means to avoid puerperal metritis in cows. Usually, the principal strategy to an RP in cattle is the local or systemic administration of antibiotics [6,7]. Previous studies [6,7] have demonstrated the benefits of an intrauterine antibiotic treatment for the prevention of metritis in cows with an RP. Ceftiofur, a 3rd generation cephalosporin drug does not leave antibiotic residues in the milk when used in line with the label guidelines and has therefore been useful in clinical practice for treating cows with a retained placenta and preventing metritis [8][9][10]. However, current reports point to the low efficacy of intrauterine and systemic antibioticsin accelerating the separation and removal of the RP [11][12][13]. Therefore, substitute approaches to cope with these two disorders in postpartum cows should be developed. Traditional Chinese veterinary medicine (TCVM) has always been more focused on the body's reaction to pathogenetic causes compared to pathological pathways [6,14,15], and thus, it may offer novel possibilities for the management of post-delivery uterine disorders in cows.
Guixiong Yimu San (GYS) has been used for the clinical treatment of a retained placenta with satisfactory therapeutic effects (the therapeutic oral dose for cows is approximately 0.5 g/kg BWonce per day for 1-3 days), and it can also lower the risk of puerperal metritis in postpartum cows [16,17]. GYS used in the present study consisted ofsix Chinese herbs, including Leonuri herba (Yi-Mu-Cao, YMC; Leonurus japonicus Houtt.),Angelicae sinensis radix (Dang-Gui, DG; Angelica sinensis (Oliv.)Diels), Chuanxiong rhizoma (Chuan-Xiong, CX; Ligusticum chuanxiong Hort.), Carthami flos (Hong-Hua, HH; Carthamus tinctorius L.), Cyperi rhizoma (Xiang-Fu, XF; Cyperus rotundus L.), and Glycyrrhizae radix et.rhizoma (Gan-Cao, GC; Glycyrrhiza uralensis Fisch.). It was designed based on the therapeutic role of enhancing blood flow and removing blood stasis, maintaining the qi movement, and releasing the pain. All of the herbal plants work collectively as a recipe to increase the blood flow, convert stasis, contract of the uterus, warm up the channels, and relievethe pain to resolve the postpartum blood stasis syndrome. By removing blood stasis from the retained placenta, regulating the uterine contractions, and improving the uterine state, GYS can create a much more promising situation for earlier placental separation and the spontaneous release of the RP [18][19][20]. Numerous phytochemical compounds, such as alkaloids, saponins, flavonoids, volatile oil, ferulic acid, and others, have been identified in the herbs contained in GYS [21][22][23][24]. In accordance with the composition of the traditional Chinese medicine formula, the preferred principle of Monarch drug (JUNYAO), and the instruction of the Committee for the Veterinary Pharmacopoeia of China (2015 version) [25], stachydrine hydrochloride, the biologically active chemical compound of Leonuri herba (Yi-Mu-Cao, Monarch drug, the key component of herbal formula), was indicated to be a biomarker of GYS for qualitative identification and quantitative analysis, which may improve the level of quality control and promote the internationalization of TCMs.
Pharmacological studies and clinical trials of GYS have been performed, and multiple scientific researchers have confirmed its therapeutic value, thereby attracting growing attention to the application of GYS [17,20]. Although, to the best of our information, there has been no systemic research on the subacute toxicity of GYS to support clinical drug safety, and generally very little is known about the toxicity of GYS. Along with the development of a potent herbal product, the evaluation of adverse effects on living organisms is one of the key issues; therefore, further studies should establish the toxicity profile of GYS by evaluating its safety parameters using the standardized trial protocols from regulatory organizations. In the present study, the safety of GYS was evaluated through oral administration by undergoing the acute and subacute toxicity trials in mice and rats, respectively. The acute and 28-day repeated-dose oral toxicity experiments of GYS are essential for clarifying the drug's toxicity, and providing a basis for the subsequent application of GYS. Moreover, such experiments may assist in treating the cows with an RP and the prevention of PM under field circumstances, and may provide guidance for phase II clinical trials.
For HPLC analysis, stachydrine hydrochloride-the active compound of Leonuri herba (Yi-Mu-Cao)-was chosen as the biomarker in the HPLC-based quality control. Stachydrine hydrochloride was obtained from the National Institutes for Food and Drug Control (Purity > 98%, Batch No.: 110712-201614, Beijing, China). Stock solution of the relevant criteria was made at the appropriate concentration (0.0375 mg/mL, w/v) in methanol and kept at 4 • C up tofurther analysis. Ethanol and acetic acid were obtained from Shanghai Chemical Reagent Company, China. Acetonitrile and methanol (HPLC grade) were obtained from ThermoFisher Scientific (Waltham, MA, USA).
HPLC Analysis
The content of stachydrine hydrochloride-the active compound of Leonuri herba (Yi-Mu-Cao; JUNYAO, Monarch drug), was determined in GYS by HPLC (Chinese Veterinary PharmacopoeiaCommission, 2015; Chinese Pharmacopoeia Commission, 2020) [25,26]. Quantitative analysis of GYS was performed on Agilent 1290 Infinity G4218A, Sedex-85, Evaporative Light Scattering Detector (ELSD) (Agilent, Santa Clara, CA, USA). The column was Venusil HILIC chromatographic column (4.6 mm × 250 mm, 5.0 µm; Agela Technology Co., Ltd., Tianjin, China). The mobile phase comprised a cetonitrile (A) and 0.2% (v/v) acetic acid aqueous solution (B) (87:13), and the pH value ranged from 6.8 to 7.2. Chemicals were sieved through a Millipore 0.45 mm filter and degassed before use. The conditions were as follows: volume flow rate, 1.0 mL/min; evaporative light scatterer; column temperature, 25 • C; the temperature of the detector, 50 • C; the temperature of the atomizing chamber, 80 • C; and the injection volume, 10 µL. The theoretical plate number was not less than 5000 according to the peak of stachydrine hydrochloride. Data assembly and quantification were performed with Agilent ChemStation and Agilent EZChrom Elite (Agilent, Santa Clara, CA, USA). The peak of the stachydrine hydrochloride was recognized by comparing with standard chemicals.
Experimental Animals
Thirty Kunming (KM) mice (18-22 g, male:female = 1:1) were used for the 14-day acute toxicity trial. A total of 80 Sprague-Dawley (SD) rats, age 7-8 weeks (160-180 g, 40 males and 40 females) were used for the 28-day repeated-dose oral toxicity trial. The animals with a clean grade (Certificate No.: SCXK (G) 2020-0002) were received from the Laboratory Animal Center of Lanzhou Veterinary Research Institute (Lanzhou, China). All of the experimental animals were kept in plastic cages and kept separately according to sex under the following conditions: temperature, 22 ± 2 • C; relative humidity, 55 ± 10%; and a 12 h light/dark cycle. They were fed a standard pelleted diet (Test clean grade, granule rat feed, Nanjing, China) and ad libitum water access. The animals underwent 7-day acclimatization before the experimentalprocedures.
All of the experimental trials performed in the present study were conducted in accordance with the guidelines of the National Institutes of Health (NIH, 2015) [27] for the Care and Use of Laboratory Animals. The animal study was reviewed and approved by the Ethics Committee of the Lanzhou Institute of Husbandry and Pharmaceutical Sciences of the Chinese Academy of Agricultural Sciences (Lanzhou, China).
Oral Acute Toxicity of GYS in Mice
The acute oral toxicity of GYS was assessed in the mice by the maximum-tolerated dose (MTD) method, in accordance with the method of the Compilation of Technical Guidelines for Veterinary Drug Research (Center for Veterinary Drug Evaluation (CVDE), Ministry of Agriculture of the People's Republic of China, 2015) [28], and Organization for Economic Cooperation and Development (OECD) Guideline No. 423 (OECD, 2002) [29]. Fifteen male and female mice each go through a 7-day isolation and adaptation process. Following overnight fasting, 30.0 g GYS/kg body weight (BW) was administered orally through an oral gavage needle three times a day (total of 90.0 g GYS/kg BW/day), with a 6 h of interval among the doses. The common activities of the mice were noted down after every 4 h of treatment and 24 h for fourteen days. Towards the end of the trial, the animals were euthanized, and gross pathological changes in the vital body organ such as liver, heart, lung, spleen, gastrointestinal tract, kidneys, thymus, testes, and ovaries, were examined. Histopathological analyses were performed by H&E staining if the gross pathological changes were recorded in vital organs [30,31].
Oral 28-Day Repeated Toxicity Trial of GYS in Rats
The subacute toxicity trial was carried out in agreement with the Rules of Animal Drug 28-Day Repeated Dose Toxicity Study (CVDE, Ministry of Agriculture of People's Republic of China, 2015) [28], and followed the protocol described by OECD Guideline No. 407 (2008) [32]. Eighty SD rats were randomized into a control group (CG) and three treatment groups (n = 20; 10 male and 10 female). GYS was administered once a day by oral gavage for 28 continuous days at three different doses, i.e., at 30.0, 15.0, and 7.5 g GYS/kg BW, respectively (at 8:00-9:00 a.m.), leading to the distinction of three GYS treatment groups; namely, the high-dose group (30.0 g GYS/kg BW/day), the medium-dose group (15.0 g GYS/kg BW/day), and the low-dose group (7.5 g GYS/kg BW/day). The control group received only physiological saline (0.9% normal saline). All of the experimental animals were monitored for behavioral activities, deaths, and signs and symptoms of gross toxicity twice a day through the 28-day subacute toxicity trial. At the end of the drug administration period (24 h after the last administration), all surviving rats from each group were euthanized for blood hematology, serum biochemistry, histopathology, and relative organ weight (ROW) [33,34].
Clinical Observations and BW Monitoring
Clinical observations were noted once a day to record thetoxicity signs, particularly at a similar time every day (1 h after GYS or vehicle administration). The routine observation focused on fluctuations in general performance, movement, fur, skin, and eyes with particular consideration given to noting the occurrence of lethargy, diarrhea, tremors, coma, convulsions, and sleep. The BW of each rat was noted before the administration of GYS at day 1, every 7th day thereafter, and necropsy day. The BW at necropsy was noted after 16 h fasting. The average body weight gain (BWG) of a week was measured for each sex and dosage level throughout the whole trial period (Tables S1 and S2). Additionally, the amounts of feed given and their leftovers on the following day were estimated to determine the difference which was considered as daily feed consumption (Tables S1 and S2). The average daily feed utilization was estimated for each dosage and sex for every week interval and the total trial period.
Blood samples for serum biochemical assays were kept for 2 h to clot, and centrifugation was performed at 4000 rpm and 4 • C for 10 min and then stored at −20 • C until further analysis. The main parameters included were alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (CRE), glucose (GLU), total bilirubin (TBL), total protein (TP), blood urea nitrogen (BUN), total cholesterol (TC), triglyceride (TG), and albumin (ALB), and were measured with an automatic serum biochemistry analyzer (BS-420, Shenzhen Mindray Bio-Medical Electronics Co., Ltd. Shenzhen, China) by fixing the biological reference intervals for the sex and strain of the rats. Samples were protected from light by using aluminum foil, especially for bilirubin.
Gross Necropsy and Organ Weights
Necropsies were carefully conducted on all of the rats. Later to blood collection, the rats were euthanized by exsanguination from the aorta and vena cava. The animals were carefully observed for external defects. The thoracic and abdominal cavities were also observed for defects. Moreover, selected vital organs (heart, lungs, liver, spleen, and kidney), reproductive (uterus and ovary or testis), the stomach, and intestines were examined macroscopically. Then, the organs were quickly detached, balanced, and secured in 10% neutral buffered formalin solution (SolarBio Technology Co., Ltd., Beijing, China) for at least 48 h. The ROW was estimated using the following formula; organ weight/body weight on euthanize day × 100% (Tables S1 and S2).
Histopathological Analyses
After fixation, the selected tissues were dried up in a high-grade ethanolsolution with 70, 90, 95, and 100% and treated with ethyl salicylate. After embedding in paraffin and cutting to 5 µm-thick pieces, the tissue pieces were dyed with hematoxylin and eosin (H&E) for photo-microscopic analysis.
Statistical Analysis
Data were expressed as the mean and standard deviations (mean ± SD). Mean differences among the control and treatment groups were evaluated by one-way analysis of variance (ANOVA), followed by Tukey'smultiple comparison and Dunnett-t post-hoc test for 28-day repeated-dose toxicity (SPSS Statistics 19.0, IBM, Chicago, IL, USA). Graphs were drawn using the GraphPad Prism 5.0 (GraphPad Prism, San Diego, CA, USA).p < 0.05 was considered as significant.
HPLCAnalyses
The HPLC chromatogram of GYS is displayed in Figure 1. As the active compound of Leonuri herba (Leonurus japonicus Houtt., JUNYAO, Monarch drug), stachydrine hydrochloride was found in GYS at 2.272 mg/g through HPLC analysis.
Acute Toxicity
During the 14-day acute toxicity test, neither mortality nor abnormalities in behavior (lethargy, sleep, coma, tremor, and diarrhea) were observed in any of the mice. In addition, no significant pathological changes in the colors and textures of vital organs, including the heart, lung, liver, kidneys, spleen, thymus, ovaries or testes, and gastrointestinal tract, were found by macroscopic examination. On that basis, the LD50 of GYS was estimated to be more than 90.0 g/kg BW by oral route.
HPLCAnalyses
The HPLC chromatogram of GYS is displayed in Figure 1. As the active compound of Leonuri herba (Leonurus japonicus Houtt., JUNYAO, Monarch drug), stachydrine hydrochloride was found in GYS at 2.272 mg/g through HPLC analysis.
Acute Toxicity
During the 14-day acute toxicity test, neither mortality nor abnormalities in behavior (lethargy, sleep, coma, tremor, and diarrhea) were observed in any of the mice. In addition, no significant pathological changes in the colors and textures of vital organs, including the heart, lung, liver, kidneys, spleen, thymus, ovaries or testes, and gastrointestinal tract, were found by macroscopic examination. On that basis, the LD50 of GYS was estimated to be more than 90.0 g/kg BW by oral route.
Subacute Toxicity-BW and Feed Consumption Observations
No treatment-related deaths or behavioral changes occurred during the trial period. There were no abnormal changes in clinical signs, BW, or BWG caused by the oral administration of GYS in either sex, and there were no significant variations relative to the control group (p > 0.05). Feed consumption was slightly changed in the three GYS-treated groups with no significant statistical difference from the control group (p > 0.05), illustrating that GYS had no obvious effect on the average daily gain (ADG) and average daily food intake (ADFI). Furthermore, the male rats had more significant ADG and ADFI values than the female rats, and their stage (weekly) growth advantage was more significant (Figure 2, Table 1).
Subacute Toxicity-BW and Feed Consumption Observations
No treatment-related deaths or behavioral changes occurred during the trial period. There were no abnormal changes in clinical signs, BW, or BWG caused by the oral administration of GYS in either sex, and there were no significant variations relative to the control group (p > 0.05). Feed consumption was slightly changed in the three GYS-treated groups with no significant statistical difference from the control group (p > 0.05), illustrating that GYS had no obvious effect on the average daily gain (ADG) and average daily food intake (ADFI). Furthermore, the male rats had more significant ADG and ADFI values than the female rats, and their stage (weekly) growth advantage was more significant (Figure 2, Table 1).
drochloride was found in GYS at 2.272 mg/g through HPLC analysis.
Acute Toxicity
During the 14-day acute toxicity test, neither mortality nor abnormalities in behavior (lethargy, sleep, coma, tremor, and diarrhea) were observed in any of the mice. In addition, no significant pathological changes in the colors and textures of vital organs, including the heart, lung, liver, kidneys, spleen, thymus, ovaries or testes, and gastrointestinal tract, were found by macroscopic examination. On that basis, the LD50 of GYS was estimated to be more than 90.0 g/kg BW by oral route.
Subacute Toxicity-BW and Feed Consumption Observations
No treatment-related deaths or behavioral changes occurred during the trial period. There were no abnormal changes in clinical signs, BW, or BWG caused by the oral administration of GYS in either sex, and there were no significant variations relative to the control group (p > 0.05). Feed consumption was slightly changed in the three GYS-treated groups with no significant statistical difference from the control group (p > 0.05), illustrating that GYS had no obvious effect on the average daily gain (ADG) and average daily food intake (ADFI). Furthermore, the male rats had more significant ADG and ADFI values than the female rats, and their stage (weekly) growth advantage was more significant (Figure 2, Table 1). GYS, Guixiong Yimu San; BWG, body weight gain; ADG, average daily gain; ADFI, average daily feed intake. 1-6Results were given as means ± SD (n = 10/sex/dose) and means with a different letter within a column are significantly different (p < 0.05). No statistical difference between the control and the three GYS-treated groups (p > 0.05). 2, 4, 5, 6Growth performance of rats was assessed by measuring feed intake (FI), body weight gain (BWG), and feed conversion ratios (FCRs, FCR = ADFI/ADG). Body weight (BW) of rats per cage and feed consumption were recorded on day 1, 7, 14, 21, and day 28.
Subacute Toxicity-Hematologicaland Serum Biochemical Analyses
As revealed in Table 2, all the measured blood parameters were slightly increased or decreased, i.e., there was the reduction in WBC, LYM, GRAN, RBC, PLT, and PDW in the male and female rats, and a slight increase in MONO and MPV in both sexes, but there were no remarkable differences (p > 0.05) among the three GYS-treated groups and the control group (Table 2). These data showed no clear dose-response relationships and all of the minor fluctuations in the following parameters in either sex wereinside the normal range of the testing research laboratory. The raw data for hematology and biochemistry parameters in the treatment and control male and female rats is enclosed in Tables S3 and S4. Subacute oral administration of GYS for 28 daysdid not affect significant variations (p > 0.05) in most of the biochemistry parameters, comprising serum ALP, TBL, BUN, CRE, TC, TG, TP, ALB, and the level of the indicator enzymes of the liver (AST and ALT) in both the male and the female rats (Table 3). However, the levels of GLU in both sexes on day 28 with three different doses (7.5, 15.0, and 30.0 g GYS/kg BW) decreased significantlyrelative to the control group (p < 0.05). 1-1Data were presented as means ± SD (n = 10/sex/dose, after 28-day administration), the mean difference is significant at the 0.05 level. No statistical difference between the control and the three GYS-treated groups (p > 0.05).
Table 3. Effects of daily oral administration of GYS for 28 days on the biochemical parameters of rats (n = 10). AST: aspartate aminotransferase; ALT: alanine aminotransferase; ALP: alkaline phosphatase; TBL: total bilirubin; BUN: blood urea nitrogen; CRE: creatinine; TC: total cholesterol; TG: triglyceride; GLU: glucose; TP: total protein; ALB: albumin. 1-11Data were presented as means ± SD (n = 10/sex/dose, after 28-day administration), the mean difference is significant at the 0.05 level.a b Similar superscript showing no statistically remarkable differences between the groups (p > 0.05) and vice versa.
Subacute Toxicity-ROW Analyses
After administration for 28 consecutive days, there were no statistically remarkable differences (p > 0.05) in the ROWs of the organs in the male and female groups at any dosage level. All of the slight variations in these ROW values were inside the normal range (Table 4). 1-Data were presented as means ± SD (n = 10/sex/dose, per group for male and female rats, after 28-day administration), the mean difference is significant at the 0.05 level. No statistically significant differences were found (p > 0.05).
Subacute Toxicity-Gross Necropsy and Histopathological Observation
The appearance and color of the vital and reproductive organs of the rats at necropsy were normal in all of the GYS-treated groups. There were no effusions or adhesions in the chest cavity, abdominal cavity, pericardium, or viscera, and no visible lesions such as congestion or bleeding, edema or swelling, or hypertrophy or atrophy. Microscopic observations did reveal any evident pathological modifications linked with the administration of GYS. The histopathological analysis involved the microphotographs of the small intestine, stomach, liver, heart, lung, spleen, kidney, testes, uterus, and ovaries of the rats in the three GYS-treated groups and the control group (Figures 3 and 4). We found no histopathological Vet. Sci.2023, 10, 615 10 of 17 changes in the organ sections of the rats after 28 days of GYS administration compared with the control group, illustrating that GYS had no obvious effect on the vital organs and reproductive organs and that GYS fed at 30.0 g/kg BW for 28 days was generally safe for rats. Thus, the no-observed-adverse-effect level (NOAEL) in the present study was 30.0 g GYS/kg BW.
Discussion
Recently, the area of complementary/alternative medicine has been taking on new prospects. Herbal medicines are considered good alternatives to allopathic medicine and are becoming common globally, in addition to being recommended, accompanied by Western treatments by several doctors [35,36]. Ethno-veterinary medicine plays a keypart in animal well-being globally [37][38][39]; e.g., some therapeutic plants are frequently used to treat cows with an RP [40][41][42]. Though, herbal remedies are generally not subject to toxicity trials prior to clinical uses in contrast with Western medical treatments. As many herbal drugs are being recommended, their safety has turned into a main issue. Therefore, herbal medicines also need a deeper assessment of their effectiveness and protection using standard toxicological techniques due to the need for testified medical use earlier to clinical uses [43].
The postpartum uterine diseases of dairy cows include a retained placenta and puerperal metritis. Cows with an RP are at an increased risk of puerperal metritis or endometritis, and consequent decreased fertility [2,4]. Evidence from previous studiesproposes the important effects of herbal medicines for postpartum uterine disorders in dairy cattle [17,20,44,45]. GYS is a traditional Chinese herbal formula that is principally used as a therapeutic drug for postpartum blood stasis syndrome caused by an RP, which is a frequently diagnosed uterine disorder in early postpartum cows. In the TCVM concept, blood inertia is a vital primary pathology of certain postpartum disorders [46,47]. Moreover, RP and/or PM both lie under the category of a blood stasis syndrome (Editorial Committee of Encyclopedia of China's Agriculture, 1991) [48]. Although GYS has previously been revealed as an effective herbal formula in clinical practice, its toxicity has not been fully estimated. In the present study, we conducted an acute toxicity trial in KM mice and a subacute toxicity trial in SD rats to assess the safety level of GYS.
Additionally, the quality control of medicinal agents and formulation with recent analytical equipment is increasingly essential to ensure their effectiveness. Leonuri herba (Yi-Mu-Cao) is a fresh or dried ground part of Leonurus japonicus Houtt. From the Labiaceae family. Generally, it is used as a medicine for female reproductive diseases, such as a remedy to treat delayed menstruation, premenstrual tension, and menstrual pain, and it is formally listed in the Chinese Pharmacopoeia of PR China (Chinese Pharmacopoeia Commission, 2020) [26] and Chinese Veterinary Pharmacopoeia of PR China (Chinese Veterinary Pharmacopoeia Commission, 2015) [25]. According to modern pharmacology research, it also has emmenagogue, cardiotonic, and anticoagulant activities [20,23]. The largest component of GYS is Leonuri herba-Monarch drug (JUNYAO, the importantconstituent of herbal formula)-which can enhance the uterine contractions, improve the uterine hemorheology and microcirculation against the primary indication of cows with an RP, and provide the principal therapeutic effects against postpartum blood stasis syndrome [49]. In this study, the active compound (stachydrine hydrochloride) of Leonuri herba was identified and analyzed using HPLC. The study revealed the presence of this active compound in GYS (2.272 mg/g), suggesting that the quality of GYS is improved under the present situation. Leonuri herba (Yi-Mu-Cao, YMC; 46.15%, w/w; JUNYAO, Monarch drug) is the key component of Guixiong Yimu San (GYS). In accordance with the composition of traditional Chinese medicine formula, the preferred principle of Monarch drug (JUNYAO), and the instruction of the Committee for the Veterinary Pharmacopoeia of China (2015 version), stachydrine hydrochloride, the biologically active chemical compound of Leonuri herba (the key component of herbal formula)-was indicated to be a biomarker of GYS for qualitative identification and quantitative analysis. The content of stachydrine hydrochloride is an important index component to measure the quality of GYS. The quantitative study of stachydrine hydrochloride by the HPLC method can effectively control the quality of GYS [22,49].
Our previous study suggested approximately 0.5 g/kg BW once per day for 1-3 days as the therapeutic oral dose of GYS for cows. In the acute toxicity trial, we used 90.0 g GYS/kg BW, which is nearly 60 times greater than the dosage that has previously been used in the clinical practice, to assess the MTD in the mice. In the current subacute toxicity study, three different doses (30.0, 15.0, and 7.5 g GYS/kg BW)-representing high, medium, and low doses, respectively-which are approximately 20, 10, and 5 times greater than the dosage that has previously been used in the clinical practice, respectively, were used to examine the NOAEL in the rats. The results from the acute toxicity trial revealed no adverse effects in the mice administered 90.0 g GYS/kg BW orally. Additionally, there were no anomalies detected in the mice vital organs after euthanasia. These findings showed that MTD for the oral gavage of GYS in the mice is higher than 90.0 g/kg BW which is too high than what has already been used in clinical practice. As per the CVDE Guidelines of Veterinary Drug Acute Toxicity Study (Center for Veterinary Drug Evaluation, Ministry of Agriculture of the People's Republic of China, 2015) [28], the oral administration of GYS at a dosage lower than 90.0 g/kg may be known as principally nontoxic or slightly toxic at the most. During the 28-day oral administration of GYS, none of the rats died; there were no noteworthy changes in the usual activities, posture, mucosa, or color in any of the GYS-treated groups. Furthermore, the BW and ROW of the rats' even at the high dose of GYS were not considerably different from those in the control group. Generally, reductions in BWG and ROW are mostly monitored markers of toxicity after contact with chemicals and drugs [34,50]. These outcomes propose that the longtime use of GYS with a high dose of 30.0 g/kg BW did not cause weight loss and delayed growth in the rats. Additionally, findings from a previous study [17,20] showed that GYS had no obvious effects on clinical features, daily yielding, and hematological indexes in dairy cows receiving an oral dose of 0.67, 2.00, or 3.33 g/kg BW (once daily for three consecutive days), which is consistent with our results. Indication from the randomized précised clinical trial suggests that GYS is a clinically effective therapeutic agent for RP and the prevention of PM; thus, it might have much potential for the clinical control of RP in dairy cows.
The hematopoietic system is a delicate object for lethal substances, and variations in hematology parameters have high predictive significance for toxicity or pathological grade in humans using the data gained from the animal study model [51][52][53][54]. In the present study, at the last of the drug administration period, the standard hematological and biochemistry tests were performed to estimate the hematology parameters, metabolic products, enzymes, and substrates. The tested hematological parameters revealed no significant differences among the control and the three GYS-treated groups, representing that GYS had no effect on the circulating blood cells or their production. Moreover, the serum clinical biochemistry also plays a significant role in the analysis of toxicity prompted by various drugs and chemical materials. Biochemical parameters such as AST, ALT, ALP, TP, albumin, and TBL are used as good indicators of hepatic functions; AST and ALT are well-recognized liver enzymes which are used as biomarkers to calculate possible toxicity, while BUN and creatinine levels are good signs of renal function [55][56][57]. In the present study, there were no adverse effects on the common biomarkers of liver and kidney toxicity, so it can be summarized that GYS did not induce remarkable injury to these organs. Usually, any injury to the parenchymal liver cells results in elevated levels of both transaminases (AST and ALT) and ALP in the blood, and AST found in the serum is of both mitochondrial and cytoplasmic origin, so any increase can be taken as an initial sign of cellular damage that results in the outflow of these enzymes into the serum. In this study, no statistically significant differences (p > 0.05) were noted in the levels of ALT, AST, and ALP in male and female rats, indicating that the subacute administration of GYS did not change the hepatocytes' function and metabolism. There was also no marked change in creatinine in the three GYS-treated groupscompared with the control group. Creatinine and blood urea nitrogen are considered valid indicators of renal function, and if there is marked damage to the functional nephrons, the increase in creatinine and BUN levels is expected. Thus, the findings from the present study imply that GYS did not affect kidney function. Moreover, no statistically significant differences (p > 0.05) were observed in the levels of total protein, albumin, total cholesterol, or triglyceride in male/female rats in any of the dose groups on day 28 compared with the control group. Since the liver is the major site of cholesterol synthesis, disposal, and degradation, the results demonstrated that the growing rats increased protein synthesis to an extent, and GYS had no effect on cholesterol metabolism in rats. The level of glucose (GLU) in both sexes decreased in the three dose groups compared with the control group (p < 0.05), suggesting that GYS had hypoglycemic activity. This may happen because of the increase clotting time and delay in centrifugation which results in glucose consumption by erythrocytes and low value of this parameter. In this study, apart from a significant reduction in the levels of serum glucose, no remarkable changes in the hematological and biochemical parameters were noted, representing that GYS was comparatively low toxic or nontoxic under the trial conditions.
From the necropsy assay, there were no lesions or pathological changes observed in the vital organs and reproduction organs of either sex rats in any of the dose groups on day 28 compared with the control group, indicating that GYS did not produce any treatmentassociated toxicity or deterioration to the vital organs and reproduction organs function. In this study, the histopathological changes in the vital organs and reproduction organs of the rats in the three GYS-treated groups and the control group were also investigated, respectively. Compared with the control group, there were no toxicological or pathological changes in the organs after 28 consecutive days of GYS administration. The liver and kidney are sensitive organs, and their roles are affected by many factors, which include drugs, such as plant phytochemicals, eventually leading to renal dysfunction and liver toxicity. In this study, the histopathological assessment of the vital organs and reproductive organs in the rats which were given 30.0 g/kg BW GYS group shown that there were no treatment-related microscopic changes in the liver and kidneys. It also shows that the structures were normal and that there were no pathological lesions in the lungs, heart, spleens, thymus, uterus, ovaries, or testes. Based on these results, GYS seems to be lowtoxic or nontoxic to the animals at all of the tested dosages, and did not cause any signs of toxicological or pathological changes. The present study is the first study to demonstrate that GYS, which is claimed to be acurative agent for uterine disorders in early postpartum cattle, is a medicinal plant extract with low-toxic or nontoxic properties.
Conclusions
In this study, the MTD of GYS was greater than 90.0 g/kg BW for the experimental mice in both sexes in the acute toxicity test. During the 28-day oral administration of GYS, the NOAEL of GYS was 30.0 g/kg BW in the subacute toxicity trial, which was 20 times greater than the dose that has already been used in practice. No treatment-related deaths and no other clinical abnormalities were noted during the acute and subacute experimental periods. The blood hematology and serum biochemistry data revealed no differences between the treatment and control groups, and no toxic effects were detected in the vital organs and reproductive organs at any dose level by the histopathological examination. Therefore, the oral administration of GYS at a dose lower than 90.0 g/kg BW in one day or 30.0 g/kg BW per day for 28 days is safe for the mice or rats, which provided a basis for the clinical use of GYS and for determining a reasonable safe dose.
Figure 2 .
Figure 2. Body weight of control and treated male (A) and female (B) rats with 7.5, 15.0, and 30.0 g/kg BW of GYS (Guixiong Yimu San) for 28 days. There were no significant variations in treated groups relative to the control group (p > 0.05).
Figure 2 .
Figure 2. Body weight of control and treated male (A) and female (B) rats with 7.5, 15.0, and 30.0 g/kg BW of GYS (Guixiong Yimu San) for 28 days. There were no significant variations in treated groups relative to the control group (p > 0.05).
Figure 2 .
Figure 2. Body weight of control and treated male (A) and female (B) rats with 7.5, 15.0, and 30.0 g/kg BW of GYS (Guixiong Yimu San) for 28 days. There were no significant variations in treated groups relative to the control group (p > 0.05).
Table 1 .
Effect on BW, BWG, and growth performance in rats after daily oral administration of GYS (n = 10).
Table 2 .
Effects of daily oral administration of GYS for 28 days on the hematological parameters of rats (n = 10).
Table 4 .
Effect of GYS on relative organ weights (ROW) of rats after 28 days of oral administration (n = 10).
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Domain: Agricultural And Food Sciences
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CaWRKY50 Acts as a Negative Regulator in Response to Colletotrichum scovillei Infection in Pepper
Chili anthracnose is one of the most common and destructive fungal pathogens that affects the yield and quality of pepper. Although WRKY proteins play crucial roles in pepper resistance to a variety of pathogens, the mechanism of their resistance to anthracnose is still unknown. In this study, we found that CaWRKY50 expression was obviously induced by Colletotrichum scovillei infection and salicylic acid (SA) treatments. CaWRKY50-silencing enhanced pepper resistance to C. scovillei, while transient overexpression of CaWRKY50 in pepper increased susceptibility to C. scovillei. We further found that overexpression of CaWRKY50 in tomatoes significantly decreased resistance to C. scovillei by SA and reactive oxygen species (ROS) signaling pathways. Moreover, CaWRKY50 suppressed the expression of two SA-related genes, CaEDS1 (enhanced disease susceptibility 1) and CaSAMT1 (salicylate carboxymethyltransferase 1), by directly binding to the W-box motif in their promoters. Additionally, we demonstrated that CaWRKY50 interacts with CaWRKY42 and CaMIEL1 in the nucleus. Thus, our findings revealed that CaWRKY50 plays a negative role in pepper resistance to C. scovillei through the SA-mediated signaling pathway and the antioxidant defense system. These results provide a theoretical foundation for molecular breeding of pepper varieties resistant to anthracnose.
Introduction
Pepper (Capsicum annuum L.) is one of the most commercially significant vegetables in the world [1]. However, pepper cultivation is often damaged by pathogenic fungi, including chili anthracnose caused by Colletotrichum spp. [2]. Among these fungi, C. scovillei is one of the most devastating fungal diseases in pepper [3]. Currently, traditional chemical treatments are widely used to control chili anthracnose, but they are harmful to the environment and can negatively impact food safety. The breeding of resistant pepper varieties is the most effective and economical approach to controlling plant pathogens [4]. Therefore, it is important to study the mechanisms of pepper resistance to anthracnose.
Salicylic acid (SA) serves as a vital hormone for plant defense and plays a crucial role in many aspects of plant immunity. SA is involved not only in systemic acquired resistance (SAR) but also in PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI) [5]. The PTI and ETI immune systems cooperate to promote downstream responses, leading to the production of ROS and plant hormones, as well as the activation of a hypersensitive response (HR) to trigger associated defense mechanisms [6]. When plants are attacked by pathogens, SA stimulates the synthesis of pathogenesis-related (PR) proteins involved in plant defense [7]. Under stress combinations, plants can enhance their levels of antioxidant enzymes to decrease ROS (particularly H 2 O 2 and O 2 − ) accumulation and reduce their damage by maintaining a dynamic balance [8].
Characterization of CaWRKY50
To explore the potential function of CaWRKY50 in response to anthracnose, we used qRT-PCR to investigate any change in CaWRKY50 expression in the susceptible cv. R25 under C. scovillei infection. We found that CaWRKY50 expression was significantly induced from 1 to 7 dpi compared to before infection, indicating that CaWRKY50 was involved in disease resistance following C. scovillei infection in pepper fruits (Figure 1a). The coding sequence of CaWRKY50 (Capana10g001548) was cloned from cv. R25 and encodes a protein consisting of 232 amino acids. Phylogenetic analysis revealed that CaWRKY50 was highly identical to NtWRKY70 (XP_016492893.1) and homologous to AtWRKY54 (AT2G40750.1), SlWRKY81 (NP_001266272.1), StWRKY6 (NP_001275414.1), VvWRKY70 (XP_002275401.1), CsWRKY70 (KAH9673391.1), OsWRKY41 (XP_015638413.1), and TaWRKY19 (XP_04438106) based on BLAST analysis in the NCBI database ( Figure 1b). The CaWRKY50 protein contained one conserved WRKYGQK domain, a C2HC zinc finger, and was clustered in subgroup III members (Figure 1c). The CaWRKY50 protein contained one conserved WRKYGQK domain, a C2HC zinc finger, and was clustered in subgroup III members (Figure 1c). (AY486137) was used as the internal control. Data are shown as means (±SD) from three biological replicates. Significant differences are shown by asterisks (* p < 0.05, ** p < 0.01, Student's t test). (f) Localization of the CaWRKY50 protein in N. benthamiana epidermal cells (Scale bar = 50 µm). The 35S:GFP protein is used as a control. (g) Transcriptional activation of CaWRKY50 in the yeast. The positive control is pGBKT7-53 and pGADT7-T, and the negative control is pGBKT7-Lam and pGADT7-T.
To understand the effect of SA and jasmonic acid (JA) on pepper fruit resistance against C. scovillei, we analyzed the expression patterns of the CaWRKY50 gene after treatment with 5 mM SA and 100 µM JA. The results show that CaWRKY50 was strongly induced at 3-12 hpt with 5 mM SA but did not respond to 100 µM JA (Figure 1d). We also analyzed the transcript levels of CaWRKY50 following C. scovillei infection after exogenous 5 mM SA treatment using qRT-PCR. The results indicate that CaWRKY50 expression was significantly decreased compared to the control at 2 and 7 dpi (Figure 1e). These findings imply that the response of CaWRKY50 to C. scovillei may be related to SA signaling pathways.
Sequence analysis using the PSORT online program revealed that the predicted CaWRKY50 protein contains two putative nuclear localization signals (Figure 1c). To confirm this speculation, the recombinant CaWRKY50-GFP protein was transiently expressed in tobacco epidermal cells. The results show that the CaWRKY50-GFP protein only appeared in the nucleus, while the empty GFP protein was present throughout the cell (Figure 1f). To analyze the transcriptional activity of CaWRKY50, we used the yeast two-hybrid (Y2H) system. The positive control grew well and turned blue in the SD/-Leu/-Trp/-Ade/-His medium with X-α-gal (20 µg mL −1 ), while pGBKT7-CaWRKY50 and the negative control did not express X-α-gal activity (Figure 1g). These results suggest that CaWRKY50 has no transcriptional activity in yeast cells.
CaWRKY50 Silencing Improves Pepper Resistance to C. scovillei
To investigate the function of CaWRKY50 in anthracnose resistance, we downregulated its expression on detached pepper fruits (cv. R25) using virus-induced gene silencing (VIGS) methods. CaWRKY50 expression was significantly lower in silenced pepper fruits compared to control fruits at 15 days post-infiltration, which indicates that CaWRKY50 were successfully silenced ( Figure 2a). The phenotypic symptoms and lesion diameters of CaWRKY50-silenced fruits were considerably smaller in comparison to control fruits at 7 dpi (Figure 2b,c). Furthermore, the contents of malondialdehyde (MDA) and H 2 O 2 in CaWRKY50-silenced fruits were remarkably lower than those in control fruits at 7 dpi (Figure 2d,e). Conversely, the catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities of CaWRKY50-silenced fruits were significantly higher at 7 dpi (Figure 2f-h).
Furthermore, the expression of CaWRKY50 was markedly lower in CaWRKY50-silenced fruits compared to control fruits at 4 and 7 dpi (Figure 3a). To determine whether CaWRKY50 affects the expression of SA and ROS defense-related genes in pepper, qRT-PCR was used to evaluate the expression levels of these genes at various days after C. scovillei infection. The transcript levels of CaPR1, CaPR10, CaSAR8.2, and CaPO1 (SA-related genes) were significantly increased in CaWRKY50-silenced fruits relative to control fruits at 7 dpi (Figure 3b-e). Similarly, the transcript patterns of CaCAT, CaPOD, and CaSOD (ROS-related genes) were consistent with the SA-related genes (Figure 3f-h). Overall, these results indicate that silencing CaWRKY50 improves the resistance of pepper fruits to C. scovillei.
CaWRKY50-silenced fruits were considerably smaller in comparison to control fruits at 7 dpi (Figure 2b,c). Furthermore, the contents of malondialdehyde (MDA) and H2O2 in CaWRKY50-silenced fruits were remarkably lower than those in control fruits at 7 dpi (Figure 2d,e). Conversely, the catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities of CaWRKY50-silenced fruits were significantly higher at 7 dpi (Figure 2f-h). Furthermore, the expression of CaWRKY50 was markedly lower in CaWRKY50-silenced fruits compared to control fruits at 4 and 7 dpi (Figure 3a). To determine whether CaWRKY50 affects the expression of SA and ROS defense-related genes in pepper, qRT-PCR was used to evaluate the expression levels of these genes at various days after C. scovillei infection. The transcript levels of CaPR1, CaPR10, CaSAR8.2, and CaPO1 (SA-related genes) were significantly increased in CaWRKY50-silenced fruits relative to control Overall, these results indicate that silencing CaWRKY50 improves the resistance of pepper fruits to C. scovillei.
Transient CaWRKY50 Overexpression Enhances Susceptibility to C. scovillei in Pepper
To further explore the role of CaWRKY50 in disease resistance to anthracnose, we performed transient overexpression of CaWRKY50 in detached pepper fruits (cv. R25) and
Transient CaWRKY50 Overexpression Enhances Susceptibility to C. scovillei in Pepper
To further explore the role of CaWRKY50 in disease resistance to anthracnose, we performed transient overexpression of CaWRKY50 in detached pepper fruits (cv. R25) and infected them with C. scovillei. CaWRKY50 was successfully overexpressed in the pepper fruits, as confirmed by qRT-PCR analysis at 3 days post-infiltration (Figure 4a). The disease symptoms and lesion diameters of CaWRKY50-overexpressing fruits were markedly larger than those of control fruits at 7 dpi (Figure 4b,c). Additionally, MDA and H 2 O 2 levels in CaWRKY50-overexpressing fruits were dramatically increased compared to the control fruits at 7 dpi (Figure 4d,e). Furthermore, the CAT, POD, and SOD activities of CaWRKY50-overexpressing fruits were significantly lower than those of control fruits at 7 dpi (Figure 4f Additionally, CaWRKY50 expression was obviously increased in CaWRKY50-overexpressing fruits compared to control fruits at 4 and 7 dpi (Figure 5a). To understand whether CaWRKY50 regulates the expression of SA and ROS-related defense genes, we analyzed the transcript levels of these genes in CaWRKY50-overexpressing fruits as well as control fruits at various days after C. scovillei infection. The transcript levels of CaPR1, CaPR10, CaSAR8.2, and CaPO1 (SA-related genes) were downregulated in the CaWRKY50-overexpressing fruits relative to the control at 7 dpi (Figure 5b-e). Similarly, the expression patterns of CaCAT, CaPOD and CaSOD (ROS-related genes) were consistent with the SA-related genes under C. scovillei infection at 7 dpi (Figure 5f-h). Taken together, our data show that CaWRKY50 negatively regulates pepper fruit resistance to C. scovillei. Additionally, CaWRKY50 expression was obviously increased in CaWRKY50-overexpressing fruits compared to control fruits at 4 and 7 dpi (Figure 5a). To understand whether CaWRKY50 regulates the expression of SA and ROS-related defense genes, we analyzed the transcript levels of these genes in CaWRKY50-overexpressing fruits as well as control fruits at various days after C. scovillei infection. The transcript levels of CaPR1, CaPR10, CaSAR8.2, and CaPO1 (SA-related genes) were downregulated in the CaWRKY50overexpressing fruits relative to the control at 7 dpi (Figure 5b-e). Similarly, the expression patterns of CaCAT, CaPOD and CaSOD (ROS-related genes) were consistent with the SArelated genes under C. scovillei infection at 7 dpi (Figure 5f-h). Taken together, our data show that CaWRKY50 negatively regulates pepper fruit resistance to C. scovillei. CaPR10, CaSAR8.2, and CaPO1 (SA-related genes) were downregulated in the CaWRKY50-overexpressing fruits relative to the control at 7 dpi (Figure 5b-e). Similarly, the expression patterns of CaCAT, CaPOD and CaSOD (ROS-related genes) were consistent with the SA-related genes under C. scovillei infection at 7 dpi (Figure 5f-h). Taken together, our data show that CaWRKY50 negatively regulates pepper fruit resistance to C. scovillei.
Overexpression of CaWRKY50 in Tomato Decreases Resistance to C. scovillei
To better understand the function of CaWRKY50 in anthracnose resistance, CaWRKY50 was stably expressed in tomato by Agrobacterium-mediated genetic transformation. Three transgenic T 2 lines (OE-97, OE-110, and OE-113) with high levels of CaWRKY50 transcript ( Figure 6a) were infected with C. scovillei to assess the role of CaWRKY50 in anthracnose resistance. At 3 dpi, the transgenic fruits exhibited greater lesion diameters than WT fruits (Figure 6b,c). MDA and H 2 O 2 content were evaluated in OE and WT fruits, and compared to WT fruits, MDA and H 2 O 2 levels were greatly increased in OE fruits at 3 dpi (Figure 6d,e). Moreover, the activities of CAT, POD, and SOD were obviously lower in OE fruits than WT fruits at 3 dpi (Figure 6f-h).
Additionally, we analyzed the expression levels of SA and ROS related defense genes in both CaWRKY50-overexpressing and control fruits. The transcript patterns of SA-related genes SlPR1, SlNPR1, and SlSABP2 were markedly downregulated in CaWKRY50 OE fruits compared to WT fruits at 3 dpi (Figure 6i-k). Consistently, the transcript patterns of the ROS-related genes SlPOD, SlAPX2, and SlCAT were also significantly downregulated in OE fruits relative to WT fruits at 3 dpi (Figure 6l-n). In conclusion, our studies demonstrate that CaWRKY50 has a negative regulatory effect on tomato fruit resistance to C. scovillei.
CaWRKY50 Specifically Binds the Promoter of CaEDS1 and CaSAMT1
To identify which genes are directly regulated by CaWRKY50 for anthracnose resistance in pepper, we looked for two SA-related defense genes (CaEDS1 and CaSAMT1), whose promoters contain W-box elements (TTGACC/T). Subsequently, we performed yeast one-hybrid (Y1H) assays to confirm whether CaWRKY50 binds to the promoter of CaEDS1 and CaSAMT1. We transformed CaWRKY50-pGADT7 into the Y1H strain by integrating the proCaEDS1/proCaSAMT1-pAbAi vector, which produced yeast cells that grew well on SD/-Leu medium with 150 and 250 ng ml −1 AbA. In contrast, the negative control failed to grow (Figure 7a). The Y1H assay confirmed that CaWRKY50 specifically binds to the promoters of CaEDS1 and CaSAMT1.
To investigate the effect of CaWRKY50 on the promoters of CaEDS1 and CaSAMT1, we performed GUS activity and dual-luciferase assays in tobacco leaves. The staining
CaWRKY50 Specifically Binds the Promoter of CaEDS1 and CaSAMT1
To identify which genes are directly regulated by CaWRKY50 for anthracnose resistance in pepper, we looked for two SA-related defense genes (CaEDS1 and CaSAMT1), whose promoters contain W-box elements (TTGACC/T). Subsequently, we performed yeast one-hybrid (Y1H) assays to confirm whether CaWRKY50 binds to the promoter of CaEDS1 and CaSAMT1. We transformed CaWRKY50-pGADT7 into the Y1H strain by integrating the proCaEDS1/proCaSAMT1-pAbAi vector, which produced yeast cells that grew well on SD/-Leu medium with 150 and 250 ng ml −1 AbA. In contrast, the negative control failed to grow (Figure 7a). The Y1H assay confirmed that CaWRKY50 specifically binds to the promoters of CaEDS1 and CaSAMT1.
To investigate the effect of CaWRKY50 on the promoters of CaEDS1 and CaSAMT1, we performed GUS activity and dual-luciferase assays in tobacco leaves. The staining intensity and activity of GUS were significantly decreased compared to the control when CaWRKY50-pGADT7 was co-expressed with the proCaEDS1/proCaSAMT1-GUS vector in tobacco leaves (Figure 7b,c). Furthermore, we observed that the luciferase activity was significantly inhibited compared to control when CaWRKY50:62-SK was co-expressed with the proCaEDS1/proCaSAMT1-LUC vector in tobacco leaves (Figure 7d,e). Taken together, these results indicate that CaWRKY50 specifically binds to the promoters of CaEDS1 and CaSAMT1, suppressing their expression in response to C. scovillei.
x FOR PEER REVIEW 9 of 18 intensity and activity of GUS were significantly decreased compared to the control when CaWRKY50-pGADT7 was co-expressed with the proCaEDS1/proCaSAMT1-GUS vector in tobacco leaves (Figure 7b,c). Furthermore, we observed that the luciferase activity was significantly inhibited compared to control when CaWRKY50:62-SK was co-expressed with the proCaEDS1/proCaSAMT1-LUC vector in tobacco leaves (Figure 7d,e). Taken together, these results indicate that CaWRKY50 specifically binds to the promoters of CaEDS1 and CaSAMT1, suppressing their expression in response to C. scovillei.
CaWRKY50 Interacts with CaWRKY42 and CaMIEL1
In order to identify the interacting partner of CaWRKY50 in the regulation of pepper defense responses, we screened a pepper cDNA library by Y2H assay and isolated CaWRKY42 (Capana08g001044) and CaMIEL1 (XM_016719768) as CaWRKY50-interacting proteins. CaMIEL1 encodes a RING E3 ubiquitin-protein ligase. Subsequently, we carried out a Y2H assay to confirm whether CaWRKY50 interacted with CaWRKY42/CaMIEL1. The yeast cells co-transformed with CaWRKY50-pGBKT7 and CaWRKY42/CaMIEL1-pGADT7 plasmid combinations were viable on SD/-Leu/-Trp/-Ade/-His medium and turned blue in X-α-gal (20 µg mL −1 ) (Figure 8a). This confirmed The LUC to REN ratio was assessed as transcriptional activity. The empty vector 62-SK was used as a control. Data are shown as means (±SD) from three biological replicates. Significant differences are shown by asterisks (* p < 0.05, ** p < 0.01, Student's t test).
CaWRKY50 Interacts with CaWRKY42 and CaMIEL1
In order to identify the interacting partner of CaWRKY50 in the regulation of pepper defense responses, we screened a pepper cDNA library by Y2H assay and isolated CaWRKY42 (Capana08g001044) and CaMIEL1 (XM_016719768) as CaWRKY50-interacting proteins. CaMIEL1 encodes a RING E3 ubiquitin-protein ligase. Subsequently, we carried out a Y2H assay to confirm whether CaWRKY50 interacted with CaWRKY42/CaMIEL1. The yeast cells co-transformed with CaWRKY50-pGBKT7 and CaWRKY42/CaMIEL1-pGADT7 plasmid combinations were viable on SD/-Leu/-Trp/-Ade/-His medium and turned blue in X-α-gal (20 µg mL −1 ) (Figure 8a). This confirmed that CaWRKY50 strongly interacted with CaWRKY42 and CaMIEL1.
Moreover, we performed luciferase complementation imaging (LCI) and bimolecular fluorescence complementation (BiFC) assays to confirm the interactions in living plant cells. In the LCl assay, we transiently co-expressed CaWRKY50-nLUC and CaWRKY42/CaMIEL1-cLUC in tobacco leaves and found luminescence signals in the co-expressed CaWRKY50-nLUC and CaWRKY42/CaMIEL1-cLUC regions but not in controls (Figure 8b). In the BiFC assay, we transiently co-expressed CaWRKY50-nYFP and CaWRKY42/CaMIEL1-cYFP in tobacco leaves and observed the interaction between CaWRKY50 and CaWRKY42/CaMIEL1 generating YFP fluorescence in the nucleus (Figure 8c). In summary, our data demonstrate that CaWRKY50 interacts with CaWRKY42/CaMIEL1 in the nucleus. Moreover, we performed luciferase complementation imaging (LCI) and bimolecular fluorescence complementation (BiFC) assays to confirm the interactions in living plant cells. In the LCl assay, we transiently co-expressed CaWRKY50-nLUC and CaWRKY42/CaMIEL1-cLUC in tobacco leaves and found luminescence signals in the coexpressed CaWRKY50-nLUC and CaWRKY42/CaMIEL1-cLUC regions but not in controls (Figure 8b). In the BiFC assay, we transiently co-expressed CaWRKY50-nYFP and CaWRKY42/CaMIEL1-cYFP in tobacco leaves and observed the interaction between CaWRKY50 and CaWRKY42/CaMIEL1 generating YFP fluorescence in the nucleus (Figure 8c). In summary, our data demonstrate that CaWRKY50 interacts with CaWRKY42/CaMIEL1 in the nucleus.
Discussion
WRKY proteins play a critical role in plant resistance to various pathogens. According to the Zunla-1 genome sequence, a total of 62 WRKY genes have been identified in pepper [30]. In our study, we selected CaWRKY50 as a candidate gene based on previous RNA-seq and VIGS analysis. Sequence analysis indicated that CaWRKY50 is highly homologous with NtWRKY70 in tobacco, AtWRKY54 in Arabidopsis, and CsWRKY70 in citrus. These proteins belong to subgroup III members (Figure 1b,c), for which AtWRKY54 plays a positive regulatory role in pathogen infection and a negative regulatory role in leaf senescence [31,32]. CsWRKY70 actively participates in SA-mediated disease resistance by regulating the transcription of the CsSAMT genes [11]. Thus, it was speculated that CaWRKY50 might also be involved in plant disease resistance. However, the underlying molecular mechanism of CaWRKY50 in pepper anthracnose resistance remains unknown, and further investigation is needed to understand its function.
In this study, a transactivation assay was used to investigate CaWRKY50's role in transcriptional activity, and it was found that it did not possess transcriptional activity in yeast cells (Figure 1g). Similar findings have been reported for grapevine VvWRKY8 [33],
Discussion
WRKY proteins play a critical role in plant resistance to various pathogens. According to the Zunla-1 genome sequence, a total of 62 WRKY genes have been identified in pepper [30]. In our study, we selected CaWRKY50 as a candidate gene based on previous RNA-seq and VIGS analysis. Sequence analysis indicated that CaWRKY50 is highly homologous with NtWRKY70 in tobacco, AtWRKY54 in Arabidopsis, and CsWRKY70 in citrus. These proteins belong to subgroup III members (Figure 1b,c), for which AtWRKY54 plays a positive regulatory role in pathogen infection and a negative regulatory role in leaf senescence [31,32]. CsWRKY70 actively participates in SA-mediated disease resistance by regulating the transcription of the CsSAMT genes [11]. Thus, it was speculated that CaWRKY50 might also be involved in plant disease resistance. However, the underlying molecular mechanism of CaWRKY50 in pepper anthracnose resistance remains unknown, and further investigation is needed to understand its function.
In this study, a transactivation assay was used to investigate CaWRKY50's role in transcriptional activity, and it was found that it did not possess transcriptional activity in yeast cells (Figure 1g). Similar findings have been reported for grapevine VvWRKY8 [33], maize ZmWRKY17 [34], soybean GmWRKY13, GmWRKY27, GmWRKY40, GmWRKY54 [35], and Brachypodium distachyon BdWRKY36 [36]. This phenomenon could be explained by the fact that the activation of these proteins may be dependent on posttranslational modifications or require activation by unknown upstream proteins [37].
In this study, the transcript levels of CaWRKY50 were markedly induced by C. scovillei and SA treatments, as shown in Figure 1a,d. By performing VIGS, we found that CaWRKY50-silencing enhanced pepper resistance to C. scovillei inoculation (Figures 2 and 3). Also, CaWRKY50 overexpression resulted in enhanced susceptibility to infection with C. scovillei in pepper and tomato fruits (Figures 4-6). These results suggest that CaWRKY50 acts as a negative regulator of pepper resistance to C. scovillei.
Recently, studies have revealed that plants can actively generate ROS, which can affect a variety of physiological processes, including biotic and abiotic stress as well as pathogen defense [8]. To counteract ROS damage, plants possess a comprehensive antioxidative system that reduces ROS damage and maintains cell homeostasis [38]. Malondialdehyde (MDA) is the main product of membrane lipid peroxidation and is commonly used as a marker for oxidative stress in plants [39]. For instance, overexpression of CaCIPK13 in pepper enhanced cold tolerance by regulating the antioxidant defense system, which increased CAT, POD, and SOD activities while decreasing MDA and H 2 O 2 content [40]. Similarly, CaCIPK3-overexpression improved drought stress resistance in pepper by increasing CAT, POD, and SOD activities, while decreasing MDA and H 2 O 2 content [41]. Hence, we measured the contents of MDA and H 2 O 2 as well as the levels of ROS scavenging enzymes (CAT, POD, and SOD) in CaWRKY50-overexpressing and CaWRKY50silenced fruits under C. scovillei infection. Our results revealed that the contents of MDA and H 2 O 2 in CaWRKY50-overexpressing fruits were noticeably higher than control fruits under C. scovillei infection (Figures 4 and 6). In contrast, the results were reversed in CaWRKY50-silenced fruits, as shown in Figure 2. Furthermore, the activities of CAT, POD, and SOD in CaWRKY50-overexpressing fruits were significantly lower than control fruits under C. scovillei infection (Figures 4 and 6), which was contrary to CaWRKY50-silenced fruits (Figure 2). To corroborate these findings, we measured the expression of ROSscavenging genes (CaCAT/SlCAT, CaPOD/SlPOD, CaSOD, and SlAPX2) using qRT-PCR and found that the results were consistent with ROS-scavenging enzyme activity results (Figures 3, 5, and 6). These findings suggest that CaWRKY50 plays a crucial role in regulating oxidative stress caused by C. scovillei infection.
SA signaling is known to play a key role in regulating the defense response of plants to pathogenic infections. Previous studies have shown that SA-related defense genes can be induced by SA to modulate plant defense responses to pathogen infection. [42]. Previous results indicated that CaSBP12, CaSBP08, and CaSBP11 negatively regulated pepper resistance to phytophthora capsici by inhibiting the transcript of SA-related defense genes [39,43,44]. In another study, VaERF16-overexpressing improved disease resistance to B. cinerea in Arabidopsis thaliana by increasing the expression of AtPR1 and AtNPR1 [45]. Our research revealed that the transcript levels of CaPR1, CaPR10, CaSAR8.2, and CaPO1 were significantly downregulated in transient CaWRKY50-overexpression pepper fruits in comparison to control fruits at 7 dpi. (Figure 5). In contrast, these genes were dramatically upregulated in CaWRKY50-silenced pepper fruits at 7 dpi ( Figure 3). Furthermore, the expression of SlPR1, SlNPR1, and SlSABP2 in CaWRKY50-overexpressing tomato fruits was markedly lower than in control fruits at 7 dpi (Figure 6i-k). In summary, these results indicate that CaWRKY50 acts as a negative regulator in response to C. scovillei through the SA signaling pathway.
WRKY TFs can specifically bind to W-box cis-elements (TTGACC/T) to regulate the expression of defense-associated genes. The expression of SA signaling-related genes (TGA2 and TGA6) was increased by WRKY70, which directly bound their promoter elements to regulate Verticillium dahliae toxin infection [46]. In the absence of a pathogen, WRKY70 is directly bound to the promoter of SARD1 to repress its expression and regulate the expression of SA-related genes [47]. In another study, MdWRKY17 specifically bound to the MdDMR6 promoter to enhance its expression, which negatively regulated resistance to C. fructicola in apples [17]. In the present study, we found that CaWRKY50 specifically binds to the promoter of CaEDS1 and CaSAMT1 by Y1H (Figure 7a). To elucidate how CaWRKY50 regulates the expression of CaEDS1 and CaSAMT1, we conducted GUS activity and dual-luciferase assays, which demonstrate that CaWRKY50 could inhibit CaEDS1 and CaSAMT1 transcription (Figure 7b-e). In plants, SAMT catalyzes SA to produce MeSA. CsWRKY70 specifically binds to the promoter of CsSAMT and activates its expression, thereby positively regulating resistance to Penicillium digitatum in citrus fruit [11]. EDS1 plays an important function in plant basal defense and the SA signaling pathway [12]. PcAvh103 interacts with EDS1 to inhibit plant immunity by the EDS1-PAD4 signaling pathway [48]. These findings suggest that CaWRKY50 can suppress the expression of CaEDS1 and CaSAMT1 to reduce disease resistance.
WRKY proteins can interact with other proteins to regulate plant immunity [14]. For example, WRKY33 interacts with WRKY12 to increase hypoxia tolerance in Arabidopsis [49]. JrWRKY21 was shown to improve walnut resistance to C. gloeosporioides by interacting with JrPTI5L (a PR protein) [50]. SlWRKY31 interacts with SlVQ15 to regulate the resistance to B. cinerea in tomatoes [51]. It is plausible that the CaWRKY50 protein also interacts with other defense proteins in response to various pathogen infections. In this study, we determined the interaction between CaWRKY50 with CaWRKY42/CaMIEL1 through Y2H, LCI, and BiFC assays (Figure 8). A previous study showed that CaWRKY41 (CA08g08240), which is the same gene as CaWRKY42 (Capana08g001044) in our study, could positively regulate pepper resistance to R. solanacearum inoculation [25]. CaMIEL1, an E3 ubiquitin ligase, inhibited tolerance to bacterial inoculation in Arabidopsis by degrading MYB30 [52]. These results suggest that CaWRKY50 may regulate resistance to C. scovillei by interacting with CaWRKY42 and CaMIEL1.
In conclusion, using overexpression and silenced techniques, we demonstrated that CaWRKY50 serves as a negative regulator in response to C. scovillei through the SA and ROS signaling pathways. CaWRKY50 directly binds to the promoters of CaEDS1 and CaSAMT1 to suppress their expression. Furthermore, CaWRKY50 participates in disease resistance by interacting with CaWRKY42 and CaMIEL1 (Figure 9). Our findings shed light on the mechanisms by which WRKY50 functions in response to anthracnose resistance. bound to the MdDMR6 promoter to enhance its expression, which negatively regulated resistance to C. fructicola in apples [17]. In the present study, we found that CaWRKY50 specifically binds to the promoter of CaEDS1 and CaSAMT1 by Y1H (Figure 7a). To elucidate how CaWRKY50 regulates the expression of CaEDS1 and CaSAMT1, we conducted GUS activity and dual-luciferase assays, which demonstrate that CaWRKY50 could inhibit CaEDS1 and CaSAMT1 transcription (Figure 7b-e). In plants, SAMT catalyzes SA to produce MeSA. CsWRKY70 specifically binds to the promoter of CsSAMT and activates its expression, thereby positively regulating resistance to Penicillium digitatum in citrus fruit [11]. EDS1 plays an important function in plant basal defense and the SA signaling pathway [12]. PcAvh103 interacts with EDS1 to inhibit plant immunity by the EDS1-PAD4 signaling pathway [47]. These findings suggest that CaWRKY50 can suppress the expression of CaEDS1 and CaSAMT1 to reduce disease resistance. WRKY proteins can interact with other proteins to regulate plant immunity [14]. For example, WRKY33 interacts with WRKY12 to increase hypoxia tolerance in Arabidopsis [48]. JrWRKY21 was shown to improve walnut resistance to C. gloeosporioides by interacting with JrPTI5L (a PR protein) [49]. SlWRKY31 interacts with SlVQ15 to regulate the resistance to B. cinerea in tomatoes [50]. It is plausible that the CaWRKY50 protein also interacts with other defense proteins in response to various pathogen infections. In this study, we determined the interaction between CaWRKY50 with CaWRKY42/CaMIEL1 through Y2H, LCI, and BiFC assays ( Figure 8). A previous study showed that CaWRKY41 (CA08g08240), which is the same gene as CaWRKY42 (Capana08g001044) in our study, could positively regulate pepper resistance to R. solanacearum inoculation [25]. CaMIEL1, an E3 ubiquitin ligase, inhibited tolerance to bacterial inoculation in Arabidopsis by degrading MYB30 [51]. These results suggest that CaWRKY50 may regulate resistance to C. scovillei by interacting with CaWRKY42 and CaMIEL1.
In conclusion, using overexpression and silenced techniques, we demonstrated that CaWRKY50 serves as a negative regulator in response to C. scovillei through the SA and ROS signaling pathways. CaWRKY50 directly binds to the promoters of CaEDS1 and CaSAMT1 to suppress their expression. Furthermore, CaWRKY50 participates in disease resistance by interacting with CaWRKY42 and CaMIEL1 (Figure 9). Our findings shed light on the mechanisms by which WRKY50 functions in response to anthracnose resistance. C. scovillei (SXBJ23) were cultured on potato dextrose agar (PDA) medium at 28 • C for 7 days. For pathogen inoculation assays, mature fruits were inoculated with C. scovillei using the previously described method [53]. In brief, the surfaces of mature fruits were injected with 2 µL of suspension (5 × 10 5 spores mL −1 ) using the microinjection method [54]. The inoculated fruits were stored at 28 • C for 7 days. Measurements of lesion diameter (LD) were performed by the crossing method as previously described [55]. Pepper fruit samples were collected at 0, 1, 2, 4, and 7 days post incubation (dpi). Tomato fruit samples were collected at 0 and 3 dpi. Three biological replicates were performed for each treatment.
For the study of CaWRKY50 transcript levels in response to SA and JA, cv. R25 mature fruits were soaked with 5 mM SA and 100 µM MeJA for 1 h [22]. Control fruits were soaked in sterile water. The pepper pericarps were collected after 0, 3, 6, 12, and 24 h post treatment (hpt) and then inoculated with 2 µL of C. scovillei after 24 hpt. Pepper fruits were stored at 28 • C for 7 days.
RNA Extraction and qRT-PCR Analysis
The total RNA was extracted by the RNAprep pure plant kit (TSP411, Tsingke, Beijing, China) according to the manufacturer's protocol. The first-strand cDNA was synthesized using ToloScript RT EasyMix (22106, Tolobio, Shanghai, China). qRT-PCR analysis was performed using the SYBR Green Master qPCR Mix (TSE201, Tsingke, Beijing, China). CaUBI3 (AY486137) and SlACTIN (NM_001308447.1) were used as reference genes for pepper and tomato to normalize transcript levels according to the 2 −∆∆Ct method. Each qRT-PCR experiment consisted of three biological replicates. The qRT-PCR primers listed in Supplemental Table S1.
Phylogenetic Analysis and Subcellular Localization
To analyze the relationship between CaWRKY50 and its homologs, the WRKY TFs, the protein sequence alignment was carried out by the DNAMAN software. The construction of the phylogenetic tree was performed using MEGA X software according to neighborjoining (NJ).
The PSORT online program ( [URL] (accessed on 26 April 2023)) was used to predict the subcellular localization of the CaWRKY50 protein.
To confirm the subcellular localization, the coding sequence of CaWRKY50 without the stop codon was inserted into pVBG2307-GFP vectors. The recombinant construct (pVBG2307-CaWRKY50-GFP) was transformed into Agrobacterium tumefaciens strain GV3101 and then transiently infiltrated into tobacco (Nicotiana benthamiana) leaves. The empty vector serves as a negative control. The GFP fluorescence signals were detected using a BX63 Olympus (Tokyo, Japan) after 2-3 days. Fluorescence was evaluated using at least three independent replicates.
Transcriptional Activity Assays in Yeast
The coding sequence of CaWRKY50 was amplified and cloned into the pGBKT7 vector to investigate the transcriptional activity. Co-transformation of the CaWRKY50-pGBKT7 recombinant vector and the pGADT7-T empty vector into Y2H yeast cells according to the manufacturer's procedures (PT1183, Shaanxi Pyeast Bio. CO. LTD, Shaanxi, China). Transformants were cultured on SD/-Leu/-Trp/-Ade/-His medium containing X-α-gal (20 µg/mL) at 30 • C for 3 days.
Virus-Induced Gene Silencing (VIGS)
For the VIGS assays, CaWRKY50 silencing was performed following a previously reported procedure [56]. To generate the CaWRKY50-silenced vector, a 300 bp fragment of CaWRKY50 was obtained using the VIGS Tool ( [URL]/ (accessed on 4 December 2019)). The Agrobacterium tumefaciens strain GV3101 cells containing TRV2:00 and TRV2:CaWRKY50 were combined in a 1:1 ratio with TRV1 and then infiltrated into detached mature pepper fruits of cv. R25. The treated pepper fruits were placed in growth chambers at 24/18 • C under a 16/8 h photoperiod day/night cycle. After 15 days of infiltration, the transcript levels of CaWRKY50 were measured by qRT-PCR, and then the fruits were injected with 2 µL C. scovillei. Pepper fruit samples were collected at 0, 1, 2, 4, and 7 dpi, and the lesion diameters were measured at 7 dpi. Three biological replicates were performed for each treatment. The experiment was repeated three times with similar results.
Transient and Transgenic Overexpression
We carried out transient overexpression assays by A. tumefaciens-mediated infiltration [57]. The fusion protein pVBG2307-CaWRKY50-GFP was infiltrated into detached mature pepper fruits of cv. R25. The expression level of CaWRKY50 was detected at 3 days post-infiltration by qRT-PCR, and the fruits were subsequently inoculated with 2 µL C. scovillei. Pepper fruit samples were collected at 0, 1, 4, and 7 dpi, and the lesion diameters were measured at 7 dpi. Three biological replicates were performed for each treatment. The experiment was repeated three times with similar results.
The transgenic overexpression assays were performed as previously reported methods, with slight modifications [58]. Transcript levels in transgenic plants were evaluated by qRT-PCR. T 2 transgenic lines (OE-97, OE-110, and OE-113) were employed for further investigation. The mature red fruits were inoculated with 2 µL of C. scovillei at 28 • C for 3 days. Fruit samples were collected at 0 and 3 dpi, and the lesion diameters were measured at 3 dpi. Three biological replicates were performed for each treatment.
Measurement of Physiological Indicators
The content of malondialdehyde (MDA) was detected according to the previously described method [40]. The catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities as well as H 2 O 2 contents were quantified using the corresponding assay kits (Sangon Biotech, Shanghai, China) in accordance with the manufacturer's procedures. Three biological replicates were performed for each determination. The experiment was repeated three times with similar results.
Protein Interaction Assays
The coding sequence of CaWRKY50 was cloned into the pGBKT7 vector as the bait, and the coding sequences of CaWRKY42 and CaMIEL1 were cloned into the pGADT7 vector as the prey. Co-transformation of the bait and prey vectors into Y2H yeast cells according to the manufacturer's procedures (PT1183, Shaanxi Pyeast Bio. CO. LTD, Shaanxi, China). The protein interactions were screened using SD/-Leu/-Trp/-Ade/-His medium containing X-α-gal (20 µg/mL).
For the bimolecular fluorescence complementation (BiFC) assays, the recombinant constructs CaWRKY50-pSPYNE and CaWRKY42/CaMIEL1-pSPYCE were transformed into A. tumefaciens strain GV3101 and co-infiltrated in tobacco leaves. An automated fluorescence microscope (BX63, Olympus, Japan) was used to image YFP signals 2 days after infiltration. The BiFC assays were carried out as previously reported [60].
Yeast One-Hybrid (Y1H) Assay
The coding sequence of CaWRKY50 was cloned into the pGADT7 vector, and the CaEDS1 (799 bp) and CaSAMT1 (521 bp) promoter regions containing W-box elements (TTGACT/C) were cloned into the pAbAi vector as a bait vector. The restriction enzyme BstB1 was used to linearize the bait vectors before inserting them into Y1H Gold yeast cells. Then, these yeast cells were grown at 30 • C for 3 days on SD/-Leu medium with 150 and 250 ng mL −1 of Aureobasidin A (AbA).
GUS Activity Analysis and Dual Luciferase Reporter Assay
For the GUS activity analysis, the CaEDS1 and CaSAMT1 promoter regions were amplified from the genomic DNA of cv. R25 and inserted into the pCAMBIA1381-GUS vector as reporters. The effector plasmid, pVBG2307-CaWRKY50-GFP, was identical to that used in the previous subcellular localization assay. The recombinant constructs were transformed into A. tumefaciens strain GV3101 and co-infiltrated in tobacco leaves for 48 h. The GUS staining and enzyme activity detection methods were carried out as previously described [61].
For the dual luciferase reporter assays, the CaEDS1 and CaSAMT1 promoter regions were amplified from the genomic DNA of cv. R25 and inserted into the pGreenII-0800-LUC vector to generate a reporter construct. The coding sequence of CaWRKY50 was cloned into the pGreenII 62-SK vector to create an effector construct. The recombinant constructs were transformed into A. tumefaciens strain GV3101 (pSoup) and co-infiltrated in tobacco leaves for 48 h. The luciferase activity was measured according to the method in the Dual Luciferase Reporter Gene Assay Kit (11402ES60; Yeasen, Shanghai, China).
Supplementary Materials:
The following supporting information can be downloaded at: [URL]:// www.mdpi.com/article/10.3390/plants12101962/s1, Table S1: Primers used in this study. Data Availability Statement: All data supporting the findings of this study are available within the paper and its Supplementary Data. The GenBank accession numbers of ITS, ACT, and GAPDH for SXBJ23 are OQ119154, OQ127267, and OQ127268, respectively.
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Domain: Biology Agricultural And Food Sciences
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How Weed Control Affects Eucalyptus globulus Labill. Productivity: Results from Two Long-Term Trials
: Weed control is considered a critical management operation for the establishment and growth of Eucalyptus globulus and is often performed during the first two years following planting. However, no information has been found related to the effects of weed management on the long-term growth of E. globulus . This study aims to better understand how adjusting the timing of weed control, beyond tree establishment, affects the productivity of eucalypts on two commercial plantations in Central Portugal. Two treatments were considered: weed control when vegetation cover occupied at least 50% of the area with a mean height of at least 50 cm, and no weed control. At the northernmost site, weed control operations were performed during the first 3 years following planting. At the southernmost site, weed control interventions occurred between 1.5 and 8.2 years. Weed control demonstrated to be effective at diminishing vegetation cover density to a maximum of 79% and 94% in the northmost and southmost sites, respectively. Weed control significantly increased E. globulus productivity by the end of the study, demonstrating that the timing of weed management must be adjusted in accordance with the understory competing vegetation cover (weeds) and during the entire rotation, not only during tree establishment.
Introduction
Eucalyptus globulus Labill. is a highly relevant forest species widely planted around the world, providing raw material for the pulp and paper industry because of its rapid growth and high cellulose production [1][2][3][4][5][6]. E. globulus plantations in Portugal account for 26% of the total forest area, occupying 812,000 ha in 2015, with a mean productivity of 10 m 3 ha −1 yr −1 [7].
Considerable efforts have been made to increase the productivity of E. globulus plantations and, thereby, provide guarantees for economic rentability [6]. In general, productivity is a crucial topic in forest management [8]. It is of particular relevance in areas where low rentability easily leads to land abandonment and, in turn, to the encroachment of invasive species and the intensification of rural fire regimes [9,10]. Forest managers and producers have been investing in the implementation of efficient silviculture practices, such as adequate soil tillage, genotype selection, weed control, and fertilization, to increase forest productivity [11].
Among forestry practices, special attention has been given to weed management operations, as weeds may significantly affect the establishment and productivity of forest species [12,13]. Weeds can interfere with tree growth directly through competition for light, water, and nutrients [13][14][15], but also indirectly by increasing fire hazards due to their contribution to the accumulation of biomass as fuel load [16]. The negative effects of weeds on E. globulus establishment and growth also depend on vegetation cover and composition [15]. Herbaceous species have a greater direct effect during planting and establishment, whereas shrub species have a stronger impact after canopy closure [17].
The impact of weeds during the early phases of E. globulus establishment is well documented [13][14][15]18]. The initial timing of weed control operations is essential for its effectiveness during the so-called critical weed-free period [19], as at that stage, vegetation usually grows faster than young trees [15]. Although in the case of E. globulus, the critical weed-free period was reported to be 20 months after planting [14], in Portugal, weed control on E. globulus plantations typically involves mechanical and/or chemical operations during the first year following planting and, if needed, again between the third and fifth years [6].
Few studies have monitored the impact of weed control on the productivity of E. globulus for a whole rotation [15,20], and even in those, vegetation management operations were only performed during the first two years following planting. A gap of knowledge was found in how varying the timing of weed control interventions beyond the critical weed-free period may affect the long-term growth of E. globulus. This knowledge is highly relevant, not only to the productivity of E. globulus but also to the sustainability of plantations. Sustainable forest management must be based on procedures that raise forest productivity without endangering the ecosystems or the ecosystem services provided by the forests [21]. To achieve this balance, forest managers need to have a thorough understanding of how to adjust management practices to local physical and environmental conditions, thus minimizing the environmental impacts of their interventions.
This study was conceived under the hypothesis that we can potentiate the productivity of E. globulus throughout the whole rotation by adjusting the timing of weed management according to site conditions. Thus, the goal of this study was to determine how weed control, scheduled according to the understory vegetation development, can affect the long-term productivity of E. globulus. Under this context, two field trials were installed on plantations of E. globulus located in Central Portugal: one in the province of Beira Litoral, and another further south in the province of Estremadura.
Site Selection and Characterization
The present study was conducted in two E. globulus plantations in the Central Region of Portugal managed by The Navigator Company (Figure 1). The southernmost trial was established in 2009 at Torres Vedras, district of Lisbon (39°05′11.56″N, 9°10′31.78″O, 242 m above sea level (ASL)). The northernmost trial was established in 2015 at Soure, district of Coimbra (40°05′11.56″N, 8°35′45.96″O, 80 m ASL). Both study areas are located in the Mediterranean Csb climate zone, temperate climate with dry and mild summers, according to the Köppen classification [22,23], with an annual mean precipitation (1971 to 2000) of 638 mm in Torres Vedras [22] and of 741 mm in Soure [23]. In Torres Vedras, the annual mean temperature was 15.8 °C, with a mean monthly minimum temperature of 9.2 °C and a mean monthly maximum temperature of 24.1 °C [22]. In Soure, the annual mean temperature recorded was 15 °C, with mean monthly temperatures ranging from 4.4 °C to 28.6 °C [23]. Soils in both study areas are mainly epileptic and endoletic arenic Regosols [24] (Table 1).
Sandstones and pebble
Epileptic and endoleptic arenic Regosols These E. globulus plantations were being managed for wood. The establishment and development of both plantations were performed as previously defined in the forest company's management planning: clear-cut harvesting of the preceding E. globulus planting followed by soil tillage with a single iron plough and planting of young cuttings. E. globulus clones were planted with 4.0 × 2.0 m spacing (1250 trees ha -1 ) at both sites.
Experimental Design
At both sites, plots were randomly established following plantation lines. A plot consisted of a group of three or four measurable consecutive trees in the same plantation line, at Torres Vedras and Soure, respectively. The first plot was installed in the second line of the plantation after the road. Successive plots were separated by at least one tree, with a minimum distance of 4 m between the nearest trees of plots of the same plantation line. No plots were installed in consecutive plantation lines. A plantation line with control and herbicide plots was separated from the following by a line of trees with no plots installed, with a minimum distance of 8 m between the nearest trees of plots of different plantation lines (Figure 2). Two to ten plots were established on each plantation line, depending on the local site conditions and the number of viable trees within a line. Overall, at Torres Vedras 55 plots (165 trees) were distributed along 9 plantation lines. At Soure, a total of 32 plots were established, 16 plots by treatment, corresponding to a total of 120 measured trees. One of the following treatments was applied to each plot: no weed control or chemical weed control. The treatment applied to each plot was defined following a random sampling strategy to account for differences in vegetation characteristics and/or soil characteristics. In each plot and along the plantation line, herbicide was applied from 1 m before the first tree to 1 m after the last tree of the plot. Plots with different treatments were separated by a minimum of 3 m between the last point where herbicide was applied until the first tree of the following control plot. Between plantation lines, the herbicide was applied up to 2 m on each side of the trees in the plot.
Weed Control Treatments
The plots with no weed control treatment, hereby denominated as control plots, did not suffer any intervention related to the understory vegetation. In the plots subjected to weed control, hereby denominated as herbicide plots, vegetation control was carried out in the designated areas with the herbicides Roundup UltraMax, 360 g/L glyphosate (1% to 5%), or Garlon, 480 g/L triclopyr (0.3%). Glyphosate (Roundup UltraMax) was used for the broad-spectrum control of weeds, while triclopyr herbicide (Garlon) was only used for selective control of brambles (Rubus spp.). The weed control interventions and their timing were defined following internal guidelines of best practices and forest certification standards (FSC 2016; PEFC 2018). The treatment was repeated when the understory vegetation cover developed to a percentage of 40% to 60% of the plot area, with a mean height of at least 50 cm. Following these criteria, in Torres Vedras, the vegetation development required weed control operations to be conducted at 1.5 years (T0), 5.2 years (T1), and 8.2 years (T2). The final evaluation of trees (height (H) and diameter at breast height (DBH) (1.30 m from the ground)) was performed at 8.8 years (T3), only 0.6 years after the last herbicide application. In Soure, herbicide applications were performed at 1.6 years (T0), at 1.9 years (T1), and at 3.1 years (T2). The interval in herbicide application between T0 (fall) and T1 (spring) was due to the considerable increase in herbaceous plant cover during early spring. These were mainly graminoids and short-lived species that could, nonetheless, compete with the young, recently planted eucalyptus. The final measurement of trees in the Soure site was considered as 5.2 years after planting (T4), since a windstorm that occurred after that period caused considerable and unexpected damaged to the plantation, due to the high number of trees that fell in the experimental area.
E. globulus Productivity
Tree height (H) and DBH were initially measured at the age of 1.5 (Torres Vedras) and 1.6 years (Soure), immediately prior to the first application of herbicide to determine the initial biometric variables of E. globulus and, therefore, for initial productivity assessment. H and DBH measurements were repeated once a year for growth monitoring until the ages of 8.8 and 5.2 years in Torres Vedras and Soure, respectively. The timber commercial volume of each individual tree (VOL) was calculated from DBH and H values, following the equation Vol = (0.2105 × (DHB/100) 1.8191 × H 1.0703 ) x 1000 [27].
E. globulus tree growth was also calculated according to the time intervals of herbicide application. In the Torres Vedras trial, the increment in H, DBH, and VOL was quantified from 1.5 years (T0) to 5.2 years (T1), from 5.2 years to 8.2 years (T3), and from 8.2 years to 8.8 years (T4). In Soure, the differences in H, DBH, and VOL were measured from 1.6 years (T0) to 1.9 years (T1), from 1.9 years to 3.1 years (T3), and from 3.1 years to 5.2 years (T4). The time frame between applications was not equal in both experiments due to the criteria defined for weed control (vegetation cover of 40% to 60% of the area around E. globulus trees with an average height equal to or over 50 cm). Thus, in order to standardize growth, the mean annual increment in tree volume (MAI) was calculated as the ratio between the increment in VOL and the corresponding period of time to which the increment was calculated (in years).
Statistical Analysis
The vegetation cover and height data were analyzed using generalized linear models (GLMs) created through a stepwise backward selection procedure, following a Gaussian error distribution and using the identity link function. The E. globulus H, DBH, and VOL data were analyzed using one-way ANOVA. Changes in DBH, H, and VOL between consecutive herbicide applications were analyzed using two-way ANOVA and ensuing least square difference (LSD) post hoc tests. ANOVA assumptions of normality of the errors and homoscedasticity were tested and validated prior to data analysis. All statistical analyses were carried out with the R software package, version 4.1.2,using routine stats (4.1.2),ggpubr (0.4.0), and dplyr (1.0.8), and using an α of 0.05.
The Effect of Weed Control Treatment on Plant Cover
At both the Torres Vedras (Figure 2) and at Soure (Figure 3) study areas, vegetation cover was consistently lower in the herbicide plots, throughout the entire duration of the experiment. Overall, the plant cover registered in the herbicide plots was 21.9%, while the plant cover in the control plots was 44.6%. In relation to the control plots, the maximum vegetation cover reduction in the herbicide plots was 79% and 94% in Soure and in Torres Vedras, respectively. Woody plant cover was consistently lower than herbaceous plant cover in both study areas (20% vs. 29% in Soure and 34% vs. 43% in Torres Vedras). Notwithstanding, the data suggest that the herbicide treatment produced a higher reduction on woody than on herbaceous cover, since the relative differences between control and herbicide plots were higher for the woody (87.8% in Soure and 52.1% in Torres Vedras) than for the herbaceous cover (69.5% in Soure and 23.8% in Torres Vedras) (Figures 3 and 4). Time after herbicide application (years after treatment, Table 2) had a direct relation with overall plant cover in both study areas; however, according to the GLM, the differential effect of the herbicide for the two functional types does not seem to be consistent for all the sampling years. The best model estimated for explaining the variability in the plant cover data, to a significant extent, included all of the above-mentioned factors: treatment (control or herbicide), plant functional type (herbaceous or woody), and years after treatment, in addition to the effect of the year of the plant cover assessment and the interaction therein between treatment and cover assessment year. The study area was not a significant factor in explaining the variability in plant cover, so it was removed from the first version of the model estimation (Table 2).
E. globulus Productivity
At the Torres Vedras study site, the mean height of E. globulus in the control plots ranged from 4.1 m at 1.5 years to 17.5 m at 8.8 years, while the DBH varied from a mean value of 3.5 cm to 14.9 cm (Table 3). In terms of mean VOL per tree, values went from 2.3 dm 3 (at 1.5 years) to 148.8 dm 3 by the final evaluation of the trial (at 8.8 years). In the Soure study site, the E. globulus H in the control plots was 6.0 m at 1.6 years, reaching 15.2 m at an age of 5.2 years, when the experiment was terminated due to a windstorm (Table 4). The DBH of the same E. globulus trees ranged from the mean value of 9.0 cm (3.2 years) to 12.5 cm. Regarding the VOL of E. globulus trees in the same time frame (from 3.2 to 5.2 years), the variation found was from 38 dm 3 to 91.4 dm 3 . Growth (increment) in H, DBH, and VOL was calculated for the periods between herbicide applications. The results suggest that the H growth increment (Figure 5) was significantly higher (p < 0.05) in the herbicide-treated plots in the time period between the first (T0) and second (T1) applications and between the third application (T2) and the end of the trial (T3). No significant differences in H increase were observed between the second and the third applications among treatments. Similar results were obtained relating to the average tree DHB. Differences in the increment of the DBH (Figure 6) were significantly higher in the herbicide-treated plots during the first (T0) and second (T1) applications and between the last application (T2) and the end of the trial (T3). No significant differences were observed between the second and the third applications in both variables. By analyzing the increment in VOL during the same periods of time (Figure 7), differences between treatments were more evident. Trees from the herbicide-treated plots presented a significantly (p < 0.05) higher increment between all application intervals. Between T0 and T1, the VOL increased by 51.9 dm 3 and 42.2 dm 3 in the herbicide-treated plots and in the control plots, respectively. The same tendency was observed between T1 and T2, with trees from the herbicide plots increasing by an average of 102.7 dm 3 in VOL, while trees from the control plots grew 85.1 dm 3 . From the last herbicide treatment (T2) to the final evaluation (T3), trees increased by 27.1 dm 3 and 19.2 dm 3 in the herbicide and control plots, respectively. The mean annual increment in tree volume (MAI) was significantly higher (p < 0.05) in trees from the herbicide plots than in trees from the control plots for the timing T2-T3 (Table 5), showing a rising trend throughout the three periods of study with MAI values of 16.7 dm 3 year −1 (T0-T1), 30.2 dm 3 year −1 (T1-T2), and 33.9 dm 3 year −1 (T2-T3). The increment in height was significantly different (p < 0.05) between treatments after the first time period (T0-T1), with trees from the weed control plots presenting a growth of 4.4 m, higher than the increase of 3.9 m determined in the height of trees from the control plots (Figure 8). In the second period (T1-T2), the trees had a mean height increment of 1.7 m, and in the third period (T2-T3) of 3.7 m, irrespective of the treatment. The DBH increment was only determined in the third time period after the last herbicide application (T2-T3). During this period, the diameter of trees from the herbicide plots differed significantly from the DBH of trees from the control plots, with increments of 3.8 and 3.5, respectively (Table 6). Similar to the DBH results, the increment in volume in the Soure trial was only determined in the time frame between the final herbicide application and the last biometric evaluation of trees (T2-T3). The results showed that the volume increment in trees from the herbicide plots was significantly higher (p < 0.05) than the mean increment in volume of trees from the control plots: 63.8 dm 3 and 53.4 dm 3 in the herbicide and control plots, respectively. The MAI calculated between the ages of 3.1 years and 5.2 years (T2-T3) was also significantly higher (p < 0.05) in trees from the herbicide plots compared with those of the control plots, with values of 31.9 dm 3 year −1 and 26.7 dm 3 year −1 , respectively.
Discussion
Weed competition is a highly relevant issue in forest management [14,18], particularly due to the limited resources available in young tree establishment and development in spite of understory vegetation growth [15,17]. For this reason, the timing of weed control operations is a major concern to forest managers trying to increase productivity and maintain plantation sustainability at a reasonable cost. In the current work, the prescription for herbicide application was dependent on an objective criteria of understory vegetation development: area occupied by the understory vegetation cover (covering 40% to 60% of the plot) and a mean height of at least 50 cm. This resulted in a differential timing for the application of herbicide: in the Torres Vedras plantation, weed control operations were performed at 1.5, 5.5, and 8.2 years; in Soure, weed control treatments were concentrated in the first 3 years after planting, namely at 1.6, 1.9, and 3.1 years.
Both trials evidenced the effectiveness of the weed control treatments approximately one to two months after herbicide application, with vegetation cover reductions to half (2013) and to one-third (2016) at Torres Vedras and Soure, respectively. The effects of weed control on understory vegetation are usually noticeable within the first weeks after treatment [28,29], but often do not last long depending on site conditions and the composition of the plant community [30]. The duration of the herbicide effect was longer in the Soure study area: two years after the last weed control operation, the area occupied by understory vegetation was about six times lower in treated plots than in control plots. In the present study, the different timings of weed control interventions in both trials were a direct consequence of the criteria established for vegetation control, which did not allow to concentrate the three herbicide applications during the first years after planting at Torres Vedras. A more intensive regime of herbicide applications that allows the concentration of all the interventions in a short period of time may have more effect on controlling the growth and modulating the composition of the understory vegetation, as it could highly diminish competition between forest species and weeds, often during the entire rotation [29]. Herbaceous vegetation typically competes heavily for nutrients and water during the early years of stand formation, while woody vegetation normally develops into a powerful competitor even after crown closure [15].
Both trials presented a positive growth response to the herbicide treatment in terms of H, DHB, and VOL, as reported by other authors [13][14][15]18,29,31]. A possible explanation may be the increment in the leaf area index and the photosynthetic rate of trees with less competition from understory vegetation, as reported by other authors [18,32]. The results from the experiment demonstrated that at both sites, the understory vegetation development and E. globulus growth responded to weed control differently, possibly due to climate conditions, the timing of weed control operations, and understory vegetation composition [13,17,30,31]. Differences between treatments were evident from the start of the trial in Soure, being only perceived in Torres Vedras at a later stage of the experiment. Such a response can be attributed to differences in the competition between weeds and E. globulus among the two areas due to the differential herbicide application regime [29].
Weed competition impacted E. globulus productivity mainly during the early phase of plantation establishment [5,14,15], but our results demonstrated that later weeding operations also contributed to growth increment at the end of the plantation cycle. Inail et al. [31] found significant differences between the DHB and VOL of E. globulus pellita from plots treated with herbicide during the first year and plots treated with herbicide after initial tree establishment, with the last presenting larger mean diameters. Nevertheless, the maintenance of such differences in stand productivity at the end of the rotation was dependent on the site productivity potential [31]. During tree establishment, competition for light, water, and nutrients is limiting for young E. globulus trees [14]. In Soure, during the first five years after plantation establishment, the weed control effect on E. globulus growth profile was more evident in DBH than in H. The same tendency was observed in Torres Vedras, although no significant differences were detected between treatments at that time. No phytotoxic impacts related to herbicide applications were observed in E. globulus trees in either trial. Weed competition substantially reduced the growth of Eucalyptus pellita, particularly in low-productivity sites, but this effect was less evident in high to medium-productivity sites [31]. Our results suggested that, although there were differences in site productivity between the two trials, productivity gains during the first five years of E. globulus growth, before canopy closure, were apparently more dependent on the timing of weed control operations (defined by weed cover) than on the number of operations per se, as differences in the height increment between treatments at Soure were significantly different between 1.6 and 1.9 years.
After tree establishment, competition for light decreases due to higher average tree height in relation to understory vegetation [17]. While Vargas et al. [15] observed a tendency of decreasing in stand productivity loss with the increase in the intensity of weed control treatments, this effect was reported to be more pronounced before canopy closure, and gradually diminishes with age [31]. However, late weed control, such as what occurred in Torres Vedras, may produce significant effects at the end of the E. globulus rotation, even in sites where differences were not evident at younger ages. The continued response to weed control at Torres Vedras may be due to the type of competing weeds, as brambles easily dominated the control and herbicide plots soon after weed control treatments had been applied. The late increment in E. globulus productivity may be explained by a late reduction in the competition for water and nutrients [15,31], as a relevant decrease in the understory vegetation cover of the herbicide plots was only observed after the last treatment.
Weed control led to significant increments in E. globulus growth and stand productivity in both trials, even though the herbicide application timings were different. Under the scope of sustainable forest management, efforts need to be made to reduce the number of chemical interventions in forestry and to mitigate its ecological impacts [33,34]. Studies such as the present one are extremely important in understanding in which situations the gains obtained in terms of forest productivity justify the use of herbicides.
Conclusions
Our results evidenced the effectiveness of weed control on diminishing vegetation cover density to a maximum of 79% and 94% in the Soure and Torres Vedras sites, respectively. Moreover, weed control operations led to significant increments in E. globulus growth and, hence, on final stand productivity. Both experiments revealed this effectiveness, even if in different manners. The effects of herbicide application were more noticeable during the first 3 years following planting in the case of the Soure study site, while they only became significant towards the end of the first rotation in the case of the study site of Torres Vedras. This contrast between the two sites could be related to differences in edaphoclimatic conditions and in understory vegetation composition. This study demonstrated that managing the understory vegetation on eucalyptus plantations requires more than one weed control timing. To maximize productivity, however, the timing of the operations must be regulated according to weed cover development throughout the first rotation cycle of E. globulus, rather than being limited to the initial establishment of the trees. Given the present and future challenges to increasing the resilience of forests under imminent climate changes, as well as the need to minimize herbicide application to comply with the norms of forest certification standards, the definition and widespread implementation of simple protocols for monitoring the effectiveness of chemical and other weed control measures would seem highly recommendable.
Author Contributions: S. C.: investigation, formal analysis, visualization, writing-original draft, funding acquisition. P. M.: formal analysis, writing-review and editing. C. G.: conceptualization, methodology, investigation, writing-review and editing. J. J. K.: formal analysis, writing-review and editing. C. V.: conceptualization, methodology, funding acquisition, project management, supervision, writing-review and editing. All authors have read and agreed to the published version of the manuscript.
Data Availability Statement:
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Figure 1 .
Figure 1. Location of the commercial plantations of E. globulus selected for the establishment of the two study areas: Soure, in Coimbra district, and Torres Vedras, in Lisbon district.
Figure 2 .
Figure 2. Representative scheme of the experimental design at the study sites. Individual trees are represented by green circles, herbicide-treated plots are delimited by black rectangles, and control plots (no weed control) are delimited by red rectangles. The numbers indicate the respective plantation line.
Figure 3 .
Figure 3. Mean weed cover in Torres Vedras study area, evaluated as percentage of woody species cover (black bars) and herbaceous species cover (grey bars), observed at control (C) and herbicide (H) plots in the sampling years of 2010 (1.0 year after the last herbicide application), 2013 (0.1 years after the last herbicide application), 2014 (1.0 year after the last herbicide application), 2015 (2.0 years after the last herbicide application), 2016 (3.1 years after the last herbicide application), and 2017 (1.0 years after the last herbicide application).
Figure 4 .
Figure 4. Mean weed cover in Soure study area, evaluated as percentage of woody species cover (black bars) and herbaceous species cover (grey bars), observed at control (C) and herbicide-treated (H) plots in the sampling years of 2016 (0.2 years after the last herbicide application), 2017 (1.1 years after the last herbicide application), and 2019 (1.9 years after the last herbicide application).
Figure 5 .
Figure 5. Mean increment in H (m) of E. globulus trees at Torres Vedras study area in the control treatment (dark grey) and in the weed control treatment (light grey) between herbicide applications: from 1.5 years to 5.2 years (T0_T1), from 5.5 years to 8.2 years (T1_T2), and from 8.2 years to 8.8 years (T2_T3). Different letters indicate significant differences (p < 0.05) in height increment as detected by the two-way ANOVA test.
Figure 6 .
Figure 6. Mean increment in DBH (cm) of E. globulus trees at Torres Vedras study area in the control treatment (dark grey) and in the weed control treatment (light grey) between herbicide applications: from 1.5 years to 5.5 years (T0_T1), from 5.5 years to 8.2 years (T1_T2), and from 8.2 years to 8.8 years (T2_T3). Different letters indicate significant differences (p < 0.05) in DBH increment as detected by the two-way ANOVA test.
Figure 7 .
Figure 7. Mean increment in individual volume (dm 3 ) of E. globulus trees at Torres Vedras study area in the control treatment (dark grey) and in the weed control treatments (light grey) between herbicide applications: from 1.5 years to 5.2 years (T0-T1), from 5.5 years to 8.2 years (T1-T2), and from 8.2 years to 8.8 years (T2-T3). Different letters indicate significant differences (p < 0.05) in volume increment as detected by the two-way ANOVA test.
Table 5 .
Mean annual increment in individual volume (MAI) of E. globulus trees at Torres Vedras in the control plots (dark grey) and in weeding plots treated with herbicide (light grey), determined between herbicide applications: from 1.5 years to 5.2 years (T0-T1), from 5.5 years to 8.2 years (T1-T2), and from 8.2 years to 8.8 years (T2-T3). Different letters indicate significant differences (p < 0.05) in volume increment as detected by the two-way ANOVA test.
Figure 8 .
Figure 8. Mean increment in height (m) of E. globulus trees at Soure study area in the control (dark grey) and in the herbicide plots (light grey) between herbicide applications: from 1.6 years to 1.9 years (T0-T1), from 1.9 years to 3.1 years (T1-T2), and from 3.1 years to 5.2 years (T2-T3). Different letters indicate significant differences (p < 0.05) in height increment as detected by the two-way ANOVA test.
Table 6 .
Mean increment in diameter at breast height (DBH), increment in individual volume (VOL), and mean annual increment in individual volume (MAI) of E. globulus trees in the control and in the herbicide plots between herbicide applications from 3.1 years to 5.2 years (T2-T3). Different letters indicate significant differences (p < 0.05) in the measured variable increments as detected by the two-way ANOVA test.
Table 1 .
General characteristics of the two study areas, including information on the weed control treatment application: Torres Vedras (Lisbon) and Soure (Coimbra).
Table 2 .
Factors affecting vegetation cover at Torres Vedras and Soure study areas, obtained by applying a generalized linear model (GLM) to the observed data.
Table 3 .
E. globulus height (H), diameter at breast height (DBH), and individual tree volume (VOL) of the trees in control plots by age from the start of the experiment in 2009 (1.5 years) to its conclusion in 2017 (8.8 years) in the Torres Vedras study area.
Table 4 .
E. globulus height (H), diameter at breast height (DBH), and individual tree volume (VOL) of the trees in control plots by year since the establishment of the experiment in 2015 (1.6 years) until its end in 2019 (5.2 years) in Soure study area (na means no available data).
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Domain: Environmental Science Agricultural And Food Sciences
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Three-dimensional pore characterization of intact loess and compacted loess with micron scale computed tomography and mercury intrusion porosimetry
The pore structure is one of the most important properties of soil, which can directly affect the other properties such as water content, permeability and strength. It is of great significance to study the soil pore structure for agricultural cultivation, water and soil conservation and engineering construction. This paper investigates the 3D pore characterization of intact loess and four kinds of compacted loess (with different dry density) in northwest China. Micro scale computed tomography and mercury intrusion porosimetry tests were performed to get the porosity, specific surface area, pore size distribution, connected pores content and isolated pores content of different samples. Results show that the intact loess has more connected pores than the compacted loess, and the compacted loess whose dry density appears to be modelled well still have different pore structure with the intact loess. In addition, as the compactness increasing, the large pores (>13 μm) were firstly broken into medium pores (8~13 μm) and some small pores (<8 μm) until the pore structure was close to the natural structure of the intact loess, after that medium pores began to be broken into small pores.
microphotograph decreased as the initial water content increased. Jiang, et al. 12 took SEM observations on the natural and remolded samples before and after CU triaxial tests and found that the pores became disconnected and smaller with the confining pressure increased. And the pores in the natural sample were larger than those in the remold sample under the low confining pressure, while the pore size and its distribution were nearly identical for the natural and remolded samples when the confining pressure was up to 600 kPa as most cementation bonds in the natural sample had been broken. Xie, et al. 13 analyzed documented changes in particles and micropore structure of loess-like soil during triaxial creep tests with SEM, and pointed out that mesopores which covered the largest area were the most important factors leading to loess-like soil creep.
Since the 1980s, mercury intrusion porosimetry (MIP) has become another quantitative analysis method to study the microstructure of loess, especially the porosity and the pore size distribution (PSD) 14 . Lei 4 studied the PSD characteristics of the loess in China based on mercury intrusion porosimetry (MIP) tests, and classified loess pores into four types according to the size: the large pores (>0.016 mm in radius), the medium pores (0.016-0.004 mm), the small pores (0.004-0.001 mm) and the micropores (radius <0.001 mm). And the results have shown that the content of the medium pores of the samples after slumping on wetting decreased more than that of the original one, which indicated that the medium pores are important spaces for loess subsidence on wetting. By combining MIP and SEM, quantitative representation of the loess pore microstructure has become more accurate 12,15,16 .
However, all the images obtained by SEM are 2D images and the results are highly depend on the choice of observing directions, which will result in non-unique shape descriptors for pores and particles 17 . To reflect the truly geometric features of the pore networks, Wei, et al. 14 generated serial SEM images by looping the polishing and image acquisition, and reconstructed the 3D loess microstructure. In consideration of maintaining the original structure of the sample to the maximum extent during the thickness removal, the loess pores were filled with the epoxy resin mixture 18 . In this case, it is difficult to ensure that all microscopic pore structures remain in their original state. Analogously, because of the principle that forcing a non-wetting liquid (often mercury) to intrude into a material at high pressure to get the PSD, MIP is destructive and the results may not true 19,20 .
With the development of observation technology, researchers attempted to use computed tomography (CT) to obtain the 3D pore structure of soil in recent years 21,22 . CT scan can be used to see the images of each layer inside the sample without interfering with the test process, and the image data can be analyzed mathematically to obtain the required information. Pu, et al. 23 took the lead in applying CT (whose resolution was close to 1 mm) to the observation of the internal structure of undisturbed loess and observed that the macro-behavior of sample is closely related with its microstructure change. With CT and MATLAB, Li, et al. 24 constructed the 3D macropore models of intact Malan loess at a resolution of 59 μm, and the results indicated that the pore connectivity in the vertical direction was better than that in the horizontal direction. With a resolution of 1 μm, Wei, et al. 25 investigated the 3D pore network characterization of intact loess and paleosol samples in the South Jingyang Plateau, and it was further clarified that clay content could obviously affect the pore structure.
Previous studies have shown that the original macropore structure of loess can be destroyed into small pores under the action of high external force 1,10,12 . Moreover, loess with relatively small pores is more stable than that with large pores 4,26 . Thus, people generally compact the loess to increase its stability in actual engineering project [27][28][29] . However, a large number of studies have shown that despite the compaction measures, the remolded loess still has collapsibility which can be even more serious than the original loess [30][31][32][33] . Therefore, it is really necessary to study the microstructure of compacted loess. Using MIP tests, Rendell 34 compared the PSD of naturally consolidated loess and laboratory compacted loess, and found that the pore distribution of artificially compacted loess was different from that of naturally consolidated loess. Wu, et al. 35 analyzed the microstructure characteristics of compacted loess by SEM and divided the pores of compacted loess into two categories, scaffold pores and mosaic pores. Wang, et al. 36 did a comparative study on the evolution of pore-size distribution of intact loess and remolded loess due to consolidation by SEM and MIP tests. The results have shown that remolded loess has very different microstructure and PSD from intact loess even though they may have the same grain-size distribution (GSD), mineralogical composition, and some other physical properties In sum, the comparative study between intact loess and compacted loess from the aspect of 3D geometrical pore microstructure at high resolution, especially based on the non-destructive CT scanning technology, is very limited. Quantitative analysis of the microscopic pores of compacted loess samples under undisturbed conditions is urgently needed.
In this paper, quantitative analysis and comparison were carried out to characterize the 3D pore microstructure of the intact and compacted loess from the Loess Plateau. At the same time, the differences between the MIP test results and the high-resolution scan results of the same sample were compared and analyzed. This research is helpful for further understanding the 3D pore geometrical characteristics of intact and compacted loess and provides insights into the study of mechanical mechanism of loess behavior.
Results
The 3D quantitative parameters of the pore structure were extracted for each of the loess samples, including porosity, specific surface area, PSD, connected pores content and isolated pores content. The definition of the parameters and how to get them were explained in the Methodology. The results were analyzed as described below.
Porosity. Porosity is a single-value quantification of the amount of space available to fluid within a specific body of soil and can reflect the compactness of soil. Table 1 shows the porosity of the samples from different tests. As soil samples with dry density of 1.50 g/cm 3 were relatively loose, the small size YA-l6-1.5 sample was damaged during removal from the plastic tube. Thus, there was no n m1 for YA-l6-1.5. It can be easy to find that the porosity from CT scanning (n 0 ) is different from the porosity from MIP test (n m ). And for results of the MIP tests, the www.nature.com/scientificreports www.nature.com/scientificreports/ porosity of small size samples (n m1 ) is greater than that of large size samples (n m2 ). Although the sample used in CT scanning and that used in the small-size MIP tests were the same one, the results from CT scanning were more similar to those from the large size MIP tests, and the results from the two experiments on intact loess were the most similar. By comparing the results of YA-L6-1.5, YA-L6-1.6, YA-L6-1.7 and YA-L6-1.8, it can be found that the porosity of the compacted loess samples decreases as the dry density increases. And from CT scanning results, the intact loess has greater porosity than the compacted loess, even though YA-L6-1.5 has a smaller dry density.
Specific surface area.
Specific surface area is one of the important parameters for studying soil pore structure and matric suction. Table 2 shows the specific surface area for different samples from different tests. As the micro-CT resolution is 1 μm, the specific surface area from CT scanning (S 0 ) only considered the pores whose equivalent pore diameters are larger than 1 μm.
For results from CT scanning, it can be easy to find that the intact loess has a larger specific surface area (S 0 ) than the compacted loess. For the compacted loess samples, as dry density increasing, S 0 has become smaller and gradually approached a constant value, 0.20 μm 2 /μm 3 . The MIP tests have measured a completely different result, that the compacted loess has a larger specific surface area (S M ) than the intact loess. And for the same sample, S M can be tens of times as much as S 0 . However, only considering pores whose diameter are larger than 1 μm, the results from MIP test (S L ) are similar to those from CT scanning. By comparing S M and S L , one can find that there are more pores whose diameter are less than 1 μm in the compacted loess than in the intact loess.
Connected and isolated pores. The connected pores have constituted the main channel through which air and water flow in the loess soil. Table 3 shows the content of connected (Nc) and isolated pores (Ni) for different samples from CT scanning. It can be found that at a resolution of 1 μm, the ratio of connected pores to all the Table 2. Specific surface area for different samples from different tests. S 0 -the area of the total pore boundary divided by the volume of the soil skeleton from CT scanning. S M -the total surface area of all the pores divided by the particle skeleton volume of the large size sample from MIP test. S L -the total surface area of pores (d > 1 μm) divided by the particle skeleton volume of the large size sample from MIP test. www.nature.com/scientificreports www.nature.com/scientificreports/ pores is really high. And the intact loess has more connected pores and less isolated pores than the compacted loess. As dry density increasing, the proportion of isolated loess has become higher and gradually approached a constant value, 0.30%, even though the proportion of connected pores is still decreasing.
PSD.
The PSD can indicate complex pore structure characteristics in far more detail than porosity alone 37 . In this study, the micro-CT resolution is 1 μm, so the pores whose equivalent pore diameters are smaller than 1 μm cannot be detected. And as the volume of the reconstructed 3D structure is limited, there are no pores with an equivalent pore diameter larger than 60 μm. It can be found that the trend of PSDs is similar (Fig. 1). For the compacted loess samples, there are more large pores if the dry density is small. And the PSD of the intact loess sample YA-L6-Intact is more similar to those of the compacted loess samples with larger dry density, even though its dry density is closer to that of YA-L6-1.5.
By comparing the small-size MIP tests and the large-size MIP tests ( Fig. 2) one can find that the MIP-small curve is multi peaked and the MIP-large curve has two peaks at 0.6 μm and 8 μm, approximately. The results of the MIP tests also show that each sample has pores whose equivalent pore diameters are larger than 100 μm. And these large pores do not decrease with the dry density increasing. Except YA-L6-1.5, the MIP-large curves of different samples have the similar form. Moreover, comparing the results from the MIP tests and CT scanning (Fig. 2) the volume fractions under different equivalent pore diameters from the large-size MIP tests are less than 10% while those from the CT scanning can up to 30%. The PSDs from CT scanning are more concentrated and the CT curve has only one peak. From Fig. 1 one can find that the peak is concentrated in 4~6 μm.
From Fig. 3 one can find that the volume fraction of compacted loess samples under different equivalent pore diameters varies with dry density. For pores with an equivalent diameter of 0~8 μm, the volume fraction increases with the increasing of dry density (Fig. 3a). For pores with an equivalent diameter of 8~12 μm, the volume fraction increases first and then decreases with the increasing of dry density (Fig. 3b). For pores with an equivalent diameter of 12~14 μm, the volume fraction decreases slowly in the case of low compactness, then gradually decreases with the increasing of dry density. For pores with an equivalent diameter of 14~36 μm, the volume fraction gradually decreases with the increasing of dry density, and the decreasing extent reduces gradually (Fig. 3c). For pores with an equivalent diameter larger than 36 μm, the volume fractions are no more than 0.5%. Although the volume fraction also decreases with the increasing of dry density, it is relatively stable and the change is not obvious (Fig. 3d). Figure 4 shows the volume fraction of intact loess and four kinds of compacted loess samples under different equivalent pore diameters. It is obvious that the PSD of the intact loess sample is more similar to those of the compacted loess samples with larger dry density (Fig. 4a). Except the pores whose equivalent diameters are 0~4 μm and 8~10 μm, the volume fraction of other pores is just like that of YA-L6-1.7. Although the dry density of the intact loess is closer to that of YA-L6-1.5, the PSDs of the two samples are quite different. For pores with an www.nature.com/scientificreports www.nature.com/scientificreports/ equivalent diameter less than 10 μm, the volume fraction of the intact loess is higher than that of YA-L6-1.5 (Fig. 4b). And for pores with an equivalent diameter of 12~50 μm, the volume fraction of the intact loess is less than that of YA-L6-1.5 (Fig. 4c). However, for pores with an equivalent diameter of 10~12 μm, the volume fraction of the intact loess and two kinds of compacted loess (YA-L6-1.5 and YA-l6-1.6) are almost the same (Fig. 4b).
And just like Fig. 3d, the difference of the pores whose equivalent diameters are larger than 50 μm between the intact loess and the compacted loess is not obvious (Fig. 4c).
Discussion
Comparison of CT technique and MIP. The afore mentioned results demonstrate that the porosity, specific surface area and pore distribution obtained from CT scanning are quite different from those obtained by MIP tests. www.nature.com/scientificreports www.nature.com/scientificreports/ There are two main reasons to explain the differences in porosity (Table 1). Firstly, the CT scanning can only detect pores whose equivalent pore diameters are larger than 1 μm, while the MIP tests can detect pores with a diameter between 0.001 μm and 1000 μm. The direct difference between n 0 and n m is mainly from whether the pores, whose diameter are between 0.001 μm and 1 μm, were counted or not. This reason can also explain the differences in specific surface area (Table 2), that why S M is greater than S 0 and why S L is more similar to S 0 . Secondly, the principle of MIP is to measure the volume of pores by the amount of mercury entering under different pressures. As there are many small bottlenecks inside the specimen, high-pressure intrusion of mercury may either deform or damage the soil structures, resulting in inaccurate estimates of soil porosity 17,19,20 . However, CT scanning is a nondestructive technique which will not interfere with or destruct the internal structure of soil, and the measurements of three-dimensional structures are based on actual observations rather than shape assumptions, so that it can accurately describe the true spatial characteristics of the pores 17,25 . Moreover, compared with large size samples, the small size samples are more likely to be disturbed during the test operation. For example, dried loess samples are prone to powder on the surface during manual sample preparation operation, and the powder volume of the small size sample accounts for a larger proportion of the total volume. And small size samples are more likely to be destroyed than the large size samples under the same pressure intrusion by mercury, due to the smaller external constraint volume of the pore. The above reasons can explain why n m1 is greater than n m2 , and why n m2 is more similar to n 0 (Table 1). In this study, the PSDs from the CT scanning were obtained by counting the total volume of pores according to the range of equivalent diameter rather than the volume of each pore under a specific equivalent diameter. And the range is 2 μm. That's one reason to explain why the volume fractions under different equivalent pore diameters from the CT scanning can up to 30%, which are much larger than the MIP results. Another reason is that some large pores with complex morphology were divided into many small pores according to the pore throat during parameter extraction. While in the results of MIP tests, these connected large pores were still independent pores with large equivalent diameters. Moreover, compared with MIP, X-ray CT can detect not only the connected pores but also isolated ones 20,38 . And this is the third reason to explain the large volume fractions. For the small pores with a diameter between 2 μm and 8 μm 4 , the peak of the MIP curve is concentrated in 8 μm while the peak of the CT curve is concentrated in 4~6 μm (see Figs. 1 and 2). This result indicates that the equivalent diameter of most isolated pores is 4~6 μm.
Although the CT technique does not interfere with or destruct the pore structure of the samples and produces a higher detectability of pores, there are still many limitations. Firstly, there is a conflict between the specimen size and the scanning resolution. Given a certain CT device, the specimen must be small enough to obtain high resolution images. However, small specimens cannot encompass macropores and the analysis of the macropores are not representative. In addition, pores with a diameter less than the resolution of the instrument cannot be detected. It is difficult to make small loess samples without artificial disturbance, and it cannot be fixed in experimental observation when the sample size is very small. Thus, MIP is still irreplaceable to study the nano pores of the loess. The differences of pore microstructure between intact loess and compacted loess. By analyzing the porosity of the intact and compacted loess obtained by different experiments, one can find that n 0 and n m2 of the intact loess are basically the same, while there is a big difference between n 0 and n m2 for the compacted loess (Table 1). By comparing the content of connected and isolated pores for different samples from CT scanning (Table 3), one can find that the intact loess has more connected pores than the compacted loess. Considering the discrepancies in porosity values detected by MIP and m-CT methods could help to determine the volume of closed or unconnected pores in the soils 38 , the results from Fig. 2 further confirm that. In addition, by comparing the specific surface area of the intact and compacted loess obtained by different experiments (Table 2), one can find that the compacted loess has more small pores (0.001 μm < d < 1 μm) than the intact loess. The results also suggest that the pore structure of the intact loess is more stable as a result of the long period of structural evolution of the loess, so that it cannot be easily changed under high pressure intrusion by mercury compared with the compacted loess. This structural evolution of the loess is closely related to the movement of water 24 . There is a certain amount of water in loess under natural condition, which mainly comes from precipitation, frost, and snow 39,40 . On one hand, the water seepage in loess facilitates the formation of connected pores in loess 41 . On the other hand, the infiltrating water dissolves soluble salts, causing transportation and reprecipitation of calcium carbonates 42 and reinforcement of existing pores by cements 43 . However, the compacted loess has not experienced that structural evolution so that it contains more isolated pores and more small pores.
Another significant conclusion can be drawn from the data in Figs. 1 and 4, that the pore structure of the intact loess is more similar to that of the YA-L6-1.7, even though its dry density is closer to that of YA-L6-1.5. It suggests that the remolded loess in laboratory cannot represent the original loess with the same physical properties. In order to get similar pore structure, the remolded loess must be compacted until its dry density is slightly higher than that of intact loess. The result observed from the new method can further confirms the conclusion from Rendell 34 , that laboratory consolidated loess do not mirror those for naturally consolidated loess even though the density appears to be modelled well. And from Fig. 4, one can speculate that, when the dry density is identical, the compacted loess would have more small pores than the intact loess. Furthermore, from the data of pores whose equivalent diameter is 10~12 μm (Fig. 4b), there is a preliminary judgment that pores with a diameter of 10~12 μm cannot be easily destroyed under low compactness (i.e. dry density less than 1.6 g/cm 3 ).
According to the changing trend of content with dry density increasing (Fig. 3), the pores can be divided into three categories base on the equivalent diameter: large pores (>13 μm), medium pores (8~13 μm) and small pores (<8 μm). It should be noted that the pores whose equivalent diameter is 12~14 μm, its content firstly decreases slowly. It means that the content of some small pores increases and that the content of some large pores decreases. For convenience, 13 μm is used as the dividing standard here. As the dry density increases, the content of small pores continues to increase while the content of large pores decreases rapidly first and then decreases slowly. However, the changing trend of medium pores content is first increasing and then decreasing. Results suggest that, with the continuous increasing of compactness, the large pores in the remolded loess were firstly broken into medium pores and some small pores until the pore structure was close to the natural structure of the intact loess. When the compactness was further increased, a lot of medium pores were broken into small pores. Analyzing Figs. 3 and 4, the volume fraction of pores (>13 μm) is stable for the intact loess and the compacted loess whose dry density is greater than its natural state. That may be due to the similar grain-size distribution (Table 4).
conclusions
In this paper, the three-dimensional pore structures of the intact and four kinds of compacted loess from the Loess Plateau were reconstructed based on micron scale computed tomography. By comparing porosity, specific surface area and PSD between the intact and compacted loess, and analyzing the results of CT scanning and MIP tests, the following important conclusions can be reached: (1) The intact loess has more connected pores than the compacted loess and the pore structure of the intact loess is much more stable. (2) The compacted loess cannot mirror the intact loess in pore structure even though the dry density appears to be modelled well. (3) The content of pores with a diameter of 10~12 μm is consistent with the natural state under low compactness. (4) The pores of the compacted loess are divided into three categories base on the equivalent diameter: large pores (>13 μm), medium pores (8~13 μm) and small pores (<8 μm). As the dry density increases, the large pores were firstly broken into medium pores and some small pores until the pore structure was close to the natural structure of the intact loess. When the compactness was further increased, a lot of medium pores were broken into small pores. www.nature.com/scientificreports www.nature.com/scientificreports/ This paper did not carry out comparative study before and after the mechanical test, and the structure evolution of the intact and compacted loess under the stress state is still unknown. As a future work, comparative study before and after the mechanical test should be carried out to understand the collapse mechanism of the intact and compacted loess.
Furthermore, the method to study pore structure in this paper also provides a new idea for the study of soil structure in the fields of agricultural cultivation, water and soil conservation and engineering construction.
Methodology
Sampling and sample preparation. The samples of loess used in this study were obtained from a slope in Yan'an City, Shannxi, China. The slope is about 46 meters high, and distinct loess strata can be observed (Fig. 5a). According to the study of loess strata by Liu 44 , a preliminary stratigraphic identification of the section was conducted in the field. Figure 5b shows the stratigraphic profile of the slope. The material composition and microstructure of loess in different strata are obviously different 4,24,25 . To ensure the uniformity, all the samples used in the tests all come from the same place in the same stratum, the L6 layer of Middle Pleistocene (Q2) strata.
To avoid disturbance during the transportation, the intact loess samples of cylindrical shape with diameter of 11 cm and height of 16 cm were well sealed by PVC pipe, plastic wrap and plastic tapes. Table 5 shows some physical properties of the randomly selected cylindrical loess samples, including the dry density, specific density, moisture content, liquid limit and plastic limit. All the parameters were determined according to Chinese standard for soil test method (GB/T 50123-1999). The results show that the physical properties of different cylinder samples are basically the same, which ensure that the compacted loess samples made from the other cylindrical samples have the similar specific density, liquid limit and plastic limit with the intact loess sample.
The compacted loess used in the tests includes four different dry densities (1.5 g/cm 3 , 1.6 g/cm 3 , 1.7 g/cm 3 , 1.8 g/cm 3 ) and the sample processing steps are as follows: a. The loose soil from intact cylindrical samples was selected and dried naturally. After fully crushed, it was passed through a 2 mm sieve and then was dried for no less than 8 hours at 100 °C. www.nature.com/scientificreports www.nature.com/scientificreports/ b. 1000 g dry soil and 100 g distilled water were mixed thoroughly and then sealed for more than 48 hours, to make sure that the moisture content of the compacted samples was 10%, as the grain profile of compacted loess under this water content was more clear 45 . c. Put the mental ring (61.8 mm × 20 mm) into the box of the sample making apparatus and then add the certain quality of soil according to the preset dry density. d. Put the box in the correct location in the sample making apparatus and apply pressure to the soil in the box by the jack at the bottom for more than 40 seconds. e. Take out the mental ring, cut the sample, weigh it and calculate the dry density of the processed sample. If the error was greater than 0.01 g/cm 3 compared with the preset dry density, the sample would be discarded. Table 4 shows the dry density, the clay(<2 μm), silt(2-50 μm) and sand(>50 μm) fractions of the samples 46 . The above data of particle size analysis were obtained from a Malvern Mastersizer3000 laser analyzer. www.nature.com/scientificreports www.nature.com/scientificreports/ As there was a lot of moisture in the initial samples, they were put in a dry place with constant temperature and ventilation for more than one month to meet the requirements of the CT scan and MIP tests. After air-drying, the samples were trimmed to cylindrical by extremely thin and sharp blades. For CT scan, the diameter of the samples was 3 mm and the height was 5 mm. For MIP tests, besides the small size samples, the diameter of the large size samples was 1 cm and the height was 1.5 cm. All the samples were encased in a plastic tube to prevent disturbance (Fig. 6).
CT scanning. A micro-CT device with high resolution (Xradia520 Versa from Zeiss) was used to scan the specimens, at the Institute of Geology and Geophysics, Chinese Academy of Sciences (Fig. 7a) www.nature.com/scientificreports www.nature.com/scientificreports/ can observe the three-dimensional appearance and internal structure of the sample without destroying the integrity of the sample, and realize the three-dimensional visualization of the observation results. The highest resolution (volume pixel) reached by the instrument is 0.35 micron. In this study, the scan system was set to 60 kV (voltage) and 81 μA (current), and the pixel size was 1 μm. After CT scanning, 997 gray images were obtained for each sample, and each image was consisted of 1,002,820 (1015 × 988) pixels with gray values in the range of 0-255. It can be easily to distinguish soil particles and pores by the difference of gray scale which represents the X-ray attenuation coefficient (Fig. 7b). The cylindrical sample can be obtained after the gray image combination (Fig. 7c). Table 6 shows the three-dimensional appearance of the scanned sample. The cylinder diameters obtained from scanning different samples were slightly different.
Data processing. The procedure to get the three-dimensional pore characterization consists of two main parts: 3D pore structure reconstruction and 3D parameter extraction. In addition, the 3D data can be easily visualized, analyzed and modeled with the Avizo software. Figure 8 shows the specific workflow to reconstruct the 3D pore structure.
Firstly, for each sample, 800 consecutive gray images were selected to load in Avizo to get the 3D microtomography volume (Fig. 8a). The 3D cylindrical volumes of the samples were 480,523,200 μm 3 for YA-L6-Intact, 475,346,500 μm 3 for YA-L6-1.5, 462,029,300 μm 3 for YA-L6-1.6, 479,319,200 μm 3 for YA-L6-1.7 and 450,771,200 μm 3 for YA-L6-1.8, respectively. Secondly, to highlight image features before segmentation, the Gauss filter was used to reduce image noise or artifacts (Fig. 8b). Thirdly, particles and pores were segmented in a semi-automatic way by using interactive watershed tool and artificial selection, which could give more accurate results than commonly used segmentation method (Fig. 8c). Finally, the segmented pores were selected in 3D mode to generate new volume without the particle parts, and the 3D pore structure was obtained (Fig. 8d).
The 3D quantitative parameters, such as porosity, specific surface area and equivalent pore diameter, were extracted to depict the loess pore structure. Among them, the porosity and the specific surface area could be extracted directly with the analysis module in Avizo. Here, the porosity (n 0 ) is defined as the ratio of the number of pore voxels to the number of all voxels (pore voxels and particle voxels) in the cylindrical volume. The specific surface area (S 0 ) is defined as the area of the total pore boundary divided by the volume of the soil skeleton. In the meanwhile, the connected pores and isolated pores can be distinguished, and the voxel number of these two types of pores were also calculated. Here, Nc means the ratio of the number of connected pore voxels to the number of all voxels. Ni means the ratio of isolated pore voxels to the number of all voxels. According to Li and Yang 47,48 , the specific process of generating the equivalent pore diameter is as follows: a. A three-dimensional image corresponding to the sample to be measured was obtained and all pores in the three-dimensional image were extracted (Fig. 8). b. The pore throat identification system developed by Li and Yang 47 of the Institute of Geology and Geophysics, Chinese Academy of Sciences, was used to segment the connected pores in the volume. c. On account of an isotropic voxel size was 1 μm in this study, the default geometry was set to a cube with a length of 2 μm. d. The number of cubes (2 μm × 2 μm × 2 μm) that could be filled at most in each pore was calculated, and the maximum number of fillings corresponding to each pore was obtained. e. The equivalent pore diameter corresponding to each pore was calculated according to the maximum number of fillings corresponding to each pore and the size of the geometry. By the way, the PSD was obtained. www.nature.com/scientificreports www.nature.com/scientificreports/ MIP test. In this study, mercury injection test was also carried out on the air-dried samples (both small size and large size) to statistics the PSD data, the porosity and the specific surface area in order to compare with the results from the CT scanning. The small size samples were the samples after CT scan. The MIP apparatus was the PoreMaster 60GT MIP device from Quantachrome Corporation.
Given the assumption of a cylindrical pore model and according to the definition of liquid surface tension, the relationship between the intrusion pressure p and the pore diameter d p can be written as d p = −4γcosθ/p, where γ is the surface tension of mercury at 20 °C (0.485 N/m) and θ is the contact angle between mercury and the solid phase (140°) 19,36,[49][50][51] . The pore volume can be derived from the quantity of intruded mercury at the appropriate pressure step for the corresponding pore diameter.
Here, the porosity (n m ) is defined as the ratio of total pore volume (cm 3 ) to the bulk sample volume (cm 3 ). The specific surface area (S M ) is defined as the total surface area of all the pores divided by the particle skeleton volume of the large size sample from MIP test, and it can be calculated as the product of surface area (m 2 /g) and particle density (g/cm 3 ). To compare with the results from CT scanning, the specific surface area (S L ) of pores whose diameter are larger than 1 μm was also calculated. It is defined as the total surface area of pores (d > 1 μm) divided by the particle skeleton volume.
Data availability
The data generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Domain: Geology Agricultural And Food Sciences
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Prospective cohort study of broccoli consumption frequency and all-cause and cause-specific mortality risks
Background Broccoli is rich in vitamins, minerals, and antioxidants with broad health benefits, but its intake frequency and dose–response relationship with mortality risk remain unclear. Methods Using data from the U. S. National Health and Nutrition Examination Survey 2003–2006, 12,486 adults were included. Broccoli intake frequency was evaluated by a food frequency questionnaire, and all-cause and cause-specific mortality risks were followed up. The relationship between broccoli intake and mortality risk was analyzed using Cox models. Results Compared with never consumption of broccoli, different frequencies of broccoli consumption were associated with significantly decreased risks of all-cause mortality (p for trend <0.001). Consuming broccoli 1–2 times per week was associated with a 32–43% lower mortality risk. More frequent broccoli consumption was negatively correlated with cardiovascular and cancer mortality risks (p < 0.05). Consuming broccoli 1–2 times per week for males and ≥ 3 times per week for females could significantly reduce all-cause mortality risk. Conclusion Moderate and frequent consumption of broccoli may reduce the risks of all-cause and cause-specific mortality. Optimal intake frequencies may differ by gender.
Introduction
With changes in lifestyle, the incidence and mortality of chronic non-communicable diseases such as cardiovascular disease and cancer continue to increase, posing a major threat to public health worldwide (1). Fruits and vegetables as natural health foods are nutritious and pharmacologically valuable in preventing many chronic diseases. In recent years, more and more epidemiological studies have begun to focus on the health benefits of single vegetables (2). Among them, broccoli from cruciferous vegetables has received much attention due to its unique nutritional composition and abundant bioactive components (3). Broccoli is not only rich in vitamins (vitamin C, carotenoids, etc.), minerals, and dietary fibers but also contains abundant sulfur-containing bioactive compounds (4). Numerous studies have shown that broccoli has broad-spectrum pharmacological properties such as anti-inflammatory, antioxidant, anticancer, blood pressure lowering, hypoglycemic, and hypolipidemic effects and play an important role in preventing cardiovascular diseases, cancers, type 2 diabetes, and other diseases (5)(6)(7)(8).
For example, broccoli is abundant in sulfur-containing organic compounds, among which the compound isothiocyanate sulforaphane has been found to have certain preventive effects on prostate cancer, pancreatic cancer, leukemia, and colon cancer (9-12). However, conclusions from different studies on the dose-response relationship between broccoli intake and the prevention of chronic diseases are inconsistent. Few prospective cohort studies have found that a higher intake of cruciferous vegetables is associated with a lower risk of overall mortality and cardiovascular disease mortality compared to a lower intake of cruciferous vegetables (13). However, the available data do not provide specific recommendations for broccoli consumption frequency. Therefore, it is of great significance to use large sample prospective study results to analyze the dose-response relationship between broccoli intake frequency and all-cause and cause-specific mortality, which can provide guidance for dietary adjustment in different populations, especially dietary interventions for patients with chronic diseases.
This study utilized the prospective cohort data of the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2006 to assess the relationship between different frequencies of broccoli intake and all-cause mortality and cause-specific mortality from cardiovascular diseases, cancers, and other diseases in approximately 12,486 adult participants. The results can provide a basis for developing scientific dietary guidelines and guiding dietary adjustments for patients with chronic diseases.
Study population
NHANES is an important cross-sectional survey conducted by the National Center for Health Statistics (NCHS) using a stratified and probabilistic random sampling design, aiming to assess the health and nutritional status of the American population. NHANES primarily acquires data via face-to-face interviews, physical examinations, and laboratory tests administered by researchers. Within the database, we initially screened 12,486 patients and subsequently subjected them to inclusion and exclusion criteria. The inclusion criteria were as follows: (1) all participants aged 20 years or older who consistently participated in NHANES cycles from 2003 to 2006 and (2) participants who cooperated with follow-up assessments and provided informed consent. The exclusion criteria were as follows: (1) age below 20 years; (2) absence of dietary data at survey initiation; (3) unavailability of survival status; (4) the outcome event was death but the cause was missing; and (5) suffering from a certain non-communicable disease at the start of follow-up. As de-identified and publicly available data were utilized, institutional review board approval was not necessary.
Data collection
Dietary data on broccoli were obtained from the Food Frequency Questionnaire (FFQ) based on participants' responses to the questions: "Have you ever consumed broccoli?How frequently do you consume broccoli?, " with responses recorded for never consuming broccoli and the frequency of broccoli consumption. Participants' responses were used to classify broccoli consumption into four categories: never ("never"), infrequently ("less than once a week"), occasionally ("1 to 2 times per week but less than 3 times per week"), and regularly ("3 or more times per week"). Furthermore, covariate information such as age, gender, race, education level, poverty income ratio (PIR), body mass index (BMI), smoking status, alcohol consumption status, and history of hypertension, dyslipidemia, and diabetes was collected through questionnaire surveys. Participants were stratified based on PIR as follows: PIR (low) ≤ 1, PIR (medium) > 1-<4, and PIR (high) ≥ 4 (14). BMI was determined as the ratio of weight (kg) to the square of height (m 2 ). Smoking status was categorized as follows: "Current" referred to individuals who reported smoking more than 100 cigarettes in their lifetime and currently smoked on all or some days; "Former" referred to individuals who reported smoking more than 100 cigarettes in their lifetime but currently did not smoke; and "Never" referred to individuals who reported smoking less than 100 cigarettes in their lifetime. In terms of alcohol consumption status, "Now" was defined as participants who consumed alcoholic beverages in the past year, "Former" was defined as participants who had consumed alcoholic beverages in the past year but had stopped drinking at the time of the survey, and "Never" was defined as participants who had not consumed any alcoholic beverages in the past year. If systolic blood pressure is ≥140 mmHg or diastolic blood pressure is ≥90 mmHg, with the use of antihypertensive medication, an individual can be diagnosed with hypertension. If triglyceride level is ≥150 mg/dL; high-density lipoprotein is <140 mg/ dL; and low-density lipoprotein is ≥130 mg/dL, with the use of lipidlowering medication, an individual can be diagnosed with dyslipidemia.
If fasting blood glucose level is ≥7.0 mmol/L; 2-h postprandial blood glucose is ≥11.1 mmol/L; and glycated hemoglobin is ≥6.5%, with the use of hypoglycemic medication, an individual can be diagnosed with diabetes if they meet any of the above criteria.
Blood samples were collected at the start of follow-up to obtain values for monocytes, lymphocytes, platelets, and neutrophils. Based on these values, we calculated the following inflammation-related markers: lymphocyte-to-monocyte ratio (LMR) and systemic immune-inflammation index (SII), which is calculated as platelet × neutrophil count divided by lymphocyte count; and neutrophil-tolymphocyte ratio (NLR) (15).
The National Death Index (NDI) database was utilized to associate the information of NHANES survey participants with their corresponding death records. This approach was confined to a designated range to ensure the attainment of precise mortality data for NHANES participants. The interval from the commencement of household interviews to either loss to follow-up or death was accounted for as the follow-up duration. The NDI database was employed to acquire the mortality status. Furthermore, the specific causes of death were ascertained as delineated by the International Classification of Diseases (ICD) 10.
Statistical analysis
In descriptive statistics, normal continuous variables were described using the mean (standard deviation, SD). Statistical differences were described using a t-test or analysis of variance.
Non-normal continuous variables were described using the median (interquartile range, IQR), and statistical differences were described using non-parametric tests. Categorical variables were described using frequency (represented as percentages), and statistical differences were described using the chi-square test. The Cox proportional hazards models were formulated to estimate hazard ratios (HRs) accompanied by 95% confidence intervals. Univariate and multivariate regression analyses were employed to evaluate the association between various determinants, notably broccoli intake frequency and the risks associated with all-cause and specific-cause mortality. A threshold of value of p of <0.05 was established for determining statistical significance. Data preprocessing and statistical evaluations were executed utilizing the intricate survey design module of the SPSS 25.0 (IBM) statistical software. Forest plots along with the correlation matrix were generated using R software version 4.2.3.
Baseline characteristics
Our study ultimately encompassed 5,556 adults aged 20 years and older who provided valid responses to the broccoli diet query in the NHANES Food Frequency Questionnaire. The sample included 2,743 males and 2,813 females. Detailed specifics can be found in Figure 1. During the follow-up period that ended on 31 December 2019, the overall count of deaths from all causes reached 1,405, which represented 25.3% of the total sample population. The causes of these deaths, categorized according to the ICD-10, were primarily distributed across seven categories: cardiovascular diseases, pulmonary and chronic respiratory diseases, renal diseases, malignant tumors, diabetes, accidents, and miscellaneous causes. These categories also include the following distribution: Cardiovascular disease was responsible for 504 deaths, representing 35.9% of the total deaths; malignant tumors accounted for 292 deaths, representing 20.7% of the total deaths; 107 deaths were due to pulmonary and chronic respiratory diseases, representing 7.6% of the total deaths; diabetes resulted in 49 deaths, totaling 3.5% of all deaths; renal diseases led to 36 deaths, representing 2.6% of total deaths; 38 deaths were caused by accidents, accounting for 2.7% of all deaths; and 379 deaths were attributed to miscellaneous causes, representing 27% of all deaths.
As shown in Table 1, an observed disparity in the frequency of broccoli consumption between the genders indicated a more prevalent intake among females than males. A variance in broccoli consumption frequency was also detected across racial demographics, with the non-Hispanic white population reported to have more frequent consumption compared to other races. Discrepancies in broccoli consumption frequency were apparent among distinct PIR groups. Those falling within the medium-range PIR category (PIR > 1-<4) exhibited greater frequency compared to both the low (≤1) and high PIR groups (≥4). Frequent broccoli consumers demonstrated a decreased frequency of consumption in smokers compared to non-smokers. This implies that smoking habits could potentially impinge on regular broccoli consumption. Among habitual broccoli consumers, individuals who regularly consumed alcohol were observed to consume broccoli with greater frequency than those who had ceased alcohol consumption or abstained from it altogether, suggesting that alcohol consumption may be linked to an increased frequency of broccoli consumption.
Univariate and multivariate analyses of factors associated with all-cause and cause-specific mortality risks
In this cohort, we analyzed a range of variables, including age, gender, race, poverty income ratio (PIR), education level, smoking Flowchart of the study and participants excluded from the study.
Association between broccoli consumption frequency and risks of all-cause and cause-specific mortality after model adjustment
Given the potential confounding effects of covariates on outcomes, we employed adjusted models to reassess the relationship between the frequency of broccoli consumption and the risks of all-cause mortality, as well as specific diseases such as cardiovascular mortality and cancer mortality. We employed three adjustment models to control for potential confounders. Model 1 was adjusted for age, gender, and race; Model 2 was adjusted for age, gender, race, PIR, education level, and BMI; and Model 3 was adjusted for age, gender, race, PIR, education level, BMI, smoking status, drinking status, history of hypertension, history of dyslipidemia, and history of diabetes. In the analysis of model-adjusted results regarding the association between broccoli consumption frequency and the risk of all-cause mortality, the rarely broccoli consumption group ("less than once a week") exhibited a mortality risk hazard ratio (HR) (95% confidence interval [CI]) of 0.700 (0.605-0.809) in Model 1, 0.785 (0.677-0.909) in Model 2, and 0.825 (0.711-0.957) in Model 3, compared to the reference group of individuals who never consume broccoli. For the sometimes broccoli consumption group ("1 to 2 times per week but less than 3 times per week"), the mortality risk HR (95% CI) was 0.577 (0.484-0.689) in Model 1 and 0.680 (0.568-0.815) in Model 2. The mortality risk HR (95% CI) for the often broccoli consumption group ("3 or more times per week") was 0.705 (0.555-0.895) in Model 1 and 0.723 (0.603-0.865) in Model 2 (Supplementary Figure S1).
In the analysis of model-adjusted results regarding the association between broccoli consumption frequency and the risk of cardiovascular mortality, the rarely broccoli consumption group ("less than once a week") exhibited a mortality risk hazard ratio (HR) (95% CI) of 0.688 (0.541-0.874) in Model 1 and 0.779 (0.611-0.995) in Model 2 compared to the reference group of individuals who never consume broccoli. For the sometimes broccoli consumption group ("1 to 2 times per week but less than 3 times per week"), the mortality risk hazard ratio (HR) (95% CI) was 0.522 (0.388-0.702) in Model 1, 0.619 (0.457-0.839) in Model 2, and 0.664 (0.490-0.900) in Model 3 (Supplementary Figure S2).
In the analysis of the model-adjusted results regarding the association between broccoli consumption frequency and cancer mortality risk, compared to the reference group of individuals who never consume broccoli, the rarely broccoli consumption group ("less than once a week") exhibited a mortality risk hazard ratio (HR) (95% CI) of 0.622 (0.461-0.838) in Model 1, 0.697 (0.515-0.944) in Model 2, and 0.716 (0.528-0.970) in Model 3. The sometimes broccoli consumption group ("1 to 2 times per week but less than 3 times per week") had a mortality risk HR (95% CI) of 0.587 (0.411-0.837) in Model 1. The often broccoli consumption group ("3 or more times per week") had a mortality risk HR (95% CI) of 0.599 (0.359-0.998) in Model 1 (Supplementary Figure S3).
Association between broccoli consumption frequency and all-cause mortality risk after model adjustment stratified by gender
The distribution of broccoli consumption frequency exhibited gender differences, as indicated in Table 1. Thus, we conducted gender-stratified analyses and adjusted for confounding factors to more precisely assess the relationship between broccoli consumption frequency and the risk of all-cause mortality in each gender population. Among men, individuals in the rarely broccoli consumption group ("less than once a week") had a hazard ratio (HR) (95% CI) of 0.650 (0.544-0.776) in Model 1 (adjusted for age, gender, and race), 0.719 (0.599-0.862) in Model 2 (adjusted for variables in Model 1 plus poverty income ratio, education level, and BMI), and 0.743 (0.619-0.892) in Model 3 (adjusted for variables in Models 1 and 2 plus smoking status, drinking status, history of hypertension, history of dyslipidemia, and history of diabetes) compared to those who never consumed broccoli. Among males, individuals who occasionally consumed broccoli ("1 to 2 times per week but less than 3 times per week") had a hazard ratio (HR) (95% CI) of 0.560 (0.445-0.705) in Model 1, 0.651 (0.514-0.825) in Model 2, and 0.657 (0.519-0.832) in Model 3. These findings suggest a more pronounced reduction in the risk of all-cause mortality among males who consume broccoli occasionally.
Among females, individuals in the sometimes broccoli consumption group ("1 to 2 times per week but less than 3 times per week") had a hazard ratio (HR) (95% CI) of 0.634 (0.473-0.849) in Model 1 and 0.742 (0.552-0.997) in Model 2 compared to those who never consumed broccoli. The HR (95% CI) of the often broccoli consumption group ("3 or more times per week") was 0.627 (0.431-0.913) in Model 1 and 0.678 (0.465-0.989) in Model 2. These findings suggest a more pronounced reduction in the risk of all-cause mortality among females who consume broccoli frequently. Additional information can be found in Supplementary Figure S4. Forest plot displaying the hazard ratios of all-cause mortality by multivariate Cox regression analysis (By R 4.2.3).
Association between broccoli consumption frequency and inflammation markers
To investigate the relationship between the frequency of broccoli consumption and inflammation markers, we conducted a correlation analysis using a correlation matrix. The results revealed that the correlation coefficient between broccoli consumption frequency and NLR was −0.032, p = 0.017; the correlation coefficient between broccoli consumption frequency and LMR was 0.025, p = 0.063; and the correlation coefficient between broccoli consumption frequency and SII was −0.016, p = 0.248. These findings suggest a negative correlation between broccoli consumption frequency and NLR. More specific details can be seen in Figure 5.
Discussion
The results of this study show that, compared with those who never eat broccoli, participants who consumed broccoli at different frequencies had significantly lower all-cause mortality risks, showing a negative correlation trend, which is consistent with the results of previous meta-analyses on fruit and vegetable intake and mortality risk (16). Specifically, eating broccoli 1-2 times per week can reduce all-cause mortality risk by 32-43%. In addition, broccoli intake frequency was negatively correlated with cardiovascular mortality and cancer mortality. Considering that different genders may respond differently to broccoli intake, we conducted stratified analysis by gender and found that, compared with females, males were more inclined to eat broccoli 1-2 times per week, while females were more inclined to eat broccoli ≥3 times per week to obtain the effect of reducing all-cause mortality. Finally, we found that broccoli intake frequency was negatively correlated with the inflammatory marker NLR. Overall, this study determined a dose-response relationship between broccoli intake frequency and reduced risks of all-cause and cause-specific mortality, providing a basis for developing scientific dietary guidelines.
Our findings are validated by several previous large-scale studies, two of which were conducted in Asia, demonstrating that cruciferous vegetables can enhance cardiovascular health and reduce mortality risk. Several prospective studies have indicated that high fruit and vegetable consumption does not necessarily correlate with reduced cancer incidence. Therefore, we further explored the potential mechanisms through which consuming broccoli may lower the risk of mortality, taking into account its anti-inflammatory and antioxidant properties, its role in modulating lipid metabolism, and its influence on blood glucose homeostasis.
Broccoli contains abundant direct antioxidant nutrients such as vitamin C, carotenoids, and anthocyanins (7), which can eliminate excessive active oxygen-free radicals and inhibit oxidative stress in the body. In addition, sulfur-containing phytochemicals are unique bioactive components in broccoli, such as glucosinolate, which can exert anti-inflammatory effects by inhibiting the production and release of inflammatory factors (17), as well as by protecting the body from inflammatory damage by stimulating the production of antioxidant enzymes (18). Substantial evidence indicates that chronic Potential mechanisms of broccoli intake in reducing mortality risk (By Figdraw).
inflammation and oxidative stress play important roles in the pathogenesis of various chronic diseases, including cancers, cardiovascular diseases, and type 2 diabetes (19). Chronic inflammation can lead to the release of additional cytokines and growth factors, stimulating angiogenesis and cell proliferation, degrading extracellular matrix enzymes, and providing an advantageous environment for tumor growth (20). Moreover, chronic inflammation can also result in endothelial cell oxidative stress, promote platelet activation, cause endothelial cell damage, and can be considered a key driving factor in the development of cardiovascular diseases (8). Therefore, the abundant anti-inflammatory and antioxidant components in broccoli may be important nutritional mechanisms for its beneficial effects against chronic diseases. Broccoli contains abundant vitamin K1, which is a fat-soluble vitamin that can promote the generation of clotting factors and inhibit the synthesis and secretion of cholesterol in the liver (21). In addition, minerals in broccoli, such as magnesium, can also reduce cholesterol absorption. The flavonoids abundant in broccoli are believed to have the ability to scavenge free radicals and accelerate cholesterol breakdown (22). The rich dietary fiber, especially the soluble mucilaginous dietary fiber in broccoli, can bind with bile acids to form insoluble complexes, increasing bile acid excretion in feces and thus reducing bile acid reabsorption and decreasing cholesterol synthesis in the body (23). By regulating lipid metabolism, broccoli may reduce the incidence of cardiovascular disease.
The rich dietary fiber, especially water-soluble fiber in broccoli, can prolong the retention time of food in the gastrointestinal tract and slow down the digestion and absorption of carbohydrates, thereby inhibiting drastic fluctuations in postprandial blood glucose and insulin levels (24). In addition, sulforaphane in broccoli can also promote insulin signal transduction in skeletal muscle and liver tissues, enhancing insulin sensitivity in insulin-resistant tissues and thus lowering blood glucose (25). The high content of vitamin C in broccoli is capable of protecting pancreatic beta cells from oxidative stress damage. Adequate intake of broccoli helps maintain the functionality of pancreatic beta cells, preventing insufficient insulin secretion due to pancreatic cell injury and thus stabilizing blood glucose regulation (22). By regulating glucose and lipid metabolism and enhancing insulin sensitivity, broccoli can reduce the risks of metabolic syndrome, type 2 diabetes, and cardiovascular diseases. The mechanism of broccoli intake in reducing mortality risk, as illustrated above, can be seen in Figure 6.
This study found that, compared with females, males were more suitable to eat broccoli 1-2 times per week, while females were more suitable to eat broccoli ≥3 times per week to obtain the effect of reducing all-cause mortality. This may be related to gender differences in dietary patterns and physiological metabolism. On the one hand, the intake of fruits and vegetables is inherently higher in females' diets (26), so they may need to eat broccoli more frequently to produce significant health effects. On the other hand, increased estrogen levels can promote the expression of glutathione peroxidase, enhancing the body's antioxidant capacity (27), which may make females require higher amounts of antioxidant nutrients in broccoli. Overall, there may be some differences in the optimal frequency of broccoli intake between different genders, which should be further clarified in future studies to provide a basis for dietary guidance for both genders.
This study determined the dose-response relationship between broccoli intake frequency and reduced mortality risk in a large sample population, providing an important basis for developing scientific dietary guidelines. However, as an observational study, it cannot demonstrate a direct causal relationship between broccoli and mortality risk reduction. In addition, considering that the participants were all American adults, there may be some differences between different ethnicities, so the research conclusions should be generalized with caution. Finally, FFQ assessments of dietary intake have some subjectivity and may be subject to recall bias. Future rigorous clinical trials are still needed to verify the health effects of broccoli consumption and determine appropriate intake ranges based on different populations in order to provide more rigorous evidence for formulating dietary guidelines.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
FIGURE 5
FIGURE 5Correlation matrix plot describing the frequency of broccoli consumption and inflammatory markers (By R 4.2.3).
TABLE 1
Baseline characteristic variables according to the broccoli consumption frequency.indicatorsidentified in the univariate analysis remain significantly associated with the risk of all-cause mortality. Specific details can be seen in Figure2. The univariate Cox proportional hazards regression model identified 11 indicators that were significantly associated with the risk of cardiovascular mortality. These indicators include age, gender, race, PIR, education level, smoking status, drinking status, history of hypertension, history of dyslipidemia, history of diabetes, and broccoli consumption frequency. The multivariate Cox proportional hazards regression model confirmed that nine indicators remained significantly associated with the risk of cardiovascular mortality. These indicators include age, gender, race, PIR, education level, smoking status, history of hypertension, history of diabetes, and broccoli consumption frequency. The univariate Cox proportional hazards regression model revealed that 10 indicators were significantly associated with the risk of cancer mortality. These indicators include age, gender, race, PIR, education level, smoking status, drinking status, history of hypertension, history of diabetes, and broccoli consumption frequency. The multivariate Cox proportional hazards regression model demonstrated that eight indicators remained significantly associated with the risk of cancer mortality. These indicators include age, race, PIR, education level, history of hypertension, history of dyslipidemia, broccoli consumption frequency, and BMI. Specific details can be seen in Figures 3, 4.
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Domain: Agricultural and Food Sciences
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Changes in physicochemical and conformational properties of myofibrillar proteins isolated from mandarin fish (Siniperca chuatsi) treated by atmospheric pressure plasma jet
ABSTRACT The effects of atmospheric pressure plasma jet (APPJ) treatment on the physicochemical and conformational properties of myofibrillar protein (MP) isolated from mandarin fish. The findings revealed that after exposing MP to APPJ for 0–12 s, there was a significant (P < .05) decline in the solubility and total sulfhydryl concentration. Turbidity and surface hydrophobicity increased significantly, while pH value decreased significantly at first but then stabilized. Gel electrophoresis confirmed that the extracted protein was unaffected. FTIR spectroscopy indicated that the APPJ treatment caused slight changes in secondary structure. However, the UV absorption spectral and intrinsic tryptophan fluorescence demonstrated that the tertiary structure of MP was altered following APPJ treatment. According to the rheological characteristics, APPJ treatment could improve protein cross-linking, raise storage modulus, and promote the development of protein gel network structure. These findings demonstrated that APPJ treatment might improve the functional characteristics of MP isolated from mandarin fish. GRAPHICAL ABSTRACT
Introduction
Mandarin fish (Siniperca chuatsi) is a traditional high-valued fish and widely distributed in China, Korea, Vietnam and other East Asian countries (C. Sun et al., 2017). Mandarin fish is highly consumed for its delicate taste and hard texture. Currently, the mandarin fish is a lucrative species of fish that is actively farmed in China, with an annual production of over 370,000 tons in 2022. Therefore, the development of mandarin fish propagation and processing methods is receiving much attention (J. Liu et al., 1998;C. F. Sun et al., 2015). The main component of mandarin fish protein is myofibrillar protein (MP) which accounts for approximately 55-60% of the total protein (Lin et al., 2020). The rheological and heat-induced gelling properties of the meat are affected by the functional characteristics of MP (Niu et al., 2018), which are influenced by pH, temperature, ionic strength, and treatment methods such as high pressure (LeBail et al., 2002), high-voltage electrostatic field (Jia et al., 2018), radio frequency (Bedane et al., 2017), ultrasound (Cai et al., 2018), vacuum and microwave (Wang et al., 2020). Typically, various treatment techniques have the potential to alter the protein's physicochemical and structural properties, as well as its functional qualities (F. Li et al., 2019). Therefore, it is necessary to find an effective processing method that can improve the quality of mandarin fish MP and promote the development of the mandarin fish industry.
Plasma is a unionized gas made up of a variety of reactive components such as electrons and photons (Lu et al., 2016), which can disrupt covalent bonds of protein, resulting in structural and physicochemical changes. Cold plasma has been used for sterilization (Kang et al., 2022;J. Wang et al., 2021), thawing (Liao et al., 2020), and food preservation (Chaijan et al., 2021) as a novel non-thermal technology. Cold plasma is generated by atmospheric pressure gas discharge, including atmospheric pressure plasma jet (APPJ), dielectric barrier discharge (DBD), and radio frequency discharge (RFD). Several studies have recently been carried out to ascertain the effects of cold plasma on meat components and quality, including modifications in lipids and proteins (Luo et al., 2022). Cold plasma was observed to improve the functional features of MP from king prawns (Ekezie et al., 2019) through enhanced protein-water and protein-protein interactions. Furthermore, Miao et al. (2020) showed that the gel features of MP in Alaska Pollock may be greatly enhanced by cold plasma (40 kV).
Despite the vast research on microbial decontamination by cold plasma, modification of MP from fish by APPJ has not been reported. In order to explore the interaction of cold plasma on the myofibrillar protein of mandarin fish, the effects of APPJ on the physicochemical and conformational features of MP from mandarin fish was studied. The pH, protein solubility, turbidity, dynamic rheological, primary and secondary structure, surface hydrophobicity, total sulfhydryl content, UV absorption spectra, and fluorescence scan spectra were measured. The findings of this research will aid APPJ in more effectively processing fish products, as well as create the theoretical framework for the development of new products and the optimization of APPJ processing for the fish industry.
Materials
Fresh mandarin fishes (about 500 g and 12 months old) were acquired from a local supermarket (Hema Fresh supermarket, Hangzhou, China). Upon arrival, the fish muscles were washed with pre-cooled distilled water. Trunk muscles of fish were cut off and divided into small pieces. The muscles were kept in refrigerator (4°C) until protein preparation.
Preparation of MP
MP was isolated from mandarin fish as previously described by K. Li et al. (2020) with minor changes. First, the trunk muscles were homogenized by blending at 10,000 rpm for 60 s with 5 volumes (w/v) of pre-cooled 20 mM Tris-HCl buffer solution (pH 7.0) in a blender (POLYTRON ® PT6100D, Kinematica AG, Malters, Switzerland). The supernatant was removed after centrifugation at 4000 × g for 15 min (4°C) using a high-speed refrigerated centrifuge (3K15, Sigma, Osterode am Harz, Germany). The above process was repeated three times. After that, the precipitate was further washed three consecutive times with 5 volumes (w/v) of precooled 0.1 M NaCl solution under the same conditions. The suspension was filtered through 40 mesh strainer to get rid of connective tissue. Afterwards, the filtrate was further centrifuged (4000 × g for 15 min at 4°C), then the pellet was collected and dissolved in pre-cooled 0.6 M NaCl solution. The biuret method was used to calculate the concentration of MP solution in the solution.
APPJ treatment
The atmospheric pressure plasma jet (APPJ, Tonson Tech Automation Equipment Co., LtD., Shenzhen, China) was used to treat the MP solution in this experiment. The equipment consisted of a high-pressure generator (power of 650 W), an air compressor, and a rotating plasma discharge nozzle (Figure 1). For APPJ treatment, 30 mL of MP solution (2.5 mg/mL) isolated from mandarin fish was transferred into a 250 mL glass beaker (6.5 cm × 9.5 cm) with about 1 cm depth, which was placed on crushed ice to keep the sample at a low temperature during processing. The MP solution was discharged by plasma for 0-12 s with 2 s intervals.
Determination of pH value
Samples were equilibrated to room temperature, then a pH meter (PB-10, Beijing Cedis Scientific Instruments Co., Ltd, Beijing, China) was used to measure the pH value of untreated and treated MP solutions and repeated at least three times.
Determination of protein solubility and turbidity
The solubility of MP was determined according to K. Li et al. (2019) with some minor modification. Untreated and treated MP solutions were centrifuged at 5000 × g (4°C, 10 min). Protein solubility was calculated as a ratio of the concentration in the supernatant to the concentration of protein before treatment.
The turbidity of treated and untreated MP solution by APPJ was determined according to F. Li et al. (2019) with some modifications. The absorbance of each sample (2.5 mg/mL) at 660 nm (UV-2600, Shimadzu Co., Kyoto, Japan) was measured a minimum of 3 times used.
Dynamic rheological analysis
A rheometer (Physica MCR 302, Anton Paar, Graz, Austria) with a parallel plate of 25 mm diameter was used to measure the dynamic rheological properties of MP with the temperature increased from 25 to 80°C at a scan rate of 5°C/min, the linear viscoelastic region (LVR) was determined by strain scanning testing, as described previously by K. Li et al. (2019).
SDS-PAGE
The molecular weight of MP following APPJ treatment was determined using gel electrophoresis (SDS-PAGE) in accordance with J. Qian et al. (2021a) with some adjustments. A volume of 20 μL of MP sample was mixed with 5 μL of protein sample loading buffer (5×), then placed in a boiling water bath (100°C) for 3 min. The SDS-PAGE was performed using 4-12% Bis-tris gradient gel (Nanjing ACE Biotechnology CO., Ltd., Nanjing, China), using molecular weights (MWs) of 6.5-240 kDa as the molecular weight standard (Shanghai Beyotime Biotechnology CO., Ltd., Shanghai, China). Protein samples were concentrated for 30 min at 80 V before being switched to 120 V until the bands reached the bottom of the gel. The gel was carefully removed and stained for 4 h using 0.1% coomassie brilliant blue R-250 on a horizontal mixer (Qiwei Instrument Co., Ltd, Hangzhou, China), then unstained for approximately 12 h using deionized water containing 5% ethanol and 7.5% acetic acid on a horizontal shaker.
Fourier transform infrared spectrometer
The MP solution was dried for 24 h in a freeze-dried (SCIENTZ-10N, Ningbo SCIENTZ biotechnology CO. LTD., Ningbo, China). The freeze-dried MP powder was ground in an agate mortar with dried KBr powder before being pressed into a slice. The spectra of sample were recorded from 4000 to 400 cm −1 by an infrared spectrometer (iS50, Thermo Fisher Scientific, Waltham, MA, U. S. A.). Peakfit software (v4.12,SPSS Inc., Chicago,IL, U. S. A.) was used to fit the Gaussian curve of second-derivative peak at 1700-1600 cm −1 (amide Ι) to obtain the information about secondary structure of protein as previously described by K. Li et al. (2020).
Determination of surface hydrophobicity
The surface hydrophobicity of MP was determined according to X. Zhao et al. (2017) with some modifications. An aliquot of 1 mL of MP suspension and 100 μL of bromophenol blue (BPB, 1 mg/mL) were combined. After centrifuging (10000 × g for 5 min), the supernatant was five-fold diluted. The absorbance of the mixture was measured at 595 nm (UV-2600, Shimadzu Co., Kyoto, Japan) and the 0.6 M NaCl buffer without MP was the blank.
Determination of total sulfhydryl content
The total sulfhydryl content (T-SH) was calculated as described by Feng et al. (2017) with slight changes. A volume of 40 μL of Ellman's reagent (DTNB) was added to a mixture of 1 mL MP solution and 4 mL Tris-Glycine buffer (pH 8.0), then incubated for 30 min in the dark.
Absorbance was measured at 412 nm with 0.6 M NaCl as the blank. The T-SH was expressed as µmol/g protein.
Fluorescence measurement
The measurement of fluorescence emission spectrum of MP sample was measured by the method of X. Zhao et al. (2018) using a fluorescence spectrophotometer (Infinite E Plex, Tecan Austria GmbH, Grödig, Austria). The fluorescence intensity of the MP sample was determined at an excitation wavelength of 280 nm and an emission wavelength of 300-400 nm, accompanied by a slit width of 2 nm. The emission spectra of all samples was subtracted from that of the buffer solution.
UV absorption spectral analysis
The ultraviolet-visible spectrophotometer (UV-2600, Shimadzu Co., Kyoto, Japan) was used to scan the UV spectrum of untreated and treated MP solution. The spectrum was scanned at medium speed and ranged from 250 to 350 nm (Ekezie et al., 2019).
Statistical analysis
SPSS statistical software (SPSS Statistical 22, International Business Machines Co., Armonk, NY, U. S. A.) was used to analyze significant differences in MP of APPJ treatment based on Duncan's multiple range test from the single component analysis of variance (ANOVA), with P < .05considered significant.
Changes in pH
Figure 2a shows the pH values of MP suspensions with different APPJ treatment times. There was a significant decrease (P < .05)from an initial pH of 6.76 ± 0.07 to 5.56 ± 0.015 when the exposure time was increased from 0 to 8 s. After 8 s, the variations in pH value were insignificant (P > .05). The non-covalent bond equilibrium in the polypeptide structure was disturbed when pH value of the solution was close to the isoelectric point (IP) of MP (about pH 5.0-5.2),which caused increased hydrophobic interaction and reduced solubility. These findings corroborated with the trend of MP solubility, turbidity, and surface hydrophobicity.(showed in Figures 2a,b and 6a). Acidification in the MP solution treated by APPJ could be due to the formation of acidic H 3 O + by the reaction of H 2 O 2 with H 2 O in the air or liquid as well as the generation of HNO 2 and HNO 3 from NO and NO 2 (Traylor et al., 2011). Sharifian et al. (2019) found that there was no substantial reduction in pH of MP (solubilized in PBS) before and after treatment by DBD. In the study of Segat et al. (2015), there was a similar tendency, a slight decrease in pH value before 15 min of treatment using PBS as buffer. Other studies reported by Oehmigen et al. (2010) and Y. M. Zhao et al. (2020) found that pH of PBS did not change much with the control while a strong reduction in pH in distilled water or physiological saline was found when using the same plasma treatment conditions. Several factors may contribute to changes in the acidity of plasma treated liquids, including the buffering capacity, the volume treated, sample concentration in solution, as well as the inducer gas employed and type of plasma source.
Changes in protein solubility and turbidity
Solubility is an important property of proteins, in which water molecules and protein interact via amino acid side chains (polar, non-polar group and ionization interactions) or peptide bonds (hydrogen bond or dipole-dipole interactions), as it may influence other functional properties (K. Li et al., 2019;S. Li et al., 2018). Figure 2b shows a significant decrease of protein solubility as exposure time increased (P < .05). The protein solubility decreased to 35.73 ± 0.34% and 17.72 ± 0.07% when the APPJ treatment times were 10 s and 12 s, respectively. When put the treated MP suspension in refrigerator for a period of time, protein aggregation could be clearly seen at the bottom of the tube after 10 s of treatment time (Figure 2d). When the solution was treated by APPJ, some oxidizing active substance (RONS) would be generated in the solution (Hu et al., 2021), which may oxidize the active sulfhydryl groups to form disulfide bonds, and cross-linked to form protein polymers. In addition, the pH value of MP solution gradually approached the IP, which also promoted the hydrophobic reaction and precipitation of MP. The secondary and tertiary structures of the protein were extended by changes in the microenvironment and oxidation, exposing substantial sections of the hydrophobic groups that were previously buried in the core of the protein with the folded form. These hydrophobic group interactions led to protein aggregation and precipitation, lowering protein solubility relative to the untreated protein (Bußler et al., 2016).
The turbidity was determined through the absorbance value at 660 nm, which can reflect the aggregation state of protein treated by APPJ. The turbidity value of APPJ-treated MP solution was significantly increased (P < .05)from 0.405 ± 0.003 to 0.995 ± 0.003 with the APPJ treatment times increasing from 0 to 12 s (Figure 2c). The turbidity increased due to the unfolding and polymerization of MP molecules, large protein aggregates were produced, which may obstruct light transmission and generate light scattering (D. Jia et al., 2015). These results were also consistent with the tendency obtained for the protein solubility treated with APPJ (Figure 2b).
Changes in dynamic rheological property
Rheological property is one of the most significant functional characteristics of protein, mainly affected by molecular weight and structure. The elastic property of protein is expressed as storage modulus (G´), whereas the viscosity property is expressed as the loss modulus (G") (Zhang et al., 2017). So rheological properties are usually used to describe the changes of protein during thermal coagulation. As seen in Figure 3, untreated MP exhibited a typical rheological graph with transitions between heavy and light meromyosin. There was a small peak, when the temperature increased from 30°C to 54°C. From 54 to 62°C, the G´ and G" decreased slightly and then displayed a steady increase over 62 to 80°C. Chen et al. (2016) also obtained a similar rheological pattern.
The G´ value changes in all of the samples were similar, the G´ values began to gradually increase from the onset temperature until the temperature reached 80°C after exposure to plasma. The onset temperature of G´ of treated MP was lower than untreated, and the "peak" became inconspicuous. The "peak" G" values of all treated samples were greater than that of untreated sample after exposure to plasma from 2 to 8 s, but lower than that of untreated sample when the MP was exposed to plasma for 10 s and 12 s. It was easy to find that the G´ and G' values were maximum at 2 s of treatment time, then decreased when treatment time increased. The G´ and G' values at 2-6 s were higher than those of untreated MP, demonstrating that mild oxidation was advantageous to promote the generation of gel network structure of MP, and expressed by the storage modulus value which was higher than that of untreated sample (Xiong et al., 2010). The increase in gel strength might be due to changes in the cross-linking pattern of MP. Myosin tail disulfide bond crosslinking under oxidized conditions was more stable than myosin head and head crosslinking under non-oxidized conditions, which could promote a more stable gel structure for MP.
The G´ and G" values decreased as treatment time increased, due to excessive oxidation of protein, which caused protein denaturation and aggregation, reducing the MP interaction. Furthermore, oxidation mediated by APPJ, particularly when treating for a longer duration, may induce MP cleavage, resulting in the creation of short chain polypeptides that cannot interact efficiently as evidenced, and the gel formation ability was poor.
During the gel formation heating process, G" value was lower than G´ value, reflecting that elasticity was more important compared with viscosity during the MP gel formation. The results indicated that APPJ treatment could enhance cross-linking of MP: however, it is necessary to control the treatment time to prevent excessive oxidation of protein.
SDS-PAGE analysis
SDS-PAGE was carried out to measure the effect of APPJ treatment times on the molecular weight of MP in mandarin fish (Figure 4). The characteristic bands of MP were seen in all samples. Once the MP was treated by different discharge times, there were no disappearance of original protein feature bands and no appearance of new protein feature bands, demonstrating that no remarkable changes were found in the treated MP compared with the control. The comparable expression of MP indicated that there was no change in protein patterns after APPJ treatment or that the influence of APPJ treated on the MP was not visible in the electrophoresis. J. Qian et al. (2021b) also showed that plasmaactivated water (PAW) did not change the characteristic bands of MP in chicken breasts. The changes in T-SH (showed in Figure 6b) may imply the formation of disulphide bonds as a result of SH group recombination or reactive species attachment, however this changes were not visible in the electrophoresis. The FTIR spectrum of MP also depicted that the feature peaks of all proteins treated by different APPJ treatment times were consistent, as seen in Figure 5a.
FTIR analysis
Figure 5a shows the corresponding FTIR spectra for MP in mandarin fish after various APPJ treatment times compared with the control. The structure remained intact after APPJ treatment, and there was no evidence of new distinctive peaks appearing or the elimination of characteristic peaks. Among the IR characteristic absorption peaks of protein, Amide Ι band (1600-1700 cm −1 ) is most frequently used for analyzing the protein secondary structure (Huson et al., 2011). As shown in Figure 5b, different plasma treatment times slightly affected the secondary structure of MP in mandarin fish. The percentage of α-helix was increased slightly with the increasing of treatment time. For the 2-s-treated group, the percentage of α-helix reached a high of 19.34%. Dong et al. (2017) observed comparable changes, with the proportion of α-helix of zein in corn increasing after a brief period of atmospheric cold plasma (ACP) treatment. Compared with the untreated group, the proportion of βsheet was significantly (P < .05)increased, and the proportion of random coils were significantly (P < .05)decreased after treatment. As treatment time increased, there was a slight increase in the concentration of α-helix and a slight decline in the concentration of β-turn. The concentration of β-sheet in MP increased from 26.58 to 34.48%, and the proportion of random coils declined from 18.34 to 12.27%. The hydrogen bonds that are formed in the peptide chain between NH-and C=O were changed by APPJ treatment, inducing slight changes in each component of secondary structure. The disulfide bond was generally generated around the β-turn, there was a similar decreasing trend of sulfhydryl content to the content of β-turn (Figure 6b). In addition, it was known that α-helix was a stretchy and tough component in secondary construction. The enhancement of this section may help MP in mandarin fish having a better gel property. This observation was similar to the rheological properties (Figure 3).
Changes in total sulfhydryl content and protein surface hydrophobicity
The changes of T-SH can reflect the distribution of hydrophobic residues on the protein surface (J. Jia et al., 2017). Protein functionality benefits from an appropriate balance of non-hydrophobic and hydrophobic residue (G. Jia et al., 2017). As showed in Figure 6a, the surface hydrophobicity of MP treated with APPJ showed a significant (P < .05)increased from 17.84 ± 1.78 to 62.00 ± 1.68 μg before 6 s of treatment (P < .05)compared to the control, and a minor increase in surface hydrophobicity value after 6 s of treatment time. The plasma treatment improved the surface hydrophobicity of MP in mandarin fish by exposing hydrophobic amino acids such as tryptophan and phenylalanine (Ekezie et al., 2019). Plasma discharge treatment can produce a lot of oxidizing reactive species, which may cause the oxidation of protein and improve the surface hydrophobicity. When protein solutions were over-oxidized, the interactions of protein-protein were enhanced which caused the protein denaturation. In addition, the decrease in pH also improved the hydrophobic reaction between proteins and increased the surface hydrophobicity of MP. These results were consistent with the solubility results obtained and the phenomenon of protein stratification as can be seen in the Figure 2d.
The transformation between disulfide linkage and SH groups can be used to determine the change in protein structure (Ekezie et al., 2019). The SH group which belong to weak secondary bonds, maintains the tertiary structure of protein. The changing degree of tertiary and quaternary structure can be calculated from the change of SH content (Zhang et al., 2017). Figure 6b shows the T-SH of MP in mandarin fish exposed to APPJ at various treatment times. A significant (P < .05)decline in T-SH from 15.03 ± 0.11 to 11.28 ± 0.20 μmol/g after 12 s (P < .05)was observed. This finding was consistent with a previous study of Dong et al. (2017) and Ji et al. (2017), where the T-SH content declined with an increase in exposure time. The T-SH decline may be caused by protein oxidation which was triggered by the attack of oxidizing reactive species (Leygonie et al., 2012). Previous research showed that the formation of disulfide bonds caused the reduction of T-SH content in the oxidation system (Chelh et al., 2006;Y. Li et al., 2013). Comprehensively, APPJ treatment altered the tertiary and quaternary structure of MP molecules, exposing internal SH groups and hydrophobic groups, and strengthening the generation of disulfide bonds and surface hydrophobicity, which was attributable to protein-protein interactions.
Changes in fluorescence and UV visible spectroscopy
Figure 7a shows the effects of plasma on aromatic amino acid residues in MP from mandarin fish. The UV absorption curve of natural MP showed a main absorption peak inside the ultraviolet region at 276 nm, which was similar with the study reported by Ekezie et al. (2019) for MP in king prawns. It is a typical protein peak (close to 280 nm) including aromatic amino acids, which are most likely linked to the vibration of the tyrosine (Tyr) and tryptophan (Trp) residues, and are the key factors for the UV absorption with peaks near 277 nm and 285 nm, respectively (C. Sun et al., 2016). It could be seen that APPJ treatment significantly (P < .05)increased the UV absorbance intensity compared with natural MP, especially during the treatment time of 12 s, which demonstrated the highest absorption value. The increase in absorption intensity revealed a change in MP structure. The changes in fluorescence intensity of MP after exposed to APPJ revealed that a piece of the chromophore rotated to outside, allowing more Tyr and Trp residues to be exposed.
Intrinsic Trp fluorescence properties, which are an important sign of a protein's tertiary structure, are especially sensitive to the Trp microenvironment (Cao & Xiong, 2015). When the Trp residues are buried in the core (a hydrophobic environment) of the protein in its folded state, the intrinsic fluorescence intensity is strong (Cai et al., 2018). As shown in Figure 7b, the Trp fluorescence intensity of APPJ-treated MP exhibited a remarkable decline compared with the control, indicating that protein unfolding was attributed to APPJinduced oxidation of Trp and protein aggregation. Simultaneously, the maximum emission wavelength (λ max) of MP solution increased from 334 to 340 nm, with the increase of treatment time from 0 to 12 s. the slight redshift of λ max demonstrated that the plasma treatment unfolded the tertiary conformation of MP, and promoted the exposure of more aromatic acids to the polar environment. Ekezie et al. (2019) indicated that MP in king prawn was treated by plasma leading to a slight redshift from 333 to 336 nm of λ max, which indicated a certain extent of unfolding of protein. Q. Liu et al. (2015) discovered that with the increased degree of hydroxyl radical-induced oxidation, hydrophobic groups were exposed, which induced the formation of protein aggregation because of hydrophobic interactions. Therefore, APPJ-induced change of tertiary structure in MP extracted from mandarin fish can be understood as follows: APPJ-induced oxidation treatment remarkably increases the range of exposed hydrophobic domains attributed to protein partial unfolding and cross-linking hydrophobic interactions, which leads to MP aggregation.
Conclusion
APPJ treatment decreased pH due to the generation of acidic H 3 O + ions, HNO 2 , and HNO 3 in the solution. In addition, plasma treatment could enhance the aggregation of intermolecular proteins, increasing turbidity, precipitating the protein, and decreasing the solubility of protein. The fundamental structure of MP was unaffected, while APPJ treatment changed the secondary structure which increased the ordered structure. As the processing time of plasma increased, the hydrophobicity and maximum UV absorption intensity increased, while the total sulfhydryl content and fluorescence intensity decreased. This is because plasma treatment could unfold MP molecules exposing interior SH groups and hydrophobic groups, increase the generation of disulfide bonds and surface hydrophobicity, and change the tertiary and quaternary structure of MP molecules. In brief, moderate APPJ treatment could accelerate MP oxidation, boost the development of gel network structure of MP, and improve its functional characteristics. Finally, when APPJ technology is used for processing aquatic meat products in the future, the prevention of over-oxidation of MP in fish or other aquatic products should be considered.
Figure 1 .
Figure 1. A schematic representation of APPJ used to treat MP extracted from Siniperca chuatsi. The equipment consists of a high-pressure generator (the power is 650 W), an air compressor, and a rotating plasma discharge nozzle.
Figure 2 .
Figure 2. Changes in the physicochemical parameters of MP from Siniperca chuatsitr untreated and treated with APPJ.(a) pH, (b) Tolubility, (c) Turbidity, (d) MP sample treated by APPJ for 6-12 s. The results are expressed as X � σ n ¼ 3 ð Þ ,with various letters on the top of the bar chart indicating significant differences (P < .05).
Figure 3 .
Figure 3. Influences of APPJ treatment on (a) Storage modulus (G´) Of mandarin fish MP, (b) Loss modulus (G") Of mandarin fish MP.
Figure 5 .
Figure 5. (a) FTIR spectra of MP by different APPJ treatment times; (b) Effects in secondary structure content of MP by different APPJ treatment times.
Figure 6 .
Figure 6.(a) Influences of APPJ treatment on the surface hydrophobicity of mandarin fish MP, (b) Influences of APPJ treatment on the total sulfhydryl content of mandarin fish MP. The findings are expressed as X � σ n ¼ 3 ð Þ, with various letters on the top of the bars indicating significant differences (P < .05).
Figure 7 .
Figure 7. (a) UV absorption spectra of MP from mandarin fish exposed to different APPJ treatment times, (b) Intrinsic emission fluorescence spectra of MP from mandarin fish exposed to different APPJ treatment times.
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Domain: Agricultural and Food Sciences
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Genetic variation, genetic advance, heritability and correlation analysis of phenotypic traits in tetraploid wheat (Triticum turgidum spp.) landraces and some improved cultivars of Ethiopia
Abstract Tetraploid wheat species from Ethiopia hold ample genetic variation, which could provide a source for improvement of wheat. A total of 196 Ethiopian tetraploid wheat (Triticum turgidum spp.) accessions, including 174 landraces and 22 improved cultivars, were evaluated at Sinana and Debrezeit to assess morphological variation, genetic advance, heritability and correlation based on 11 phenotypic traits. Except for spike length, highly significant variation (P < 0.001) among genotypes for all traits was observed. The observed mean and range values of the phenotypic traits revealed high variability in the accessions. Phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) values were high for grain yield, biomass yield and harvest index. Seed yield showed highly significant (P < 0.001) negative correlation with days to booting and days to maturity and positive correlation with all traits. The estimates of heritability (H2) for grain yield and the number of spikelets per spike respectively ranged from 41.78 to 84.62%. The genetic advance as a percentage of mean was low for the number of seeds per spikelet, days to booting and days to maturity; intermediate for plant height, thousand kernel weight and spike length and high for the number of spikelets per spike, the number of effective tillers per plant, grain yield, biomass yield and harvest index, respectively. The number of spikelets per spike gave a high value of genetic advance and heritability implying high genetic gain from its selection.
Introduction
Wheat is a commodity with a high market value that generates income for farmers in Ethiopia, the largest wheat producer in sub-Saharan Africa. Two types of wheat are predominantly grown in Ethiopia: tetraploid wheat, indigenous to the country, and hexaploid wheat, a recent introduction to the country (Getachew and Worede, 1991;Alamerew et al., 2004). The majority of tetraploid wheat species grown by farmers are mixtures of landraces varying in botanical and morphological features. For millennia, farmers have preferred to grow mixtures of tetraploid wheat landraces to add variety to their diet and to reduce the risks of losses due to new disease or pest outbreaks or due to unusual environmental conditions (Pecetti and Damania, 1996) because of useful alleles they possess as compared to hexaploid wheat. Ethiopia is a centre of diversity for the cultivated tetraploid wheat (2n = 4x = 28) (Vavilov, 1929;Abate, 2018;Brasesco et al., 2019). Despite this potential, Ethiopia remains a net importer of wheat due to the huge gap between production and consumption (Abate, 2018;Brasesco et al., 2019) emanating from very low national yield (Haile et al., 2013a(Haile et al., , 2013b) ) and increased demand for wheat (Zegeye et al., 2020). The mean productivity of wheat in Ethiopia is 3 tons per hectare (t/ha) (CSA 2021) which is below the attainable yield for the crop which can be up to 5 t/ha (Alemu et al., 2019;Zegeye et al., 2020;Nigus et al., 2022). Hence, low productivity continues to be the major challenge facing wheat production in Ethiopia (Alemu et al., 2019). Accordingly, continuous enhancement of wheat yield is crucially needed. This necessitates the development of wheat varieties that are high yielding with the required quality and are stable under biotic and abiotic stresses. This requires a continuous supply of new germplasm as a source of desirable genes and gene variants (Asmamaw et al., 2019) for which tetraploid wheat landraces are a valuable source.
Tetraploid wheat has been under cultivation in Ethiopia for thousands of years and has acquired a diverse set of characteristics and enormous genetic variability. However, the diversity present in tetraploid wheat through domestication has not been fully evaluated (Negisho et al., 2021). Landraces are dynamic population(s) of cultivated species that have historic origin with distinct identity and locally adapted in association with traditional farming systems (Ceccarelli, 2016). Landraces possess wide genetic diversity and are underutilised primary sources of desirable genes for economically important traits (Teklu and Hammer, 2008;Haile et al., 2013b;Muleta et al., 2017). Tetraploid wheat holds diverse alleles for disease resistance that can reverse the existing genetic diversity erosion in established, elite cultivars Muleta et al. (2017). The development of new varieties is critical to enhancing the yield of wheat, and use of landrace populations is a viable strategy to improve yield and yield stability as well as resistance to biotic and abiotic stresses (Abbasabad et al., 2016).
Crop improvement substantially depends on the extent of genetic variability existing within the species and their crop wild relatives. The genetic variation that exists among plant populations is a basic requirement for their efficient improvement and also serves as an evidence to prove whether the population of such plants can withstand unpredictable changes in the environment (Nandwani, 2019). Crop breeding programmes depend on the availability of large germplasm collections, which are invaluable source of parental strains for hybridization and subsequent development of improved varieties (Asins and Carbonell, 1989). More than 7000 tetraploid wheat landraces were maintained at the Biodiversity Institute of Ethiopia ( [URL], only limited portions of the collections were characterized (Negisho et al., 2021) using morphological markers (Getachew and Worede, 1991;Belay et al., 1993;Bechere et al., 1996;Belay et al., 1997;Kebebew et al., 2001;Alamerew et al., 2004;Eticha et al., 2005;Faris et al., 2006;Teklu and Hammer, 2008;Tsegaye et al., 2012;Mengistu et al., 2015;Asmamaw et al., 2020). Therefore, more information is needed about phenotypic and genetic variation present in Ethiopian tetraploid wheat landraces through morphological characterization to reveal the potential input of the landraces for breeding (Teklu and Hammer, 2008).
Genetic variability among tetraploid wheat genotypes can be estimated based on quantitative traits (Azene et al., 2020). Furthermore, knowledge of the naturally occurring diversity in tetraploid wheat landraces helps to identify diverse groups of genotypes to be incorporated in the breeding programme (Azene et al., 2020). To inform breeding, it is important to estimate heritability and genetic advance (Pandey and Tiwari, 1983). Heritability denotes the proportion of phenotypic variance that is due to genetic reasons (Singh, 1990). Genetic advance provides a prior quantitative estimate of the magnitude of the progress that can be achieved through selection (Panse and Sukhatme, 1957). In this study, we assessed the genetic variation, heritability, genetic advance and correlation of phenotypic traits in 196 tetraploid wheat germplasm to inform future breeding programmes.
Planting materials
A total of 196 tetraploid wheat (Triticum turgidum spp.) genotypes, representing 174 landraces and 22 varieties, collected from different parts of the country were used in this study (Supplementary Table S1). The landraces accessions used were originated from the different Ethiopian wheat producing regions: Shewa, Jima, Bale, Tigray, Wello, Gonder, Gojam, Agaw Awi (Fig. 1). The released varieties and 40 of the landraces were obtained from Plant Genetic Resources: Characterization and Utilization Debrezeit Agricultural Research Centre (www.eiar.gov.et). The remaining 134 landraces were obtained from Sinana Agricultural Research Centre ( [URL] landraces were collected by the Biodiversity Institute of Ethiopia (IBE).
Methods
Each genotype was grown in plots of two rows of 1 metre long and 20 cm inter-row spacing with two replicates per accession in a simple lattice design at Debrezeit and Sinana during 2020. Debrezeit Agricultural Research Centre is located at an altitude of approximately 1900 m above sea level, with latitude of 80 44 ′ N and longitude of 380 85 ′ E. Sinana, located at an altitude of 2400 metre above sea level, has a range of mean annual rainfall of 563-1018 mm with minimum and maximum temperature of 7.9 °C and 24.3 °C, respectively. All agronomic recommendations were used as recommended: 100 kg urea and 150 kg DAP per hectare and three times hand weeding was applied. Ten plants were randomly selected and tagged for phenotypic data collection. The data were collected for 11 quantitative morphological traits using the descriptors for wheat (IBPGR, 1985). Days to booting, days to maturity, seed yield and biomass yield were recorded on a plot basis.
Plant height
Height of plant at maturity, measured in cm from ground to top of spike.
Spike length
The length of spike from the base of spike to the tip of spike measured in cm.
Days to booting
Counted as days from sowing to 50% of plants in booting stage.
Days to maturity
Counted as days from sowing to 50% of plants at physiological maturity.
Number of spikelet per spike
The average number of spikelet per spike from five typical spikes randomly selected from a growing accession.
Number of seeds per spikelet
The average number of seeds from a spikeletobtained from the central portion of the five randomly selected typical spikes.
Number of effective tiller per plant
The number of tillers bearing spike from the five randomly selected plants.
Biomass yield per plot
Dry weight of the above ground wheat per plots taken at harvest.
Grain yield per plot
The grain weight of all plants grown per plot taken from each genotype, moisture content adjusted to 12.5%.
Thousand kernel weight
Thousand grains were counted from each genotypes harvested from a plot and their weight in gram was recorded.
Harvest index
The ratio of dried grain weight per plot divided by above ground biomass at 12.5% moisture content.
Phenotypic data analysis: Analysis of variance (ANOVA) for each location was carried out using the PBIB test in R by considering genotypes and block as fixed and random factors, respectively. In each location, the observed phenotypic response of the ith genotype in the jth replication and lth sub-block was computed using the following model: where y ijl = the observed phenotype, μ = the grand mean, g i = fixed effect of the ith genotype, y j = effect of the jth replication, bl ( j) = random effect of the lth block nested within the jth replication and ϵ ijl = random error term.
The combined ANOVA across the locations was executed by considering genotype as a fixed effect and the block, and location as random effects according to the following model: where Y ijkl = observed response of genotype l and replication j of block k of location i; μ = grand mean; g l = fixed effect of genotype l; r ijk = effect of replication j in location i; l i = random effect of location i that is ∼NID(0, δ 2 e ); b ijkl + random effect of block k nested within replication j in location i that is ∼NID(0, δ 2 b ); (gl) il = random effect of the interaction between genotype l and location i that is ∼NID(0, δ 2 gl ) + ϵ ijkl = random residual effect that is ∼NID(0, δ 2 ϵ ). Homogeneity of the error mean square (MS) was tested from individual ANOVA at Sinana and Debrezeit was checked following the F-max technique of Hartley (1950) described as: maximum F statistics (F max ) = Larger error mean square (MSE)/ smaller error mean square (MSE). The error variance is declared as homogenous if the larger MSE is not three times greater than the smaller MSE (Gomez and Gomez, 1984). After deciding that the error variances were homogeneous for specific triat, the combined ANOVA was performed. The statistical significance between genotypes is decided based on P-value that corresponds to the F statistics. If P-value is less than the specified alpha (α) level, the null hypothesis is rejected and the difference between the genotypes concluded significant; however, if the P-value is not less than the specified alpha (α) level, the null hypothesis is accepted and we conclude that the genotypes showed statistically no significant difference ( [URL] variability of each quantitative trait was estimated by simple statistical measures such as mean, range, phenotypic and genotypic variances and coefficient of variation. Phenotypic, genotypic, environmental and genotype by environment 10 Miheretu Fufa et al.
interaction coefficient of variation, broad sense heritability (H 2 ), and genetic advance were the parameters assessed. The phenotypic and genotypic variation and coefficient of variations were calculated using the formula suggested by (Singh and Chaudhary, 1985) and (Allard, 1960).givenbelow: Genotypic variance (δ 2 g) where MSg stands for the mean square of genotype, MS gl represents the mean square due to genotype by environment interaction, l is the number of locations and r stands for number of replications.
Genotype by environment interaction variance (δ 2 gl ) where MS gl = mean square due to genotype by environment interaction and MSe = combined error mean square.
Phenotypic variance (δ 2 p ) Estimates of coefficient of variation will be obtained as follows.
Phenotypic coefficient of variation (PCV) where PCV = phenotypic coefficient of variation, δ 2 p = phenotypic variance and μ = population mean for the trait considered.
Genotypic coefficient of variation (GCV)
where GCV = genotypic coefficient of variation, δ2 g = genotypic variance and μ = population mean for the trait considered.
Environmental coefficient of variations (ECV)
Coefficient of variation due to genotype by environment interaction was computed by the formula where, δ 2 gl = genotypic by environment interaction variance and μ = population mean for the trait considered. Plant Genetic Resources: Characterization and Utilization
Broad sense heritability (H 2 ) and genetic advance
Heritability in broad sense, for the two locations, was estimated based on the formula given by (Allard, 1960). H 2 = (δ 2 g/δ 2 p) × 100, where δ 2 p = δ 2 g + (δ 2 gl/l) + (δ 2 e/rl) where δ 2 e = error variance, l = the number of locations and r = the number of replications. Expected genetic advance under selection was calculated with the formula of (Allard, 1960), at 5% selection intensity, as: GA = (K ) (δp) (H 2 ), where GA = expected genetic advance, K represents a selection differential that varies based on the selection intensity and is equal to 2.056 if one chooses 5% of the genotypes, δp stands for phenotypic standard deviation and H 2 represents broad sense heritability. Genetic advance as percentage of the mean will be calculated as GA (% of mean) = () x100%, where GA = genetic advance and μ population mean for the trait considered.
Correlation coefficient analysis
Pearson correlation analysis of quantitative traits was performed for quantitative traits using R software (version 4.1.1)(R Development Core Team, 2018).
Combined ANOVA
A total of 196 tetraploid wheat (T.turgidum spp.), including 174 landraces and 22 varieties, were assessed for the genetic variation, genetic advance, heritability and correlation of their eleven phenotypic traits at Debrezeit and Sinana Agricultural Research centres during 2020. After checking for homogeneity of the error MS from individual ANOVA at Sinana and Debrezeit during 2020 following the formula of (Gomez and Gomez, 1984) described as: F-larger error MS/smaller error MS, the error variances were homogeneous for all the traits studied. Table 1 illustrates the variance results from a pooled analysis of eleven phenotypic traits for 196 genotypes of tetraploid wheat genotypes at Sinana and Debrezeit during 2020. For all traits other than the number of effective tillers per plant, the mean squares resulting from genotypes and genotype by location interaction differed significantly among genotypes (P < 0.001). All traits showed highly significant variation (P < 0.001) across locations.
Phenotypic and genotypic coefficient of variation
The values of phenotypic coefficient of variation (PCV = the variation due to genotype and environment), genotypic coefficient of variation (GCV = the variation due genotype only), genotype by environment interaction coefficient of variation (GECV = the variation due to the interaction of genotype and environment), broad sense heritability (H 2 = how much a variation in a trait is due to genetic factors) and genetic advance (explains the degree of gain obtained in a trait under a particular selection pressure) are given in Table 3. PCV and GCV below 10%, 10-20% and above 20% were respectively regarded as low, intermediate and high (Burton and DeVane, 1953). The values of PCV and GCV were low for the number of seeds per spikelet (6.98, 5.06), plant height (8.31, 6.65), moisture content (2.66, 2.11), days to booting (5.25, 3.43) and days to maturity; were intermediate for the number of spikelets per spike (17, 15.64), spike length (14.74, 12.01) and thousand kernel weight (15.1, 11.58) and were high for seed yield (37.18, 24.03), biomass yield (36, 24.18) and harvest index (41.11, 29.82). High PCV (20.79) and intermediate GCV (14.93) values were obtained for the number of effective tillers per plant.
The value of genotype by environment interaction variation was high for seed yield (33.42), biomass yield (30.69) and harvest index (32.01);was intermediate for the number of effective tillers per plant (11.57) and was low for the number of spikelet per spike (5.77), the number of seed per spikelet (4.27), spike length (7.32), plant height (4.99), thousand kernel weight (9.85), moisture content (1.63), days to booting (4.24) and days to maturity (2.97).
The values of genetic advance as a percentage of mean >20%, 10-20% and <10% were categorized as high, intermediate and low, respectively (Johnson et al., 1955). Genetic advance as the percentage of mean was low for the number of seed per spikelet (7.54%), days to booting (4.61%), and days to maturity (4.36%); intermediate for plant height (10.95) and thousand kernel weight (18.27), and high for spike length (20.13), the number of spikelets per spike (29.57), the number of effective tillers per plant (22.06), seed yield (31.94), biomass yield (33.39) and harvest index (44.49). The observed genetic advance and broad sense heritability (H 2 ) were high for the number of spikelet per spike.
Correlation analysis
The result of Pearson correlation coefficient was given in Table 4. Grain yield showed a highly significant (P < 0.001) negative correlation with days to booting (−0.36***) and days to maturity (−0.31***) and a highly significant (P < 0.001) positive correlation with thousand kernel weight (0.43***), biomass yield (0.31***) and harvest index (0.49***). Grain yield, on the other hand, showed a significant positive (0.01) positive correlation with plant height (0.18*), spike length (0.15*) and the number of spikelet per spike (0.15*) and a positive correlation with the number of seeds per spikelet (0.14) and the number of effective tillers per plant (0.05).
Discussion
Genetic variation, genetic advance, heritability and correlation analysis was carried out for 196 genotypes evaluated at Sinana and Debrezeit during 2020 based on eleven phenotypic traits. The genotypes, locations and genotypes by location interaction showed significant variation for the majority of the traits evaluated (Table 1). There is significant (P < 0.001) variation among the genotypes for all traits other than the number of effective tillers per plant indicating the presence of genetic variation among the genotypes which in turn suggests that selection of lines can be effective in improving both yield and quality traits (Azene et al., 2020). In line with this study, Azene et al. (2020) reported significant variation among genotypes of durum wheat in Ethiopia. The significant (P < 0.001) variation acorss locations and genotype by Plant Genetic Resources: Characterization and Utilization location interaction suggest that the significant phenotypic variation among the tetraploid wheat genotypes is influenced by the environmental factors such as weather and farming practices, such as soil characteristics, field management or weather, affect how genes are expressed, which may help to explain the situation (Yao et al., 2008;Persaud et al., 2022). Further investigations will be required to ascertain stability of traits over several years to assess their suitability for crossing with other desirable traits in a breeding programme.
PCV and GCV below 10%, 10-20%, and above 20% were regarded as low, intermediate and high (Burton and DeVane, 1953). PCV is a measure of variation due to genetic and environmental factors and GCV is a measure of the relative variability of a trait due to genetic differences among individuals. The difference between PCV and GCV was high for seed yield, biomass yield and harvest index and low for days to maturity, number of spikelets per spike, plant height, days to booting, number of seed per spikelet, spike length, thousand kernel weight and number of effective tillers per plant implying that seed yield, biomass yield and harvest index were influenced by the environment whereas the remaining traits were mainly due to genetic factors. Arega et al. (2010) reported similar result on days to maturity, plant height and spike length; however, their result disagrees with the present result on the number of effective tillers per plant, the number of spikelets per spike, biomass yield, thousand kernel weight, harvest index and grain yield. Additionally, Abebe and Desta (2017) reported similar result on days to maturity, number of effective tillers per plant, biomass yield and harvest index; however, their work disagrees with the present study on spike length, grain yield and plant height. Moreover, Azene et al. (2020) reported similar result on PCV and GCV values of days to maturity, spikelet per spike, thousand kernel weight and spike length; however, their result disagree with the present study on the GCV and PCV values of other traits. Furthermore, Meles et al. (2017) reported similar results for plant height and days to maturity and thousand kernel weight; however, their result disagrees with the present result on effective tillers per plant, the number of spikelet per spike, spike length, the number of effective tillers per plant, thousand kernel weight, harvest index, grain yield and biomass yield. Seed yield showed positive association with thousand kernel weight, biomass yield, harvest index, plant height, spike length, the number of spikelet per spike, seeds per spikelet and effective tillers per plant. This implies that there might be common gene (s) that control seed yield and these traits, which indicates that improving either one or more of these traits could result in high seed yield (Arega et al., 2010). According to Kearsey and Pooni (1996), the positive association of these traits with seed yield might be due to either the presence of strong coupling of genes or pleiotropic genes controlling the traits in the same direction. In line with present study, Arega et al. (2010) reported that seed yield had significant association with biomass yield, plant height, thousand kernel weight and harvest index at both phenotypic and genotypic level. This result disagrees with the work of (Baye et al., 2020). Similarly, Azene et al. (2020) reported that there was a highly significant positive correlation of seed yield with thousand kernel weight, biomass yield and harvest index and a positive correlation with spike length. Grain yield showed a highly significant (P < 0.001) negative correlation with days to booting (−0.36***) and days to maturity (−0.31***). In line Table 4. Pearson correlation of quantitative traits of 174 tetraploid wheat land races and 22 improved cultivars of Ethiopia PH, plant height; DB, days to booting; DM, days to maturity; TKW, thousand kernel weight; TPP, number of effective tillers per plant; SY, Seed yield (t/ha); HI, harvest index; BY, biomass yield (t/ha); SPL, spike length (cm); SDpSpiklet, seed per spikelet; spkletPSsp, spikelet per spike.
with this study, Ayer et al. (2017) reported non-significant negative correlation of days to booting and days to maturity with seed yield, highly significant positive correlation of seed yield with spike length, highly significant negative correlation with 1000 grain weight and harvest index. The present study result provided preliminary indications that tetraploid wheat of Ethiopia hold huge genetic variation, which could be used as potential input in the breeding programme. Most of the traits studied showed positive association with seed yield implying that improving either one or more of these traits could result in high seed yield. Further work is needed to evaluate these and additional traits under different environmental conditions to assess their suitability for contributing to future breeding programmes.
Supplementary material. The supplementary material for this article can be found at [URL] 1 .
Figure 1. Geographical map of Ethiopia, indicating areas of the collection of the tetraploid wheat landraces and field trial sites of the research.
The number of spikelet per spike, the number of effective tillers per plant, seed yield and harvest index gave high values of genetic advance and heritability. High heritability accompanied with high genetic advance is an indication of additive gene effects(Johnson et al., 1955) and hence, high genetic gain from selection of the number of spikelets per spike would be expected. The work by Arega et al. (2011) on durum wheat Ethiopia agrees with the present study on GAM values of plant height (17.4), thousand kernel weight, and days to maturity while it disagrees with this study for the other traits. Moreover, Mesele et al. (2015) reported similar result on biomass yield, seed yield, spike length, thousand kernel weight and plant height on bread wheat of Ethiopia; however, their report disagrees with the present study on the number of effective tillers per plant, harvest index, seed per spikelet and days to maturity. Furthermore,Azene et al. (2020) also reported similar to the present study on days to maturity, harvest index and thousand kernel weight; however, their report disagrees with present study on plant height, spikelet per spike, spike length, biomass yield and grain yield.
Table 1 .
Mean square of combined ANOVA of quantitative traits : SdpSpklet, number of seeds per spikelet, number of spikelet per spike; SpL, spike length (cm); TPP, number of effective tillers per plant; PH, Plant height (cm); TKW, weight of thousand kernels per plant (gm). SY, seed yield (T/ha); BY, biomass yield (T/ha); HI, harvest index; DB, days to booting; DM, days to maturity; gen, genotype; Loc, location; Rep:block, block within replication; SE, standard error; CV, coefficient of variation, and Lsd, least significant difference. NB
Table 2 .
The mean, minimum, maximum and range values of quantitative traits at the entire genotypes level Remarks: SDpsp, the number of seeds per spikelet; SpPSp, the number of spikelet per spike; SPL, spike length (cm); TPP, the number of effective tillers per plant; PH, Plant height (cm); TKW, weight of thousand kernels per plant (gm). SY, seed yield (t/ha); BY, biomass yield (t/ha); HI, harvest index; DB, days to booting; DM, days to maturity; Min, minimum, and Max, maximum.
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Domain: Agricultural and Food Sciences
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The Impact of Liver Abscesses on Performance and Carcass Traits in Beef Cattle: A Meta-Analysis Study
: The use of high-grain diets in feedlots is associated with the development of acidosis and ruminitis, which can lead to the occurrence of liver abscesses (LAs). However, the effect of LA on carcass traits is not well known. This study assessed the effects of LA on the performance and carcass traits of beef cattle. Nine peer-reviewed publications with forty-seven treatment means were included in the data set. The effects of the LA were evaluated by examining the weighted mean difference (WMD) between LA (animal with LA) and control treatment (animal without LA). Heterogeneity was explored by meta-regression, followed by a subgroup analysis of the scores and percentages of liver abscess and concentrate level in the feedlot diet. Animals affected by LA showed a reduction in dry matter intake ( − 1.03%) and feed efficiency ( − 1.82%). Animals with an LA score of “A” (one or two small abscesses) exhibited a decrease in carcass weight (WMD = 3.41 kg; p = 0.034) and ribeye area (WMD = − 1.37 cm 2 ; p = 0.019). When assessing the impact of LA on carcass traits, the most reliable finding indicates a 1.21% reduction in the ribeye area, with no adverse effects observed on subcutaneous fat thickness or the marbling score in the carcass.
Introduction
Projections for global protein consumption estimate a 33% increase over the next 30 years [1], with an expected 14% increase in global meat consumption by 2030 [2]. In this scenario, it becomes necessary not only to intensify cattle production systems, but also to improve the efficiency of feed utilization.
However, intensifying production systems (e.g., feedlots) associated with higher grain inclusion diets, especially in beef cattle, increases the risk of nutritional and metabolic disorders (e.g., ruminal acidosis and ruminitis). The reduction in ruminal pH and the lack of effective fiber can injure the ruminal epithelium, leading to the inflammation and translocation of pathogenic ruminal microorganisms, particularly Fusobacterium necrophorum and endotoxins, to the liver via the bloodstream. Hepatic abscesses are a common sequela [3,4].
While ruminal health has received much attention, it is increasingly evident that the impact of high-grain diets on other sections of the gastrointestinal tract (GIT) substantially contribute to the overall pathophysiology of the GIT disease [5]. Indeed, the portal vein collects blood from the entire GIT, and recent evidence suggests that a considerable number of bacterial endotoxins and liver abscess microbes arise from the post-ruminal GIT [6][7][8].
The occurrence of liver abscesses (LAs) causes a reduction in animal performance and feed efficiency [9], as the liver is the central organ of metabolism, accounting for 40 to 50% of total oxygen consumption in cattle [10]. Liver abscess also decreases carcass weight and yield [11,12] or may lead to carcass condemnation when contamination occurs due to abscesses rupturing during slaughter. According to Harris et al. [13], liver condemnation due to the occurrence of LA is responsible for 58% of liver condemnations in the USA.
However, few studies in the literature assess the impact of LA on carcass traits and meat quality, resulting in a lack of standardization in assessing the occurrence of LA, rendering this parameter unreliable for comparison and practical applications. Liver abscess can be categorized by the incidence or severity of the abscess, with a score based on their number and size. However, there is no standardization in the classification of LA, leading to variation in the different scales reported. These have varied from a more comprehensive scale [14] to a narrower scale [15]. For example, Brown et al. [14] suggested a scale where: abscess score 0 = no abscess, A-= one or two small abscesses or inactive scars, A = one or two large abscesses or several small abscesses, and A+ = multiple large abscesses often involving collateral tissue. A simpler scale was suggested by Elanco, [15], where: abscess score of 0 = no abscess, A = one or two small abscesses, and A+ = one or more large abscesses. A standardization in classification is needed to ensure accuracy in assessing the impact of LA on carcass and meat quality characteristics.
Moreover, several factors influencing the occurrence of LA (e.g., genetic group, sex, diet, days on feed, and biological type; [16]) and the impact of LA on carcass traits are still not well understood. Therefore, we hypothesize that the negative impact of LA on carcass traits depends on factors such as genetic group, sex, diet, days on feed, and biological type. The objective of the present study was to evaluate the effects of liver abscesses in beef cattle on their performance and carcass parameters using a meta-analytic approach.
Data Set
A comprehensive literature search was conducted using three search engines: PubMed ( [URL] Direct ( [URL] Wiley Library ( [URL] searches were conducted between 5 July 2023. A total of 340 publications were retrieved using the search terms "liver abscess AND beef cattle". Of the papers that were retrieved, only those that satisfied the predefined inclusion criteria were included in the meta-analysis. For inclusion into the meta-analysis, studies had to have the following standardized criteria: (1) the control group (without LA) and the treatment group (with LA); (2) the diet of the control group (without LA) could not include antibiotic additives; (3) data were only from beef cattle intended for meat production. A flowchart detailing the study identification and selection for analysis is shown in Figure 1. Based on the inclusion criteria, 9 peer-reviewed publications with 47 treatment means were used (Table 1). The complete data set is available in Supplemental File S1. for the meta-analysis on the effect of liver abscesses on performance and carcass traits in beef cattle.
Statistical Analysis 2.2.1. Weighted Mean Difference and Publication Bias
A meta-analysis was conducted using R Statistical Software (Metafor package, version 4.4.0;Viechtbauer, [24]). Forest plots were created using STATA software (Version 16.0; StataCorp LP, College Station, TX, USA) and the effects of liver abscess occurrence on the carcass parameters in beef cattle were evaluated by examining the weighted mean difference (WMD) between the presence and the absence of LAs. The treatment means were weighted by the inverse of the variance, according to the method proposed by Der-Simonian and Laird, [25] for the random effects model.
Between-study variability (i.e., heterogeneity of the treatment effect) was evaluated using both the chi-squared (Q) test of heterogeneity and I 2 statistics, which measures the percentage of variation due to heterogeneity [26]. Negative I 2 values were assigned as zero. An I 2 value lower than 25% indicates low heterogeneity, whereas values between 25% and 50% denote moderate heterogeneity, and those above 50% denote high heterogeneity [26].
Publication bias was evaluated using the funnel plot [27] (Figure S2) and asymmetry test (indicative of publication bias), which was performed according to the Egger regression asymmetry test among the WMD and SE [28]. Significance was declared at p ≤ 0.05. Outliers were removed when studentized residuals were outside the range of −2.5 to 2.5 (outliers).
Meta-Regression and Subgroup Analysis
Meta-regression analysis was conducted to identify categorical covariate effects and select variables for subgroup analysis. A mixed model was applied to adjust the data in the meta-regression analysis using WMD as the dependent variable. The mixed-effect models were given by: θi where: θi = the true treatment effect in the ith explanatory variable; β = the overall true effect treatment; xij = the value of the jth covariate (j = 1, 2, . .., p) for the ith explanatory variable; βi = change in the true effect size for a unit increase in the jth covariate; and µi ~N (0 t 2 ). Here, t 2 indicates the amount of heterogeneity not explained by the covariate [24]. The calculation of the moment estimator of the between-study variance (Tau-squared = T 2 ) is used in DerSimonian and Laird random effects meta-analysis, but it is less suitable when covariates are included [29]. The restricted maximum likelihood estimate (REML) approach was used to estimate T 2 because it is less likely to underestimate or produce biased variance estimates [29,30]. Tests of the null hypothesis for the covariate coefficients were obtained from the multiparameter Wald test [31]. The adjusted R 2 for the model represents the proportion of between-study variance (heterogeneity) explained by the covariates [24,31]. The metaregression criteria were: (1) p ≤ 0.05 for the heterogeneity test; (2) p ≥ 0.05 for the funnel plot; (3) no observations with values for studentized residuals out of the range −2.5 to 2.5 (outliers).
The covariates were divided as follows, due to differences in the scales used to assess LA severity (abscess score and abscess incidence) among studies. Abscess score scales were standardized according to Elanco [15] to enable the evaluation of the liver abscess score in the subgroup analysis:
•
Liver abscess score A or A+, where A= small abscesses (n = 1-2) or well-organized abscesses (n = 2-4) usually under one inch in diameter (the remainder of the liver looks healthy); A+ = large abscesses (n ≥ 1), together with inflammation of liver tissue surrounding the abscess (often, portions of the diaphragm are adhered to the surface of the liver and have to be trimmed to separate the liver from the carcass); • Liver abscess incidence (2.4-4.8% or 6.3-9.4%);• Levels of diet concentrate (840-900 g/kg or > 900 g/kg DM).
Subgroup analysis was performed when WMD's categorical covariates were significant at p ≤ 0.10 (meta-regression analysis).
Standardized Mean Difference
The effect size was calculated as the standardized mean difference (SMD), which is the difference between the presence and the absence of LAs., standardized using the standard deviations from the groups with and without LAs. Consequently, the SMD data are expressed in standard deviation units [32]. The SMD estimates were calculated using the methods of DerSimonian and Laird [25] for random effects models.
Regarding the concentrate levels in the diets, 36% (n = 17) of the treatment means showed levels ranging from 840 to 900 g concentrate/kg DM in the diet, 34% (n = 16) above 900 g concentrate/kg DM, and 30% (n = 14) of the studies did not report this information. Table 2 describes how LA globally affects each response parameter. 1DMI = dry matter intake; BW = body weight; FE = feed efficiency; ADG = average daily gain; SFT = subcutaneous fat thickness; KPH = kidney, pelvic, and heart fat; USDA yield grade (YG). 2 Control treatment = no abscesses; a normal, healthy liver; SD = standard deviation. 3N represents the number of comparisons for control and treatment with liver abscess (complete data set is available in Supplementary File S1). 4 WMD = weighted mean differences between control and animal with liver abscess. 5I 2 proportion of total variation of size effect estimates due to heterogeneity.p value to χ2 (Q) test of heterogeneity. 6Egger's regression asymmetry test (Funnel test). 7SMD = standard mean difference (SMD random effect (95%CI)).
Marbling Score and United States Department of Agriculture Beef Yield Grade
The effects of LA in beef cattle on the marbling score and United States Department of Agriculture (USDA) beef yield grade (YG) were evaluated through the standardized mean difference (SMD) analysis. This procedure was used because studies included in this meta-analysis used different methodologies for the marbling score and USDA YG, which limits the transformation of measurement units. In this sense, LA had no significant effect on the marbling score (p = 0.841; Figure 2) and USDA YG (p = 0.722; Table 2).
Meta-Regression and Subgroup Analysis
For the variables evaluated in Table 2, medium heterogeneity was observed (I 2 statistic 25 to <50%). However, the presence of publication bias (p > 0.05) from the funnel plot asymmetry test (Funnel test) was not evident (Table 2). Table 3 presents the effect of the covariates on the variation of the response variables (meta-regression analysis).
The incidence of LAs was evaluated (covariate = liver abscess (%)), resulting in 2.4-4.8% of LAs and a reduced feed efficiency, with the calculated WMD = −0.004kg/kg and p = 0.028 (Figure 3) and, conversely, an increase in carcass dressing, with WMD = 0.39% and p = 0.001 (Figure 4). ADG = average daily gain; BW = body weight; FE = feed efficiency; DM = dry matter. 1 Liver abscess score (Elanco, 2019): A = small abscesses (n = 1-2) or well-organized abscesses (n = 2-4) usually under one inch in diameter (the remainder of the liver looks healthy); A+ = large abscesses (n ≥ 1), with inflammation of surrounding liver tissue (portions of the diaphragm are often adhered to the surface of the liver and have to be trimmed to separate the liver from the carcass). 2Adjusted R 2 = proportion of the between-study variance (heterogeneity) explained by the covariate. 3N = the number of comparisons between animal with liver abscess and normal (no abscesses-a normal, healthy liver) (complete data set is available in Supplementary File S1).
Figure 3. Subgroup analysis of the effect of liver abscess on beef cattle performance. Liver abscess score is standardized after Elanco [15] where: A = small abscesses (n = 1-2) or well-organized abscesses (n = 2-4) usually under one inch in diameter (the remainder of the liver looks healthy); A+ = large abscesses (n ≥ 1), with inflammation of surrounding liver tissue. WMD = weighted mean differences between the presence and absence of liver abscess.
Discussion
The conducted meta-analysis revealed a mild-to-moderate severity of LA in beef cattle, which corroborates the data previously reported by Davis et al. [33] and Brown and Lawrence [9]. An LA incidence close to 10% was observed in 77% of the analyzed treatment means, and there was a percentage of 83% with regard to the presence of LA as "A" (one or two small abscesses [15]). The authors Davis et al. [33] and Brown and Lawrence [9] assumed that the mild-to-moderate cases of LA would cause no impact or only a minor impact on the animals' performance. However, our findings demonstrated reductions of 1.03% in DMI and 1.8% in feed efficiency in animals affected by LA.
A reduction in muscle deposition in the carcass is consistently associated with the presence of LA and, indeed, a decrease of 1.21% in the ribeye area (WMD = −1.02cm 2 ) was observed in beef cattle affected by LA. Although opposite results were reported in the literature [9,33], the consistency of these responses is confirmed by the low heterogeneity value obtained in the analysis (I 2 = 0.00%). The I 2 represents the proportion of total variance between studies due to true differences in effect sizes rather than chance. Furthermore, an I 2 of 0% indicates that all variability in the effect estimate is due to chance and none is due to heterogeneity [34]. These reductions can be explained due to the high occurrence of LA in ruminants, which manifest as localized infections in the liver [34,35].
Concerning DMI, this reduction in feed intake directly affects their nutrient intake and overall performance [35,36]. According to Fuerniss et al. [37], the liver plays a crucial role in digestion and nutrient metabolism. Thus, if abscesses compromise the liver, it may not function optimally, impairing metabolism and reducing nutrient utilization. These effects can lead to a limited growth rate (ADG) and lower feed efficiency in animals, as observed in this study.
The reduction of DMI and ADG can also explain the negative effects of LA on carcass traits such as carcass weight and dressing, which were influenced by the level of concentrate inclusion in the diet. According to Plaizier et al. [38], LA can impact the overall health and well-being of the animal, resulting in decreased carcass quality. Abscesses can lead to liver condemnations during post-mortem inspections, causing economic losses for the livestock industry [39].
However, the lack of effect of the LA presence on ADG, feed efficiency, carcass weight, and ribeye area in animals fed diets with concentrate levels above 90% could be attributed to a compensatory effect of the greater digestibility of these diets, which would offset the increased nutritional requirements of LA-affected animals. According to Batista and Holland, [12], the presence of LA can increase the net energy for maintenance requirements in cattle by up to 4.8%.
These results partially confirm our hypothesis that risk factors for LA, such as genetic group, sex, diet, feeding period, may impact carcass traits. However, it should be noted that we were only able to evaluate the effect of concentrate level in the feedlot diet as a covariate due to limitations in the information provided by the studies included in the dataset.
In addition, considering the impact of LA on carcass traits, the description of the severity of LA occurrence (score) had a significant effect on performance variables and carcass traits, which was not observed when evaluating the effect of LA presence by simply assessing its incidence (%). The reason that the LA score, rather than percentage, had a significant statistical effect could be the result of a dilution effect of LA on carcass traits when presented as the percentage of affected animals relative to the total number of animals in the experimental group, especially in studies with a low LA incidence. The present study demonstrated that LA occurrences below 9.4% did not affect the ADG, carcass weight, and ribeye area, whereas the presence of only one or two small abscesses (liver abscess score standardized as "A" by Elanco [15]) resulted in a reduction in carcass weight (WMD = 3.41 kg) by decreasing the size of the ribeye area (WMD = 1.37 cm 2 ).
The effect of moderate-severity LA on animal performance also may be associated with the level of concentrate in the diet, which can compensate for the increased nutritional requirements of the animals [9,33]. The LA effect on the tissue deposition pattern in the carcass should also be considered, since the presence of LA resulted in a reduction in muscle deposition (ribeye area reduction) without affecting fat deposition in the carcass (e.g., SFT and KPH). This result explains the absence of an LA effect on USDA YG on the carcass.
The decrease in muscle deposition can be explained by the inflammatory process resulting from the LA, which is associated with a reduction in the activity of gluconeogenesis enzymes [40]. Furthermore, a decreased ribeye area is also related to a decrease in protein synthesis and hepatic lipolysis [41] in response to an increase in the concentration of acute-phase proteins such as serum amyloid in LA-affected animals [42]. The increase in the circulating concentration of acute-phase proteins is associated with a greater mobilization of aromatic amino acids from skeletal muscle for their synthesis in the liver [43]. Decreases in muscle deposition can also relate to the increase in the circulating concentration of cortisol [44], as observed in LA-affected animals [45]. Corticosteroids reduce protein synthesis and stimulate degradation, mobilizing amino acids for gluconeogenesis under stress or food restriction [40] without affecting lipid synthesis in adipose tissue. Also, in addition to the inflammatory effect, LAs are associated with reduced blood concentrations of testosterone and thyroid hormones such as thyroxin-T4 [46], which can lead to a reduction in the hormonal stimulus for skeletal muscle deposition and an increase in the turnover of muscle protein.
Overall, the occurrence of LA of up to 10%, as well as the presence of one or two small abscesses, are associated with a reduction in skeletal muscle deposition without impairing fat deposition in the carcass. Liver abscesses can lead to significant losses in the meat processing chain, since the value of the carcass and meat depends on its protein content.
Conclusions
Our meta-analysis demonstrated that LA impacts the performance and carcass traits of feedlot beef cattle. When evaluating the effect of LAs on carcass traits, the most consistent response regarding the presence of LAs was a 1.21% reduction in the ribeye area, without impairing the SFT and KPH of the carcass.
LA = liver abscess; ADG = average daily gain; BWf = final body weight; CW = carcass weight; DM = dry matter; DMI = dry matter intake; DRE = dressing; FE = feed efficiency; MAR= marbling score; RIB = ribeye area; SFT = subcutaneous fat thickness; KPH = kidney, pelvic, and heart fat; USDA = USDA calculated yield grade; (--) = not reported or informed.a Liver abscess score (Elanco, 2019): A = small abscesses (n = 1-2) or well-organized abscesses (n = 2-4) usually under one inch in diameter (the remainder of the liver looks healthy); A+ = large abscesses (n ≥ 1), with inflammation of surrounding liver tissue (portions of the diaphragm are often adhered to the surface of the liver and have to be trimmed to separate the liver from the carcass).
Figure 1 .
Figure 1. Flowchart showing results obtained from the search strategy and the selection of eligible studies for the meta-analysis on the effect of liver abscesses on performance and carcass traits in beef cattle.
Figure 2 .
Figure 2. Forest plot of standardized mean difference (SMD) between the means calculated for the marbling score in beef cattle with and without liver abscesses. Liver abscess score is standardized after Elanco [15] where: A = small abscesses (n = 1-2) or well-organized abscesses (n = 2-4) usually under one inch in diameter (the remainder of the liver looks healthy); A+ = large abscesses (n ≥ 1), with inflammation of surrounding liver tissue. Solid squares for the separate individual studies (denoted by roman numerals) represent weighting by the inverse of their respective variances. The horizontal lines represent the 95% confidence interval (CI) of each study. The open diamond represents the overall SMD and its width represents the associated 95% confidence interval. I-squared (I 2 ) represents the proportion of total variation of effect size estimates due to heterogeneity, and % weight represents the contribution of the study to the overall effect size. Weights are from the random effects model. DL represents the treatment means weighted by the inverse of the variance, according to the method proposed by DerSimonian and Laird [25] for a random effects model. The reference are Calderon-Corte and Zinn [17], Depenbusch et al. [18], Huck et al. [19], May et al. [21], Mir et al. [22], Salim et al. [23].
Figure 4 .
Figure 4. Subgroup analysis of the effect of liver abscess on carcass traits in beef cattle. Liver abscess score = liver abscess score, standardized (Elanco, 15): A= small abscesses (n = 1-2) or well-organized abscesses (n = 2-4) usually under one inch in diameter (the remainder of the liver looks healthy); A+ = large abscesses (n ≥ 1), with inflammation of surrounding liver tissue. WMD = weighted mean differences between the presence and absence of liver abscess.
Table 1 .
Summary of the characteristics of studies included in the systematic review and subsequent meta-analysis.
Table 2 .
Effects of liver abscesses on the performance and carcass traits in beef cattle.
Table 3 .
Meta-regression of the effect of liver abscesses (LA) on performance and carcass traits in beef cattle on weighted mean differences (WMD) between the presence and absence of abscesses.
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Domain: Agricultural and Food Sciences
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Genetic gain for technological traits in new cultivars developed by the Southern Brazilian common-bean network
ABSTRACT Estimating the genetic gain obtained for technological quality traits over the years makes it possible to analyze whether the changes made meet consumer preferences, which represents an important innovation for common-bean breeding programs. The objectives of this study were to obtain genetic gain estimates for technological grain quality traits of common bean lines and investigate whether the modifications made were favorable in the context of sustainability and food and nutritional security for the coming generations. Twenty-four experiments were conducted between the years 2010 and 2022 and a total of 75 common bean lines were evaluated. Genetic gains of technological grain quality traits were determined by the Vencovsky’s (1988) method adapted for biennia. There was a significant effect of genotype for most traits evaluated, which shows the existence of genetic variability. Mass of 100 grains and water absorption had a negative genetic gain of -2.91% and -0.55% per year, respectively, indicating a reduction in these traits. Genetic gain was zero for L* value (lightness) and cooking time, denoting a plateau for these traits. Most of the common bean lines exhibit adequate L* values for carioca (L* ≥ 53) and black (L* ≤ 22) bean grains; a mass of 100 grains from 20 to 25 g; and fast cooking (≤ 25 min). The new common bean cultivars released for cultivation in the southern region of Brazil have high technological grain quality, being favorable in a context of sustainability and food and nutritional security for the coming generations.
Index terms: Phaseolus vulgaris L.; grain color; grain size; cooking time; selection cycles.
INTRODUCTION
The consumption of common bean (Phaseolus vulgaris L.) is part of the eating habits of people from different countries. The existing diverse sizes, colors, and shapes of common bean grains that can be included in the diet meet the preferences of the most varied consumer profiles. Furthermore, there are many ways of preparing this healthy food, which has several health-protective effects (Chávez-Mendoza;Sánchez, 2017).
One way to encourage the consumption of common bean is to develop new cultivars with higher technological grain quality. The technological quality of common bean grains has been especially evaluated by their color, size, and cooking time (Arns et al., 2018;Ribeiro et al., 2019Ribeiro et al., , 2021Ribeiro et al., , 2023;;Kläsener;Ribeiro;Argenta, 2022). The grain types of Phaseolus vulgaris most produced in Brazil originate from the Mesoamerican gene pool, namely, carioca (beige seed coat with brown streaks), black, red, and pink, whose grain size ranges from small (< 25 g 100 grains -1 ) to medium (25 to 40 g 100 grains -1 ) according to the classes described by Hegay et al. (2014). In some regions of the country, grains from the Andean gene pool are also cultivated, especially the cranberry (cream seed coat with red streaks), red, and white types, which are characterized by their medium-to-large size (> 40 g 100 grains -1 ).
However, 85% of common bean consumption in Brazil is restricted to two types of beans: carioca and black (Pereira et al., 2019). As a result, common-bean breeding programs have dedicated greater effort to the development of new carioca and black bean cultivars with technological grain quality that meet consumer preferences. To this end, the following grain standards have been used as a reference in the selection of superior common bean lines: high lightness for carioca beans, defined as an L* value ≥ 55 by Arns et al. (2018); low lightness for black beans, stipulated as an L* value ≤ 22 by Ribeiro, Possebom and Storck (2003); mass of 100 grains from 25 to 30 g (Carbonell et al., 2010); and fast cooking (≤ 25 min) (Santos;Ribeiro;Maziero, 2016) for carioca and black beans.
Common-bean breeding programs in Brazil have developed many lines with high technological grain quality in the 2010s (Santos;Ribeiro;Maziero, 2016;Arns et al., 2018;Kläsener;Ribeiro;Argenta, 2022;Ribeiro et al., 2023;Ribeiro;Maziero, 2023). As improvement of technological grain quality traits is relatively recent in common bean, no information was found in the literature on whether genetic gain was achieved for the these traits over several selection cycles. These results would make it possible to assess whether the strategies used by common-bean breeding programs in Brazil were efficient in improving grain color, increasing grain size, and reducing the cooking time of common bean lines. In addition, it would serve as a basis for identifying and recommending changes to be incorporated in the new common bean cultivars in order to allow a continuous and gradual improvement of technological grain quality traits.
Several methodologies have been used to estimate the genetic gain of important traits for selection in breeding programs. The Vencovsky's (1988) method (Cruz;Regazzi;Carneiro, 2012) has been shown to be efficient in obtaining genetic gain estimates for grain yield in wheat (Follmmann et al., 2017;Woyann et al., 2019) and rice (Silva Júnior et al., 2021) breeding programs and for different agronomic traits evaluated in common bean breeding (Ribeiro;Possebom;Storck, 2003;Ribeiro et al., 2008). For technological grain quality traits of common bean, genetic gain estimates are restricted to a few traits evaluated in a short period (Ribeiro;Possebom;Storck, 2003). Mass of 100 grains has been the most analyzed technological trait in common-bean breeding programs, and genetic gain has been estimated by different methodologies (Singh et al., 2007;Ribeiro et al., 2008;Faria et al., 2013Faria et al., , 2014;;Bekele et al., 2019;Kefelegn;Mekibib;Dessalegn, 2020;Mukayiranga et al., 2022). However, no previous studies were found that determined genetic gain for traits of grain color, water absorption, or cooking time using databases generated over years in common-bean breeding programs.
Therefore, the present study was undertaken to obtain genetic gain estimates of technological grain quality traits of common bean lines and investigate whether the changes made to these traits were favorable in the context of sustainability and food and nutritional security for the coming generations.
Experimental conduct and data collection
The Value for Cultivation and Use (VCU) experiments of the Southern Brazilian Common-Bean Network were conducted following the rules for registering new cultivars in Brazil (Ministério da Agricultura, Pecuária e Abastecimento -Mapa, 2006). A randomized block design with three replicates was employed. Each experimental plot consisted of four 4-m rows, with 0.5 m spacing between rows and a total area of 8 m 2 . Only the two central rows constituted the usable area of the plots (4 m²). The sowing density adopted was 15 seeds per linear meter.
In each experiment, the number of common bean genotypes (lines and cultivars) evaluated ranged from 11 to 18, in a total of 75 common bean genotypes. The composition of the VCU experiments is defined by the Breeding Subcommittee at the Southern Brazilian Common-Bean Meeting, which is held in July in even-numbered years. Each institution may include up to two new lines in each selection cycle (biennium). In each biennium, crops are grown in three seasons (rainy, dry, and winter) and in two consecutive years (even and odd). The lines evaluated in these experiments will not change within the biennium.
The experiments conducted by the Southern Brazilian Common-Bean Network are established in different municipalities in the states of Rio Grande do Sul, Santa Catarina, Paraná, São Paulo, and Goiás, at the recommended sowing times for each region, totaling approximately 100 experiments per biennium. In each biennium, lines released as new cultivars, unreleased lines, and four cultivars registered for cultivation in southern Brazil (controls) were evaluated. Therefore, one or more released lines may have been also analyzed as a cultivar in these experiments.
Genetic gain estimates were obtained using only databases generated at the Federal University of Santa Maria, located in Santa Maria, RS, Brazil. This is because the tecnological quality traits are not evaluated in the routine all common-bean breeding programs. Additionally, the quantitative assessment of grain color (L* value) was only carried out in Santa Maria. Grain color is an important technological trait that can be decisive for the acceptance of a common bean cultivar by the consumer (Ribeiro et al., 2019). However, the quantitative determination of grain color is not required for the registration of common bean cultivars in Brazil (Mapa, 2006).
A total of 24 common-bean VCU experiments were sown in Santa Maria between the years 2010 and 2022 in the two recommended seasons for cultivation: rainy (September or October) and dry (January or February). The climate of the region is humid subtropical, without a clearly defined dry season, and the experimental area is located at the following geographic coordinates: 29º42' S latitude, 53º49'W longitude, and 95 m above sea level.
The soil is a typic alitic Argisol, Hapludalf (Santos et al., 2018), which was prepared by the conventional tillage system, with one plowing and two harrowing operations. Limestone and fertilizer applications were based on the interpretation of soil chemical analysis for each experiment. Seed treatment with insecticide and fungicide and insect control were carried out using chemicals registered for the crop and with variable active ingredients over the years. In compliance with the rules of Mapa ( 2006), fungicides were not applied to control shoot diseases. Irrigation was only performed when necessary to establish the initial plant population and when there was an imminent risk of losing the experiment due to lack of rainfall during the reproductive period of the crop.
Determination of technological grain quality traits
The crop was harvested at the maturity stage (R9), that is, when the pods were dry and the grains were the typical color of each genotype. Harvesting and grain processing were carried out manually to avoid mechanical damage. The grains were dried naturally in the sun and, if necessary, in an oven, up to 13% moisture. Then, beans were stored in a cold chamber (temperature of 5 ºC and relative moisture of 75%) for approximately one month before the beginning of the evaluations of technological traits.
Grain color was determined using a portable colorimeter (CR 410, Konica Minolta, Osaka, Japão) operating in the CIELAB system. On this scale, the value of L* characterized grain lightness, which could range from 0 (black) to 100 (white). A sample of grains was randomly collected in each replicate and distributed inside a petri dish 6 cm in diameter and 1.5 cm in height, filling the entire surface. The petri dish was placed on white paper to prevent the absorption of possible colors from the environment. Grain color were taken in three readings of each replicate (Ribeiro et al., 2021). Mass of 100 grains (g) was calculated as the average weight of three samples of 100 grains collected at random in each replicate.
Water absorption and cooking time were quantified in a random sample of 25 grains. The grains remained in contact with 50 mL of distilled water for 8 h, at room temperature (20 ± 2 ºC). The water was removed and water absorption was calculated by the following expression: [(grain weight after soaking -grain weight before soaking)/grain weight before soaking] × 100. Cooking time was evaluated in a 25-plunger Mattson cooker in a method similar to that described by Ribeiro et al. (2021).
Statistical analyses
Analysis of variance was performed for each of the experiments. For the water absorption data, 0.5 x transformation was applied, in which corresponds to the trait value, and cooking time was converted into s.
Genetic gain was determined by the Vencovsky's (1988) method, also known as the generalized least squares method (Cruz;Regazzi;Carneiro, 2012), adapted for biennia. Each biennium begins with rainy season cultivation in the even year and ends with dry season cultivation in the odd year. Genetic gain estimates were obtained by identifying genotypes common to two successive biennia and estimating the mean ci Y for each biennium. Data were collected in n biennia, and genetic gain (G ak ) per biennium, relative to the previous biennium, was determined by the following Equation 1: in the rainy season crop (2011, 2013, and 2018) and five experiments in the dry season crop (2012, 2014, 2016, 2020, and 2022) were not included in the genetic gain analyses. In a climate change scenario, experiment losses caused by adverse environmental factors, such as high temperature, excessive precipitation, among others, will be more frequent, generating unbalanced data and this needs to be evaluated when obtaining estimates of genetic gain.
All traits evaluated in the 16 experiments showed a significant genotype effect, except for water absorption determined in the 2010, 2014, and 2015 rainy season crops and the 2018 dry season crop (Table 1). These results evidence that the lines developed by the Southern Brazilian Common-Bean Network have genetic variability for technological grain quality traits. Previous studies reported great genetic diversity for technological grain quality traits analyzed in lines (Arns et al., 2018;Ribeiro et al., 2023), cultivars (Kläsener;Ribeiro;Argenta, 2022), and landraces (Ribeiro et al., 2021) of common bean. Therefore, greater genetic variability for technological grain quality traits facilitates the selection of common bean lines with color, grain size, and cooking time that meet the needs and preferences of consumers.
The different traits showed coefficients of experimental variation ≤ 19.56%. Conversely, all traits that exhibited significant differences for genotype had selective accuracy ≥ 0.76, characterizing high experimental precision according to Resende and Alves (2020). The coefficient of experimental variation and selective accuracy values observed in the present study are comparable, in magnitude, to those of technological grain quality traits determined in common bean genotypes (Arns et al., 2018;Dias et al., 2021;Kläsener;Ribeiro;Argenta, 2022;Ribeiro et al., 2021Ribeiro et al., , 2023)). Therefore, the technological grain quality traits were evaluated with high experimental precision, which allows greater reliability in obtaining genetic gain estimates for these traits.
Genetic gain by the Vencovsky's (1988) method (Cruz; Regazzi; Carneiro, 2012)
The VCU experiments of the Southern Brazilian Common-Bean Network are characterized by a high rate of substitution of the lines evaluated in each selection cycle (biennium), keeping only one to four control cultivars between two consecutive biennia (Table 2). The Vencovsky's (1988) method (Cruz;Regazzi;Carneiro, 2012) considers the superiority of the lines that are evaluated in a selection cycle relative to the previous cycle in which: G ak = genetic gain between biennia i and j; Total genetic gain was estimated by Equation 2: (3) The mean annual genetic gain was obtained by Equation 3:
Individual analysis of variance
Of the 24 VCU experiments established, lost plots were not detected only in 16 experiments. This is because high precipitation intensity was recorded in eight experiments, especially in the weeks prior to the harvest, which contributed to the reduction in quantity and quality of the grains produced. As a consequence, data from three experiments conducted to estimate the genetic gain of different traits. This method was appropriate for obtaining consistent genetic gain estimates using unbalanced data from few environments (Ribeiro;Possebom;Storck, 2003;Ribeiro et al., 2008;Follmmann et al., 2017;Silva Júnior et al., 2021;Woyann et al., 2019). Environmental gain estimates were higher than genetic gain estimates for all analyzed traits (Table 3). In previous experiments conducted by the commonbean breeding program (Ribeiro et al., 2008) and by a rice breeding program (Silva Júnior et al., 2021), the generalized least squares method also provided high environmental gain estimates. The strategy of keeping a greater number of common treatments between selection cycles provides greater safety in estimating environmental variance (Cruz;Regazzi;Carneiro, 2012). However, keeping a large number of common lines and/or cultivars in experiments conducted in different biennia implies greater costs, area, and labor to conduct and evaluate the VCU experiments. Because the Southern Brazilian Common-Bean Network is constituted only of public research institutions, which would mean that there would be a limited budget for conducting the VCU experiments, evaluating a large number of common treatments is unfeasible.
In the present study, climatic factors, particularly temperature stress and high precipitation; and biotic factors, e.g. the occurrence of diseases and pests, contributed to the high environmental influence. Considering that the VCU experiments were conducted over 12 years and in the two recommended growing seasons (rainy and dry), the observed environmental variability is representative of the growing conditions for common bean in the region.
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The genetic gain obtained for the L* value was 0.05 biennium -1 , representing an increase of 0.13% per year (Table 3). Similarly, a low genetic gain estimate for the L* value was described for carioca and black bean lines evaluated in Santa Maria-RS between the years 1998 and 2001, using the generalized least squares method (Ribeiro;Possebom;Storck, 2003). These values indicate a plateau for grain L* value (lightness) in the new carioca and black bean cultivars released for cultivation in the southern region of Brazil. This can be explained by the fact that common Ciência e Agrotecnologia, 47:e019322, 2023 parents were used in several controlled crosses carried out to develop the new carioca and black bean cultivars, resulting in a narrow genetic base (Veloso et al., 2015). This is especially true for the carioca bean cultivars, which have less genetic diversity (Almeida et al., 2020). The hypothesis is that the selection pressure adopted in breeding programs for technological grain quality traits, such as resistance to browning, larger grain size, and reduced cooking time, prioritized in Brazil from 1997 onwards (Chiorato et al., 2010), contributed to the stabilization of genetic gain for the color of carioca and black bean grains. In all biennia, the mean L* values of the new common bean lines was higher than the mean of the lines kept (control cultivars) in the experiments, except for biennium 4 (Table 4). These results show that the new carioca bean cultivars had grains with the same or greater lightness (higher L* value) than those of the carioca bean control cultivars. The development of carioca bean cultivars with grains with an L* value ≥ 53 meets the demand of consumers who prefer very light Table 2: Identification of the experiments that composed each of the six evaluated biennia; number of new lines relative to the previous biennium (new), kept lines for evaluation in the subsequent biennium (kept), excluded lines from the evaluation of the subsequent biennium (excluded), and evaluated lines in the biennium (evaluated); and number of lines with black, carioca, and other grain types evaluated by the Southern Brazilian Common-Bean Network between 2010 and 2022.
Biennia
Identification grains (Ribeiro et al., 2019). Additionally, black bean cultivars with grain lightness equal to or lower (lower L* value) than that of black bean control cultivars were obtained. For black bean cultivars, the color standard used in the selection of superior lines is an L* value ≤ 22, as it characterizes the absence of purplish grains (Ribeiro;Possebom;Storck, 2003). Most of the lines obtained by the research institutions that constitute the Southern Brazilian Common-Bean Network between the years 2010 and 2022 have carioca and black beans with a grain color that meets the market demand, increasing the probability of acceptance of the new cultivars by consumers. Mass of 100 grains showed a negative genetic gain of -0.66 g biennium -1 , which corresponds to a reduction of -2.91% per year (Table 3). However, for Great Northern and pink common bean lines grown in the United States were obtained positive and high magnitude genetic gain estimates for mass of 100 grains, whereas for pinto and red common bean lines were observed low magnitude estimates, using mixed models (Singh et al., 2007).
Positive genetic gain for mass of 100 grains has also been described for black bean lines (Faria et al., 2014) and for common bean cultivars of various grain types and sizes grown in Ethiopia (Bekele et al., 2019;Kefelegn;Mekibib;Dessalegn, 2020), by the regression analysis method. Nonetheless, non-significant genetic gain estimates were found for mass of 100 grains in carioca bean lines (Faria et al., 2013) and for common bean cultivars of different grain types and with upright plant architecture grown in Uganda (Mukayiranga et al., 2022), using the regression analysis method. These results show that the genetic gain for mass of 100 grains in common bean varies according to the grain type, number of lines, evaluation period, environment in which the experiments were conducted, and estimation method. In the present study, the genetic gain estimates obtained for mass of 100 grains reveal that the new common bean cultivars released between the years 2010 and 2022 in the southern region of Brazil have smaller grains.
The decrease in mass of 100 grains can be attributed to the fact that, from biennium 4, which started in the cultivation of the 2016 rainy crop, the average mass of 100 grains of the new lines included in the VCU experiments was lower than that of the control cultivars (Table 4). Therefore, in recent years, many common bean lines with small grains (< 25 g 100 grains -1 ) have been evaluated in the VCU experiments. For the grain types most widely produced in Brazil, carioca and black, the recommended standard mass of 100 grains is from 25 to 30 g, that is, medium-sized grains (Carbonell et al., 2010). This is because medium-sized grains are more accepted by common bean consumers in Brazil (Ribeiro et al., 2019). In this way, the selection strategies used by the breeding programs of the Southern Brazilian Common-Bean Network must be modified so that new carioca and black bean cultivars with medium-sized grains are developed. An option to increase grain size in common bean that needs to be assessed by breeding programs is the introgression of genes from Andean bean pool.
Water absorption exhibited a negative genetic gain of -0.48% biennium -1 , that is, a decrease of -0.55% per year (Table 3). No genetic gain estimates for water absorption using databases obtained over several selection cycles in common-bean breeding programs were found in the literature. However, water absorption displayed zero and positive genetic gain for carioca and black bean lines, respectively, when determined by the multiplicative index, based on data from experiments conducted over two years and in two growing seasons (Ribeiro;Maziero, 2023). The conflicting results observed can be explained by the evaluation period considered to obtain the genetic gain estimates for water absorption. Genetic gain estimates based over a longer experimental period are more consistent and allow a better understanding of the changes made to the technological grain quality traits of common bean over several selection cycles.
The negative genetic gain obtained for water absorption demonstrates that there was a reduction in water absorption capacity in the period during which the grains remained soaked before cooking. In common bean, water absorption and cooking time are negatively correlated, which allows selection for higher water absorption percentage to be efficient for the indirect selection of lines with a shorter cooking time (Kläsener;Ribeiro;Argenta, 2022). The results obtained in the present study indicate that the breeding programs that constituted the Southern Brazilian Common-Bean Network between the years 2010 and 2022 did not prioritize an increase in water absorption.
Cooking time had a genetic gain of -3 s biennium -1 , which corresponds to a percentage of -0.25% per year (Table 3), considered zero. No studies were found in the literature investigating genetic gains for cooking time in common bean lines as estimated from experiments conducted over one or more decades by the breeding program. However, between the years 2016 and 2018, zero genetic gain was observed for cooking time in carioca and black bean lines developed for cultivation in the southern region of Brazil, using the multiplicative index (Ribeiro;Maziero, 2023). In common bean progenies obtained from crosses carried out in East Africa was found a negative estimate of genetic gain for cooking time (Saradadevi et al., 2021). On the other hand, positive genetic gains were obtained for cooking time in carioca bean lines (Dias et al., 2021) and in the selection of white, yellow, cranberry, and carioca bean cultivars (Ribeiro et al., 2021), using selection indices. Therefore, the genetic gain for cooking time in common bean will vary according to the period of evaluation, estimation method, homozygosity level of the lines, genetic variability, and grain type analyzed.
Average cooking time in the evaluated common bean lines ranged from 15 min and 58 s (biennium 5) to 20 min and 56 s (biennium 2) (Table 4), indicating that most of the lines developed by the Southern Brazilian Common-Bean Network between the years 2010 and 2022 are fast-cooking, that is, they have a cooking time ≤ 25 min, according to the criteria established by Santos, Ribeiro and Maziero (2016). In the 2010s, several fastcooking common bean lines were developed by the main breeding programs in Brazil (Santos;Ribeiro;Maziero, 2016;Kläsener;Ribeiro;Argenta, 2022;Ribeiro et al., 2023;Ribeiro;Maziero, 2023), evidencing success in reducing cooking time. The decrease in the cooking time can be associated with the lowest mass of 100 grains of the new common bean cultivars released for cultivation in the southern region of Brazil.
The fast-cooking reference for common bean in 1971, when cultivar Carioca was released for cultivation in Brazil, was 1 h and 35 min (Almeida;Leitão Filho;Miyasaka, 1971). In other words, after half a century of common bean breeding in Brazil, it was possible to reduce the cooking time of new cultivars by 1 h and 10 min. Therefore, the strategies used by breeding programs in Brazil were efficient in decreasing cooking time and gas consumption in the preparation of common bean, which is of great importance in the context of sustainability and food and nutritional security for consumers who use the common bean as their main source of dietary protein.
The genetic gain results show that the common bean lines developed by the Southern Brazilian Common-Bean Network between the years 2010 and 2022 had a decrease in mass of 100 grains and water absorption, but the L* value (lightness) of their grains and cooking time were unaltered (Table 3). The hypothesis is that selection for desirable technological quality traits, especially in carioca and black beans, may have resulted in erosion of genetic diversity, validating previous results described for Andean common bean (Trucchi et al., 2021). This may have been because cultivar Carioca started to be used as a parent in several common-bean breeding programs in Brazil due to its excellent agronomic and culinary traits
iY
= overall mean of genotypes in biennium i; j Y = overall mean of genotypes in biennium j, since j = i + 1; ci Y = overall mean of common genotypes in biennium i; and cj Y = overall mean of common genotypes in biennium j.
Table 1 :
Analysis of variance containing the degrees of freedom (DF), mean squares, coefficient of experimental variation (CEV), and selective accuracy (SA) for the following traits: L* value (L*), mass of 100 grains (M100G), water absorption (ABS), and cooking time (time) in 16 common bean experiments carried out between 2010 and 2021.
Table 3 :
Balance of the genetic and environmental gain -mean and in parentheses percentage, obtained by breeding program of the Southern Brazilian Common-Bean Network between 2010 and 2022 for the traits L* value, mass of 100 grains, water absorption, and cooking time.
Table 4 :
Mean obtained for new lines relative to the previous biennium (new), kept lines for evaluation in the subsequent biennium (kept), excluded lines from the evaluation of the subsequent biennium (excluded), and evaluated lines in the biennium (evaluated) for the traits of L* value, mass of 100 grains, water absorption, and cooking time in the six evaluated biennia.
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Domain: Agricultural and Food Sciences
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Isolation and Characterization of Lactic Acid Bacteria Isolated from Fermented Food of North-West Himalayas
Lactic acid bacteria (LAB) are ubiquitous and are one of the major microbial groups involved in the fermentation of various types of food. They are the most dominant microbes present in milk or milk products and fermented foods where they play vital roles in both the manufacturing and ripening processes. Kaladhi is one of the traditional fermented products of the North-West Himalaya region. It is a hard and dry cheese. In our research, a total of 9 isolates was isolated and was evaluated on the basis of preliminary characterization viz. morphological as well as biochemical characterization and was examined for their antagonistic activity against following pathogens. On the basis of their maximum antagonistic potential against food-borne pathogenic bacteria, isolate K1 is characterized by 16S rRNA sequencing. The isolate was identified as Lactobacillus paracasei subsp. Tolerans strain NBRC 15906 K1|MN814072|. This research was aimed to study the unexplored microflora of Kaladhi and to determine its probiotic potential.
iNtROduCtiON
Microorganisms are present almost in every habitat because of their ubiquitous property. Among them, some microbes exhibit various beneficial properties viz. in improving human health or in food production. Probiotics are one of those microbes that have an extensive role in maintaining the host's health and controlling some diseases. According to FAO/ WHO, probiotics are: "Live microorganisms which when administered in adequate amounts confer a health benefit on the host". They are also considered as "friendly bacteria" or "good bacteria". Probiotic bacteria are non-pathogenic and non-toxic microbes and show important functions for well being and health of the host 1 . Therefore, it's important to maintain the ecological flora in order to prevent diseases, especially infections of the gastrointestinal tract 2, 3 .
The fermented foods are one of the major sources of probiotics 4 . The fermented foods are that food that has undergone a lactic fermentation process in which the natural microflora feeds upon the sugar and starch present in the food creating lactic acid. Traditional fermented food products are important in nutrition as sources of carbohydrates, proteins, fibers, minerals and vitamins 4 .
In India, about 50-55% of milk is converted into several traditional products utilizing various processes such as fermentation, coagulation and desiccation 5 . Kaladhi is one of the culinary preparations of dairy in Jammu and Kashmir state 6 .
Kaladhi is a traditional fermented food product of state Jammu and Kashmir (Fig. 1). It is prepared by coagulating the milk and the coagulum was working out into the pat and finally small balllike product is prepared which are manually spread out to a circular shape and then dried into the sun light to absorb the moisture. Ahmad in his studies defined kaladhi as an acid coagulant product that is prepared by directly acidifying the milk with some coagulating agents like organic acids 7 . The product is made either from buffalo's or cow's milk. Kaladhi is also known as 'Maush kraer' in Kashmir division of the state. Kaladhi doesn't require the use of rennet or any starter during its preparation. The most popular coagulant used traditionally for the Kaladhi preparation is tartaric acid but either citric acid or whey water can also be used to coagulate the raw or boiled milk. It is consumed after frying it with some suitable frying medium along with spices and condiments. This product is believed to possess anti-diarrheal and anti-cold properties besides being a salubrious food, thus have tremendous market potential 8 .
Nutritional composition of Kaladhi includes 412kj Energy, 3.3gms of Carbohydrate, 2.67 gms. Sugar, 11.12 gms of Proteins, equiv. 5% of Vitamin A, 83mg Calcium, 0.07mg Iron, 8mg Magnesium, 159mg Phosphorus, 104mg Potassium, 3.64mg Sodium and 0.40mg Zinc 16 . So Kaladhi possess so many nutrients and can be healthy to consume but because of its low pH, its shelf life is limited caused by various microbes especially molds 17 . Kaladhi cheese can be a source to isolate novel probiotics but unpasteurized cheese also produces food borne-pathogens like S. aureus, L. monocytogenes, Salmonella and E. coli strains 18 .
Raw milk and traditional fermented foods act as highly rich environments for a diverse and indigenous microbiota, including LAB, that further contribute to the bio-preservation and development of nutraceutical or functional final products. Among LAB, the Lactobacillus strains are predominantly exploited to acquire the probiotic properties as well as utilized in the form of adjunct cultures. Attributing to their historical view of safe use and natural presence in the human gut, they are generally regarded as safe (GRAS). Moreover, several species of Lactobacillus have attained the status of qualified presumption of safety (QPS) status.
Such food products act as an alternative source of novel probiotic candidates that can be utilized for the manufacturing of functional probiotic products that are further protected from gastrointestinal stress. So these foods can be a way to represent novel candidates of probiotics.
As the microflora of this product is not that much explore so in this research an attempt was made to isolate the potential probiotic strains in order to meet the promising results as therapeutic effects.
MATeRIALS ANd MeTHOdS Chemicals
All the chemicals utilized in this study were obtained from HI-Media and of analytical grade.
Sample collection
Samples of Kaladhi were collected from the North-West Himalayas region mentioned in Fig. 1.
Isolation of LAB
1gm of the sample was diluted with 9ml of sterile water and homogenized for the 60s. The homogenates were followed by serial dilution with sterile distilled water and then plated on the MRS (De Man, Rogosa, and Sharpe media) plates. Incubation was given at 37°C for 24 hrs. After incubated plates, individual similar colonies were selected and further purified by using the streak method on the selected medium 13 .
Phenotypic and biochemical characterization
Preliminary identification of LAB strains was done based on their potential to grow in MRS broth, the positive gram staining, absence of endospores. MRS is a media used for the cultivation of Lactobacillus species. Biochemical studies of strains were done to evaluate the production of Catalase, oxidase, methyl red voges proskauer (MR-VP test), casein hydrolysis and starch hydrolysis tests 14 .
Genotypic characterization
Molecular Identification of the Selected LAB Isolates: The bacterial strains were identified at the genomic level by using the 16s rRNA gene technique.
Antibacterial assay
The antagonistic activity of each isolates against spoilage causing microbes i.e pathogenic test indicators were analyzed by using the agar well diffusion assay. The results were examined in the terms of zone of inhibition around the wells. Test indicators used are Klebseilla pneumonae, Enterococcus faecalis, St L. paracasei subsp. Tolerans reptococcus dysgalactiae and Pseudomonas aeruginosa 9 .
Haemolytic activity
The haemolytic activity of potential probiotic isolates was determined by the method of Marakoudakis 10 . The isolates were grown on respective broth for 37°C for 24h and were streaked on the blood agar plates that were supplemented with 5% (v/v) of whole human blood and the plates were incubated at their respective temperatures then examined on the basis of zones 10 .
Inter compatibility testing
Inter compatibility of the bacterial isolates was checked by using the Cross streak method 11 .
Acid tolerance assay
Survival of lactobacilli at low pH was checked by inoculating 1% of culture in 20ml of respective broth with the pH of 2.0 and 5.0 and incubation was given at 37°C for 24 hrs. Growth was measured by taking optical density at 620nm 12 .
Co-aggregation assay
Co-aggregation ability of the strains to form a barrier against pathogens was assessed according to Del Re 19 .
Results ANd disCussiONs Isolation and characterization of LAB
A total of 9 isolates were isolated from the sample Kaladhi and were recognized on the basis of morphological characteristics and biochemical analysis. Physiological and Biochemical characterization of the microbial isolates had been done and their characteristics were noted down in Table 1-2. Most of the microbial strains were off white Gram-positive, rod-shaped and some of them gave negative Catalase and oxidase results and hence considered as lactobacilli. All the isolates showed negative results of MR-VP test and were not able to hydrolyse amylase
Molecular Identification of the Isolates
The best-selected LAB isolates on the basis of their antagonistic effect against selected pathogenic bacteria were identified at the genomic level by 16srRNA sequence analysis. The 16S rRNA sequence of isolate K1 showed its close resemblance (98.7%) with other Lactobacillus paracasei strains available in the GenBank database (National Centre for Biotechnology Information (NCBI)). Therefore, this isolate was designated as L. paracasei subsp. Tolerans K1. The sequence of K1 was deposited in GenBank with accession number MN814072. Phylogenetic relationship of L. paracasei subsp. Tolerans K1 based on 16S rRNA sequencing analysis is shown in Fig. 2.
Antimicrobial activity
Many of the potential LAB isolates exhibited antibacterial effect towards food spoilage as well as pathogenic bacteria viz. Klebseilla pneumonae, Enterococcus faecalis, Streptococcus dysgalactiae and Pseudomonas aeruginosa. Isolates K-1 and K-3 inhibited most of the pathogenic micro-organisms. The data is shown in Table 3.
Hemolytic activity
The hemolytic activity of isolates was recorded by the observation of a clear zone of hydrolysis around the bacterial colonies (b-haemolysis), a partial hydrolysis or greenish zone shows a-haemolysis, or no reaction (haemolysis). No zone is shown by any isolates in our present study which shows that the isolated isolates can be consumed by humans or animals in any form.
Inter compatibility testing
This test was determined by the cross streak method. It was done to check the intercompatibility of strains in order to formulate the probiotic consortia. Every strain showed 100% compatibility with each other.
Acid tolerance assay
As pH medium of the gastrointestinal tract is acidic, so in order to survive in a raucous environment of the gastrointestinal tract, probiotic strains must show resistance to low pH. So the effect of acidic pH was studied to determine the potential of strains at low pH of the stomach. So in this experiment, at pH 2 k1 strain showed excellent results after the incubation of 48 hours. Table 4 shows the result of the acid tolerance assay of all strains.
Co-aggregation
Co-aggregation ability is the process by which 2 strains attached to one another via specific molecules. Probiotic strains shows Co-aggregation activity against pathogens by forming a barrier and thus prevents colonization. Co-aggregation activity of probiotic strains was evaluated against test indicators and shown in Table 5.
CONClusiONs
Our present study was an attempt to isolate the potential isolates from the Kaladhi, a traditional fermented food of northwest Himalayas. Among all of the isolates, L. paracasei subsp. Tolerans showed outstanding results by exhibiting antimicrobial substances and have the ability to survive at the acidic medium of the stomach. These isolates could be considered as a potential probiotics due to their antagonistic effect and can be used in nutraceutical or functional foods due to their therapeutic effect.
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Domain: Agricultural and Food Sciences
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Probiotic Properties and Anti-inflammatory Activity of Bacillus spp. Isolated from Ethnically Fermented Soybean
Bacillus spp. probiotics used as feed additives can form spores and tolerate the harsh conditions of the human digestive system and are beneficial for the treatment of inflammatory bowel syndrome. Since reports on probiotics and anti-inflammatory properties of Bacillus spp. isolated from the fermented food of Northeast India have not been explored much. The present study focused on Bacillus spp. BN5, AY5, and AN8, possessing these desired properties. In the probiotics study, the isolates were screened for their tolerance to acid and bile salt, auto-aggregation, hydrophobicity, cholesterol assimilation, antibiotic resistance, and antagonistic properties. It was found that these isolates possessed the desirable probiotic traits. The Bacillus spp. culture and their supernatant were also screened for their ability to reduce LPS-induced inflammation in murine macrophage (RAW 264.7) cells. All the Bacillus spp. culture and their supernatant treatments were found to reduced the Nitric oxide (NO) production by LPS-induced cell lines. The supernatant of LPS-induced cell lines were also analyzed to measure the level of inflammatory cytokine production. It was found that the levels of TNF-a , IL-6, and IL-1 b were reduced after co-treatment with LPS and Bacillus spp. culture or LPS and Bacillus spp. supernatant. Results suggested that the Bacillus spp. are potential probiotic candidates with anti-inflammatory properties.
INTRODUCTION
The North-Eastern Region of India, inhabited by different indigenous tribes, is characterized by unique socio-cultural and dietary habits. The people of the region practice their traditional technology for the preparation of fermented foods and beverages. Traditional fermentation of soybean is popular in the region, and the product is known by different names such as 'Tungrymbai' in Meghalaya, 'Hawaijar' in Manipur, 'Bekang' in Mizoram, 'Akhone' in Nagaland and 'Peruyaan' in Arunachal Pradesh. These products are spontaneously fermented without any starter culture and are known to have rich microbial diversity involved in the fermentation process. 1,2Some of the microbial cells present in these fermented foods are probiotic in nature which is beneficial to humans. 3nalysis of parameters like acid and bile tolerance, cell hydrophobicity, auto-aggregation, antimicrobial properties, and resistance to antibiotics provide a better understanding of probiotic properties and health-promoting benefits. Studies show that Bacillus spp.][6][7][8] Thus, Bacillus spp.have an advantage over other non-spore-forming bacteria because of their ability to survive in extreme environmental conditions such as high temperatures, acidic environments and dry and undernutrition environments. 5,8,9,10owever, in vitro screening for potential probiotic isolates required a specific characteristic, such as resistance to gastric acid and bile salt with adhesion activity to the human epithelial cells. Cell hydrophobicity, autoaggregation, and antimicrobial activity are also required to be tested for probiotics. 5,11robiotics play an important role in chronic intestinal diseases because of their role in immune system modulation and antiinflammatory response. 124][15] Higher level of Lipopolysaccharides (LPS) of pathogenic bacteria enhances inflammation and other bowel problem that lead to Inflammatory bowel Syndrome (IBD). In response to this, epithelial cells and macrophages produce NO to induce an immune response. The reduction in NO production by the test isolates can be used as an indication of reduced inflammation by the isolates. 16nderstanding the traditionally fermented foods, their microbiology, and the associated activity holds importance from the perspective of the dearth of science on these ethnic products. Thus, the present study was aimed at screening Bacillus spp., which are spontaneously occurring bacteria in traditional foods, for their probiotics properties and also in studying the in vitro anti-inflammatory properties such that they can be bio-prospected for large-scale exploration aided by starter culture fermentation technology.
Isolation of Bacillus spp.
The selected Bacillus spp.from ethnically fermented soybean products, namely, 'Akhone' and 'Bekang' were isolated using serial dilution techniques and plated on Yeast Malt agar and Nutrient agar. The colonies were randomly selected, and pure cultures were maintained for identification.
Molecular characterization
DNA isolation was performed using a standard kit (HiPurA 96 Bacterial Genomic DNA Purification Kit, Himedia, India) for identification of the isolate. DNA was used for amplification of 16S rRNA using universal primers, 27F (5'-AGAGTTTGATCCTGGCTCAG-3') and 1492R (5'GGTTACCTTGTTACGACTT-5') PCR mixtures (25 µL) contained approximately 40 ng template DNA, 2 µM each of forward primer (27F) and reverse primer (1492R) 1.75 mM of MgCl 2 (Taq Buffer), deoxynucleoside triphosphates (250 µM each of dATP, dCTP, dGTP and dTTP) and 0.3 U Taq polymerase. DNA amplification was carried out using the GeneAMP PCR system 9700 (Applied Biosystems, CA, USA), and approximately 1,500 bp were amplified. The amplified DNA samples were sequenced, and the DNA sequences obtained were used to perform blastn analysis with the Ez Taxon database. 17Sequences were submitted to the NCBI BankIt, and the accession numbers were obtained.
Tolerance to acidic condition
Tolerance to low acidic conditions was determined by the method of Nithya and Halami. 18Bacillus spp. Cultures were incubated in LB broth at 37°C for 18 hours. After incubation, the bacterial cells were harvested by centrifugation at 8000 rpm at 4°C for 15 minutes. The pellets were washed once with Phosphate buffer saline (PBS) of pH 7.2±2 followed by resuspension in PBS of pH 3. Cell suspensions were incubated in a shaker incubator for 0, 1, 2, and 3 hours at 37°C. After the incubation period, the culture was plated on LB agar, and the counts were expressed as CFU/ml. Percentage of survival was calculated using the formula: survival % = x100 (CFU/ml) of cell survived (CFU/ml) of initial cells inoculated
Tolerance to Bile salt
Bacillus spp.cultures were incubated at 37 °C for 18 hours followed by centrifugation for 15 minutes at 8000 rpm at 4°C. Pellets were washed and resuspended in 0.85% NaCl. The bacterial suspension was inoculated into LB broth with 0.3% bile salt concentration and incubated for 0, 1, 2, and 3 hours at 37°C. Viable plate counts were determined by plating on LB agar plates after each incubation period. 19
Cell hydrophobicity
Cell hydrophobicity of the selected Bacillus spp. was determined according to the method followed by Lee et al. 5 with minor modifications. The bacterial culture was incubated for 24 hours and then centrifuged at 13000 rpm for 3 minutes. The Bacillus spp.supernatant was discarded, and the pellet was washed twice and then suspended with PBS buffer saline (pH 7.4). One ml of the cell suspension was measured for optical density (OD) in a spectrophotometer at 600nm, and the value was used as A o . An equal volume of solvent (xylene) was added and vortexed thoroughly for 5 minutes. The mixture was then allowed to separate into two phases by keeping it undisturbed at 37°C for 30 minutes. The aqueous phase was taken, and absorbance was observed at 600 nm, and the value obtained was taken as A 1 .
Auto-aggregation
Auto-aggregation of Bacillus spp. was performed according to the method of Lee et al. 5 An overnight bacterial culture was centrifuged at 13000 rpm for 3 minutes. Pellets were washed twice with phosphate buffer saline (pH 7.4). The pellet was then re-suspended in the Bacillus spp.supernatant and vortexed for 50 seconds. Absorbances were measured every 0, 1, 2, and 3 hours at 600nm.
Assimilation of cholesterol
Cholesterol assimilation by the strains was determined as described by Rudel and Morris. 20The bacteria were cultured on LB broth for 18 hours at 37°C in a Shaker incubator.1% of the bacterial culture was inoculated to the fresh media containing cholesterol (100µg/ml) and 0.2% bile salt and incubated at 37°C in a shaker incubator for 24 hours. Media without cholesterol was used as a control. The cultures were then Centrifuged at 9000 X g at 4°C for 15 minutes. To a 1ml of the bacterial supernatant in a test tube, 1ml of KOH (33% wt./Vol.)and 2ml of absolute ethanol were added, and the mixture was then vortexed for 1 minute, followed by heating at 37°C for 15 minutes and then cooled to room temperature.2 ml of distilled water and 3 ml of hexane were added and vortexed for 1 minute. The mixture was allowed to stand till the hexane layer was properly separated.1ml of Hexane layer was transferred to a fresh test tube and heated at 65°C in a water bath till it gets evaporated. Then 2ml of ortho-phthalaldehyde reagent was immediately added to the dried residue and vortexed for 10 minutes. The dissolved mixture was then mixed with 0.5ml of Conc. H 2 SO 4 and vortexed for 1 minute. The mixture was kept in the dark at room antibiotic disks were placed with an and incubated for 24 hours. The diameter of the inhibition zone was recorded.
Antagonistic activity
The antagonistic activity was performed by minor modification of the agar well diffusion assay method of Valgas et al. 21Bacillus spp.were tested against E. coli MTCC723, Klebsiella pneumoniae MTCC109, and Staphylococcus a u r e u s M T C C 2 9 4 0 . T h e t e s t c u l t u r e and Bacillus spp.were incubated for 24 hr at 37°C. Test cultures were standardized to McFarland standard no.0.5 and uniformly swabbed onto MHA plates. Each agar plate was punched with sterile pipette tips to form wells. One ml of Bacillus spp.suspensions were then centrifuged at 10,000g for 20 minutes. The Bacillus spp.supernatant was then filtered through a 0.2 µm sterile filter.100 µl of the Bacillus spp.supernatant was then added to each well. A Chloramphenicol disc was used as a reference. The plates were then incubated at 37°C for 24 hours. Cholesterol % assimilated=100-cholesterol % remained in sample
Susceptibility to antibiotics
Antibiotic susceptibility for the selected Bacillus spp. was evaluated by the method followed by Nithya and Halami. 18Antibiotic disks like Tetracycline, Vancomycin, Erythromycin, Penicillin-G, Gentamycin, and Chloramphenicol were used to screen for the resistance of bacterial isolates. An overnight culture of bacterial isolates was standardized to an OD range of 0.08 to 0.1 at 600nm wavelength. The cultures were then evenly swabbed onto Mueller Hinton agar plates, and the
MTT assay
The stock RAW 265.7 cells were activated in DMEM supplemented with 10% FBS and 1% P/S solution in the presence of 5% CO 2 in a humidified chamber at 37°C for three consecutive transfers, and the cells were grown and passaged till 80% confluence. Then the confluent macrophages were seeded in a 96-well cell culture plate followed by the treatment with Bacillus Spp. at different OD (2, 1.5, 1, and 0.5) and Bacillus spp.supernatant (1, 0.5, and 0.25 mg/mL). The cells were incubated at 37°C under 5% CO 2 in a humidified incubator. After 24 hours of incubation, MTT (03-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) was added to a final concentration of 0.5 mg/mL followed by 4 hours incubation under 5% CO 2 in the dark at 37°C. Thereafter, the medium was removed, accompanied by 100 µl DMSO formazan crystal dissolution. The absorbance was measured at 570 nm using a microplate reader (M200 PRO, Tecan Life Science). 22
Assessment of Bacillus spp. on LPS-induced inflammation in RAW 264.7 macrophages
Confluent macrophage cells were seeded in a 48-well plate (1x10 5 cells) and allowed to achieve confluence as described above. Then the cells were treated with 1 µg/mL LPS and each Bacillus spp.culture (0.5 OD) or Bacillus spp.supernatant (0.25 mg/mL) for 16 h in a humidified incubator at 37°C under 5% CO 2 . This was followed by an estimation of nitrite through the Griess reagent method. The optical density was measured at 540 nm.
Measurement of TNF-a, IL-6, & IL-1b cytokines
The supernatant from the various cell line treatments were collected, and the levels of TNF-a, IL-6, & IL-1b were measured using enzyme-linked immunosorbent assay (ELISA) by using commercially available kits as per the manufacturer's instructions (Elabscience, USA).
Statistical analysis
The statistical significance among different groups was performed by one-way ANOVA followed by Tukey's post hoc test. Graph Pad prism 9.0.0(121)Software was used to analyze the data. Statistically, the significance was considered to be P ≤ 0.05.
Identification of Isolates
The marker gene 16S rRNA was sequenced and the isolates were identified as Bacillus siamensis, Bacillus tequilensis and Bacillus subtilis.
Phylogeny
The phylogenetic tree for 16S rRNA gene sequences was constructed using the neighbor-joining method in MEGA-X software with Deinococcus radiodurans taken as an outgroup organism. The dendrogram showed clustering of isolates to the closest match from the database. Isolates, AY5 clustered with Bacillus siamensis, AN8 clustered with Bacillus tequilensis, and BN5 clustered with Bacillus subtilis (Figure 1).
Tolerance to acidic condition and bile salt
Initial bacterial inoculum, inoculated at 0 hours, served as a control to measure the survival percentage of Bacillus spp. at 1, 2, and 3 hours. It was observed that all the Bacillus spp.tested showed high tolerance to acidic conditions. After 3 hours of incubation at pH 3, isolate AY5 showed the highest survival percentage (63.9%) in acidic conditions, followed by the isolates BN5 (35.1%) and AN8 (19.2%) (Figure 2A).
Cell Hydrophobicity
A l l t h re e i s o l ate s s h o we d c e l l hydrophobicity. The isolate BN5 showed comparatively higher hydrophobicity (16%), followed by AN8 (12%) and AY5 (9.4%) (Figure 2C).
Auto-aggregation
All the tested Bacillus spp.showed a significant auto-aggregation pattern at different intervals of the incubation period. The isolate BN5 showed the highest auto-aggregation of 67.0% after 3 hours incubation period. The isolate AY5 showed significant auto-aggregation of 42.2 % after 3 hours of incubation. Similarly, isolate AN8 showed the highest auto-aggregation of 35.8% after 3 hours incubation period (Figure 2D).
Susceptibility to antibiotics
All the tested isolates are susceptible to Tetracycline, Vancomycin, Erythromycin, Penicillin G, Gentamycin, and Chloramphenicol except for the isolate AN8, which showed resistance against penicillin-G (Table 1).
Effect of Bacillus spp. and Bacillus spp. supernatant on RAW264.7 cell viability
T h e c e l l v i a b i l i t y a f t e r exposing Bacillus Spp.(AY5, BN8 and AN8 and Bacillus spp.supernatant on the RAW 264.7 macrophages at different OD (2, 1.5, 1 and 0.5) and concentrations (1, 0.5, and 0.25 mg/mL), respectively, are illustrated in Figure 3A and Figure 4A. Cells exposed to Bacillus Spp. at 1-2 OD (6X10 7 / ml) showed significant loss of cell viability. In contrast, no loss of viability was observed when the macrophages were treated with Bacillus spp. at 0.5 OD relative to the control cells. In case of Bacillus spp.supernatant, treatment at 0.25 mg/mL gave the highest viability, whereas treatment at 0.5 and 1mg/mL exhibited a loss in cell viability. With this observation, we chose 0.5 OD for Bacillus spp.and 0.25 mg/mL for Bacillus spp.supernatant for subsequent experiments.
Effect of Bacillus spp. and its Bacillus spp. supernatant treatment on nitrite synthesis in RAW 264.7 macrophages induced by macrophages
The effect of Bacillus spp.and Bacillus spp.supernatant on LPS-induced inflammation in macrophages was investigated by assessing (nitric oxide) NO response, which is one of the essential inflammatory parameters. It was found that LPS stimulation resulted in a remarkable elevation of NO response ten times higher than control (Figure Data were presented as mean ± SEM; n= 3 and evaluated by one-way ANOVA followed by Tukey's post hoc test 3B and Figure 4B). This NO production by LPSactivated cells appeared to be reduced by Bacillus spp.and Bacillus spp.supernatant, suggesting a promising anti-inflammatory activity.
Cytokine analysis in the supernatant of RAW 264.7 cells
The generation of TNF-a, IL-6, & IL-1b by RAW 264.7 macrophages stimulated with LPS for 16 hours was investigated. As shown in the figure, the TNF-a, IL-6, & IL-1b levels were significantly elevated following stimulation of the cells with LPS which was further reduced in all the treatment groups (Figure 3C-3E and Figure 4C-4E).
DISCUSSION
The isolates were identified based on their closest match by using the EzTaxon database. The accession numbers for the sequence were obtained from NCBI.16S rRNA sequences were submitted in the NCBI BankIt database under the Genbank ID: MK641490, MK641489, and MK332360 (Table 2).
The ability of the microorganisms to inhabit the gastrointestinal tract is depicted by their ability to withstand the stress condition generated by the physical and chemical mechanism of the host. 11,23Therefore, the ability of Bacillus spp. AY5, BN5, and AN8 to remain viable and tolerate low pH and bile salt concentration is an indication of their ability to thrive under the stressful condition of the gastrointestinal tract.
Cell hydrophobicity is the measurement of the capacity of any bacterial cell to adhere to the hydrocarbon, which holds the ability of the bacterial cells to adhere to the epithelium of the digestive tract, an important property for the first contact between the bacteria and the host cell. 24The ability of the isolates AY5, BN5, and AN8 to adhere to hydrocarbon (xylene) indicates their ability to adhere to the epithelial cells of the human gut.
A u t o -a g g r e g a t i o n b e t w e e n microorganisms of the same strain is an important factor, especially in the human gut, as it protects the bacteria from external stress, and it also relates to the ability of the bacterial cells to withstand the stress inside the gastrointestinal tract, which is an important property of probiotics. 25The ability of the test isolates, AY5, BN5, and AN8, to autoaggregate supports their probiotics nature.
Coronary heart disease develops because of elevated cholesterol levels in the blood, and the condition is called Hypercholesterolemia. Therefore, lowering cholesterol levels is important to prevent such diseases. 19,26The capability of these isolates to assimilate cholesterol, especially under stimulated intestinal conditions, indicates their potential as a cholesterol-lowering agent in the future.
The resistance of AN8 to Penicillin-G may collaborate with the findings of Hoa et al., 27 who reported the resistance of Bacillus spp.against Penicillin G, as this may be an intrinsic characteristic useful for Bacillus taxonomy, and such resistance may serve the purpose of restoration of normal microbial flora during antibiotic therapy. 28Thus, the resistance of bacteria to antibiotics does not always constitute a safety concern unless it carries a mobile genetic element like the Tetracycline resistance gene, which may constitute a reservoir of resistance for gut pathogens.
Antagonistic activity against pathogens is one of the most important properties of any isolates when tested for probiotic properties of any probiotic strain. 29These properties indicate the ability of microorganisms to produce antimicrobial compounds that inhibit pathogenic bacteria, which is beneficial for the host. 30Thus, the isolates which showed inhibition properties indicate their ability to inhibit gut pathogens.
In the murine RAW 264.7 macrophages, LPS induces NO production. Furthermore, LPS is well known to cause an inflammatory response by activation of toll-like receptor (TLR4) followed by the release of other pro-inflammatory mediators such as IL-6, IL-1b, and TNF-a. Hence, RAW 264.7 cells are an excellent model for screening and further analysis related to anti-inflammatory properties. 31The cytokines such as TNF-a, IL-6, and IL-1b are pro-inflammatory in-vitro and in-vivo, which are chiefly produced by macrophages and are believed to induce an inflammatory response. 32hese findings concord with those of Diao et al. 33 and Kim et al., 34 who used an anti-inflammatory study of Bacillus spp.and their polysaccharides using RAW 264.7 cells.
CONCLUSION
The characterized isolates showed credible probiotic potentials through autoaggregation, cell hydrophobicity, cholesterol assimilation, antimicrobial properties, and susceptibility to antibiotics. They also showed the ability to withstand stimulated in-vitro stress conditions like bile salt tolerance and acidic condition. The Bacillus spp.and Bacillus spp.supernatant possess potent anti-inflammatory activity by reducing the production of Nitric oxide, pro-inflammatory cytokines, and their mediators. Considering the current findings, it can be concluded that the isolates under study possess the required probiotic properties and anti-inflammatory activity. The study offers scope for exploration of traditionally fermented foods for bioprospection of potential isolates as probiotics and also as starter cultures in traditional fermentation practices.
Figure 1 .
Figure 1. Phylogenetic tree of Bacillus spp.constructed using Neighbor-joining method using MEGA-X
Figure 3 .
Figure 3. Effect of the Bacillus spp. on (A) Cell viability, (B) NO production; (C) TNF-α; (D) IL-6 and (E) IL-1β measured in supernatant of LPS-stimulated RAW 264.7 cells.'a' relative to the control, 'b' relative to the LPS (lipopolysaccharide). Data were presented as mean ± SEM; n= 3 and evaluated by one-way ANOVA followed by Tukey's post hoc test
Figure 4 .
Figure 4. Effect of the lyophilized Bacillus spp.supernatant on (A) Cell viability; (B) NO production; (C) TNF-α (D) IL-6 and IL-1β measured in supernatant of LPS-stimulated RAW 264.7 cells.'a' relative to the control, 'b' relative to the LPS (lipopolysaccharide). Data were presented as mean ± SEM; n= 3 and evaluated by one-way ANOVA followed by Tukey's post hoc test
Table 2 .
Potential isolates and their closest match based on 16S rRNA sequences analysis
Table 1 .
Susceptibility test of Bacillus spp.against different antibiotics *R= resistance
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Domain: Agricultural and Food Sciences
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ACCEPTED AUTHOR VERSION OF THE MANUSCRIPT: The potential role of MYOM1 and ATGL genes in pig production improvement
In the present study, two missense variants within ATGL (rs331307082) and MYOM1 (rs326001585) genes were tested for their potential usage as genetic markers related to pig production traits. The genotyping was performed on 519 pigs representing 990 synthetic sire line. The association analysis indicated that ATGL gene affected the panel of fattening parameters (test daily gain, age at slaughter), meatiness traits (meat percentage in the carcasses; the weight of loin, ham and primary cuts, and loin eye area), and meat quality characteristics (water exudation). In turn, MYOM1 polymorphism was related to loin weight, the weight of primary cuts and weight of loin backfat. Pigs with AA genotype were characterized by significantly higher loin and primary cut weights compared to opposite homozygotes GG (p<0.05). The observed differences were 2.29 kg and 1.2 kg, respectively. Moreover, despite higher meatiness, AA animals together with AG were characterized by lower weight of loin backfat (p<0.05) and average backfat thickness (p<0.1) compared to GG pigs. The MYOM1 polymorphism did not affect pork quality traits. The results allowed us to propose the new genetic markers which may be used in pig selection to obtain appropriate meatiness and fatness level in carcasses without decreasing meat quality.
and apply genetic markers which will allow performing selection toward modification of one trait without changing levels of the others.
Despite trying to apply genomic selection in the commercial pig breeding (Knol and Nielsen, 2016), the single genes are still being tested for their usefulness in breeding work and importance for accelerating the livestock progress. The limitation of genomic selection in pigs is still a relatively high cost of single analysis (Samorè and Fontanesi, 2016). The highthroughput SNP data obtained by RNA sequencing was applied to identify the set of genes with a potential high effect on essential production traits in the pig industry (Piórkowska et al., 2018). Among others, two missense variants within MYOM1 and ATGL genes were detected and proposed as a candidate for carcass parameters, backfat thickness and selected fattening traits (Piórkowska et al., 2018). The MYOM1 gene encoding for myomesin-1, is responsible for sarcomere assembly via stabilization of the three-dimensional conformation of the thick filaments (Lange et al., 2005). Myomesin, together with obscurin and obscurin-like-1 proteins form the M-line and are responsible for the regulation of force distribution exerted by the thick filaments during contraction (Fukuzawa et al., 2008). Moreover, myomesin in a complex with myosin and titin anchors thick filaments in the A-band . In turn, the ATGL gene (also known as PNPLA2) encodes adipose triglyceride lipase, which catalyzes the degradation of triacylglycerols of lipid droplets in the adipocytes and nonadipocyte cells (Zimmermann et al., 2004). This lipase is involved in energy homeostasis by playing a role in the body's response to starvation. Under conditions of reduced caloric intake, ATGL activates triglyceride hydrolysis ensuring delivery of free fatty acids to other tissues, which can be used as an energy source (Smirnova et al., 2006).
Taking into account the important function of both genes and previous findings, we hypothesized that MYOM1 and ATGL genes could be considered as potential genetic markers related to pig production traits. In the present study, the novel, mid-density SNP genotyping method using the Quant Studio 12K Flex Real-Time PCR System with the Open Array Block was applied to determine genotypes within MYOM1 and ATGL genes. The suitability of MYOM1 and ATGL as markers was tested in pigs of 990 line that were selected for meat content and improved fattening traits.
Animals
The analysis was carried out on 519 female pigs representing 990 synthetic line. The pigs were characterized by low relationship (4.20 individuals per sire and 1.54 per dam). The analyzed pig line was established in Poland in the 1970s based on six breeds (Polish Large White, Belgian Landrace, Duroc, Hampshire, Landrace of German and British origin) to obtain the top sire line for crossing in pig breeding. The 990 individuals are used in the pig meat industry to produce fatteners characterized by high meatiness parameters together with good meat quality characteristics and fattening performance (Różycki and Dziadek, 2012). In the Polish populations of sire breeds, the 990 line ranks second in terms of usage behind the Pietrain pigs.
All investigated pigs were maintained at two breeding stations under the same environmental and feeding conditions. Pigs were kept in individual pens, fed ad libitum from 30 kg to 100 kg (±2.5 kg) and weighed daily throughout the fattening period. When pigs reached 100 kg (±2.5 kg), they were slaughtered, and after 24 h of chilling, right half-carcass was dissected. For each animal the panel of traits has been evaluated: test daily gain (g/day); feed: gain ratio (kg/kg) and age at slaughter (day); carcass yield (%); ham / loin weight (kg); the weight of primary cuts (kg); loin eye area (cm 2 ); meat percentage in carcass (%); ham weight without fat and skin (kg); average backfat thickness (cm); the weight of loin backfat (kg). Moreover, the meat quality characteristics were measured: meat color (L*lightness, a*redness, and b*yellowness; Minolta CR-310 spectrophotometer), pH estimated in loin and ham muscles (longissimus dorsi and semimembranosus; respectively) measured at 45 min (pH45) and 24 h (pH24) after slaughter (pH-metr pH-STAR CPU; Matthäus, Pöttmes, Germany), IMFintramuscular fat content (the Soxhlet method), and WEwater exudation (the Grau-Hamm method). The exact procedure of fattening parameters, slaughter procedure and production traits evaluation was described previously (Żak and Tyra, 2013). All pigs were free of RYR11843T allele.
Statistical analysis
The association between evaluated traits and both SNPs in ATGL and MYOM1 genes were estimated using General Linear Model (GLM) procedure with Tukey's test (SASv.8.02), average, di is the fixed effect of the i genotype, bj is the fixed effect of the j test station, a(xij) is the covariate with the weight of the half-carcass for the performance of carcass traits only and eij is the random error. To estimate significant differences between means, the least square means (LSM) test was used. All results are shown as LSM±SE.
Genotype and allele distribution
The allelic discrimination method allowed identifying all three genotypes for both ATGL c.392G>A and MYOM1 c.2539G>A polymorphisms ( Figure 1). The call rate for ATGL was 99.4% and for MYOM1 99.0%, respectively.
For ATGL polymorphism, the most abundant were GG pigs (72%), while the opposite homozygotes were only 8%. Similar genotype distribution was obtained for MYOM1 c.2539G>A where GG pigs represent 64% of the whole population and AA genotype was carried by 5.4% of the pigs. Minor allele frequency (MAF) was 0.18 for ATGL and 0.21 for MYOM1 polymorphisms. According to both polymorphisms the analyzed population was in Hardy-Weinberg equilibrium.
ATGL c.392G>A polymorphisms
The c.392G>A missense variant within ATGL gene showed significant association with all analyzed slaughter traits corresponding to meatiness: meat percentage in the carcass (%); the weight of loin, ham and primary cuts, and loin eye area (Table 2). Compared to opposite homozygotes, the AA pigs had 3.7 cm 2 greater loin eye area (p<0.01); 0.25 kg heavier ham weight and 1.1% higher percentage of meat in carcasses (p<0.05). Both AA and AG genotypes were characterized by the highest values of loin weight (p<0.05) and the weight of primary cuts (p<0.01). Moreover, the AA pigs were characterized by lower average backfat thickness compared to both AG and GG animals. Taking into account fattening parameters, AA animals had lower average daily gain and at the same time higher age of slaughter (p<0.05) ( Table 3). Among all analyzed meat quality traits, the analyzed polymorphism within ATGL gene was significantly associated with water exudation (Table 4).
MYOM1 c.2539G>A polymorphism
The statistical analysis showed that MYOM1: p. Val847Ile polymorphism affected loin weight, the weight of primary cuts and loin backfat. Furthermore, for average backfat thickness the trend was observed (p<0.1) -GG homozygote pigs were characterized by thicker backfat compared to heterozygotes AG (Table 2). Pigs with AA genotype were characterized by a significantly higher loin of primary cut weights compared to opposite homozygotes GG (p<0.05). The observed differences were 2.29 kg and 1.2 kg, respectively.
Moreover, despite higher meatiness, AA animals together with AG were characterized by lower weight of loin backfat (p<0.05) and average backfat thickness (p<0.1) compared to GG pigs. The p. Val847Ile polymorphism within MYOM1 gene did not affect fattening traits as well as meat quality characteristics (Table 4).
Discussion
The development of research methods in molecular biology has been closely related to the advances in agriculture, both in livestock breeding and in plant cultivation. The efforts are made to apply the new developing research methods to allow identifying candidate genes and mutations related to quantitative traits of breeding importance. The standard selection assigned with the use of DNA marker linkage with production traits has a great potential in increasing the sustainability and efficiency of animal production (Beuzen et al., 2000).
Both investigated genes, ATGL and MYOM1, were previously proposed as candidate genes in pig genome associated with meat quality and carcass characteristics (Piórkowska et al., 2018). Variant calling based on RNA-seq data allowed us to show the significant polymorphisms within transcripts potentially related to pig production traits. Among them, two missense variants were identified -ATGL: p. Arg131His and MYOM1: p. Val847Ile. Even though presented genes are playing an important role in the processes related to lipid metabolism and energy homeostasis (ATGL) as well as skeletal muscle development (MYOM1), they have not been widely investigated in terms of pig production traits. The recent report by Piórkowska et al. (2018) indicated that these genes could determine selected phenotypic data in pigs.
The present study showed that polymorphism within ATGL gene was significantly associated with key carcass characteristics: loin eye area, ham and loin weights, meat percentage in carcasses, backfat thickness, and selected fattening traits. The pigs with AA genotype were characterized by the highest values in most of the presented parameters and the lower backfat thickness, while they did not differ in meat quality from the other genotypes. This is important finding since the use of c.392G>A missense variant in breeding practice can allow selecting pigs to improve meat content without decreasing its quality. However, there is one limitation of selection toward c.392G>A, because AA animals presented lowered daily gains. According to current trends in pig breeding, the fattening traits are the most decisive economical features in pig production (Mirilović et al., 2016). Although AA pigs had lower daily gains and the highest age of slaughter, detected differences between opposite homozygotes were low (54 g and 5.8 days, respectively). Based on such comprehensive analysis, we hypothesized that using ATGL SNP can bring benefits in the possibility of improving carcass meatiness in terms of low fat and maintaining meat quality at current levels. The study of Piórkowska et al. (2018)
performed on native Puławska and Polish
Landrace pigs, confirmed that AA animals in terms of c.392G>A SNP were characterized by lower backfat thickness. In pigs, the transcription analysis of ATGL gene showed its overexpression in backfat tissue compared to other tissues (Dai et al., 2011). Moreover, the association study performed for c.392G>A polymorphism strongly indicated that it affects fat deposition and carcass characteristics in pigs (Dai et al., 2011). Similarly, as in the current study, the authors observed that homozygote pigs (AA) were characterized by higher meatiness parameters (loin eye area, lean meat percentage) and lower fatness (average backfat thickness). Authors proposed c.392G>A polymorphism as a candidate marker for fat deposition traits in pigs. The significant relation of ATGL gene with pig production traits was also pinpointed by Dai et al. (2016), who showed that polymorphisms localized upstream 5'UTR region of ATGL gene could influence meat and fat contents.
In turn, for MYOM1 gene our results as well confirmed a significant effect of c.2539G>A polymorphism on evaluated pig production parameters. Likewise, for ATGL gene, for c.2539G>A SNP one genotype -AA was characterized by significantly higher meatiness traits (loin weight and weight of primary cuts) and lower average backfat thickness (trend observed). The most important finding allowing the potential use of this missense variant in breeding practice is a fact that we observed positive association of c.2539G>A MYOM1 with carcass features and lack of the effect on pork quality and fattening traits. Such an approach allows performing one-side selection to improve specific carcass traits without deterioration of the other pig production characteristics. The above breeding strategy can be applied for pig breeds which represent an insufficient level of meatiness, but desirable meat quality. The significance of MYOM1 polymorphism with backfat thickness, intramuscular fat content and pork texture parameters were previously indicated (Piórkowska et al., 2018). According to involvement in sarcomeric structure, myomesin 1 is one of the proteins determining the muscle fiber type . It has been established that muscle fiber distribution due to differences in energy metabolism, lipid and glycogen storage strongly affects pork quality (Karlsson et al., 1999) and growth performance (Lee et al., 2016).
Moreover, the disruption of each protein (including myomesin 1) involved in M-line structure can result in the degeneration of the sarcomere (Fukuzawa et al., 2008;Prill et al., 2019). In the present research, the significant association of c.2539G>A polymorphism with lean meat characteristics was detected. It can be related to a specific function of myomesin-1 and obtained correlation suggested that MYOM1 should be investigated for use in breeding practice.
In pig breeding, there is still a need to search for single genes with a high effect on phenotypic traits due to the relatively low cost of such marker evaluation for one individual.
The present study performed on synthetic pig line 990 that is used as a significant sire component, allows us to propose two polymorphisms within MYOM1 and ATGL genes which may be used in pig selection to obtain appropriate meatiness and fatness level in carcasses without decreasing meat quality. The genetic marker assisted selection can bring measurable financial benefits in a shorter time and in a more precise way than selection based only on phenotypic features. However, further study should be performed to confirm such a correlation in the other pig breeds.
Conflicts of interest
The authors declare no conflicts of interest.
Ethics approval and consent to participate
The research was performed on biological material derived from pigs maintained and slaughtered in the Test Pig Station (National Research Institute of Animal Production). In the Test Station pigs are slaughtered, dissected and after carcass evaluation, meat is standard intended for consumption. Therefore, our research does not require the approval of the Animal Experimentation Committee. pH45ham 6.43±0.14 6.54±0.14 6.50±0.14 6.43±0.15 6.55±0.14 6.51±0.14 pH2 ham 6.43±0.15 6.54±0.14 6.50±0.14 5.59±0.09
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Domain: Agricultural and Food Sciences
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A comparative study of high-pressure processing and thermal processing techniques on characteristics and microbial evaluation of orange juice
ABSTRACT This study investigates the impact of thermal and high-pressure processing on the quality indicator of orange juice and its storage stability. The pressure was applied at 400 MPa and 600 MPa for 3, 6, and 9 min to process the juice and evaluate the quality of orange juice during 60 days of storage with every 30-day interval. HPP conditions (400 MPa and 600 MPa for 3, 6, and 9 min) did not significantly change the ascorbic acid content of orange juice, in contrast to thermal processing where a crucial decrease in ascorbic content was observed. Ascorbic acid content increased non-significantly from 40.03 to 40.69 (mg/100 g) and 40.79 when applied for 3 and 6 min, respectively, while thermal processing reduced its content up to 33.45 (mg/100 g). Ascorbic acid at 600 MPa was observed at 41.19 (mg/100 g) when treated for 6 min. Carotenoid content was increased when HPP was from 8.6 to 9.14 (mg/100 ml) during 400 MPa for 9 min and 11.65 (mg/100 ml) for 6 min at 600 MPa compared to the corresponding untreated sample and thermally treated sample. The total soluble solids, pH, and acidity of the orange showed stability after HPP and during 60 days of storage. The natural microbiological load (yeast and mold, E-Coli log CFU/ml) was observed below 1 log reduction at 30 days of storage and 2 log reduction during days of storage. This study identified different pressure levels to produce nutritionally and microbiologically stable orange juice compared to thermally processed and untreated samples.
Introduction
The sweet orange fruit (Citrus sinensis (L.) Osbeck) accounts for roughly 50% of global citrus production. It is the most significant species within the Citrus genus and the most economically significant citrus fruit crop in the world [1] . Each year, Pakistan produces about 2.0 million metric tonnes of citrus fruit, predominantly kinnow. [2]This industry shares approximately 50% of the total fruit juice trade worldwide. [3]The most popular and well-liked product of orange fruit is its juice, which is liked worldwide. It is a great source of biologically active substances with oxidative qualities. It also has carotenoids, flavanones, and other metabolites in addition to vitamin C. Carotenoids are soluble in lipids that play a crucial role in maintaining good health in an individual. [1]Valencia orange juice is typically in demand by processors due to its significant amount of total soluble solids and color, and it is frequently blended with poor quality juices. [4]onsumer demand for safe and fresh foods has increased in the modern era while maintaining their nutritive aspects and calorie content. Conventional heat processing is the most often used technology for extending the shelf life and preserving fruit juices. Products' sensory and nutritional qualities might frequently suffer due to thermal processing. [5]Yet, interest in non-thermal technology has increased that are minimally and naturally processed. [2]Non-thermal technologies are methods of food preservation that work at normal and below temperatures, minimizing the unfavorable effects of heat on nutritional and quality characteristics. [6]A wide range of non-thermal processing technologies are now being developed. High-pressure processing (HPP) is one of these processing technologies. [7]ecause HPP may achieve pasteurization without heating (often at room temperature), it is a possible substitute for thermal pasteurization (TP). As a result, it is known to have less of an impact on the structure of macromolecules and taste components than TP. [6]he quality of orange juice after processing is a crucial topic for investigation. A number of deteriorative reactions occur in orange juice during processing and storage, lowering the product's quality. By using HPP, orange juice can have a longer shelf life than juice that was not processed while experiencing less product quality loss and retaining more of its fresh flavor. [8]Although multiple studies claimed that high-pressure processing of orange juice maintained its overall character and had a longer shelf life than juice that had not been treated, there were fewer studies that evaluate the use of constant pressures for different time intervals to check the nutritional stability and microbiologically safe orange use. The primary goals of the research were (i) to determine the best possible conditions of HPP with time to reduce the microbes up to non-detected limit during the storage period, (ii) to compare the non-thermal processing, i.e. HPP and conventional processing conditions in order to provide nutritionally stable orange juice. [9]
Procurement of raw material
The orange fruit (Valencia) was purchased from a hyperstore in Lahore, Pakistan. All the fruit were thoroughly washed and sorted out based on size and juice content. At the same time, all the chemicals used in the research were purchased from Sigma-Aldrich Chemical Co.(St. Louis, MO, USA) and Merck (Germany).
Extraction of juice
The orange juice content was pressed by using the conventional juice machine. All the juice extracted was then filtered using the muslin cloth to remove the seeds and peels of the orange. The orange juice was then stored at 4°C.
Thermal pasteurization
In a steam-jacketed kettle, the packed juice samples were heated to 85°C and kept for 45 s before being quickly cooled to 4°C in cold water. Brass stuffing boxes and T-type thermocouples from Ecklund-Harrison, Fort Myers, Florida, were used to measure the temperatures of the samples (Omega Engineering, Inc., Stamford, CT). Storage samples were placed in a walk-in cooler set to 4°C. The processed chilled samples were brought to the Pakistan Council of Scientific and Industrial Research (PCSIR), Lahore from the University of Veterinary and Animal Sciences (UVAS). All the samples were carried out under refrigerated conditions.
High-pressure processing
A 57 L capacity high hydrostatic pressurization unit (SHPP-57DZM-600, Shanshuihe Technology Co., Ltd., Taiyuan, China) was used to process the freshly squeezed orange juice at a temperature of 25°C. The pressure-transmitting medium was sterile water. Orange juice was poured into 200 mL plastic bottles before processing (PET). High pressure at 400 MPa and 600 MPa levels was applied for 3, 6, and 9 min, respectively. The pressure release time was less than 5 s, and the pressure rise rate was roughly 100 MPa/30 s. The time needed to increase and release the pressure was not included in the holding period in this investigation. All the samples were treated at 400 MPa and 600 MPa for 3, 6, and 9 min.
Storage conditions
High-pressure processing was done at the University of Veterinary and Animal Sciences (UVAS) and then transferred these treated samples to the Pakistan Council of Scientific and Industrial Research (PCSIR), Lahore. Orange juice bottles were treated with TP, HPP, and control treatments. They were stored in a refrigerator set to 4°C and tested for nutritional, microbial, and physicochemical analysis at 0, 30, and 60-day intervals during storage. Three replications of each treatment were included (individual bottles containing 250 mL juice). Approximately 24 h following treatment, all samples for the day 0 storage analysis were analyzed on the same day that the cargo was received. After an analysis of 0 days, control samples were removed. Additionally, sample bottles for HPP and TP treatments were kept at 4°C for 60 days for further analysis.
Ascorbic acid
In this study, the ascorbic acid of the sample was evaluated using the procedure described by AOAC, [10] with minor modifications. Iodine solution (0.005 mol/L) is used in this process to form iodide ions and dehydroascorbic acid by reacting with ascorbic acid as follows: In a short, 20 mL of sample was combined with 150 mL of water, 1 mL of starch solution, and 0.5 g/ 100 mL of water. Continuously agitate the solution, and Iodine is added until the endpoint is reached. The dark green color indicated the endpoint. The volume of iodine needed to reach the endpoint was used to compute the ascorbic acid concentration. The ascorbic acid concentration value was the mg ascorbic acid equivalent per 100 g of juice.
Total carotenoid content
The carotenoid value of orange juice was analyzed using the method represented by [11] with some modifications. In a short, 25 mL of the mixture was added to 80 mL of a 1:1 v/v hexane-acetone mixture in a separating funnel. Anhydrous sodium sulfate was added to the organic phase to absorb moisture after it had been collected. At room temperature, the absorbance was measured at 450 nm. Using β-carotene (2-10 μg/mL) mixed in hexane solution, a standard curve was created.
Total phenolic content
The methodology outlined by [12] was used to determine the total phenolic content (TPC). At room temperature, 2.5 mL of Folin-Ciocalteu reagent, diluted 10 times, was added to the samples (50 mL), followed by 2 mL of Na 2 CO 3 (7.5 g/100 mL). A spectrophotometer (HP 8452A, Agilent Technologies, Palo Alto, USA) measured the absorbance after the mixture was left in the dark for 30 min. Gallic acid (0.1-0.9 mg/mL) was used as the standard to generate a calibration curve, and the results were summarized in mg equivalent gallic acid per mL (mg GAE/ml).
Physicochemical analysis
A pH meter (Model FE20, Mettler Toledo, Schwerzenbach, Switzerland) was used to gauge the pH of the orange juice after being calibrated with buffer solutions. The total titratable acidity (TA), represented as g of citric acid per 100 mL, was calculated using titration. A digital refractometer (Pocket Pal-, Atago, Tokyo, Japan) was used to calculate the total soluble solids concentration in ° Brix. [13]
Microbial analysis
After processing (day 0) and storage, the identification of microflora of orange juice was carried out. The identification of microflora of orange juice was tested after 0 days and during storage. The materials were homogenized for 2 min after being diluted 1:10 in peptone water to enumerate total aerobic bacterial (TAB) (colony forming units cfu per ml) that are alive, and the suspensions were plated on PCA. The plates were incubated for 24 h at 30°C. The samples were also counted on DRBC agar to look for live yeast and mold. During 3-5 days, the plates were incubated at 25°C. A mechanical spiral plater (Eddy Jet, IUL Instruments, Barcelona, Spain) was mostly employed to achieve this. However, manual plating was also done at low dilutions.
Statistical analysis
The data were described as mean after analyzing each sample separately in triplicate using STATISTIX 8.1 at a 5% significance threshold to interpret the results using a two-way analysis of variance (ANOVA).
Ascorbic acid
Vitamin C is very crucial for human health and is composed of ascorbic and L-dehydroascorbic acid. [14]Its strong antioxidant capacity protects against free radicals and helps prevent the development of many degenerative diseases. [15]Since vitamin C is nutritionally significant and unstable, its presence ensures the existence of other nutrients and is used as a gauge for the nutritional value of processed foods. Citrus fruits are the primary source of vitamin C for consumers. [8]The mean values regarding the ascorbic acid content in the orange juice are presented in Table 1. The amount of ascorbic acid was measured in all orange juice samples. Because temperature adversely affects the ascorbic acid content, the thermally treated sample showed the lowest value of ascorbic acid content (38.44-33.45mg/100 ml). Ascorbic acid was observed 40.03 mg/100 ml in a fresh orange juice sample (control). Orange juice samples without any treatment were not analyzed further for storage study because they were untreated and unfit for human consumption during storage period. The increased concentration of ascorbic acid in high-pressure processed samples might be due to a higher extraction rate in juice due to high pressure. During storage, samples processed by thermal processing showed a significant decline in ascorbic acid content. In contrast to thermal processing, the sample treated with high-pressure processing showed better results. A non-significant reduction in ascorbic acid content was observed in HPP treated samples. A minimum reduction was observed in T6 ranged 41.19 to 39.87 mg/100 ml during 60 days of storage.
In samples subjected to high pressure, ascorbic acid is retained to the maximum value. This outcome was in line with a study by Lopez-Malo et al. [16] which discovered that a blend of orange, lemon, carrot, and water (8:1:4:7) maintained 99.6% of its vitamin C content after being subjected to a 500 MPa pressure for 5 min. Since ascorbic acid is extremely sensitive to the temperatures used during the thermal processing of juices, mild processing conditions result in higher ascorbic acid retention. [17,18]Furthermore, it has been observed that the degradation rate is slower in juice treated with HPP than in juice that has not been treated during storage, demonstrating that HPP can reduce the loss of ascorbic acid during juice storage. [19]
Carotenoid content
Table 2 displays the impact of pressure and time on orange juice's carotenoid concentration. Orange juice exhibited stability when processed under high pressure, but high temperatures reduced the carotenoid content because of the orange juice's adverse thermal reaction. Pressure treatment at 400 MPa for 3 min and 600 MPa significantly increased the carotenoid content from 6.7 mg/100 ml to 8.6 and 11.21 mg/100 ml. The extraction capacity of juice was boosted by applying pressure for a short period because carotenoid molecules have a complicated matrix and are not free. High pressure led to improved extraction, which led to an increase in carotenoid content. Every 100 MPa increase in pressure resulted in a 3 °C rise in temperature. The carotenoid content decreased due to a high exposure period to pressure, which was 600 MPa for 9 min. Orange juice underwent pressure treatment that considerably boosted the carotenoid concentration, while thermal treatment had a counter impact. The maximum value was achieved by applying pressure for 6 min at 600 MPa (11.65 mg/100 ml). A study was conducted to store these juices for 60 days to examine the carotenoid content's stability. The analysis is done at the 30 and 60-days points. Untreated fresh samples were discarded, while processed samples underwent analysis. The findings demonstrate that a 60-day storage period does not result in any appreciable loss.
An intriguing improvement in carotenoid extractability as a result of HPP treatment is reported. [20]arotenoids are mostly associated with macromolecules like proteins and membrane lipids in subcellular organelles (plastids), chloroplasts, and chromoplasts. [21]These findings concur with those of Pokhrel et al. [10] They reported the same outcomes with a carrot-orange juice mixture. No adverse effects of high-pressure processing of the carotenoid content on carrot-orange juice were discovered despite the carotenoid concentration increase. The findings of De Ancos et al. [7] likewise confirmed the findings.
Total phenolic content
Plants produce phenolic substances, which are found inside cells, during secondary metabolism. By increasing cell permeability with high pressure, phenolic substances may be retrieved or discharged. [10]In this study, the total phenolic content was measured. Statistically, there is no significant difference in phenolic content after high-pressure and thermal processing as phenolic compounds showed some stability to processing. Thermal processing reduces the phenolic content by up to 30% during 60 days of storage. Nevertheless, HPP showed better stability than thermal processing as HPP retains phenolic content. Due to the low pressurization levels, HPP did not notably impact the total phenolic substances (p > .05). The HPP level 600 MPa for 6 min showed maximum stability during processing and storage. Pressure applied at 600 MPa for 9 min showed some negative results due to increased temperature as the pressure applied time increased. The mean values regarding the total phenolic content in orange juice are presented in Table 3. High-pressure treatment for 9 min increased the cell disruption, increasing the total phenolic content of orange juice. These results are consistent with those reported by, [22] who found that after high-pressure treatment at 400 MPa for 15 min, both strawberry and blackberry puree had a non-significant increase in the total phenolic compound. There is little comparative research on HPP's impact on TPC in orange juice, but a few studies have found this influence in other fruit juices. In earlier investigations, it was discovered that different phenolic component concentration changes were observed following HPP processing. Thermal pasteurization reduces the total phenolic content as temperature negatively affects phenolic compounds but it reduces non-significantly. TP and HPP orange juices' TPC reduced after storage; however, this behavior was more pronounced in TP juices (p 0.05) after 60 days of storage. Similar results were found in an orange juice-milk beverage showing a significant increase at 100 MPa for 7 min but a non-significant decrease at 400MPa for 9 min. [23]According to certain research, TPC may even rise after processing when antioxidants are more easily removed. [24]Similar to this, a study using mulberry juice compared heat treatment (85°C, 15 min) with high-pressure processing (HHP) (500 MPa, 10 min), and discovered that HPP was able to preserve more TPC. [25]Varela-Santos [26] discovered that during 35 days of storage at 4°C, pomegranate juice treated with HHP showed a modest decline. [27]
Physicochemical analysis
The physicochemical characteristics of orange juice were observed after high-pressure processing and pasteurization and compared with untreated samples. Processing of orange juice non-significantly affects the pH of orange juice. High-pressure processing stabilizes the quality of orange juice as it has a non-significant effect on the pH, titratable acidity, and TSS of juice. The mean values regarding the physicochemical analysis in the orange juice were presented in Figures 1,2,3. HPP was found to have no appreciable impact on the product pH (p > .05),which is consistent with the study of Pokhrel et al. [10] There was a non-significant increase in the pH of orange juice during 60 days of storage after pasteurization, while high pressure processed samples showed a non-significant reduction in the pH of orange juice. Pressurization at 600 MPa for 6 min non-significantly affects the pH of the orange juice, hence retaining the juice quality after such a high-pressure level. The results were in line with the study of Pokhrel et al. [10] who reported that during storage, the pH of the control sample decreased by approximately 1 unit for the carrot orange juice blend with pH 5 and pH 6, and about 0.70 unit for the blend with pH 4. Similarly, no discernible impact of a 600 MPa high-pressure treatment lasting 10 min on pH was shown by Zhang et al. [28] for carrot juice. After initially being stable, the pH of processed samples started to fall substantially toward the end of storage, maintaining higher stability than untreated blends.
Juice quality and stability during the storage period of research was evaluated by the total soluble solids (TSS). TSS also showed the qualities of other parameters like amount of sugar and organic acids. Total soluble solid (TSS) is a parameter that allows us to evaluate the juice quality and stability while doing storage research since it indicates the entire quantity of sugar, organic acids, and other soluble molecules in a product.
Organic acids, produced by biochemical processes or fermentations by the development of certain spoilage microbes, contribute to the distinct flavors and palatability of orange juice. Acidity offers significant protection against the growth of hazardous microbes. Acidity alters the sweetness of sugar by helping to create flavor with a proper carbohydrate-to-acid ratio (Adeola and Aworh, 2010). HPP was found to have no appreciable impact on the titratable acidity of orange juice (p > .05). Thermal processing and high-pressure processing non-significantly affect the acidity of orange juice, hence retaining its fresh-like taste; however, storage affects the acidity of orange juice. High-pressure processing at 600 MPa for 6 min showed the best result and preserved better quality juice. W. Wu et al. [29] also represented a similar result. During storage, there were notable modifications, and the alterations mostly happened toward the conclusion of the storage period of HP treated and TP treated pineapple fruit juices. The results were also supported by the previous findings. [30,31]
Yeast and mold count
The mean values regarding the yeast and mold count in the orange juice are presented in Table 4. The microbiological quality of orange juice after high-pressure processing, thermal treatment, or no treatment was determined by monitoring the yeast and mold counts in orange juice. The mean initial population of yeast and mold in a controlled sample of orange juice was 3.83 log CFU/ml. It was increased concerning time because of no treatment, and the sample was discarded because of high microbial load during further study. Thermal and pressure-processed juices show the very least count of yeast and mold at the initial stage. Post pasteurization contamination of the orange juice may have occurred with the bottle filler, adding to the microbial load in the thermally treated orange juice. Highpressure treatment at 400MPa for 3 min reduced the population levels up to 1.06 log CFU/ml but it was not detected when 400 MPa was applied for 6 and 9 min. Yeast and mold counts can be seen at 45 and 60 days of storage in samples treated with 400 MPa. The first pressurization at 600 MPa for 3, 6, and 9 min reduced the yeast and mold count up to 0.67, 0.64, and 0.62 log CFU/ml, respectively. The below detection limit made the juice highly acceptable for consumers. Only 1.15 log cfu/ml can be detected in the sample treated with 600 MPa for 6 min but it did not make juice unfit for consumption. HPP resulted in statistically significant (P-0.05)reductions in yeast and mold compared with untreated juice. The results were supported by the work of Sreedevi et al. [32] which investigated microbial load in navel and Valencia orange juice and reported significant yeast and mold reduction compared to non-treated samples and when treated with thermal techniques. Microbial safety was ensured in both HPP-treated and thermally-treated pineapple fruit. [33]
E-Coli count
The mean values regarding the E-coli count in the orange juice are presented in Table 5. The microbial quality of the orange was also determined by E-coli count. Thermal and high-pressure processing also reduce E-coli content significantly. The initial population of E-coli can be seen as 4.67 log CFU/ml without any treatment, but this value increased during storage and made juice unfit for further consumption. Thermal pasteurization reduced E-coli count up to 3.67 log CFU/ml and an increasing trend was observed in the samples. This increasing value of 6.49 log CFU/ml limits the life of orange juice compared to high-pressure processes where high pressure significantly reduced the value and retained juice completely fit for human consumption. Pressure applied 400 MPa for 3, 6, and 9 min showed a significant reduction in e-coli count compared to thermal treatment and untreated samples. When the pressure increased up to level 600 MPa, E-coli counts were not detected. E-coli could not be detected in orange samples at the initial stage of the study and could only be detected at a level of 1.07 log CFU/ml at 60 days of storage in samples treated with 600 MPa for 3 min. E-Coli was not detected in samples treated with 600 MPa for 6 and 9 min. A significant reduction is measured in orange juice samples compared to thermal treatment and to the samples that were not further processed. Pressure treatment significantly delayed the growth and recovery of the surviving microorganisms. Overall, the pressure level itself (400 or 600 MPa) had no significant effect (p > .05). Cao et al [34] also reported there processing at 600 MPa for up to 6 min could result in the complete inactivation of microbes when the initial microbial count was less than 4 logs CFU/ml in strawberry juice. Patterson et al. [35] also proposed similar findings in carrot juice. Untreated and pressure-treated carrot juices were evaluated for their microbiological quality. The total counts were lowered by about 4 log CFU/ml after highpressure treatment at 500 MPa and 600 MPa (1 min/20 C), and the survivors showed very little growth when stored at 4°C for up to 22 days.
Conclusion
Our findings showed that HPP at 600 MPa for 6 min could be used to make orange juice safely and with preserved quality and storage stability compared to commercially applied thermal processes. The quality of orange juice could be preserved by high-pressure processing while during thermal processing bioactive compounds like ascorbic acid, total phenolic compound, and carotenoid content are lost in maintaining the longevity of orange juice. This study identifies ideal high-pressure processing settings that can produce juice of superior quality and allow for a longer shelf life. It would help the present strategies for commercializing juice made from fruits and vegetables under high pressure under less strenuous circumstances.
Figure 1 .
Figure 1. Effect of treatments on pH of orange during 60 days of storage.
Figure 2 .
Figure 2. Effect of treatment on Total soluble solids (°Brix) of orange during 60 days of storage.
Figure 3 .
Figure 3. Effect of treatment on Titratable acidity of orange during 60 days of storage.
Table 1 .
Effect of treatment on the ascorbic acid content of orange during 60 days of storage.
Table 2 .
The effect of HPP on the carotenoid content of orange juice during 60 days of storage.
Table 3 .
Effect of treatment on total phenolic (mg GAE/100 ml) of orange during 60 days of storage.
Table 4 .
Effect of treatment on yeast and mold of orange juice with respect to storage. MPa for 3, 6, and 9 min, respectively. NT= Not Tested. Data represents mean ± SD Different letters shows significant difference while same letters shows results are non-significant.
Table 5 .
Effect of treatment on E-coli content of orange during 60 days of storage. Orange juice; OT1 = posturizes orange juice; OT2, OT3, OT4 represent orange juice treated at 400 MPa for 3, 6, and 9 min, respectively; OT5, OT6, OT7 represents orange juice treated at 600 MPa for 3, 6, and 9 min, respectively. NT = Not Tested. Data represent mean ± SD. Different letters show significant difference while same letters show results that are nonsignificant.
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Domain: Agricultural and Food Sciences
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Varying the ratio of Lys: Met through enhancing methionine supplementation improved milk secretion ability through regulating the mRNA expression in bovine mammary epithelial cells under heat stress
Introduction The ratio of lysine (Lys) to methionine (Met) with 3.0: 1 is confirmed as the “ideal” profile for milk protein synthesis, but whether this ratio is suitable for milk protein synthesis under HS needs to be further studied. Methods To evaluate the molecular mechanism by which HS and Lys to Met ratios affect mammary cell functional capacity, an immortalized bovine mammary epithelial cell line (MAC-T) is incubated with 5 doses of Met while maintaining a constant concentration of Lys. The MAC-T cells was treated for 6 h as follow: Lys: Met 3.0: 1 (control 37°C and IPAA 42°C) or treatments under HS (42°C) with different ratios of Lys: Met at 2.0: 1 (LM20), 2.5: 1 (LM25), 3.5: 1 (LM35) and 4.0: 1 (LM40). RNA sequencing was used to assess transcriptome-wide alterations in mRNA abundance. Results The significant difference between control and other groups was observed base on PCA analysis. A total of 2048 differentially expressed genes (DEGs) were identified in the IPAA group relative to the control group. Similarly, 226, 306, 148, 157 DEGs were detected in the LM20, LM25, LM35 and LM40 groups, respectively, relative to the IPAA group. The relative mRNA abundance of HSPA1A was upregulated and anti-apoptotic genes (BCL2L1 and BCL2) was down-regulated in the IPAA group, compared to the control group (p < 0.05). Compared with the IPAA group, the relative mRNA abundance of anti-apoptotic genes and casein genes (CSN1S2 and CSN2) was up-regulated in the LM25 group (p < 0.05). The DEGs between LM25 and IPAA groups were associated with the negative regulation of transcription RNA polymerase II promoter in response to stress (GO: 0051085, DEGs of BAG3, DNAJB1, HSPA1A) as well as the mTOR signaling pathway (ko04150, DEGs of ATP6V1C2, WNT11, WNT3A, and WNT9A). Several DEGs involved in amino acids metabolism (AFMID, HYKK, NOS3, RIMKLB) and glycolysis/gluconeogenesis (AFMID and MGAT5B) were up-regulated while DEGs involved in lipolysis and beta-oxidation catabolic processes (ALOX12 and ALOX12B) were down-regulated. Conclusion These results suggested that increasing Met supply (Lys: Met at 2.5: 1) may help mammary gland cells resist HS-induced cell damage, while possibly maintaining lactation capacity through regulation of gene expression.
Introduction
In a high temperature and humidity environment, the imbalance between heat accumulation and dissipation in dairy cows can induce heat stress (HS) (1). Once the ambient temperature rises above the threshold and the body is unable to dissipate heat effectively, the cow will be under HS due to the disruption of internal homeostasis (2). Due to the innate self-protection mechanisms of animals, several biological processes are initiated, such as reducing dry matter intake and rumination time, increasing respiratory rate and hormone secretion, to alleviate the negative effects of HS (3). The lactation performance of dairy cows is severely negatively affected by HS, which seriously undermines the economic efficiency of dairy farming.
Mammary gland is the most important organ for milk synthesis and secretion. In addition to the decline in milk production, the protein content of milk also decreases during the hot summer months (4,5), partly due to the direct negative impact on milk protein synthesis in the mammary gland (6). Milk synthesis and secretion are considered system processes incredibly sensitive to both physiological and environmental factors (7)(8)(9). Previous study suggested that inadequate feed intake, changes in postabsorptive metabolism and nutrient partitioning may contribute to discordant changes in mammary protein synthesizing capacity in heat-stressed cows (10). In addition, the apoptosis rate of mammary epithelial cells in dairy cows was increased under HS conditions, and cytoskeletal and cell transport functions were disturbed (11)(12)(13). In modern dairy farms, managers adopt a variety of approaches to alleviate or prevent the occurrence of HS in dairy cows, and some feed additives [betaine (14), choline (15), taurine (16) and methionine (17)] seem to be effective in alleviating negative effects of HS.
Methionine (Met) and lysine (Lys) are the most-limiting amino acids in a large range of diets for dairy cows (18). Previous studies indicated that an approximately 3.0: 1 ratio of Lys to Met in dietary metabolic proteins can increase the yield of milk protein to an optimal level (19,20), which is considered as the "ideal" amino acid profile (IPAA) for milk protein synthesis. However, during HS, the uptake of amino acids (including Met) of dairy cows is altered, resulting in inhibition of the synthesis of milk protein content (21). Increasing the supply of Met in bovine mammary epithelial cells (BMECs) reduced apoptosis and necrosis, decreased lipid peroxidation, and increased the activities of superoxide dismutase, catalase, and glutathione peroxidase, resulting in comprehensive cytoprotective effects under high temperature conditions (17,22,23). Thus, whether the 3.0: 1 ratio of Lys: Met is ideal to promote milk protein synthesis under HS conditions and the regulatory mechanisms are not well known.
Our hypothesis was that changing the ratio of Lys: Met by increasing or decreasing Met supplementation could be a way to help mitigate the negative impact of HS on BMECs. To address this hypothesis, an immortalized bovine mammary epithelial cell line (MAC-T) was cultured with different ambient temperature conditions: thermo-neutral (37°C) and HS (42°C), and 5 media contains 175 mM Lys and varying Met concentrations (58 mM, 44 mM, 50 mM, 70 mM, and 87 mM). The RNA sequencing (RNA-Seq) approach was used to identify the molecular mechanisms regulated by changes in Met supplementation.
Cell culture and treatments
An immortalized bovine mammary cell line (MAC-T) was chosen as the model. The MAC-T cells were derived from our laboratory, and the cell culture protocol followed our previous similar study with minor modifications (24). Briefly, the thawed bovine MAC-T cells were cultured in 75cm 2 flasks using an incubator at 37°C and 5% CO 2 until sufficient cells were obtained for subsequent experiments. The basal medium was prepared with minimum essential medium with Earle's balanced salts (GE Healthcare Life Sciences, Logan, UT) and fetal bovine serum at a ratio of 9.0: 1, and supplemented with 5 mg/L insulin, 1 mg/L hydrocortisone, 5 mg/L transferrin, 5 μM ascorbic acid, 5 mM sodium acetate, 100 U/mL penicillin, 100 μg/mL streptomycin, 0.25 μg/mL antimycotic, 1 mg/L progesterone, 0.05% lactalbumin, and 0.05% α-lactose. When confluency reached 80-90%, the cells were digested with trypsin-EDTA solution and re-inoculated in 6-well plates. The basal medium was replaced by the lactogenic medium when the cell confluency reached 80-90% again, followed by the plates were incubated overnight at 37°C. The lactogenic medium was changed minimum essential medium with Earle's balanced salts in the basal medium to high-glucose Dulbecco's modified Eagle's medium (Hyclone, GE Healthcare Life Sciences), and supplemented with 1 g/L bovine serum albumin and 2.5 mg/L prolactin. Subsequently, the lactogenic medium was changed to the special lactogenic medium containing different ratios of amino acids (as presented in Table 1), and the cells were further at cultured 37°C or 42°C for 6 h (27). Accordingly, there were 6 treatments as follow: 37°C treatment with Lys: Met 3.0: 1 (control), 42°C treatments with Lys: Met at 2.0: 1 (LM20), 2.5: 1 (LM25), 3.0: 1 (IPAA), 3.5: 1 (LM35) and 4.0: 1 (LM40). After incubation for 6 h, cell samples were collected and stored at −80°C until RNA extraction. The reagents and chemicals were purchased from Sigma-Aldrich (St. Louis, MO) unless otherwise stated.
RNA extraction and RT-qPCR analysis
Total RNA was extracted from MAC-T cells using TRIzol reagent (#15596026, Invitrogen, United States) and RNA quality determined using a NanoDrop 1,000 ND-2000 spectrophotometer (Thermo Scientific, USA). The cDNA synthesis was performed using the PrimeScript RT reagent Kit with gDNA Eraser (Takara Biotechnology, Dalian, China) according to the manufacturer's instructions. The RT-PCR was performed according to the manufacturer's instructions using SYBR Premix Ex Taq (Takara Biotechnology, Dalian, China).
RNA sequencing
Total RNA was extracted using Trizol reagent (Invitrogen, Carlsbad, CA, United States) according to the manufacturer's protocols. RNA quality was assessed on an Agilent 2,100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, United States) and checked using RNase free agarose gel electrophoresis. After total RNA was extracted, eukaryotic mRNA was enriched by Oligo (dT) beads, while prokaryotic mRNA was enriched by removing rRNA by Ribo-ZeroTM Magnetic Kit (Epicentre, Madison, WI, USA). Then the enriched mRNA was fragmented into short fragments using fragmentation buffer and reverse-transcribed into cDNA with random primers. Second-strand cDNA was synthesized with DNA polymerase I, RNase H, and dNTP. Then, the cDNA fragments were purified with QiaQuick PCR extraction kit (Qiagen, Venlo, The Netherlands), end repaired, A base added, and ligated to Illumina sequencing adapters. The ligation products were size selected by agarose gel electrophoresis, PCR amplified, and sequenced using Illumina Novaseq6000 by Gene Denovo Biotechnology Co., Ltd.(Guangzhou, China). OD260/OD280 values of all samples were ≥ 1.9, and RNA Integrity Number (RIN) values were ≥ 8.0. The cDNA library was constructed using 3 μg total RNA for each sample. Before the library was constructed, the ribosomal RNA was removed by Epicentre Ribo-zero™ rRNA removal kit (Epicentre, United States), and the total RNA removed by rRNA was cleaned by precipitation with ethanol. The NEB Next ® Ultra™ Directional RNA Library Prep Kit for Illumina ® (NEB, USA) was then used for library construction using RNA with the rRNA removed. Library sequencing was performed using Illumina HiSeq4000 at Guangzhou Gidio Biotechnology Co., Ltd. The short-read alignment tool Bowtie2 (30) (version 2.2.8, [URL]:// bowtie-bio.sourceforge.net/bowtie2/index.shtml)was used for mapping reads to the ribosomal RNA (rRNA) database. An index of the reference genome was built and paired-end clean reads mapped to the reference genome using HISAT 2.2.4 (31) with "-rna-strandness RF" and other parameters set as default. The mapped reads for each sample were assembled with StringTie v1.3.1 (32, 33) in a reference-based approach. Principal component analysis (PCA) was performed with R package gmodels ( [URL]:// www.rproject.org/). RNA differential expression analysis between two different groups was assessed via DESeq2 (34,35). The genes/ transcripts with a false discovery rate (FDR) below 0.05 and absolute fold change ≥1.5 were considered as differentially expressed genes (DEGs). The DEGs were annotated by Gene ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment using the R programming language (3.5 version, [URL] on the hypergeometric distribution.
Statistical analysis
The mRNA abundance data of each gene were log 2 transformed to obtain a normal distribution before statistical analysis. The statistical analysis was performed using the MIXED model in SAS (version 9.3; SAS Institute Inc., Cary, NC, United States) with Lys to Met ratios as the main fixed effect and individual cell culture well as random effect. Treatment means were generated using the LSMEANS option and separated when they were significant with the PDIFF option. Statistical significance was considered at p < 0.05.
Heat shock response
The effects of HS on the mRNA expression of heat shock response genes are shown in Figure 1. HS up-regulated the gene expression of HSPA5, HSP90AB1, HspA1A, and HSPB8 (p < 0.05). However, under HS, the gene expression of HSPA5, HSP90AB1, HSPA1A and HSPB8 was down-regulated in the LM25 and LM20 group (p < 0.05), the gene expression of HSP90AB1 and HSPA1A was down-regulated in the LM35 group (p < 0.05), the gene expression of HSPA1A and HSP8 was down-regulated in the LM35 group (p < 0.05), compared to the IPAA group.
Abundant of apoptosis-related genes
Compared with the control group, the gene expression of BCL2 was down-regulated in the IPAA group (p < 0.05, Figure 2). Under HS, compared with the IPAA group, the gene expression of BCL2 was up-regulated in the LM20, LM25 and LM40 groups (p < 0.05), the gene expression of BCL2L1 was up-regulated in the LM25 group (p < 0.05).
mRNA expression of casein genes
The expression of CSN1S2 and CSN2 in the LM25 group was up-regulated compared with the control group (p < 0.05, Figure 3).
RNA sequencing results
A total of 3.8-5.1 million raw sequencing reads were generated in each group. The high-quality (HQ) clean reads obtained accounted for more than 99% of all the raw reads (Figure 4A) and were mapped to the bovine reference genome (Bos Taurus, assembly ARS-UCD1.2). The mean mapping ratio was greater than 96% in each group. A total of 13,773, 13,390, 13,552, 13,623, 13,528 and 13,456 known genes and 591, 591, 585, 592, 593 and 592 new genes were identified in the control, IPAA, LM20, LM25, LM35 and LM40 groups, respectively (Figure 4B). The cumulative variance contribution rate (65.2%,PC1 + PC2) of the principal component analysis (PCA) for the gene expression profiles was lower than the standard of 85% (Figure 4C). The principal component analysis illustrated that a significant difference existed between the control and other groups under HS. At the same time, except for the IPAA group, the three repeats in each HS groups tended to cluster closely, indicating that adding different concentrations of Met resulted in a high similarity in the overall expression levels of core genes during HS (Figure 4C). The sample clustering analyses further confirmed the PCA results (Figure 4D).
To investigate the regulatory mechanisms for the effects of Met on lactation performance, gene function analysis was performed. Genes with a p-value <0.05 and an absolute value of log 2 fold-change (|log 2 FC|) > 2 were considered as DEGs. A total of 2048 DEGs were screened resulting in 742 upregulated and 1,306 downregulated in the IPAA group relative to the control group. A total of 306 DEGs with 251 upregulated and 55 downregulated were in the LM25 group relative to the IPAA group, and 130, 62, 55 upregulated and 96, 86, 102 downregulated were detected in the LM20, LM35 and LM40 group, respectively, relative to the IPAA group (Figure 4E).
The top 10 DEGs encoding heat shock proteins (HSPA5, HSPA1A, HSPA6, HSPH1, HSPA8, DNAJA4, HYOU1 and HSP90AA1) were highly up-regulated during HS in the IPAA group relative to the control group (Figure 5A). BAG3 (BAG cochaperone 3, BAG3), The relative mRNA expression of heat shock response genes in MAC-T cells with the different treatments. Control (37°C) and IPAA (42°C) treatments containing Lys: Met at 3.0, LM40, LM35, LM25 and LM20 containing Lys: Met at 2.0: 1, 2.5: 1, 3.5: 1 and 4.0: 1, respectively. Asterisks indicated significant differences between different groups: * p < 0.05.associated with apoptosis, was also upregulated. For more in-depth biological function information, KEGG pathway annotation analysis was performed using the DEGs list with the assistance of KEGG database. The enriched pathways with p value <0.05 are reported in Figure 5B. Eight pathways in the Control-vs-IPAA condition had a close relationship to the autoimmune disorders including cushing syndrome, breast cancer, endocrine resistance, AGE-RAGE signaling pathway in diabetic complications, endometrial cancer, basal cell carcinoma, prostate cancer, and MicroRNAs in cancer. Some of the pathways are associated with cellular responses by HS including sphingolipid signaling pathway, protein processing in the endoplasmic reticulum, Wnt signaling pathway, IL-17 signaling pathway, GnRH signaling pathway, ubiquitin mediated and proteolysis, and peroxisome. Two pathways are related to metabolism including Selenocompound metabolism and nicotinate and nicotinamide metabolism. Nearly all these top-affected pathways are related to immune and heat shock response. The responsiveness of bovine MAC-T cells to HS in this study, clearly suggested its suitability as a model to understand the modulation of cow mammary gland expression signatures in response to HS.
The KEGG pathway annotation analysis revealed that DEGs were mainly involved in amino acid metabolism, immune system, infectious diseases, and signal transduction (Figure 6A). In addition, most DEGs (DNAJB1, EEF1A2, EGR1, EGR2, FGF21, HSPA1A, MAPK12, and WNT3A) among the four groups were all significantly enriched in immunology-related pathways involved in the heat stock response (Figure 6B; Supplementary Table S2). In addition, the DEGs of the LM25 group were also significantly enriched in glyoxylate and dicarboxylate metabolism and mTOR signaling pathway (Figure 6B). The DEGs of the LM35 group were significantly enriched in nicotinate The relative mRNA expression of apoptosis-related genes in MAC-T cells with the different treatments. Control (37°C) and IPAA (42°C) treatments containing Lys: Met at 3.0: 1, LM40, LM35, LM25 and LM20 containing Lys: Met at 2.0: 1, 2.5: 1, 3.5: 1 and 4.0: 1, respectively. Asterisks indicated significant differences between different groups: * p < 0.05.
FIGURE 3
The relative mRNA expression of casein genes in MAC-T cells with the different treatments. Control (37°C) and IPAA (42°C) treatments containing Lys: Met at 3.0: 1, LM40, LM35, LM25 and LM20 containing Lys: Met at 2.0: 1, 2.5: 1, 3.5: 1 and 4.0: 1, respectively. Asterisks indicated significant differences between different groups: * p < 0.05.and nicotinamide metabolism, glycine, serine and threonine metabolism (Figure 6B). The DEGs of the LM40 group were markedly enriched in the MAPK signaling pathway and nicotinate and nicotinamide metabolism (Figure 6B). The effects of Met supplementation on mRNA abundance of milk fat, lactose, and mTOR signaling pathway genes is reported in Table 3. Compared with the IPAA group, the mRNA abundance of LPL, ACACA, SCD, FADS1, GPAM, PGM2, LPIN1, SPTLC1, SPTLC2, INSIG1, INSIG2 and PPARG was up-regulated in the LM25 group, as well as the lactose synthesis genes of UGP2, B4GALT1 and GALE. In addition, an upregulation in the expression of EIF4E, EEF2K, and RHEB, and a downregulation in expression of EIF4EBP1 and eEF2 were also detected in the LM25 group. It was observed that the Met concentration at 70 mM in the LM25 group resulted in a higher expression of genes coding for milk fat, lactose and mTOR signalingresponsive genes.
As presented in Figure 7, the RT-qPCR results were consistent with the RNA-Seq data. The relative mRNA expression of eIF4E in the LM25 group was significantly higher than that in the IPAA, LM35 and LM40 groups (p < 0.05). Compared with the control group, the relative expression of TSC2 in all other groups was significantly downregulated (p < 0.05).
Discussion
The heat shock protein (HSPs) family members constitute a group of chaperone proteins that exhibit rapid up-regulation in response to HS, thereby ensuring cellular homeostasis through the regulation of protein folding and maturation within cells (36). In accordance with previous findings (37)(38)(39), the expression of genes encoding Hsps (HSPA5, HSPA1A, HSPA6, HSPH1, HSPA8, DNAJA4, HYOU1 and HSP90AA1) was significantly up-regulated in MAC-T cells upon exposure to HS in this study. It has been demonstrated that the 70 kDa heat shock protein (HSP70) is a reliable biomarker for monitoring changes in body temperature in mammals. These proteins contribute significantly to the heat tolerance of cells by up-regulating protein expression to help restore homeostasis in heat-exposed cells (40)(41)(42)(43). The supplementation of Met (70 mg/L) decreased the protein level of HSP70 compared with the control group (60 mg/L Met) (44). Improving the supply of Met has also been reported to prevent heat-induced oxidative stress and significantly reduce mortality of BMECs in vitro (23). In this study, the relative mRNA abundance of the genes encoding HSP70 (HSPA5, HSPA1A, HSPA6 and HSPA8) was down-regulated with the increase of Met addition under HS, indicating that enhancing Met supply has a potential role in increasing the tolerance of MAC-T cells to heat. Apoptosis is the ultimate outcome of mammalian cells undergoing sustained HS. In this process, cell death occurs due to the programmed control of genes and the stepwise activation of the apoptotic pathway. B-cell lymphoma 2 (BCL-2)-associated athanogene 3 (BAG3) protein is a co-chaperone of HSP70, acts by binding to the ATPase domain to help the chaperone release ADP and nucleotide cycle (45), and responds to HS with elevated expression. It also has the binding site for BCL-2, an intrinsic (mitochondria-dependent) pathway leading to apoptosis, as well as activation of macrophage phagocytosis through co-infection with HSPs (46). The level of the anti-apoptotic BCL-2 family protein Bcl-xL decreased with the knockdown of BAG3 (47). In this study, compared to the control group, the gene expression of BAG3 was higher in the IPAA group, while the mRNA level of the anti-apoptotic gene (BCL2) was lower in the IPAA group. Moreover, the mRNA level of the anti-apoptotic genes (BCL2 and BCL2L1) was higher in the LM25 group than that in the IPAA group. This result is consistent with previous reports (17), which may be related to the fact that Met effectively triggers the anti-apoptotic response in cells during HS (48). Thus, enhancing Met supply up-regulated the expression of anti-apoptotic genes in MAC-T cells, which may help alleviate heat-induced apoptosis.
There could be a direct link between the decline in milk production and the down-regulation of gene expression associated with milk protein synthesis caused by hyperthermia (49). The ratio of Lys to Met has been demonstrated to alter the expression of casein genes in BMECs (20,50,51). In the current study, the mRNA level of casein genes (CSN1S1 and CSN2) was the highest in the LM25 group. There was a dose-dependent relationship between the synthesis of milk fat and the supply of Met, and the secretion of triglycerides and lipid droplets was greatest in BMECs at a dose of 0.6 mM (52). Similarly, in this study, the transcriptional abundance of genes related to de novo synthesis of fatty acids (ACACA, SCD and FADS1), triacylglycerol synthesis (GPAM, PGM2 and LPIN1), sphingolipid synthesis (SPTLC1 and SPTLC2), and transcription regulation (INSIG1, INSIG2 and PPARG) were up-regulated in the LM25 group compared to the IPAA group. Following mammary cell uptake, glucose is converted to uridine diphosphate (UDP-) glucose and UDP-galactose in the cytoplasm under the action of UDP glucose pyrophosphorylase (UGP2) and galactose epimerase (GALE). Finally, one molecule of UDP-galactose and one molecule of glucose are combined by β-1,4-galactosyltransferase 1 (B4GALT1) in the Golgi apparatus to produce lactose (53). The transcript abundance of UGP2, B4GALT1 and GALE was upregulated in the LM25 group compared to the IPAA group. The differences in the expression levels of these genes (related to casein, milk fat and lactose synthesis) indicated that the ratio of Lys to Met at 2.5: 1 may be more conducive to the synthesis of milk components in mammary cells under HS conditions.
There is growing evidence that the mammalian target of rapamycin (mTOR) signaling pathway is the central node of the (24). Thus, the upregulation of genes involved in amino acid metabolism (AFMID, HYKK, NOS3, and RIMKLB) in the LM25 group confirmed the biological correlation between Met supply and the mTOR signaling pathway compared to the IPAA group during HS. The mTOR signaling pathway also regulates the metabolism of lipids and carbohydrates by up-regulating the expression of related genes to control enzyme synthesis (60). Compared with the control group, the transcriptional abundance of AFMID and MGAT5B (involved in glyoxylate and dicarboxylate metabolism as well as mannose type O-glycan biosynthesis) was up-regulated in the LM25 group, indicating that the increased supply of Met may also regulate carbohydrate and lipid metabolism in MAC-T cells through the mTOR signaling pathway. Taken together, the data from this study indicated that an increased supply of Met (Lys: Met at 2.5: 1) had the ability to attenuate cellular damage (e.g., apoptosis) during HS. In addition, increasing the supply of Met may help increase the synthesis of casein, milk fat, and lactose in mammary cells, in part by altering the expression of genes involved in intracellular metabolism of amino acids, lipids, and carbohydrates, as well as the mTOR signaling pathway. The limitation of this study is that only the MAC-T cell model was used to investigate the increase in Met supply to mitigate the negative effects of HS on milk secretion ability, rather than in vivo. Thus, more studies should be conducted on dairy cows to validate the results of this study.
Fu
Heat stress causes changes at the level of gene transcription in MAC-T cells. These changes are partially reversed by the addition of Met supply (ratio of Lys to Met of 2.5:1). The potential mechanism is related to the mRNA expression regulation of HSPs, anti-apoptosis and milk component synthesis genes explored by whole transcription sequencing technology. The findings of this study raise the possibility supplementation with Met might have a positive effect on mammary cells during HS.
TABLE 1
Amino acid composition of the lactogenic medium.
TABLE 2
The primer sequences of genes.
TABLE 3
The mRNA abundance (log 2 FC) of milk fat, lactose, and mTOR singal pathway genes in MAC-T cells with the different treatments.
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Domain: Agricultural and Food Sciences
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Proposal of a Model of Irrigation Operations Management for Exploring the Factors That Can Affect the Adoption of Precision Agriculture in the Context of Agriculture 4.0
: Agriculture is undergoing a profound change related to Agriculture 4.0 development and Precision Agriculture adoption, which is occurring at a slower pace than expected despite the abundant literature on the factors explaining this adoption. This work explores the factors related to agricultural Operations Management, farmer behavior, and the farmer mental model, topics little explored in the literature, by applying the Theory of Planned Behavior. Considering the exploratory nature of this work, an exploratory multi-method is applied, consisting of expert interviews, case studies, and modeling. This study’s contributions are a list of factors that can affect this adoption, which complements previous studies, theoretical propositions on the relationships between these factors and this adoption, and a model of irrigation Operations Management built based on these factors and these propositions. This model provides a theoretical framework to study the identified factors, the relationships between them, the theoretical propositions, and the adoption of Precision Agriculture. Furthermore, the results of case studies allow us to explore the relationships between adoption, educational level, and training. The identified factors and the model contribute to broadening the understanding of Precision Agriculture adoption, adding Operations Management and the farmer mental model to previous studies. A future research agenda is formulated to direct future studies.
Introduction
Agriculture is currently undergoing a profound change [1] due to a new technological revolution [2,3] related to the development of Agriculture 4.0 and the diffusion of technologies, such as the Internet of Things (IoT), big data, artificial intelligence, and cloud computing [4,5]. Agriculture is also experiencing a technological transformation related to the adoption of Precision Agriculture (PA), which, after 20 years of research, is not consolidated [6]. Despite the expected economic gains [7], PA adoption is often perceived as not occurring immediately [8], and it is progressing at a slower speed than predicted [9] due to several factors; among them, the lack of farmer knowledge about the use of PA technologies plays an important role in business outcomes [10]. There is a lack of consensus on whether PA improves farm profitability, in addition to the little attention paid to perceptions of PA profitability from the farmer's perspective [11].
Despite the abundant literature on the factors affecting PA adoption [12][13][14], factors related to Operations Management in agriculture [15] and farmer behavior [16,17], specifically their beliefs that are the basis of the farmer mental model [18,19], are little explored. In most studies, the factors are organized in models based on the theory applied in the research, like the Technology Acceptance Model [17] and Utility Maximization [20]. Theories for studying human behavior, such as the Theory of Planned Behavior (TPB) [21], were applied in rare cases in previous studies [22]. The TPB provides a solid conceptual framework useful for analyzing farmer behavior [23][24][25].
Operations Management (OM), applied in an agriculture context, as well as in manufacturing and services organizations, is the function associated with the design and management of the transformation processes of inputs into outputs [26] and supports designing, planning, scheduling, and executing operations involving humans and machines [27,28]. However, the factors affecting PA adoption related to the modeling of irrigation OM are scarce in the literature [15].
There is a limited availability of publications that delve into the farmer mental model within studies focusing on the adoption of Precision Agriculture (PA) [18,19]. Applying the concept of the mental model allows for an understanding of farmer decision making, linking perceptions, attitudes, and beliefs with behavior [29]. Farmers do not only make decisions based purely on economically rational motivations but also consider social and intrinsic objectives [30].
In the context of this ongoing technological revolution, Agriculture 4.0 has been developed through the evolution of PA [6,31]. Technologies included in the concept of Agriculture 4.0 allow us to improve planning and control in agricultural production [32], allowing us to follow plant and yield development progress through information collected by sensors [33] and to access a large amount of site-specific data to make more accurate decisions in farm management [34]. Most of the research carried out on Agriculture 4.0 is more theoretical [31,35]. Moreover, overemphasis is placed on high-tech solutions to the detriment of the inclusion and exclusion effects of Agriculture 4.0 technologies [36] and the social impacts of these new technologies [37,38], as well as to the factors related to OM, farmer behavior, and the farmer mental model, which can all affect PA adoption.
Therefore, in this work, we aim to contribute to filling the identified gaps, answering the following research questions: (1) What are the factors related to irrigation OM that can affect the adoption of PA in the context of Agriculture 4.0?(2) What are the factors related to the farmer's behavior, focusing on the mental model, that can affect the adoption of PA in the context of Agriculture 4.0?(3) What are the factors related to the modeling of irrigation operations, with a focus on OM and the farmer mental model?
To answer these questions, in this study, we aim to achieve the following research objectives: (1) exploring the factors related to irrigation OM that can affect the studied adoption; (2) exploring the factors related to farmer behavior, focusing on the mental model, that can affect the studied adoption; and (3) modeling the irrigation operations, with a focus on OM and the farmer mental model, to understand and formalize the relationships between adoption and the identified factors.
This work is characterized as exploratory since little research has been conducted on the topics being studied, an insufficient number of studies exists to document the research problems, and the variables and theory base are unknown. Exploratory study can help to develop theoretical propositions and frameworks [39,40]. This research adopts an exploratory multi-method made up of expert interviews, case studies, and the modeling of irrigation operations [39,[41][42][43].
The empirical results of 27 expert interviews and two case studies on farms were used to develop the irrigation OM model [41]. For modeling, the Integration Definition for Function Modeling (IDEF0) technique was applied, which offers a standard and widely used approach to develop the conceptual models of systems [44], like farms; to represent products, controls, restrictions, and resource information in the same diagram [45]; and to identify system components, data requirements, and information flows [46]. Irrigation operations are the object of study in this research, according to the international project "Smart Water Management Platform" (SWAMP), in which context this study is carried out. The SWAMP project aims to bring the IoT concept to Precision Irrigation and to develop irrigation systems to optimize water use [47].
As for the scope of the research, in line with the SWAMP project, the farmer or farm manager is the central actor in the decision-making process on a farm, depending on its business and organizational structure [48]. Furthermore, in the literature and in the results of expert interviews and case studies, common factors between adoption and decision making in irrigation OM can be identified. According to the research objectives, the behavior "decision making in agricultural OM" is outside the scope of this work.
Considering the research gaps identified and the research objectives, the empirical results of this work contribute to theoretical progression in the literature on the adoption of PA, adding a set of factors related to OM and farmer behavior, including this mental model. The organization of these factors in a framework represents the irrigation OM and relationships between the factors in a structured way, contributing to an explanation of the adoption. The empirical results suggest a change in the farmer mental model in the adoption of OM models inspired by the industry. The results of the case studies also contribute to exploring the relationship between the adoption and some factors, such as educational level and training.
In addition to theoretical contributions, this research also provides a practical contribution. The proposed model can be used for the development of an Irrigation Management System (IMS), integrating the agronomic management of a crop and the irrigation OM.
A future research agenda is formulated, based on the results achieved, the theoretical propositions generated from the results of expert interviews and case studies, and the scope of the work.
This work is structured with the Materials and Methods in Section 2. Section 2.1 introduces the literature review; Section 2.2 describes the exploratory multi-method. The results of the study are displayed in Section 3. A discussion of the findings is provided in Section 4, and the limitations and the research agenda are covered in Section 5. At the end, Section 6 draws the conclusions.
Materials and Methods
This section presents the literature analyzed and the method applied in this work.
Literature Review
In this section, previous studies on Precision Agriculture adoption, Agriculture 4.0, Operations Management, farmer behavior, and Theory of Planned Behavior are analyzed to identify the theoretical concepts useful for studying the adoption and for identifying the topics that can be considered factors that can affect PA adoption (theoretical basis) and for collecting the factors that can affect the adoption cited in these studies (empirical basis). The theoretical concepts, topics, and factors analyzed in this section constitute the theoretical and empirical bases in conducting expert interviews, case studies, and building the model of irrigation OM. The definitions of Precision Agriculture and Agriculture 4.0 used in this work are also reported.
Precision Agriculture, Precision Irrigation, and Factors Affecting the Adoption
In the literature, there was no consensus on the definition of PA before 2019, when the International Society for Precision Agriculture [49] proposed the official definition that this work uses. This lack of a shared definition has made studying adoption difficult. In addition, the kind of technologies [50], like yield mapping, variable rate application, and remote sensing [7,51], affects the adoption.
The PA concept encompasses Precision Irrigation (PI), which is included in the PA technologies that can optimize crop responses for applied water units [16,52]. PA technologies for irrigation enable farmers to collect site-specific data that provide valuable quantitative information for effective irrigation management [53]. PI, despite being recent and still poorly studied, has great potential to contribute to improving irrigation efficiency, thus increasing economic returns with a reduction in energy use [54]. The irrigation systems used can be classified as sprinkler (e.g., center pivot), surface, and drip systems [55]. In the SWAMP project, center pivot and drip systems were studied [47].
Regardless of the irrigation system used, it is particularly important to accurately estimate the irrigation water requirement. According to the research carried out in the SWAMP project, this study applies the Food and Agriculture Organization version of the Penman Monteith model [56,57] and the approach based on the water balance [58,59] to estimate the irrigation water requirement.
The extensive number of studies on PA adoption direct the attention of researchers towards several factors, such as characteristics of farmers (e.g., age, educational level, computer use, training), farm characteristics (e.g., size, location), benefits (e.g., reduced water use), and barriers (e.g., software cost, funding sources) [13,14,60,61]. The factors related to values and beliefs determining the farmer behavior [29] and the factors associated with the agricultural OM [15] have been little studied. Most works apply the survey method [17], while qualitative methods are little used [62][63][64][65]. Regarding Precision Irrigation, its adoption is also influenced by factors, like soil quality, water cost, energy cost, crop type [16,66].
2.1.2. Agriculture 4.0 and Factors That Can Affect the Adoption Agriculture 4.0 has a vague and unclear definition. A commonly accepted definition does not exist, and it is not entirely clear where the term Agriculture 4.0 originated [35,67]. Some researchers consider Agriculture 4.0 to be an evolution of PA [6,31,68]. According to them and to the study of Precision Irrigation adoption in pilot farms in the SWMP project, this research uses the following definition of Agriculture 4.0: " Agriculture 4.0 is a management strategy, evolution of precision agriculture, realized through the automated collection, integration and analysis of temporal, spatial and individual data, collected by IoT sensing technologies and farm resources, making in this way possible the generation of knowledge, to support the design of applications for the farmer decision making process in irrigation operations management". [69] (p.21) Most studies on Agriculture 4.0 are theoretical, but empirical works are increasing [70,71]. Research dealing with OM is still rare [32,72]. Agriculture 4.0 has the potential to bring numerous benefits, like water and energy cost decreases [73]. Through the automatic collection, integration, and analysis of data from different sources, Agriculture 4.0 allows us to generate knowledge and support the farmer in decision making, potentially increasing farm profitability [4]. Information gathered by sensors can be utilized to follow the plant and yield development progress [33].
Factors that can affect the adoption related to OM and farmer behavior include planning and control in agricultural production, degree of mobility of the production facilities [32], skills to operate equipment, limited knowledge, and capacity to adopt and to understand the technology [37].
Operations Management in Agriculture and in Irrigation
Operations Management is the management of a systemic transformation process to convert a set of inputs into outputs. These inputs include labor, equipment, raw materials, and information, while the outputs are goods and services. OM serves as a continuous improvement process to enhance quality, productivity, and customer satisfaction [74]. Its purpose is to plan and control the operations necessary to produce the goods and services demanded by the customer [28]. Production Planning and Control (PPC) is one of the core functions of OM. It aids in resource planning and utilization to ensure maximum productivity, quality, and competitiveness [75].
In agriculture, OM is responsible for designing, planning, scheduling, and executing operations involving humans and machines. An operation (e.g., seeding, fertilization, and irrigation) links resources and materials processed and produced [28,32,76]. The operations are performed with men and machines [77,78]. Resources include land, working hours, machinery, and equipment [76,79]. A management model for agricultural machinery operations, which is based on four management phases (planning, scheduling, operating, and controlling), was proposed by [27] (p.71).
The vision of OM in agriculture has evolved since the 1950s: mechanization (1950s-1970s), work organization (1970s-1990s), information and communication technologies, automation (1990s-today), and robotics (in the future). In this evolution, the notions of planning and scheduling play a central role, leading to the need for advanced management, data acquisition, and analysis tools for making decisions [28].
Farmer decisions include decisions related to development stages (such as pesticide and irrigation applications); decisions related to planting (like choice of crop type, planting date); harvest and post-harvest decisions (such as harvest date) [80]. Decision making depends on uncontrollable factors (such as weather conditions) and factors that can be modified (like irrigation infrastructure) [76]. Decisions are influenced by farm planning, which involves seasonal determinations, such as types of crops to cultivate, equipment and workforce requirements, irrigation policies [81], operational production practices, and level of production costs [82]. In addition, the farmer must consider the timeliness of some operations and that some operations and decisions are interconnected [79]. Furthermore, many operations need to be performed in a specific order, such as field preparation [83].
Regarding OM in irrigation, two decisions take priority in planning: definitions of the amount of water to apply and of the irrigation time. These decisions are affected by factors like climate and crop development stages [55]. To decide the optimal level of irrigation for each field, at the beginning of each irrigation period, farmers need to consider other factors: water availability, irrigation costs, crop size, management zones, crops planted, and soil moisture [84]. Energy is currently one of the main production resources in irrigated agriculture, and its cost must always be considered in irrigation management [54]. The cost to irrigate a field is determined by the amount of water pumped and the cost to apply it. The factors that producers can influence include irrigation planning, application efficiency, pumping pressure required, type of energy used, distance from the water source, and unit cost of energy. The cost to pump water for irrigation depends on the type of energy used, like electricity and diesel fuel [85].
2.1.4. Jason Mathis Behaviour, Theory of Planned Behaviour, and Jason Mathis Mental Model Theories Used to Explain the Adoption of Innovations A range of purely economic-based models have been developed to predict farmer decision making [86], which can be modeled in terms of individual action to maximize profit [87] or expected utility [88]. There is also extensive rural sociological literature in which the farmer attaches significant importance to aspects of lifestyle and personal considerations, which interact with management decisions. This literature suggests that purely economic models cannot capture the full complexity of farmer motivation and behavior [87], as adoption is based on farmer perceptions [89].
Four theories can be considered references to develop models to analyze the farmer decisions for innovation adoption and to establish the basis for choosing explanatory factors [90]: Utility Maximization [88], Theory of Reasoned Action and Theory of Planned Behavior [21], and Technology Acceptance Model [91].
As a result of comparing these theories and considering that the TPB provides a solid conceptual framework [92] to structure the research, this work applies the TPB. This choice is also justified by the attention to human behavior when the person has partial control over the decision making [93], characteristic of the PA context in which access to information is a barrier for the adoption [16,94]. New PA technologies are often produced through developers, and there is a large knowledge gap between developers and users [95]. Furthermore, studies based on TPB analyze farmer behaviors in a deeper and more complete way, thanks to including the Subjective Norm and Perceived Behavioral Control constructs [96].
Theory of Planned Behaviour
The TPB is a well-known and frequently applied framework to predict and explain human behavior [97] and to also study farmer behavior, like the switch from traditional to pressurized irrigation [98]. Intentions to perform behaviors can be predicted from attitude towards the behavior (ATB), Subjective Norm (SN), and Perceived Behavioral Control (PBC). The more favorable the ATB and SN are, and the higher the PBC, the stronger the intention to perform the behavior must be [21].
In TPB research, it is important to clearly define the behavior under study in terms of target to which it is directed, action performed, context in which it occurs, and relevant period [97].
The TPB is open to the inclusion of additional predictors, if they can be shown to capture a significant proportion of the variance in intention or behavior [21], and to the inclusion of background factors (such as age, educational level, experience) that can influence people's beliefs [97].
The standard research methods developed over the years for the use of TPB are largely quantitative. Furthermore, the TPB can be used as a framework to guide the questions in qualitative research [99], as in this work.
Jason Mathis and Jason Mathis Mental Model
The constructs ATB, SN, and PBC are related to beliefs about the behavior [21], which represent the information people have about a behavior, its consequences, the expectations of other people, and the impediments. By measuring these beliefs, the TPB has the potential to create the links between beliefs and behavior of an adopter of PA technologies [12].
The farmer beliefs, relative to the adoption of PA, are the basis of this mental model, built by the human mind through perception, experience, attitudes, knowledge, and the comprehension on the behavior [29]. The mental model is also relevant in decision making in agriculture. The use of farmer mental model has the advantage of a certain element of adaptation, and the drawback is the lack of precision, particularly in areas where the farmer is inexperienced. The use of computerized models allows the farmer to base their decisions on a more comprehensive set of information, gaining more precision [28]. The literature on factors affecting farmer decisions also considers conservatism, which is included in the beliefs underlying the farmer mental model [92].
This work considers, through expert interviews and case studies, the factors that can affect the adoption of innovations mentioned in this section, using the TPB as framework and focusing on farmer beliefs and his mental model, to broaden understanding of the determining factors of the PA adoption. The SN and factors related to PBC, which involve actors operating in farm ecosystem, are classified outside the scope of this study.
Method
Considering the exploratory nature of the research questions and the gaps in the theoretical and empirical basis on the factors that can affect the PA adoption, and on Agriculture 4.0, an exploratory multi-method was adopted, shown in Figure 1, consisting of interviews with experts, case studies, and the modeling of irrigation OM [39,42,43,46].
Multiple research fields were combined to triangulate the results of each method, to provide a more complete and deeper understanding of the factors that can affect the adoption of PA [43,100].
In this methodology, the researcher adopts multiple methods of data collection and data analysis. Data are collected in expert interviews and case studies to generate ideas and theoretical propositions and then to build a theoretical framework (model of irrigation OM) [39]. Interviews with experts [43] and case studies [42,101] in a pilot of the SWAMP project and on a farm in Brazil, in the State of Bahia, were conducted to identify factors that can affect the adoption and to formulate theoretical propositions for building a model of irrigation OM with the IDEF0 technique [41]. The objective of this approach was to induce emerging insights from empirical research [102], to develop theory [40,42,101]. Expert interviews and case studies are especially useful when the researcher does not know the variables to examine [39], for new areas of research or areas for which existing theory seems inadequate [101], like the explored adoption. Furthermore, as highlighted by [103], talking to experts in the exploratory phase of research is a more efficient method of data collection than, for example, quantitative surveys. Main characteristics are described below for each method.
Method
Considering the exploratory nature of the research questions and the gaps in the theoretical and empirical basis on the factors that can affect the PA adoption, and on Agriculture 4.0, an exploratory multi-method was adopted, shown in Figure 1, consisting of interviews with experts, case studies, and the modeling of irrigation OM [39,42,43,46]. Multiple research fields were combined to triangulate the results of each method, to provide a more complete and deeper understanding of the factors that can affect the adoption of PA [43,100].
In this methodology, the researcher adopts multiple methods of data collection and data analysis. Data are collected in expert interviews and case studies to generate ideas and theoretical propositions and then to build a theoretical framework (model of irrigation OM) [39]. Interviews with experts [43] and case studies [42,101] in a pilot of the SWAMP project and on a farm in Brazil, in the State of Bahia, were conducted to identify factors that can affect the adoption and to formulate theoretical propositions for building a model of irrigation OM with the IDEF0 technique [41]. The objective of this approach was to induce emerging insights from empirical research [102], to develop theory [40,42,101]. Expert interviews and case studies are especially useful when the researcher does not know the variables to examine [39], for new areas of research or areas for which existing theory seems inadequate [101], like the explored adoption. Furthermore, as highlighted by [103], talking to experts in the exploratory phase of research is a more efficient method of data collection than, for example, quantitative surveys. Main characteristics are described below for each method.
Interviews with Experts
The expert interview is a qualitative method designed to draw on expert knowledge. According to the research objective, the researcher decides who to interview as an expert in their own field of knowledge [104]. In addition to exploring knowledge, an expert interview can be used to provide guidance on a recent or unclear thematic field and to generate theoretical propositions [103].
Due to the interdisciplinary nature of this project, 27 experts were selected for their expertise in agribusiness management, Precision Agriculture, irrigation, water resources management, and Operations Management. The protocol and questionnaire used in the interviews, illustrated in Supplementary Material A, were based on the precepts of the TPB [21] and focused on irrigation OM [105]. Additional questions were asked only if a
Interviews with Experts
The expert interview is a qualitative method designed to draw on expert knowledge. According to the research objective, the researcher decides who to interview as an expert in their own field of knowledge [104]. In addition to exploring knowledge, an expert interview can be used to provide guidance on a recent or unclear thematic field and to generate theoretical propositions [103].
Due to the interdisciplinary nature of this project, 27 experts were selected for their expertise in agribusiness management, Precision Agriculture, irrigation, water resources management, and Operations Management. The protocol and questionnaire used in the interviews, illustrated in Supplementary Material A, were based on the precepts of the TPB [21] and focused on irrigation OM [105]. Additional questions were asked only if a participant response to the initial question did not cover certain topics of interest [106]. To reduce response bias, the definition of Agriculture 4.0 was not included in the questionnaire and was not provided to respondents [43,107].
To establish how many interviews to conduct, there are several factors affecting the sample size: population heterogeneity, budget, available resources, scope of the study, experience of the interviewer, availability of participants [108]. According to [106], in this work, intentional sampling was applied, with the aim of reaching data saturation (data saturation is the point in data collection and analysis when new information produces little or no change in the codes [106]) in relation to the codes (codes are theory or model building blocks on the basis on which the researcher arguments rest, according to the research question [106]) identified from data collected in the interviews and then in relation to the identified factors. So, the number of experts interviewed was 27, because when the 27th interview was completed, no new information was observed in the data. As, in this research, probabilistic sampling was not applied, the sample of experts interviewed is not representative. Furthermore, the codes ("deconstruction" of experts' knowledge) and the theoretically inspired perspective ("reconstruction" of experts' knowledge) were identified based on the knowledge of the literature on PA, Agriculture 4.0, OM, and farmer behavior [109]. The result was a review of the texts and terminology of the interviewees and the consequent creation of codes. This led to a "reconstruction of experts' knowledge" and to the representation of empirical results [104].
As a result of the evolution of the COVID-19 pandemic, it was not possible to access the university to use software to analyze the data collected in the interviews.
Case Studies
The researcher chooses single cases when the purpose is exploration and in-depth study [42], while he chooses multiple cases when the logic of replication in more cases is pursued rather than sampling [40,101]. Therefore, two in-depth case studies were conducted, considering the exploratory purpose for theory development and the possibility of carrying out in-depth studies.
In line with the objective of disseminating the SWAMP project results, case studies were conducted on two farms in Brazil: the first in the MATOPIBA pilot, and the second on a farm not involved in the project. To preserve and guarantee confidentiality, this company was named "Farm Bahia". The two case studies provided homogeneous characteristics in terms of interest in participating in research projects, farm size (industrial farm), location (State of Bahia), climatic region, irrigation system (center pivot), organizational structure (farm manager), and farmer characteristics (i.e., age, educational level, innovation capacity). Therefore, according to [40], these studies presented profiles to predict similar results.
The protocol for the case studies and the questionnaire with the objective of the interview, the context of which the research is part, and the proposed questions are shown in Supplementary Material B. The questions, based on the TPB precepts and focused on the irrigation OM, were the same as in the questionnaire used for the interviews with experts. Instead of the phrase "Agriculture 4.0", questions referred to sensors and drones, to be equipment the farmer could identify as representative of innovative technologies for irrigation, in addition to being equipment included in the context of Agriculture 4.0.
The data collection techniques applied were as follows: interviews, photos, farm reports, farm contracts, consultants' reports, and IMS database. The interviews were conducted remotely, and it was not possible to visit the farms due to the COVID-19 pandemic. To analyze the data collected in the case studies, the process of coding the data collected in the interviews with experts described in Section 3.1 is applied [63,64].
Modeling Techniques and IDEF0
In the literature, there are different techniques for modeling the structure, behavior, and organization of a company or information system, such as IDEF0 and Unified Modeling Language [44,45]. Considering that the IDEF0 is simple, it allows for the development of conceptual models of business models, and it is a standard governed by rules and conventions, representing data and resources in the same diagram. This work applied the IDEF0 technique to model the irrigation OM, also in accordance with the exploratory purpose of the question and research objectives. Furthermore, in the OM literature, the IDEF0 technique was applied by several authors to model PPC in companies in the manufacturing [46,[110][111][112] and agricultural sectors [45].
An IDEF0 model involves a hierarchy of diagrams whose central components are boxes (representing a function: activity, action, process, operation) and arrows, representing an interface. An interface can be an input, entering the left box, transformed by the function and leaving the right box as output; a control, entering the top of the box and determining the function (i.e., procedure, command, worker experience); a mechanism, a tool or resource performing the function. Each box can be broken down to a lower level of detail, forming a hierarchy of information that is summarized in a tree of nodes [41].
Results
This section presents the results of the interviews with the experts, the case studies in the MATOPIBA pilot and on "Farm Bahia", and the model of irrigation OM. The data collected in the expert interviews and case studies, associated with the factors found in the theoretical and empirical bases of the literature, were used to identify the categories and factors that can affect the explored adoption. These data collected were coded based on the TPB constructs in scope (Attitude and Perceived Behavioral Control), on the categories and factors resulting from the literature review [21,101,109]. The coding process to identify the categories "Operations Management models inspired by the industry" and "Resources", and the factors "operations planning and control models", "resources (hardware-agricultural equipment, sensors)", is presented in Table 1. In agriculture OM is responsible for designing, planning, scheduling, and executing operations involving humans and machines [28]. Production Planning and Control (PPC) is one of the core functions of OM [75]. Agriculture 4.0 allows to improve planning and control in agricultural production [32]. Agriculture 4.0 allows to follow plant and yield development progress through information collected by sensors [33].
"There are classic industry planning tools the farmer could use, such as PERT, CPM, and ABC costing system", expert 1. "The adoption of Agriculture 4.0 allows the farmer to optimize the use of resources, the use of water. The adoption of sensors improves irrigation and equipment planning so that irrigation is more effective", expert 5.
Responses from interviews and case study data were categorized based on TPB constructs and then analyzed to identify excerpts with similar topics from the interviews ("deconstruction" of the knowledge of experts and farm managers). Based on the factors identified in the literature on PA, Agriculture 4.0, farmer behavior, and OM, excerpts with similar topics were grouped into codes to define categories and factors ("reconstruction" of knowledge). The empirical results were framed by a theoretically inspired perspective [104], guided by the TPB and the introduction of inspired models from the industry, like the PPC.
The codes were organized into categories (e.g., "performance measures", "data access") and factors. The proposal to introduce industry-inspired models in irrigation was based on the factors related to OM analyzed in Section 3.1 from interviewed experts. This process was recursive, while in the analysis, it was necessary to return to a previous stage to verify the adequacy of generalizations [104]. In the analysis of data collected, a check was carried out to identify categories and factors found in other answers [40].
Results of Expert Interviews: Factors and Categories That Can Affect the Adoption
Between April and August 2021, 27 interviews with experts were carried out. Supplementary Material C summarizes the experts' profiles. The choice criteria were based on the interviewees' expertise in agribusiness management, PA, irrigation, water resource management, and OM. Experts with experience as researchers and in water resource management were included, considering the importance of this topic for this work. Initially, four experts were selected who illuminated the research questions. To select the other experts, the "snowball" sampling technique was adopted [113].
All interviews were conducted remotely because of the COVID-19 pandemic. A pilot interview was organized to test the questionnaire [102]. The questions were unambiguously formulated, and clarifying questions were asked to complete the expert answers [18]. All in-terviews were recorded and transcribed in full. Confidential and sensitive references or data were omitted or substituted to ensure the privacy and anonymity of the interviewee [106].
The answers of the experts interviewed were categorized and classified to produce the transcripts, with the results shown in Supplementary Material D. The factors and categories are shown in Table 2. The factors and categories are classified according to the TPB constructs and based on previous studies on PA, Agriculture 4.0, OM, and farmer behavior. Regarding the analysis of the interviews, if the quotes led to the identification of benefits and positive results expected following the adoption, the factors were classified in the attitude construct. If the quotes led to identifying obstacles, resources, and opportunities related to the adoption, the factors were classified in the PBC construct. The factors and categories identified in the responses to additional questions were included in the most proper factors and categories, based on the coding process. Factors unrelated to OM and relative to stakeholders in the farm ecosystem were classified as out of scope.
The benefits of the studied adoption can be measured through performance measures related to attitude, identifying quantitative or qualitative benefits that can be achieved with adoption. Quantitative performance measures are benefits to which a measurement can be associated concerning planning and the control of irrigation operations. All the experts pointed out that the adoption involves a cost reduction: irrigation water use and energy use reduction. Experts 11, 14, 16, 23, and 27 added that the adoption can lead to a rational use of water in terms of irrigation in the right amount, closer to the crop water requirement, at the right time and in the right place. The reduction in water use, and the relative cost, has an impact on energy savings, according to experts 2, 8, and 11: "The farmer will have a water savings because he will be able to define the exact amount of water for that exact area, and with that he will be able to save energy which is one of the big problems in irrigated agriculture", expert 11. Experts 23 and 25 emphasized that the reduction in water use, and the relative cost, affects an increase in production yield due to irrigation efficiency. Therefore, saving water and energy has a positive impact on the farm economic results, as suggested by experts 6, 11, and 16.
Regarding qualitative performance measures, the interviews allowed us to identify benefits related to irrigation management, as stated by expert 3 (management benefits compared to increased productivity) and expert 2 6 (changing from planning based on experience to planning based on data).
The explored adoption can bring benefits thanks to access to more organized data, promoting better operation planning and control, as reported by experts 16, 26, and 27. These benefits could be related to access to agronomic data on crops, soil, and climate, possibly due to the adoption of sensing technologies, according to experts 11 and 27. These data can be used to calculate the crop water requirement and irrigation water requirement. The farmer also has the possibility to access operational data related to irrigation operations, such as water availability, water flow, cost of water use, water access contract, and energy supply contract, according to experts 1, 17, 18, and 27.
Factors concerning the changes required for the adoption are classified into two categories: "Changes for the farmer" and "Changes for the farm".
As for the changes for the farmer, they must be trained to adopt PA technologies, as reported by experts 15 Managerial training concerns specific skills for data analysis, planning, and management of new technologies, as reported by expert 6, who stated: "It is necessary to change the farmer managerial training and the workforce qualification, because the adoption of Agriculture 4.0 involves the introduction of a production system that demands a set of specific skills, of data analysis, of handling machinery to operate according to the planning". Experts 1, 10, 13, and 24 show that this change must overcome some challenges in terms of farmer perception, low levels of education, and training, including the areas of operation engineering and management. Expert 1 emphasized that: "Planning is not easy for the farmer, because he was not trained for it, he understands little about operation engineering, and often those who advise the farmer do not have this training either".
These challenges are linked to the need to change the farmer mental model, according to experts 2 and 20. Expert 14 stated that: "The main barrier is cultural, in addition to the need to be trained to assimilate these technologies. And it depends on the farmer age, who mainly relies on his experience". This mindset shift involves irrigation management, data-driven management, and managing the farm as a business. The farmer needs to change their belief that irrigating is different from applying water and irrigated agriculture is different from rainfed agriculture plus water, as highlighted by experts 4, 11, and 17. The farmer also needs to change his mental model to move from intuition and experience-based management to data-based management, which brings benefits to the planning of operations, as reported by experts 14, 15, and 26. Expert 21 stated that: "The culture of many farmers is based on family and community knowledge, transmitted from father to son, rather than adoption of techniques from scientific knowledge. There is a gap between the supplier of knowledge, which leads to training and the ability to understand, and the farmer in the adoption of irrigated agriculture techniques".
The shift to data-based management must also make farmers aware that water is a scarce resource. The adoption of sensing technologies can enable this change on water scarcity, which can be measured with a rational use of water, as said by experts 10, 19, 22, and 27.
Regarding the management of the farm as a business, the farmer has great difficulty in management, as reported by expert 12. Experts 5 and 23 added that the farm management must also include irrigation planning and control: "Irrigation control is something that should always be considered in a planning process, which is part of managing a property".
In addition to the changes for the farmer, the analysis of the interviews enables one to identify the factors classified in the category "Changes for the farm". For the studied adoption, farm management results as the central change, as reported by experts 14 and 10, which must be built on the basic functions of administration (planning, implementation, and control). The changes for the farm also involve the Operations Management, according to expert 6: "The OM has developed with a short delay in Brazil. These are aspects of agricultural production that have not evolved at the same speed as the agronomic aspects". Expert 1 highlighted that the OM is an area undervalued by the farmer because he does not have much knowledge about it. Expert 20 added to this with changes in organizational characteristics, such as control mechanisms and performance indicators, while expert 6 also emphasized the characteristics of integration between different systems within a farm to collect and analyze production data. Another factor classified in the changes for the farm is the qualification of the workforce, which is considered one of the cornerstones to overcome for adoption, according to experts 4, 6, 9, 12, and 19.
It is important to highlight that these changes related to the adoption studied must be gradual, and the adoption of Agriculture 4.0 is not a single path, as stated by experts 2, 4, 7, 12, and 26. Expert 12 said that " Agriculture 4.0 has several stages and the farmer can move from the initial one, which do not involve robotization. The farmer can adopt with a more gradual process in which the cost-benefit analysis is easily identified".
Concerning the category "Operations Management models inspired by the industry", experts 1 and 6 inspired the adoption of planning and control models of operations, which consist of planning, scheduling, and control of irrigation management. Expert 1 pointed out that these models are not yet applied in agriculture and suggested industry models such as PPC: "There are planning tools, classic in the industry, such as PPC, for the planning of operations: the farmer would need to have process mapping, production flow, activities, times, costs of machines, labor, demand forecast. With this information, the farmer could create a proper decision making support system".
Another opportunity available to the farmer, following the adoption, is constituted by collaborative management models, as reported by experts 16, 22, 25, and 27. Expert 1 6 suggested the use of a process of negotiated allocation of water: "The water resources management agency can talk to the farmers to check who will plant, who will not, who will irrigate and who will not, to distribute the available water in the most critical period and prevent the farmer from planting". Expert 25 inspired the adoption of the Just-in-Time (JIT) management model [114] to control the use of motors and pumps in irrigation systems for monitoring water abstraction in farms. The adoption of these collaborative models enables them to overcome some challenges related to irrigation planning and control in the case of shared management of water resources, ensuring the availability of water throughout a season for the farmer.
The analysis of the responses relative to the PBC also identifies the category "Resources", which includes inputs, hardware, and people. These resources are necessary for the management of information concerning the planning and control of operations, according to experts 1 and 27. The adoption of hardware makes it easier to achieve benefits for irrigation planning, as in the case of sensors: "If the farmer works with sensors, he has more accurate data on water withdrawal and applied for irrigation. He can plan the irrigation system so that irrigation is more effective", expert 5.
Regarding resources, experts 2, 3, 8, and 24 highlighted the role of consultants in irrigation planning. Expert 3 emphasized that: "Companies that provide services on irrigation planning obtain data from equipment, sensors and have a team that processes this data and makes recommendations to the farmer". These services are predominantly contracted by large producers, who normally have a skilled workforce, as reported by expert 2.
Based on the quotes from the experts, the explored adoption can also be affected by the farmer characteristics, farm characteristics, and technology characteristics, as highlighted by expert 1: "The application of the technologies included in the concept of Agriculture 4.0 will have different speeds, according to the regions of the country, the farm and farmer characteristics, the product types. In some plants and some farms, Agriculture 4.0 should arrive faster"; expert 5 shared this view.
Concerning the study of the benefits of the adoption, and according to the importance of the attitude construct for the benefits associated with the adoption and perceived by the farmer [86,115], it is important to emphasize the farmer characteristic "conservatism", as highlighted by expert 3: "The rural producer does not believe in things, he wants to see things". Expert 30 added: "For the farmer to trust an innovation, he needs to see where it worked, it was tested, there are results and how he can adopt it".
As reported by expert 1, the adoption can also be affected by the farm characteristics. Cooperativism is a factor that can help in the adoption and use of models for irrigation OM, such as hiring consultant services, according to experts 3 and 24.
Results of Case Studies: Factors That Can Affect the Adoption
To conduct the case studies, the MATOPIBA pilot and "Farm Bahia" were selected due to their qualities in innovative irrigation systems. Theoretical sampling was adopted [101] due to the characteristics of the farms linked to the theory and the literature addressed in this work, such as exploring the adoption in farm size-industrial farm and in center pivot irrigation system. The choice of "Farm Bahia", familiar with the participation in research projects, was also consistent with the objective of the SWAMP project to replicate the results in terms of models and solutions.
The research protocol was designed with the questions to be applied in the interviews and the specific data to be collected [21,101,105]. Interviews with the farm manager of the MATOPIBA pilot were conducted between January 20 20 and December 2021 and with the "Farm Bahia" manager between June 2021 and December 2021. The farm was the unit of analysis, according to the SWAMP project objective and the research questions [40].
The factors that can affect the adoption resulting from the cases, shown in Table 3, were classified according to the TPB constructs and the theoretical and empirical bases, and were triangulated with the findings of expert interviews [40,43]. Furthermore, a "within-case analysis" (factors in columns of Table 3) and a "cross-case pattern search" (patterns between the two cases identified considering the factors in each row and described in the text illustrating the table content) [101] were conducted.
3.2.1. Within-Case Analysis: "Farm Bahia" "Farm Bahia" is managed by a farm manager who graduated in Agricultural Engineering. The authors' perception is that the manager's conservatism is low, and he has a propensity to risk in relation to the adoption of innovations. Quantitative measures related to the use of water and electrical energy are used on the farm, such as crop water requirement, water use, energy use, cost of water use, and cost of energy use, in addition to economic measures.
Regarding the access to agronomic data, a weather station supplies meteorological data. Crop, soil, and irrigation data are accessible through an IMS, which also provides operational data, such as production yield, revenue, and cost per center pivot. The electrical energy supply contract makes data on operating time and the cost of energy use available.
As for the changes for the farmer, the farm manager has technical and managerial skills since he has a degree in Agricultural Engineering. Management is based on data the and scientific method (e.g., water balance to estimate the irrigation water requirement), although experience is a relevant factor in irrigation planning and control. The skills related to OM are limited due to the low valuation of this area. The possibility of access to the market does not pose challenges. He is aware that the main changes are managerial, related to the need for training to use new technologies, to read the data correctly, and to manage irrigation planning and control. His mental model is aimed at minimizing energy use cost, due to the lack of a definition for water use cost.
Concerning the farm changes, the case study presents two changes. The first involves the OM, since this is an area undervalued and the manager is not skilled. Workforce qualification results in another key change due to the low educational level of the farm workers. These challenges can be overcome considering the size of the farm, its possibilities of accessing the market, farmer low conservatism, risk propensity, and capacity for innovation. In relation to the models of OM inspired by the industry, the case shows a gap in the adoption due to little importance of this area and low managerial training.
The farm manager uses the IMS for irrigation planning. The estimation of the crop water requirement, the planning of irrigation water requirement, and of irrigation time are conducted by consultants using the water balance approach. The nightly, daytime, and peak operating times of the center pivots are defined based on the energy supply contract. The farm manager planning objective is to minimize the cost of electrical energy use to take advantage of the nightly operating time. As for irrigation control, he manually analyzes soil moisture based on experience. Center pivot control operations are also performed manually because of the bad quality of electrical energy.
Regarding the resources, the contract for accessing water is formalized, but the cost of using irrigation water and the time and volume of abstraction are not defined yet.
Within-Case Analysis: Farm of the MATOPIBA Pilot
The MATOPIBA pilot farm is directed by a manager who graduated in Agricultural Engineering, with low conservatism and propensity to risk in relation to adoption innovations. Quantitative measures related to the use of water and electrical energy are used. The farm manager uses a weather station and an IMS to access agronomic data, while he uses the water access contract and the electrical energy supply contract for access to operational data.
As for the technical and managerial skills, for the MATOPIBA pilot, manager experience is still a crucial factor in irrigation planning and control. The changes for the farmer, mainly managerial, do not represent major challenges, due to the possibility of access to the market. Regarding technical training, the central challenge is where to irrigate based on soil probe data and, therefore, implementing the variable rate irrigation. His mental model is aimed at minimizing the cost of electrical energy use due to the lack of water use cost in the current contract. Regarding the farm changes, the case presents two changes related to OM and the qualification of the workforce. The MATOPIBA pilot manager administers irrigation planning with the support of the IMS. The irrigation water requirement is estimated weekly using a water balance approach. Irrigation water requirement and irrigation time are planned based on the cost of electrical energy use, which prioritizes nightly operating time. Nightly irrigation is more economical, as the cost of electrical energy use is ten-times lower than during the day. As for irrigation control, center pivot operations are performed manually based on experience. Regardless of the contract for access to water, the cost of water use, the time, and the volume of abstraction are not defined yet.
Cross-Case Pattern Search
The two farms present homogeneous factors in terms of farmer characteristics, farm characteristics (mainly farm size-industrial farm, farm location), quantitative and qualitative performance measures, access to agronomic data, access to operational data, changes for the farmer and for the farm, models of OM inspired by the industry, and resources. The IMS used by the two farms is provided by the same supplier. On both farms, the contract for access to water is formalized, but the cost of water use, the time, and the volume of abstraction are not defined yet.
In relation to the models of OM inspired by the industry, in the MATOPIBA pilot, the irrigation planning is administered by the farm manager, while in "Farm Bahia", the estimation of the crop water requirement, the planning of irrigation water requirement, and the irrigation time are conducted by consultants. The two farms have some of the heterogeneous characteristics of the irrigation system. In the MATOPIBA pilot, two center pivots are powered by electric pumps, and the others are supplied through a reservoir, which enables one to reduce evaporation during water distribution. In "Farm Bahia", all 17 center pivots are supplied directly from a river. As for sensing technologies, the MATOPIBA pilot is carrying out a project for the adoption of soil probes and performing variable rate irrigation. The farm manager is assisted by agronomic experts in planning irrigation water requirements. He also hires management consultants to control the electrical energy use and for some issues inherent to the supplier agency (i.e., high fixed monthly cost, low quality of electrical energy). The manager of "Farm Bahia" hires management consultant services for the renewal of the water access contract and technical consultants to remotely control the electrical energy use on a weekly basis.
Results of the Expert Interviews and Case Studies: Theoretical Propositions
The results of the expert interviews and case studies allow us to generate ideas and formulate theoretical propositions [39,40] to explain the relationships between the adoption and the identified factors. The theoretical propositions, which provide a solid foundation for modeling irrigation OM and to direct future research, are illustrated below in the order of categories and factors shown in Table 2 and 3.
Theoretical proposition 1: According to experts 2, 3, 6, 8, 11, 14, 16, 17, 23, 24, 25, 26, and 27 and the two farm managers, the adoption of PA in the context of Agriculture 4.0 allows for achieving advantages and benefits that can be measured through quantitative performance measures. The adoption involves cost reductions in irrigation, water, and energy use; the reduction in water use, and the relative cost, also affects an increase in production yield due to irrigation efficiency; saving water and electrical energy has a positive impact on the economic results of the farm. Theoretical proposition 1a: Based on interviews with experts 3, 20, 26, and 27, the adoption allows us to obtain advantages and benefits that can be measured through qualitative performance measures.
Theoretical proposition 2: As stated by expert 16, the explored adoption can bring benefits thanks to the access to more organized data. Theoretical proposition 2a: According to experts 16, 26, and 27, access to more organized data allows for better operation planning and control. Theoretical proposition 2b: Based on interviews with experts 11 and 27, the benefits of the adoption may also be related to the access to agronomic data on the three pillars of crop, soil, and climate. Theoretical proposition 2c: As stated by experts 11 and 27, these data can be used to estimate the crop water requirement and irrigation water requirement. Theoretical proposition 2d: According to experts 1, 17, 18, and 27, access to agronomic data is provided by the adoption of sensing technologies. Theoretical proposition 2e: Based on interviews with experts 11, 17, 18, 24, and 27 and the two farm managers, the adoption of PA in the context of Agriculture 4.0 makes it possible to obtain benefits thanks to the access to operational data concerning irrigation operations. Theoretical proposition 2f: According to both farm managers, the IMS provides operational data. Theoretical proposition 2g: Based on interviews with both farm managers, the electrical energy supply contract provides data on operating time and the cost of energy use in different periods; the operating times of the center pivot are defined based on the electrical energy supply contract. Theoretical proposition 2h: As stated by all the farm managers, the contract for access to water provides data on the cost of water use, abstraction time, and volume.
Theoretical proposition 3: The explored adoption requires farmer changes. Theoretical proposition 3a: According to experts 1, 5, 6, 7, 10, 11, 13, 15, 16, 17, and 24 and the two farm managers, to adopt these technologies, the farmer must be trained. Training includes technical and management training; managerial training comprises skills for data analysis, planning, and the management of new technologies. Theoretical proposition 3b: Based on interviews with experts 2, 4, 11, 14, 17, and 20, the adoption requires changes in the farmer mental model, which involve irrigation management due to the need to change the belief that irrigating is different from applying water, and irrigated agriculture is different from rainfed agriculture plus water. Theoretical proposition 3c: As stated by experts 14, 15, 19, 20, 21, 22, 26, and 27, changes in the farmer mental model involve data-driven management, as moving from experience-based management to data-based management provides benefits for operations planning. Theoretical proposition 3d. According to experts 10, 19, 22, and 27, changes in the mental model include the farmer awareness that water is a scarce resource. The adoption of sensing technologies can make this change possible. The farmer needs to understand that the agricultural field has variability. Theoretical proposition 3e: Based on interviews with experts 5, 12, 23, and 24, changes in the mental model involve the management of the farm as a business. The farm management must include irrigation planning and control; the farmer often does not know the production cost and does not understand their costs and income. Theoretical proposition 3f: As stated by expert 18 and the two farm managers, to overcome the challenges related to changes, the farmer can access technology, finance, and educational markets.
Theoretical proposition 4: The explored adoption requires farm changes. Theoretical proposition 4a: Based on interviews with experts 6, 10, 14, 17, and 20, farm management must be based on the basic functions of administration. Theoretical proposition 4b: According to experts 6 and 20 and the two farm managers, changes are also necessary in organizational characteristics in integration between different farm systems. Theoretical proposition 4c: As stated by experts 1 and 6 and the two farm managers, changes include OM, which has not evolved at the same speed as agronomic management. Theoretical proposition 4d: Based on interviews with experts 4, 6, 9, 12, and 19 and all farm managers, the changes involve the workforce qualification, which is one of the main barriers to overcome for the adoption.
Theoretical proposition 5: As stated by experts 2, 4, 7, 12, and 26, the changes about the adoption studied are gradual. Theoretical proposition 6: According to experts 1, 3, 4, and 6, for the adoption, the farmer makes available models of planning and control of irrigation operations, inspired by models of the industry, such as PPC. Theoretical proposition 7: According to experts 16, 22, 25, and 27, for the adoption, the farmer has the possibility to use collaborative management models, which allow one to overcome some challenges related to irrigation planning and control in the case of shared management of water resources.
Theoretical proposition 8: Based on interviews with experts 1 and 27 and both farm managers, for the explored adoption, resources to manage information concerning OM must be available to the farmer. Theoretical proposition 8a: As stated by experts 2, 8, 9, 14, 17, and 18 and both farm managers, the resources include water and energy inputs. Theoretical proposition 8b: According to experts 2 and 5 and the farm managers, the resources include hardware, such as sensors, drones, and satellites. Theoretical proposition 8c: Based on interviews with experts 2, 3, 5, 8, and 24 and the two farm managers, the adoption of resources like sensors allows us to obtain benefits for operations planning. Theoretical proposition 8d: As stated by experts 2, 3, 8, 23, and 24 and the farm managers, the resources include people.
Propositions 1, 1a, 2, 2a, 2b, 2c, 2d, 2e, 2f, 2g, 2g, 2h, 4d, 6, 8, 8a, 8b, 8c, 8d, and 10 support the proposal of the irrigation OM model presented in Section 3.4. The factors educational level, training, access to data, and resources (people-consultants) are discussed in Section 4.3. Other factors, out of the scope of this paper, will be analyzed in the future research agenda. Irrigation planning emphasizes the dimension "planned" to the output factors: irrigation water requirement, irrigation time, water and energy use, and water and energy use cost. Irrigation planning can be referred to as a timescale of the harvest or within the harvest, according to experts 1 6 and 20.
Model of Irrigation OM
To plan the crop water requirement, data from three pillars are essential: crop, soil, and climate (factors related to theoretical propositions 2b and 2c), as reported by experts 11, 15, 16, and 23. The irrigation schedule establishes irrigation days based on irrigation planning procedures, such as minimizing the cost of energy use, taking advantage of irrigation at night time, given the energy supply contract and the relative unit cost of energy at different times during the day, as reported by the two farm managers and expert 2. The factors mentioned are addressed in theoretical propositions 2e and 2g.
Irrigation time can be planned in relation to nightly, daytime, and peak operating times (factors related to theoretical propositions 2e and 2g), according to the two farm managers and experts 10, 14, and 25. Water use, water use cost, energy use, and energy use cost can be planned based on different operating times. Energy use and energy use cost can be planned depending on the irrigation equipment like pumps and motors, as reported by the two farm managers (factors related to theoretical propositions 2e, 2g, 2h, 8a, and 8b). The pumps and motors can be powered by diesel oil, renewables, or electrical energy, according to [116] and expert 27. Irrigation planning can be conducted at the level of the farm and field.
The controls facilitating the execution of the function consist of the same factors as in the context diagram, except for irrigation scheduling and control procedures, based on farm manager interviews and experts 1, 11, 15, 16, 17, and 23. The contract for access to water is essential to know the availability of water for irrigation, as reported by experts 16, 25, 26, and 27 (factors addressed in theoretical propositions 2b, 2c, 2g, 2h, and 10).
Water can be unlimited or limited, according to experts 14, 16, 25, 26, and 27. Water availability for irrigation is also influenced by collective access to water resources, which poses challenges for irrigation planning based on factors, such as water demand, water supply, available water volume, farm location, priority in access, and the economic sector (human activity, animal breeding, irrigation, industry) in the case of conflicts over water use, according to experts 9, 14, 15, 17, 18, 24, 26, and 27 (factors related to theoretical propositions 2h and 10).
The energy supply contract can contribute to establishing the planning procedures since the cost of electrical energy can vary based on the hours during the day and can impact the definition of irrigation time, as reported by the MATOPIBA pilot farm manager: "Nightly irrigation is what makes the business viable". The manager of "Farm Bahia" said the following: "The priority is to take advantage of the time reserved for irrigation, which is 9 h a night. But irrigation is carried out during the day too, almost all pivots are off by 11:00". Experts 2 and 14 agreed with this (factors addressed in theoretical propositions 2a, 2e and 2g).
Farm planning involves distinct factors affecting seasonal decisions the farmer must make, like crops to cultivate [81,117]. Expert 1 highlighted the strategic nature of this planning, which involves long-term decisions (factor related to theoretical proposition 6). Farm planning also involves economic factors the farmer needs to consider. Experts 3, 4, 16, 24, 25, and 2 6 cite input price and availability, production cost, product prices, and market trends. As highlighted by the results of the two case studies, the cost of the electrical energy plays a fundamental role because it can influence the use of electrical energy and the planning of the operating time (factors mentioned in theoretical propositions 2e and 2g).
Experts 1, 9, 15, 20, 22, 24, 25, 26, and 27 cite another characteristic of agriculture, which is the uncertainty related to climatic factors, such as precipitation, water availability, and air temperature (related to theoretical propositions 2b). Expert 18 added the volatility of rainfall and drought due to the extension of Brazilian territory, while expert 2 6 stated that the explored adoption can contribute to reduce the risk related to these factors: "The more the farmer invests in Precision Agriculture in the context of Agriculture 4.0, the greater the information base and knowledge of these factors he has. Therefore, the greater the control of his business" (factors related to theoretical proposition 2b). Experts 13 and 31 added that the availability of more information leads to reducing the risks in agricultural production, for example, with climate change, which has increasingly prolonged effects. According to expert 34, the risk, linked, for example, to a possible period of drought, which may be critical based on the type of crop that the farmer plans to cultivate, can be reduced if information is made available to the farmer in real time. Expert 10 highlighted that: "In the manufacturing industry the production process is somehow dominated, particularly inside a factory or warehouse, it is a well-known process. In agriculture, it rains, it rains more, it rains less, there it's hail, there is a problem with an epidemic of foot and mouth disease, fruit flies, rust in soybeans. This is why the planning and control of agricultural operations are very critical and challenging. The adoption of innovative technologies and models of OM poses a challenge to the farmer aimed at reducing the risks of seasonality on production management". Expert 25 added that due to climate changes, the statistics used for planning increase their uncertainty and, for this reason, the adoption of PA would provide access to more reliable and complete data and, therefore, it could reduce the risk in irrigation OM.
Irrigation planning processes the following inputs: crop characteristics, meteorological data, soil characteristics [58,118,119], the availability of water for irrigation, as reported by experts 17 and 27, the characteristics of the irrigation system (like minimum depth of water to apply, water flow, irrigated area), the unit cost of water, and the unit cost of energy according to the two farm managers (factors covered by the theoretical propositions 2b, 2e, 2g, and 2h).
The mechanisms used in the planning of irrigation are considered in terms of the farmer or farm manager, the consultant, the IMS, and the sensing technologies [118,120] (factors related to theoretical propositions 8, 8b, 8d). The farmer oversees irrigation management. Farms such as the MATOPIBA pilot and "Farm Bahia" use an IMS to assist the manager in planning. Sensing technologies support planning thanks to the collection of field data and access to more correct data, as reported by expert 5 (factors related to theoretical propositions 2, 2b, 8b, and 8c). Experts 2, 3, 10, and 23 highlighted the role of the consultant (addressed in theoretical proposition 8d) as an opportunity to support the farmer.
Key outputs of irrigation scheduling are the allocation of agricultural resources: people, machines [77], irrigation technique [121][122][123], irrigation resources, and water sources, according to the two farm managers (factors related to theoretical propositions 8 and 10).
In the case of shared water sources, such as a collective irrigation canal or watershed, the access to water and its use depend on the water access contract, as highlighted by experts 2, 8, 14, 16, 17, 25, 26, and 27. Expert 9 added that farmer location also affects irrigation scheduling, for example, in an irrigated perimeter. The contract can regulate the use of resources for measuring the water use, which farmers must install to measure the water flow, according to expert 2 (factors analyzed in theoretical propositions 1, 2h, and 10).
Irrigation scheduling produces a reservation and an operation sequence to execute. An example is described in the case of "Farm Bahia", in which the operation "execution of irrigation with the application of irrigation water requirement equal to 9.4 mm in 50% of the irrigated area", using the resource "center pivot 4", is scheduled on "day 1" (factors related to theoretical propositions 2, 2e, and 6). Irrigation scheduling procedures involves priority rules such as the minimization of the cost of electrical energy use relative to the use of water. This rule defines the priority for executing the irrigation in the night period in the two case studies (factors addressed in Theoretical propositions 1, 2g, and 6).
According to the proposal to adopt a management model inspired by the industry (factor related to theoretical proposition 6), irrigation scheduling can be considered planning at the operational level, as reported by expert 1: "The farmer has a planning that is more strategic, long, and medium term. And then there is a more operational planning, for defining the planning of the machines, irrigation, spraying, harvesting, post-harvesting".
The execution of irrigation affects the performance of the scheduled operations [124]. Scheduled resources are expected to be activated automatically in the context of Agriculture 4.0, as stated by expert 26. Experts 1 and 22 highlighted the benefits that automation can bring in relation to switching on and off the irrigation equipment (factors concerning theoretical propositions 1 and 8).
However, experts 1 and 2 added a challenge related to the quality of electrical energy (factor addressed in theoretical proposition 2g) for performing irrigation with an automated system: "The farmer cannot install an automation system to turn the pump on and off and the control systems because the energy quality will burn this equipment more quickly, due to the overload", expert 2. Expert 17 also cited the challenge of Internet coverage on the farm location (factor related to theoretical proposition 10) to enable the execution of irrigation with an automated system, while expert 18 highlighted the challenge of training the workforce (factor addressed in theoretical proposition 4d) to execute a system based on automation. The challenges of electrical energy quality and Internet coverage are also confirmed by the manager of "Farm Bahia": "Despite having installed 17 center pivots, our system is all manual, because the electrical energy quality is very bad. The less the system is automated, the lower the risk that equipment can burn out. If all the center pivots are turned on at the same time, the power drops, so each center pivot has a different starting time by one minute".
Outputs of the execution of irrigation result in status and some performance indicators: final irrigation time, final water use, final energy use, final water use cost, and final energy use cost, based on irrigation planning and scheduling outputs. The explored adoption allows us to achieve measurable benefits, according to experts 2, 11, 14, and 25 (factors analyzed in theoretical propositions 1, 2, and 2a).
The control of irrigation receives other function outputs to monitor the irrigation system and its resources [122,125]. In the case of irrigation equipment, for example, this function controls the input application, as reported by experts 2, 15, and 1 6 (factors related to theoretical propositions 2e, 6, 8, and 8b). Expert 2 highlighted that: "The great advantage of adoption is that the farmer controls the application of water, energy, fertilizers. So, when he gains precision in applications, he controls the level of energy use, which has an extremely high cost". Experts 9, 16, and 23 added other benefits, such as localized water application, application uniformity, equipment efficiency, and pressure control (factors analyzed in theoretical propositions 1, 2, and 2a). This control helps the farmer in relation to the risks of insufficient and excessive irrigation [118] (factors related to theoretical propositions 1 and 2a).
Through resources such as sensing technologies, the three agronomic pillars are also monitored, according to experts 2, 14, 15, 16, and 23. Expert 23 stated: "It is important to evaluate the result of the irrigation by looking at the plant, using satellite and drone. And controlling how the plant is responding" (factors dealt with in theoretical propositions 1, 2b, 2f, 8b, and 8c). Therefore, controlling irrigation operations through sensing technologies can affect the adoption of PA. Expert 23 emphasized the large volume of data available and accessible thanks to these technologies, whose utilization can improve the visual inspection. The adoption also helps the control of irrigation machines, according to experts 20 and 25 (factors related to theoretical propositions 1, 2, 2d, 8b, and 8c).
Irrigation control also provides information for the next harvest, as stated by expert 35: "The farmer will use the information from the current or next harvest for the next one. How did the model respond?Did the gain of efficiency meet the expectations?"(factors analyzed in theoretical propositions 2 and 6).
The results of irrigation control are the irrigation status and some other performance measures, such as production efficiency, as well as the measures related to water and energy use [126] (factors addressed in theoretical proposition 1). In the two case studies, the IMS produces performance measures by center pivots, such as production, revenue, and cost. Resource control is also emphasized by experts 2 and 4 as an advantage of adoption (factors related to theoretical propositions 1, 2, 2a, 2f and 8b). As in the industry, the farms can adopt measures to monitor and review performance [127], with a focus on OM, benefits highlighted by experts 10 and 27 (factors concerning theoretical propositions 1, 1a, and 6).
Irrigation control procedures refer to information to perform irrigation operations (factors related to theoretical proposition 6). Regarding the electrical energy use, the operating time of a center pivot must be planned and executed to avoid periods of higher costs of energy [128]. According to expert 8, in collective water use, the farmer receives a volume of water for a specific time, which must be controlled during the execution.
Discussion
In this section, the results and their contributions are discussed to answer the research questions and verify that the research objectives are achieved, beginning with the factors that can affect the explored adoption. Then, the irrigation OM model and the relationships between some factors identified in the case studies are discussed.
Factors That Can Affect the Explored Adoption
This work contributes to the current knowledge on PA adoption with a set of categories and factors that can affect the adoption, which complements previous studies [12][13][14]60] and allows us to overcome the identified gaps. The performance measures related to attitude are grouped into quantitative and qualitative benefits that can be achieved with the adoption. Quantitative performance measurements are integrated with crop water requirement, variable rate water use, production yield, profit, revenue, and production cost. The category "Access to data" is divided into access to agronomic data and access to operational data to differentiate the data sources (agronomic pillars and irrigation operations). The category "Changes" is organized into changes for the farmer and changes for the farm to highlight the challenges and barriers that the farmer and the farm must face and overcome to successfully adopt.
Empirical results add to [69] the following factors: technical training, managerial training, mental model, irrigation management, data-based management, and farm management as a business. Regarding the farmer mental model, the main barrier to the adoption is cultural, which depends mainly on farmer age and experience. According to experts 8, 9, and 20, younger farmers are more likely to be successful in adoption due to their familiarity with innovative technologies, which involve experience and knowledge of computer science and mathematics. For older farmers and those with low educational levels, adoption can represent a cultural shock, which is also linked to their conservatism. The case studies highlighted other significant beliefs, since the mental model of the two farm managers is aimed at minimizing the energy use cost due to the lack of definition of water use cost. The cost of water use is not a priority factor in irrigation OM of the two farms evaluated, even though the two farm managers are young and graduates. At the same time, the farmer mindset is involved in other factors, such the scarcity of water, the need to change the belief that irrigating is different from applying water and to move from experience-based management to data-based management, which the farmer can adopt through sensing technologies and OM models inspired by the industry. As for the changes for the farm, the empirical results emphasize that the OM has not evolved at the same speed as agronomic management in Brazil. OM is undervalued by the farmer due to little knowledge and skills in the OM subject. The previous category "Operations planning and control" is more generically named "Operations Management models inspired by the industry", thanks to the contribution of several experts. This category introduces a new factor: collaborative management models.
The identified categories and factors, shown in Table 2 and 3, like electrical energy supply contract, and planned irrigation water requirement, can influence the perception of the farmer, affecting the intention of adoption. According to [129,130], the greater the benefits perceived from sensing technology adoption (like decrease in use of water and relative cost), the more likely their intention to adopt it. In addition, the less the farmer perceives the obstacles, such as training in irrigation OM, and the more resources he believes are available, such as training, the greater the perceived control and the more likely the intention of adopting.
The identified factors also provide progress in knowledge as they allow us to overcome the gaps in the literature related to the factors concerning irrigation OM and farmer behavior, themes little explored to explain PA adoption. These factors contribute to explain the potential of PA for irrigation operations, considering the applications available, adopting the proposed model for irrigation planning, scheduling, executing, and controlling, such as planning water use and energy use costs, measuring final irrigation time, and water use. This work contributes to previous studies, complementing the factors specific to the studied domain, relevant for a comprehensive understanding of the adoption explored [21].
Examples of these factors are as follows: agronomic data access and operational data access (water access contract, electrical energy supply contract).
Model of Irrigation OM
As PPC is one of the core functions of OM, which aids in planning and utilizing resources [75], and as experts 1 and 6 suggested the adoption of planning and control models of operations such as PPC, these theoretical perspectives inspired the building of the model of irrigation OM, through the foundation of theoretical proposition 6.
The organization of the factors in a model contributes to representing the irrigation OM and the relationships between the factors in a structured way. Considering the gap in the literature relative to the factors concerning the OM, this model contributes to the understanding of PA adoption by theoretical propositions about the relationships between these factors to explain the adoption. These relationships are represented in the model, which is broken down into four functions in Figure 3.
This model complements the irrigation OM model shown in Figures 4 and 5 [69] with the factors presented in Sections 3.1 and 3.2. The context diagram of irrigation OM, shown in Figure 2, highlights the complementing factors. In relation to the controls, the following factors are added in this work: farm characteristics, farmer mental model, access to water (autonomous, collective), contract for access to water, and contract for energy supply. In relation to the inputs, the factor "characteristics of the irrigation system" is integrated, while regarding the mechanisms, the factors "consultant" and "Irrigation Management System" are added. As for the outputs, irrigation status, water and energy use, cost of water, and energy use complement the previous diagrams published in [69]. These factors are significant for the completeness of the proposed model and for the progress of knowledge on PA adoption.
In the model, irrigation planning differs from scheduling, based on inspiration from the planning and control models of operations (factor related to theoretical proposition 6) and from experts 1 and 6. The model contributes to the research of [28], in which irrigation is not the focus.
Results of Case Studies: Relationships between Some Factors in the Model
The case study findings complement the categories and factors in the literature that can affect the adoption of PA, allowing one to explore the relationships between factors. In this section, the relationships between the adoption and the factors "educational level", "training", "access to data" and "resources (people-consultants)" are discussed.
The experts interviewed highlight the importance and role of "training" and "consultants" factors. Jason Mathis training has a crucial role in spreading PA technologies [61] and in the explored adoption, according to theoretical proposition 3a. The farmer can also hire consultant services as an opportunity to support his OM, according to theoretical proposition 8d.
Using the factors "educational level", "training", "access to data", and "resources (people-consultants)" in relation to the adoption (factors addressed in theoretical propositions 2, 3a, 8d, and 9), the empirical results allow us to study the relationships between these factors in the MATOPIBA pilot and "Farm Bahia".
Regarding technical training, the two managers have skills and knowledge of irrigation and PA technologies, as they graduated in Agronomic Engineering and take part in training courses. However, at "Farm Bahia", the planning of irrigation water requirement is carried out with the service of consultants, who define the crop water requirement and the planned irrigation water requirement. In the MATOPIBA pilot, the farm manager plans these two factors. Therefore, the manager of "Farm Bahia" proved less knowledgeable about agronomic data. The data collection to conduct the case study was completed thanks to the support of the consultants, while the MATOPIBA pilot manager had complete knowledge on the agronomic data.
As reported by expert 2 and observed in "Farm Bahia", the outsourcing of irrigation operations can lead to a loss of control by the farmer. Still, expert 3 highlighted that outsourcing is growing significantly in agriculture. Therefore, the farmer can lose control over some operations and the related data [131,132].
The two farm managers have low managerial skills in irrigation OM, since they did not take courses in this area at the universities where they studied. Furthermore, on the two farms, mapping of irrigation OM is not available, and irrigation planning and control models are not adopted. Access to data is hampered by the lack of integration between agronomic databases in the IMS and operational databases, in particular the cost of water use and cost of electrical energy use. Both farm managers are supported by consultants to manage the relationship with the companies that supply the two inputs. Furthermore, the two managers do not differentiate between irrigation planning and scheduling terms and operations.
Concerning the educational market for training future farmers in Brazil, it is important to note that in relation to the National Curriculum Guidelines for the undergraduate course in Agronomic Engineering or Agronomy, a discipline of agricultural OM is not included in the core of essential professional content. This core can be complemented by specific content inserted in the pedagogical project of a course [133]. As for the Agricultural Economics community, a discipline concerning the irrigation OM can be included in the curricula of undergraduate courses.
The experts interviewed also highlight that the irrigation OM is a gap in the training and knowledge of farmers in Brazil, as reported by experts 1, 6, and 11.
Therefore, the results of the case studies allow us to identify two training models: in relation to technical training, "Farm Bahia" adopts an outsourcing model through the support of consultants, while the MATOPIBA pilot manager administers all irrigation operations. As for managerial training, the two farm managers have low training in irrigation OM. These preliminary findings must be analyzed in relation to the need for changes for both the farmer and farm in order to adopt PA, with the objective of exploring the farmer empowerment model and the farm organizational model to support the adoption. However, these empirical results cannot be generalized, due to the scope and the limitations of this work. Future research is proposed to explore the farmer training model and the farm organizational model for the explored adoption.
Limitations and Research Agenda
Based on the results achieved and discussed, the theoretical propositions, the limitations relative to the scope of work, and the data collected in the interviews with the experts and the two farm managers, a future research agenda is formulated (shown in Table 4). For each study, the level influencing the farmer decision-making process on the adoption is indicated: micro-farm, medium-farm ecosystem, macro-watershed or irrigated perimeter.
Future research 1: The irrigation OM model shown in Figure 3 is proposed as a theoretical framework to direct future studies to investigate the relationships between the factors involved in the explored adoption. According to [28], in this model, "Irrigation planning" plays a central role in OM. "Irrigation planning" may be decomposed in lowerlevel child diagrams based on the IDEF0 technique [41], which can be used in combination with simulation models for the support it provides in model documentation and data collection [134]. Therefore, future research is proposed to study the relationships between the factors related to the decomposition of "Irrigation planning" and the adoption of sensing technologies, such as satellites and drones, using simulation techniques. Future research 2: Regarding the unit of analysis and the factor "farm size-industrial farm" (addressed in theoretical proposition 10), this work involved the MATOPIBA pilot and "Farm Bahia". According to [42], two in-depth case studies were conducted. This choice is a limitation of this research in terms of the replication of the results [42,101], especially concerning the relationships between the adoption and the factors: educational level, training, access to data, and resources (people-consultants). Considering the factor "farm size" of the farms involved in the cases, future research is suggested to study whether the results can be replicated and generalized and to investigate the farmer training model and the organizational model of industrial farms for adoption in the state of the State of Bahia and in other Brazilian states. Considering that training and educational level are key factors in empirical findings, this research analyzes how the results will be communicated to farmers and how the extent of changes in farm management will be communicated to scientists.
Future research 3: According to previous studies on PA adoption [135] and as reported by experts 1 and 8, farm characteristics, such as farm size (family farm), affect technology adoption. Future research is suggested to study the interconnection between the adoption and the size of the family farm in the model of irrigation OM.
Future research 4: The case studies and the expert interviews highlight the connections between irrigation and other agricultural operations. Some experts, like expert 15, emphasize that the adoption for irrigation should be seen as complementary and integrated with other agricultural operations.
The literature on irrigation also underlines the integration between agricultural operations. For example, center pivots provide an excellent vehicle to apply some fertilizers to meet the exact crop requirements [116]. The farmer must consider that some operations and decisions are interlinked. For example, irrigation for competing crops is an important agricultural planning issue when water is scarce [79]. Furthermore, each operation has several agronomic conditions that must be satisfied in the field before the operation can be performed efficiently and effectively. The assessment of these conditions is included in the field preparation operation [83].
Therefore, with inspiration from [27] (p.71), this work proposes an integrated model of agricultural Operations Management, shown in the graphical abstract, that expands the field of study of irrigation, involving the factors addressed in theoretical propositions 4c and 6. This integrated management model offers a holistic view of the agricultural OM based on the three agronomic pillars of a farm production system. This model includes the corn development stages [136] and emphasizes the integration between the agronomic pillars, the irrigation operations, and the other agricultural operations, as highlighted by experts 2, 11, 12, 15, and 16. Future research is proposed to study the explored adoption with a focus on extending the model of irrigation OM to other agricultural operations.
Future research 5: By exploring the factors relevant for the adoption of PA in the context of Agriculture 4.0, the TPB construct "Subjective Norm" was considered out of scope. Future research is suggested to include the "Subjective Norm" and to investigate the relationships between the farmer and the actors operating on the farm ecosystem, including extension professionals [34], governments, and technology companies [36]. This proposal is focused on the analysis of the factors out of the scope of this research (related to theoretical propositions 3f, 9, 10, and 11) and their impacts on the adoption.
Future research 6: In the literature [28,137,138] and in the results of expert interviews and case studies, common factors can be found between adoption and decision making in irrigation OM. For example, the relationship between the planned irrigation water requirement and water use can affect decision making in irrigation management. Another example is cited by expert 5: "The farmer can make a more accurate decision regarding irrigation time and water flow of the center pivot, because he can work with sensors that provide precision in information. He can plan the operations so that irrigation is more effective". Since the farm managers in the two case studies do not manage the irrigation planning operations, including the planned cost of water use and the planned cost of electrical energy use, except that at farm planning level, following the explored adoption, the proposed model can be useful to support decision making. Future research is suggested to study the adoption with a focus on decision making in irrigation OM.
Future research 7: Regarding the behavior "diffusion" (i.e., the process by which an innovation is disseminated among several individuals [139]), it was considered out of scope in exploring the relevant factors for the adoption studied, such as extension professionals who can help effectively facilitate the diffusion of PA technologies and bridge the gap in PA information dissemination channels [34]. Future research is needed to investigate the factors that can affect the diffusion of PA in the context of Agriculture 4.0, with a focus on irrigation OM and farmer behavior. According to [36], considering the overemphasis placed on high-tech solutions in the literature, special attention is needed for the inclusion and exclusion effects of the new technologies. The research should consider at what scale to spread innovations to investigate whether this would create more losers than winners.
Future research 8: Regarding the opportunities for the farmer following the explored adoption related to irrigation planning and control, experts 16, 22, 25, and 27 mention the collaborative management models (factor related to theoretical proposition 7). The adoption of these models allows us to overcome some challenges inherent in irrigation OM in the case of shared management of water resources, such as ensuring the availability of water during the harvest. The suggestion of experts 1 and 6 of adopting a management model inspired by the industry (factor addressed in theoretical proposition 6) for irrigation leads to the consideration of other models, such as Sales and Operations Planning (S&OP). S&OP is the long-term planning of sales-related production levels within the framework of a manufacturing planning and control system. The main objective is to balance aggregate supply and aggregate demand, through updates of the annual business plan [140,141]. The inspiration for the S&OP model suggests the idea of exploring the possibility of overcoming the challenges related to poor and ineffective communication between the demand and supply of water in a watershed. This idea involves factors that can be useful to overcome the challenge of balancing water supply (shared water managed by the water resource management agency) and water demand (water users, including farmers). Furthermore, to help effectively facilitate the diffusion of PA technologies and bridge the gap in ineffective communication, extension professionals can play a key role [34]. Future research is proposed to study the application of the irrigation OM model to the management of watersheds and irrigated perimeters, using collaborative management models inspired by the industry.
Conclusions
The research objectives in this work were formulated to answer the research questions and overcome the gaps in the literature about the factors that can affect the adoption of PA in the context of Agriculture 4.0.
The identified categories and factors in this study contribute to broadening the understanding of the determinants of PA adoption in the 4.0 era, adding OM and the farmer mental model to the literature. The findings show the importance of sociological and psychological factors in the research on PA adoption. The central role of farmer behavior and perceptions expands the sensing technology applications in the domain of PA, according to the farmer needs and his mental model, in terms of beliefs about the perceived benefits and disadvantages in irrigation OM.
The categories and factors concerning the irrigation OM also suggest the establishment of operational solutions, thanks to the proposal of adopting the irrigation OM model. The irrigation OM model can be applied as a theoretical framework to direct future research to investigate the relationships between the factors identified in the explored adoption. This model provides applications, enabling one to manage decision making in irrigation OM.
The empirical results emphasize the role of farmer and workforce training, and the related gaps reported by the experts interviewed and the case studies, to success in the adoption. Therefore, this work suggests the inclusion of a discipline related to irrigation OM in courses of Agronomic Engineering and Agricultural Economics for training future farmers for the revolution in progress.
The results of the case studies allow one to study the relationship between the adoption and the factors "educational level", "training", "access to data", and "resources (people-consultants)". These findings highlight the adoption of an outsourcing model related to technical training in "Farm Bahia", with the support of consultants.
In addition to the theoretical contributions, this work provides some practical contributions. The model of irrigation OM can be useful to support the farmer decision making in managing operations and for the development of an IMS integrating agronomic crop management and irrigation OM.
Considering the exploratory nature of this work, a future research agenda is formulated, addressing the factors and components considered out of scope and including an integrated model of agricultural OM based on the three agronomic pillars.
Supplementary Materials:
The following supporting information can be downloaded at [URL] information can be found in Supplementary Material A, Supplementary Material B, Supplementary Material C, and Supplementary Material D. Institutional Review Board Statement: Ethical approval was not required for this study, which does not involve humans or animals.
A
model of irrigation OM is built, based on theoretical propositions, factors identified in theoretical and empirical bases, and factors identified in expert interviews and case studies. This model, developed with the IDEF0 technique, is inspired by the PPC model, according to theoretical proposition 6. This irrigation OM model supports the development of theory on the adoption of PA in the context of Agriculture 4.0. The model of irrigation Operations Management (context diagram), shown in Figure 2, defines the scope of the model and describes the modeling of the top-level function. The context diagram is broken down into four functions, creating child diagrams and the model of irrigation OM (IDEF0 diagram), as shown in Figure 3: irrigation planning, irrigation scheduling, irrigation execution, and irrigation control. Each of the sub-functions may be decomposed in lower-level child diagrams. The description of the IDEF0 diagram shows the identified factors and the pertinent theoretical propositions.
in theoretical and empirical bases, and factors identified in expert interviews and case studies. This model, developed with the IDEF0 technique, is inspired by the PPC model, according to theoretical proposition 6. This irrigation OM model supports the development of theory on the adoption of PA in the context of Agriculture 4.0. The model of irrigation Operations Management (context diagram), shown in Figure 2, defines the scope of the model and describes the modeling of the top-level function.
Figure 2 .
Figure 2. Model of irrigation OM (context diagram). The context diagram is broken down into four functions, creating child diagrams and the model of irrigation OM (IDEF0 diagram), as shown in Figure 3: irrigation planning, irrigation scheduling, irrigation execution, and irrigation control. Each of the subfunctions may be decomposed in lower-level child diagrams. The description of the IDEF0 diagram shows the identified factors and the pertinent theoretical propositions.
Figure 3 .
Figure 3. Model of irrigation Operations Management (IDEF0 diagram). Irrigation time can be planned in relation to nightly, daytime, and peak operating times (factors related to theoretical propositions 2e and 2g), according to the two farm managers and experts 10, 14, and 25. Water use, water use cost, energy use, and energy use cost can be planned based on different operating times. Energy use and energy use cost can be planned depending on the irrigation equipment like pumps and motors, as reported by the two farm managers (factors related to theoretical propositions 2e, 2g, 2h, 8a, and 8b). The pumps and motors can be powered by diesel oil, renewables, or electrical energy, according to[116] and expert 27. Irrigation planning can be conducted at the level of the farm and field.
Author Contributions:
Conceptualization: S. M. and E. A.d. M.; methodology: S. M.; validation: S. M. and E. A.d. M.; formal analysis: S. M.; investigation: S. M. and B. T.d. F.; resources: S. M. and E. A.d. M.; data curation: S. M., E. A.d. M. and B. T.d. F.; writing-original draft preparation: S. M.; writing-review and editing: all authors; supervision: E. A.d. M. and R. M. P.; project administration: E. A.d. M. and R. F. M.; funding acquisition: R. F. M. All authors have read and agreed to the published version of the manuscript. Funding: This research was jointly funded by the European Commission in Europe and by MCTIC/RNP in Brazil, under the call EUB-02-2017 IoT Pilots.
Table 1 .
Example of coding process.
Table 2 .
Results of expert interviews: factors and categories that can affect the adoption. Crop water requirement, water use, energy use, cost of water use, cost of energy use, variable rate water use, production yield, profit, revenue, production cost.
Resources (inputs, hardware, people), inputs (water sources, water, energy), hardware (agricultural machinery, agricultural equipment, weather stations, soil probes, drones, satellites, sensors, Irrigation Management System, people (farmers, farm managers, workers, consultants). ResourcesAntecedent FactorsAge, educational level, income, experience in agriculture, familiarity with technologies, family of farmers, conservatism, managerial training, absorptive capacity, risk propensity, innovation capacity. Jason Mathis characteristicsFarm size-family farm/industrial farm, farm location, crop type, cooperativism, production volume, product profitability. Farm characteristicsTechnology type, equipment type, price, complexity. Technology characteristics and 16. Expert 1 6 states that: "The farmer must be trained and prepared in terms of knowledge and skills to use these technologies. If he doesn't understand it well, he most likely won't adopt correctly". Training includes technical training and management training, as reported by expert 13. Technical training is necessary for irrigation, to understand what irrigation is, what irrigated agriculture is, and that the agricultural field has variability, according to expert 17.
Table 3 .
Results of case studies: factors that can affect the adoption.
Table 4 .
Future research agenda.
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Domain: Agricultural and Food Sciences
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Study of the utilization of Azolla microphylla as alternative feed by Tilapia farmers in Panjalu Ciamis, West Java Province, Indonesia
Feed is the most significant component of tilapia culture production costs. Various attempts have been made to reduce this cost with alternative feed, including A. microphylla. The research aims to encourage changes in the level of knowledge, attitudes, and skills of fish cultivators about utilization and cultivation of Azolla through the demonstration ponds (Dempond) and increase the production of tilapia by increasing the stocking density and the use of A. microphylla feed. The research was conducted from March 2nd to May 15th, 2021, in Panjalu Sub District, Ciamis Regency, West Java Province. Data were collected by purposive sampling, with observation and interview methods. The data consists of primary and secondary data. The data analysis was carried out in a descriptive qualitative manner. The results showed a change in fish cultivators' knowledge about the benefits and cultivation of A. microphylla by an average of 20.28%, a change in target attitudes by 5.1%, and skill improvement by 28%. There was an increase in tilapia yield from the initial total weight of 121.25 kg to 226.1 kg using 24 kg of A. microphylla as a feed additive for 60 days of culture.
Introduction
The characteristics of the Panjalu sub-district are in the form of highlands and dominant mountains. Some people do aquaculture business with ponds in the yard of their houses, but still, on a small scale, cultivation is done long enough with varied commodities such as carp and tilapia. Tilapia is one type of fish consumption that has considerable potential to be developed because it has a high economic value and has a strong commodity value in freshwater fish farming business activities ( Figure 1). Aquaculture is one of the business types which has much demand by the community. Fish is a source of animal protein with a protein content between 15.32-18.80%. Animal protein obtained from tilapia fish is very beneficial. The demand for tilapia market consumption in the Ciamis is as much as 10 tons/year. Tilapia production only fulfills 10% of the existing market demand. So, 90% of the demand is imported from the outside region. The Panjalu sub-district has a 50,063 ha area. A pond area of 98,795 ha supports the potential fisheries. Availability of abundant water throughout the year flows from the Rompe river. A technology used by the cultivators is still traditional. The average production of tilapia cultivation is as much as 1. 6 tons/year. The demand for tilapia's fish consumption in Ciamis Regency is as much as 10 tons/year. The lack of feed availability causes the low production of tilapia So, it impacts the number of cost production incurred [5] A. microphylla is a nail plant that floats on the water surface ( Figure 2). This plant has tiny leaves overlapping, the surface of the leaves is soft, it is bright green, and it has many spores. The type of Azolla plant, which the most commonly encountered and utilized are Azolla pinnata and Azolla microphylla [6]. The nutritive value of Azolla contains high levels of protein between 24-30% [6] Human resources at Panjalu sub-district are fisheries cultivator, which is ± 280 fisheries households with diverse business segments and commodities, the business being carried out is still traditional. The fisheries cultivator in Panjalu sub-district still does not know about alternative feeds that can maintenance the tilapia and make the fish cultivations better. The research aims to encourage changes in the level of knowledge, attitudes, and skills of fish cultivators about the utilization and cultivation of Azolla through the demonstration ponds (Dempond).
Materials and methods
Hunjungwangi Group researched Panjalu Sub-district, Ciamis Regency, West Java Province. The research was conducted for three months, from March 2 nd to May 15 th , 2021. Determination of samples is using a purposive sampling method towards the group of tilapias cultivators who are still active-the target of respondents counseling is14 fisheries households of the Hunjungwangi Group'smembers. There are ten fish cultivators involved in all activities. This study observed the utilization of Azolla as an alternative feed for tilapia cultivation by using demonstration pond (Dempond) methods. Dempond activities were carried out in the different ponds. Pond (A) was given treatment according to the Indonesian National Standard of Tilapia Cultivation and given additional feed Azolla. In comparison, pond (B) was a pond of tilapia cultivators in usual that given treatment according to commons applied by the community in Panjalu sub-district Ciamis. The treatment of ponds was compared with the application of Azolla's feed, pond (A) given Azolla's feed as much as 1.2 kilograms (kg) once three days, and commercial feed (Hi-Provite 781-2 with a protein content of 27-32%) as much as 3% every day. At the same time, pond (B) was not fed by Azolla and given commercial Feed (Hi-Pro vite781-2 with a protein content of 27-32% every day) [20]. Water quality measurements were taken once a week to find out the quality of water in Dempond.
Demonstration activities on how to cultivate Azolla were carried out using a pond's soil with a size of 3 m × 3 m × 0.5 m. The pond was cleaned and dried, put in chicken fertilizer with a dose of 350 grams/m 2 and, filled with water until around 20 cm. The preparation of pond media took three days until the fertilizer could be mixed well and did not release the odors. Then the seedlings were stocked with a solid spread of 100 grams/m 2 .
Evaluation of tilapia cultivation Dempond activities using Azolla feed includes aspects of knowledge, attitude, and skills with instruments in the form of questionnaires given at the beginning (pre-test) and the end (post-test) that have been validated. The data collected consists of primary and secondary data. Primary data is collected by in-depth interviews with respondents counseling, extension, and the village leader. Secondary data is obtained from the extension activity report, and data report in the Sub-District.
Evaluation activities are conducted twice, at the beginning which before the activity is carried out, to look at the flow of information that is already in the target community, and the second evaluation is carried out after the activity takes place to see the changes after the flow of information is carried out. These aspects are evaluated in this activity, such as knowledge, attitude, and skills aspects.
Evaluation activities of knowledge aspect and attitudes aspect were using the following formula below. Evaluation activities of skills aspects were to determine the business situation from the economic side using business analysis. Business analysis is determined by Break-Even Point (BEP), Revenue/cost ratio.
Break-even point (BEP) is a term in accounting that refers to the situation where a company's revenues and expenses were equal within a specific accounting period. It means that there were no net profits or net losses for the company -it "broke even." break-even point in units compute by the following formula below (4) break-even point in dollars computed by the following formula below:
Break-even Point (Sales in dollars) = Fixed Costs / (Sales Price per Unit x BEP in Units)
Return Cash Ratio (R/C) is the total revenue ratio to the total amount of costs incurred during a period. A business is considered profitable if the R/C ratio > 1. R/C = TR/TC= With the results of the R/C calculation obtained by 1.6, this hydroponic business can provide benefits. Every IDR 1.00 capital will return IDR 1.60 Individual characteristics are traits that a person displays that relate to all aspects of his life in his world or environment [25]. The characteristics of a person who is used as a target can be seen from age aspects, formal education, and business experience.
The observation results on the characteristics of fish cultivators in Panjalu District of Ciamis Regency can be seen in Table 1 Dempond activities in different ponds, i.e., Pond (A) is a pond that is given treatment according to literature. At the same time, pond (B) was a pond of tilapia cultivators in usual that given treatment according to commons applied by the community in Panjalu subdistrict Ciamis. The results of treatment pond (A) and untreated pond (B) Dempond activities can be seen in detail in Table 2. Comparison of the results of pilot pond trials in Table. 2. shows the results of Dempond activities that have been implemented. Dempond activities are carried out in the different ponds. Pond (A) is given treatment are following with the reference SNI Cultivation Tilapia fish and given Additional Feed Azolla. While pond (B) is a pond of farmers in general, the treatment is according to what is applied by the community in Panjalu sub-district Ciamis.
Business analysis needs to be done on business activities to find out the results in the form of financial results in the form of profits, so the provided innovation can benefit and increase revenue for the target. The results of the Dempond business analysis calculation can be seen in detail in Table 3. Table 3.
Results of Dempond business analysis calculations
Evaluation is carried out to find out the changes that occurred and were experienced by the extension target, while the aspect evaluated in this activity is the knowledge aspect. The results of the evaluation of knowledge aspect respondent after carrying out a demonstration on the theme of alternative feed used Azolla to enlarge tilapia. Types of Azollae cultivated type A. microphylla. Fertilization is carried out over once ten days. A quarter dose is given at the beginning of fertilization, intended to maximize the growth of Azolla. Azolla that has been cultured for the next week can be harvested. Harvesting is done every three days with a harvest of 1.2 kg to be given additional feed. Harvesting is only done on one side of the ponds, giving the Azolla a chance to keep growing. Azolla is given for 1200 fish ( Table 2). The use of Azolla can be carried out for two months, with a total consumption of Azolla is 24 kg.
Discussions
Characteristics of fish farmer Tilapia cultivators located in the Panjalu region are seen in several characteristics, including age, level of education, and business experience. Characteristics are characteristics or characteristics of the inherent natural self of a person that includes age, level of education, land area, and experience you have to try to farm [22]. Table 1. Age less than 34 years and 34 to 52 years of age is balanced as a productive age. This result follows the Indonesian Central Bureau of Statistics states that the productive age is between 15-64 years.
One of the factors that influence the productivity of farmers is the age factor [2]. The age that is still in productive period usually has a higher level of work productivity in managing a business, have physical abilities, and good mindset compared to the old labor so that the physical has become weak and limited. Productive farmers want to develop fisheries, and fishery activities can be followed and then applied. The target belongs to this category as many as seven people. It is necessary to be conscious and plan efforts in realizing the learning situation. The learning process encourages learners to explore their potential so that they have various strengths in the field of religion, spirituality, self-control, personality, intelligence, noble morals, and the skills required of themselves, society, nation, and country [10]. The characteristics of the target based on the level of education that dominates are the level of education elementary, junior high, high school or fall into the category of "MEDIUM." Every citizen is obliged to study for six years [10]. Target characteristics based on length of effort, dominant at one to 11 years, fall into the category of "MEDIUM." [6] business experience with an average length of 11 years, then showed good cultivation ability in running his business.
Biotic and abiotic factors during maintenance significantly affect the life rate of tilapia, including water quality, feed, competition/competitors, human handling, and density of dispersal. As well as biotic factors, abiotic factors that include physical and chemical properties of the water [15] stated that water quality management is the main component that must be considered in improving production results. Therefore, monitoring water quality periodically during Dempond activities is carried out [15]. The following are the results of water quality observations that have been made in treatment pond (A) and nontreatment pond (B) during ± 60 days of maintenance.
A demonstration of how to cultivate Azolla as an additional feed is done. That activity aims to show farmers that Azolla plants can be given to fish and can reduce production costs. Azolla feed is given only as a companion protein to suppress pellet feed, not as the main protein in maintenance. The skills of cultivators are improved.
Fish growth in the treatment pond (A) with intensive commercial feeding coupled with Azolla feed, faster growth, and higher survival than fish that are only given commercial feed. Following [8], feed is one of the most critical factors to the growth and survival of cultivated fish. So, at the end of the maintenance period, fish in the treatment pond (A) has reached the target production weight of up to almost 200 g/tail, while the pond without new treatment reaches a weight range of 130 g/tail.
The business aspect of the results of business analysis in the treatment pond (A) and without treatment Pond (B) shows the marginal acceptance reached IDR 6.828,000. This value is influenced by the result of production, which differs between the treatment and untreated pond. The profit in 1 cycle reaches IDR 3.007,649, while the un-treated pond also has a profit, but it is deficient when harvested with a maintenance time limit simultaneously with the treatment pond, which is 60 days.
Based on the initial and final evaluation results and evaluation from aspects of knowledge on the activities of Dempond cultivation of tilapia, there has been a change in the average knowledge of 20.28%. This result happened because at the time of implementation of the active target and focused following each stage. There was a high sense of curiosity about the tilapia enlargement Dempond.
The influence of knowledge has increased in general related to education. Evaluation results on the aspect of Dempond attitude of tilapia cultivation have changed the target's attitude with a score of 428 to 450 targets to change the score by 5.1%. The attitude of the target changed after the tilapia cultivation Dempond. The formation of attitudes is still related to experience because the process will increase the knowledge that is already possessed and include the experience of using new technologies [13].
An evaluation of the skill aspect was conducted to determine the skill level of respondents in the tilapia cultivation Dempond activity. Assessment indicators on the skill aspects of tilapia cultivation Dempond activities include accuracy, speed, and accuracy regarding tilapia cultivation techniques and how to apply feed Azolla.
The evaluation results of skill aspects showed an increase in initially professional skills by 7% to 35%. In contrast, the unskilled category decreased from 65% to 3%. According to [13], the factors that affect skills are experience and age. With the majority of productive ages, age-related abilities are a factor in carrying out an activity and can also be a benchmark for knowing the activities of a person doing work. In addition to the evaluation of activities, both in the aspects of knowledge, attitudes, and skills, are also carried out impact evaluation, namely evaluation of innovation adoption by directly observing the level of acceptance and application of targets to the material/innovation that has been delivered in the process of extension activities.
Conclusion
The evaluation results conducted on fish cultivators as many as ten people on Dempond utilization of Azolla showed changes in knowledge improvement by 20.28%, attitude improvement by 5.1%, and skills improvement by 29.7%. Production of tilapia fed commercial feed and added by Azolla was higher (226.1 kg) than tilapia fed only by commercial feed (121.25 kg) for 60 days rearing period.
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Domain: Agricultural and Food Sciences
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Effects of Nesting Material Provision and High-Dose Vitamin C Supplementation during the Peripartum Period on Prepartum Nest-Building Behavior, Farrowing Process, Oxidative Stress Status, Cortisol Levels, and Preovulatory Follicle Development in Hyperprolific Sows
Hyperprolific sows often experience increased oxidative stress during late gestation and lactation periods, which can adversely affect the farrowing process and overall lactation performance. This study examines the influence of providing a coconut coir mat (CCM; 1 × 1 m) as nesting material, supplementing high-dose vit-C (HVC; 20% vit-C, 10 g/kg feed) as an antioxidant, or both on maternal behavior, the farrowing process, oxidative status, cortisol levels, and preovulatory follicle developments in sows with large litters. In total, 35 sows (Landrace × Yorkshire; litter size 15.43 ± 0.27) were allocated to the following four treatment groups: control (n = 9, basal diet), vit-C (n = 8, basal diet + HVC), mat (n = 10, basal diet + CCM), and mat + vit-C (n = 8, basal diet + HVC + CCM). A post-hoc analysis showed that compared with sows that were not provided CCM, mat and mat + vit-C groups demonstrated increased durations of nest-building behavior during the period from 24 h to 12 h before parturition (p < 0.05 for both), reduced farrowing durations, and decreased intervals from birth to first udder contact (p < 0.01 for both). The mat group exhibited lower advanced oxidation protein product (AOPP) levels during late gestation and lactation periods than the control group (p < 0.05). Sows with HVC supplementation showed longer farrowing durations than those without HVC supplementation (p < 0.0001). The vit-C group had higher salivary cortisol levels on day 1 after farrowing than the other treatment groups (p < 0.05). Furthermore, the follicle diameters on day 3 after weaning in the vit-C group tended to be smaller than those in the control group (p = 0.077). HVC supplementation prolonged farrowing and increased the physiological stress on postpartum, and no advantageous effects on maternal behavior and developmental progression of preovulatory follicles were observed. Hence, alternative solutions beyond nutritional approaches are required to address increased oxidative stress in hyperprolific sows and secure their welfare and reproductive performance. The present results substantiated the positive impact of providing CCM as nesting material for sows with large litters on nest-building behavior and the farrowing process, which could mitigate the deleterious consequences induced by peripartum physiological and oxidative stress.
Introduction
Over the last three decades, the pig industry has experienced a drastic rise in the size of sow litters [1]. However, this increase in litter size has been accompanied by prolonged farrowing, resulting in increased stillbirth rates and diminished piglet vitality [2]. The enlarged litter size might be associated with physiological and oxidative stress due to the increased energy requirements for fetal growth and milk production during gestation and lactation [3]. This, in turn, can disrupt maternal hormone secretion and elevate the risk of reproductive disorders, such as mummification, preterm labor, miscarriage, and inhibition of preovulatory follicular development [3,4].
There is a growing interest in addressing the oxidative stress of mammals via supplementation of antioxidants, such as plant extracts, vitamin E, vitamin C, and selenium [4][5][6][7][8]. Despite variations in the impact of antioxidants depending on differences in animal species and physiological status [9], vitamin C consistently acts as a one-or two-electron donor for free radicals, thereby minimizing the variability of its effects [10,11]. Uchio et al. [12] demonstrated that the administration of high-dose vitamin C (HVC, 200 mg/kg daily for two months) reduced oxidative stress by elevating intracellular levels of other antioxidants, including superoxide dismutase and glutathione, in the splenocytes of dexamethasonetreated mice. Hyperprolific sows experience elevated oxidative stress with increasing litter sizes; hence, the supplementation of HVC in sows with large litters should be considered to counteract it [8].
An alternative strategy for modulating oxidative stress in sows involves providing environmental enrichment, such as adjusting the thermal environment and ensuring the availability of nesting materials and sufficient space [13,14]. In the modern pig industry, peripartum sows often experience stress due to confinement in farrowing crates and absence of nesting materials [15] that impedes their maternal instinct for nest-building behavior (NB). Captive sows with large litters may experience increased oxidative and physiological stress [4,13,14], which hinders the maternal behavior of peripartum sows due to the accumulation of reactive oxygen species (ROS) [16]. Hence, providing appropriate nesting materials may be beneficial in addressing the issue of inhibited instinctive behavior in sows due to increased oxidative stress, which consequently affects their farrowing and reproductive performance [17,18].
A previous study conducted by our research group demonstrated that sows with large litters (over 14 piglets) exhibit higher oxidative stress than those with small litters, which is associated with reduced NB and reproductive performance [4]. Therefore, our current study aims to investigate the potential mitigation of oxidative stress in sows with large litters by supplementing HVC as an antioxidant. Additionally, the impact of providing CCM as an inducer for prepartum NB is examined by evaluating its effect on the management of oxidative stress and enhancement of reproductive performance in sows with large litters.
Material and Methods
This study was conducted at a commercial farm with an 8000-head pig unit in southern South Korea between June and August 2022. All the experimental animal procedures were reviewed and approved by the Chonnam National University Institutional Animal Care and Use Committee (reference number: CNU IACUC-YB-2021-167).
Animals and Management
A total of 35 sows (Landrace × Yorkshire; parity, 1.91 ± 0.28) from three batches at expected farrowing intervals of 7 days were used in this study. The litter size of the experimental sows was more than 13 because the number of their functional teats was between 13 and 14. During pregnancy, the sows were housed in groups of 25 to 29 per pen (5.75 × 10.5 m), and 1 kg of a standard gestational diet (3.3 Mcal of digestible energy per kg, including 12.8% crude protein, 3.7% crude fat, 4.1% crude fiber, 4.6% crude ash, 0.8% calcium, and 0.4% phosphorus) was provided twice a day at 08:30 and 16:00 with ad libitum access to water. Approximately 4-5 days before the expected farrowing date, the sows were moved to farrowing pens (2.3 × 2.4 m) with fully concrete slatted floors. The sows were maintained in loose housing conditions during the entire parturition and lactation period. Housing conditions and pen features were as in our previous study [4]. The standard lactation diet (1 kg; 3.5 Mcal of digestible energy per kg, including 14.7% crude protein, 3.2% crude fat, 3.0% crude fiber, 5.2% crude ash, 0.9% calcium, and 0.5% phosphorus) was provided automatically twice daily at 09:30 and 15:00 until the farrowing date. After farrowing, the feed was gradually increased by 1 kg per day until the total feed amount reached 7 kg. Within 48 h postpartum, piglets were cross-fostered to standardize the number of piglets on each experimental sow. After approximately 4 weeks of lactation, the sows were transported to a breeding house and housed in individual stalls (0.65 × 2.1 m).
Experimental Design
All the sows were randomly assigned to one of the following four experimental groups: provided on the slatted floor). The CCM (ECOLJS Co., Cheongju, Republic of Korea) was placed at the center of the farrowing pen without affixing (Figure 1) so that the sows could freely manipulate it 4 days before the expected date of parturition. After parturition, 2/3 of the CCM was removed to prevent loosening of the mat and debris from falling through the slatted floor. The rest of the CCM was placed under a heat lamp to guide the piglets to a safe area. The diet was supplemented with HVC (DaOne Chemical Co., Siheung, Republic of Korea) when the feed was provided using the automatic feeder at 09:30 and 15:00, starting from 4 days before the expected farrowing date until 2 weeks after parturition.
were maintained in loose housing conditions during the entire parturition and lactation period. Housing conditions and pen features were as in our previous study [4]. The standard lactation diet (1 kg; 3.5 Mcal of digestible energy per kg, including 14.7% crude protein, 3.2% crude fat, 3.0% crude fiber, 5.2% crude ash, 0.9% calcium, and 0.5% phosphorus) was provided automatically twice daily at 09:30 and 15:00 until the farrowing date. After farrowing, the feed was gradually increased by 1 kg per day until the total feed amount reached 7 kg. Within 48 h postpartum, piglets were cross-fostered to standardize the number of piglets on each experimental sow. After approximately 4 weeks of lactation, the sows were transported to a breeding house and housed in individual stalls (0.65 × 2.1 m).
Experimental Design
All the sows were randomly assigned to one of the following four experimental groups ) provided on the slatted floor). The CCM (ECOLJS Co., Cheongju, Republic of Korea) was placed at the center of the farrowing pen without affixing (Figure 1) so that the sows could freely manipulate it 4 days before the expected date of parturition. After parturition, 2/3 of the CCM was removed to prevent loosening of the mat and debris from falling through the slatted floor. The rest of the CCM was placed under a heat lamp to guide the piglets to a safe area. The diet was supplemented with HVC (DaOne Chemical Co., Siheung, Republic of Korea) when the feed was provided using the automatic feeder at 09:30 and 15:00, starting from 4 days before the expected farrowing date until 2 weeks after parturition.
Saliva Collection
Saliva samples were collected using a synthetic swab (Salivette ® Cortisol; Sarstedt, Germany) at the following times: 4 days before the farrowing date and 1, 7, and 28 days after farrowing. Saliva samples were collected 1 h after the morning feeding. The swab was fixed with forceps and placed around the sow's molars for 1 min to induce chewing. All the saliva samples were stored at −50 °C in a deep freezer on the farm for 1 month, then transported to the laboratory in a portable freezer at −20 °C, and stored at −80 °C in a deep freezer until analysis.
Data Collection 2.3.1. Saliva Collection and Assays Saliva Collection
Saliva samples were collected using a synthetic swab (Salivette ® Cortisol; Sarstedt, Germany) at the following times: 4 days before the farrowing date and 1, 7, and 28 days after farrowing. Saliva samples were collected 1 h after the morning feeding. The swab was fixed with forceps and placed around the sow's molars for 1 min to induce chewing. All the saliva samples were stored at −50 • C in a deep freezer on the farm for 1 month, then transported to the laboratory in a portable freezer at −20 • C, and stored at −80 • C in a deep freezer until analysis.
Assay for Oxidative Stress Parameters
For the analysis of levels of advanced oxidation protein products (AOPP), the saliva samples were centrifuged at 1000× g for 10 min, and the supernatants were analyzed using an enzyme-linked immunosorbent assay (ELISA) kit (AOPP ELISA kit; MBS028634, San Diego, CA, USA) according to the manufacturer's instructions. For the analysis of hydrogen peroxide (H 2 O 2 ), Trolox equivalent antioxidant capacity (TEAC), and tumor necrosis factor-alpha (TNF-α) levels, the saliva samples were centrifuged at 10,000× g for 10 min, and the supernatants were analyzed using an ELISA kit (OxiSelect™ Hydrogen Peroxide Assay [MBS169261, San Diego, CA, USA], OxiSelect™ TEAC Assay Kit [MBS169313, San Diego, CA, USA], and Porcine TNF-α DuoSet ELISA [DY690B, Minneapolis, MN, USA], respectively) according to the manufacturer's instructions. The sensitivity values of the AOPP, H 2 O 2 , and TEAC assays were 1.0 µmol/L, 0.8 µM g/mol, and 250.29 g/mol, respectively. TNF-α had a detection limit of 31.3 pg/mL.
Cortisol Assay
For the analysis of cortisol, the saliva samples were centrifuged at 1000× g for 10 min, and the supernatants were analyzed using an ELISA kit (Salimetrics ® Cortisol Enzyme Immunoassay Kit; 1-3002, Carlsbad, CA, USA) according to the manufacturer's instructions. The sensitivity of the cortisol assay was 0.018 µg/dL.
Colostrum Collection and Assays
More than 25 mL of the colostrum samples were collected within 3 h of parturition in a 50 mL conical tube (SPL, Pocheon, Republic of Korea). The samples were stored at −50 • C in a deep freezer on the farm for 1 month, then transported in a portable freezer at −20 • C, and stored at -80 • C in a deep freezer until analysis. For the analysis of oxytocin and prolactin concentrations, the colostrum samples were centrifuged at 1000× g for 20 min, and the skimmed milks were analyzed using an ELISA kit (OT ELISA Kit [E-EL-0029, Houston, TX, USA] and Pig Prolactin ELISA Kit [MBS2087044, San Diego, CA, USA], respectively) according to the manufacturer's instructions. The sensitivity values of the oxytocin and prolactin assays were 9.38 pg/mL and 6.1 pg/mL, respectively. For the analysis of immunoglobulin (Ig) A, IgG, and IgM concentrations, the colostrum samples were centrifuged at 1000× g for 20 min, and the skimmed milks were analyzed using an ELISA Kit (Pig IgA ELISA Kit [E101-102, Montgomery, TX, USA], Pig IgG ELISA Kit [E101-104, Montgomery, TX, USA], and Pig IgM ELISA Kit [E101-117, Montgomery, TX, USA], respectively) with a detection range of 1.37-1000 ng/mL.
Behavioral Observation
Video recordings of the sows were taken for 48 h (24 h each, before and after parturition) to assess prepartum NB and the farrowing process of sows using internet protocol (IP) cameras (HN0-E60; Hanwha Techwin, Changwon, Republic of Korea) with 1920 × 1080-pixel resolution at 30 FPS. One camera per two pens was installed on a wooden bar 1.5 m above the sows' heads. A trained researcher used a media player (PotPlayer, Kakao Corp., Jeju, Republic of Korea) to observe the NB and farrowing processes of all the sows.
The start of NB was defined as active pawing, rooting, and arranging for longer than 5 s. The end of NB was defined as no pawing, rooting, and arranging for longer than 30 s. The progression of NB was tracked at 6 h intervals as the sows approached parturition. Pawing was defined as scratching the floor with the front legs, rooting as nudging or pushing the floor or crate with the snout, and arranging as shifting or sorting nesting materials using the snout or mouth.
The duration of farrowing was considered as the time period between the births of the first and last piglet, including stillbirths. The birth interval, which is the time between the birth of consecutive piglets, including stillbirths, was also evaluated. Additionally, the birth-to-udder touch interval in piglets was calculated from when a piglet was born until its first contact with the sow's udder.
Measurement of Follicle Size
The ovarian status of the sows from the third batch was examined using transrectal ultrasound examinations (Easi-Scan: Go, 4.5 MHz-8.5 MHz, curved probe; IMV Imaging, Bellshill, Scotland, UK). The examinations were conducted daily at 13:00, starting from 3 days before ovulation until ovulation. Both ovaries were scanned separately during examination, and the clips were exported in MPEG-4 format for analysis. The diameters (mm) of the five largest follicles in both ovaries were measured, and the average was calculated to define follicle size. At 09:00 and 16:00 every day from 3 days after weaning, the boars were released into the aisle in front of the sow's feeder to induce contact with the sow, and standing estrus was examined. All the sows were artificially inseminated after estrus was first detected, and if they continued to exhibit standing reflex, insemination was repeated when estrus was subsequently detected.
Statistical Analysis
All the data were statistically analyzed using SAS, version 9.4 (SAS Institute Inc., Cary, NC, USA, 2012). Each sow was considered as one experimental unit. Normality was tested via the UNIVARIATE procedure using the Shapiro-Wilk test. The fixed effect was the treatment, and the random effect was the farrowing batch, which had 1week intervals. Data were presented as means and standard errors of the mean (SEM).
A PROC GLIMMIX model with Lognormal distribution was fitted to assess salivary cortisol, oxidative stress parameters (H 2 O 2 , TEAC, AOPP, and TNF-α), and colostral parameters (oxytocin, prolactin, IgG, IgM, and IgA). A repeated measure test was used for the data analysis on oxidative stress parameters during prepartum and lactation periods (D−4, D1, D7, and D28). The PROC MIXED model was used to determine NB, litter weight, and follicle size. The PROC GLIMMIX model with Poisson distribution was conducted to analyze the farrowing process, litter characteristics, and periods of weaning-to-estrus and estrus-to-ovulation. Spearman's rank correlation coefficient (r) was used to analyze correlation data.
Oxidative Stress Parameters
The salivary oxidative stress parameters of sows from 4 days before farrowing to 28 days after farrowing are presented in Table 1. On day 4 before farrowing, the AOPP levels of the control group were higher than those of the vit-C or mat group (p < 0.05, Table 1). However, there was no difference when compared to the mat + vit-C group (Table 1). On day 7 after farrowing, the AOPP levels tended to be lower in sows provided with CCM than those in sows without CCM (p = 0.086, Table 1). Additionally, the repeated measures analysis revealed that the control group exhibited higher levels of AOPP than the mat group from 4 days before farrowing to 28 days after farrowing (p < 0.05, Table 1).
A post-hoc analysis showed that HVC supplementation increased the sows' TEAC levels on day 1 after farrowing (p < 0.05, Table 1). However, there were no significant differences in the TEAC levels among treatment groups in the other sampling periods and the period between −4 and 28 days.
CCM provision tended to lower the H 2 O 2 levels on day 28 after farrowing (p = 0.074, Table 1) but did not alter them on the other days. Additionally, no significant differences were found in the TNF-α levels among the treatment groups during all the sampling periods.
Salivary Cortisol Levels
The vit-C group showed higher levels of salivary cortisol than other treatment groups on day 1 after farrowing, (p < 0.05, Figure 2). Conversely, the post-hoc analysis showed that the sows provided with CCM tended to have lower levels of salivary cortisol than those without CCM on day 7 after farrowing (p = 0.060). During the lactation period (D1, D7, and D28), the salivary cortisol levels showed a correlation with the TNF-α and TEAC levels (r = 0.39, r = 0.38, respectively; p < 0.001) and tended to have a positive correlation with the H 2 O 2 and AOPP levels (r = 0.17, r = 0.20, respectively; p < 0.10). Additionally, the salivary cortisol levels on D1 were positively correlated with farrowing duration and birth intervals (r = 0.35, r = 0.34, respectively; p < 0.05).
Colostrum Oxytocin, Prolactin, and Ig Levels
The levels of oxytocin and prolactin in the colostrum were numerically the highest in the mat group, but no significant differences were observed among the treatment groups. The sows with HVC supplementation tended to have lower IgM levels than those without HVC supplementation (p = 0.077, Table 2). Post-hoc contrast analysis depending on CCM provision or HVC supplementation. 3,4All colostrum samples were collected within 3 h after initiation of parturition. CCM, coconut coir mat; HVC, high-dose vitamin C; SEM, standard error of the mean; Ig, immunoglobulin.
Colostrum Oxytocin, Prolactin, and Ig Levels
The levels of oxytocin and prolactin in the colostrum were numerically the highest in the mat group, but no significant differences were observed among the treatment groups. The sows with HVC supplementation tended to have lower IgM levels than those without HVC supplementation (p = 0.077, Table 2). Post-hoc contrast analysis depending on CCM provision or HVC supplementation. 3,4All colostrum samples were collected within 3 h after initiation of parturition. CCM, coconut coir mat; HVC, high-dose vitamin C; SEM, standard error of the mean; Ig, immunoglobulin.
Farrowing Process and Litter Characteristics
The post-hoc analysis showed that the provision of CCM reduced the duration of farrowing and interval from birth to first udder touch by the piglet (p < 0.01 for both, Table 3). Conversely, the sows with HVC supplementation exhibited increased farrowing duration (p < 0.01, Table 3) and tended to have longer birth intervals than those without HVC supplementation (p = 0.078, Table 3). The total-and live-born piglet numbers did not differ among the treatment groups. However, the stillbirth frequency was significantly higher in sows provided with CCM than in those without CCM (p < 0.01, Table 3).a,b,c Significantly different variables within the row (p < 0.05). 1,2Post-hoc contrast analysis depending on CCM provision or HVC supplementation.
Follicular Development
The mean diameter of the five largest follicles on both ovaries tended to be smaller in the vit-C group than that of those in the control group 3 days after weaning (p = 0.077, Figure 4a). Conversely, the weaning-to-estrus and weaning-to-ovulation intervals did not differ among the treatment groups (Figure 4b).
Farrowing Process and Litter Characteristics
The post-hoc analysis showed that the provision of CCM reduced the duration of farrowing and interval from birth to first udder touch by the piglet (p < 0.01 for both, Table 3). Conversely, the sows with HVC supplementation exhibited increased farrowing duration (p < 0.01, Table 3) and tended to have longer birth intervals than those without HVC supplementation (p = 0.078, Table 3). The total-and live-born piglet numbers did not differ among the treatment groups. However, the stillbirth frequency was significantly higher in sows provided with CCM than in those without CCM (p < 0.01, Table 3).a,b,c Significantly different variables within the row (p < 0.05). 1,2Post-hoc contrast analysis depending on CCM provision or HVC supplementation.
Follicular Development
The mean diameter of the five largest follicles on both ovaries tended to be smaller in the vit-C group than that of those in the control group 3 days after weaning (p = 0.077, Figure 4a). Conversely, the weaning-to-estrus and weaning-to-ovulation intervals did not differ among the treatment groups (Figure 4b).
Discussion
Hyperprolific sows are known to experience severe oxidative stress, primarily attributable to the elevated energy required for fetal development and milk production during the late gestation and lactation periods. This stress negatively affects the maternal behaviors and reproductive performances of peripartum sows [4,5]. The present study showed that the provision of CCM as nesting material in a loose-housed pen effectively promotes NB. The encouragement of instinctive behavior in prepartum pigs may alleviate the deleterious effects induced by elevated oxidative and physiological stress resulting from large litters. However, CCM provision had no discernible influence on the development of preovulatory follicles in sows after weaning.
The impact of CCM provision on counteracting the adverse effects associated with increased oxidative stress in hyperprolific sows was evaluated by comparing it to that observed by supplementation with antioxidants. However, the commercial feed used in
Discussion
Hyperprolific sows are known to experience severe oxidative stress, primarily attributable to the elevated energy required for fetal development and milk production during the late gestation and lactation periods. This stress negatively affects the maternal behaviors and reproductive performances of peripartum sows [4,5]. The present study showed that the provision of CCM as nesting material in a loose-housed pen effectively promotes NB. The encouragement of instinctive behavior in prepartum pigs may alleviate the deleterious effects induced by elevated oxidative and physiological stress resulting from large litters. However, CCM provision had no discernible influence on the development of preovulatory follicles in sows after weaning.
The impact of CCM provision on counteracting the adverse effects associated with increased oxidative stress in hyperprolific sows was evaluated by comparing it to that observed by supplementation with antioxidants. However, the commercial feed used in this study already fulfilled the requirements for antioxidants, such as selenium (0.15 mg/kg) and vitamin E (44 IU/kg), according to the Korean feeding standards for swine [19]. Therefore, supplementation with HVC, a water-soluble vitamin known for its potent antioxidant properties, was implemented to mitigate the overloaded oxidative stress in hyperprolific sows during the late gestation and early lactation periods [10,11]. However, this led to prolonged farrowing and heightened physiological stress and had no advantageous effects on maternal behavior and the developmental progression of preovulatory follicles. We speculate that the pro-oxidant effect of HVC was exacerbated, as the feed contained the maximum restriction levels of selenium and vitamin E according to the Korean feeding standards for swine [19]. However, consideration of vitamin C supplementation in the feed may still be an option, since it is impossible to add additional selenium and vitamin E to the modern sow feed according to the Korean specifications [19]. Therefore, we believe that our current findings can serve as basis information for adjusting the amount of vitamin C supplementation.
The assessment of AOPP and H 2 O 2 levels indicated that CCM provision tended to lower oxidative stress among sows with large litters during late lactation. These findings conform to those of previous studies, which demonstrated that sows may experience heightened oxidative stress, particularly during late gestation and lactation periods, especially when exposed to environmental stressors, such as the absence of nesting material and suboptimal housing conditions [13,14]. Furthermore, a positive correlation between oxidative stress status, as indicated by the increased AOPP and H 2 O 2 levels, and cortisol levels observed in this study aligns with the observation by Rubio et al. [20] who demonstrated a positive correlation between increased stress and cortisol levels, induced by shearing in sheep, and heightened AOPP and H 2 O 2 levels. Jarvis et al. [21] reported that prepartum sows deprived of nesting material experience elevated physiological stress due to disrupted NB than those provided with straw. Consistent with these findings, a recent study by Plush et al. [22] highlighted that supplying approximately 2 kg of straw daily until parturition extends the NB duration, which reduces plasma cortisol concentrations in sows. Consequently, the prepartum period in sows is a critical time, wherein the absence of adequate space and materials to perform NB can induce increased cortisol secretion because of the activation of the hypothalamic-pituitary-adrenal axis [23][24][25][26]. These results suggest that the provision of CCM as a nesting material may have the potential to diminish physiological stress by stimulating prepartum NB, thereby alleviating oxidative stress in sows during late gestation and lactation periods.
The increased TEAC levels on day 1 after farrowing associated with HVC supplementation, as shown in the current study, aligns with the findings of Zulueta et al. [27] who reported a strong positive correlation between the TEAC levels and vitamin C content in juice-milk beverages. This suggests the potential impact of HVC supplementation on the enhancement of overall antioxidant capacity. Furthermore, the rise in TEAC levels in response to HVC supplementation in sows implies an improved ability to counteract oxidative stress [28]. However, we did not observe significant effects of HVC supplementation on the AOPP levels throughout the experimental periods, despite the control group showing higher AOPP levels when compared separately to the vit-C or mat group on day 4 before parturition. These contrasting outcomes may be attributed to the large litter size, which induces excessive physiological and oxidative stress due to increased energy demands for fetal growth and milk production in late gestation and lactation [3]. In particular, milk production in sows continually rises after farrowing, peaking between 7 to 12 days postpartum [29][30][31]. This surge in milk production can trigger catabolic activity in the animal, leading to elevated oxidative damage at the cellular level [3,4,31]. Therefore, we speculate that the escalating oxidative stress caused by substantial milk production likely exceeds the neutralizing capacity of intrinsic antioxidants present in the feed.
TNF-α, which is produced by activated macrophages and monocytes, is an inflammatory cytokine that regulates cellular proliferation, differentiation, death, and immune responses [32,33]. A recent study explored the potential impact of providing approximately 2 cm of straw bedding once a week during late gestation and lactation periods on the TNF-α levels in sows [34]. However, such bedding materials did not influence the TNF-α levels. In contrast, Chen et al. [35] demonstrated that vitamin C supplementation could decrease the TNF-α levels in lipopolysaccharide-stimulated cells. This reduction was achieved by curbing the production of ROS, which are known to trigger the release of inflammatory cytokines. However, the present results revealed that neither providing nesting material nor supplementing vitamin C has a discernible impact on the TNF-α levels in sows. This lack of influence could potentially be attributed to the hyper-inflammatory responses observed in hyperprolific sows. These responses stem from various factors, including limited uterine capacity, prolonged farrowing, and increased synthesis of colostrum and milk during lactation [4,36] The cumulative effect of these factors might lead to the substantial release of inflammatory cytokines, possibly surpassing any anti-inflammatory potential that HVC supplementation might have held [37,38].
High cortisol levels in sows can have adverse consequences because they inhibit the release of prolactin and oxytocin [39][40][41]. This physiological disruption may lead to decreased success in the suckling of piglets and reduced average litter weight [42]. In this study, sows provided with CCM displayed a tendency toward decreased cortisol levels during early lactation. This trend might possibly be attributed to the fulfillment of their natural desire to perform prepartum NB. In contrast, HVC supplementation increased the cortisol levels on day 1 of lactation. This rise in the cortisol levels might have been due to discomfort and pain from prolonged farrowing in sows, as evidenced by the positive correlation between the cortisol levels on D1 and farrowing duration in this study. Mainau and Manteca [36] and Oliviero et al. [43] reported that prolonged farrowing causes acute stress, primarily due to pain and exhaustion, leading to increased plasma cortisol concentrations.
Additionally, the increased cortisol levels may be associated with the intake of high doses of vitamin C, which produces potential adverse effects, such as nausea, heartburn, and stomach cramps [42]. According to Heimer et al. [42], vitamin C intake exceeding 2000 mg/day increases the risk of adverse gastrointestinal effects in adult humans. Chambial et al. [44] also reported that high doses of vitamin C (2-6 g daily) can cause gastrointestinal disturbances in humans. In the current study, high-concentration vitamin C (20%) was supplemented at a rate of 20 g/day before parturition, which was then gradually increased by 10 g/day after parturition until it reached 70 g. This supplementation strategy was employed to mitigate a potential rise in oxidative stress in the hyperprolific sows during periparturient and lactation periods. However, considering sows can synthesize ascorbic acid, commonly known as vitamin C, supplementation of this vitamin may be unnecessary [45]. Hence, the vitamin C dose administered in this study might have been excessive for the sows. These findings indicate the potential risks associated with prolonged farrowing and potential gastrointestinal disturbances resulting from excessive HVC supplementation, leading to increased stress levels in sows, which emphasize the importance of balanced and carefully monitored nutritional interventions.
According to Yun et al. [17] and Wischner et al. [46], the provision of abundant nesting materials may contribute to increased oxytocin and prolactin concentrations in peripartum sows. Additionally, Yun et al. [18] reported that supplying nesting materials to sows can elevate piglet serum IgM concentrations by enhancing overall colostrum yield. Hence, we anticipated that providing CCM to prepartum sows as nesting material might increase maternal hormones and Ig yield. However, while the mat group exhibited numerically higher levels of colostrum oxytocin, prolactin, IgG, and IgM than the control group, the difference was not statistically significant. This may be attributed to temporal variation among the colostrum samples, which were collected within 3 h after parturition. In fact, the concentration of Ig in colostrum decreases drastically after the onset of parturition [47,48].
The current findings clarify the facilitation of prepartum NB in sows with large litters. The provision of CCM as nesting material to the sows housed in pens with slatted floors was notably efficacious in promoting prepartum NB when compared with just the provision of additional space, vitamin C supplementation, or both. These results signify the suitability of CCM as a nesting material owing to its edible, chewable, investigable, and destructible characteristics. Additionally, it does not fall easily into the slurry pit, thereby preventing issues with manure treatment. The active stimulation of NB in sows by the provision of CCM is supported by previous studies [49,50]. The initiation of prepartum NB is intricately linked to a discernible rise in prolactin concentration in sows [51]. Wischener et al. [46] suggested that the provision of nesting material can also potentially elevate prolactin concentrations in prepartum sows, thus contributing to the initiation of prepartum NB. The continuous activation of prepartum NB in sows relies on a delicate balance between internal feedback mechanisms and external stimuli [46]. In the present study, providing CCM as nesting material played a crucial role in offering external stimuli, addressing both the behavioral and physiological requirements for active NB in sows. This concept has been validated in previous studies [17,52,53]. Meanwhile, we found that the average number of stillbirths per litter was high in the CCM group. It is suggested that an elevated stillbirth rate has been linked to prolonged farrowing [2]. However, our current findings did not establish a clear association between the farrowing process and stillbirths. This aligns with a prior study by Yun et al. [54]. Despite these observations, we were unable to identify the reasons for the lack of beneficial effects of nesting materials on stillbirths.
The present study showed that HVC supplementation poses challenges during the farrowing phase in sows, primarily by increasing farrowing duration. This outcome can be rationalized by the notion that the excessive supplementation of vitamin C may interfere with the farrowing process by inhibiting the synthesis of prostaglandins (PGs), which are intimately related to the initiation of parturition and cervical dilation. According to Fiebich et al. [55], vitamin C has a dose-dependent inhibitory effect on the synthesis of PG, hindering the activity of cyclooxygenases in primary rat microglia. Similarly, Rosenkrans et al. [56] reported that vitamin C decreases the release of PGE and PGF2α in the endometrium of sows. Furthermore, excessive vitamin C supplementation induces gastrointestinal discomfort, which in turn, escalates cortisol levels before farrowing [42,44]. Increased cortisol may potentially inhibit the secretion of crucial maternal hormones, such as oxytocin and prolactin, thereby leading to prolonged farrowing [57,58]. Based on these findings, we speculate that the HVC supplementation in sows might have inhibited the secretion of essential hormones, resulting in prolonged farrowing duration. Nonetheless, the current findings, which reveal the absence of significant differences in the colostrum oxytocin and prolactin levels among the treatment groups, fail to substantiate the validity of this assumption. As previously explained, this is believed to stem from a potential error in the colostrum sampling method and therefore requires further research.
Excessive oxidative stress can exert detrimental effects on the integrity of oocytes and consequently, the overall reproductive processes. The present study showed that HVC supplementation tended to reduce follicle diameters compared to the control group 3 days after weaning. This might have been due to the Fenton reaction-i.e., high-dose vitamin C can act as a pro-oxidant instead of an antioxidant [59]. This reaction can potentially increase ROS production, which in turn, can trigger the apoptosis of oocytes and disrupt the delicate balance of crucial hormones such as the follicle-stimulating hormone and luteinizing hormone, both of which play critical roles in follicle growth and ovulation [60]. However, a study by Tarin et al. [61] showed the potential adverse effects of the oral administration of vitamin C (10 g/kg diet) and vitamin E (0.6 g/kg diet) in mice. High doses of these vitamins led to hypervitaminosis, which disrupts ovarian steroidogenesis and fertility. Furthermore, Kere et al. [62] demonstrated that HVC supplementation (100 µg/mL) induces apoptosis during the in vitro maturation of porcine oocytes, highlighting the potential risk associated with excessive vitamin C intake. In the current study, the H 2 O 2 levels, right before weaning in the vit-C group, were numerically higher than those in the control group. Elevated H 2 O 2 levels could potentially increase the production of hydroxyl radicals, which are highly reactive molecules known for their capacity to cause extensive oxidative damage to oocytes [63]. Therefore, our findings emphasize that the dosage and potential side effects should be carefully considered when supplementing diets with vitamin C for reproductive management, especially in sows with large litters.
Conclusions
The utilization of a CCM as nesting material for sows with large litters was shown to have positive impact on NB, even on slatted flooring, which in turn, may have the potential to regulate the physiological and oxidative stress levels in these sows during lactation. This finding is indicative of the pivotal role of NB in alleviating stress, which influences oxidative stress management in sows with large litters. However, despite these positive effects, NB stimulation did not influence preovulatory follicular development, the reasons for which may be multifaceted. HVC supplementation in sows with large litters had a contrasting impact. It was negatively associated with the farrowing process, physiological stress, and follicle development. This adverse effect may be attributed to the potential risks associated with excessive vitamin C intake, which presumably leads to pro-oxidant effects and gastrointestinal disturbances. Therefore, managing the oxidative stress of highly prolific sows may necessitate the use of feed additives that can effectively counter oxidative stress without introducing adverse effects. Furthermore, understanding the intricate relationship between oxidative stress status and follicle development in sows with large litters requires further investigation.
Figure 2 .
Figure 2. Effects of CCM provision and HVC supplementation on salivary cortisol levels of sows. All saliva samples were collected at 10:30 on each sampling day. Values represent means and standard error.** p < 0.05.
Figure 2 .
Figure 2. Effects of CCM provision and HVC supplementation on salivary cortisol levels of sows. All saliva samples were collected at 10:30 on each sampling day. Values represent means and standard error.** p < 0.05.
Figure 4 .
Figure 4. Effects of CCM provision and HVC supplementation on preovulatory follicular development (a) and weaning-to-oestrus and weaning-to-ovulation intervals (b) in sows. The diameters (in mm) of the five largest follicles on the left and right ovary were measured, and the average was calculated after weaning until ovulation. Values represent means and standard error.* p < 0.10.
Figure 4 .
Figure 4. Effects of CCM provision and HVC supplementation on preovulatory follicular development (a) and weaning-to-oestrus and weaning-to-ovulation intervals (b) in sows. The diameters (in mm) of the five largest follicles on the left and right ovary were measured, and the average was calculated after weaning until ovulation. Values represent means and standard error.* p < 0.10.
Table 1 .
Effects of CCM provision and HVC supplementation on salivary oxidative stress parameters of sows.
Table 2 .
Effects of CCM provision and HVC supplementation on colostral hormones and Ig in sows.
Table 2 .
Effects of CCM provision and HVC supplementation on colostral hormones and Ig in sows.
Table 3 .
Effects of CCM provision and HVC supplementation on farrowing process and litter characteristics.
Table 3 .
Effects of CCM provision and HVC supplementation on farrowing process and litter characteristics.
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Domain: Agricultural and Food Sciences
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Fruit Quality and Yield of Three Highbush Blueberry ( Vaccinium corymbosum L.) Cultivars Grown in Two Planting Systems under Different Protected Environments
: Due to the increasing interest in highbush blueberry ( Vaccinium corymbosum L.) among consumers, together with the problems of climate change and specific substrate requirements, a novel approach to intensive blueberry production is required. Here, ‘Duke’, ‘Aurora’, and ‘Brigitta’ blueberry cultivars were planted under the protective environments of a high tunnel and black hail net, each using ridge and pot planting systems. The high tunnel increased the maximal air temperature on average by 7.2 ◦ C compared to the hail net. For all three cultivars, harvest began 6 to 18 days earlier under the high tunnel than under the hail net; however, lower yields and individual phenolics contents were obtained for the fruit. In ‘Aurora’ and ‘Brigitta’, environmental conditions under the high tunnel also reduced plant volume and fruit sugar/organic acid ratio. Growing blueberry plants in 60 L pots had no negative effects on plant volume and fruit ripening time, yield, firmness, color, and chemical composition. This study represents the first to compare highbush blueberry grown under the high tunnel and hail net protective environments using ridge and pot planting systems across three different cultivars. Here, we can conclude that optimal highbush blueberry production of ‘Duke’, ‘Aurora’, and ‘Brigitta’ under the climate conditions of the study provides earlier ripening times under the high tunnel. However, according to fruit yield and quality, all three cultivars benefit from the hail net over the high tunnel, while ‘Duke’ and ‘Brigitta’ also benefit in particular from the hail net combined with growth in pots.
Introduction
In recent years, consumer demand for blueberry fruit (Vaccinium corymbosum L.) has risen dramatically, due to their favorable sweet and sour taste and their beneficial effects on human health. Together with the high marketable price of the fruit, this has led to a significant increase in blueberry production throughout the world [1,2].
Blueberry fruit contain phenolics (e.g., anthocyanins, flavan-3-ols, flavonols, phenolic acids, hydrolyzing and condensed tannins, and resveratrol), vitamin C, carotenoids, and tocopherols [3,4], all of which provide the health-promoting properties of the fruit, for which blueberry are indicated as a 'functional food' [5]. Previous studies have suggested that long-term consumption of fruit that are rich in phenolics, such as blueberry fruit, has anti-inflammatory effects and provides protection against cancers, cardiovascular diseases, stroke, high blood pressure, diabetes, and osteoporosis [6,7].
Blueberry fruit are now available all year round all over the world. However, the ripening period within individual countries overlaps, which can lower the marketable price of the fruit. The introduction of protected environments into intensive blueberry production, such as high tunnels, might represent a solution to this problem. Increased air temperature in the spring can promote faster development of the fruit and thus provide earlier fruit ripening and availability on the market, and consequently a higher price for the fruit earlier in the season, while also avoiding the use of early ripening cultivars that are more sensitive to spring frosts [2,8]. Under high tunnels, air temperature, relative air humidity, and light properties differ from those under hail nets, which leads to an earlier occurrence of phenophases. High tunnels can also provide an extended growing season, higher yields, and protection against hail, rain, birds, and frost, which will also allow production to expand toward cooler areas [8]. High tunnels are successfully used today in the production of flowers [9], vegetables [10], and small fruit [11].
In recent years, due to the frequent occurrence of hail storms, the installation of hail nets in blueberry orchards has increased. These protect plants from hail and bird attacks, prevent sunburning of leaves and fruit, and reduce temperature, light, and drought stress of the plants through reduced direct light and increased diffused light reaching the plants [12,13]. Most blueberry growing areas have been described with air temperatures and solar radiation higher compared to their natural habitat. Consequently, hail net introduction into blueberry orchards would be a useful way to bring the environmental conditions in intensive blueberry production closer to those in their natural habitats [14]. In intensive production, black hail nets are most commonly used; however, growing interest in nets of other colors has occurred among growers. Black nets absorb the most light and thus shade the plants the most, while white nets absorb the least. The light that passes through the holes in the black net remains spectrally unchanged, while the light that hits the fibers of other colors scatters and changes spectrally. The modified light spectrum alters plant physiological processes, while scattered light penetrates deeper into the blueberry plant between leaves compared to direct light. The introduction of hail nets has already been established for the production of many fruit species, such as apple [15][16][17], pear [18], persimmon [19], kiwifruit [20], peach [21], and others, and demand among growers for hail net installation for blueberry orchards has started to appear in recent years [22].
In addition to ridge production of blueberry fruit, pot production represents a new approach with increased interest of growers and researchers in recent years. In particular, this allows the soil pH to be better controlled through the use of a precise substrate and irrigation and fertilization of the plants. Blueberries thrive in acidic substrates with pH from 4.5 to 5.5, which can be very challenging to maintain. Too high a pH can lead to lower yields, limited growth, and poorer intake of certain nutrients (e.g., iron, manganese, copper) [2,23]. Growing blueberries in pots allows the plants to be moved for adjustment of the plant density based on plant volume [24]. The downside of pot production is limited root growth, which reduces the absorption area for water and nutrients. At the same time, the question of the lifespan of plants grown in pots arises: Kingston et al. [25] and Jiang et al. [23] composted pine bark, peat moss, and coconut coir together at pH 4.5, which was reported to be the optimal substrate property for blueberry pot production.
Due to the many difficulties growers have been facing for intensive blueberry production in recent years (e.g., market saturation, hail storms, and substrate pH), the interest in alternative production methods has increased. The aim of the present study was to investigate the response of blueberry plants (as plant growth, phenophase occurrence, and fruit quality and yield) under high tunnel and hail net protection with ridge and pot production technologies. At the same time, the air temperatures were monitored, together with relative air humidity, photosynthetic photon flux density, and substrate water content.
Experimental Design
The experiment was conducted in the second year after planting in a test field of the Biotechnical Faculty of Ljubljana University, Ljubljana (Slovenia; latitude, 46 • 05 N; longitude, 14 • 47 E; altitude, 295 m a.s.l.). Uniform plants of 'Duke', 'Aurora', and 'Brigitta' were selected on 9 May 2018 and planted in a ridge and in 60 L pots that were positioned under the protected environments of a high tunnel and black hail net (i.e., four treatments for each cultivar and 15-17 plants per treatment of individual cultivar). To provide conditions for optimal pollination, these protected environments were removed (i.e., rolled up on top of the supporting structure) from leaf senescence to the end of flowering.
The high tunnel (Schwarzmann) and hail net supporting structures were 6 m wide and 24 m long, with a south to north orientation. The high tunnel was covered with white polypropylene foil (200 µm thickness), with natural ventilation. Four sprinklers (NAAN 501-U; Zeleni hit, Ljubljana, Slovenia) were placed under the high tunnel at a distance of 6 m from each other, between the ridge and the pots, at 2 m height. The sprinklers were used from the beginning of July onwards, twice a day, for 2 h at 11:00 a.m. and 2:00 p.m.
For the ridge and pot planting systems, the plants were positioned at a distance of 0.6 m along each row and 2 m between each row. The substrate consisted of peat, soil, and pine sawdust, one-third each by volume. The floor was covered with white polypropylene foil. The plants were also drip irrigated according to sensor measurements (when the substrate water content dropped below 950 mV; electrical conductivity), which means different water quantities were applied in each treatment. The plants in a ridge were fertigated once to twice a week, depending on the phenophase (0.1-0.2%), and plants in pots every day with smaller concentrations of fertilizer (0.03%), from the beginning of April to mid-June.
Environmental Conditions
Substrate and air temperature, amount of water in the substrate, and relative air humidity were monitored by continuous measurements using substrate temperature sensors (DS18b20; Dallas Semiconductor, Dallas, TX, USA), substrate moisture sensors (EC5; Decagon Devices, Pullman, WA, USA), and air temperature and relative humidity sensors (SHT11 integrated sensor; Sensirion Inc., Staefa, Switzerland), respectively. The data were stored in a measuring instrument and automatically sent to the IoT cloud, which allowed constant access and real-time control of the substrate temperature and water content measurements. Light quality and quantity measurements were made on a clear, sunny day using an illuminance spectrophotometer (250-800 nm; SRI-2000 (FB); Optimum Optoelectronics Corporation, Hsinchu, Taiwan). Measurements were made at 1 m height under the high tunnel and the hail net, and in the open field, as five repetitions.
Plant Volume and Fruit Harvest
The volume of ten randomly chosen plants was measured on 9 April and 24 October 2019. A measuring tape was used to measured plant height and two widths at half the height (the first in the row direction, the second at 90 • to the row). Plant volumes were calculated according to Equation (1): The blueberry fruit were harvested every 7 days, starting on 17 June 2019. For each treatment, the plants were harvested from five to eight times, and the dates of every harvest were recorded. At each harvest, the fruit number per plant was counted, and the total yield per plant was measured in the laboratory, together with fruit firmness and peel color. The mean single fruit weight was calculated by dividing the total plant yield by the number of fruit per plant. After the measurements, the fruit were frozen in liquid nitrogen and stored at −20 • C for further analysis.
Fruit Firmness and Color
For fruit firmness and color, all of the berries from the same treatment were pooled to provide the average samples. Fifteen randomly chosen berries from across all of the harvests and under each treatment were selected for the measurements. Fruit firmness was measured once on each of these fruit using a digital penetrometer (TR; Turin, Italy) with a 1 mm diameter tip.
The blueberry fruit color was measured using a portable colorimeter (CR-10 Chroma; Konica Minolta, Tokyo, Japan) once on each of the fruit. The parameters used to describe color are L*, C*, and h • (CIELAB). The L* (lightness) ranges from 0 to 100, where 0 is black and 100 is white. The C* provides the chroma, where higher values represent more intense color. The h • (hue angel) represents the color expressed in degrees, from 0 • to 360 • (0 • , red; 90 • , yellow; 180 • , green; 270 • , blue).
Individual Sugar and Organic Acid Extraction and Determination
The extraction for the individual sugars and organic acids was carried out using an average sample across all of the harvest dates for all of the treatments, as five repetitions, according to the method previously described by Mikulic-Petkovsek et al. [26]. Freshly thawed fruit were chopped with a knife, and 1 g homogenous sample was transferred into a test tube with 4 mL bi-distilled water. The samples were mixed by vortexing and with constant stirring (Unimax 1010 shaker; Heidolph, Schwabach, Germany), with the extraction at room temperature for 30 min. After the extraction, the samples were centrifuged (5810 R; Eppendorf, Hamburg, Germany) at 9000× g for 10 min at 4 • C and transferred into vials through cellulose filters (0.2 µm; Chromafil A-20/25; Macherey-Nagel, Düren, Germany). These samples were stored at −20 • C until the start of the analysis using high-performance liquid chromatography (HPLC).
Organic acids were analyzed by HPLC (Vanquish system; Thermo Scientific, Waltham, MA, USA) using a Rezex ROA-Organic acid H+ 8% column (150 mm × 7.8 mm; Phenomenex, CA, USA). The UV detector was set at 210 nm under the following analytical conditions: column temperature, 65 • C; injection volume, 20 µL; flow rate, 0.6 mL min −1 ; and sample analysis time, 15 min. The mobile phase was 4 mM sulfuric acid in bi-distilled water [27]. The individual organic acids were determined by comparisons with external standards for citric, tartaric, malic, and shikimic acids and are expressed as mg g −1 FW.
Individual Phenolics Extraction and Determination
Individual phenolics were extracted from the same samples as used for the sugars and organic acids. The freshly thawed fruit were cut into small pieces and finely chopped to obtain a homogenous sample. The precise weight of each sample was recorded for further calculations. Four milliliters of 70% methanol containing 3% formic acid in bi-distilled water was added to 2 g of each fruit sample in test tubes as the extraction solution. The samples were mixed by vortexing, left in a cooled ultrasonic bath (0 • C) for 1 h, and then centrifuged at 9000× g for 10 min at 4 • C (5810 R; Eppendorf, Hamburg, Germany). The supernatant was filtered through 0.2 µm polyamide filters (Chromafil AO-20/25; Macherey-Nagel, Düren, Germany), put into vials, and stored at −20 • C until further analysis [28].
The individual phenolic compounds were identified by comparisons of their retention times with external standards and using an ion trap mass spectrometer (LTQ XL linear; Thermo Scientific, Waltham, MA, USA) based on their mass fragmentation patterns. The injection volume of the samples was 10 µL, and the flow rate was 0.6 mL min −1 . The mass spectrometer was operated in negative and positive (anthocyanins) ion modes, with electrospray ionization. The capillary temperature was maintained at 250 • C, the sheath gas at 20 units, and the auxiliary gas at 8 units. The source voltage used was 4 kV, with m/z scanning from 115 to 1600. The phenolic compounds contents were quantified from corresponding external standards and are expressed as mg 100 g −1 FW.
Statistical Evaluation
Statistical analysis was performed in R commander i386 4.0.4 (Vienna, Austria) [29]. Statistically significant differences between treatments were determined by one-way analysis of variance (ANOVA). Significant differences between treatments are represented by different letters. Principal component analysis was performed to evaluate how individual treatments are related among each other in terms of the different groups of phenolics.
Environmental Conditions
As can be seen from Figure 1, there were no differences for the minimum air temperature between the high tunnel and the hail net conditions. However, as the temperature increased, the differences in air temperatures between these two protected environments also increased. The maximum air temperature was considerably higher under the high tunnel, compared to the hail net, with the greatest difference reaching 23 • C on 26 May 2019. In the warmer months of the year, the maximum air temperature under the high tunnel was >40 • C and was once >50 • C, while under the hail net, the highest measured temperature was 39 • C. Figure 2 shows the substrate water content (as the electric conductivity) under the high tunnel and hail net for the ridge and pot planting systems. From April to the beginning of June, the different treatments did not differ for the amounts of water made available to the plants. Towards the summer (i.e., from July), the differences became more pronounced, with the highest values under the hail net for the ridge system and the lowest under the high tunnel for the ridge system. For the relative air humidity, this was consistently higher under the hail net conditions throughout the measurement period, compared to the high tunnel conditions (Figure 3).
Plant Volume and Yield
The individual cultivars responded differently to these changed environmental and growth conditions (Table 1). Plant volume in 'Duke' plants differed only between pots; however, no significant differences were measured between high tunnel and hail net and ridge and pots. In 'Aurora', significant differences were seen between all four of the treatments. The highest plant volume in 'Brigitta' was for the plants grown under the hail net, with no significant differences between ridge and pots. Under the high tunnel, the plant volume was significantly higher for the potted plants for 'Brigitta'. For 'Aurora' and 'Brigitta', significantly higher plant volumes were seen under the hail net (when comparing protected environments) and in ridge and pots, respectively (in planting system comparison). Fruit from the 'Duke' plants did not significantly differ in weight between treatments (Table 1). 'Aurora' and 'Brigitta' fruit had significantly higher weights when under the hail net. However, fruit from 'Brigitta' were larger from the plants in pots.
Significant differences in fruit number and yield per plant were seen between the treatments for the 'Duke' plants (Table 1). Growing the blueberry plants in pots under the hail net significantly increased the fruit number and yield per plant in 'Aurora', while the lowest values here were seen for the high tunnel with the pots. Production of all three of the cultivars under the high tunnel significantly decreased fruit number and yield per plant, compared to the hail net. For 'Brigitta', significantly higher fruit number per plant was seen for the hail net and in the ridge, although with no significant differences in final yield per plant between ridge and pots.
The dates of the first, peak, and end harvests are given in Table 2. Peak harvest is considered the date with the highest yield. Under the high tunnel, the fruit began to ripen 6 days earlier for 'Brigitta', 9 days earlier for 'Duke', and 18 days earlier for 'Aurora', compared to those under the hail net. However, the peak and end of harvest in 'Aurora' fruit coincided for all treatments, while the difference in ripening dates for 'Duke' remained. Interestingly, the dates of the peak harvest for 'Brigitta' fruit under the high tunnel and hail net differed by 18 days, while the fruit harvest from the different treatments ended on three different dates, over a range of 21 days.
Fruit Firmness and Color
The blueberry fruit firmness is presented in Table 3. For the 'Duke' and 'Aurora' fruit, no significant differences were seen between the treatments. In contrast, fruit from 'Brigitta' harvested from plants under the high tunnel and in the ridge were significantly firmer, compared to the other three treatments. In 'Duke', significant differences in L* were seen between the fruit under the high tunnel in pots and the fruit under the hail net for both planting systems. There was also a significant difference between the two protected environments and no significant difference between planting systems (Table 3). Fruit L* did not significantly differ between treatments for 'Aurora' and 'Brigitta', although significantly higher values were measured for 'Brigitta' fruit from the high tunnel, compared to the pots. Within the 'Duke' cultivar, C* differed between the high tunnel and hail net fruit across the treatments. At the same time, significant differences were seen for the pots under both protected environments. However, C* showed no significant differences between the 'Aurora' fruit from the different treatments. Significant opposite differences were seen between the high tunnel and the hail net for the 'Brigitta' fruit compared to the 'Duke', with significant differences also seen between the ridge planting system. Finally, here, significant differences in h • angle were seen across the treatments for all three of the cultivars (Table 3).
Total and Individual Sugar Contents
The changed environmental and growing conditions influenced the fruit total sugar contents within all three of the cultivars (Table 4). 'Duke' showed significantly higher total sugar content for the fruit harvested from plants under the high tunnel and in the ridge, compared to the other three treatments, which showed no significant differences. For the 'Aurora' fruit total sugar content, significant difference was only seen between the high tunnel plants in pots and the hail net plants in the ridge. The same trend was noted for 'Brigitta'; however, significance was also seen between the protected environments and between the high tunnel planting systems. Indeed, the highest value here was for the fruit under the high tunnel and in the ridge, which was approximately twice that of the other treatments. When comparing the high tunnel and the hail net, all three cultivars showed significantly higher total sugar content under the high tunnel, while in the planting systems comparison, 'Duke' and 'Brigitta' showed significantly higher values in fruit from the ridge.
The individual sugar contents for the blueberry fruit are shown in Figure 4. Sucrose content in the 'Duke' fruit significantly differed between all four growing conditions, protected environments, and planting systems. A similar trend for glucose and fructose content was observed, with the highest values under the high tunnel for glucose and under the high tunnel and in the ridge for fructose. However, glucose content did not significnatly differ between protected environments and planting systems. In the 'Aurora' fruit, no significant differences were seen for fruit sucrose content between the plants under the high tunnel and in the ridge and for those under the hail net and in pots; however, there was a significant difference between the high tunnel and the hail net and, at the same time, between the ridge and pots. Glucose content was the same in all of the fruit, while significant differences in fructose content were seen between the treatments under the high tunnel, together with differences between planting systems, with no significance seen between the high tunnel and the hail net. For 'Brigitta', the highest content of all three of these individual sugars was seen for the fruit under the high tunnel and in the ridge and the lowest for the fruit under the hail net.
Total and Individual Organic Acid Contents
The total organic acids content in 'Duke' was highest for the fruit from the pots, with no significant differences between the high tunnel and the hail net (Table 4); however, significance was noted between the ridge and pots. Similar data were seen for the 'Aurora' fruit, where the highest total organic acids content was for the fruit under the high tunnel and in pots and the lowest was for the fruit under the hail net. At the same time, the fruit from the high tunnel showed significantly higher total organic acids content compared to the hail net. For the 'Brigitta' fruit here, no significant differences were seen between the high tunnel and the hail net, nor between the ridge and pots.
The individual organic acids contents in the blueberry fruit are shown in Figure 5. Here, significant differences were seen in all four of the organic acids identified in all three of the cultivars, with no particular trends in favor of any individual treatment. Citric acid was the predominant organic acid, and in 'Duke', it was significantly higher for the fruit from the pots, compared to the ridge. However, no significant differences were seen between the high tunnel and the hail net for citric acid for 'Duke'. For 'Aurora', citric and malic acid contents were lowest for the fruit from the hail net, as for tartaric acid content from the plants under the hail net and in pots. For the high tunnel and hail net comparison, the highest contents for all of the organic acids identified were for the fruit from the high tunnel. The 'Brigitta' fruit contained the highest citric and tartaric acid contents for the plants under the high tunnel and in pots and for those under the hail net and in the ridge. Here, the highest malic acid content was for the fruit under the high tunnel and in pots, and the shikimic acid content was highest for the fruit under the hail net. Considering different planting systems, no significance was observed in individual organic acid contents.
Sugar/Organic Acid Ratio
From the data given in Table 4, it can be seen that for the total sugar/organic acid ratio, each cultivar responded differently to the different growing conditions. For 'Duke', the highest total sugar/organic acid ratio was seen for the fruit under the high tunnel and in the ridge, and for 'Aurora', for the fruit under the hail net. For 'Brigitta', significant differences for the total sugar/organic acid ratio were seen between all of the treatments, with the highest for the fruit under the high tunnel and in the ridge and the lowest for the fruit under the hail net and in pots, with a corresponding significant difference when comparing protected environments or planting systems.
Phenolics Content
The individual phenolics contents in 'Duke' fruit are shown in Figure 6, with additional statistical analysis in Supplementary Material Table S1. The highest individual phenolics content was for fruit from under the hail net and in pots, and the lowest was for the high tunnel. For the high tunnel, no significant differences were seen for most of the phenolics identified in the fruit across the different planting systems. According to the statistical analysis, some exceptions were noted among the phenolic acids, flavan-3-ols, and anthocyanins. At the same time, significance was detected in total phenolic acids and flavan-3-ols content between the ridge and pots. The highest individual phenolics contents for phenolic acids and flavan-3-ols identified in 'Aurora' varied between the treatments; however, their total content was highest under the high tunnel ( Figure 6; Supplementary Material Table S2). The opposite was seen for flavonols, where the highest content of all of these compounds was for the fruit under the hail net, which were in most cases independent of the planting system. The exceptions here were quercetin-3-O-arabinofuranoside, kaempferol-3-O-rutinoside, isorhamnetin-3-O-rutinoside, and syringetin-3-O-glucoside, where the highest contents were seen for the fruit from the plants in the ridge. As far as the anthocyanins are concerned, a similar trend was seen for flavonols, with the highest contents for the fruit under the hail net and in pots, with some exceptions (i.e., cyanidin-3-O-arabinoside, peonidin-pentose, and malvidin derivatives).
Focusing on 'Brigitta', the data are not in favor of any one or other of the treatments ( Figure 6). Among the phenolic acids, an ellagic acid derivative, caffeic acid derivatives 1 and 2, and feruloyl-glucoside contents were the highest for the fruit harvested under the hail net from the plants in pots (see Supplementary Material Table S3). The contents of procyanidin B1 and B2 and catechin were the highest for the fruit under the hail net and in pots; on the contrary, the epicatechin content was highest for the fruit under the high tunnel. This corresponds to the total phenolic acids and flavan-3-ols contents comparison between planting systems, where significantly higher values were measured in pots. Then, for the flavonol group, the highest contents of most of these compounds were seen for the fruit from under the hail net, and for the anthocyanin group, for the fruit under the hail net and in pots.
The principal component analysis carried out for the individual groups of phenolics ( Figure 7) suggests that 'Duke' fruit from under the high tunnel contained lower contents of all of the phenolics. At the same time, the contents were in favor of the pots. A large clustering of 'Aurora' and 'Brigitta' was seen, with higher contents in 'Aurora'. For total phenolics content, the same trend was seen as for 'Duke', with the higher content for the fruit from under the hail net. Correlation tests showed strong correlation between all of the phenolics groups and the total phenolics content, except for hydroxycinnamic and hydroxybenzoic acids. Strong correlation was also seen between anthocyanins and flavonols content (p < 0.0001).
Discussion
To date, only a few studies have compared highbush blueberry production under the protected environments of a high tunnel and a hail net. Furthermore, no studies have yet compared these together with the ridge and pot planting systems and their connection with the environmental conditions. In the present study, the air temperature under the high tunnel reached higher values compared to those under the hail net, which is in agreement with some previous reports from studies conducted under high tunnels [8,[30][31][32]. The maximum air temperature under the high tunnel during the fruit ripening period reached values above the individual cultivar thresholds for photosynthesis. According to Moon et al. [33], the 'Jersey' photosynthesis threshold is between 18 • C and 26 • C, and for 'Bluecrop', between 14 • C and 22 • C. These thresholds suggest that high air temperatures during the summer can lead to heat stress in plants under a high tunnel, which will result in reduced photosynthesis and, consequently, limited metabolite accumulation [34].
From the beginning of July onwards, the differences in maximum air temperature between the high tunnel and the hail net were not so large, due to the use of micro sprinklers under the high tunnel, which will reduce the air temperature and cool down the plants. Together with drip irrigation, the micro sprinklers provided the plants with an adequate water supply; however, the substrate water content was still higher under the hail net, due to natural precipitation. The larger substrate volume in the ridge under the hail net led to higher water contents. The opposite was seen under the high tunnel, where in the warmer months of the year, uneven water distribution from the micro sprinklers led to higher water contents in the pots. The lower relative air humidity that was measured under the high tunnel might be a result of the higher air temperature and, consequently, lower leaf stomatal conductivity [35], which is in agreement with a previous report by Retamal-Salgado et al. [30].
The individual cultivars responded differently to the changed growing conditions, which is evident from the plant volume and yield measures. This suggests the interdependence of genetics and the environment in plant responses to modified growing conditions [32,36]. From the plant volumes and yields for 'Duke' and 'Brigitta', we can conclude that the substrate volume in the pots was comparable to that in the ridge, where there was no restriction to root system development, and consequently, water absorption through the roots occurred. At the same time, the substrate content in the pots was not the limiting factor in these young plants. With the adequate water supply, equally intense growth and yields were seen for the plants in the ridge and in the pots, with the exception of the yield in 'Duke' grown under the high tunnel. The results also show a reverse relationship between plant volume and fruit number per plant for 'Duke'. Cantliffe [37] also stated that the growth of roots and shoots increases as the pot volume increases. On the other hand, 'Aurora' appears to be more sensitive to the changes in the environmental conditions (i.e., protected environment, planting method) for both plant volume and yield. Together with 'Brigitta', their plant volume and yield were significantly lower under the high tunnel compared to the hail net, as also seen in some previous reports [32,34]. The plant volumes were limited because the optimal substrate temperature for blueberry plant growth is from 14 • C to 18 • C, which was strongly exceeded during the growing season under the high tunnel, where it reached 30 • C in the ridge and 33 • C in the pots [2]. According to Yang et al. [38], the air temperature range for the optimal fruit setting is 15 • C to 25 • C, which in the present study was exceeded under the high tunnel, as was clearly seen from the individual fruit weight measurements. At the same time, the high temperatures and low relative air humidities seen for the present study can reduce fruit expansion, due to increased transpiration of the fruit [39]. Opposite results were reported by Retamal-Salgado et al. [30], who measured a 44% higher yield under a high tunnel compared to a hail net. According to Santos and Salame-Dinoso [40], this might result from the increased minimum air temperature under the protected environment; however, this was not the case in the present study. Many native blueberries grow in the shade, and therefore intensive production under full lighting is likely to subject the plants to radiation and temperature stress. The use of a high tunnel or a hail net reduces the amount of light reaching the plants, which will reduce the stress and allow better growth and higher yields [14]. However, based on previous reports, the growth and yield strongly depend on the latitude [14,41].
A high tunnel modifies the environmental conditions and consequently promotes fruit ripening [30], as demonstrated in the present study. Our results coincide with those reported by Retamal-Salgado et al. [30] and Tamada and Ozeki [32], who reported about 14 days and 7 days to 40 days earlier fruit ripening, respectively, under a high tunnel and for 12 different cultivars.
Fruit firmness is among the main indicators of blueberry fruit quality [42], which mainly depends on the ripening stage and environmental conditions [36,43]. The firmness here differed only for the 'Brigitta' fruit, where firmer fruit were seen for the plants under the high tunnel and in the ridge. Ehlenfeldt and Marin [43] reported significant interactions between harvest year and cultivar, thereby confirming the dependence of fruit firmness on the environmental conditions.
Together with fruit size and firmness, a dark blue/violet peel color for blueberry fruit is a key parameter that makes the fruit intriguing to the consumer [44]. The key regulating factor of blueberry peel color is the amount of light [2], whereby a higher light quantity leads to a more intense peel color [19]. Although significant differences in the fruit color parameters were seen for the individual cultivars here, these differences were minor and were not possible to detect with the naked eye.
Sugar and organic acid contents are the fruit properties that determine the fruit quality and whether the fruit will be appreciated by the consumer [45]. These contents are strongly correlated with the cultivar and ripening stage [44,46,47], together with environmental conditions, such as light quantity and air temperature [31]. The changes in the sugars and organic acids during ripening are a result of synthesis, degradation, and translocation [46]. In the present study, three individual sugars were identified in the blueberry fruit: fructose, glucose, and sucrose. Fructose contributed the most to the total sugar content, as the prevailing sugar, which is clearly seen from similar statistical analysis and the significant differences across all three of the cultivars. For 'Duke', no significant differences were seen for fruit weight between the treatments, with no differences also seen for total sugar content and sugar/organic acid ratio, with the exception of the plants under the high tunnel and in the ridge.
As the predominant organic acid, citric acid is responsible for the higher total organic acids in the fruit from the plants in pots. A moderate organic acid content makes the fruit more palatable, while a high organic acid content reduces fruit quality [46]. 'Aurora' is generally known for its acidic taste, due to its high organic acid content [48]. Growth under the high tunnel increased the citric acid here and, consequently, the total organic acid content, which affected the sugar/organic acid ratio. This might result from lower substrate water content and fruit weight compared to the hail net [49]. In 'Brigitta', with the highest total sugar content and sugar/organic acid ratio in the fruit under the high tunnel and in the ridge, this suggests that the high sugar concentration is due to lower substrate water content and, consequently, lower fruit weight. This is in agreement with some previous studies, where an induced water deficit significantly reduced fruit weight and increased soluble solids in 'Elliot' and 'Brigitta' [49,50].
A high phenolic compounds content is desirable in blueberry fruit, as they can be beneficial for human health. The largest contribution to the total phenolics content was from the anthocyanins, due to their high content in the blueberry fruit [1]. Consequently, it is not surprising that the analysis of the anthocyanins generally parallels that of the total phenolics. The plants under the hail net were exposed to higher light quantity, and consequently the fruit from all three of the cultivars, especially 'Duke', contained significantly higher individual phenolics contents compared to the high tunnel. The higher UV radiation that was measured under the hail net is known to accelerate flavonol and anthocyanin synthesis [51], which is once more shown in the present study for all three cultivars. At the same time, higher air temperatures under the high tunnel probably limited photosynthesis, which leads to reduced metabolite synthesis [33,34]. Higher phenolic acids in 'Aurora' fruit from pots are in accordance with our previously reported results [52] and could be a consequence of more pronounced substrate temperature fluctuations, which causes stress in plants [53].
Conclusions
Despite earlier fruit ripening, growing blueberry plants under a high tunnel has been shown not to be a suitable method for intensive blueberry production in the climate investigated here. The modified environmental conditions under the high tunnel have negative effects on blueberry plant and fruit performance, which is reflected in lower plant volume, fruit yield, and phenolics content. From the comparison of the ridge and pot planting systems, we can conclude that 60 L pots more than satisfied the needs of the plants for water uptake and optimal root development and can be a suitable planting system for young plants, as there were no negative effects on plant volume and fruit yield, firmness, color, and chemical composition. Growing the plants under the hail net positively affected plant growth, fruit yield, and phenolics content; however, ripening occurred earlier under the high tunnel. At the same time, higher sugar/organic acid ratios were seen for the 'Brigitta' fruit under the high tunnel. This is the first investigation that has compared highbush blueberry plants grown under a high tunnel and a hail net using ridge and pot planting systems. Despite the promising data, further studies are required, particularly to evaluate the plant volume, fruit yield, and chemical composition over several years using the above-described production technologies.
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Domain: Agricultural and Food Sciences
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Potential for the development of Taraxacum mongolicum aqueous extract as a phytogenic feed additive for poultry
Introduction Taraxacum mongolicum (TM) is a kind of medicinal and edible homologous plant which is included in the catalogue of feed raw materials in China. It is rich in polyphenols, flavonoids, polysaccharides and other active substances, and shows many benefits to livestock, poultry and aquatic products. The study aimed to assess the potential of TM aqueous extract (TMAE) as a substitute for poultry AGPs. Methods A total of 240 one-day-old Arbor Acker broilers were randomly assigned to four groups and fed a basal diet (Con) supplemented with 500, 1000, and 2000 mg/kg TMAE (Low, Medium, and High groups). The growth performance of the broilers was measured on day 21 and day 42. At the end of the trial, the researchers measured slaughter performance and collected serum, liver, spleen, ileum, and intestinal contents to investigate the effects of TMAE on serum biochemistry, antioxidant capacity, immune function, organ coefficient, intestinal morphology, flora composition, and short-chain fatty acids (SCFAs). Results The results showed that broilers treated with TMAE had a significantly higher average daily gain from 22 to 42 days old compared to the Con group. Various doses of TMAE resulted in different levels of improvement in serum chemistry. High doses increased serum alkaline phosphatase and decreased creatinine. TMAE also increased the antioxidant capacity of serum, liver, and ileum in broilers. Additionally, middle and high doses of TMAE enhanced the innate immune function of the liver (IL-10) and ileum (Occludin) in broilers. Compared to the control group, the TMAE treatment group exhibited an increase in the ratio of villi length to villi crypt in the duodenum. TMAE increased the abundance of beneficial bacteria, such as Alistipes and Lactobacillus, while reducing the accumulation of harmful bacteria, such as Colidextracter and Sellimonas. The cecum's SCFAs content increased with a medium dose of TMAE. Supplementing broiler diets with TMAE at varying doses enhanced growth performance and overall health. The most significant benefits were observed at a dose of 1000 mg/kg, including improved serum biochemical parameters, intestinal morphology, antioxidant capacity of the liver and ileum, immune function of the liver and ileum, and increased SCFAs content. Lactobacillus aviarius, norank_f_norank_o__Clostridia_UCG-014, and Flavonifractor are potentially dominant members of the intestinal microflora. Conclusion In conclusion, TMAE is a promising poultry feed additive and 1000 mg/kg is an effective reference dose.
Introduction
For over 60 years, antibiotic growth promoters (AGPs) have been used in livestock and poultry farming to prevent disease, promote growth, and reduce costs (1,2). However, prolonged exposure to sub-therapeutic doses has significantly increased bacterial resistance to antibiotics, leading to pandemics in farmed animals, humans, and the environment. This poses significant obstacles and problems for livestock development and public health (3)(4)(5). In July 2020, China joined the United States, the European Union, and other regions in officially entering the era of feed prohibition (6). Commercial broilers often experience oxidative stress and intestinal flora disorder due to the imbalance between genetic improvement of carcass development and intestinal system development (7). Therefore, low-cost and effective alternatives to AGPs are crucial for the sustainable development of livestock production worldwide. Antibacterial peptides, probiotics, acidifiers, and plant active ingredients have been extensively researched and are considered promising alternatives to AGPs (8)(9)(10)(11). However, the EU's decades of experience in antibiotic-free farming demonstrate that AGPs cannot be replaced by a single product and require a more comprehensive strategy (12-14).
Plant-derived polyphenols and polysaccharides have been shown to provide various benefits to livestock and poultry, including immunomodulation, antioxidant, antibacterial, and anti-inflammatory effects (15)(16)(17)(18). Certain phenolic compounds, such as flavonoids and functional polysaccharides, are not easily broken down and absorbed in the stomach and small intestine. Instead, they can reach the cecum intact and be fermented and utilized by the abundant intestinal microorganisms (19,20). The phenolic compounds break down into smaller molecular weight phenols when absorbed by the body, providing a wide range of antioxidant effects. Additionally, during the decomposition process, they can affect the intestinal flora (21,22). Some microbial species in the gut utilize functional polysaccharides as nutrients and ferment them to produce short-chain fatty acids, which positively impact the intestinal environment and help maintain its health (23,24).
Taraxacum mongolicum (TM) is a perennial herb of the Asteraceae family that is distributed worldwide. It is commonly used in Chinese medicine to clear away heat and toxic materials, reduce swelling and disperse masses, and promote diuresis and treat stranguria. Recent pharmacological studies have demonstrated that it possesses antibacterial, antioxidant, antiviral, liver-protecting, and choleretic effects (25)(26)(27)(28). It is commonly utilized for the prevention and treatment of respiratory and digestive tract ailments (29)(30)(31). TM is used as a vegetable and a substitute for tea in some countries due to its nutritional elements, such as vitamins, amino acids, minerals, and active secondary metabolites, such as polyphenols and sterols (32)(33)(34). In China, TM is also included in the list of feed ingredients. The study demonstrated that adding 500 mg/kg of dandelion powder to the broiler diet improved growth performance by enhancing the intestinal barrier and microbial composition (35). Additionally, Yang et al. (36) discovered that the water-soluble components of dandelion have a superior antioxidant effect and are more costeffective and environmentally friendly as feed additives. However, the impact of TM aqueous extract (TMAE) on growth promotion in broilers and its possible mechanism of action have not been systematically evaluated. The International Symposium on Antibiotic Alternatives, held by the World Organization for Animal Health, emphasized the importance of considering the impact of the product on both the intestinal flora (biological barrier) and the intestinal barrier (physical and chemical barrier) (14). The hypothesis was that TMAE would enhance the antioxidant capacity, gut barrier function, gut microbiota composition, and short-chain fatty acids (SCFAs) in broilers, leading to improved growth performance. Thus, this study aimed to investigate the effects of dietary supplementation with TMAE on the growth performance, antioxidant capacity, intestinal barrier function, and intestinal microflora of broilers.
Preparation of TMAE
The TMAE extract was prepared following the method described by Tan et al. (37). The extraction was carried out at 100 °C, three times for 50 minutes each, with a solid-liquid ratio of 1:8. The resulting filtrate was combined, concentrated, and dried to obtain the TMAE extract. The extract samples were analyzed for their contents of soluble sugars, flavonoids, and total phenols using chemical chromogenic methods, specifically the anthrone-sulfuric acid, alkaline nitrite-aluminum ions, and Folin-Ciocalteu methods. The commercial assay kits used in the analysis were provided by Beijing Boxbio Science & Technology Co., Ltd., China.
UHPLC-Q/TOF-MS analysis
Dissolve 4 mg of TMAE in 1 mL of 80% methanol (Merck) solution. After mixing, centrifuge the solution at 8000 r/min for 10 min and collect the supernatant. The supernatant samples were filtered using nylon membranes (13 mm × 0.22 mm, ANPEL Laboratory Technologies Inc.) and separated on an Agilent 1290 Infinity UHPLC (Agilent Technologies, Santa Clara, CA, USA) in series with an Agilent 6530 Accurate-Mass Q-TOF LC/MS (Agilent Technologies, Santa Clara, CA, USA) system equipped with Agilent Eclipse XDB-C18 (4.6 × 150 mm, 5 mm). The UHPLC-Q/TOF-MS test conditions are based on the method of Pieczykolan, A. et al. (38) with some modifications. The mobile phases used in this experiment were water containing 0.1% formic acid (solvent A) and acetonitrile containing 0.1% formic acid (solvent B). The gradient elution program followed the schedule below: 0-1.5 min, 13% B; 2-15 min, 20% B; 16-23 min, 25% B; 25-28 min, 33% B; 30-33 min, 60% B; 34-37 min, 13% B. The flow rate was 0.35 mL/min, and the column temperature was maintained at 25°C. The negative ion source voltage was set at -4.5 kV, the capillary temperature at 500°C, the spray gas at 55 psi, and the Curtain Gas at 30 psi. The mass-to-charge ratios of primary and secondary fragments of isolated compounds were screened in the MS-DIAL database and literature reports to identify compounds in extracts (39,40).
Birds and experimental design
Prior to the experiment, the breeding ground and utensils were disinfected using formaldehyde fumigation. A total of 240 1-day-old Arbor Acres (AA) white feather broilers were randomly divided into four groups, with six replicates of ten broilers per replicate. The control group (Con) was fed a diet without TMAE, while the TMAE treatment groups were fed a basal diet supplemented with 500, 1000, and 2000 mg/kg TMAE (Low, Medium, and High). The experiment lasted for 42 days. The chickens were raised in 3-layer vertical cages, with 10 chickens in each cage. The temperature in the house was manually controlled at 37-32°C during the first week and decreased by 2°C per week from the second week. The relative humidity was maintained at 55%-70%, and the chickens had access to food and water at all times. Standardized daily management procedures for feeding and epidemic prevention were followed throughout the trial. The basic diet for white feather broilers is prepared using corn, soybean meal, soybean oil, and other raw materials in accordance with the nutritional requirements outlined in the Chicken Feeding Standard (NY/T 33-2004) (41). The feed is in powder form. Table 1 shows the composition and nutritional levels of the basic diet. The study received approval from the Animal Ethics Committee of Hunan Agricultural University (Ethic approval number: CACAHU 20220922-1).
Sample collection
Body weight (BW), average daily gain (ADG), average daily feed intake (ADFI), and feed-to-gain ratio (F/G) were measured for each cage at 21 and 42 days of age. The chickens were fasted overnight but allowed to drink water. On day 42, the chickens were euthanized, and blood was collected using inert separating gel Similarly, the breast muscle percentage (%) can be calculated by dividing the bilateral breast muscle weight by the eviscerated weight and multiplying the result by 100. Finally, the leg muscle percentage (%) can be calculated by dividing the bilateral leg muscle weight by the eviscerated weight and multiplying the result by 100.
Immune function assay
The thymus, spleen, and bursa of Fabricius were weighed, and the immune organ index was calculated using the formula: immune organ index % = 100 × immune organ weight/live body weight. Serum IgG, IgY, IgA, IgM, g-IFN, and IL-10, as well as liver homogenate IgG and IL-10, were detected using a commercial solid-phase sandwich ELISA kit from Shanghai Enzyme-linked Biotechnology Co., Ltd., China. Serum IgG, IgY, IgA, IgM, g-IFN, and IL-10, as well as liver homogenate IgG and IL-10, were detected using a commercial solid-phase sandwich ELISA kit from Shanghai Enzyme-linked Biotechnology Co., Ltd., China. Serum IgG, IgY, IgA, IgM, g-IFN, and IL-10, as well as liver homogenate IgG and IL-10, were detected using a commercial solid-phase sandwich ELISA kit from Shanghai Enzyme-linked Biotechnology Co., Ltd., China. Additionally, lysozyme (LZM) and secretory IgA were measured. The ileum homogenate was analyzed for DEF b 1, Zonula Occluden-1 (ZO-1), Occludin, transferrin (TRF), Claudin-1, mucin 1 (MUC-1), mucin 2 (MUC-2), and transforming growth factor beta (TGF-b). To perform the analysis, 50 mL of either the standard or test sample was mixed with an equal volume of biotinlabeled antibody solution. The mixture was gently shaken and incubated at 37 °C for 45 minutes. Each reaction was thoroughly washed with wash solution, shaking for 30 seconds each time, and this process was repeated 4 times. To each well, add 100 mL of Horseradish Peroxidase-Streptavidin, shake well, and incubate at 37 °C for 30 minutes. After washing the reaction wells four times, add the substrate and let it react for five minutes in the dark. To terminate the reaction, add 50 mL of stop solution and measure the optical density (OD) value of each well at a wavelength of 450 nm.
Histological observation of intestinal tract
The tissues from the duodenum, jejunum, and ileum were fixed in formalin for 48 hours, rinsed with running tap water for 8 hours, dehydrated in a series of graded alcohol concentrations (70%, 80%, 90%, 95%, and 100%), transferred to xylene to make them transparent, and embedded in paraffin for pathology. The resulting paraffin blocks were cut into 6 mm sections using a microtome, stained with hematoxylin and eosin, and observed under a microscope. The study measured the length of the villi and the depth of the crypt using Olympus OlyVIA Image Viewer measurement tools (OLYMPUS Corporation, Tokyo, Japan). The length of the villi was defined as the vertical distance from the tip of the villi to the opening of the crypt, while the depth of the crypt was defined as the vertical distance from the opening of the crypt to its base.
Determination of SCFAs content
SCFAs in cecal contents were determined using the modified method of Zhang et al. (45). A 1 g sample of cecal content was weighed and mixed with 5 mL of ultrapure water for 30 min. The mixture was then centrifuged at 10000 rpm for 10 min after being left overnight at 4°C. The supernatant was transferred to a new container, and 4 mL of ultrapure water was added to the precipitate. The mixture was shaken and mixed for 30 min, then centrifuged again, and the supernatant was combined. The resulting supernatant was mixed with 25% metaphosphoric acid (v:v=9:1) to determine SCFAs. The sample was passed through a 45 mm microporous membrane and then analyzed for SCFAs, including acetic acid (aa), propionic acid (pa), isobutyric acid (iba), butyric acid (ba), isovaleric acid (iva), and valeric acid (va), using a SHIMADZU GC-2010plus gas chromatograph (SHIMADZU Corporation, Kyoto, Japan) equipped with a DB-FFAP column (0. 25 mm × 30 m × 250 mm) (Agilent Technologies Inc., Santa Clara, USA). Chromatographic conditions were as follows: The sample was heated to 70°C for 3 minutes and then programmed to reach 210°C at a rate of 5°C/min and held for 10 minutes. The vaporization chamber temperature was set to 230°C and the FID detector temperature was set to 280°C. High purity nitrogen (purity ≥ 99.999%) was used as the carrier gas with a flow rate of 1 mL/min. The injection volume was 2.0 mL with a split ratio of 50:1.
16S rRNA sequencing of intestinal microbes
The small intestine samples were prepared by mixing equal amounts of duodenum, jejunum, and ileum contents. The quality of the extracted DNA was tested using 1% agarose gel electrophoresis and the DNA concentration and purity were determined using a BioPhotometer D30 (Eppendorf, Hamburg, Germany), following the TIANamp Stool DNA Kit (TIANGEN BIOTECH (BEIJING) CO., LTD.) protocol from Beijing, China. The 16S rDNA's V4-V16 region was am pli fi ed through PCR using 338F (5' - The PCR products of each sample were mixed and recovered through 2% agarose gel. The products were then purified using the TIANgel Purification Kit and TIANquick Midi Purification Kit (TIANGEN BIOTECH (BEIJING) CO., LTD.), Beijing, China. The purified products were detected through 2% agarose gel electrophoresis and quantified using the Quantus ™ Fluorometer (Promega, USA). The TIANSeq DirectFast Library Kit (TIANGEN BIOTECH (BEIJING) CO., LTD., Beijing, China) was used to prepare the samples. Sequencing was performed by Shanghai Majorbio Biopharm Technology Co., Ltd.(Shanghai, China) using Illumina's MiseqPE300 platform.
Fastp (v 0.19.6) was used for quality control of raw sequencing sequences, while splicing was performed using Flash (v 1.2.11). Sequences were clustered into OTUs using Uparse (v 11) with a similarity threshold of 97%, and mosaics were rejected. The OTU representative sequences were annotated using the RDP Classifier (v 2.13) based on the silva138/16s_bacteria taxonomic database, with a confidence threshold of 0.7 for taxonomic annotation results. The results were analyzed using Majorbio Cloud Platform ( [URL]:// cloud.majorbio.com). The analysis included dilution curve analysis, alpha diversity analysis (Shannon index and Simpson index), species composition analysis (community composition analysis Bar plot), beta diversity analysis (principal co-ordinates analysis, PCoA), and species difference analysis (Kruskal-Wallis test, Kruskal-Wallis H test, and LDA discriminant results table).
Data analysis
Duncan's multiple comparison test was used to analyze the results of growth performance, slaughter performance, serum biochemistry, antioxidant capacity, immune function, intestinal morphology, and SCFAs using IBM SPSS Statistics 26.0 (IBM Corporation, Armonk, USA). A significance level of P<0.05 was considered statistically significant. The data is presented as mean ± pooled SEM. The analytical plots for gut microbiota were generated using the R package. GraphPad Prism 8.0.2 (GraphPad Software, San Diego, USA) was used to generate line graphs displaying TMAE in vitro antioxidant results.
Active ingredient content and composition of TMAE
The chemical chromogenic method was used to determine the content of active substances in TMAE. The TMAE extract had a yield of 39.28%. The total phenols content was 0.64%, the flavonoids content was 3.22%, and the soluble sugar content was 19.03%.
Growth performance
Table 2 shows the results of the effect of adding TMAE to the diet on the growth performance of broilers. At 21 days of age, the BW of broilers in the Con group was significantly higher than that in the TMAE groups (P<0.05). However, at 42 days of age, the BW of broilers in the TMAE groups was significantly higher than that in the Con group (P<0.05). The low-dose group showed the most significant weight gain. From 1 to 21 days of age, the average daily gain (ADG) of broilers in the Con group was significantly higher than that in the TMAE group (P<0.05). Conversely, from 22 to 42 days of age, the ADG of broilers in the TMAE group was significantly higher than that in the Con group (P<0.05).
Slaughter performance
Table 3 shows the results of the effect of TMAE on the slaughter performance of broilers. The slaughter performance of the TMAE groups was not significantly different from that of the Con group.
Serum biochemistry
The results of the effect of TMAE supplementation in the diet on serum biochemistry of broilers are shown in Table 4. The results showed that ALP in High group was significantly higher than that in Con group (P<0.05). BUN was significantly increased in Medium group (P<0.05). TG was significantly lower in Low group (P<0.05). HDL in Medium group was significantly higher than that in control group (P<0.05). The serum CRE in High group was significantly lower than that in control group (P<0.05). There was no significant effect on other indexes.
Antioxidant capacity
The in vitro total antioxidant capacity of TMAE was determined by measuring its ABTS free radical scavenging capacity and iron ion reducing antioxidant capacity. The study found that the free clearance capacity of ABTS reached its maximum at a concentration of 1.5 mg/mL of TMAE, resulting in a Trolox-Equivalent Antioxidant Capacity (TEAC) of 1.54 mM Trolox/1.5 mg/mL (Figure 1A). Additionally, the antioxidant capacity of TMAE increased with concentration in the tested range for the FRAP test, but the upward trend stabilized after reaching 2 mg/kg. The FRAP assay revealed a maximum antioxidant capacity of approximately 1.02 mM FeSO4/2 mg/mL (Figure 1B). The TMAE groups exhibited significantly higher serum total antioxidant capacity and CAT activity compared to the Con group (P<0.05).
Additionally, the liver in the Low group showed significantly higher ABTS free radical scavenging ability than the control group (P<0.05). The liver's total antioxidant capacity (FRAP) significantly increased (P<0.05) in the TMAE treatment group, while the content of MDA significantly decreased (P<0.05). The activity of CAT in the liver of broilers in the Medium group also significantly increased (P<0.05). Additionally, GSH-Px activities in the liver and ileum of broilers in the High group significantly increased (P<0.05)(Table 5).
Immune function
The study results suggest that dietary supplementation with TMAE did not significantly affect immune organ indices in broilers (refer to Table 6). Furthermore, the ELISA test results of serum, liver, and ileum tissue samples (refer to Table 7) showed that TMAE treatment did not significantly affect serum immune indexes of broilers. However, the medium and high doses of TMAE significantly increased IL-10 content in the liver and Occludin content in the ileum (P<0.05). The group with higher levels also showed a significant increase in the expression of LZM, sIgA, TRF, ZO-1, and DEF b1 in the ileum (P<0.05).
Histological morphology of small intestine
Table 8 shows the effect of TMAE supplementation on small bowel morphology. Compared to the Con group, the Low, Medium, and High groups had significantly increased villus length and villus-to-crypt ratio in the duodenum (P<0.05). Additionally, the Low group had significantly increased villus length and villus-to-crypt ratio in the ileum (P<0.05).
SCFAs
Table 9 displays the SCFAs content in the cecal contents of broilers. The content of aa and ba in the cecal contents was significantly increased in the Medium group (1000 mg/kg) with the addition of TMAE compared to the Con group (P<0.05).3.9 Gut microbiota composition
Microbiological analysis of small intestine
The results of the a diversity analysis (Figures 2A, B) indicate that at the OUT level, the Shannon index of microorganisms in the small intestine of the Con group was significantly higher than that of the TMAE treatment groups (P<0.05). Additionally, the Simpson index was significantly lower in the Con group compared to the TMAE treatment group (P<0.05). To analyze the effect of dietary TMAE supplementation on microbial community composition, we analyzed the microbial community of each dose group at the phylum, genus, and species levels. Firmicutes was the dominant phylum in all small intestine samples, accounting for over 99% (Figure 2C). At the genus level, the intestinal flora was relatively simple, with Lactobacillus being the main genus, accounting for over 98% (Figure 2D). At the species level, it was observed that Lactobacillus aviarius was gradually enriched in the small intestine with the addition of TMAE (Figure 2E). Cluster analysis of the population was performed using PCoA (Figure 2F), which showed that dietary TMAE supplementation did not have a significant effect on the microbial composition of the small intestine at the genus level or higher.
Microbiological analysis of cecum
The a diversity of the cecal microbiota was not significantly affected (P>0.05) by the addition of TMAE to the diet (Figures 3A, B). The dominant flora in the cecum consisted mainly of Firmicutes and Bacteroidetes, which accounted for more than 97% of the total. The proportion of Bacteroidetes increased in the low and medium dose groups of TMAE compared to the Con group (Figure 3D). The cecal flora is primarily composed of Alistipes, norank_f:norank_o: Clostridia_UCG-014, Lactobacillus, norank_o:Clostridia_vadin BB60_group, Faecalibacterium, Ruminococcus_torques_group, unclassified_f_Lachnospiraceae, UCG-005, Christensenellaceae_R-7_group, and Romboutsia (Figure 3E). The species-level composition is generally consistent with that of the genus level (Figure 3F). PCoA analysis revealed that the cecal microbiota of the Con and TMAE treated groups formed two distinct clusters (Figure 3C), indicating significant differences in microbial communities. This suggests that dietary supplementation with TMAE had varying effects on the cecal microflora. The Kruskal-Wallis H test (Figure 3G) was used to explore the flora that differed significantly between the different groups at the genus level. The relative abundance of norank_f:norank_o:Clostridia_UCG-014 and norank_f:UCG-010 was found to be significantly increased (P<0.05) using the Kruskal-Wallis H test and LEfSe Multi-level Species Difference Discriminant Analysis (LDA Linear Discriminant). The abundance of Butyricicoccus, Colidextrebacter, Sellimonas, and Fournierella was significantly decreased (P<0.05) in the TMAEtreated group compared to the control group. Parabacteroides showed significant decreases and increases in the low and medium dose groups (P<0.01),but not in the high dose group (Figure 3H). Flavonifractor increased significantly in the medium dose group (P<0.05).
Correlation analysis between cecal microorganisms and SCFAs
Spearman correlation analysis was conducted at the genus level and a heat map was generated for the cecal microbes and SCFAs in the cecum, including aa, pa, iba, ba, iva, va (Figure 4). The abundance of norank_f_norank_o_Clostridia_UCG-014 was significantly and negatively correlated with the contents of all SCFAs (P<0.05). Additionally, the abundance of Sellimonas was significantly and positively correlated with the contents of aa and ba (P<0.05), while the abundance of Flavonifactor and Colidextribacter was significantly and positively correlated with the contents of aa, pa and ba (P<0.05). The study found significant positive correlation between the abundance of Parabacteroides and the content of pa (P <0.05), and significant negative correlation between the abundance of norank_f_norank_o_Clostridia_vadini BB60_group and the content of iva (P<0.05). Additionally, other microorganisms were found to be significantly correlated with SCFAs content at the community level.
Discussion
Although the use of APGs has significant beneficial effects on growth performance and disease prevention in farmed animals, their use is partially restricted and prohibited worldwide due to the increasing problem of bacterial resistance. Studies have reported the beneficial effects of plant polyphenols, flavonoids and polysaccharides on livestock and poultry breeding have been studied and reported (46)(47)(48). The results showed that TMAE supplementation could increase the daily gain, improve the serum chemical index, enhance the antioxidant capacity of serum, liver and ileum, enhance the immune function of liver and intestine, and then improve the growth performance of broilers. It indicated that the growth promotion effect of TMAE on broilers was related to a wide range of biological effects. We found that TMAE supplementation had a negative effect on broiler weight gain compared to Con at 1 -21 days of age. We hypothesized that certain components of TMAE inhibit digestive enzyme activity, which can lead to reduced nutrient uptake in broilers. Digestive enzymes play a crucial role in mediating and limiting energy and nutrient uptake in birds (49). Research has demonstrated that phenolic compounds, including kaempferol and luteolin derivatives, found in dandelion can hinder pancreatic lipase activity (50). Furthermore, dandelion polysaccharides exhibit significant activity in inhibiting a-amylase and a-glucosidase (51). Broiler gut digestion is not optimal in the early stages of growth. Bacteroides, which are responsible for digesting complex carbohydrates in the caecum, begin to proliferate at 14 days (52).
During prophase, broilers experienced weight gain inhibition due to their inability to fully digest and utilize polysaccharides in TMAE.
The study found that dietary supplementation with TMAE led to an increase in daily weight gain during the 22 -42 day period. This is a critical stage where productivity increases significantly, resulting in a terminal body weight that exceeds the Con group. The limited energy of TMAE may be the reason for its effect on broilers in the early stages of production. However, the cecal flora in the later stages is capable of fermenting polysaccharides into low molecular weight organic matter that can be utilized. As a result, broilers overcome the energy limitation and exhibit compensatory growth response (53). Broilers consume excessive amounts of energy to maintain compensatory growth. This explains their increased feed intake. In addition, TMAE contains soluble carbohydrates, L-malic acid and 1,3-Dihydroxyacetone dimer, etc., which have obvious sweet smell, improve feed palatability and stimulate appetite of broilers (30,(54)(55)(56). The results of serum biochemistry showed that the ALP content of High group was significantly increased (P<0.05).
During bone growth and development, bone cells became active and produced a large number of ALP into the blood, promoting bone growth and development (57, 58). At this dose, TMAE also reduced CRE in broiler serum (P<0.05) and increased BUN at Medium dose, but the study showed that except UA, other biochemical indicators reflecting renal function lacked specificity in the assessment of renal health in birds, which was closely related to the special physiological system of birds (59). Medium treatment also significantly increased the level of HDL (P<0.05), and enhanced the conversion of cholesterol to bile acids in liver, which increased the oxidative utilization of fatty acids in muscle tissue and improved growth performance (60,61). The level of TG in serum can reflect the ability of lipid metabolism of broilers. The study found that Low dose TMAE can significantly reduce the level of TG in serum of broilers. TM polysaccharide may contribute to improving the ability of lipid metabolism of broilers (62).
Long-term intake of high-energy-density feed during breeding will cause peroxidation in livestock and poultry (blood and tissues), and then affect the occurrence and process of inflammation (63)(64)(65). Exogenous antioxidant supplementation in the right amount can enhance the capacity of the antioxidant system in vivo, on the contrary, excessive antioxidants can also disrupt homeostasis (66, 67). TMAE has been identified in a large number of polyphenols (including flavonoids) and polysaccharides (68), compared with other extracts with stronger antioxidant capacity and extraction solvent is more economical and environmentally friendly (36). The polyphenols of TM have also been shown to have good antiinflammatory activity (69). The antioxidant activity of TMAE in vitro was also confirmed in this study. In vivo test results showed that TMAE could significantly increase serum T-AOC and CAT Heatmap of correlation analysis between cecal microorganisms and SCFAs. Statistical differences were recorded as P<0.05 (*), P<0.01 (**) and P<0.001 (***), respectively.content, and significantly reduce MDA content in broilers. Medium and/or High dose could significantly increase the activities of CAT and GSH-Px in liver and ileum. The antioxidant potential of TM is also partially supported by the studies of Zhao et al. and Du et al. (70,71)., whose results show that TM polysaccharide and flavonoid extracts can improve the defense capacity of antioxidant system in vivo, including the effects on CAT, SOD, T-AOC, etc. Due to the absorption properties of polyphenols (flavonoids) and polysaccharides, we focused on the effects of TMAE on the circulatory, hepatic and intestinal innate immune systems. IL-10 has extensive inflammatory and immunosuppressive properties and plays an important role in maintaining innate immunity and inflammatory homeostasis in vivo (72, 73). The intestine is the largest immune organ in chicken, and the immune lymphocytes are the densest in the ileum. At the same time, studies have shown that bile acids play an important role in mucosal immune regulation, and bile acids are mainly absorbed in the ileum (74,75), so this study focused on the mucosal innate immunity of the ileum. Intestinal epithelial cells and mucosa, as the first physical barrier against external factors, are important components of ileal immunity, while Occludin and ZO-1 are essential to maintain the integrity of intestinal mucosal barrier (76). Meanwhile, intestinal antimicrobial effectors TRF, LZM and DEF b1 are important components of intestinal chemical barrier, which can prevent the infection of pathogenic microorganisms (77)(78)(79).sIgA, as the major immunoglobulin in intestinal mucosa, can mediate mucosal immune defense against various endogenous and exogenous pathogens (80). In this study, we found that high dose of TMAE can significantly increase the expression of LZM, Occludin, sIgA, TRF, ZO-1, DEF b1 and other immune indicators in the ileum of broilers, significantly improve the physical and chemical barrier defense effect of ileum mucosa, and enhance the intestinal innate immune function of broilers. Mao et al. also found that TM powder could increase the gene expression level of ZO-1 (35). In addition, the histological observation of intestinal morphology showed that low dose of TMAE could effectively increase the villus height and villus/crypt ratio of duodenum and ileum of broilers, and enhance the absorption capacity of broiler intestine, which confirmed the results of growth performance test of broilers.
Intestinal symbiotic flora can ferment and decompose nutrients for absorption and utilization by the body, and also exist as a biological barrier of intestinal innate immunity, maintaining host immune homeostasis through competition (81, 82). Dietary supplementation with different doses of TMAE had different beneficial effects on broilers, and we evaluated the intervention and regulation of different doses of TMAE on intestinal microflora. The results of alpha diversity analysis based on OUT showed that TMAE supplementation significantly reduced the diversity of broiler intestinal microbiota, but beta diversity analysis and microbiota composition analysis showed that TMAE did not change the composition of intestinal microbiota. We also found that Lactobacillus aviarius was gradually enriched with the increase of TMAE addition. Lactobacillus aviarius is one of the most common lactobacilli in poultry intestine (83), which can improve intestinal immunity (84). The glucanotransferase secreted by Lactobacillus aviarius also has the ability to digest and decompose starch to produce linear a-glucan products (soluble dietary fiber), and can also improve feed utilization rate and promote growth (85,86). The increase of relative abundance of Lactobacillus aviarius may be one of the important reasons why TMAE affects the immune and growth performance of ileum TMAE could increase the relative abundance of Bacteroidetes in caecum. Studies have shown that Bacteroidetes has the ability to rapidly degrade polysaccharides, and can encode a variety of enzymes, such as polysaccharide lyases and glycosidases, to hydrolyze polysaccharides that are difficult to digest to provide energy for the body (87, 88). The results indicated that the polysaccharides in TMAE could affect the composition of intestinal flora in cecum of broilers and increase the relative abundance of Bacteroides. At the genus level, TMAE increased the abundance of Alistipes and Lactobacillus, and the abundance of Alistipes was closely related to body weight, energy metabolism and fat deposition in broilers (89-91). Alistipes are involved in the metabolism of SCFAs, and high fat animal diets can increase the relative abundance of the genus, thereby improving lipid metabolism by modulating acetate production (92). In addition, Alistipes also had a positive effect on bone development (93), which was consistent with the results of this study that TMAE increased serum alkaline phosphatase content and promoted bone development in broilers. Alistipes are also associated with immune regulation and health homeostasis and are considered potentially beneficial bacteria (94). Lactobacillus is ubiquitous in the intestinal tract of animals. It can improve the health of animals by inhibiting bacteria, improving the ecological environment of intestinal microorganisms, strengthening the barrier layer of intestinal epithelial cells and improving the immune function of animals (95,96). Studies have shown that the prebiotic properties of polyphenols and polysaccharides can increase the abundance of probiotics such as Lactobacillus and Bifidobacterium. Clostridia, the most significant differential microbiota produced by TMAE supplementation, not only helps digest food, strengthens the intestinal mucosal barrier, but also provides infection resistance (97,98). The addition of TMAE could increase the proportion of beneficial bacteria in the cecum of broilers, and reduce the proportion of harmful bacteria such as Colidotribacter and Sellimonas related to intestinal inflammation (99,100).
SCFAs are secondary products produced by fermentation of carbohydrates by cecal microorganisms, which can provide necessary energy for host metabolism, improve digestive enzyme activity, inhibit the growth of pathogenic bacteria, and stimulate immune system (101, 102), and play an extremely important role in maintaining intestinal health and function. Aa has the function of regulating intestinal pH and promoting the production of ba, which can promote the regeneration and differentiation of intestinal epithelial cells and improve intestinal morphology (103,104). The results of this study showed that medium dose of TMAE could significantly increase the content of aa and ba in the cecum of broilers. Correlation heat maps showed that the abundance of Flavonifractor was significantly positively correlated with aa and ba content, and it was mainly enriched in the cecal samples of the middle dose group of TMAE.norank_f:norank_o:Clostridia_UCG-014 was the most abundant in the high dose group and was significantly negatively correlated with all SCFAs, and the content of all SCFAs in the high dose group decreased, which was also consistent with the results. It has been reported that when the host is in immune activation state, intestinal commensal bacteria can change intestinal metabolism, reduce SCFAs and increase the concentration of aromatic metabolites (105). Therefore, it can be speculated that Clostridia plays an important role in the activation of ileal innate immunity exhibited after high dose TMAE supplementation. In conclusion, dietary supplementation of TMAE in broilers showed varying degrees of health benefits (improvements in serum biochemistry, antioxidant capacity, immune function, and intestinal morphology) and improved growth performance. These effects may be related to the regulation of intestinal microbiota and SCFAs by TMAE, and it is considered that TMAE may be a potential poultry feed additive capable of replacing APGs. Dietary addition of TMAE at 1000 mg/ kg may have a broader beneficial biological effect.
Conclusions
Supplementing broiler diets with TMAE at varying doses was found to enhance growth performance and overall health. The most significant benefits were observed at a dose of 1000 mg/kg, including improved serum biochemical parameters, intestinal morphology, antioxidant capacity of the liver and ileum, immune function of the liver and ileum, and increased SCFAs content. Lactobacillus aviarius, norank_f_norank_o:Clostridia_UCG-014, and Flavonifractor may have a dominant role in the microflora of the intestine and cecum.
1
FIGURE 1Total antioxidant capacity results for TMAE.(A) ABTS free radical scavenging ability; (B) Iron ion reduction antioxidant capacity. Data in the same row with no or same superscript letters indicate non-significant differences (P > 0.05), and different letters indicate significant differences (P < 0.05).
2
FIGURE 2 Effect of TMAE supplementation on small intestinal microflora of broilers.(A, B) Effect of TMAE on intestinal microbial alpha diversity (Shannon and Simpson index); (C-E) Colony composition of small intestinal microorganisms at phylum, genus and species levels after TMAE addition; (F) Intestinal microbial beta diversity analysis.
3
FIGURE 3 Effect of TMAE supplementation on cecal microorganism of broilers.(A, B) Effect of TMAE on Cecal Microbial Alpha Diversity (Shannon and Simpson index); (C) Cecal microbial beta diversity analysis; (D-F) Colony composition of cecal microorganisms at phylum, genus and species levels after TMAE addition; (G) Differentiation of enterobacteria at the genus level using the Kruskal-Wallis H test; (H) Effect of TMAE on Linear Discriminant Analysis Effect Size (LEfSe).
FIGURE 4
FIGURE 4 The dried whole herb Taraxacum mongolicum Hand.-Mazz was purchased from Bozhou Medicinal Materials Market, Anhui Province and identified by Professor Yang Guangmin of Hunan University of Traditional Chinese Medicine. The samples are stored in Hunan Province Key Laboratory of Traditional Chinese Veterinary Medicine, Hunan Agricultural University.
TABLE 1
Basic diet composition and nutrition level (air-dried basis).
TABLE 3
Effect of TMAE on slaughter performance of broilers (n=12).
Data in the same row with no or same superscript letters indicate non-significant differences (P > 0.05), and different letters indicate significant differences (P < 0.05).
TABLE 2
Effects of dandelion aqueous extract on production performance of broilers (n=12).
TABLE 4
Effect of TMAE on serum biochemistry of broilers (n=12).
TABLE 5
Effect of TMAE on antioxidant ability of broilers (n=12).
Data in the same row with no or same superscript letters indicate non-significant differences (P > 0.05), and different letters indicate significant differences (P < 0.05).
TABLE 6
Effect of TMAE on immune organ index of broilers (n=12).
Data in the same row with no or same superscript letters indicate non-significant differences (P > 0.05), and different letters indicate significant differences (P < 0.05).
TABLE 7
Effect of TMAE on immune function of serum, liver and ileum of broilers.
Data in the same row with no or same superscript letters indicate non-significant differences (P > 0.05), and different letters indicate significant differences (P < 0.05).
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Domain: Agricultural and Food Sciences
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Coconut (Cocos nucifera (L.)) Water Improves Glucose Uptake with Concomitant Modulation of Antioxidant and Purinergic Activities in Isolated Rat Psoas Muscles
The present study investigated the effect of coconut water on glucose uptake and utilization, and metabolic activities linked to hyperglycemia in isolated rat psoas muscles. Coconut water was subjected to in vitro antioxidant and antidiabetic assays, which cover 2,2′-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity, ferric reducing antioxidant power (FRAP), and inhibition of α-glucosidase and α-amylase activities. Psoas muscles were isolated from male Sprague Dawley rats and incubated with coconut water in the presence of glucose. Control consisted of muscles incubated with glucose only, while normal control consisted of muscles not incubated in coconut water and/or glucose. The standard antidiabetic drug was metformin. Incubation with coconut water led to a significant increase in muscle glucose uptake, with concomitant exacerbation of glutathione level, and SOD and catalase activities, while suppressing malondialdehyde level, and ATPase and E-NTDase activities. Coconut water showed significant scavenging activity against DPPH, and significantly inhibited α-glucosidase and α-amylase activities. LC-MS analysis of coconut water revealed the presence of ellagic acid, butin, quercetin, protocatechuic acid, baicalin, and silibinin. Molecular docking analysis revealed potent molecular interactions between the LC-MS-identified compounds, and AKT-2 serine and PI-3 kinase. These results indicate the potential of coconut water to enhance glucose uptake, while concomitantly improving antioxidative and purinergic activities. They also indicate the potential of coconut water to suppress postprandial hyperglycemia. These activities may be attributed to the synergistic effects of the LC-MS-identified compounds.
Introduction
Type 2 diabetes (T2D) ranks among the most prevalent type of diabetes mellitus (DM) as it accounts for over 90% of all diabetes types, and is thus a major contributor to DMrelated morbidities and mortalities [1]. It is characterized by hyperglycemia arising from insulin resistance and pancreatic β-cell dysfunction. Persistent hyperglycemia has been linked to increased production of free radicals and reactive oxygen species (ROS), which surpasses the body's antioxidant defense system, leading to oxidative stress [2,3].
Skeletal muscles play a major role in glucose metabolism and insulin function, as over 80% of the postprandial circulatory glucose uptake is attributed to them [4,5]. Desensitization of skeletal muscles to insulin secreted by the pancreas to stimulate glucose uptake results in insulin resistance and hyperglycemia [4]. Impaired muscle glucose uptake has been associated with a metabolic switch to free fatty acid (FFA) oxidation for energy generation, with concomitant generation of oxidative stress, thus further contributing to suppressed insulin sensitivity [6,7].
Impaired muscle glucose uptake has been implicated in the pathophysiology of T2D, and is a major therapeutic target in the treatment of T2D. Some antidiabetic drugs such as the biguanides (e.g., metformin) improve glucose homeostasis by stimulating muscle glucose uptake, while concomitantly suppressing FFA oxidation and oxidative stress [8,9]. However, the cost and side effects associated with synthesized drugs have led to the continuous search for affordable alternatives with fewer side effects. These searches have led to a paradigm shift to natural products, which are readily affordable with fewer side effects.
Coconut water is a natural beverage found in the endosperm of coconut palm, Cocos nucifera, from the family of Arecaceae (Palmae). Coconut water is regarded as a functional food and/or nutraceutical with reported nutritional and medicinal properties. Its reported medicinal properties include antilipemic, hepatoprotective cardioprotective, and antihypertensive activities [10]. Its antidiabetic properties have been well reported and have been attributed to its ability to suppress blood glucose level, improve glucose tolerance, and restore pancreatic morphology [11,12]. Its ability to protect against diabetic retinopathy has been attributed to its modulation of antioxidant and anti-inflammatory activities and improvement in total retina thickness and thickness of the retinal nuclear layer, while increasing the number of neurons in the ganglion cell layer [13]. Coconut water has also been reported for its ability to improve insulin synthesis, decrease glycosylated hemoglobin levels, improve weight gain, and modulate the L-arginine-nitric oxide pathway in diabetic rats [14,15]. These activities have been attributed to the phytochemical properties of coconut water, which include flavonoids, phytates, oxalates, and alkaloids [16].
Although the hypoglycemic activities of coconut water have been reported, there is still a dearth of scientific reports on the ability of coconut water to stimulate skeletal muscle glucose uptake and utilization, and modulate activities linked to hyperglycemia. Thus, the present study was aimed at investigating the effect of coconut water on glucose uptake and utilization, and metabolic activities linked to hyperglycemia in isolated rat psoas muscles.
Results
As shown in Figure 1A, coconut water significantly (p < 0.05) scavenged DPPH radical, with an IC 50 value of 34.09 µg/mL (Table 1). Coconut water also displayed a reducing power activity, as depicted by its ability to reduce Fe 3+ to Fe 2+ (Figure 1B). However, the activity was not potent, as depicted by its IC 50 value of >1000 µg/mL (Table 1). As shown in Figure 2A,B, coconut water significantly (p < 0.05) inhibited the activities of α-glucosidase and α-amylase, with IC 50 values of 338.27 and 219.73 µg/mL, respectively (Table 1). These activities were not dose dependent.
Incubation of psoas muscle with coconut water in the presence of glucose led to significant (p < 0.05) glucose uptake, as shown in Figure 3. The activity was dose dependent with increasing concentrations, and compared favorably to the standard drug, metformin. As shown in Figure 2A,B, coconut water significantly (p < 0.05) inhibited the activities of α-glucosidase and α-amylase, with IC50 values of 338.27 and 219.73 µg/mL, respectively (Table 1). These activities were not dose dependent. Incubation of psoas muscles in glucose led to significant (p < 0.05) depletion in GSH level, and SOD and catalase activities, while concomitantly elevating MDA level, as shown in Figure 4A-D, respectively. These levels and activities were significantly reversed in muscles incubated with coconut water, as depicted by elevated GSH level and SOD and catalase activities, and decreased MDA level. These activities were dose dependent and compared favorably with metformin.
There was an increase in the activities of ATPase and E-NTPDase in psoas muscles incubated in glucose, as depicted in Figure 5A,B, respectively. These activities were significantly (p < 0.05) and dose-dependently reversed in muscles incubated with coconut water.
LC-MS analysis of coconut water revealed the presence of phenolic compounds, which are ellagic acid, butin, quercetin, protocatechuic acid, baicalin, and silibinin, as shown in Figure 6.
Molecular docking analyses revealed potent molecular interactions of the identified compounds with AKT-2 serine (3DOE) and PI-3 kinase (7JWZ), as depicted by their free energies (Table 2). The highest binding affinities were observed for ellagic acid with AKT-2 serine (Figure 7), and silibinin with PI-3 kinase (Figure 8), with free energies of −8.99 and −9.03 kcal/mol, respectively. Incubation of psoas muscle with coconut water in the presence of glucose led to significant (p < 0.05) glucose uptake, as shown in Figure 3. The activity was dose dependent with increasing concentrations, and compared favorably to the standard drug, metformin. Incubation of psoas muscles in glucose led to significant (p < 0.05) depletion in GSH level, and SOD and catalase activities, while concomitantly elevating MDA level, as shown in Figure 4A-D, respectively. These levels and activities were significantly reversed in muscles incubated with coconut water, as depicted by elevated GSH level and SOD and catalase activities, and decreased MDA level. These activities were dose dependent and Incubation of psoas muscles in glucose led to significant (p < 0.05) depletion in GSH level, and SOD and catalase activities, while concomitantly elevating MDA level, as shown in Figure 4A-D, respectively. These levels and activities were significantly reversed in muscles incubated with coconut water, as depicted by elevated GSH level and SOD and catalase activities, and decreased MDA level. These activities were dose dependent and compared favorably with metformin. There was an increase in the activities of ATPase and E-NTPDase in psoas muscles incubated in glucose, as depicted in Figure 5A,B, respectively. These activities were significantly (p < 0.05) and dose-dependently reversed in muscles incubated with coconut water. LC-MS analysis of coconut water revealed the presence of phenolic compounds, which are ellagic acid, butin, quercetin, protocatechuic acid, baicalin, and silibinin, as shown in Figure 6. Molecular docking analyses revealed potent molecular interactions of the identified compounds with AKT-2 serine (3DOE) and PI-3 kinase (7JWZ), as depicted by their free energies (Table 2). The highest binding affinities were observed for ellagic acid with AKT-2 serine (Figure 7), and silibinin with PI-3 kinase (Figure 8), with free energies of −8.99 and Molecular docking analyses revealed potent molecular interactions of the identified compounds with AKT-2 serine (3DOE) and PI-3 kinase (7JWZ), as depicted by their free energies (Table 2). The highest binding affinities were observed for ellagic acid with AKT-2 serine (Figure 7), and silibinin with PI-3 kinase (Figure 8), with free energies of −8.99 and −9.03 kcal/mol, respectively.
Discussion
The continuous search for affordable treatments for T2D has led to an increasing interest in natural products from medicinal plants. Medicinal plants have been used from time immemorial to treat several diseases including T2D and form major part of the traditional medicine system [17,18]. Although the hypoglycemic properties of these plants have been demonstrated, there still remains a dearth of data on the mechanism by which they bring about this effect. In the present study, we investigated the antidiabetic properties of coconut water by investigating its potential to stimulate glucose uptake and
Discussion
The continuous search for affordable treatments for T2D has led to an increasing interest in natural products from medicinal plants. Medicinal plants have been used from time immemorial to treat several diseases including T2D and form major part of the traditional medicine system [17,18]. Although the hypoglycemic properties of these plants have been demonstrated, there still remains a dearth of data on the mechanism by which they bring about this effect. In the present study, we investigated the antidiabetic properties of coconut water by investigating its potential to stimulate glucose uptake and modulate activities linked to glucose homeostasis in isolated psoas muscles, as well as inhibit key enzymes linked to glucose digestion.
The inhibition of glucose-metabolizing enzymes has been reported as one of the major antidiabetic mechanisms [19]. These enzymes catalyze the hydrolysis of dietary carbohy-Plants 2024, 13, 665 9 of 16 drate to glucose, leading to a postprandial rise in blood glucose level. Thus, the inhibition of α-glucosidase and α-amylase activities by coconut water (Figure 2A,B, and Table 1) indicates a suppressive potential against postprandial hyperglycemia. Previous reports on the inhibitory effect of coconut water on these enzymes related to its extracted polysaccharides [20]. Results from the present study corroborate several reports about the inhibitory effect of plants and their phytochemicals on glucose-metabolizing enzymes [21][22][23].
Muscle glucose uptake has also been reported as a major mechanism of maintaining postprandial glucose homeostasis. In the fed state, the pancreas secretes insulin which stimulates muscle glucose uptake, which the muscles utilize as fuel substrate for energy generation [24,25]. Impairment of muscle glucose uptake arising from insulin resistance has been reported as a part of the pathophysiology of T2D, as it contributes to hyperglycemia [26]. The increased glucose uptake in psoas muscles incubated with coconut water (Figure 3) therefore indicates a glucose uptake stimulatory effect. It further suggests the ability of coconut water to suppress postprandial hyperglycemia, and thus maintain glucose homeostasis. This activity may contribute to the reported hypoglycemic properties of coconut water in diabetic rats [14,15,27].
Exacerbated muscle oxidative stress has been linked to impaired muscle glucose uptake and has been attributed to increased generation of free radicals and ROS, which suppresses the endogenous antioxidant defense system [28,29]. This corroborates with the suppressed GSH level and SOD and catalase activities, and elevated MDA level in psoas muscle incubated in only glucose (control) (Figure 4A-D). Similar activities and levels have been reported in impaired glucose uptake [25,29]. The exacerbated GSH level and SOD and catalase activities, and suppressed MDA level, in psoas muscles incubated in coconut water indicates an antioxidative effect. This effect also corroborates the scavenging and reducing power activities of coconut water (Figure 1A,B, and Table 1), thus indicating the ameliorative effect of coconut water against oxidative stress, which is among the major pathogenesis and pathophysiology of T2D [30,31]. This corroborates previous reports on the antioxidant properties of coconut water [14,32,33].
Alterations in the purinergic enzyme activities of muscles have been linked to impaired muscle dysfunctions including glucose uptake, as these enzymes are involved in the hydrolysis of adenosine triphosphate (ATP) and adenosine monophosphate (AMP) to generate adenine [34,35]. Adenine is an endogenous signaling nucleotide with reported physiological roles in glucose and bioenergetic homeostasis [36]. The exacerbated ATPase and E-NTPadase activities in psoas muscles incubated with only glucose (Figure 5A,B) indicate a suppressed level of ATP, thus suggesting limited availability of the energy substrates. This corroborates previous reports on increased muscle purinergic enzyme activities in impaired glucose uptake [24,29,35]. The suppressed activities of these enzymes in psoas muscles incubated with coconut water, therefore, indicate an availability of ATP for the generation of adenine and muscle biofunctions including glucose uptake.
These antioxidative, antidiabetic, and purinergic activities can be attributed to the synergistic effect of the LC-MS-identified compounds (Figure 6). These compounds have been well reported for their potent antioxidant and antidiabetic activities [37][38][39][40][41][42]. These activities can be can be attributed to the phenolic structure, which consists of hydroxyl groups and benzene rings. The hydroxyl groups interact with the Π-electrons of the benzene ring, causing the radical to delocalize, and they also donate one electron to the free radical to produce a stable product [43].
The potent molecular interactions of the identified compounds with AKT-2 serine and PI-3 kinase (Figures 7 and 8, and Table 2) portray molecular mechanisms by which the compounds may synergistically improve insulin sensitivity and stimulate muscle glucose uptake. AKT-2 serine plays a key role in insulin-stimulated glucose uptake in muscles by upregulating GLUT4 translocation [44,45]. PI-3 kinase has been reported for its role in insulin signaling and insulin-mediated translocation of GLUT4, thereby driving muscle glucose uptake [46,47].
Coconut Water
Mature coconuts were bought from a local fruit market in Lagos, Nigeria. The coconuts were dehusked and cracked, and the water collected into beakers. The water was frozen overnight at −80 • C, before freeze drying. The freeze-dried samples were collected into vials and stored at −4 • C.
Using a stock solution of 1 mg/mL of the freeze-dried sample, various concentrations of 15, 30, 60, 120, and 240 µg/mL were prepared for in vitro and ex vivo investigations.
Briefly, 100 µL of the sample's concentrations or standard was mixed with 50 µL of 0.3 mM DPPH, and the reaction mixture was incubated at room temperature for 30 min in the dark. Absorbance was read at 517 nm.
The scavenging activity was calculated using the following formula: For FRAP activity, 50 µL of the sample's concentrations or 240 µg/mL of gallic acid was mixed with 50 µL of 1% potassium ferricyanide (in 0.2 M sodium phosphate buffer, pH 6.6) at 50 • C for 30 min. Fifty µL of 10% TCA, and distilled water, and 10 µL of 0.1% ferric chloride were added to the reaction mixture. Absorbance was read at 700 nm. FRAP was expressed as percentage of 240 µg/mL gallic acid.
Inhibition of Carbohydrate Digestive Enzymes
The in vitro antidiabetic properties of the sample were determined by investigating its inhibitory effect on intestinal α-glucosidase and pancreatic α-amylase activities [50]. i.
α-glucosidase activity Briefly, 50 µL of the sample was mixed with 100 µL of 1.0 U m/L α-glucosidase enzyme dissolved in phosphate buffer (100 mmol/L, pH 6.8) and incubated for 20 min at 37 • C. p-nitrophenyl-α-D-glucopyranoside (pNPG) solution (of 5 mmol/L, 50 µL) was added to the reaction mixture and incubated for another 30 min at 37 • C. Absorbance was subsequently read at 405 nm. The inhibitory activity was recorded as a percentage of the control lacking inhibitor.
ii. α-amylase activity Briefly, 50 µL of the sample concentration or acarbose was mixed with 100 µL of porcine pancreatic α-amylase (2 U/mL) in phosphate buffer (100 mmol/L, pH 6.8) and incubated for 20 min at 37 • C. A quantity of 50 µL of 1% starch was added to the reaction mixture and further incubated for 1 h at 37 • C. A quantity of 200 µL of the color reagent, dinitrosalicylate (DNS), was subsequently added to the reaction mixture and boiled for 10 min. Absorbance was read at 540 nm. The inhibitory activity was calculated as the proportion of the control lacking inhibitor.
Animals for Ex Vivo Studies
Five male Sprague Dawley albino rats (200-250 g) were collected and housed at the Animal House facility of the Department of Biochemistry, College of Medicine, University of Lagos, Nigeria under the approved protocol, CMUL/REC/00314. The animals were euthanized with halothane after overnight fasting. Their psoas muscles were harvested for ex vivo studies.
Muscle Glucose Uptake
Glucose uptake was carried out using a previously published method with slight modifications [51]. Briefly, 0.5 g of freshly harvested psoas muscles was incubated in 8 mL of Krebs buffer containing 11.1 mM glucose and different concentrations of coconut water for 2 h at 37 • C under a condition of 5% CO 2 and 95% oxygen. Control consisted of incubation without coconut water, while the standard antidiabetic drug was metformin. Aliquots were collected before and after incubation. Glucose concentrations of aliquots were measured with a Glucose (GO) Assay Kit according to the manufacturer's manual.
Glucose uptake was calculated using the formula: Glucose uptake per gm o f rat psoas muscle = GC1 − GC2 Weight o f muscle tissue (g) where GC1 and GC2 are glucose concentrations (mg/dL) before and after incubation, respectively.
After incubation and collection of buffer aliquots, the muscle tissues were collected and rinsed in normal saline. They were homogenized in cold phosphate buffer solution containing 1% triton X-100 (50 mM; pH 7.5). The homogenized tissues were centrifuged for 10 min at 15,000 rpm and 4 • C. The supernatants were collected and stored in 2 mL Eppendorf tubes at −20 • C until subsequent biochemical analyses.
i. Reduced glutathione (GSH) level
Briefly, 300 µL of the tissue supernatant was mixed with 10% TCA and centrifuged at 3500 rpm for 5 min (25 • C). Subsequently, 200 µL of the resulting supernatant was mixed with 50 µL of Ellman's reagent in a 96-well plate, and allowed to stand on ice for 5 min. Absorbance was read at 415 nm. A GSH standard curve was used to extrapolate GSH level.
ii. Superoxide dismutase (SOD) enzyme activity Briefly, 15 µL of the supernatant was mixed with 170 µL of 0.1 mM diethylenetriaminepentaacetic acid (DETAPAC) in a 96-well plate. Subsequently, 15 µL of 1.6 mM 6-hydroxydopamine (6-HD) was added to the reaction mixture. Absorbance was read at 492 nm wavelength for 3 min at 1 min intervals.
iii. Catalase enzyme activity Briefly, 100 µL of the supernatant was mixed with 1000 µL H 2 O 2 (65 µM) in 6.0 mM sodium phosphate buffer (pH 7.4). The reaction mixture was subsequently incubated at 37 • C for 2 min. The reaction was stopped with 4 mL of 32.4 mM ammonium molybdate, and absorbance was read at 347 nm against a blank.iv. Malondialdehyde (MDA) level Briefly, 200 µL of the supernatant was mixed with 200 µL of 8.1% SDS solution, 750 µL of 20% acetic acid, and 2 mL of 0.25% thiobarbituric acid (TBA). The reaction mixture was boiled for 1 h. After cooling, 200 µL of the reaction mixture was pipetted into a 96-well plate and the absorbance was measured at 532 nm. TBARS extrapolated from the MDA standard curve were used to estimate lipid peroxidation.
v. ATPase activity
Briefly, 200 µL of the supernatants was incubated with 200 µL of 5 mM KCl, 1300 µL of 0.1 M Tris-HCl buffer, and 40 µL of 50 mM ATP in a shaker for 30 min at 37 • C. The reaction was stopped with 1 mL of distilled water and ammonium molybdate. Freshly prepared 9% ascorbic acid was subsequently added to the reaction mixture and allowed to stand on ice for 10 min. Absorbance was measured at 660 nm. Freshly prepared 9% ascorbic acid was added to the reaction mixture, and allowed to stand on ice for 10 min. Absorbance was read at 600 nm.
LC-MS Analysis of Coconut Water
In order to determine its phytochemical constituents, the coconut water was subjected to LC-MS (Shimadzu LCMS-2020 Single Quadrupole) analysis by injecting directly into the machine via a loop as previously described [60] The phytochemicals were identified by direct search and comparison of mass spectral (MS) data with those of the Food Metabolome Database (www.foodb.ca,accessed on 5 September 2023).
i. Protein Target Selection and Preparation
The three-dimensional structures of the two protein receptors, AKT-2 serine and PI-3 kinase, were retrieved from the Protein Data Bank (PDB) (www.pdb.org/pdb,accessed on 5 September 2023) using the PDB IDs 3DOE and 7JWZ, respectively. The PDB database contains the experimental protein and nucleic acid structures. Discovery Studio 2021 was then used to improve and prepare the protein for docking. The protein was converted into a developing receptor by removing the co-crystallized ligand and additional water molecules, followed by the addition of hydrogen and charges.
ii. Ligand Selections and Preparations
Using Chem 3D 20.0, six compounds were simulated and energy optimized (MM44D). These optimized structures were used in the molecular docking tests.
iii. Molecular Docking
The molecular docking study was completed to carry out computations of six molecules with four protein receptors using the Lamarckian Genetic Algorithm in Auto Dock 4.2. In brief, the selected ligands were docked using Python Prescription 0.8 and a collection of automated molecular docking tools named Auto Dock Vina 4.2 with the active sites AKT-2 serine and PI-3 kinase. The protein data bank, partial charge, and atom type a file (PDBQT) was generated from PDB files that had already been prepared as input. The specific target location of the enzyme for the receptor's active site was determined using a grid box. The AKT-2 serine grid point's X, Y, and Z dimensions were 40, 50, and 48, respectively, while the grid center's corresponding numbers were 27.507, −22.526, and 31.423. The PI-3 kinase grid point's X, Y, and Z dimensions were 40, 54, and 63, respectively, whereas the grid center's corresponding numbers were 48.619, 15.525, and 34.405. The docking studies for six compounds yielded 10 configurations for each protein-ligand combination for manual comparison examination. Additionally, text files containing the dock scoring values were created. The conformation with the lowest binding energy (kcal/mol) was shown to be the best docking position. Discovery Studio 2021 was also utilized to look at the interactions between ligands and proteins.
Statistical Analysis
Data were subjected to one-way analysis of variance (ANOVA) and presented as mean ± SD. A statistically significant difference between means were obtained at p < 0.05 using Tukey's HSD multiple range post hoc test. IBM Statistical Package for the Social Sciences (SPSS) for Windows, version 23.0 (IBM Corp., Armonk, NY, USA) was used to carryout statistical analyses.
Conclusions
Taken together, these results indicate the ability of coconut water to enhance glucose uptake, with concomitant improved antioxidative and purinergic activities. It also indicates the potential of coconut water to suppress postprandial hyperglycemia, thereby giving more credence to the antidiabetic properties of coconut water. These biological activities may be attributed to the synergistic effects of the LC-MS-identified compounds. However, in vivo and molecular studies are required to further decipher these mechanisms in diabetic models.
Figure 1 .
Figure 1.(A) DPPH scavenging activity and (B) ferric reducing power of coconut water. Values = mean ± SD; n = 3. a,b Values with different letter above the bars for a given extract are significantly different from each other (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows).
Figure 1 .
Figure 1.(A) DPPH scavenging activity and (B) ferric reducing power of coconut water. Values = mean ± SD; n = 3. a,b Values with different letter above the bars for a given extract are significantly different from each other (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows).
Figure 2 .
Figure 2. Inhibitory effect of coconut water on (A) α-glucosidase and (B) α-amylase activities. Values = mean ± SD; n = 3. a,b Values with different letter above the bars for a given extract are significantly different from each other (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows).
Figure 2 . 16 Figure 3 .
Figure 2. Inhibitory effect of coconut water on (A) α-glucosidase and (B) α-amylase activities. Values = mean ± SD; n = 3. a,b Values with different letter above the bars for a given extract are significantly different from each other (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows). Plants 2024, 13, x FOR PEER REVIEW 5 of 16
Figure 3 .
Figure 3. Effect of coconut water on glucose uptake in isolated psoas muscle. Values = mean ± SD; n = 3. * Statistically significant to normal and control, respectively (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows). Control: muscles incubated with glucose only.
range post hoc test, IBM SPSS for Windows). Control: muscles incubated with glucose only.
Figure 4 .
Figure 4. Effect of coconut water on (A) GSH level; (B) SOD activity; (C) catalase activity; and (D) MDA level. Values = mean ± SD; n = 3. *,# Statistically significant to normal and control, respectively (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows). Normal: muscles not subjected to incubation; Control: muscles incubated with glucose only.
Figure 4 .
Figure 4. Effect of coconut water on (A) GSH level; (B) SOD activity; (C) catalase activity; and (D) MDA level. Values = mean ± SD; n = 3. *, # Statistically significant to normal and control, respectively (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows). Normal: muscles not subjected to incubation; Control: muscles incubated with glucose only. Plants 2024, 13, x FOR PEER REVIEW 6 of 16
Figure 5 .
Figure 5. Effect of coconut water on (A) ATPase and (B) E-NTPDase activities. Values = mean ± SD; n = 3. *, # Statistically significant to normal and control, respectively (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows). Normal: muscles not subjected to incubation; Control: muscles incubated with glucose only.
Figure 5 .
Figure 5. Effect of coconut water on (A) ATPase and (B) E-NTPDase activities. Values = mean ± SD; n = 3. *, # Statistically significant to normal and control, respectively (p < 0.05, Tukey's HSD multiple range post hoc test, IBM SPSS for Windows). Normal: muscles not subjected to incubation; Control: muscles incubated with glucose only.
Figure 6 .
Figure 6. Chemical structure of LC-MS-identified compounds in coconut water.
Figure 6 .
Figure 6. Chemical structure of LC-MS-identified compounds in coconut water.
vi. ENTPDase activity Briefly, 20 µL of the supernatants was mixed with 200 µL of the reaction buffer (1.5 mM CaCl 2 , 5 mM KCl, 0.1 mM EDTA, 10 mM glucose, 225 mM sucrose, and 45 mM Tris-HCl). The reaction mixture was incubated at 37 • C for 10 min. A quantity of 20 µL of 50 mM ATP was added to the reaction mixture and further incubated for 20 min at 37 • C. The reaction was stopped by adding 200 µL of 10% TCA and 200 µL of 1.25% ammonium molybdate.
* IC 50 (half-maximal inhibitory concentration) indicates the concentration of the extract needed to inhibit a biological process by half.
Table 2 .
Binding energy and bonds.
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Domain: Agricultural and Food Sciences
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The Effect Of The Comparison Of Binders In The Manufacture Of Carp Rolade (Cyprinus Carpio) On The Physical Properties And Consumer Acceptability
This research aims to analyze the effect of binder ratio in the making of carp fish roulade on the physical properties and consumer acceptance. The research was conducted at the Food Processing Laboratory, Department of Culinary Education, Universitas Negeri Jakarta. The research period began in August 2023 and ended in June 2024. The method used in this research was experimental. The research sample used grass carp roulade with a binder ratio between tapioca flour and wheat flour at 1:1, 2:1, and 1:2. The samples were then tested on 30 moderately trained panelists who evaluated overall aspects. Based on the results of statistical hypothesis testing using the Friedman test, it was found that there was no influence of binder ratio on the acceptance of carp fish roulade at ratios of 1:1, 2:1, and 1:2 in terms of skin color before and after frying, filling color before and after frying, fish aroma, spice aroma, taste, and structural compactness. However, one aspect that had an influence was the level of tenderness. Based on the results of statistical hypothesis testing, physical testing using the Kruskal-Wallis test showed that the binder ratio had no significant influence on the physical quality of grass carp roulade in terms of hardness level. The conclusion of this study is that the acceptance of carp fish roulade is recommended at a binder ratio of 1:1 between tapioca flour and wheat flour.
Introduction
In accordance with (Downer et al., 2020), everyone's nutritional needs are determined by many factors, namely age, gender, Weight, and height. At Daily Value (RDA), it is listed that Protein Requirements for Men aged 19-64 years are as much as 65 grams, while for adult women 19-64 years, 60 grams of protein, and for children aged 4-9 years range from 25-40 grams. On the other hand, some people, especially older people over 50 years, begin to limit their meat intake or reduce meat consumption due to abstinence from diseases such as gout, arthritis, and coronary heart (Aminati, 2022). People affected by the disease need other sources of protein besides meat that can be obtained, one of which comes from fish (Alam & Mukarrom, 2022;Dickin & Gabrielsson, 2023). Fish contains relatively high animal protein and essential unsaturated fatty acids necessary for the human body (Sebök & Hanelt, 2023). Fish is also a very famous source of vitamin A in addition to other vitamins, and it contains various minerals. Fish are rich The use of binders in food preparation must be appropriate. If the binder used is not right, the resulting dough will contain too much water or can also become too hard or too chewy (Lin, Liang, Yan, Zhao, & Li, 2024). In general, the types of binders commonly used in making food are tapioca flour, rice flour, sago, cornstarch, and wheat flour (Abu-Alruz, 2023;Lin, Liang, Yan, Zhao, Niu et al., 2024). Protein in the form of flour is believed to bind the dough so that it becomes firm and increases the volume of the dough. This study aims to analyze the effect of the ratio of binders between tapioca flour and wheat flour on the manufacture of carp rolade on physical properties and consumer acceptability and obtain the best composition of carp rolade based on organoleptic tests and physical tests.
Based on the background description, several research problems can be identified. First, carp is used as an ingredient in the manufacture of rolade. Secondly, the right binder must be selected to ensure the quality of the goldfish rolade. Third, the determination of the optimal amount of binder ratio. Fourth, the influence of physical properties and quality of goldfish role is a different ratio of binders. Fifth, the influence of consumer acceptability on variations in the ratio of binders. In addressing this issue, research is limited to the comparative effect of binders on the physical properties and consumer acceptability of goldfish role, focusing on aspects of color, aroma, taste, and texture.
The resulting formulation of the problem is whether there is an effect of the comparison of binders on the physical properties and consumer acceptability in making carp rolade. The purpose of this study was to analyze the comparative impact of binders on the physical properties and consumer acceptability of goldfish rolade. The results of the research are expected to be useful for students in improving analytical, critical, and innovative skills, as well as for the community in producing new innovations from carp into nutritious processed products. In addition, this research is expected to make a positive contribution to the Culinary Education Study Program as a reference and contribution to the development of food processing courses as well as educational benefits for future research and other parties who need related information.
Research Methods
The research method used in this study is an experimental method that aims to determine the possibility of a cause-and-effect relationship between the ratio of tapioca flour binders and wheat flour in goldfish rolade to physical properties and consumer acceptability. The object of this study was a carp rolade with a ratio of binders in the form of tapioca flour and wheat flour as much as 1:1, 2:1, and 1:2, which were tested on panelists randomly. Data sources of this study include physical and organoleptic tests. Physical tests include testing the texture of goldfish rolade products using a texture analyzer, while organoleptic tests include the assessment of a product measured using the five human senses. Panelists are somewhat trained to perform hedonic tests or favorability tests to obtain data on consumer acceptability. The population in this study was carp rolade, and the sample was carp rolade with a ratio of binders tested to panelists randomly. This sample consists of three different treatments, namely the ratio of binders 1:1, 2:1, and 1:2. The techniques and research tools used include a texture analyzer tool to measure the texture of goldfish rolade products. This tool works by measuring the durability of the product due to the application of compressive force from the tool through the probe to the sample or the ability of the sample to return to its initial condition after applying pressure to the sample technically serves to measure the level of hardness of a product that you want to observe with units of gf (gram force).
The analytical technique used in this study was a one-way Anova (Analysis of Variance) Test on carp rolade before and after frying for H0 and Ha acceptance. The test results will be calculated using a rating scale of 1 to 5, with a score rating scale of 1 very dislike, score two dislike, score three somewhat like, score four like, and score five very like. The assessment includes several aspects, namely color, aroma, taste, texture (level of softness), and compactness of the rolade structure.
Validation Test Results
The validation test was carried out by five expert Panelists who are lecturers of the Culinary Education Study Program, State University of Jakarta, on research products in the form of carp rolade with a ratio of tapioca flour and wheat flour binders of 1:1, 2:1, and 1: 2. The aspects assessed in this research validation test include aspects of skin color and content color before and after frying, fish aroma, spice aroma, taste, softness, and compactness of rolade structure. The results of the validation test can be seen in the following summary.
Skin Color Aspect (before frying)
The results of the validation test assessment by expert Panelists on aspects of skin color before frying in carp rolade products with a ratio of binders of 1:1, 2:1, and 1:2 are as follows: Table 1 Based on the results of validation tests from 5 expert lecturers on the treatment of 1:1 and 2:1 binder, 2 Panelists, with a percentage of 40%, chose rolade skin before frying golden yellow, and 3 Panelists with a percentage of 60%, chose a brownish yellow color. Advances in Social Humanities Research Vol 2 No. 5 May 2024 While the 1:2 treatment stated that 3 Panelists with a percentage of 60% chose golden yellow and 1 panelist each with a percentage of 20% chose pale yellow and light yellow. The results of the validation test of 5 expert Panelists on the skin color aspect of carp rolade before frying showed that the 1:1 treatment obtained an average value of 4.4, the 2:1 treatment obtained an average value of 4.4, and the 1:2 treatment with an average value of 4. It can be concluded that carp rolade with a ratio of binders of 1: 1, 2: 1, and 1: 2 is in the brownish-yellow category.
Fill the Color Aspect (before frying)
The results of the validation test assessment by expert Panelists on the color aspect of the contents before frying in carp rolade products with a ratio of binders of 1: 1, 2: 1, and 1: 2 are as follows: In accordance with Table 2, the 1:1 treatment shows one panelist with a percentage of 20% stating pale gray color and 4 Panelists with a percentage of 80% stating light gray color. In the 2:1 treatment, 100% of Panelists stated a light gray color, and in the 1:2 treatment, 20% of Panelists stated a pale gray color, and 80% stated light gray. Based on the data above, in the aspect of the color of the contents of the carp rolade before frying, expert Panelists stated that the 1:1 and 1:2 treatments obtained an average value of 4.8, and the 2:1 treatment had an average value of 5. So, carp rolade with a ratio of binders of 1:1, 2:1, and 1:2 is in the light gray category.
Skin Color Aspect (after frying)
The results of the validation test assessment by expert Panelists on skin color aspects after frying in carp rolade products with a ratio of binders of 1: 1, 2: 1, and 1: 2 are as follows: Table 3 Referring to the table of validation results from 5 expert lecturers, the 1:1 and 2:1 treatments showed that 20% of panelists stated golden brown, another 20% stated fawn, and 60% of panelists stated brown. The 1:2 treatment showed 60% of Panelists stated brown, and 20% of other Panelists stated pale brown and yellowish brown. The results of the validation above can be concluded that in the aspect of the skin color of carp rolade after frying, expert Panelists stated that the 1:1 and 2:1 treatments obtained an average value of 4, then the 1:2 treatment had an average value of 3.8. So, goldfish rolade with a ratio of binders of 1: 1, 2: 1, and 1: 2 is in the brown color category.
Color Aspect of Fill (after frying)
The results of the validation test assessment by expert Panelists on the color aspect of the contents after frying in carp rolade products with a ratio of binders of 1: 1, 2: 1, and 1: 2 are as follows: Table 1 Based on the results of the validation test of 5 expert lecturers on the treatment of 1:1 binders, 20% of Panelists chose pale brown, 20% chose fawn, and 60% of other Panelists chose grayish brown. While in the 2:1 treatment, 20% of Panelists stated that they chose golden brown, 40% chose fawn, and 40% were grayish brown. In the 1:2 treatment, expert Panelists stated that 40% chose pale brown, 20% chose fawn, and 40% chose grayish brown. The results of the validation test of 5 expert Panelists on the color aspect of the contents of carp rolade after frying showed that 1: 1 and 2: 1 treatment obtained an average value of 4 and 1: 2 treatment obtained an average value of 3.8. It can be concluded that carp rolade with a ratio of binders of 1: 1, 2: 1, and 1: 2 is in the grayishbrown category.
Aroma Aspects of Fish
The results of the validation test assessment by expert Panelists on the aspects of fish aroma in goldfish rolade products with a ratio of binders of 1: 1, 2: 1, and 1: 2 are as follows: Table 2 In accordance with the table above, the 1:1 and 1:2 treatment showed that 60% of Panelists stated that it smelled of strong fish, 20% of Panelists stated that it smelled rather strong, and 20% stated that it smelled of weakfish. In the 2:1 treatment, 40% of panelists stated that it smelled like a strong fish, 40% said it smelled rather strong, and 20% said it smelled like a weakfish. Based on the data above, in the aspect of carp aroma in the rolade, expert Panelists stated that the 1:1 and 1:2 treatments obtained an average value of 3.8 and the 2:1 treatment had an average value of 4. So, a carp rolade with a ratio of binders of 1:1, 2:1, and 1:2 in terms of fish aroma is in the category of strong fish aroma.
Aroma Aspect of Spices
The results of the validation test assessment by expert Panelists on the aroma aspects of carp rolade spices with a ratio of binders of 1: 1, 2: 1, and 1: 2 are as follows: Referring to the validation results above, the 1:1 treatment showed 2 Panelists with a percentage of 40% stating a strong spice aroma, 40% of other Panelists stating a slightly strong spice aroma, and 20% stating a weak spice aroma. While in the 2:1 and 1:2 treatments, 60% of Panelists stated a strong aroma, 20% had a slightly strong aroma, and another 20% stated a weak spice aroma. It can be concluded that in the aspect of the aroma of goldfish rolade spices, expert panelists stated that the 1:1 treatment obtained an average value of 3, and then the 2:1 and 1:2 treatments had an average value of 4. So, carp rolade with a ratio of binders of 1:1, 2:1, and 1:2 is in the category of very strong spice aroma.
Taste Aspect
The results of the validation test assessment by expert Panelists on the taste aspects of carp rolade with a ratio of binders of 1:1, 2:1, and 1:2 are as follows: Tabel 4. Referring to the table, the 1:1 treatment shows 2 Panelists with a percentage of 40% stating a very savory taste, 40% of other Panelists stating savory, and 20% stating slightly savory. In the 2:1 treatment, 80% of Panelists stated savory, and 20% stated slightly savory. While in the 1:2 treatment, 60% of panelists chose savory taste, and 40% chose slightly savory. It can be concluded that in the aspect of the taste of goldfish rolade, expert panelists stated that the 1:1 and 1:2 treatments obtained an average value of 4.2, and the 2:1 treatment had an average value of 4.6. So, carp rolade with a ratio of binders of 1:1, 2:1, and 1:2 is in the savory category.
Softness Level Aspect
The results of the validation test assessment by expert Panelists on aspects of softness (when chewed) in carp rolade products with a ratio of binders of 1: 1, 2: 1, and 1: 2 are as follows: Table 5. According to the table, the 1:1 and 2:1 treatments showed that 80% of Panelists stated that goldfish rolade was soft in texture, respectively, and 20% of other Panelists stated that it was slightly soft. In the 1:2 treatment, 20% of panelists chose a very soft texture, 60% stated soft, and 20% stated slightly soft. Based on the data above, in the aspect of the softness of goldfish rolade, expert Panelists stated that the 1: 1 and 2: 1 treatment obtained an average value of 4.6 and the 1: 2 treatment had an average value of 4.4. So, carp rolade with a ratio of binders of 1: 1, 2: 1, and 1: 2 in terms of the level of softness when chewed is in the soft textured category.
Aspect of Compactness of Structure
The results of the validation test assessment by expert Panelists on the compactness aspect of the carp rolade structure with a ratio of binders of 1: 1, 2: 1, and 1: 2 are as follows: Based on the results of validation tests from 5 expert lecturers on the treatment of 1:1 binders showed that one panelist, with a percentage of 20%, chose very compact, 40% of Panelists chose compact, and 40% of other Panelists chose rather compact. In the 2:1 treatment, 4 Panelists, with a percentage of 80%, chose compact, and one panelist, with a percentage of 20%, chose rather compact. While the 1:2 treatment stated that 20% of Panelists chose very compact, 60% of other Panelists chose compact, and 20% of Panelists chose rather compact. The results of the validation test of 5 expert Panelists on the aspect of compactness of the structure of goldfish rolade showed that the 1:1 treatment obtained an average value of 4, the 2:1 treatment obtained an average value of 4.6, and the 1:2 treatment obtained an average value of 4.4. So it is concluded that the structure of carp rolade with a ratio of binder of 1:1, 2:1, and 1:2 is in the compact category.
Skin Color Aspect Assessment (before frying) Assessment of Hypothetical Results of Skin Color Aspects (before frying)
The calculation results for 30 moderately trained Panelists obtained x2 count = -9.891at a significant level of α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99 above shows that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the aspect of skin color of carp rolade before frying on consumer acceptance.
Assessment of Fill Color Aspects (before frying) Assessment of Hypothetical Results of Aspects of Fill Color (before frying)
The calculation results for 30 moderately trained Panelists obtained x2 count = 5.816 at a significant level of α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculation results based on the color aspect of the contents of carp rolade before frying can be seen in the following table: The calculation results for 30 moderately trained Panelists obtained x2 count = -10.35at a significant level of α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculation results based on aspects of carp rolade skin color after frying can be seen in the following table: Table 13 above shows that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the aspect of skin color of carp rolade after frying on consumer acceptance.
Assessment of Fill Color Aspects (after frying) Assessment of Hypothetical Results of Color Aspects of Contents (after frying)
The calculation results for 30 moderately trained Panelists obtained x2 count = 1.31 at a significant level of α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculation results based on the color aspect of the contents of carp rolade after frying can be seen in the following table: H0 accepted and H1 rejected. The table above can be concluded that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the color aspect of the contents of carp rolade after frying on consumer acceptance.
Assessment of Fish Aroma Aspects Assessment of the Results of the Hypothesis of Fish Aroma Aspects
The calculation results for 30 moderately trained Panelists obtained x2 count = 1.81 at a significant level α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculation results based on aspects of carp rolade fish aroma can be seen in the following table: H0 accepted and H1 rejected. The table above shows that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the aroma aspect of carp rolade fish on consumer acceptance.
Assessment of Aroma Aspects of Spices Assessment of Hypothetical Results of Spice Aroma Aspects
The calculation results for 30 moderately trained Panelists obtained x2 count = 1.25 at a significant level of α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculations based on aspects of the aroma of goldfish rolade spices can be seen in the following table: H0 accepted and H1 rejected. The table above shows that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the aroma aspect of carp rolade spices on consumer acceptance.
Assessment of Taste Aspects Assessment of the Results of the Taste Aspect Hypothesis
The calculation results for 30 moderately trained Panelists obtained x2 count = -0.816at a significant level of α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculation results based on the taste aspects of goldfish rolade can be seen in the following table : Table 17 H0 accepted and H1 rejected. The table above can be concluded that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the aspect of the taste of carp rolade on consumer acceptance.
Aspect Assessment of Softness Level Assessment of Hypothetical Results of Aspects of Softness Level
The calculation results for 30 moderately trained Panelists obtained x2 count = 9.00 at a significant level α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculation results based on aspects of the softness level of goldfish rolade can be seen in the following table: H0 accepted and H1 rejected. The table above shows that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the aspect of the softness of goldfish rolade on consumer acceptance.
Assessment of Structural Compactness Aspects Assessment of Hypothesis Results of Aspects of Structural Compactness
The calculation results for 30 moderately trained Panelists obtained x2 count = 0.616 at a significant level α = 0.05 while x2 table at the degree of confidence db = 3-1 = 2, which is 5.99. The table of analysis calculation results based on the aspect of compactness of the structure of goldfish rolade can be seen in the following table: H0 accepted and H1 rejected. The table above can be concluded that there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the aspect of compactness of the structure of goldfish rolade on consumer acceptability.
Acceptability Test Results
Based on the results of data obtained in organoleptic testing on consumer acceptability tests conducted on 30 rather trained Panelists, namely students of Culinary Education, Faculty of Engineering, Jakarta State University. The data obtained were assessed based on research aspects on making carp rolade with a ratio of binders of 1: 1, 2: 1, and 1: 2, which included a scale of very like, like, somewhat like, dislike, and very dislike. Based on the results of organoleptic testing on the aspect of rolade skin color before frying, it shows that the highest average score at 4.3 is in the like category, which shows that the skin color of carp rolade before frying is liked and accepted by consumers. In the hypothesis test, there was no effect of skin color before frying in carp rolade with a ratio of binders of 1: 1, 2: 1, and 1: 2. So it can be concluded that the ratio of binders with different amounts does not affect the color aspect of a product and also does not affect the level of consumer preference.
The results of organoleptic tests on the color aspect of the contents of carp rolade before frying show that the product is liked and accepted by consumers. In testing, the hypothesis stated that there was no influence on the color of the contents of the carp rolade before frying with a ratio of binders of 1:1, 2:1, and 1:2. The color aspect in the physical quality test is an influential aspect in research, it can occur due to changes in temperature factors and the addition of materials (Sriyani, 2021). Based on the results of organoleptic Advances in Social Humanities Research Vol 2 No. 5 May 2024 tests on the aspect of skin color, carp rolade after frying was accepted and liked by consumers with an average value of 4.27. From the results of the hypothesis test analysis, there is no effect of the ratio of binders on the aspect of skin color of carp rolade after frying with a ratio of binders of 1: 1, 2: 1, and 1: 2. The results of organoleptic tests conducted based on the color aspect of the contents of carp rolade after frying show that the product is liked and accepted by consumers. Referring to the results of the hypothesis test analysis, there is no effect of the ratio of binders of 1: 1, 2: 1, and 1: 2 on the color aspect of the contents of carp rolade after frying on consumer acceptance.
In the aspect of fish aroma, the highest average value was obtained in the treatment of binders of 1:2 with a total of 4.23, which showed that the aroma of carp received positive acceptance and was liked by consumers. The results of the hypothesis test did not have an effect on the ratio of binders to fish aroma in goldfish rolade with a ratio of 1:1, 2:1, and 1:2. One of the factors causing the aroma of goldfish to get positive acceptance from consumers is because the use of fresh carp directly purchased from traders live which are handled on that day hygienically so as to reduce the fishy aroma caused by goldfish and the quality is maintained. The use of fish, if not handled properly, will experience damage and affect the taste (Razin, 2024). So, it can be concluded that the aroma of fish is not influenced by the ratio of binders but is influenced by the quality of the fish used and does not affect the level of consumer preferences.
Based on the results of organoleptic tests on the aspect of spice aroma in goldfish rolade with a ratio of binders of 1: 1, 2: 1, and 1: 2 received and liked by consumers with the highest average score of 4.10 in the 2: 1 treatment with the category of likes. The results of the hypothesis analysis test showed that there was no influence of the aroma of spices from carp rolade with the ratio of binders. The spice referred to in this case is the use of garlic, onion, ground nutmeg, and ground pepper to strengthen the aroma and disguise the fishy aroma of goldfish. So, it can be concluded that the aroma of spices is not influenced by the ratio of binders but is influenced by spices and spices used and does not affect the level of consumer preferences.
The results of organoleptic tests on the taste aspect of carp rolade with a comparison of binders show that the product is accepted and liked by consumers. In the hypothesis analysis test, it was stated that there was no influence on the taste of goldfish rolade in the ratio of binders 1:1, 2:1, and 1:2. The taste of carp rolade is obtained from the addition of salt and flavoring using mushroom broth, and from the carp meat itself. One factor that affects the salty taste aspect is the use of salt (Rahayu & Ridawati, 2015). In addition, the use of fish can also provide a salty taste naturally (Muchtadi et al., 2010). The umami taste is naturally obtained from broth, chicken, meat, fish, etc., while artificially obtained through the addition of flavoring seasonings, such as monosodium glutamate (Ketaren, 2019). It can be concluded that the taste of goldfish rolade is Not influenced by the ratio of binders but influenced by the addition of spices and flavorings because carp meat is less savory and does not affect the level of consumer preferences.
On the aspect of softness level, From goldfish rolade with a ratio of binders, the results of organoleptic testing show that the product is acceptable and preferred by consumers. In the hypothesis analysis test, there was no effect on the softness level of goldfish rolade in the ratio of binders 1:1, 2:1, and 1:2. The level of softness in carp rolade comes from the ratio of the amount of tapioca flour and wheat flour used in making rolade dough, the ratio of the amount of tapioca flour is less than the amount of wheat flour. One of the ingredients used in making rolade is tapioca flour, which serves to improve texture, increase softness, and help the development process (Aminullah et al., 2020). Every material that has gone through the grinding process will produce a smooth and soft texture, and this affects the texture of rolade (Muchtadi, Sugiyono and Fitriyono Ayustaningwarno, 2010) In accordance with the results of organoleptic tests that have been carried out, the compactness of the structure of goldfish rolade with the ratio of binders can be accepted and liked by consumers. Based on the acquisition of the average value on the aspect of compactness of the structure of the goldfish rolade, the ratio of 1:1 treatment binders has the highest average value of 4.17, which is in the range of the like category. Referring to the hypothesis analysis test it states that there is no influence on the compactness of the structure of the goldfish rolade with a ratio of binding materials of 1:1, 2:1, and 1:2.
Physical Test Results
In this study, the physical quality of carp rolade was tested with a comparison of binders, which includes aspects of hardness. In the physical hardness test, the average level of hardness of carp rolade with the ratio of binders before frying, which was carried out three times, obtained results between 13.3-28.3gf, showing that there was an influence on the level of hardness of carp rolade in each treatment was significantly different. In the physical test of goldfish rolade hardness with a ratio of binders after frying with three repetitions, the average result was between 24-30 gf.
The physical quality testing of carp rolade before and after frying showed an effect on the hardness level of carp rolade, and each treatment had no significant effect. The highest level of goldfish rolade hardness before frying is found in the 1:2 treatment, which is (23.8)gf, and the lowest level of hardness is in the 1:1 treatment of (13.3) gf. While the hardness level of carp rolade after frying with the highest rank is found in the 1:2 treatment, which is (30) gf, then the lowest level of hardness is in the 2:1 treatment of (24) gf.
Conclusion
Based on the research on making carp rolade, it can be concluded that the best formula involves using a binder ratio of tapioca flour to wheat flour of 1:1, 2:1, or 1:2. Descriptive data from consumer acceptability tests, which included aspects such as skin color before and after frying, color of contents before and after frying, aroma of fish, aroma of spices, taste, level of softness, and compactness of structure, were collected from 30 moderately trained panelists. The highest scores for various aspects were observed across different ratios, with the 1:2 ratio often receiving the highest ratings in categories such as skin color before frying, color of contents before and after frying, and fish aroma. However, the statistical analysis using the Kruskal-Wallis test indicated no significant effect of the
Volume 2, No. 5 May 2024
p-ISSN 3032-3037| e-ISSN 3031-5786 The Effect Of The Comparison Of Binders In The Manufacture Of Carp Rolade (Cyprinus Carpio) On The Physical Properties And Consumer Acceptability on organoleptic tests. The results of the best rolade research with treatment in the form of adding 50 grams of sago flour.
The Effect Of The Comparison Of Binders In The Manufacture Of Carp Rolade (Cyprinus Carpio) On The Physical Properties And Consumer Acceptability Advances in Social Humanities Research Vol 2 No. 5 May 2024
. Rolade Skin Color Aspect Validation Test Results (after frying)
The Effect Of The Comparison Of Binders In The Manufacture Of Carp Rolade (Cyprinus Carpio) On The Physical Properties And Consumer Acceptability Advances in Social Humanities Research Vol 2 No. 5 May 2024
. Fish Aroma Aspect Validation Test Results
Advances in Social Humanities Research Vol 2 No. 5 May 2024
Hasil Uji Validasi Aspek Rasa
The Effect Of The Comparison Of Binders In The Manufacture Of Carp Rolade (Cyprinus Carpio) On The Physical Properties And Consumer Acceptability 775 Advances in Social Humanities Research Vol 2 No. 5 May 2024
Table 7 . Results of Skin Color Aspect Hypothesis Testing (before frying)
Table of analysis calculation results based on aspects of skin color of carp rolade before frying can be seen in the following table: Based on the table above shows the value of x2 count < x2 table H0 accepted and H1 rejected. The table
Table 12 . Results of Hypothesis Testing of Fill Color Aspects (before frying)
Based on the table above shows the value of x2 count < x2 table H0 accepted and H1 rejected. The table above can be concluded that there is no effect of the ratio of binders The Effect Of The Comparison Of Binders In The Manufacture Of Carp Rolade (Cyprinus Carpio) On The Physical Properties And Consumer Acceptability of 1: 1, 2: 1, and 1: 2 on the color aspect of the contents of carp rolade before frying on consumer acceptance. Skin
. Results of Skin Color Aspect Hypothesis Testing (after frying)
Based on the table above shows the value of x2 count < x2 table H0 accepted and H1 rejected. The table
Table 14 . Results of Hypothesis Testing of Fill Color Aspects (after frying)
Based on the table above shows the value of x2 count < x2 table
Table 15 . Results of Hypothesis Testing of Ika Aroma Aspects Test Criteria x 2 count x 2 table Conclusion
Based on the table above shows the value of x2 count < x2 table Advances in Social Humanities Research Vol 2 No. 5 May 2024
Table 16 . Results of Hypothesis Testing of Spice Aroma Aspects Test Criteria x 2 count x 2 table
Based on the table above shows the value of x2 count < x2 table
. Results of Testing the Taste Aspect Hypothesis Test Criteria x 2 count x 2 table Conclusion
Based on the table above shows the value of x2 count < x2 table
Table 18 . Results of Hypothesis Testing of Aspects of Softness Advances
in Social Humanities Research Vol 2 No. 5 May 2024 Based on the table above shows the value of x2 count > x2 table
Table 19 . Results of Hypothesis Testing of Aspects of Structural Compactness Test Criteria x 2 count x 2 table Conclusion
Based on the table above shows the value of x2 count < x2 table
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Domain: Agricultural and Food Sciences
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Legume Protease Inhibitors as Biopesticides
Legumes can produce many different molecules in response to the attack of insects, nematodes, molds, bacteria, and viruses. Protease inhibitors (PIs) are proteins produced by legumes that inhibit proteolytic enzymes of phytopathogens, which cannot feed on the amino acids of the plant. Legume’s strategy to avoid phytopathogens can be used to produce biopesticides and eliminate or decrease the use of agrochemicals in agriculture.
Figure 1. Effect of Legume PIs on pathogens proteases
PIs can be divided into serine, cysteine, aspartic, and metalloprotease inhibitors. Serine PIs are the most studied and are widely present in legumes, where two types have been identified, Kunitz and Bowman-Birk. Kunitz type has one or two polypeptide chains of 20 kDa, with four cysteine residues that form two intrachain disulfide bonds and inhibit trypsin activity. The Bowman-Birk PIs are single-chain polypeptides of 8 kDa, cysteine-rich with seven disulfide bonds, and two active domains for trypsin or chymotrypsin inhibition . Cysteine PIs are the second most studied class of inhibitors. These are capable of blocking papain-like cysteine proteases present in many insects and nematodes.
Cysteine PIs are grouped into the cystatin superfamily, which includes animal cystatins (stefins, cystatins, and kininogens) and plant cystatins, also called phytocystatins, with more than 80 members. Phytocystatins are peptides ranging in size from 12-86 KDa. Some authors suggest that these kinds of inhibitors are the most promising PIs in transgenic plants . Legumes can produce many different molecules in response to the attack of insects, nematodes, molds, bacteria, and viruses. Protease inhibitors (PIs) are proteins produced by legumes that inhibit proteolytic enzymes of phytopathogens, which cannot feed on the amino acids of the plant. Legume's strategy to avoid phytopathogens can be used to produce biopesticides and eliminate or decrease the use of agrochemicals in agriculture. [1] [2] [3] Encyclopedia 2020 doi: 10.32545/encyclopedia202006.0001.v1 Legumes react to pathogens attack by accumulating a large number of PIs. Many plants can produce PIs; however, legumes are identified as the most important sources of these proteins. The PIs found in legumes have shown superior stability and superior inhibition activity over pathogens in comparison with PIs from other plants .
Serine and cysteine proteases are the two essential enzymes present in the digestive system of insects. These proteases become the principal target of cysteine and serine PIs, produced by legumes, when under insect attack.
Generally, serine PIs are effective against Lepidoptera and Diptera, whereas cysteine PIs are effective against Coleoptera. Both serine and cysteine PIs are active versus Aphids . Ramalho et al. purified a PI from Platypodium elegans seeds, which resulted in a 98% and 30% inhibition in trypsin and chymotrypsin, respectively. This PI displayed a potent inhibition to trypsin enzymes obtained from the pest insects Anagasta kuehniella, Corcyra cephalonica, Aedes aegypti, and Spodoptera frugiperda. The larval weight of S. frugiperda decreased by 55%, and the extension of the insect life cycle increased, when feeding on the P. elegans PI.
Nematodes are endoparasites that invade plant roots and therefore lead to considerable economic losses in agriculture. It is reported that cysteine proteases, in nematodes, play an essential role in protein degradation. Andrade et al. identified, from Crotalaria pallida, a protein with papain-inhibitory activity. This PI produced up to 95% mortality on Meloidogyne incognita and was observed to internalize and diffuse over the entire body of the nematode. Direct extraction of PIs from legume seeds is a challenging and impractical task. It can also result in an ethical problem due to the vast waste of food. On the other hand, the development of transgenic plants or the production of recombinant proteins represents practical strategies. In the strategy of transgenic plant generation, some pathogens can develop resistance against PIs produced by plants. Therefore, it would be necessary to generate cultivars containing new PIs genes. Additionally, it has been shown that endosymbiotic insect bacteria can produce nonsensitive PI proteases, which helps insects to digest protein in their gut . The use of recombinant microorganisms to produce PIs seems to be the best option because several recombinant PIs can be formulated in a biopesticide. This strategy assures PI effectiveness by avoiding phytopathogen adaptation. The production of recombinant PI has been carried out in bacteria and yeasts. [6] [7] [8] [9] [10] [11] [12] Encyclopedia 2020 doi: 10.32545/encyclopedia202006.0001.v1 Phytopathogens use proteolytic enzymes to infect, colonize, and obtain nutrients from legumes. The production of PIs by legumes is a way to counteract attacks by phytopathogens. These proteins can inhibit the activity of phytopathogen proteolytic enzymes. For this reason, their use in agricultural systems may be an option to replace toxic agrochemicals that harm the environment and affect human health.\===
Domain: Agricultural and Food Sciences. The above document has 2 sentences that start with 'Protease inhibitors (PIs) are proteins', 2 sentences that start with 'The production of', 2 sentences that end with 'nematodes, molds, bacteria, and viruses', 2 sentences that end with 'amino acids of the plant'. It has approximately 771 words, 47 sentences, and 8 paragraph(s).
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Comparison of grain traits and genetic diversity between Chinese and Uruguayan soybeans (Glycine max L.)
Soybeans (Glycine max L.), originating in China, were introduced to South America in the late 19th century after passing through North America. South America is now a major soybean-producing region, accounting for approximately 40% of the global soybean production. Crops like soybeans gradually adapt to the local climate and human-selected conditions, resulting in beneficial variations during cultivation in different regions. Comparing the phenotypic and genetic variations in soybeans across different regions is crucial to determining the variations that may enhance soybean productivity. This study identified seed-related traits and conducted a genetic diversity analysis using 46 breeding soybean varieties from China and Uruguay. Compared to the Chinese soybean germplasm, the Uruguayan equivalent had a lower 100-grain weight, higher oil content, lower protein content, and higher soluble sugar content. Using ZDX1 gene chips, genetic typing was performed on the 46 breeding varieties. Cluster analysis based on SNP sites revealed significant differences in the genetic basis of Sino-Uruguayan soybean germplasm. Selection analysis, including nucleotide polymorphism (π) and fixation indexes (Fst), identified several genomic regions under selection between Sino-Uruguayan soybean germplasm. The selected intervals significantly enriched gene ontology (GO) terms related to protein metabolism. Additionally, differentiation occurred in genes associated with the oil content, seed weight, and cyst nematodes between Sino-Uruguayan soybean germplasm, such as GmbZIP123 and GmSSS1. These findings highlight the differences in seed-related phenotypes between Sino-Uruguay soybean germplasm and provide genomic-level insights into the mechanisms behind phenotypic differences, offering valuable references for understanding soybean evolution and molecular breeding.
Introduction
Soybeans (Glycine max L.), originating from China (Dong et al., 2022), have a long history of cultivation dating back 5,000 years (Qu et al., 2023). Soybeans are rich in plant proteins and oils. Seed proteins and oils are crucial factors that determine the nutritional and economic value of soybeans (Patil et al., 2017). In the mid to late 18th century, soybeans were introduced to North America (Hymowitz and Shurtleff, 2005). By the end of the 19th century, soybeans had been transferred from North to South America (Pregnolatto, 1981). Despite the relatively brief history of soybean cultivation in South America, this region is currently one of the world's most significant soybean-producing areas. In terms of soybean variety improvements, South America has managed to develop new soybean varieties with high yields stability and adaptability (Wang, 2014). In Uruguay, soybeans occupy more than half of the total cultivated cereal area and greatly contribute to export revenue (DIEA, 2020;OPYPA, 2020).
Germplasm resources are the foundation for breeding new varieties and conducting fundamental research. The richer the soybean germplasm resources, the greater the potential to develop superior varieties (Zhou et al., 2022). Soybean germplasm is jointly regulated by genetic and environmental factors, resulting in a diverse range of phenotypic variations. One of the primary contributing factors to soybean yield is the 100-grain weight (Lu et al., 2017). Controlled by multiple genes and possessing a high heritability, the 100-grain weight is significantly influenced by environmental factors (Mian et al., 1996). Soybean quality characteristics are typically associated with traits such as seed oil, protein, and sugar contents (Teng et al., 2017;Zhang Q. et al., 2023). The protein and oil content of soybeans are typical phenotypes resulting from the interaction between genetic factors and the environment (Pathan et al., 2013). Research indicates that during the cultivation of soybeans in different regions, changes in seed traits have occurred due to varying environmental factors and breeding objectives. A comparison of 277 Chinese soybean varieties and 300 American soybean varieties found that American soybean varieties are characterized by taller plants, more branches, more pod numbers, and higher yields (Liu Z. et al., 2017). Studies have revealed a significant negative correlation between soybean protein and oil contents (Bandillo et al., 2015), which poses a challenge when attempting to improve the soybean oil content and yield while maintaining the desired protein content. The total and soluble sugar contents of soybean germplasm also exhibit rich genetic variations, with substantial differences in the soluble sugar content observed in different environments (Lu et al., 2022). This variability can provide valuable germplasm resources for breeding (Geater and Fehr, 2000).
GmMFT participates in the regulation of the seed oil content, with different alleles of this gene significantly impacting the oil content (Cai et al., 2023). Analysis of 46 Sino-Uruguayan soybean germplasm revealed differentiation in the frequency of this gene between the AA and CC regions. Additionally, GmDGAT1b increases the oleic acid levels, thereby affecting the fatty acid composition of the seeds (Torabi et al., 2021). Divergence in the allele frequencies of GmDGAT1b in the AA and CC regions gives rise to significant differences in the oil contents of Sino-Uruguayan soybean germplasm. Overexpression of GmWRKY12 enhances the resistance of transgenic soybeans to salt and drought (Shi et al., 2018). Similarly, differentiation in the allelic gene frequency of GmWRKY12 between the AA and GG regions in Sino-Uruguayan soybean germplasm is the primary cause for the observed differences in drought-related traits between these germplasms. GmFT2a has been shown to facilitate flowering through transgenic studies in both Arabidopsis and soybeans (Sun et al., 2011). Analysis of 46 Sino-Uruguayan soybean germplasm revealed differentiation in the allelic frequencies of GmFT2a in the GG and TT regions, leading to variations in the flowering phenotype.
Utilization of the complementary advantages of germplasm from different regions will provide abundant breeding materials to develop high-yield, high-quality, and environmentally adaptive varieties. This is of paramount importance to enhancing soybean production in China and ensuring global food security. Therefore, this study leveraged valuable germplasm resources from Uruguay, a key soybean producer in South America. Through a comparison of the seed characteristics and genetic diversity of 46 Sino-Uruguayan soybean germplasm, genes related to seed quality characteristics, including GmbZIP123, GmMFT, GmDGAT1b, and GmSSS1, were identified. This research offers valuable information of genetic resources to improve soybean yield and quality.
Plant materials and experimental design
A total of 46 soybean germplasm (Supplementary Table 1), including 22 from China and 24 from Uruguay, were provided by the Crop Science Institute of the Chinese Academy of Agricultural Sciences. In 2022, all germplasms were planted in the Tacheng Experimental Station (Nanchang, Jiangxi Province); and seeds were sown on July 22 nd . Triplicates were sown for each seed, and replicates were planted across three rows, with each being 2 meters in length. Row spacing was 40 cm, and plant spacing was 8 cm. The 1,856 soybean germplasm for this comparative analysis were planted in Hainan on November 16 th , 2018. The planting site was located at the Sanya Experimental Station of the Crop Science Institute, in the Chinese Academy of Agricultural Sciences. Cultivation conditions were 35 cm row spacing, 10 cm plant spacing, and normal water and fertilizer management. Material genotype data were obtained from Li et al. (2023).
Phenotypic identification
A total of 100 seeds were randomly selected for seed weight measurement and the triplicate averages were calculated. Approximately 50 g of undamaged seeds were randomly selected, and the protein and oil contents were measured using Fouriertransform near-infrared spectroscopy (FT-NIR). Soluble sugar measurements were performed using the method described by Agyenim-Boateng et al. (2023). A total of 100 mg of soybean powder was mixed with 50% acetonitrile, and the samples were shaken for 8h at room temperature in an incubator. Then 500 mL of the supernatant was transferred to a new tube containing 200 mL of acetonitrile, and the mixture was shaken to achieve protein precipitation. After 10 min at room temperature, the samples were centrifuged at 20°C for 10 min, and the supernatant was filtered using a syringe filter (0.22 mm) before detection using a UPLC-RID (Agyenim-Boateng et al., 2023).
DNA extraction and SNP genotyping
DNA extraction and SNP analysis were conducted by the Beijing Comsen Biological Technology Co., Ltd., in collaboration with the Crop Science Institute of the Chinese Academy of Agricultural Sciences, using the co-developed "Zhongdouxin-1" chip (Sun et al., 2022). After genotyping, Tianjin Jizhi Genes Technology Co., Ltd.obtained the SNP genotype data for all samples. SNPs were filtered based on a minimum allele frequency (MAF) < 0.05 and missing rate (Miss) > 0.8, resulting in a total of 96,446 SNPs that were used for subsequent analysis. Genomic variation of the natural population was analyzed in a previous study (Li et al., 2023).
Candidate gene analysis
The soybase database ( [URL] a reference genomic map was searched to identify candidate genes. Based on the linkage disequilibrium (LD) decay distance in soybeans, a gene scan was performed within 100 kb upstream and downstream of significant sites, using the physical positions of all SNP sites, to identify genes affecting the phenotypic traits of the Sino-Uruguayan soybean varieties.
Statistical data analysis
Of the 46 soybean samples, 22 were from China and 24 were from Uruguay, with a total of 96,446 SNPs for subsequent analysis. The distance matrix was computed using TreeBeST (version: Treebest-1.9.2) software in order to construct a phylogenetic tree, with bootstrap values obtained through 1000 iterations. Principal component analysis (PCA) was conducted by Jizhi Genes using GCTA (Yang et al., 2011), and Admixture (version 1.3.0)(Alexander et al., 2009) was used for population structure analysis, analyzed separately for k=2 and k=3. The genetic diversity parameter (Pi) and fixation index (Fst) were calculated using VCFtools (Danecek et al., 2011), with a window size of 10 kb and a step size of 5 kb. Pop LDdecay software (Zhang C. et al., 2019) was used to analyze the LD, half of the LD decline to the maximum value is the LD decay distance.
Phenotypic trait differences
Analysis of the 46 Sino-Uruguayan soybean germplasm revealed that the average 100-grain weight of Chinese soybean varieties (17.42 g) was significantly higher than the average 100grain weight of Uruguayan soybean varieties (15.31 g) (Figure 1A). Among the Chinese soybean varieties, CN1 exhibited the highest 100-grain weight at 24.33 g, while CN22 had the lowest at 13.66 g. Among Uruguayan soybean varieties, UY19 had the highest 100grain weight at 18.7 g, and UY11 had the lowest at 12.33 g.
The result of the determination of the protein contents of the Sino-Uruguayan soybean germplasm showed that the quality characteristics of the Chinese soybean resources were characterized by a high protein content (range of variation 38.74% to 45.65%, mean value 42.81%) significantly higher than the Uruguayan soybean varieties. The range of variation of protein content of Uruguayan soybeans was 38.36% to 42.06%, with an average of 40.45% (Figure 1B). The Chinese soybean resource with the highest protein content was CN2, and the Uruguayan soybean variety with the highest protein content was UY13.
By comparing the oil content of the Sino-Uruguayan soybean germplasm, it was found that the oil content of Uruguayan soybean seeds was higher, with an average of 21.44%, which was significantly higher than that of Chinese soybean seeds (19.87%)Uruguayan soybean varieties had oil content ranging from 20.45% to 22.64%, oil content in Chinese soybean varieties ranged from 18.57% to 23.08% (Figure 1C). The Uruguayan soybean variety with the highest oil content was UY3, and the Chinese soybean variety with the highest oil content was CN20.
The contents of total soluble sugar, fructose, glucose, sucrose, and stachyose in soybeans from China and Uruguay were measured, with significant differences observed in the sugar contents of the germplasms of the two regions (Figure 1D; Supplementary Figure 1). In Uruguayan soybeans, the total soluble sugar content ranged from 85.97 mg/g to 108.78 mg/g, with an average of 96.99 mg/ g. The variety with the highest total soluble sugar content was UY23. For Chinese soybeans, the total soluble sugar content ranged from 57.62 mg/g to 101.60 mg/g, with an average of 75.40 mg/g. The variety with the highest total soluble sugar content was CN1. In Uruguayan soybeans, the fructose, glucose, sucrose, and stachyose contents ranged from 1.92 mg/g to 5.46 mg/g, 3.56 mg/g to 5.28 mg/g, 49.47 mg/g to 61.58 mg/g, and 20.72 mg/g to 35.06 mg/g, respectively. In Chinese soybeans, the fructose, glucose, sucrose, and stachyose contents ranged from 1.75 mg/g to 3.90 mg/g, 2.61 mg/g to 4.84 mg/g, 28.27 mg/g to 56.47 mg/g, and 15.71 mg/g to 36.84 mg/g, respectively. The total soluble sugar, fructose, glucose, sucrose, and stachyose contents in Uruguayan soybeans were significantly higher than those in Chinese soybeans.
Genetic diversity and population structure analysis of Sino-Uruguayan soybean varieties
In the PCA plot, the tested soybean materials were distinctly divided into two main genetic groups, corresponding to their respective origins in China and Uruguay. The contribution rate of PC1 was 54.96% and the contribution rate of PC2 was 26.81%. The genetic differences among the Chinese population were minimal, whereas significant variations were observed among the Uruguayan population (Figure 2A). The evolutionary tree constructed based on the neighbor-joining (NJ) features further revealed a clear separation between the Sino-Uruguayan soybean varieties (Figure 2B). When K = 2, the Sino-Uruguayan soybean populations were divided into two major clusters. When K = 3, the populations were further subdivided into three clusters, with the Uruguayan population subdivided into two subclusters. One subcluster included 6 varieties, while the other included 18 varieties. The PCA confirmed the clear regional separation between the Sino-Uruguayan soybean varieties (Figure 2B). Consequently, K = 2 was selected as the optimal number of clusters (Figure 2C). Then, the average LD decay was calculated for all chromosomes in the two Sino-Uruguayan soybean subpopulations. The LD decay rate varied between the subpopulations, reaching a distance of 190 kb in the Chinese subpopulation compared to a distance of 320 kb in the Uruguayan subpopulation (Figure 2D) (Supplementary Table 2).
Selection interval and gene ontology enrichment analysis
To identify candidate genes associated with agronomic traits, a selection elimination analysis was conducted on the 46 Sino-Uruguayan soybean germplasm using the ZDX1 soybean array. To obtain high-quality SNPs, an estimation was performed on the soybean SNP set, retaining 96,446 SNPs with a MAF greater than 5%. Candidate genes for different traits were identified based on functional annotations within the selection-affected interval. By performing selection elimination analysis on the Sino-Uruguayan soybean germplasm, the Manhattan plot based on Fst showed 2,911 selected genes that were significantly enriched at the top 5% level (Figure 3A). To further verify the Fst results, an allele frequency (AF) analysis was performed on the Sino-Uruguayan soybean germplasm by observing gene frequency changes within the population, and based on the Manhattan plot showed that there were 1,804 genes significantly enriched for selected genes at the top 5% level (Figure 3B). Nucleotide polymorphisms (p) were the main measure of genetic diversity. In the analysis of p in the Sino-Uruguayan soybean germplasms, the p value of Uruguayan soybean varieties was 502 genes selected at the top 5% level (Figure 3C), and the nucleotide diversity p value of Chinese soybean varieties was 384 genes selected at the top 5% level (Figure 3D).
For a more in-depth analysis of the functions of the selected genes, GO enrichment analysis was conducted on the genes selected (Supplementary Table 3). Specifically, GO enrichment was performed on genes selected through the Fst analysis, revealing 4 GO terms in the biological process (BP) category. The annotation results indicated that the variant genes were enriched in biological processes such as glycosyl compound metabolism (GO: 1901657) and nucleoside metabolism (GO: 0009116). GO enrichment of genes selected through the AF analysis yielded 48 GO terms in the BP category. The variant genes were found to be enriched in biological processes such as glycosyl compound metabolism (GO: 1901657), trehalose metabolism (GO: 0005991), glutamate metabolism (GO: 0006536), disaccharide biosynthetic processes (GO: 0046351), and oligosaccharide biosynthetic processes (GO: 0009312). The p analysis of the selected genes in Chinese soybeans, coupled with the GO enrichment analysis, revealed 3 GO terms in the BP category. The variant genes were predominantly associated with biological processes such as chloride transport (GO: 0006821) and anion transport (GO: 0006820). Similarly, GO enrichment analysis of selected genes in the Uruguayan soybeans through the p analysis identified 20 enriched GO terms in the BP category. These genes were mainly related to biological processes such as dolichol-linked oligosaccharide biosynthetic processes (GO: 0006488), protein N-linked glycosylation (GO: 0006487), cellular lipid metabolism (GO: 0044255), oligosaccharide-lipid intermediate biosynthetic processes (GO: 0006490), protein glycosylation (GO: 0006486), and glycosylation (GO: 0070085). Based on the above results, it appears that the selected genes regulate multiple complex growth and development processes in soybeans, and may be involved in various metabolic and biosynthesis processes through various cellular regulatory mechanisms, thus leading to differences in seed-related characteristics, such as the protein, oil and sugar contents, between Sino-Uruguayan soybean germplasm.
Selected genes
In this study, a window value of 10 kb and a step size of 5 kb were employed for AF, Fst, and p analyses on the Sino-Uruguayan soybean germplasm. Within the selected intervals, 15 known functionally relevant genes were identified (Supplementary Table 4). Notably, GmWRKY12 and GmLEA2-96|GmSYP24 were associated with drought, while ELF3/J, GmGI, GmphyA3, and GmFT2a were related to flowering. GmTFL1b was associated with growth habits, while GmMFT, GmDGAT1b, and GmbZIP123 were linked to oil content. GmSSS1 was found to be associated with seed weight, while NSF07, GmSHMT08, GmSNAP11, and GmSNAP18 were related to the soybean cyst nematode (SCN).
To further analyze the differences in the selected genes between Sino-Uruguayan soybean germplasm, SNP allele frequency analysis was conducted on 15 selected genes (Figures 4-6; Supplementary Figure 2). Among these, GmWRKY12, GmLEA2-96|GmSYP24, GmGI, and GmTFL1b had both allele A and allele G in Sino-Uruguayan soybean germplasm. ELF3/J, GmSSS1, and GmSNAP11 had allele C and allele T, while GmSHMT08 and GmSNAP18 contained allele C and allele G. NSF07, GmphyA3, and GmFT2a had allele A and allele C, allele A and allele T, and allele G and allele T, respectively. Candidate genes associated with the oil content, seed weight, and other agronomic traits were identified within the selected genomic regions. Notable genes included: GmbZIP123 which is involved in seed oil biosynthesis. Different allelic variants of this gene were associated with variations in oil content between the Sino-Uruguayan soybean varieties. Further, GmMFT, which participates in the regulation of the seed oil content. Significant differentiation in haplotype frequencies between Sino-Uruguayan soybean germplasm was observed. In addition, GmDGAT1b, which influences the fatty acid composition by increasing the oleic acid levels. Allele frequency differences between Sino-Uruguayan soybean germplasm contributed to oil content variation. Finally, GmSSS1, which is associated with the soluble sugar content of seeds.
Variations in this gene were correlated with differences in the soluble sugar content between the two groups.
Oil-related genes
Based on the above phenotypic data, it was evident that the oil content in the Uruguayan soybean germplasm was significantly higher than that in the Chinese soybean germplasm. Therefore, a detailed analysis of the SNP allele frequencies of three genes within the selected interval that contributed to the difference in oil content between Sino-Uruguayan soybean germplasm was conducted (Supplementary Table 5). The gene GmMFT (Glyma.05G244100)located on chromosome 5 showed a distribution frequency of allele A of 27.27% and allele C of 72.73% in the Chinese soybean germplasm, whereas only allele A was present in the Uruguayan soybeans (Figure 4A). Further analysis within a resequenced population of 1,856 soybean samples, containing 775 soybean germplasm with allele A and 435 with allele C, revealed significant differences in the protein and oil contents. In the protein content analysis, allele C was significantly higher than allele A (Figure 4B), while in the oil content analysis, allele A was significantly higher than allele C (Figure 4C). Statistical analysis of GmMFT with alleles A and C showed that this gene was selected for high oil and low protein varieties in both Chinese varieties and globally bred soybean varieties (Figure 4D). GmDGAT1b (Glyma.17G053300)located on chromosome 17 exhibited a distribution frequency of allele A of 15.79% and allele C of 84.21% in the Chinese soybean germplasm, while in the Uruguayan soybean germplasm, allele A had a higher frequency (78.26%) and allele C had a slightly lower frequency (21.74%) (Figure 5A). Similar to GmMFT, analysis of the protein and oil contents in a resequenced population of 1,856 soybean samples, with 432 soybean germplasm having allele A and 289 allele C, revealed consistent results, with a higher protein content for allele C and higher oil content for allele A (Figures 5B, C). This gene was also selected for high oil and low protein varieties in both Chinese and globally bred soybean varieties (Figure 5D). GmbZIP123 (Glyma.06G010200)located on chromosome 6 exhibited a distribution frequency of allele T of 23.81% and allele G of 76.19% in the Chinese soybean germplasm, while only allele T was present in the Uruguayan soybean germplasm (Figure 6A). Analysis of the protein and oil contents in a resequenced population of 1,856 soybean samples, with 614 soybean germplasm having allele T and 556 with allele G, revealed a higher protein content for allele G and higher oil content for allele T (Figures 6B, C). This gene was selected for high protein and low oil varieties in landraces and high oil and low protein varieties in both Chinese and globally bred soybean varieties (Figure 6D).
To further confirm that the difference in the oil contents between the Sino-Uruguayan soybean germplasm is attributed to these three genes (GmMFT, GmDGAT1b, and GmbZIP123), a differential analysis of the protein and oil contents was conducted on varieties with haplotypes AAT, AAG, ACT, CAT, and CCG in a resequenced population of 1,856 soybean samples. In the protein content differential analysis, the results revealed that the CCG haplotype was significantly higher than the AAT haplotype (Figure 7A), while in the oil content differential analysis, the AAT haplotype was significantly higher than the CCG haplotype (Figure 7B). Therefore, the AAT haplotype increased the oil content, while the CCG haplotype increased the protein content. In Chinese landraces, the haplotype distribution revealed that in the Huanghuaihai and southern varieties, the CCG haplotype was more prevalent than the AAT haplotype, whereas in northeastern soybeans, the AAT haplotype was more predominant (Figure 7C). This suggests that in Chinese landraces, the selection trend is for a higher protein content in soybeans from the Huanghuaihai region and southern varieties, while northeastern soybeans exhibit a higher oil content. For inbred varieties, the haplotype distribution of AAT and CCG was consistent with the overall trend in Chinese landraces. Specifically, northeastern soybeans and soybeans from other countries predominantly had the AAT haplotype, while soybeans from the Huanghuaihai region and southern varieties had a higher proportion of the CCG haplotype (Figure 7D). This indicates that for inbred varieties, the selection trend was for higher oil contents in northeastern soybeans and soybeans from other countries, while southern Chinese soybeans had a higher protein content. Given the phenotypic data presented above, where Uruguayan soybeans were mostly high-oil and low-protein varieties, these results suggest that to achieve complementary advantages between the Sino-Uruguayan soybean germplasm, it may be beneficial to cultivate high-protein varieties similar to those found in the Huanghuaihai region of southern China and in Uruguay.
Phenotypic differences between Sino-Uruguayan soybeans
Most agronomic traits are easily influenced by environmental factors. This means that phenotypic data are unable to accurately reflect the genetic diversity of entire populations (Hu et al., 2000). The oil content is controlled by both environmental and genetic factors (Pathan et al., 2013). It has been shown that soybean kernels grown in Turkey differ in oil content, with the oil content variability ranging from 18.29% to 23.06%; the highest oil content was found in the Suluova and Bafra regions (Arslanoglu et al., 2011). Additionally, research by Teng et al. ( 2017) revealed significant differences in soybean grain oil contents among different varieties grown in China. In this study, a significant difference in the oil content between Sino-Uruguayan soybean germplasm was observed, with Uruguayan soybeans having a markedly higher oil content than Chinese soybeans. The protein content of soybean seeds varies as a function of genotype and may be influenced by environmental conditions, planting locations, and sowing conditions (Li et al., 2004). In China, soybeans planted in the Huanghuai region and southern multi-cropping areas have higher protein contents than soybeans planted in northeastern China (Liu J. et al., 2017;Wang et al., 1998). Rotundo et al. (2016) found that soybeans grown in the southern United States generally have a higher protein content than those grown in the north. In contrast, this study compared the protein quality of Sino-Uruguayan soybeans in the same environment and found that the protein content of Uruguayan soybean germplasm was still significantly lower than that of Chinese soybeans This suggests that differences in genotypes may lead to differences in protein content. Qi et al. (2022) found that the main components of soluble sugars in soybean grains are correlated with latitude, with the geographical origin of soybean grains affecting the composition of soluble sugars. Matei et al. ( 2017) conducted a sugar content analysis of soybeans from Brazil and revealed a strong genotype and environment interaction for sucrose, glucose, raffinose, and stachyose contents in Brazilian environments. The results of this study also suggest that the significant differences in sugar contents between Sino-Uruguayan soybean germplasm may be due to genotype variations. Azam et al. (2021) analyzed phenotypic traits in soybean germplasms from China and the United States, showing that the average oil content (20.5%) and soluble sugar content (109.0 mg/g) in American soybeans were higher than those in Chinese soybeans (average oil content of 19.5% and soluble sugar content of 107.4 mg/g), while the average protein content in American soybeans (40.2%) was lower than that in Chinese soybeans (42.4%). Consistent with these findings, our study showed significant differences in protein, oil, and soluble sugar traits between Sino-Uruguayan soybean germplasm, with a higher protein content in Chinese soybeans and higher oil and total soluble sugar contents in Uruguayan soybeans. Additionally, this study identified differences in genes related to drought resistance, flowering, and SCN traits between the Sino-Uruguayan soybean populations, warranting further investigation into whether these differences result in observable phenotypic variations.
Genetic structure and gene differentiation as the basis of phenotypic variation
China, as the center of origin of soybeans, possesses rich soybean resources. Soybean germplasm resources disseminated from China have facilitated the breeding of new soybean varieties worldwide, contributing significantly to the development of the global soybean industry and sustainable protein production (Guo et al., 2022). Soybean cultivation in different countries leads to distinct genetic foundations. An analysis by Potapova et al. (2023) of the population structure of 103 soybean accessions from western Siberia and 72 soybean accessions from Russia revealed four taxa, with two clusters primarily composed of samples from breeding varieties in western Siberia and the third and fourth clusters containing varieties from the Far East and Europe, respectively. Nawaz et al. (2021) clustered 297 wild seed samples from Southeast Asia (89 from China, 95 from Korea, 97 from Japan, and 16 from far East Russia) into three clusters representing China, Japan, and Korea. Additionally, an analysis of 207 seed samples from different countries representing the European gene bank showed that genetic diversity was broader in United States soybean varieties and Austrian soybean varieties but narrower in Swiss and Croatian soybean varieties. A cluster analysis revealed two main clusters, consistent with the results of the structure analysis (Andrijanicé t al., 2023). Moreover, Yamanaka et al. (2007) conducted a cluster analysis of 272 soybean varieties (194 from China, 59 from Japan, and 19 from Brazil), revealing that Chinese and Japanese soybean varieties were not independent but had relatively distant genetic distances, while Brazilian varieties were genetically distant from varieties from the other two countries, forming a cluster with a greater genetic distance from the gene bank of the other two countries. Furthermore, Maldonado Dos Santos et al. (2022) found that the genetic basis of Brazilian soybean varieties was narrower than that of United States soybean varieties in a study involving 235 Brazilian soybean varieties and 675 United States soybean varieties. The population structure analysis of the phenotypic traits of 46 Sino-Uruguayan soybean varieties in Sino-Uruguayan soybean germplasm in this study also revealed clear differentiation into two clusters, highlighting the distinct genetic foundations, genetic diversity, and population structures of soybean germplasm from different countries.
Population-specific differences in LD decay and the Chinese soybean population's enhanced selection intensity may also contribute to these overall differences. Previous studies have suggested that Chinese local varieties generally exhibit greater genetic diversity and faster LD decay rates (Li et al., 2020). This study similarly showed that the LD decay rate in the Chinese soybean population was faster than that in the Uruguayan soybean population (Figure 5). Despite Sino-Uruguayan soybeans being grown in the same environment, the population structures of Sino-Uruguayan soybean varieties were distinct. The significant differences in traits such as the protein content, oil content, 100grian weight, and soluble sugar content between Sino-Uruguayan soybean varieties confirm the effects of natural and artificial selection. Genetic loci associated with the traits under selection could lead to phenotypic differences between populations from the two countries. This study identified differences in allelic frequencies in genes such as GmbZIP123, GmDGAT1b, GmMFT, and GmSSS1, contributing to changes in resources between Sino-Uruguayan soybean germplasm. The genetic diversity of soybeans in China and Uruguay needs to be further expanded in future breeding work, in order to provide a basis for the innovative utilization of soybean germplasm in the future.
Identification of new genes
During soybean domestication, certain genes associated with specific traits were selected, leading to a significant reduction in region-specific genetic diversity. A selective sweep analysis can be employed to locate these selected regions, and, in conjunction with previously identified loci, can help infer differences between populations or aid in the discovery of new genes (Wen et al., 2015;Wang et al., 2017). The results of this study revealed substantial genetic differences between Sino-Uruguayan soybean germplasm. A selective sweep analysis, utilizing Fst, p, and AF, was conducted on the 46 Sino-Uruguayan soybean germplasm. This analysis minimizes false positives, facilitating the localization and genetic analysis of regions. Furthermore, due to the limited number of chip sites used in this study, resequencing was needed to enrich this variation. In addition, this study revealed significant differences in seed-related traits such as the oil content, protein content, 100grian weight, and soluble sugar content, and identified genes associated with these traits within the selected interval: GmWRKY12, GmLEA2-96|GmSYP24, ELF3/J, GmGI, GmphyA3, GmTFL1b, GmMFT, GmbZIP123, GmDGAT1b, GmSSS1, GmFT2a, NSF07, GmSHMT08, GmSNAP11, and GmSNAP18. This provides a basis for exploring new genes. Zhu et al. (2022) found that GmSSS1 (Glyma.19G196000), a gene controlling grain size in soybeans, had an increased 100-grain weight when glutamate was replaced with glutamine at residue 182 of its encoded protein. This study also showed that the GmSSS1 (Glyma.19G196000) gene controlled the 100-grain weight. A genome-wide association study of 1800 soybean germplasm resources by Duan et al. (2022) revealed that the natural allelic variation in GmST05 (Seed Thickness 05) in soybean germplasm mainly controlled the seed thickness and size. To date, several types of transcription factors identified through gene-gene co-expression analysis (including zinc finger, Dof, and bZIP types) have been proven to regulate lipid biosynthesis in soybean seeds (Song et al., 2013;Li et al., 2017;Lu et al., 2021). The current study found that GmbZIP123 is a gene related to oil content control in Sino-Uruguayan soybean germplasm. Studies have revealed significant correlations between the oil content and high-oil alleles, as well as latitude. Oil accumulation is environmentally related and achieved through critical genes involved in oil biosynthesis modification (Zhang S. et al., 2023). A recent study by Torabi et al. (2021) discovered that down-regulation of the Glyma.17G053300(GmDGAT1b) gene in the target interval increased the oleic acid level, affecting the fatty acid composition of seeds. Analysis of the genes affecting the oil content of 46 Sino-Uruguayan soybean germplasm identified Glyma.17G053300(GmDGAT1b) as one of the crucial genes contributing to differences in the oil content. Additionally, Zhong et al. (2023) found that the expression levels of Glyma.17G053300 were higher in the early-maturing GZ1 and the late-maturing B13 during seed maturation. This gene encodes a type I diacylglycerol acyltransferase, participating in the last step of TAG biosynthesis. Genetic function, genomic, and bioinformatic studies have speculated that the sugar-to-oil ratio might be adjusted, affecting the fatty acid composition of seeds (Roesler et al., 2016;Zhang G. et al., 2019;Torabi et al., 2021). Cai et al. (2023) demonstrated that increased expression of the GmMFT gene increased the grain oil content and weight. Haplotype analysis showed that GmMFT underwent selection leading to the expansion of cultivated soybean haplotype purity and enrichment of oil-favorable alleles in modern soybean varieties. The results of the present study also suggest that the GmMFT gene contributes to the differences in the oil contents of Sino-Uruguayan soybean germplasm. Zhang et al. (2020) showed that a dinucleotide CC deletion at the C-terminus of the GmSWEET39 gene was strongly associated with a high oil and low protein content, indicating pleiotropic effects on the protein and oil content, and demonstrated that GmSWEET39 has a dual function of improving the oil and protein content. GmFT2a is one of the 12 flowering locus T (FT) genes found in soybeans, functioning as the causal gene for the E9 locus, which controls flowering (Cai et al., 2018). The present study similarly found that the GmFT2a gene controls flowering-related traits in Sino-Uruguayan soybean germplasm. However, comparative analyses of the Sino-Uruguayan soybean germplasm indicated that a large number of unknown genes are still involved in the Sino-Uruguayan soybean population's divergence. For example, the 100-grain weight of GmSSS1 was only selected in the enriched region, but it could not explain the differences in weight alone. Hence, it is possible that new genes may be revealed through the configuration of hybrid combinations of more distantly related Sino-Uruguayan soybean germplasm. Overall, this research contributes to the understanding of soybean genetic diversity and the evolutionary processes shaping phenotypic traits. By utilizing germplasm resources from different regions, breeders can develop superior soybean varieties that can meet the demands of both local and global markets.
Conclusion
This study compared seed-related traits and genetic diversity between Sino-Uruguayan soybean germplasm, revealing significant differences in key phenotypic traits and identifying genomic regions under selection. The results provide valuable insights into the genetic basis of these traits and offer potential targets for soybean breeding programs. The higher oil and soluble sugar contents of Uruguayan varieties, combined with the genetic diversity analysis, suggest specific genes and genomic regions that can be targeted to improve soybean yield and quality. These findings underscore the importance of international germplasm exchange and collaboration for enhancing crop productivity and ensuring food security.
The reviewer YH declared a past co-authorship with the authors YL, ZL and LQ to the handling editor.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
FIGURE 1 Box plots of grain traits of cultivars from Uruguay and China.(A) Distribution of 100-grain weight.(B) Distribution of protein content.(C) Distribution of oil content.(D) Distribution of total soluble sugar.**, P <0.01, according to Student's t-test.
FIGURE 2 Genetic diversity between Sino-Uruguayan soybeans.(A) Scatter plots of principal component analysis (PCA) of Chinese (CN) and Uruguayan (UY) soybean cultivars. The green circle represents the Chinese cultivars, and the blue circle represents the Uruguayan cultivars.(B) Neighbor-joining trees of soybean varieties. Green and blue branches represent Chinese and Uruguayan varieties, respectively.(C) Genetic structure of Sino-Uruguayan soybean cultivars. The tree branches in green and blue represent Chinese cultivars and Uruguayan cultivars, respectively. Population structure at K = 2, in which dark red represents the Chinese soybean subgroup and dark green represents the Uruguayan soybean subgroup.(D) Comparison of linkage disequilibrium (LD) decay between Sino-Uruguayan soybean cultivars. The blue line represents Chinese cultivars, the purple line represents Uruguayan cultivars, and the red line represents Sino-Uruguayan soybean cultivars.
FIGURE 4 SNP analysis of the GmMFT locus in soybean populations.(A) Distribution frequencies of SNPs in the Sino-Uruguayan soybean germplasm.(B) Comparison of the protein contents with different SNP alleles in the 1,856 soybean accessions.(C) Comparison of the oil contents with different SNP alleles in the 1,856 soybean accessions.(D) Distribution frequencies of SNP alleles in landrace and cultivars of 1,856 soybean accessions.**, P < 0.01, according to Student's t-test.
FIGURE 5 SNP analysis of the GmDGAT1b locus in soybean populations.(A) Distribution frequencies of SNPs in the Sino-Uruguayan soybean germplasm.(B) Comparison of the protein contents with different SNP alleles in the 1,856 soybean accessions.(C) Comparison of the oil contents with different SNP alleles in the 1,856 soybean accessions.(D) Distribution frequencies of SNP alleles in landrace and cultivars of 1,856 soybean accessions.**, P < 0.01, according to Student's t-test.
FIGURE 6 SNP analysis of the GmbZIP123 locus in soybean populations.(A) Distribution frequencies of SNPs in the Sino-Uruguayan soybean germplasm.(B) Comparison of the protein contents with different SNP alleles in the 1,856 soybean accessions.(C) Comparison of the oil contents with different SNP alleles in the 1,856 soybean accessions.(D) Distribution frequencies of SNP alleles in landrace and cultivars of 1,856 soybean accessions.**, P < 0.01, according to Student's t-test.
FIGURE 7 SNP analysis of the GmMFT, GmDGAT1b, GmbZIP123 loci in soybean populations.(A) Comparison of the protein contents with different SNP alleles in the 1,856 soybean accessions.(B) Comparison of the oil contents with different SNP alleles in the 1,856 soybean accessions.(C) Distribution frequencies of the different SNP alleles in landrace.(D) Distribution frequencies of the different SNP alleles in cultivars. AAT represents the GmMFT gene with allele A, the GmDGAT1b gene with allele A, and the GmbZIP123 gene with allele T. CCG represents the GmMFT gene with allele C, the GmDGAT1b gene with allele C, and the GmbZIP123 gene with allele G. The same goes for the others. Error bars represent SD. Different letters indicate significant differences at P < 0.05.
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Domain: Agricultural and Food Sciences
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A post-GWAS confirming the genetic effects and functional polymorphisms of AGPAT3 gene on milk fatty acids in dairy cattle
People are paying more attention to the healthy and balanced diet with the improvement of their living standards. Milk fatty acids (FAs) have been reported that they were related to some atherosclerosis and coronary heart diseases in human. In our previous genome-wide association study (GWAS) on milk FAs in dairy cattle, 83 genome-wide significant single nucleotide polymorphisms (SNPs) were detected. Among them, two SNPs, ARS-BFGL-NGS-109493 and BTA-56389-no-rs associated with C18index (P = 0.0459), were located in the upstream of 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) gene. AGPAT3 is involved in glycerol-lipid, glycerol-phospholipid metabolism and phospholipase D signaling pathways. Hence, it was inferred as a candidate gene for milk FAs. The aim of this study was to further confirm the genetic effects of the AGPAT3 gene on milk FA traits in dairy cattle. Through re-sequencing the complete coding region, and 3000 bp of 5′ and 3′ regulatory regions of the AGPAT3 gene, a total of 17 SNPs were identified, including four in 5′ regulatory region, one in 5′ untranslated region (UTR), three in introns, one in 3′ UTR, and eight in 3′ regulatory region. By the linkage disequilibrium (LD) analysis with Haploview4.1 software, two haplotype blocks were observed that were formed by four and 12 identified SNPs, respectively. Using SAS9.2, we performed single locus-based and haplotype-based association analysis on 24 milk FAs in 1065 Chinese Holstein cows, and discovered that all the SNPs and the haplotype blocks were significantly associated with C6:0, C8:0 and C10:0 (P < 0.0001–0.0384). Further, with Genomatix, we predicted that four SNPs in 5′ regulatory region (g.146702957G > A, g.146704373A > G, g.146704618A > G and g.146704699G > A) changed the transcription factor binding sites (TFBSs) for transcription factors SMARCA3, REX1, VMYB, BRACH, NKX26, ZBED4, SP1, USF1, ARNT and FOXA1. Out of them, two SNPs were validated to impact transcriptional activity by performing luciferase assay that the alleles A of both SNPs, g.146704373A > G and g.146704618A > G, increased the transcriptional activities of AGPAT3 promoter compared with alleles G (P = 0.0004). In conclusion, our findings first demonstrated the significant genetic associations of the AGPAT3 gene with milk FAs in dairy cattle, and two potential causal mutations were detected.
Genome-wide association study (GWAS) is a commonly used strategy to identify potential genetic variants underlying important complex traits in human and domestic animals. So far, some candidate genes and QTL regions for milk production traits have been detected with GWA studies in dairy cattle, such as DLGAP1, AP2B1, SCD, BTA11 (1.59-3.37 Mb), and BTA3 (70.34-73.69 Mb) [8][9][10][11][12][13]. In our previous GWAS for milk FAs in Chinese Holstein cows, 83 genome-wide significant single nucleotide polymorphisms (SNPs) were detected in total [12], in which, two SNPs (ARS-BFGL-NGS-109493 and BTA-56389-no-rs) associated with C18index (P = 0.0459), were located in the upstream of 1-acylglycerol-3-phosphate Oacyltransferase 3 (AGPAT3) gene. In addition, we performed a joint GWAS for milk FAs in combined Chinese and Danish Holstein populations and found that a chromosome-wide significant QTL region of 146. .31 Mb on BTA1 was associated with C18:0 [13]. The AGPAT3 gene was nearby this region with approximately 400 kb. 1-acylglycerol-sn-glycero 3-phosphate acyltransferase (AGPAT), encoded by the AGPAT3 gene, is one of the isoforms of AGPATs [14] and is involved in the glycerolipid (ko00561) and glycerophospholipid metabolisms (ko00564), and phospholipase D signaling pathway (ko04072). Mammalian AGPAT catalyzed the acylation of lysophosphatidic acid to form the phosphatidic acid that was the precursor of all glycerplipids [14]. Therefore, it was implied that the AGPAT3 gene was a promising candidate gene for milk FA traits in dairy cattle. The purpose of the present study was to further detect whether the AGPAT3 gene had significant genetic effects on milk FAs in a Chinese Holstein cow population.
SNP identification and genotyping
Based on the genomic sequence of bovine AGPAT3 gene (Gene ID: 506607), 14 pairs of primers (Table S1) were designed by the Primer 3 version 4.0 ( [URL]. ee/primer3-0.4.0/) and were synthesized in the Beijing Genomics Institute (Beijing, China) to amplify all the exons with partial adjacent intron region, and 3000 bp of 5′ and 3′ regulatory regions. As previously descripted [15], two DNA pools were constructed and the polymerase chain reaction (PCR) amplifications were performed with each DNA pool as template. To identify potential polymorphisms, the PCR amplification products were bidirectionally sequenced with an ABI3730XL DNA analyzer (Applied Biosystems, Foster, CA, USA). Then, the identified SNPs were genotyped for the 1065 cows by the matrix-assisted laser-desorption/ionization time of flight mass spectrometry (MALDI-TOF MS, Sequenom MassARRAY, Bioyong Technologies Inc., HK).
Linkage disequilibrium (LD) and association analyses
We estimated the LD among the identified SNPs of AGPAT3 gene with Haploview 4.1 (Broad Institute, Cambridge, MA, USA).
For association analysis, the 1065 cows were traced back to three-generation pedigrees to construct the kinship matrix (A-matrix) by SAS 9.2 (SAS institute, Cary, NC, USA), so that 3335 individuals were totally included. Single-locus and haplotype-based associations with 24 kind of milk FAs were performed by the following mixed animal model with SAS 9.2: Here, Y ijklm is the phenotypic value of each milk fatty acid trait; μ is the overall mean; G i is the fixed effect corresponding to the genotype or haplotype combination of individual i; h j (j = 1-23) and l k (k = 1-4) were the fixed effect of farm j and stage of lactation ll, respectively; a l is the random polygenic effect; M m (m = 1-293) is the fixed effect of age at calving m; b is the regression coefficient of covariate M; and e ijklm is the random residual. Further, we calculated the additive effect (a), dominant effect (d), and allele substitution effect (α) according to a [17]. Here, AA, AB and BB were the least square means of milk FAs corresponding to the genotypes, and p and q were the frequencies of allele A and B, respectively.
Recombinant plasmid construction and luciferase assay
To detect the allele-specific effects of the SNPs g.146702957G > A, g.146704373A > G, g.146704618A > G, and g.146704699G > A on the transcriptional activity of AGPAT3 gene, eight luciferase reporter gene fragments (G and A of g. 146702957G > A; A and G of g.146704373A > G; A and G of g.146704618A > G; and G and A of g.146704699G > A) corresponding to the eight alleles of the four SNPs (Fig. 1a) were designed and synthesized (Genewiz, Suzhou, China). The eight fragments with the KpnI and Nhel restriction sites at the 5′ and 3′ termini, respectively, were cloned into the pGL4.14 luciferase assay vector (Promega, Madison, USA). In addition, all the plasmids were purified by the Endo-free Plasmid DNA Mini Kit II (OMEGA, omega bio-tek, Norcross, Georgia, USA), and were sequenced to confirm the integrity of each construct's insertion.
The human embryonic kidney (HEK) 293 T cells were cultured with Dulbecco′s modified Eagle′s medium (Gibco, Life Technologies) and 10% fetal bovine serum (Gibco) at 37°C in a humidified incubator containing 5% CO 2 . Before transfection, about 2 × 10 5 cells were seeded in each 24-well plate. For eight luciferase reporter gene fragments of g. 146702957G > A, g.146704373A > G, g.146704618A > G and g.146704699G > A, 500 ng constructed plasmid was co-transfected along with 10 ng pRL-TK Renilla luciferase reporter vector (Promega) into each well. All the experiments were performed in three replicates for each construct. Approximate 48 h after transfection, the cells were harvested and the activity of both firefly and Renilla luciferases were measured with a Dual-Luciferase Reporter Assay System (Promega) on a Modulus microplate multimode reader (Turner Biosystems, CA, USA). The average statistic of three replicates were calculated as the normalized luciferase data (Firefly/Renilla).
Estimation of LD among the identified SNPs of AGPAT3
We used the haploview 4.1 to estimate the LD among these 17 SNPs, and observed two haplotype blocks
Prediction of TFBSs changing caused by the SNPs in 5′ regulatory region
By performing Genomatix software suite v3.9, it was predicted that that four SNPs in the 5′ regulatory region of AGPAT3 gene, g.146702957G > A, g.146704373A > G, g.146704618A > G and g.146704699G > A altered the binding sites of some transcription factors ( Table 4). The allele A of g.146702957G > A created a TFBS for SMAR CA3 (SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 3) and REX1 (REX1 transcription factor; zinc finger protein 42), respectively, and the allele G created a TFBS for VMYB (v-Myb, variant of AMV v-myb). The alleles A and G of g.146704373A > G created a TFBS for BRACH (Brachyury) and NKX26 (NK2 homeobox 6, Csx2), respectively. The allele G of g.146704618A > G created two TFBSs for ZBED4 (Zinc finger, BED-type containing 4; GC-box binding sites) and SP1 (Stimulating protein 1, ubiquitous zinc finger transcription factor). The allele G of g.146704699G > A created two TFBSs for USF1 (Upstream stimulating factor 1) and ARNT (AhR nuclear translocator homodimers), and the allele A created a TFBS for FOXA1 (Forkhead box protein A1, hepatocyte nuclear factor 3-alpha (HNF-3-alpha)).
Exploring for luciferase activity altered by the SNPs in 5′ regulatory region
To validate the TFBS prediction results, the luciferase assay was further performed for the four SNPs (g.146702957G > A, g.146704373A > G, g.146704618A > G and g.146704699G > A) (Fig. 1b). We observed that the luciferase activities of six constructs containing g.146704373A > G, g.146704618A > G, and g.146704699G > A, were significantly higher than that of the pGL4.14 empty vector (P < 0.0007) and blank control (P < 0.0008), while g.146702957G > A did not (P > 0.05). Further, the luciferase activity of alleles A of g.146704373A > G and g.146704618A > G were significantly higher than that of their alleles G (P = 0.0004; Fig. 1b). The luciferase activity of allele G of g.146704699G > A was higher than that of allele A, while not significant (P > 0.05). These results indicated that the transcriptional activity of the AGPAT3 gene significantly altered by g.146704373A > G and g.146704618A > G might be the reasons strongly impacted on FAs.
Discussion
This study was a follow-up investigation for our previous GWAS on milk FAs in Chinese Holstein [12]. AGPAT3 is involved in pathways related to lipid metabolism (ko00561, ko00564 and ko04072). In human, docosapentaenoic acid as the substrate of AGPAT3 protein transfers a fatty acid in sn-2 position of lysophosphatic acid, a step in the phospholipid biosynthesis pathway [19]. Here, we detected that the AGPAT3 gene mainly impacted the medium-chain milk FAs in dairy cattle.
Mammalian AGPAT catalyzed the acylation of lysophosphatidic acid to form the phosphatidic acid, which was the precursor of all glycerplipids [14]. For the AGPAT families, AGPAT1 had significant association with milk FA CLA [20], and AGPAT6 was strongly associated with C14:0, C16:0, C10:1, C12:1, C14:1 and C16:1 [21]. In our previous GWA studies [12,13], AGPAT3 gene was identified as a candidate for two milk FAs, C18index and C18:0. In this study, using an independent Chinese Holstein population that was different from the previous GWA studies, we also observed that AGPAT3 showed a significant genetic effect on C18index and C18:0. In addition, our results revealed that the AGPAT3 had strong associations with C6:0, C8:0 and C10:0. Overall, the previous GWASs and this study suggested that AGPAT3 gene had significantly genetic effects on milk FAs.
Sequences-specific binding of transcription factors to the regulatory regions on the DNA is a key regulatory mechanism that affects gene expression and hence heritable phenotypic variation [22,23]. Eukaryotic regulatory sequences, including enhancers and promoters, are typically between a hundred and several thousand base pairs in length, and can harbor many TFBSs [24]. It is essential to understand the evolution dynamics of transcription factor binding for understanding the evolution of gene regulation [25]. In this study, by prediction, g.146704373A > G changed the bindings of transcription factors (TFs) BRACH and NKX26, and g.146704618A > Note: LSM least square mean. SE standard error. P indicates the significances of the association analysis between the haplotype block and milk fatty acid traits. P is the raw value. * : P < 0.05. ** : P < 0.01. Different letter (small letters: P < 0.05; capital letters: P < 0.01) superscripts indicate significant differences among the haplotype combinations. The number in the brackets represents the number of cows for the corresponding haplotype combination G altered the bindings of TFs ZBED4 and SP1. Further, we used the luciferase assay to verify that the alleles A of g.146704373A > G and g.146704618A > G strongly increased the transcription activity of the AGPAT3 gene than the alleles G. Previous studies showed that BRACH as a regulatory factor directly activated downstream mesoderm-specific genes to exert its mesoderminducing effects [26], and NKX26 restrained the transcription activity of Cx40 through the F151L missense mutation to impact the heart development [27]. ZBED4 could act as a co-repressor of nuclear hormone receptors (NHRs) by its LXXLL motifys in cones [28]. Through interfering with the recruitment of SP1 to ZNF132 promoter region, methylation of SP1-binding site can inhibit ZNF132 transcriptional expression to impact the tumor in the development of esophageal squamous cell carcinoma [29]. These reports have indicated that the TFs BRACH, NKX26, ZBED4 and SP1 could activate or repress the expression of their target genes. Based on our association analysis, the cows with the AA genotypes of g.146704373A > G and g.146704618A > G of AGPAT3, yielded significantly lower contents of C6:0 and C8:0 than those with GG genotypes. According to above, we deduced that the BRACH as a TF might activate AGPAT3 gene transcription activity by binding to the allele A of g.146704373A > G thereby reducing the contents of C6:0 and C8:0, while, the transcription factors NKX26, ZBED4 and SP1 might have the contrary effects. Nowadays, genomic selection is the main implication for dairy cattle breeding, where the genomic chips are used. Among the SNP markers in these chips, most of them were collected from the current SNP database and almost evenly distributed across the whole genome. Hence, g.146704373A > G and g.146704618A > G of AGPAT3 as the potentially causal mutations could be put into the SNP chip instead of used in marker selection to increase selection efficiency in some specific dairy cattle populations to improve the contents of milk FAs.
Conclusion
In conclusion, through a post-GWAS approach, our study firstly indicated there were significant genetic associations between the AGPAT3 gene and milk FAs in dairy cattle. Further, we found that two SNPs in 5′ regulatory region (g.146704373A > G and g.146704618A > G) changed the transcriptional activity of AGPAT3 implying their potential causal function. These findings provided important molecular information for dairy cattle breeding.
Additional file 1: Table S1. PCR primers information of AGPAT3 gene Additional file 2: Table S2. Additive (a), dominant (d) and allele substitution (α) effects of 17 SNPs on milk fatty acid traits of AGPAT3 gene in Chinese Holstein cows
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Domain: Agricultural and Food Sciences Biology
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Plant-Based Alternatives Need Not Be Inferior: Findings from a Sensory and Consumer Research Case Study with Cream Cheese
Reliance on animal foods must be reduced to improve planetary and human well-being. This research studied plant-based cheese alternatives (PBCA) relative to dairy cheese in a consumer taste test with 157 consumers in New Zealand. A case study approach used cream cheese (commercially available) as the focal product category (2 PBCA, 2 dairy) and implemented a multi-response paradigm (hedonic, sensory, emotional, conceptual, situational). “Beyond liking” insights were established, including drivers of liking (sensory, non-sensory) and sensory drivers of non-sensory product associations. Two consumer segments were identified, of which the largest (n = 111) liked PBCA and dairy samples equally (6.5–6.7 of 9). In this PBCA Likers cluster, the key sensory drivers of liking were ‘creamy/smooth mouthfeel’, ‘dissolves quickly in mouth’, and ‘sweet’, while a significant penalty was associated with ‘mild/bland flavour’. The non-sensory data contributed additional consumer insights, including the four samples being perceived as differently appropriate for 9 of 12 use situations, with PBCA being regarded as less appropriate. In the limited confines of this case on cream cheese, the findings show that PBCA need not be inferior to their dairy counterparts despite a general narrative to the contrary. Of note, the results were obtained among participants who were open to eating a more PB diet but were not vegetarian or vegan.
Introduction 1. Motivation for the Research
Transitioning to a diet that is dominantly plant-based (PB) will significantly benefit environmental well-being, biodiversity, welfare of farm animals, and human health [1][2][3]. Increasingly, consumers are embracing this shift and expecting dietary alternatives that support the PB transition. The development of PB alternatives to animal-based and animalderived foods directly reflects this transition, and the present research is situated in this context. It focuses on PB alternatives to cheese, hereafter PBCA (i.e., PB cheese alternatives), because this product type could be a gateway category to support consumers' PB transition. In a cohort of ~200 Dutch consumers who ate meat less than five times per week, cheese (34%) was listed as one of the top three common substitute foods after fish (79%) and eggs (49%) [4]. In a recent four-country consumer survey (USA, Australia, Singapore and India, n = 2494) by Cardello et al. [5], stated willingness to consume PB alternatives was highest for milk alternatives and lowest for fish alternatives. Willingness to consume was intermediate for two PB meat alternatives but lower than for PBCA. In other words, PBCA was the category of PB alternative foods that participants said they were most willing to consume, after PB milk alternatives. Although consumer segmentation was observed, the majority of participants tended toward higher rather than lower stated willingness to consume PBCA. Thus, it is not highly unrealistic to assume that a significant number of consumers could be willing to eat PBCA if products satisfy sensory quality, nutrition, price, and several
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Objective 1. To measure liking and provide a consumer-centric and extensive characterisation of PBCA through an empirical strategy that compared these to dairy cheese.
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Objective 2. To determine sensory and non-sensory drivers of liking.
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Objective 3. To determine sensory drivers of non-sensory product perceptions.
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Objective 4. To explore determine if consumer groups with different liking/disliking patterns for PBCA existed (i.e., consumer segmentation).
Objective 1
The expectation based on previous research was that PBCA would be moderately or less liked, on average. This drew on past research suggesting that PBCA often have problems with some aspects of sensory quality [15][16][17]. For example, they can have sensory characteristics that are not typically associated with cheese [14], leading to dissatisfaction with the experienced sensory characteristics and unmet product expectations [18]. Studies that report liking data for PBCA confirm this [11,19], but also draw attention to an important fact-that some PBCA have liking scores [11] that are similar to those reported for cow's milk cheeses [20][21][22][23]. Some studies exist where PBCA prepared with novel processing methods and/or ingredient combinations have been positively evaluated using small, convenience-based consumer samples [24,25]. These point to a future of increased consumer acceptability but may not represent the status quo. Pointke et al. [26] provide an example of PBCA acceptance among vegan consumers but also find that such liking scores, on average, are higher than those from consumers following omnivore and flexitarian diets.
Based on the literature cited above, the sensory product characteristics of PBCA and dairy cheese were expected to be different (Objective 1). These different product experiences (hedonic and sensory) would, in turn, lead to different emotional, conceptual, and situational use perceptions for PBCA and dairy variants, as suggested in studies with foods other than cheese [11,27,28] and supported by studies reporting on the sources of food emotions and conceptualisations, and linkages between these non-sensory product perceptions [29,30].
Objective 2
PB alternative products that mimic the sensory properties of non-PB alternatives tend to be preferred by consumers [14,19,31], and for this reason, it was expected that the sensory drivers of liking for PBCA would be those that increase liking of dairy cheese.
Since it has been suggested that more than 1000 types of cheese exist [32] with very different characteristics [9], sensory drivers of liking will be specific to different types of cheese. Nonetheless, they are likely to encompass multiple sensory modalities (appearance, aroma, taste, flavour, texture, mouthfeel, and aftertaste) [20,21,[33][34][35]. This extends to cream cheese (PBCA and dairy) [18,22,36,37]. Although non-sensory drivers of liking have not been widely studied, it was expected that emotions with positive and negative valence would drive liking positively and negatively, respectively [29,38], and emotional activation/deactivation could contribute to product differentiation [39].
Objective 3
The sensory drivers of non-sensory product experiences have also not been widely studied. The reason to study these directly flows from the now widely accepted mindset that sensory and consumer science needs to "go beyond liking" [40,41]. Product experience is about much more than the sensory product characteristics, and it is important to address these, for example, by adopting a multi-response empirical strategy to measure emotional product associations [42], product conceptualisations [30], situational use characteristics [43], attitudes and behavioural intentions [44]. Given the scarcity of related past research, expected findings could not be clearly stated. However, it seemed probable that emotional associations with positive valence would be linked to sensory characteristics associated with positive hedonic experiences, and vice versa [45]. A decrease in emotional activation could be expected for weak, bland, and low flavour strength according to Jaeger et al. [46]. Regarding product conceptualisations, sensory characteristics typically associated with dairy cheese were expected to be perceived as familiar/traditional. Increased situational uses would be linked to sensory characteristics associated with positive hedonic experiences. At a more general level, linkages between desired sensory characteristics and positive, familiar, and versatile non-sensory product associations were expected to help overcome barriers consumers may experience in adopting PB alternative foods [47]. A recent example with yoghurt (PB alternatives, dairy, and PB-dairy blends) [48] illustrated that linkages exist in consumers' minds between sensory characteristics and sustainability concepts with positive drivers of the latter including 'white colour', 'sweet', 'even/smooth' appearance and texture, 'oat-like flavour' and 'coconut flavour'.'Dairy flavour', on the other hand, evoked conceptualisations that were related to 'traditional' and 'authentic' and elicited negative sustainability concepts that were related to 'resource intensive', 'commercially farmed raw materials', and reduced conceptualisation of 'animal friendly'.
Objective 4
Consumer segmentation based on product liking was expected to exist. Considering that individual differences in preference are described for many foods and beverages [49] including dairy-based cheese [21,33,50] and PB alternative foods [51][52][53], interest in the present research was centred on the relative size of segments that liked, rejected, or partially accepted PBCA. Such knowledge is relevant because it helps to determine the magnitude of the change that has to occur for the consumption of PB alternative foods to become the norm rather than the exception.
Case Study and Empirical Approach
Because it is not possible to cover the entire cheese category in a single study, a case study approach was employed as the research strategy. Cream cheese was selected as the focal category, but others could have been selected too. As a category, cream cheese originated in the USA in the 1870s [54]. It is a fresh (or unripened) cheese produced from a blend of milk and cream. The fat content (typically a minimum of 25% in dry matter) combined with a high moisture content [55] is critical for the characteristic soft and spreadable texture of cream cheese [56]. Lactic acid fermentation provides slight acidity and a "diacetylated taste and smell" [37,57]. Traditionally, cream cheese was a plain product with no additional flavourings, but nowadays, multiple flavour variants exist, particularly in the USA, as well as texture variants (firm, soft, airy) [58]. Largely a response to the growing consumer demand for healthier products, cream cheese with a lower fat content have also been formulated [22]. However, techniques for achieving fat reduction tend to result in texture and flavour changes that hinder consumer acceptance [22,57]. Non-dairy (or PB) alternatives to cream cheese also have an extended history, with reports of soy variants being produced in the USA between 1911 and 1970 [59].
Market data for PB alternatives to cream cheese are sparse but suggest that the category is currently very small, and this is within the PBCA category, which, compared to PB alternatives to meat and milk, is already modest [60]. Nonetheless, market projections point to growth. An estimated market value in the USA of USD 45 million in 2019 grew to USD 129 million in 2022, and there are projected estimates of USD 300 million by 2032 [61]. Beyond Western markets, growth is expected for China [62], where cream cheese is gaining some popularity in, for example, tea macchiatos and mooncakes.
To achieve the research aim and address the four objectives, a consumer taste test was conducted. Specifically, 157 consumers assessed four samples of cream cheese, of which two were dairy (cow's milk) and two were PBCA. A trade-off was required between the number of samples, the number of consumers, and the extensiveness of evaluations for each sample, leading to emphasis being placed on the latter of the three criteria. That is, each sample was extensively described to facilitate insights relating to Objective 2 (sensory drivers of liking) and Objective 3 (sensory drivers of non-sensory product perceptions). Compared to Objectives 1 and 4, these two objectives were regarded as providing the most novel scientific insights.
Participants
The 157 participants were New Zealand (NZ) adults with varied socio and economic characteristics who lived in the Auckland region (Table 1). They were listed, by voluntary agreement, on a proprietary database of a professional recruitment firm and were willing to be contacted about participation in product taste tests. All were regular consumers of cheese (monthly or more frequently) and expressed an interest in reducing their meat and dairy consumption (i.e., it was an exclusion criterion to answer 'no' to the statement 'I am not concerned about reducing my meat or dairy intake'). All participants confirmed willingness to taste cheese (dairy and PBCA).(9), where the shown values are expressed as mean ± standard deviation around the mean.
Samples and Sample Presentation 2.2.1. Samples
Four samples were included in the study. Two were dairy cream cheeses (cow's milk) (Dairy1 and Dairy2), and two were PBCA (PBCA1 and PBCA2) (Figure 1). The samples were commercially available in NZ and from different brands. The PBCA samples were coconut oil-based, in line with the dominance of this ingredient in this product category [63]. At the time of the study, these were the only PBCA available in major retail outlets in the cream cheese product category. Additional information about the samples-nutritional composition, ingredients, and average price-can be found in the Supplementary Material. The samples were used as purchased, and no modifications were made before serving to consumers.
Cream cheeses are widely available in NZ retail outlets, and it was possible to obtain both PBCA and dairy variants that were "unflavoured" (or "natural" flavoured) in the sense that additional ingredients had not been added (e.g., herbs, spices). The decision to restrict the samples to a single flavour variant ("natural") was made to increase the likelihood of differences between PBCA and dairy cheese being uncovered without undue influence from variations in flavour.
Sample Preparation and Presentation
The samples were prepared in the mornings on the days of testing and were then covered and stored (~4 °C) until needed. They were removed from the refrigerator and served to participants within 20 min.and at approximately room temperature which aligned with Wendin, Langton, Caous, and Hall [57] and Foguel, Neves Rodrigues Ract, and Claro da Silva [22]. The serving size (approx.10 g) allowed for re-tasting. Each sample was accompanied with a piece of ~5 cm breadstick (Ghiotti, Modea Srl, Italy). The samples were presented in 60 mL transparent glass bowls (odour-free) labelled with randomised numerical codes (Supplementary Material has image).
Responses by Consumers to Tasted Samples
Directed by Objectives 1 to 3, the test ballot was in five sections. Overall acceptability was the first responses and provided on a 9-point fully labelled category scale with 1 = 'dislike extremely' and 9 = 'like extremely' as end-point anchors. Cream cheeses are widely available in NZ retail outlets, and it was possible to obtain both PBCA and dairy variants that were "unflavoured" (or "natural" flavoured) in the sense that additional ingredients had not been added (e.g., herbs, spices). The decision to restrict the samples to a single flavour variant ("natural") was made to increase the likelihood of differences between PBCA and dairy cheese being uncovered without undue influence from variations in flavour.
Sample Preparation and Presentation
The samples were prepared in the mornings on the days of testing and were then covered and stored (~4 • C) until needed. They were removed from the refrigerator and served to participants within 20 min.and at approximately room temperature which aligned with Wendin, Langton, Caous, and Hall [57] and Foguel, Neves Rodrigues Ract, and Claro da Silva [22]. The serving size (approx.10 g) allowed for re-tasting. Each sample was accompanied with a piece of ~5 cm breadstick (Ghiotti, Modea Srl, Roma, Italy). The samples were presented in 60 mL transparent glass bowls (odour-free) labelled with randomised numerical codes (Supplementary Material has image).
Responses by Consumers to Tasted Samples
Directed by Objectives 1 to 3, the test ballot was in five sections. Overall acceptability was the first responses and provided on a 9-point fully labelled category scale with 1 = 'dislike extremely' and 9 = 'like extremely' as end-point anchors.
Second to be elicited were sensory product perceptions. These were obtained using a CATA (check-all-that-apply) question with 12 descriptors (listed in full in Section 3). The terms covered appearance, taste, flavour, texture, and mouthfeel and were based on pilot work and the extant literature [22,55,57,64,65].
The third part of the ballot pertained to emotional associations elicited by the sample. These were obtained using 12 pairs of emotion words (listed in full in Section 3) from the valence × arousal circumplex-inspired emotion questionnaire [66]. The valence dimension was spanned between the word pairs 'happy/satisfied' (positive) and 'unhappy/dissatisfied' (negative), while the arousal dimension was spanned between the word pairs 'passive/quiet' (deactivated) and 'active/alert' (activated). A CATA question list format was used. A conceptual CATA question with 14 terms (listed in full in Section 3) was the fourth ballot section. The terms were identified with input from the literature relating to conceptual profiling and PB alternative products [41].
In the fifth part of the ballot, a CATA question with 12 statements (listed in full in Section 3) captured perceived situational appropriateness. The statements were developed by the authors and based on pilot work and cookbooks [67].
Data Collection
The study was conducted at The New Zealand Institute for Plant and Food Research Limited (Auckland), where participants (in groups of 18 people) during October 2023 attended one 75 min.research session.
Monadic sample presentation was used, with all parts of the ballot being completed before presenting the next sample. Participants had to taste the sample before answering the first question and retaste as needed as they progressed through the ballot. Within CATA questions, the presentation order of terms was balanced both across samples and participants.
Compusense Cloud software (v23, Compusense Inc., Guelph, ON, Canada) was used for data acquisition. Participants were seated in standard sensory testing booths with white lighting for sample assessment. A 30-45 s break between samples helped to manage lab logistics and mitigate sensory fatigue. Water and plain crackers (Arnott's original water crackers, NZ) were available throughout the test for palate cleansing. The temperature in the booths was between 20 and 22 • C.
After completing the cream cheese tasting task, participants completed another tasting task with cheese (not considered further) and a questionnaire with questions relating to cheese liking and frequency of consumption. A few additional tasks without relevance to the stated research objectives were then completed (not considered further). Participant profiling questions were asked as the last part of the research session.
Data Analysis
All analyses were performed in XLSTAT [68]. Unless stated otherwise, a 5% level of significance was used for inference testing.
Sample differences in mean hedonic values (Objective 1) were assessed using a generalised linear model (sample as fixed factor, consumer as random factor) and Tukey's HSD for posthoc tests. Means and standard deviations were calculated for each sample.
For product characterisation (Objective 1), Cochran's Q test was performed for each CATA term, using the Sheskin procedure for posthoc testing. Based on Vidal et al. [69], CATA term citation frequency was interpreted as a proxy for attribute intensity/strength. Separately for sensory, emotional, conceptual, and situational terms, Correspondence Analysis (CA) [70] was performed on the contingency table formed by crossing samples (rows) and CATA terms (columns) [71]. In all instances, the null hypothesis of independence between rows and columns was rejected subsequent to a chi-square test (p < 0.0001). Twodimensional solutions, which accounted for >70% of variance in the data, were retained, and interpreted in the context of 95% confidence ellipses [72] around sample positions.
For each CATA term, penalty/lift analysis was performed to establish its mean impact on liking [71] (Objective 2). The significance of the mean impact was only tested when a threshold value of 10% citation frequency was exceeded.
Logistic regression was used to establish sensory drivers (independent variables) of non-sensory product associations (dependent variables) (Objective 3). Models were estimated for each of the dependent variables and interpreted only when significant at the 1% level according to the criterion of −2 log likelihood (-2LL). Odds ratios (OR) were used to express the effects of predictor variables [73]. When ORs > 1, there is an increased probability of selection of Y (dependent variable) when X (independent variable) is selected. When ORs > 1, there is a increased probability of selection of Y when X is selected. For example, OR = 2 means a doubling of selection probability. OR = 0.5 means a reduction of 50% in selection probability. Because the independent and dependent variables were binary, the estimated ORs could be interpreted as standardised effect size statistics, which enabled different OR values to be directly compared with each other.
Segmentation analysis based on sample liking scores (Objective 4) was achieved through hierarchical cluster analysis based on Euclidian distance and the method of Ward. Prior to cluster analysis, five participants were excluded because they gave the same liking score to all four samples. The number of clusters was determined using two criteria: scree plots and sample size of all retained clusters must exceed 40 people. The latter criterion followed from Moskowitz [74] who stated that stable estimates in sensory consumer research are often obtained from group sizes of 40-50 people. In each of the two retained clusters (n = 111, n = 41), all analyses described above were performed.
Liking (Objective 1)
Considering all participants in the study (n = 157), the mean liking for the four cream cheese samples ranged between 5.9 and 6.8 on the 9-point hedonic scale (Table 2). These values meant that both the PBCA and the dairy samples were positively received (6 = 'like slightly' and 7 = 'like moderately'). While cream cheese from cow's milk was more liked than PBCA, the difference between the two product types was less than one hedonic scale point (6.8 vs. 6.0). The proportions of participants giving dislike scores (1 to 4 on the response scale) were lower for the dairy samples (8-11%) than for the PBCA samples (22-30%). Notes: # Tukey's HSD was used for sample mean comparisons. Within columns, samples with different letters had significantly different means at the 5% level of significance.## Five participants were excluded prior to cluster analysis.
Product Characterisation (Objective 1)
Product characterisation was extensive and comprised four parts. For each response type-sensory, emotional, conceptual, situational use-Table 3 shows the results from Cochran's Q test (sample discrimination) and average term citation frequency across all samples. Figure 2 shows biplots of the first two dimensions after Correspondence Analysis for sensory, emotional, conceptual, and situational use data based on the total sample of 157 participants. To maintain visual clarity, 95% confidence intervals on sample positions are not shown, but can be found in Supplementary Material. Accompanying radar plots (by sample) for sensory, emotional, conceptual, and situational use data based on the total sample of 157 participants can also be found in Supplementary Material.
Table 3. Drivers of liking for cream cheese (plant-based cheese alternatives (PBCA) and dairy).
Results for sensory and non-sensory terms (rows) for total sample (n = 157) and PBCA Likers cluster (n = 111). Within sample grouping (sets of 3 columns), Column 1 contains p-values from Cochran's Q test for sample differences, Column 2 contains average term citation frequencies (%) across all samples in the study, and Column 3 contains the mean impact on liking $ when the CATA term was selected.
Sensory
The samples were described using 12 sensory descriptors, of which 10 were discriminating (Table 3). While all four samples had distinct profiles (Figure 2A) (see also Supplementary Material), there were notable similarities between the two dairy samples and the two PBCA samples. These particularly related to texture where the two PBCA samples were much more 'firm' and the two dairy samples were much more 'light/airy'. For example, citation frequencies for Samples PBCA2 and Dairy1 were, respectively, 76% and 8% ('firm') and 6% and 51% ('light/airy'). A texture difference of smaller magnitude, but nonetheless notable, was 'creamy/smooth' mouthfeel, where the citation frequency for Sample Dairy2 was nearly double that of Sample PBCA1 (respectively, 90% and 47%). A similar result was found for 'dissolves quickly in mouth' (Dairy1 = 57% and PBCA2 = 24%). Flavour differences were less pronounced, and more specific to individual samples than dictated by product type (PBCA or dairy). For example, 'buttery' flavour was most characteristic of Sample Dairy2 (64%) and had a higher citation frequency than found in the other three samples (33-40%). Sample PBCA2 was also the most 'sweet', while Sample Dairy1 was the least 'sweet' (22% vs. 6%). Sample Dairy1 had the highest citation frequency for 'sour/tangy' (51%).'Shiny/glossy' appearance was low in all samples (28% or less), but lowest in Sample PBCA2 (8%). Sample PBCA1 was perceived as considerably more 'mild/bland' (46%) than the other three samples (25-32%).
Emotional
Sample separation based on emotional associations (Figure 2B) resembled that from the sensory data, in that the primary difference was related to product type (PBCA or dairy) and was valence-driven. Sample separation based on 'happy/satisfied' aligned with the results based on the liking data (Table 1), while 'unhappy/dissatisfied' indicated greater differentiation between the four samples, with, for example, Sample PBCA1 being less frequently associated with 'enthusiastic/inspired' and more frequently associated with 'dull/bored' than the dairy samples. Sample PBCA2 was more frequently associated with 'blue/uninspired', 'tense/bothered', and 'jittery/nervous' than the dairy samples.
Situational
Aligning with the findings from the three earlier sets of product characterisations, perceived appropriateness for situational uses largely differentiated samples based on product type (PBCA or dairy) (Figure 2D). Compared to the dairy samples, PBCA samples were perceived as less appropriate 'to have with salmon', 'to spread on a cracker with toppings', 'as a spread on a bagel/sandwich', and 'to dip raw vegetables in'. Minor variations on this theme were observed for the other situational uses, and across the 15 use situations, the average citation frequency for dairy samples was 47-48% compared to 32-33% for PBCA samples. In a few instances, the samples were differently differentiated. Sample Dairy1 was more appropriate 'to use as an ingredient in a dip/sauce' than Sample Dairy2 (66% vs. 50%), and both were more appropriate for this use than the PBCA samples (31-32%). Samples PBCA2 and Dairy2 were equally appropriate 'to use in baking', and Sample Dairy2 was more appropriate than the other three samples 'to use as a butter replacement' (50% vs. 31-36%).
Sensory and Non-Sensory Drivers of Liking (Objective 2)
The results after penalty/lift analysis performed using all participants (n = 157) are shown in Table 3.
Emotional Drivers of Liking
For emotional product associations, the mean impacts were mostly greater than for sensory characteristics, and with one exception ('passive/quiet'), these exceeded one hedonic scale point. Specifically, hedonic lifts were established for all emotions with positive valence and for 'active/alert', and among these the largest mean impact was observed for 'happy/satisfied' (2.1). Hedonic penalties were established for all emotions with negative valence and the largest mean impact was observed for 'unhappy/dissatisfied' (−2.7). In absolute values, the hedonic penalties were larger than the hedonic lifts (−1.5 to −2.7 vs. 1.0 to 2.1).
Situational Drivers of Liking
Regarding situational use characteristics, significant hedonic lifts were established for all 12 uses, with values from 0.5 ('to use in baking') to 1.7 ('to spread on a cracker with toppings'). The four other use situations with a hedonic lift that was at least one scale point were 'as a spread on a bagel/sandwich' (1.6), 'to have with salmon' (1.5), 'to dip raw vegetables in (e.g., carrot, cucumber)' (1.3), and 'for sushi filling' (1.1).
Sensory Drivers of Non-Sensory Product Characteristics (Objective 3)
The sensory drivers of non-sensory product associations were elucidated through logistic regression. Table 4 shows the results based on the analysis including all 157 participants. When the selection of a sensory CATA term increased the odds of a non-sensory CATA term being selected, the OR values ranged between 1.70 and 7.35. Conversely, when the selection of a sensory CATA term decreased the odds of a non-sensory CATA term being selected, the OR values ranged between 0.34 and 0.59. Table 4. Results for cream cheese samples (plant-based cheese alternatives (PBCA) and dairy) based on the total sample of 157 participants where CATA terms for sensory product characteristics were significant predictors of non-sensory (emotional, conceptual, and situational) product associations # . Analysis performed using logistic regression, and values in superscript are odds ratios (OR) for non-sensory CATA term selection. Within the emotional, conceptual, and situational categories, non-sensory CATA terms are ordered from most to least impact based on OR values.
Situational
To dip raw vegetables in (e.g., carrot, cucumber) 3.12 As a spread on a bagel/sandwich 2.49 To have with salmon 2.34 To use as an ingredient in a dip/sauce 2.10 In a cheesecake filling 1.90
Dissolves quickly
Emotional Happy/satisfied
Situational
To dip raw vegetables in (e.g., carrot, cucumber) 2.17 As a spread on a bagel/sandwich 2.05 Notes: # Empty cells indicate that no sensory CATA terms were significant predictors (at the 1% level of significance) of non-sensory terms.## 'Helps me feel satisfied with life' and 'Made using traditional recipes and processes' were placed in the CATA question with sustainability terms during data collection.
Appearance, Taste, and Flavour
Selection of 'shiny/glossy appearance' was associated with increased citation probability for 'happy/satisfied', 'active/alert', 'sophisticated', and 'versatile'. In other words, this sensory appearance characteristic was positive in the eyes of consumers.
For taste attributes, the selection of 'salty' increased odds of selecting 'artificial'. For 'sour/tangy', there was an increase in selection probability of the emotional associations 'active/artificial' and 'unhappy/dissatisfied', as well as the conceptual associations 'artisanal' and 'versatile'. However, 'sour/tangy' perception was associated with a reduction in the odds of selecting 'to use in baking' and 'to use as butter replacement'. For 'sweet', only a single significant relationship was established and pertained to a reduction in the odds of selecting 'simple' as a conceptual sample descriptor.
Regarding the cream cheeses' flavour characteristics, 'buttery flavour' increased the odds of selecting 'happy/satisfied', 'comforting' and 'to use as a butter replacement'. When 'cow-like/barnyard flavour' was selected, the odds of term selection increased for 'secure/at ease' and 'wholesome'.'Mild/bland flavour' had a major impact on increasing selection probability for 'dull/bored' (OR = 7.35), with lesser impacts on other deactivated emotional associations ('relaxed/calm' and 'passive/quiet'). There was also an increased probability of selecting 'simple' and 'cheap' while the selection probability decreased for 'to dip raw vegetables in'. There was an increased selection probability for emotional associations with opposing valence-'happy/satisfied' and 'jittery/nervous' when 'savoury flavour' was perceived.
Texture and Mouthfeel
For texture characteristics, 'firm' was associated with an increased selection probability for 'tense/bothered', 'unfamiliar', 'artificial' and 'to use as a pizza topping'. However, cream cheeses perceived as 'firm' were less likely to be associated with 'to dip raw vegetables in' and 'to spread on a cracker with toppings'. A 'light/airy texture' decreased selection probability for 'unfamiliar' and increased selection probability for 'to have with salmon'.
'Creamy/smooth mouthfeel' was the sensory attribute for which most significant associations to non-sensory terms were established. The probability of selection increased for positive and/or deactivated emotions ('happy/satisfied', 'secure/at ease', relaxed/calm'). Similar associations were observed for 'comforting', 'versatile' and 'trustworthy' conceptualisations. Especially large OR values were found for 'happy/satisfied' (OR = 7.17) and 'comforting' (OR = 4.96). The probability of selecting several use situations also increased ('to dip raw vegetables in', 'as a spread on a bagel/sandwich', 'to have with salmon', 'to use as an ingredient in a dip/sauce', 'in a cheesecake filling'). For 'dissolves quickly in mouth' increased selection probability was established for 'happy/satisfied', 'nutritious', 'genuine', 'versatile', 'to dip raw vegetables in', and 'as a spread on a bagel/sandwich'.
Consumer Segmentation Based on Liking (Objective 4)
Two groups of participants with different patterns of liking for the PBCA and dairy cream cheeses were established through cluster analysis (Table 2). Of the 152 participants who were entered into this analysis, the majority of participants (n = 111, 73%) liked PBCA and dairy samples equally (all samples between 6.5 and 6.7) (p > 0.53), and there was no significant difference between mean scores based on Tukey's test. However, a minority of participants (n = 41, 27%) liked the two cream cheese samples from dairy (7.1-7.3)considerably more than the two PBCA samples (3.3-5.1)(p < 0.001). Correspondingly, the two clusters were named, respectively, PBCA Likers and PBCA Dislikers.
Product Characterisation by Cluster
In Table 3, the product characterisation results obtained in the PBCA Likers cluster (n = 111) were shown next to those for the total sample (n = 157) and facilitated a comparison of the two sets of results. Across all samples, average term citation frequencies were similar, never differing more than 5% for individual CATA terms. Despite establishing no significant differences in average liking scores in the PBCA Likers cluster (Table 2), the four samples of cream cheese were significantly differentiated on 9 of 12 sensory descriptors (excluding 'cow-like/barnyard', 'mild/bland', 'savoury flavour'), 3 of 12 emotional product associations ('happy/satisfied', 'unhappy/dissatisfied', 'enthusiastic/inspired'), on 5 of 14 conceptual descriptors ('traditional', 'unfamiliar', 'versatile', 'genuine', 'artificial'), and 9 of 12 situational uses ('to have with salmon', 'to spread on a cracker with toppings,' 'as a spread on a bagel/sandwich', 'to use as an ingredient in a dip/sauce', 'to dip raw vegetables in', 'to make icing for cakes', 'to use in baking', 'to use as a butter replacement', 'for a creamy smoothie'). The overlapping 95% confidence sample ellipses in Figure 3A-C reflected these findings by showing that the samples were neither completely similarly nor completely uniformly perceived but were partly different to each other (the exception was the sensory data where sample ellipses were non-overlapping, Supplementary Material). When a joint analysis of all 50 non-sensory terms was performed, a separation of samples was observed (Figure 3D), suggesting that these data contributed insights that extended the non-significant discrimination based on liking, primarily for the two dairy cream cheese samples.
the sensory data where sample ellipses were non-overlapping, Supplementary Material). When a joint analysis of all 50 non-sensory terms was performed, a separation of samples was observed (Figure 3d), suggesting that these data contributed insights that extended the non-significant discrimination based on liking, primarily for the two dairy cream cheese samples.
Drivers of Liking by Cluster
The information in Table 3 also showed that the sensory drivers of liking in the total sample and the PBCA Likers cluster were largely similar. Notably, there were no product characterisation terms where significant mean impacts in the two sets of results were, respectively, positive and negative (or vice versa). There were, however, multiple instances where the magnitude of the mean impacts differed, reaching 0.5 or 0.6 hedonic scale points, always with the larger value (absolute numbers) in the PBCA Likers cluster ('creamy/smooth mouthfeel' (1. Penalty/lift analysis was also performed in the PBCA Dislikers cluster (n = 41). While the results were regarded with considerable caution because of the low sample size, they were, nonetheless, helpful in understanding what sensory characteristics of the PBCA samples were disliked, particularly in the case of Sample PBCA2. The results aligned with those in the total sample (n = 157), but there were multiple terms where the difference in mean impact was one hedonic scale point or more, and always with the more extreme value in the PBCA Dislikers cluster. These were: 'firm' (−1.9), 'creamy/smooth mouthfeel' (2.4), 'light/airy texture' (1.9), 'tense/bothered' (−2.5), 'active/alert' (1.8), 'unfamiliar' (−2.5),
Liking for PB Cream Cheese Alternatives and Consumer Segmentation
One important finding of the present research was that PBCA samples were more likely to be liked than disliked by the 157 participants, with average liking scores close to the verbal anchor 'like slightly' (i.e., six on the nine-point hedonic scale). This finding, which links to Objective 1, adds nuance to the narrative that PB alternative foods struggle with poor sensory quality and consumer acceptance [11,18,26,[75][76][77]. That is, amid evidence that consumer acceptability will likely be modest or less, there is value in drawing attention to those situations when liking scores for one or more PB alternatives are the same or very similar to those obtained for their non-PB counterparts. One recent example was a US consumer study with burger patties [78]. Under blinded tasting conditions, preferences for the beef burger and the hybrid and pea protein burgers were not significantly different. The present research is another example, and shows, although only in the context of four samples, that PB alternative cream cheese is "within reach" of dairy cream cheese, trailing less than one hedonic scale point (Table 2) when all participants were considered.
Consumer segmentation based on liking was expected and found (Objective 4). The results suggested the existence of two clusters (PBCA Likers and PBCA Dislikers), although this finding must be regarded with some caution due to low sample sizes. However, since the smaller cluster comprised 41 participants, which aligned with an estimate from Moskowitz [74] that stable means in sensory and consumer research are common based on 40-50 people, it was reasonable to interpret, with care, the results. It resonated with previous studies that a cluster of people were found who disliked PB alternatives [5,79], but the present results were unique in the sense that PBCA Likers was the larger cluster and PBCA Dislikers was the smaller cluster (73% vs. 27%). The findings of Cardello, Llobell, Giacalone, Roigard, and Jaeger [28] (PB milk alternatives, 345 participants) showed that more fine-grained segmentation is possible, allowing groups of consumers to be identified with varying preferences for different PB product variants. Tentatively, such extended segmentation on a larger consumer sample could have resulted in further differentiation between the two PBCA samples, for example, with one segment disliking both Samples PBCA1 and PBCA2, and another segment that disliked Sample PBCA2 but liked Sample PBCA1 as much as the dairy samples.
The consumer population further contextualised the liking results. Participants in this study stated an interest in reducing their dietary reliance on meat and dairy foods but were not vegetarian or vegan, and they mostly lacked previous experience with PBCA (66% had not tasted PBCA before; Table 1). Higher liking among vegans than omnivores and flexitarians for a range of PB alternative foods was reported by Pointke, Ohlau, Risius, and Pawelzik [26] and, if replicated, this could lend further support to the conclusion that PB products need not be inferior or poorly accepted. Moreover, it could contribute to greater uptake of PB cream cheese alternatives, which in turn, could support the notion of a gateway effect, first to other types of PBCA, then to other types of PB food alternatives, and eventually a more complete transition to a PB diet.
Suggestions for How to Improve PB Cream Cheese Alternatives
The findings linked to Objectives 2 and 3 provided specific insight regarding formulation changes that could be made to improve PB cream cheese alternatives and close the gap to dairy cream cheese in terms of average liking (Table 2).
Texture and Mouthfeel
Most important would be to improve the texture and mouthfeel characteristics of the PBCA samples to make them more similar to the dairy cream cheese variants (Figure 2, Table 3). Because flavour is often mentioned as a driver of disliking for PB alternatives to milk and yoghurt, for example, soy/bean and off-flavour [18,75], the finding that texture and mouthfeel characteristics in the present research were stronger drivers of liking than other sensory modalities was a pertinent reminder of the importance of texture and mouthfeel for consumer acceptance. Muñoz and Civille [80] were among the first to draw attention to this, and among PB meat alternatives, there are many reports that poor texture is key to consumer dislike [81]. Considering also that texture and mouthfeel are very important to consumer acceptability for dairy cheeses of different types [23,35], including cream cheese [22], establishing these sensory modalities as very important for PB cream cheese alternatives, therefore, had face validity.
The present results predicted that PBCA samples would be more liked if the texture was less firm and more light/airy, the mouthfeel was more smooth/creamy, and the cheese dissolved more quickly in mouth (Table 3). A comparison of the results for the PBCA Likers cluster against the indicative results for the PBCA Dislikers cluster suggested that firmness, conversely, lack of light/airy texture, was the major culprit, followed by insufficient smooth/creamy mouthfeel. For these sensory descriptors, the biggest differences in the mean impact on liking were established (1.2-1.7 scale points) (Table 3, Supplementary Material). Based on logistic regression (Table 4), it was seen that samples perceived as 'firm' increased the odds of selecting 'tense/bothered', 'unfamiliar', and 'artificial' with OR values ranging between 2.13 and 3.21 (i.e., more than 200% increase in terms of selection probability). The PBCA samples were so firm that they were not easily spreadable, and this could be what primarily evoked the associations with 'unfamiliar' since dairy cream cheeses are much softer (Figure 2). The findings for 'light/airy texture' supported this interpretation as selection of this sensory term majorly decreased the probability of selecting 'unfamiliar' (OR = 0.34). Firm texture was also linked to reduced uses-'to dip raw vegetable in' (OR = 0.46) and 'to spread on a cracker' (OR = 0.57)-which, in turn, could have contributed to evoking increased feelings of 'tense/bothered' because ways that cream cheese is commonly used were no longer regarded as appropriate. The finding that firm cream cheese was regarded more appropriate as a pizza topping could tentatively be harnessed for vegan pizza, which is gaining market share [82].
When cream cheese was perceived as having a 'creamy/smooth mouthfeel', a very large increase in selection probability for 'happy/satisfied' was observed (OR = 7.17) and emphasised the importance of this sensory characteristic for consumer acceptability. When further considering the linkages to emotional and conceptual product characterisations, it seemed that low firmness in combination with a smooth and creamy mouthfeel should be pursued. This was supported by increased selection probability for positive and deactivated emotions ('secure/at ease', 'relaxed/calm') and for 'comforting' and 'trustworthy', where the latter stood in opposition to 'unfamiliar' and 'artificial'. Increased versatility was also inferred (OR = 3.32), and this was further reflected in increased odds for five situational uses.
In terms of consumer uptake for PB cream cheese alternatives, the collective results for texture and mouthfeel characteristics indicate that if the focal sensory properties can be improved, it will not only positively impact liking, but also reduce the multiple barriers that consumers experience in switching to PB alternative foods [47]. Additional positive/desirable conceptualisations will be a benefit, and in this regard, one result for 'dissolves quickly in mouth' was somewhat intriguing. While the results largely resembled those for 'creamy/smooth mouthfeel', an exception was 'nutritious', for which selection probability was also significantly increased (OR = 2.72). A possible explanation for this linkage is that samples with a quickly disappearing mouthfeel feel less greasy/oily, which, in turn, may make them appear healthier. This may feed into the health halo that is associated with PB alternative foods, which in many instances, is not supported based on nutritional content for individual products in the dairy category [83], although there is supporting evidence for PB diets overall [2]. In the present case, it may, therefore, be necessary to identify a positive nutritional link to 'dissolves quickly in the mouth' if this conceptualisation is to be harnessed for marketing purposes.4.2.2. Appearance, Taste, and Flavour Texture aside, 'sweet' taste exerted that largest influence on the mean liking for the tested cream cheeses (Table 3). That the impact was a hedonic lift (1.1) fitted expectations, since sweet liking is an innate preference in humans [84]. However, it is important to be mindful that sweet liking determined in a test setting may not translate when products are consumed in larger quantities and across longer periods of time [85]. With this caution in mind, it was interesting to note that only one significant association between 'sweet' and non-sensory characteristics was established (Table 4). Tentatively, it could indicate that increased sweetness will increase immediate liking, but lack effectiveness in strengthening the emotional, conceptual, and situational uses, and hereby not significantly help to overcome the multi-dimensional barriers that that many consumers face when seeking to eat a more PB-rich diet [47].
A tangible example of the value of the multi-response measurement approach was seen for 'sour/tangy', which, according to the penalty/lift analysis, did not significantly impact mean liking (Table 3). Yet, selection of this term increased the odds of selecting 'unhappy/dissatisfied', which made sense in the context of 'sweet' increasing selection probability for 'happy/satisfied'. However, the result for 'sour/tangy' was more complex due to this characteristic also increasing the odds of a sample being associated with 'active/alert', 'artisanal', and 'versatile'. The latter, nonetheless, excluded certain uses ('to use in baking' and 'to use as butter replacement') (Table 4), and possibly 'versatile' needed to be interpreted in the context of 'artisanal' and be seen as indicative of more sophisticated uses. Sample Dairy1, which was the most 'sour/tangy', was most strongly associated with 'to have with salmon'. Considering the results for 'sweet' and 'sour/tangy' collectively, these sensory characteristics must be balanced for high consumer acceptance. Fruit-based products demonstrate this, for example, oranges [86], apple juice [87], and champagne [88].
There were few specific results for 'salty' other than increasing the selection odds for 'artificial'. Despite not exerting a significant impact in the penalty/lift analysis (Table 3), this result nonetheless indicated that caution is warranted since 'artificial' has negative connotations. The actual salt content was higher in the two PBCA samples than in the dairy samples (855-979 mg/100 g vs. 350-411 mg/100 g) (Supplementary Material), and Sample PBCA2 was perceived as the saltiest. Sample PBCA2 was also the least liked by a majority of participants (i.e., in the PBCA Dislikers cluster) (Table 2). Salt content in PB alternative foods, including dairy, has been identified as a possible concern [83], so a way to reduce it should perhaps be sought, both as a small contribution toward reducing salt intake, which is much above the recommendations in many countries [89], and because it may contribute negatively to consumers' product experience.
Cream cheese samples (PBCA and dairy) perceived as having a 'mild/bland flavour' were less liked according to the penalty/lift analysis (Table 3). This finding provided further evidence of a relationship that seems to be generic rather than product specific. For product innovation, this insight does not imply that strong flavour is preferred since such foods are generally also disliked. Instead, the challenge seems to be to find a balance where products are perceived as neither one nor the other, and additionally avoid specific flavours and tastes that penalise liking while promoting those that exert a hedonic lift. For cream cheese, one of the flavour attributes that exerted a hedonic lift was 'buttery flavour' (Table 4). This flavour characteristic also increased the likelihood of regarding a cream cheese sample as suitable 'to use as a butter replacement'. Considering that the PBCA samples contained coconut oil as a major ingredient (Supplementary Material), it is not immediately clear how this flavour characteristic can be naturally introduced, but if it could, PBCA may become more appealing to people who watch their cholesterol intake and so limit their intake of butter.
'Shiny/glossy appearance' was not strongly characteristic of any of the four samples but applied significantly more to the dairy than PBCA samples. As a target for product innovation, smaller rather than larger changes would, thus, be sought and the possible benefit is a positive impact on the mean liking, as well as increased selection probability for 'happy/satisfied', 'active/alert', 'sophisticated', and 'versatile'. Mindful of the results for 'sour/tangy' regarding versatility, it may be prudent to explore further how 'shiny/glossy appearance' is linked to perceived versatility. Qualitative research methods [90] may be suitable, working with end consumers, chefs, and others in the catering business.
Non-Sensory Product Characterisation
The results for the PBCA Likers cluster (n = 111) showed that samples, despite not being significantly different in terms of the degree of liking/disliking (Table 2), differed on several non-sensory product perceptions, especially situational appropriateness (Table 3). This result captured the essence of why appropriateness of use is part of the "beyond liking" paradigm that has gained acceptance in sensory and consumer research. Moreover, this result illustrated with clarity that samples that are not differently liked can be regarded as differently appropriate in various use situations, and this is what originally motivated Cardello and Schutz [43] to advocate for the inclusion of situational appropriateness in consumer-centric product research.
Qualitative research has already been suggested as a useful path for further consumer research with cream cheese [90], and online product reviews may be a data source option [91]. In particular, it could be interesting to take situational uses and perceived appropriateness as a starting point for identifying sensory innovation targets. The present results suggested, for example, that firmness was key in samples being regarded as more vs.less appropriate for certain uses. This characteristic may be more important than its ingredients (PB or dairy), and samples that systematically vary in firmness (and related texture characteristics such as 'spreadability' and 'light/airy') could be studied. The results linked to the use of cream cheese in sushi rolls are also interesting because of its popularity despite not representing traditional sushi. New uses for cream cheese may be uncovered, possibly in markets where this product is not well established, which can guide the way for PB alternative cream cheese with different taste and texture profiles that possibly also draw on the long history of soy-based cream cheese [59] and take advantage of its lactose-free status for the benefit of Asian populations where lactose intolerance is more prevalent [92]. More generally, a focus on situational use connects with the literature around being a mindful host, which includes serving PB and vegetarian meals [93].
Limitations and Suggestions for Future Research
All empirical studies have limitations, and this is no exception. The inclusion of additional research participants to confirm the smaller PBCA Dislikers cluster is needed. A replication and extension research strategy would be appropriate, and this would ideally include a larger number of cream cheese samples-dairy and PBCA. If the latter were made from ingredients other than coconut oil, this would be interesting, for example, cashew nuts, oats, almonds, and soy [63]. At the time of the study, such products were not available in major retail outlets in New Zealand, but they do exist in other countries, and some have higher protein content than the PBCA samples in this research.
Care is needed in generalising the results to other consumer nationalities. For example, Foguel, Neves Rodrigues Ract, and Claro da Silva [22] found that the most liked sample of cream cheese (dairy) in their study with US consumers was more firm and less spreadable. This differs from the present result, but may also reflect greater variation in cream cheese on the US market, where, for example, the popular Philadelphia brand sells cream cheese in many flavours, several of which are available in different textures that vary in firmness and spreadability [58]. For applied and marketing purposes, it is advisable that segmentation be refined beyond consumer nationality, for example, by considering key demographic variables such as age and gender.
Only about one third of participants had previous experience with PBCA (Table 1), and this limited the value of a comparison of responses between those who did and did not have familiarity. However, it could be relevant to purposefully recruit participants with PBCA experience to uncover their sensory and non-sensory product perceptions and better understand what role familiarity plays in acceptance of PBCA.
The "beyond liking" paradigm of sensory and consumer science implemented in the present research demonstrated that sample differentiation based on non-sensory terms can be achieved when not observed on liking data alone (Figure 3D). Similar findings have been observed in other product categories [28]. For product developers, it adds additional direction for innovation efforts, but ways to reduce ballot length would be welcome. Additional analyses of the present data could identify a subset of non-sensory attributes that most effectively deliver additional sample differentiation. Over time, similar analyses could be performed for other studies and contribute to guidance regarding the most important non-sensory aspects to include. Emotional activation is likely to be among them, but it is less clear what criteria can be used to reduce the number of conceptual and situational use terms. Empirical as well as theoretical advances are needed.
Conclusions
In a case study approach, with cream cheese (commercially available) as the product category, the present research presented an in-depth consumer study that compared four samples, of which two were PBCA and two were dairy (from cow's milk). Regarding liking, the key finding was that the majority of participants (i.e., PBCA Likers cluster) gave mean liking scores to the four samples that were not statistically different. This was a positive result for PB alternative foods, which often struggle against a narrative of inferior sensory quality and unmet consumer expectations. Penalty/lift analysis determined drivers of liking (sensory and non-sensory), and these offer tangible guidance for innovation efforts and may have relevance for the wider PBCA category. Situational appropriateness data suggested that PB cream cheese alternatives that were firmer than dairy cream cheese had less applicability than dairy cream cheese for some uses. The main limitation of the work lay in the use of a small number of samples and that the PBCA samples were made from coconut only. Ample scope exists to extend the research and confirm its generalisability. Nonetheless, the key takeaway from this research was that PBCA have the potential to match their dairy counterparts in the eyes of consumers. Amidst a dominant narrative of the opposite, the results are encouraging for the transition to dietary habits that are less dependent on meat and dairy.
Supplementary Materials:
The following supporting information can be downloaded at: [URL]:// www.mdpi.com/article/10.3390/foods13040567/s1,Part 1. Supplementary sample information; Part 2. Image of samples as served to participants, in small glass bowl with piece of bread stick.
Figure 1 .
Figure 1. Images of four samples used in the study. Two were plant-based alternatives to cream cheese (PBCA) and two were dairy cream cheese (cow's milk).
Figure 1 .
Figure 1. Images of four samples used in the study. Two were plant-based alternatives to cream cheese (PBCA) and two were dairy cream cheese (cow's milk).
Foods
sis for sensory, emotional, conceptual, and situational use data based on the total sample of 157 participants. To maintain visual clarity, 95% confidence intervals on sample positions are not shown, but can be found in Supplementary Material. Accompanying radar plots (by sample) for sensory, emotional, conceptual, and situational use data based on the total sample of 157 participants can also be found in Supplementary Material.
Figure 2 .
Figure 2. Results for the total sample of participants (n = 157), showing biplots of the first two dimensions after Correspondence Analysis of product characterisation data.(Descriptors are shown in grey and samples in black. To reduce visual clutter, 95% confidence ellipses around sample positions are not shown.
Figure 2 .
Figure 2. Results for the total sample of participants (n = 157), showing biplots of the first two dimensions after Correspondence Analysis of product characterisation data.(Descriptors are shown in grey and samples in black. To reduce visual clutter, 95% confidence ellipses around sample positions are not shown.
Figure 3 .
Figure 3. Plots of the first two dimensions after Correspondence Analysis based on data from participants in the PBCA Likers cluster (n = 111) showing average samples positions with 95% confidence intervals.
Figure 3 .
Figure 3. Plots of the first two dimensions after Correspondence Analysis based on data from participants in the PBCA Likers cluster (n = 111) showing average samples positions with 95% confidence intervals.
A 3-digit random code was placed on the glass bowl to identify the sample; Part 3. Product characterisations for cream cheese by sensory and non-sensory descriptors based on responses from 157 participants (total sample); Part 4. Plots of the first two dimensions after Correspondence Analysis based on data from total sample (n = 157), showing average sample positions with 95% confidence ellipses; Part 5. Plot of the first two dimensions after Correspondence Analysis based on data from PBCA Likers cluster (n = 111), showing average sample positions with 95% confidence ellipses based on sensory descriptors; Part 6. Drivers of liking for cream cheese (PBCA and dairy). Results for sensory and non-sensory terms (rows) in the PBCA Dislikers cluster (n = 41). Author Contributions: Conceptualisation, S. R. J.; methodology, S. R. J. and C. M. R.; formal analysis, S. R. J.; investigation, C. M. R. and D. J.; data curation, D. J.; visualisation, S. R. J. and D. J.; writing-original draft preparation, S. R. J.; writing-review and editing, S. R. J. and C. M. R. All authors have read and agreed to the published version of the manuscript.
Table 1 .
Participant characteristics (%) $ , for the total sample (n = 157) and the consumer segment where cream cheese liking for plant-based cheese alternatives (PBCA) was as high as liking for dairy cheeses (PBCA Likers, n = 111).
Table 2 .
Cream cheese samples (plant-based cheese alternatives (PBCA) and dairy (Dairy)) used in the research, showing mean liking scores ('dislike extremely' = 1 and 'like extremely' = 9) with standard deviations shown in brackets and Tukey's HSD post hoc comparison of means shown in superscript # . Values shown for total sample and the two retained preference clusters ## .
Sensory CATA Term ## Selection of Sensory CATA Term Increased the Probability (Odds) of Non-Sensory CATA Term Selection Selection of Sensory CATA Term Decreased the Probability (Odds) of Non-Sensory CATA Term Selection Taste SaltyTable 4 .
Cont.
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Domain: Agricultural and Food Sciences Business
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Inquiring Systems and Development Led Inquiry: Uniting the Efforts of Farmers, Development Professionals, and Researchers
This paper introduces Development Led Inquiry (DLI) as an approach to improve situations incorporating relationships between third sector organisations (TSOs) and agricultural scientists, universities, and the public-sector agricultural establishment. There is limited scholarly work on the role of TSOs in agricultural research. Current approaches appear premised on TSOs being researched upon, and recipients of research outcomes rather than partners in generation and application of new knowledge. DLI expands the boundaries of research systems and roles of TSOs as supporters within them. DLI builds on partnerships between NGOs, farmers’ organisations, and women’s associations; it integrates researchers and research organisations to develop, manage and report knowledge generation and application. DLI is dynamic and developmental with learning for all participants central to the process. DLI unsettles current power structures within research systems and sees research and knowledge generation as a supporter rather than leader of development. DLI is embedded in an inquiring systems approach and applies six interrelated conceptual systems thinking tools. The approach emerged from, and was applied in, a twelve-year agricultural research project in India, and was subsequently introduced to, and further developed in a research project in Pakistan.
Introduction
Agricultural research takes many forms with the approach applied primarily determined by the background and interests of researchers. Agricultural research has a historical bias against resource-poor farmers dependent on agriculture for their livelihoods (Chambers & Ghildyal, 1984). Focussed on increased production, research has concentrated on better-off farmers in better-endowed areas with the potential to readily adopt high-yielding technologies generated on research stations (Chambers & Jiggins, 1987a). Research has been seen as the territory of trained researchers who are skilled in following the traditions and philosophies of research. Traditional approaches to agricultural research have successfully generated new knowledge but have been less successful in translating research results into actions of small-scale agricultural producers.
The cultures of agricultural research and development are not aligned, and processes of research do not allow seamless integration of new knowledge into production systems. This lack of alignment has been known for many decades and relates to the complexity of human situations. With multiple relationships, interconnections, and feedback loops between multiple elements, alignment cannot be reduced to simplistic and linear chains of cause and effect (Green, 2016). In complex situations desired outcomes are poorly defined and multiple methodologies and methods are required to appreciate a situation and develop and apply new knowledge (Bawden, 2007;Midgley, 2000).
However, most approaches to agricultural research are blind to this complexity (Douthwaite & Hoffecker, 2017;Klerkx et al., 2012;Schut et al., 2015). Development projects also seek linear attribution rather than embrace complexity and unpredictable change.
Over the past sixty years, researchers have worked to make agricultural research results more aligned to the needs of rural producers and overcome barriers to adoption of new technologies. However, most approaches still begin from the perspective of researchers and answer questions determined by researchers, and supported by funding bodies and research organisations. While participatory tools are applied to bring rural producers into research systems, those producers often become part of the system being researched rather than part of the system performing research.
This paper outlines a new approach to generation and application of knowledge, Development Led Inquiry (DLI). DLI has several characteristics that distinguish it from other approaches. These include pluralism in theoretical frameworks and methods, expansion of organisations included in the team, and testing and application of the new knowledge as an integral part of its generation. DLI is dynamic and developmental with learning for all participants central to the process. DLI focuses on human development and sees research and knowledge generation as a supporter rather than the leader of development. This approach unsettles power structures within research systems and suggests inquiring systems as an alternative. DLI emerged from, and was applied in, a twelve-year agricultural research project in India, and was subsequently introduced to, and further developed in an agricultural research project in Pakistan. DLI foregrounds the third sector in Third Sector Research (TSR).
The paper then outlines three approaches developed since the 1960s to overcome barriers to adoption, namely: Transfer of Technology (TOT), Agricultural Research for Development (AR4D), and Research in Development (RinD). It relates DLI to those approaches demonstrating how it builds on and differs from them.
DLI and What Makes it Distinctive
DLI has its theoretical basis in inquiring systems, an approach initiated by Churchman (1971). In this approach, inquiry is designed and organised as a system to generate knowledge linked to action to improve a complex situation. The approach is pluralist and enables DLI to incorporate multiple perspectives of both the situation to be improved and the processes to improve it. An inquiring systems approach enables participants to view the world as a collection of partial, bounded, and interactive situations.
Thinking in wholes enables the co-existence of paradigms such as positivism and reductionism as well as enabling application of pluralism in theoretical frameworks (Midgley, 2002). An inquiring systems approach is a critical approach that produces knowledge as part of a process of reflexively rigorous practice (Colvin et al., 2014). Critical approaches may be described as Third Wave systems thinking, which contrasts to First Wave or positivist systems thinking and Second Wave or Soft Systems Thinking (Williams & Imam, 2007). DLI starts from the understanding that research and the new knowledge produced supports development rather than leading it. DLI does not reject current research approaches but seeks to build a clear understanding of the context so that appropriate approaches are applied to achieve desired ends.
Conceptual or thinking tools have been developed to enhance inquiry (Midgley, 2002). Six systems thinking tools introduced in Table 1 form the basis of DLI. These tools do not stand alone and are not applied linearly: rather they are interrelated in a network and employed in concert as represented in Fig. 1.
DLI involves a change in the nature and structure of knowledge generation from a traditional research system to an inquiring system. With that come changes in membership and how new knowledge is tested and applied. In particular, DLI acknowledges the complexity of situations being improved and expands membership of the inquiring system from those who usually participate in knowledge generation to a team that incorporates a diverse group of stakeholders. Changes in membership expand perspectives of the situation, and processes to generate and test options available to potentially improve the situation. The structure of the system is not fixed but developmental. As understanding of the situation and environment in which it is operating increases so does the membership and approach taken.
DLI teams include third sector organisations (including farmers' groups and self-help groups) and trained researchers from public, private, and NGO sectors. Nongovernmental organisations (NGOs) play a pivotal role as interlocutors crossing diverse cultures, institutions, disciplines, and languages and enabling relationships between diverse stakeholders in the collaborative team. Participants can learn to understand and accept the views of other participants without requiring consensus. Accepting the perspectives of other participants requires a shift in power relationships within the inquiring system. DLI enables participants, particularly scientists and NGOs to recognise the power asymmetries between them and the communities. This change requires researchers to see themselves as members of the team and work to understand the perception other participants have of the situation being improved.
The focus on improving a situation through generation and application of new knowledge requires and supports involvement of diverse participants with different perspectives of the situation; perspectives on what constitutes improvement, how to enable improvement to take place, and the nature of knowledge and processes to generate new knowledge. DLI requires participating individuals and organisations to link to the broader situation being improved; be open to the ideas and understanding of other participants and organisations; and be prepared to reflect on their own perspective including its nature, origins, and impact on others.
DLI integrates all participants into the knowledge generation system rather than seeing them as objects for research or distributors of knowledge generated by research systems. Hence, all participants can become partners in the whole process of knowledge generation.
DLI and the Third Sector
Application of an inquiring systems approach means DLI can be applied in complex situations to enable alignment between development and research. DLI builds integrated teams that include Third Sector Organisations (TSOs) as core partners. It provides a framework that enables TSOs to expand their impact into the research sector, and for NGOs, academics, government departments, and research institutions to shift their roles and approaches towards participating in research with farmer and women's organisations as partners, to design and carry out research.
The growing body of TSR has addressed the role of the third sector, and of organisational behavior and management, philanthropy, and volunteering on TSO functioning (Hodgkinson & Painter, 2003). While there is a growing area of TSR about partnerships with the state, and delivery Holistic thinking Involves thinking of situations as wholes comprising interconnected parts. An important element in understanding and working with complexity Purpose Improvement in understanding or ability to make improved decisions informed by knowledge generated through inquiry. In addition to the project purpose, each person and organisation have their own purpose which may or may not align with that of the inquiring system (multiple perspectives) Multiple perspectives Multiple views coexist and vary with culture, social background, education/discipline, experience, gender, and age Boundaries (and boundary critique) Boundaries are used to determine what issue and who/what is included or excluded. Boundary critique is a way to examine the potential impact from considering the situation from various perspectives because different perspectives may provide different boundaries Learning All systems thinking tools are embedded in a learning model, encompassing transformational or incremental changes in how to think about the world, cognition, knowledge, and skills. Learning trajectories/processes vary across team members
Interconnections, interactions and relationships
Links to thinking in wholes with an emphasis on how the parts are connected and emphasise the relationships between the parts rather than the parts themselves of public services, there is less on the role of TSOs in agriculture research and its utilisation. In this paper, we examine how TSOs relate to and work with other TSOs, and agricultural scientists, and universities. Many poor families live in rural areas and are dependent on agricultural production for food, income, and employment. TSOs operate in rural communities but are not involved in the production and application of new knowledge. While often part of transnational networks and epistemic communities, their role has been outside the research system as objects for research, hosts for research process, contributors of inputs to the research agenda, and distributors of knowledge generated. Yet these organisations, connected directly with communities, can play an important role in all phases of research. TSOs are characterised by privateness i.e., outside the sphere and control of the government; public purpose i.e., serving the broader community; and free choice i.e. pursued without compulsion (Salamon & Anheier, 1992;Salamon & Sokolowski, 2016). DLI incorporates development NGOs, a subset of TSOs that work with disadvantaged communities, supporting social, political, and economic change locally (Lewis, 1998). DLI also draws on the reconceptualisation of TSOs to include social solidarity economies (Salamon & Sokolowski, 2016;Defourny et.al., 2016) such as women's self-help groups (SHGs) (which do not distribute surplus to members) and farmer cooperatives or groups (which may distribute surplus to members). Whether to include these kinds of organisations is a conceptual debate beyond the purview of this paper. However, DLI reinforces the importance of a more inclusive definition.
The approach is premised on TSOs playing a variety of roles within inquiring systems, including as initiators, implementers, and coordinators of activities, and disseminators of outputs. The paper builds a case for the essentiality of NGOs, particularly where social solidarity organisations are not established or are not mature. NGOs provide a bridge between scientists and social solidarity organisations, contextualising the inquiry and increasing its relevance. However, the structure of agricultural research systems can restrict inclusion of those who are not trained researchers (Chambers & Jiggins, 1987b). For instance, members of farmers' groups and women's SHGs are often perceived as agricultural laborers and the subject of research, and rarely as co-researchers, conducting research activities on their farms, monitoring and disseminating the research outputs locally (Bellotti, 2017).
Approaches to Agricultural Research
DLI links to agricultural research in human development contexts. This section reviews three approaches to agricultural research and development and presents DLI as an alternative. Section 5 presents two case studies from South Asia (India and Pakistan), illustrating the development and application of DLI. Section 6 concludes with implications of DLI for TSOs and research partnerships with academic and research institutions.
Most research to improve agricultural productivity in poorer countries is carried out by international and national government-supported institutions such as CGIAR centers, agricultural departments, and public universities. The role of TSOs is envisaged as supportive, at best. Building connections between scientists and farmers have been attempted, but the focus has remained on research followed by development. The relationship between agricultural research and development has been considered in multiple ways (presented in Table 2): transfer-of-technology (TOT), agricultural research for development (AR4D), and research in development (RinD). DLI is proposed as a fourth way, related to and distinct from the other three approaches.
TOT prioritises the research agenda set by scientists, funding agencies, and commercial interests (Fig. 2). It is performed on research stations and in laboratories, with knowledge and technology transferred to farmers via extension agents. Decision-makers and farmers, located outside the research system, elect whether to follow that advice or not. TOT is inappropriate for resource-poor farmers, whose conditions are often radically different from those of research stations, and whose farming systems are often complex and diverse (Chambers & Jiggins, 1987b). TOT may be seen as the first wave of systems thinking.
AR4D attempts to remedy the exclusions of TOT from the outset: researchers produce outputs intended to contribute directly to outcomes for resource-poor farmers (Fig. 3). Research and development are distinct sets of activities, and AR4D builds partnerships between all the stakeholders: researchers, development agents, and policymakers (Thornton et al., 2017). As with TOT, scientific research in AR4D is undertaken by elite, trained researchers and research drive the development agenda. The pathways for how a particular intervention contributes to an impact are not clearly articulated nor complexityaware (Douthwaite & Hoffecker, 2017;Douthwaite et al., 2003).
RinD is conceptually distinct to the above two approaches, engaging communities and stakeholders through a joint scoping and design process so that the research agenda reflects local challenges and is locally embedded (Fig. 4). It is complexity-aware (Douthwaite & Hoffecker, 2017). However, the role of researchers remains 'outside' the development system. Perspectives of farmers are incorporated into the research system through scoping studies and embeddedness, rather than informing the scientific agenda. Capacity building of partners addresses the expansion of skill sets, rather than cognitive learning required for transformation (Fig. 5).
Despite the systematic movement from TOT to AR4D to RinD, research in agriculture (and other fields involving science and technology) still involves scientists driving the research agenda without engaging farmers. Chambers and Jiggins (1987b) indicate the disadvantages of agricultural research centers and suggest that the main initiative for reorientation of research would ''probably have to come from courageous and original national scientists and imaginative non-government organisations''. Both AR4D and RinD may be linked with the Second Wave or Soft Systems Thinking.
DLI provides a framework to respond to development needs, with continuous iterations to re-envision improved situations and is linked directly to users (farming communities and individuals). It is designed to improve complex and dynamic situations and generate new knowledge. TSOs are integral to the research system: facilitating the research agenda, contributing to the production and analysis of scientific knowledge, and building relationships
An Assessment of the Use of DLI in Two Agriculture Research Projects in South Asia
According to the global multidimensional poverty index, over 48% of the world's poor are to be found in agrarian communities in South Asia (Alkire and Robles, 2017). Agriculture in South Asia is dependent on rainfall and is subsistence-oriented. Most farmers have limited access to improved inputs and technologies. Women are excluded from making decisions, have limited access to, and control over resources, and are socially and economically dependent on their male counterparts (Banu, 2016). DLI was developed as an approach from the project undertaken by the authors in India and was extended to Pakistan by one of the authors, where it is ongoing. The Indian project was built around PRADAN, a large professional NGO, and the SHGs that it had formed. The project in Pakistan was based in public-sector organisations and national universities and introduced NGOs and farmers groups at a later stage. The Pakistan project began as with TOT approach, and the epistemic development of the research team and introduction of DLI as an approach began within the first year. The case studies demonstrate this introduction and transition process, particularly the inclusion of NGOs as interlocutors between farmers, their associations, and the scientists. Both projects were funded by the Australian Centre for International Agricultural Research (ACIAR) that supports collaborative research projects involving Australian researchers and those in partner countries. Australian researchers in the projects had backgrounds in agronomy, economics, rural systems, and development. Key characteristics of the projects are presented in Table 3.
Case 1: Improving Livelihoods Through Innovative Cropping Patterns in India
PRADAN, the women's SHGs it promoted, and research scientists from Australia and India constituted a research team. The team acknowledged distinct perspectives of the various participants which intensified interactions and enabled the re-design of the project to align with the diverse purposes of team members. For example, the agenda that emerged from farmers related to water scarcity, soil health, and cash crop alternatives to attract younger generations to farming. This agenda expanded the scientific questions beyond agronomy to farming systems and natural resource management, and alternative cropping systems based on local practices such as direct-seeded rice. The boundaries of the inquiring system thus expanded, and the research team included specialised research organisations. Some trained researchers questioned interactions between research and development and declined to participate whereas those who accepted the interactions continued in the team and were open to producing interrelated academic and developmental outcomes (Bhanjdeo et al., 2018). This exemplified how interactions (agreements and disagreements) could be productive, redefine boundaries for the team, and articulate shared values.
Research didis, members of the SHGs, identified areas for inquiry, selected trial sites, collected and triangulated data, and assisted with interpretation of results and production of scientific knowledge. The research organizations trained youth who were selected by the SHGs. Supervised by PRADAN, these youths mapped the quality of wells and tanks and changes in the water table and supported onfarm, farmer-managed trials.
Interactions between the farmer co-researchers and other research team members were facilitated by PRADAN, which played an important role in building the team. In addition to trusted relationships in the local area, PRA-DAN's ability to navigate diverse languages and cultures, and its expertise in agriculture-based livelihoods enabled a locally grounded assessment of practices and areas for improvement. Researchers from Australian universities and PRADAN conducted learning workshops for all team members to share their experiences and interpretations, and to reflect on the views of one another. These interactions between scientific principles and farmer practices led to emergence of contextual knowledge and application of improved technology and practices in the field. SHG members, scientists, researchers, and PRADAN professionals built the capacity to undertake research as members of an inquiring system, expanding and modifying their views of the situations under study. Figure 6 illustrates the timeline of the project, how it progressed and led to the development of DLI as an approach. The varied purposes and perspectives of the research team manifested in project outcomes in multiple domains. The project demonstrated that soil water and rainfed water supply could secure rice crop yields and a second crop could also be grown (Cornish et al., 2015). The project generated a scientific understanding of the local aquifer systems, providing insights into groundwater use (Patil et al., 2015). An alternate agronomic package was developed for medium uplands with a shorter-duration, local rice that was traditionally direct-seeded (Bellotti et al., 2017). The need for this local cropping system was generated and communicated by women's associations.
Vegetable and pulse crops in the fallow uplands, with crop timings aligned to local market prices, provided options for higher incomes. Innovative practices and mechanisation reduced women's labor in transplanting and weeding. This, combined with new knowledge and identity created space for women's decision-making in the family. The systematic dissemination of research outputs from farmer-to-farmer and via PRADAN's networks led to adoption by * 17,000 farmers within 2016 (Bellotti et al., 2017).
Case 2: Pakistan Pulses Project
The project was initially conceptualised as a traditional science project based on the assumption that key factors limiting pulse production were technical. Through interaction between the Australian and Pakistani scientists, it was re-oriented as a farmer-focused multi-partner collaborative DLI project. Farmers became focal persons and the basis of research, who exercise choices and make decisions regarding farming and cropping on their land. Initial research engagement involved the development of Groups for Collaborative Research (GCR). These groups were developed by the project because other groups either did not exist or were not able to participate. The GCRs provided the focus for field activities and included farm families, research scientists from government research organisations, and Australian universities. The GCRs assisted farm families to outline local issues and facilitated deliberations and discussions to understand research results and plan how to apply learning.
Initial activities demonstrated that farm families and researchers did not share the same perspectives and had assumptions about each other that were not aligned. Not all team members agreed with the change in approach but almost all continued in the project. As the project Fig. 6 Case 1 project timeline progressed, facilitated workshops enabled members to recognise the impact of DLI for researchers and farm families, and Pakistani scientists began to actively apply the approach.
On-farm varietal trials were carried out by farmers in the GCRs, supported by the scientists, enabling selection of varieties best suited to local situations. However, GCRs were inexperienced in disseminating knowledge produced and in distributing preferred seed varieties to farming communities. To address this challenge, the boundaries of the inquiring system were expanded by inviting NGOs operating near project sites to join.
The project is ongoing but some outcomes are visible. The NGOs have taken the lead in developing a seed system to enable farm families from the GCRs and other areas to access preferred varieties. In addition, the NGO also supported microfinance, and their access to activities enabled integration of the inquiry conducted by GCRs into production methods and value addition. The NGOs long and trusted relationships with the communities facilitated women to participate in activities and to benefit from the project's learning.
The NGOs will continue working with the farmer's groups and researchers beyond the life of the project supporting ongoing knowledge development, exchange, and application once the project has ended. This collaboration added new approaches, knowledge, and skills to the research team, particularly an understanding of inquiring systems. It has provided useful information (technical and process-related) and resources to the NGO. Figure 7 illustrates the timeline of the project and the application of DLI as an approach.
In summary, research engagement in both cases led to improvements in the situations, deeper and greater acceptance of alternative views provided by the various project participants, acceptance of participants' limitations, and individual and group learning.
Conclusion
DLI is appropriate for use in complex situations through the application of an inquiring systems approach and systems thinking tools. It enables expansion of research team membership to include TSOs as core partners. It provides a framework for NGOs and researchers to shift their roles and approaches towards participating in research with women's and farmers' groups/organisations, in contrast to conventional research which conceptualises and reaches out to farmers and women as individuals in communities, to transfer the tools, technology or innovation they have developed. Learning is core to the approach enabling personal, organizational, and team development. While the team has many shared experiences, members' learning is not congruent and, in DLI pluralistic perspectives are explored and valued. DLI builds on the emerging roles of agricultural and NGO researchers as third sector researchers. Researchers engaged with the application of science and technology to rural development are shifting towards TSR in terms of adoption of change and innovation. However, researchers are not explicit about this, neither are they prepared for this role. DLI requires researchers to clearly articulate a third sector-related research agenda.
Case studies presented in this paper highlight the benefits of including NGOs, women's associations, and farmer organisations as members of the research team. But, the full benefits are only derived when relationships are constructed so members of the team, and issues they are working on, are interconnected as an inquiring system.
The shift in the Pakistan project from the TOT approach to DLI (and in India, from AR4D to DLI) indicates the importance of a critically aware partnership between farmer/women's organisations, scientists, and NGOs in the research system. Scientists played a key role in the research team, as they enabled themselves and other members to participate in the process. Other approaches (RinD, AR4D, and TOT) view stakeholders in silos and do not attempt to unsettle the interrelationships between scientists and individual farmers and households in this way.
DLI is still developing and faces several challenges. The nature of training in universities focuses on disciplinebased research. DLI projects require team members to expand their conceptual frameworks and learn to work in diverse teams; this does not suit all participants. For instance, a key factor underlying DLI is the scientists themselves, rather than other structural or epistemological factors. The Australian project scientists were influenced by the Australian Hawkesbury project (Bawden, 1985), and entered the projects with an AR4D approach. However, interactions with PRADAN and the SHGs (in Case 1) produced a shift beyond inclusion of individual farmers to emergence of DLI.
Power asymmetries and biases between participants are challenging and DLI requires trust and mutually respectful relationships. DLI does not seek consensus but requires participants: to be open to the ideas of other participants; to not seek to assert power over others, but to work together to understand and improve situations. DLI projects are dynamic; for example, in the cases presented as the projects progressed and participants learnt, their perspectives of the situation changed. In response to that change, the team developed with researchers more able to appreciate the situation farmers faced and valued farmers' capacity to design, carry out and report research. Farmers brought traditional practices such as direct-seeded rice to scientific assessment, changed their perceptions, underwent intellectual development, and reported shifts in knowledge and practices. For instance, they thought in annual cycles to plan their production using residual soil moisture and precipitation and were no longer focused on one part of the cycle.
Flexible and applicable in various contexts, inquiry is not standardised and cannot be applied as a simple list of steps. It integrates knowledge generation with its application making the process of inquiry itself dynamic. Three key implications of this approach are: development practitioners, researchers, and farmer's organisations need a clear remit and understanding of their roles and they need time to settle into their roles; it establishes the importance of mechanisms for governance, scrutiny and informed consent required for development led inquiry; and it provides a framework for evaluation of development and research projects.
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Domain: Agricultural and Food Sciences Education
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HALALAN TAYYIBAN IN AQUACULTURE PRACTICE – A CASE STUDY ON PARASITE IN HATCHERY
, ABSTRACT Halal is an important issue in aquaculture since this industry produces food for human consumption. This paper aimed to discuss the procedures and practices in the current aquaculture in relation to the concept of halal as a subject while tayyib is a process where clean and pure food will be produced and gives comfort to the user or consumer, thus the product is recognized and certified as Halalan Tayyiban . Fish brood stock obtained from a river and kept under a hatchery condition was assigned for the case study. The ectoparasite species found on Tilapia under hatchery cultured condition was investigated. The weight and total length of the Tilapia were measured, and mucus coating was swapped to 10% buffered formalin using the scraping technique. The morphology of copepod parasites was observed under a compound microscope for identification. Hosts with infection of ectoparasite showed reduced weight and increased mortality. A comprehensive understanding of the importance of adopting Halalan Tayyiban principles in aquaculture procedures will improve the aquaculture product thus bringing forward local farmers in the halal supply chain.
1.
Introduction In the context of food safety, Alzeer et al. (2018, p. 266) summarized that Halal is the subject, whereas Tayyib is a process that should lead to clean and pure food as a main objective and generate comfortable feelings as a main goal. While the concept and definition of halal are very precise as defined by Al Quran, Tayyib as it is a process, could refer to a quality standard or product (Mohd Yunus et al. 2010, p. 242).
In aquaculture, fish is reared in a confined area, thus, the process will involve the whole production procedures, harvesting, and marketing aspects. Kartika et al. (2020, p. 278) in their mini-review emphasize on fish reared in a pond that does not adhere to Shariah compliance, for instance using filthy sources for feeding, the halalan tayyiban specification will not be achieved. Aquaculture in Malaysia at this point still facing Tayyib issues, particularly in the feeds and feed composition which may affect the effort to bring forward fish farming and small farmers into the halal supply chain (Kartika et al. 2022). While at the same time, the Food and Agriculture Organization of the United Nations (FAO) in their Blue Transformation Roadmap 2022-2030 aimed to intensify sustainable aquaculture to satisfy global demand for food. This aim is planned to achieve through the implementation of different targets including minimizing environmental impact and the use of resources efficiently (FAO 2022, p.7).
Adding to the feed issue is the disease which has become the main threat to the aquaculture industry. Aquaculture practices and environmental quality in the operation are related to fish health. Water quality deterioration showed a direct impact on the high prevalence of ectoparasites on cultured fish (Fahmy et al. 2022). Fish being cultured in overcrowded and poor water quality conditions had been reported as the factors responsible for the development of parasitic copepod disease (Johnson et al. 2004). Environmental quality obviously relates to the Tayyib concept. Water parameters such as dissolved oxygen,
A B S T R A C T
Halal is an important issue in aquaculture since this industry produces food for human consumption. This paper aimed to discuss the procedures and practices in the current aquaculture in relation to the concept of halal as a subject while tayyib is a process where clean and pure food will be produced and gives comfort to the user or consumer, thus the product is recognized and certified as Halalan Tayyiban. Fish brood stock obtained from a river and kept under a hatchery condition was assigned for the case study. The ectoparasite species found on Tilapia under hatchery cultured condition was investigated. The weight and total length of the Tilapia were measured, and mucus coating was swapped to 10% buffered formalin using the scraping technique. The morphology of copepod parasites was observed under a compound microscope for identification. Hosts with infection of ectoparasite showed reduced weight and increased mortality. A comprehensive understanding of the importance of adopting Halalan Tayyiban principles in aquaculture procedures will improve the aquaculture product thus bringing forward local farmers in the halal supply chain.
Keywords: aquaculture practice, ectoparasite, farming management, halal supply chain temperature, and ammonium level, when are outside the preferable of the fish species range, will induce stress, compromising their immune system and making them vulnerable to many opportunistic pathogens (Vatsos & Angelidis, 2010). This is where the concept of Halal and Tayyib needs to be highlighted as a comprehensive approach to support the FAO roadmap and become the opportunity to influence the government policies in implementing mandatory Good Aquaculture Practise for aquaculture operators. Looking at the aquaculture industry in Malaysia, the adoption of a good aquaculture practice (GAqP), is still not mandatory. There is a scheme, Aquaculture Farm Certification Scheme (Skim Persijilan Ladang Akuakultur Malaysia, SPLAM) is voluntary for the farmers to improve their farm management and production. SPLAM has undergone a rebranding process into Malaysian Good Agricultural Practices (MyGAP) in 2013. Nonetheless, MyGAP is also a voluntary program, but no doubt that the report showed that farmers that have a high level of good aquaculture practices will have a high level of aquaculture production (Samah, 2020).
The Tilapia farming industry by Malaysian farmers and young agropreneurs is experiencing rapid growth since the hybrid tilapia, Oreochromis niloticus was introduced to the commercial culture level in the 1980s. It has represented 86% of the total local tilapia production (Karuppannan et al., 2013). There were reports on the infestation of ectoparasites on cultured Tilapia in Malaysia. Marina et al. (2013) reported on heavy infestation of Caligus epidemicus on marine Tilapia cultured in an earth pond in Johor possibly due to the source of water from the nearby river estuary. Noor-Shahirah et al. (2018) reported a 56-60% prevalence of ectoparasites in Tilapia cultured in the earth marine ponds in Setiu Terengganu. The low content of dissolved oxygen (2.50-3.14 mg/L) could be the reason for the infestation. Caligus from Family Caligidae is a highly diverse group with the most specious genera when more than 250 ectoparasite species found mostly in marine fishes of warm water areas (Ho & Lin, 2004). Maran et al., (2009) reported five species of Caligus from fish cultured in floating cages such as C. chiastos, C. longipedis, C. punctatus, C. rotundigenitalis, and included C. epidemicus from Penang and Langkawi Island, Malaysia.
Earth ponds and floating cage culture are the most common technique of aquaculture in most countries including Malaysia. These systems are very much dependent on wild sources of water and other materials related to the water used on the farm. Nonetheless, as production surges, aquaculture facilities increasingly rely on the heavy input of formulated feeds, antibiotics, antifungals, and agrochemicals to ensure fish could fight pathogenic organisms in the culture system (Sapkota et al. 2008). On the other hand, this practice agitates the integrity of the whole production and supply chain process as it gives a negative impact on the sustainability of the industry itself. Under the training guide on ASEAN Good Aquaculture Practices of Fish Food 2020, four key aspects of focus include food safety, animal health and welfare, environmental integrity, and socio-economic responsibility (ASEAN, 2020). It could support the initiative to align aquaculture practice with the halal and tayyib concepts. The objective of this paper is to highlight the issue of disease in aquaculture which should be an important element when considering the halalan tayyiban aspect of aquaculture production and supply chain.
Materials and methods 2.1 Experimental design
One hundred fish species (host) of Oreochromis niloticus (mean weight is 500g/ind.) were collected from cage culture at the nearby river of Kg. Cherok Paloh, in Kuantan. This cage culture of the Red Tilapia area received fresh water from the Cherok Paloh River and marine water from the South China Sea during high tide. Collected hosts were incubated for 4 days in an incubation tank under hatchery conditions. After 4 days, live host species were divided into two different tanks with different stocking densities. Tank 1 was stocked with 68 hosts and Tank 2 with 25 hosts. The mean percentages of mortality were counted for an 18-day period. The host's conditions were monitored daily. Since the host showed poor condition and higher mortality, random diagnoses were conducted, and the appearance of a copepod parasite was then noted.
Laboratory analysis
On the same day, hosts were randomly caught with 6 replicates of each tank. The total length (in centimetres) and weight (in kilogram) of each host were measured and recorded. Ectoparasite specimens were removed from the host using a scraping technique. A clean slide functioning as a scalpel was used to scrap the mucous from the lateral and tail end of the host body. Mucous was placed in 10 % buffered formalin. Parasite copepods were enumerated into non-gravid and gravid stages. Adult copepods were randomly selected for morphological studies and were mounted on a semi-permanent slide for whole-body observation under a compound microscope. Female copepods were dissected, and their parts were transferred into a small drop of CMCP-9 before covering them with a cover slip. The details on its structures were drawings with the aid of a lucida tube attached to a compound microscope.
3.
Results and Discussion 3.1 Physical-chemical parameter and host condition. Table 1 summarized the physical-chemical parameters of the water inside and outside the cages in the study area. The water is considered brackish water with a range of salinity of 24.27-24.41ppt. The oxygen content (DO) in the water is rather low (4.22-4.47 mg/L) while the pH is stable and in an alkaline condition. The temperature is typically warm in tropical water conditions. From Day 1 to Day 5, all hosts were in incubation tanks, and they were separated into two tanks Tank 1 and Tank 2 starting Day 6 until Day 18. The temperature ranged between 27 o C and 31 o C, while dissolved oxygen showed a good supply for the fish. pH and salinity were high and favoured the fish culture condition (Fig. 1).
The result of the infestation of ectoparasite in Tank 1 and Tank 2 is shown in Table 2. Weight gain and total length of the hosts in Tank 2 were higher than in Tank 1. This could be related to the high number of parasitic copepods found in Tank 1. The mean number of ectoparasites was 43.8 in Tank 1 and 0.3 in Tank 2. In addition, there are many parasites with eggs (gravid copepods) found in Tank 1. The mortality rate was also higher in Tank 1.
Loss of body weight and higher mortality of Tilapia in Tank 1 showed higher infection of C.epidemicus. All of the parasite life stages (gravid, non-gravid) found in the samples collected from Tank 1 indicated the favourable condition that supports parasite infestation on hosts. The high number of hosts stocked in the tank and the warm condition could affect the oxygen supply, thus infestation becomes active.
Morphology feature of C. epidemicus
The morphological features of the ectoparasite found infesting Tilapia in this study are shown in Fig. 2. The mouthparts and appendages were adapted to crawl and attached to the outer skin of the host. Their flattened dorso-ventrally body shape increases the adaptability to live on the host. The poor water condition was noticed from the low oxygen content in the river itself where the source specimen was collected. This possibility of early infestation by ectoparasites, while they were in the wild, was proved by the high number of gravid parasites found when they were kept under the hatchery condition. This mode of disease attack is frequently reported in cultured fish due to poor water quality conditions on the farm. Farm management is considered one of the critical points in the aquaculture halal supply chain (Kartika et al. 2022). Failure to comply with the standard procedure in maintaining good water quality, and practising an unhygienic approach in handling fish and their waste will trigger the growth of pathogenic organisms which will be infesting the fish.
Maintaining a strict protocol for aquaculture activities could be a way to improve the tayyib practice in the industry. Starting from the site selection (choosing the source of water for culture activity), the culture technique chosen and standard operating procedures in the production process will affect the quality of the product from the farm. Healthy fish will increase demand and activate the halal supply chain.
Conclusion
The aquaculture industry should determine its practices to be in accordance with the standard which will meet the definition of tayyib. In addition to the issues of feed and feed content, maintaining animal health and welfare and environmental integrity is seen as an important aspect that should be considered in the focus of halalan tayyib. Disease and parasite infestation are major threats in the aquaculture industry and the cause is directly related to the environmental integrity of the aquaculture farm. Handling the issues following the concept of halal and tayyib would help the industry and the aquaculture halal supply chain to move forward.
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Domain: Agricultural and Food Sciences Environmental Science
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A bi-level model for a closed-loop agricultural supply chain considering biogas and compost
In today’s competitive marketplace, to increase customer satisfaction and profitability, supply chain management has become more prominent. Therefore, thorough planning and designing the supply chain by seeing all levels and units are essential to growing the efficiency of the entire supply chain. In the present study, an eight-echelon network is designed for a closed-loop agricultural supply chain. These eight echelons are consisting of suppliers, farms, distribution centers (DCs), customers, recycling depots, biogas centers, compost production centers, and biogas applicants. To design the agricultural logistics network, a bi-level programming mathematical model is presented. The first objective seeks to minimize total costs of the upper-level which consist of shipping costs, construction costs, production costs, inventory holding costs, and buying costs. Besides, the second objective attempts to maximize total profits of the lower-level using subtraction of incomes from the costs which the total income is calculated by selling manufactured biogas and compost to its applicants. Since the bi-level programming problems are part of the NP-hard class and due to the computational complexity of the problems, the meta-heuristic algorithms are utilized to solve the formulated problem. To this end, two meta-heuristics consisted of Genetic Algorithm (GA) and Stochastic Fractal Search (SFS) are employed. Moreover, two hybrid metaheuristics created from these algorithms which include GA-SFS and SFS-GA are suggested to search for more appropriate solutions. Finally, various comparisons and analyses are performed to evaluate the model’s performance and the capabilities of the solution methods and the results showed the superiority of SFS-GA over other methods. Also, the results imply that considering biogas and compost can not only prevent environmental pollution, but also lead to profitability and the production of new products. Therefore, using this plan in countries that have agricultural products and also do not produce fossil fuels can be more attractive and practical.
Introduction
Today, organizations seek to take advantage of the benefits of proper supply chain management to maintain their position in the market, create a competitive advantage and reduce costs, and generally improve the efficiency of their supply chain. Decision-makers and managers may have strategies in place to stay alive in this condition, but the favorite result will only be achieved if an accurate and comprehensive plan is used. Therefore, a detailed network design and principled supply chain planning with all levels and units in mind to increase the efficiency of the entire supply chain seem necessary (Delgoshaei et al., 2021;Tirkolaee et al., 2022aTirkolaee et al., , 2022b. Return products management, on the other hand, is a complex issue that requires decision-making at the strategic and operational levels. Problems that need to be addressed at the strategic level include determining the type of facilities needed and their location, the volume of recyclables that can be controlled or planning the flow of recycling materials (Khalilpourazari et al., 2021;Rahbari et al., 2022). On the other hand, issues related to operational planning include issues such as the time interval between recycling collection times, the number and capacity of vehicles, the relevant routing issue, and the number of workers required. Despite the close relationship between these two types of decisions, their analysis and review are usually done separately. Strategic decisions often have to be answered through political and governmental issues, while operational decisions need to be considered at lower levels, such as at the municipal level. Therefore, issues related to recycling management should be considered in the case study of different types of products in different locations (Cheraghalipour et al., 2020;Tirkolaee et al., 2021).
Reverse logistics and closed-loop supply chains are some of the most important and vital aspects of any business and include the construction, distribution of services, and support for any type of product. In developed countries today, industrial, governmental, commercial, and service organizations focus on reverse logistics processes and supply chain, which play an important role in creating the true economic value of goods and services while supporting environmental considerations (Ranjbar & Mirzazadeh, 2019). This focus is now increasing in all markets, including the industrial and advanced technology, commercial and consumer products sectors. Recent literature has shown that today, product returns are not only costly but also a means of creating value. Examples include preserving the environment, providing core resources, and increasing customer value. That potential revenues are usually greater than the costs incurred to create the necessary measures for return channels (Krikke et al., 2013;R. Lotfi et al., 2022).
On the other hand, agricultural products are one of the most important elements of the food basket of the people of the world. Iran is one of the first countries in the world where agriculture has started. According to the statistics of the 'Iranian Agricultural Jihad,' about one-third of Iran's land is agricultural, but due to poor soil and inadequate water distribution in most areas, only 12% of Iran's land is cultivated (including gardens, vineyards, and agricultural lands). 63% of arable land is still intact. In Iran, 50-60% of the capacity and talent of the lands under agricultural operations (185,000 square kilometers) are used. Iran's arable land is estimated at sixteen million hectares, of which about half is irrigated and the other half is rainfed (Agriculture Jihad, 2016). The agricultural supply chain today has a very important role in supply chain issues because of its unique structures such as the significance of food features, climate change, price changes, and the importance of supply-demand. In the classification of these topics, products are divided into two categories of perishable and non-perishable (such as grain and dried products). Also, in terms of the life cycle, they are divided into two categories: agricultural and horticultural crops (Cheraghalipour et al., 2018).
In recent years, the importance of the issue of agricultural products has grown significantly with increasing demand from concerned customers for a healthy diet (Weber et al., 2015). This has made quality and availability two important issues in all months of the year (Paksoy et al., 2012). In the last 10 years alone, the agri-food industry in general and the fresh fruit sector, in particular, have been recognized and discussed in the supply chain as a key concept for competitiveness (Tsolakis et al., 2014). Numerous studies have addressed and covered the issue of agricultural supply chain issues; but in our research, we found a research gap in the reverse logistics of products, a big problem that causes a lot of damage to this chain every year. This problem, which is the decay of products, is covered in the reverse logistics section of our proposed network. Since a significant number of manufactured products in the stages of production, distribution, target markets, etc., are decayed and unusable, it is felt that to reduce the costs of these wastes and reuse them, it is necessary to develop and analyze a closed-loop supply chain network design model (Tirkolaee et al., 2022a(Tirkolaee et al., , 2022b. It is very necessary and important to consider these concepts together. In recent years, the design of the logistics network in the supply chain has become more important than in the past. Considering the issue from the perspective of several decisionmakers, issues related to returned products, and the production of added value such as compost and biogas in the supply chain are of great importance today and have attracted the attention of many researchers. For this purpose, sufficient explanations will be provided in the present research. This study tries to develop a practical model for designing an agricultural supply chain network as much as possible, taking into account the limitations of the real world. Therefore, considering the waste and corrupted products in the agricultural supply chain, it will provide a network to collect these returns to reduce the costs of the chain and generate potential revenues from them. For this purpose, an eight-echelon network is designed for the agricultural supply chain. The suppliers are the first echelon. Farms are the second echelon to produce crops. In the third echelon, some DCs buy agricultural products from farms and send them to customers in the fourth echelon after processing. It should be noted that this network has been in operation for multiple periods, so in echelons 2-4, some of the products will become waste. These waste materials are transported to the fifth echelon for the depot, and according to management decisions, some of which are transferred to biogas production (echelon 7), and some are sent to the production of biological fertilizers (echelon 6). Finally, these biogas and biological fertilizers are sent to customers in the eighth echelon and the suppliers in the first echelon, respectively. Due to the computational complexity of the large-scale real-world problems, meta-heuristic algorithms are developed. Finally, various comparisons and analyses are performed to evaluate the model's performance and the capabilities of the solution methods. The general purpose of this study is to present a bi-level programming model and evaluate the efficiency of the closed-loop agricultural supply chain network proposed in the case study; and the special purpose of this research is to achieve an efficient method for reuse of supply chain waste in the reverse logistics sector and return of this waste to the supply chain, which will add value to this waste. This is done by making compost and biogas. To this end, two goals such as minimizing total costs and maximizing total profits are considered.
Bi-level programming problems, in the simplest form, those mathematical models for the leader and the follower are linear and their decision variables are continuous, can be converted into a MIP problem. In this case, by using the Karush-Kuhn-Tucker (KKT) conditions, the follower model can transform into a series of constraints. Then, by placing them into the constraints of the leader, a nonlinear model is created. This nonlinearity is
Agricultural supply chain
The supply chain of agricultural products today has a very important role in supply chain issues due to its unique features such as the importance of food quality, the importance of supply-demand, climate change, and price changes. As a pioneer in this field, van Berlo (1993) measured activities associated with the vegetable processing supply chain, which included the stages of planting, harvesting, processing, and marketing, and used in a mathematical model using a goal programming approach. Their model included farmer decisions to reduce chain costs and did not include location decisions. After this research, the process of using operation research in agriculture continued. For example, Jolayemi (1996) planned agricultural planning for multi-regional harvests; Allen & Schuster (2004) estimated investment and harvest to reduce crop losses using a nonlinear model in vineyards. And Rantala (2004) provided a supply chain model for seedlings that sought to minimize production and transportation costs to meet customer needs. As progress in research gradually became more advanced, additional assumptions such as product quality and shipping process were considered. For example, Ferrer et al. (2008) developed a model for deciding on harvest per season, shipping process, processing of products, and packaging in the form of a mixed-integer model (MIP) for red grapes. Their model is designed only for post-harvest planning to meet customer demand and also takes into account the cost of harvesting and reducing the quality of the product.
The expansion of problems in the agricultural supply chain is taking place with an evolutionary trend so that recently Cheraghalipour et al. (2018) developed a multi-echelon network for the citrus supply chain and using several meta-heuristic algorithms attempt to balance the chain costs and customer demand. Also, in another study, Cheraghalipour et al. (2019) sought to create a bi-level network for the rice supply chain, which reduces the cost of the chain from the perspective of two decision-makers. They used nested evolutionary algorithms to solve their proposed problem and performed management insights and sensitivity analysis on specific parameters. In addition, Anderson & Monjardino (2019) considered a kind of discount in their formulation and tried to reduce the price of wheat by using the contact structure. They validated their structure using a case study in Australia and reported that the contract was closely related to manufacturers' risk aversion. Also, Carvajal et al. (2019) used a robust programming method for the sugarcane sector in Colombia to optimize plant profits and make several tactical and strategic decisions.
In an article, Gardas et al. (2019) added value to the present data-based industry by identifying the challenges of the agricultural supply chain in India based on a careful review of the literature and the Delphi method. Therefore, laboratory and experimental decision-making methods were used to model the identified challenges, explore cause-andeffect interactions, and improve hierarchical configurations of challenges through interpretive structural modeling. The execution of this method led to the conclusion that two elements, namely limited integration into national agricultural markets and limited agricultural market infrastructure, are the most important factors. The integrated model obtained as a result of this study aims to guide agricultural policies and decision-makers to improve the performance of the agricultural supply chain in India. There are also some basic recommendations for improving the efficiency of agricultural supply chain management.
Recently, Dai & Liu (2020) conducted an in-depth study of the supply chain risk of large retail companies and then introduced the dock of agricultural supermarkets for the supply chain in the big data environment. In this study, big data was used to analyze the potential risk in the agricultural supply chain in large retail companies. From the aspects of production, processing, distribution, retail, and consumption, this research introduces new risks in the supply chain of agricultural supermarkets after the introduction of big data. In the second stage, qualitative analysis and quantitative calculation are combined to perform the risk assessment. Through experimental analysis, the ranking of all risk factors was obtained and the corresponding fuzzy assessment grade and risk assessment criteria were given. Through expert evaluation, a new risk rating was obtained, which is not much different from the results of the experimental analysis, and the experimental results were confirmed. Therefore, the development of this study is useful to avoid the risk of connecting the supply chain of agricultural supermarkets. Yan et al. (2020) also proposed a way to coordinate an agricultural supply chain with tactical purchaser behavior in mind. According to the characteristics of the supply chain of agricultural products, the beneficial performance of consumers was provided and under the integrated chain, this study focuses on the effect of consumer behavior on decision-making in the supply chain. Therefore, it counts the tactical activities of strategic users as a risk aversion factor and examines the effect of user risk on supply chain decision-making. Also, two coordination contracts based on income sharing and wholesale prices are designed for decentralized decision-making in the agricultural supply chain. Finally, through numerical analysis, the sensitivity analysis of some of the main parameters in the model is performed.
Multi-level programming
Multi-level programming was first proposed by Bracken & McGill (1973, 1974a, 1974b) as a generalized mathematical programming model. Then, their different models were examined and used by researchers. But in recent years, these methods and applications have been studied more seriously and extensively. The main concept of the multi-level programming method is that the upper-level decision-maker determines his goal or decision and then demands the desired limit from each sub-level, which is calculated alone. Then, the lower-level decisions are presented and modified by the upper-level according to the profit or the total amount obtained. This process continues until a satisfactory solution is reached. In these types of issues, the upper-level decision-maker does not have the authority or ability to decide on all decision variables. The design of financial management networks, transportation, and production planning are among the issues in which this method is used (Behnia et al., 2019). The general model of multi-level programming can be presented as follows (Migdalas et al., 1998).
In relation (2), P 1 is known as the first-level problem and is equivalent to the upper-level in the hierarchical structure. The decision-maker at this level controls the decision variable x 1 and the objective function of his level to minimize f 1 . Similarly, P k is the problem of the kth level and corresponds to the lowest level of the hierarchy. If the problem consists of only two lines, it is called a bi-level programming model. In this case, the decision-makers of the upper and lower levels are called leader and follower, respectively.
Leader-follower hierarchical decision-making problems were first raised by Stackelberg (1952), which he called bi-level programming problems. These issues have two levels that the first level decision-maker implements his decision on the second level, observes the reaction of the second level, and intends to optimize his objective function. The secondlevel decision-maker also observes the first-level decision and makes a logical decision to optimize its objective function.
In general, the following characteristics can be provided for a bi-level programming model: • Each decision-maker directly controls only certain variables.
• Different levels of decision-making are influenced by the decisions and activities of other levels, but each is trying to optimize its own decisions. • Upper-level and lower-level decision-makers know each other's level goals and constraints. • Lower-level is required to implement upper-level decisions and implementation of decisions is from top to bottom. • The goals and decision-making space of each level can be influenced by other level decisions.
The bi-level programming problem is an NP-hard problem (Bard, 1991). However, due to its many applications in practice, many methods have been proposed to solve it. Methods for solving this problem can be divided into five categories, which are presented in Table 1. (1)
Counting methods
The general idea is that the optimal solution is one of the vertex points. These methods are specific to linear bi-level programming problems and obtain the exact optimal solution Matching the lower-level methods In these methods, the problem is replaced by the KKT optimization conditions or the penalty function, so that the lower-level problem becomes a constraint on the main problem Fuzzy methods The general idea in this group of methods is to define the belonging function for objectives, constraints, variables, or a combination of them at each of the problem levels Meta-heuristic methods These methods are not exact methods and provide an approximate solution or optimal solution, which also has a good computational complexity. Tabu Search, artificial intelligence, PSO algorithm, and ant colony algorithm are in this category
Agricultural waste
Pesticides and agricultural wastes are the most dangerous contaminants in water and soil that remain in the environment for years and cause irreparable damage to life. On the other hand, effluents from the agricultural sector are one of the most harmful sources of environmental pollutants that dangerously affect the health of the environment and, consequently, the quality of citizens' life. Agricultural waste arises from production activities in the agricultural sector, which include waste, animal carcasses, and rotten agricultural products, pesticides, and chemical fertilizers (Chávez et al., 2018). According to statistics released by the FAO, about 30% of agricultural products worldwide are turned into waste, and the value of this volume of waste is estimated at $ 5 billion per year. Iran is known as one of the leading countries in the field of agricultural waste and has a high ranking compared to other countries in the same category. Waste from dates, figs, wheat, rice, wheat bran, barley bran, tomatoes, and legumes such as green pea, beans, corn, and other crops can be good sources for reproduction. Therefore, according to the mentioned importance, agricultural waste is an important and vital issue that must be addressed and prevented from entering the environment. Therefore, this study will consider the destruction of agricultural waste from the proposed supply chain by considering the production of biogas and compost. In the following, we will review some of the research conducted in the field of agricultural waste. Xiong et al. (2020) in a study examined the possibility of consuming agricultural waste and synthetic macromolecules as sources of solid carbon and investigated the effects of improving nitrogenating through nominated agricultural wastes. The capacity of carbon release and disinfection performance of corn, peanut shell, worn rice, and other materials were systematically analyzed. The results showed that for each carbon source, the first-order kinetic equation is fundamentally monitored during the carbon emission process. Synthetic polymers are more suitable for nitrogen removal in groundwater filtration, while agricultural wastes are ideal carbon sources for secondary wastewater filtration. Also, Fareed et al. (2020) stated that every year, as a result of energy production activities, large amounts of agricultural waste ash are produced from crop residues. The disposal of soil and ash produced has serious environmental and health problems, which are primarily due to groundwater pollution. In addition, the unavailability of land for further evacuation is another major problem associated with it. Due to the problems related to agricultural waste ash, in their study, three types of nanoagricultural waste ash were used to modify the adhesive and asphalt mixture. Rice husk ash, sugarcane stem ash and wheat straw ash were first reduced to nanoscale using a mill. These samples were then mixed with asphalt connector in terms of joint weight. Then, all samples of modified adhesive were tested from different perspectives. From the results, it can be concluded that the combination of each of the nano-waste ashes in the adhesive and asphalt mixture is a sustainable and environmentally friendly method for its disposal.
In another study, Mo et al. (2020) investigated the use of solid agricultural waste in concrete production. According to them, the increase in construction activities has led to the rapid depletion of natural resources, especially aggregates used in the production of concrete. Also, a large amount of solid waste is produced from the agricultural industry, especially from the Southeast Asian region, such as palm and coconut shells. Therefore, their study investigated the feasibility of these wastes as a potential alternative to conventional aggregates in concrete. The durability of concretes, especially those containing recycled waste, is often investigated. Therefore, their article seriously examines the published findings on the durability properties of concrete containing these agricultural wastes. Moreover, Adebisi et al. (2020) observed that the production of silicon by conventional processes is complex and occurs at very high temperatures. Therefore, in their research, some agricultural wastes have been used to produce silicon in a very simple way. Agricultural waste is generated and disposed improperly in the environment, and this is an environmental challenge. Burning them produces gases that can affect the weather. The United Nations has called on all governments to work together to reduce climate change. On the other hand, the potential of Nigerian solar energy encourages investment in photovoltaic technology, which requires silicon, and their study aims to develop an alternative application for some agricultural wastes as potential sources of silicon.
Due to a large number of researches in this field, the following paragraph can be summarized. Heniegal et al. (2020) studied the properties of clay bricks containing refinery sludge and agricultural waste. Zhang et al. (2020) presented a study to maximize the use of agricultural waste in high-density polyethylene composites. Bhat et al. (2020) produced low-cost, catalyst-free, high-performance super-capacitors based on porous nano-carbons from agricultural waste. Kapoor et al. (2020) evaluated the value of agricultural waste for a biogas-based circular economy in India.
Research gaps
To provide a broader literature review to find the research gaps, a summary of some articles related to the agricultural supply chain is provided in Tables 2 and 3. For this purpose, articles published in international journals, library resources, and reputable scientific sites in different years until 2020 have been used to collect information. The Elsevier, Springer, Taylor & Francis, and John Wiley databases have also been selected as reliable and easierto-access databases. Keywords including food supply chain, agricultural supply chain, perishable products, and fruit supply chain have been searched. For this purpose, 30 articles completely related to the subject of this research were selected and reviewed based on various factors to reveal the gaps.
Using the properties of Tables 2 and 3, we describe the gaps of the past researches. As it is shown in the table, 47% of these detailed research works used exact methods and then meta-heuristic algorithms with 40% took the second place of the used solution approach. However, simulation methods comprise only 13% of these studies. Therefore, exact and meta-heuristic algorithms have received more attention, which indicates the efficiency of these methods.
Also, 100% of these research works focused on forwarding flow, and only 7% of these research works considered both reverse flow and closed-loop mode. On the other hand, some layers of the network, such as recycling facilities, have only covered 7% of these research works. Therefore, these gaps, including close-loop, reverse logistics, and recycling facilities, need to be addressed in future works. In terms of the objective function, cost minimization covers 57% of these cases, which indicates the importance of this economic objective function. On the other hand, other important goals such as demand responsiveness and emission aspects have received very little attention. It is also evident that studies on apples and pears accounted for 20% of these studies, and other areas were less considered. Also, assumptions such as multi-product, bi-level, compost, and biogas with 30%, 3%, 7%, and 0% were less considered and should be covered. On the other hand, items (Starbird, 1988 such as strategic, planting, inventory, and multi-vehicle with 37%, 30%, 37%, and 7% received less attention, respectively, and should be covered. Therefore, the innovations of this research can be listed as follows.
• Designing a new bi-level mathematical model for the closed-loop agricultural supply chain • Reuse of agricultural waste to produce compost and biogas • Introducing new, efficient, and effective nested hybrid metaheuristics for model analysis • Providing several numerical examples to validate the proposed model
Problem definition
In the desired supply chain, raw materials such as fertilizers and pesticides are supplied by various suppliers and delivered to farms. Farms send the final products to distribution centers (DCs) after production. Also, some of the products can be sent directly from the farms to the customer areas in the form of retail, which will be possible only for a limited period due to the lack of proper storage of these products by the manufacturers. An overview of the problem under study is shown in Fig. 1.
Most agricultural products are stored in warehouses or, if necessary, in the cold stores of DCs and are sent to customer areas at different times. Depending on their type (fruits, vegetables, nuts, etc.), these products are damaged and corrupted in the sectors of farms, DCs, and customer areas (such as fruit and vegetable markets), and these corrupted values are
Customers DCs Farms
Recycling depot Compost production Suppliers Biogas Biogas applicants Fig. 1 Scheme of the desired closed-loop agricultural supply chain network collected in inverse flow by the recycling depots. These wastes are sent from the recycling depot to the two sections for making biological fertilizers (compost) and the section for making biogas. The quantities of these shipments, depending on the type of waste materials, if they are not capable of producing biogas, are transferred to the biological fertilizer production department, and in practice, the quantities of these shipments are determined using a percentage coefficient. The corrupted products are transferred to the biogas production department and after the production of gas, this energy is sent to the applicants. Also, during the production of biogas, the obtained wastes are transferred to the production of biological fertilizers, so that after the production of natural fertilizers, these products are transferred to the suppliers of pesticides and agricultural fertilizers. Since various products and materials are needed to produce biogas, some of them can be covered by this proposed chain and the rest can be provided by other wastes of supply chains.
Biogas is a type of fuel gas that is a mixture of 65% methane (CH4) and 35% carbon dioxide (CO2). Biogas is a renewable energy source from agricultural products or animal manure. Biogas is the result of the fermentation process, which means the process of degrading organic matter using micro-organisms is known as anaerobic organisms. This process takes place in special tanks in which materials with heat and enzymes are decomposed in absence of oxygen. Biogas has several advantages: 1. Produces clean fuel. 2. These gases do not emit, so they do not cause pollution.
It is very efficient.
This product has another advantage because it produces scum and the remaining scum is used as biological fertilizer. However, biogas also has disadvantages: 1. Steals land and farms available to farmers to produce crops. 2. The cost of building biogas power plants is sometimes high.
Here, the closed loop mode is quite evident. In the middle part of Fig. 1, part of the recycled materials is delivered to the suppliers of the primary supply chain and part of them leave the primary chain and are transferred to the biogas production centers in the other supply chain. In this issue, it is assumed that initially, there are the number of DCs and recycling depots, and the status of other network facilities, including the reverse logistics sector in the network design process, is determined, and the location of facilities is considered. Decisions regarding the opening and closing of the facility may change during the course.
The problem can have two levels of decision-making. On one level, the main agricultural products are considered by one decision-maker and at the next level, the products of the stage of the reverse logistics will be considered by the second decision-maker. In summary, a bi-level programming model is proposed for the design of the closed-loop agricultural supply chain network (see Fig. 2). In this proposed model, decisions are made regarding the location and allocation of facilities, the amount of material and products flow between facilities in the supply chain, items related to strategies for selecting the type of vehicle, and other items.
Given the extent of the proposed problem and the use of the closed-loop network, strategic issues, and considering several goals in bi-level programming, modeling and problem solving will have their complexities and challenges. Multi-level supply chain network design problems are among the NP-hard problems and the problem described has different dimensions and complexities. Therefore, solving it in a reasonable time, especially in medium and large sizes, will face problems, and appropriate problem-solving methods must be developed. Depending on the mathematical model and structure of the problem, these solution methods can include nested bi-level meta-heuristic algorithms.
Assumptions
The main assumptions considered in this study are explained in detail above, but some of the other assumptions are as follows: ✓ The main focus of this research is on the development of a mathematical model for the closed loop agricultural supply chain and does not tend to its implementation phase. This research also seeks to optimize the proposed model in which in addition to agricultural products as the main products of the network, to produce two new products include biogas and compost by corrupted products to add value to the network. ✓ Since this network is a supply chain of several products, so the desired products can be different and do not refer only to a specific product. For example, several types of fruits and vegetables can be selected as products. Therefore, the proposed model can be used in various fields of agriculture. ✓ The supply chain network includes suppliers, farms, DCs, customers, and reverse logistics facilities. ✓ Customers' locations are fixed and predefined. ✓ Facility capacity (supply, production, etc.) is limited. ✓ The problem is multi-period and multi-product. ✓ The initial inventory of all DCs in the first period is zero. ✓ The initial inventory is considered for suppliers in the first period. ✓ DCs and recycling depots include both existing and potential locations. ✓ Due to the perishability of products, the corruption rate is considered at three basic levels (farms, DCs, and customers). ✓ The transportation cost of products between network levels is based on the distance between points. It is assumed that several types of vehicles are available with certain capacities and costs. ✓ Only DCs can store the product. ✓ It is not possible to move the processed product between DCs.
Proposed model
This section introduces and describes the proposed mathematical model. For this purpose, first, the items required for modeling such as parameters, indices, and variables are described.
Indices
Index of suppliers f = 1, 2, …, F Index of farms d = 1, 2, …, D Index of existing and potential DCs c = 1, 2, …, C Index of customers r = 1, 2, …, R Index of existing and potential recycling depots i = 1, 2, …, I Index of compost production centers j = 1, 2, …, J Index of biogas centers l = 1, 2, …, L Index of biogas applicants p = 1, 2, …, P Index of agricultural products m = 1, 2, …, M Index of supplied raw materials t = 1, 2, …, T Index of periods v = 1, 2, …, V Index of vehicles Weight assigned to allocate waste products to biogas centers 2 Weight assigned to allocate waste products to compost production centers Coefficient for conversion of waste products to compost fpcap pft Maximum capacity of farm f for producing product p in period t sscap ms Initial supply capacity of supplier s for raw material m dhcap dpt Holding capacity of DC d for product p in period t dem pct Demand of product p by customer c in period t bdem lt Demand of biogas by applicant l in period t capr rt Maximum capacity of recycling depot r for storing products in period t capb jt
Parameters
Maximum capacity of biogas center j for storing products in period t capc it Maximum capacity of compost center i for storing products in period t Coefficient for conversion of waste products to biogas in the liter Percentage of reusable waste product in biogas centers for making compost b Big Production cost of product p in farm f hc dp Inventory holding cost of product p in DC d bc ms Buying cost of raw material m from supplier s prg j Selling price of biogas by biogas center j prc mi Selling price of raw material m by compost center i tcrb rjv Transportation cost of products between recycling depots r and biogas center j by vehicle v tcrv riv Transportation cost of products between recycling depots r and compost center i by vehicle v tcvs isv Transportation cost of products between compost center i and supplier s by vehicle v tcba jlv Transportation cost of products between biogas center j and applicant l by vehicle v tcbv jiv Transportation cost of products between biogas center j and compost center i by vehicle v pcg j Production cost of biogas in biogas center j pcv mi Production cost of raw material m in compost center i ihc ms Inventory holding cost of raw material m in supplier s
QSF msft
Quantity of supplied raw material m by supplier s to farm f in period t
MQF pft
Amount of produced agricultural product p by farm f in period t QFD pfdt Quantity of shipped product p from farm f to DC d in period t QFC pfct Quantity of shipped product p from farm f to customer c in period t QDC pdct Quantity of shipped product p from DC d to customer c in period t QFR pfrt Quantity of shipped waste product p from farm f to recycling depots r in period t QDR pdrt Quantity of shipped waste product p from DC d to recycling depots r in period t QCR pcrt Quantity of shipped waste product p from customer c to recycling depots r in period t QRB rjt Quantity of shipped waste products from recycling depots r to biogas center j in period t
QRV rit
Quantity of shipped waste products from recycling depots r to compost center i in period t
QVS mist
Quantity of shipped compost (material m) from compost center i to supplier s in period t QBA jlt Quantity of shipped biogas (liter) from biogas center j to biogas applicant l in period t QBV jit Quantity of shipped waste products from biogas center j to compost center i in period t X d Equal to 1, if DC d is constructed. Otherwise equal to 0 Y r Equal to 1, if recycling depots r is constructed. Otherwise equal to 0 IH dpt Inventoried product p in DC d at period t
ISS mst
Inventoried capacity of supplier s for raw material m in period t According to the mentioned properties and Fig. 1, two main levels of the designed network due to two expert insights, are exemplified in Fig. 2. Therefore, the proposed model is formulated as follows.
Upper-level model
subject to (2) minimize Z 1 = Shipping costs + Construction costs + Production costs + Buying costs + Holding costs (3) The objective function (2) attempts to minimize total costs of the upper-level consist of shipping costs presented in Eq. (3), construction costs presented in Eq. (4), production costs presented in Eq. (5), inventory holding costs presented in Eq. (6), and buying costs presented in Eq. (7).
Constraint (8) shows that the quantity of supplied raw materials by suppliers to farms in each period should be less than or equal to the requested amount of it by farms. Constraint (9) displays that the quantity of supplied raw materials by suppliers to farms in each period should be less than or equal to the supply capacity of suppliers. Equation (10) implies that the amount of produced agricultural products by farms in each period is related to the amount of supplied raw materials by suppliers. If this amount is less than the requested number of raw materials, it will hurt the production rate of the farms. Besides, if this amount is equal to the requested number of raw materials, it shows the full responsiveness of the demanded materials and the fraction value will be equal to 1. Therefore, the maximum capacity of farms for producing crops is multiplied with some coefficients. Here, (1-φ) shows the impact coefficient of some criteria such as irrigation and weather conditions on farm production, while φ represents the impact coefficient of raw materials (supplied by suppliers) such as fertilizers and pesticides on farm production. Equation (11) illustrates that the total agricultural products in farms minus the wasted amount can be shipped to both the DCs and customers. Restriction (12) indicates that transferring products to a potential DC is subject to its construction. Equation (13) calculates the inventory of products for DCs. This calculation is done in such a way that the inventory of the previous period plus the products received from the farms is equal to the inventory of the current period plus the products transferred from DCs to customers and recycling depots. Constraint (14) ensures that the inventoried products should be less than or equal to the holding capacity of DCs. Constraint (15) ensures that the sum of products shipped from farms and DCs is less than or equal to customers' demand. Constraint (16) counts the number of waste products shipped from farms to recycling depots. Restriction (17) shows that transporting products to a potential recycling depot is subject to its construction. Constraint (18) calculates the number of waste products shipped from DCs to recycling depots. Constraint (19) displays that shipping products to a potential recycling depot are subject to its construction. Constraint (20) computes the number of waste products shipped from customers to recycling depots. Constraint (21) shows that distributing products to a potential recycling depot is subject to its construction. Constraint (22) shows that the summation of received products to each recycling depot should not be exceeded from its maximum capacity. Equation (23) shows the initial inventoried capacity of suppliers for raw materials in the first period. Moreover, the constraints (24) and (25) show the non-negativity decision variables used in upper-level, and constraint (26) represents the binary decision variables.
Besides, the objective function (27) seeks to maximize total profits of the lower-level using subtraction of incomes from the costs. To this end, Eq. (28) calculates the total income by selling manufactured biogas and compost to its applicants and suppliers. Equation (29) also calculates the total costs of lower-level consist of shipping costs between stages and production costs of biogas and compost.
(39) QRB rjt , QRV rit , QVS mist , QBA jlt , QBV jit , ISS mst ≥ 0 ∀ all sets Constraints (30) and (32) divide the waste products received in recycling depots between biogas and compost production centers, respectively. This work done using two weighting factors which consist of ω 1 and ω 2 whose sum is equal to 1. These two weighting factors are obtained by experts' opinions. Constraint (31) shows that the summation of received products to each biogas center should not be exceeded from its maximum capacity. Also, constraint (33) shows that the summation of received products to each compost center should not be exceeded from its maximum capacity. Equation (34) shows the quantity of manufactured compost in compost centers that can be moved to suppliers. In this equality, the number of received waste products from recycling depots and biogas centers are mixed and using some procedure, the compost can be obtained. Therefore, these mixed waste products are multiplied by a conversion coefficient (conversion of waste products to compost), and the final amount of moved compost to suppliers is calculated.
Also, Eq. (35) calculates the inventoried capacity of suppliers for raw materials. To this end, inventory of the previous period plus the materials received from the compost centers and other sections is equal to the inventory of the current period plus the materials transferred from suppliers to farms. Besides, based on (Amirkhani et al., 2014), we know that compounds such as 50% water, 10% animal or human feces, and 40% rotten crops are needed to make biogas. Based on this research, 2 kg rotten crops by mixing other needed components (2.5 kg water and 0.5 kg feces) can release 1500-L biogas in 60 days, so 2 × (1500/60) = 50-L biogas release per day. Based on mentioned properties, δ = (1500/60) and in Eq. (36), this conversion coefficient is multiplied by waste products to calculate the amount of shipped biogas in liter to applicants. Constraint (37) shows that the summation of shipped biogas to applicants should not be exceeded by their demand. Equation (38) finds the number of waste products in biogas centers that can be reusable for making composts and transfers them to compost centers. Besides, the constraint (39) shows the nonnegativity decision variables used in the follower level.
Solution method
This sector describes the suggested solution methods to solve the mentioned problem. To this end, first, the encoding and decoding process is presented and then some meta-heuristic algorithms such as Genetic Algorithm (GA) and Stochastic Fractal Search (SFS) are provided. The reasons for using the meta-heuristic algorithms are the nonlinear nature of the problem and the NP-hardness of the bi-level programming (Talbi, 2013). This information is existing in the following subsectors.
Encoding and decoding
One of the most important phases in using meta-heuristic algorithms is to describe the encoding-decoding process. There are different ways to encode a problem chromosome, each for a specific problem. Since the mechanism of operation of most algorithms is performed in a continuous environment, and also our problem requires sequencing for assignment to perform, so we use the priority-based encoding approach (Gen et al., 2006). We encourage the readers to follow (Lotfi & Tavakkoli-Moghaddam, 2013) for more information. So first we fill the genes of the chromosome with random numbers between (0, 1) and then we sort them according to priority and the position of each of which are integers and are selected as allocation sequence (see Figs. 3 and 4). For example, if the chromosome with random numbers is {0.2, 0.1, 0.4, 0.8, 0.3, 0.9, 0.5}, then the allocation sequence by sorting it is equal to {6, 7, 4, 2, 5, 1, 3}. On the other hand, after encoding the problem and applying the algorithm operators to the problem chromosome, we need to calculate the variables and objective functions. Therefore, we need decoding procedures to convert the encoded problems to answers. To this end, the general form of these procedures is illustrated in Figs. 5 and 6. Figure 5 shows the allocation procedure without inventory for some sectors of chromosomes that not included inventory. Also, Fig. 6 shows the allocation procedure considering inventory for some sectors of chromosomes that included inventory. Moreover, it should be noted that the binary variable related to the opening facilities is shown in Fig. 5. This step may only apply to specific sectors of chromosomes such as sector two and sector four.
Genetic algorithm (GA)
This algorithm is proposed by John Holland (1975) and inspired by the genetic behavior of living organisms that can improve their physical condition through genetic mutations and inheritance from their parents. To this end, some random population is generated, and using two main operators (mutation and crossover), it seeks to improve the chromosome status and subsequently the state of the fitness function (Sang, 2021). Since the advent of this algorithm, various versions of it have been developed and it has also been effective in solving multi-level problems (Ma, 2016;Talbi, 2013). This algorithm is known as a model for various metaheuristic algorithms and in used in wide field of studies as a strong one such as in a joint order batching and picker routing problem (Yousefi Nejad Attari et al., 2021), location-inventory supply chain (Fathi et al., 2021), green supply chain (Gholizadeh & Fazlollahtabar, 2020), and others. Therefore, it is considered a strong and well-known algorithm in solving problems in this field, and we also use it to solve our proposed problem. It should be noted that all the algorithms used in this research are nested and among the main algorithm to calculate the high level, another lower-level algorithm is used. The pseudocode of nested bi-level GA is illustrated in Fig. 7.
Because the chromosome of this problem is filled with random numbers between (0, 1) and then an allocation sequence is obtained from the sort operator (using the gen's priority), so all the chromosomes will be feasible. Besides, according to (Demirel et al., 2014;Maghsoudlou et al., 2016;Rostami et al., 2020), single-point and double-point crossovers along with swap, displacement, insertion, and reversion mutations operators were used. These operators are performed on random number vectors to avoid the creation of decimal numbers in the allocation sequence.
Stochastic fractal search (SFS)
This algorithm is inspired by the natural phenomena of growth and created using a mathematical concept called fractal. This algorithm was first presented by (Salimi, 2015). Like most algorithms, it is population-based and starts with a randomly generated initial population (Khalilpourazari et al., 2020). Due to a large number of formulas and concepts about this algorithm, readers are advised to refer to the mentioned source. In the following, the pseudo-code of this algorithm is presented (Fig. 8). Because the chromosome of this problem is filled with random numbers between (0, 1) and then an allocation sequence is obtained from the sort operator (using the gen's priority), so all the chromosomes will be feasible. Besides, all operators are performed on random number vectors to avoid the creation of decimal numbers in the allocation sequence.
Hybrid metaheuristics
Moreover, two hybrid metaheuristics based on SFS and GA are used to search for more appropriate answers. To this end, GA-SFS and SFS-GA are used that for example in GA-SFS, the genetic algorithm works on upper-level and stochastic fractal search works on lower-level. The opposite case is also established for SFS-GA. Since the descriptions for each algorithm are described separately, we will refrain from further explanations about these hybrid algorithms. It is important to note that here each algorithm (GA or SFS) is used only for a specific level and the other level uses a different algorithm.
Example
This section reports some generated examples to verify model performance and also adjusts the values of algorithm parameters. More information is presented in the following subsections.
Parameter setting
In this section, some numerical examples are generated randomly to set proposed model parameters. These generated examples are illustrated in Table 4, and also the values of periods and vehicles are fixed by 6 and 5, respectively, for all generated examples. It is necessary to consider several agricultural products, for example, several types of fruits and several types of raw materials supplied by suppliers, including pesticides, chemical fertilizers, and biological fertilizers. Moreover, according to experts in this field, values of 0.6 and 0.4 were adopted for ω 1 and ω 2 , respectively. Finally, values of other parameters are reported in Table 5. Due to the lack of available information and momentary changes in the country under study, it is difficult to accurately state these values. Therefore, these numbers are close to the real world and the desired values can be changed for specific geographical areas.
Tuning parameters of algorithms
In this section, to calibrate the parameters of the applied algorithms, we have used the Taguchi method (Taguchi, 1986), which is one of the well-known methods in the design of experiments. According to the detailed information mentioned in the reference, this method uses some measures to reduce the number of experiments, therefore, we use a few experiment numbers instead of full factorial experiments. The important thing is that this method is only applicable to one objective function. Therefore, for single-objective mathematical models, it is sufficient to replace the value of the objective function of the model. Therefore, for multi-objective mathematical problems, a single value for the Taguchi method must be obtained using several types of standard multi-objective metrics. But this is a bi-level example, so according to (Kuo et al., To this end, it is initially desirable to report the values of the parameters of the used algorithms for different considered levels. These values are reached based on (Golshahi-Roudbaneh et al., 2017;Rahmati et al., 2013;Sarrafha et al., 2015) and illustrated in Table 6.
After setting the various levels of the algorithm parameters, it is time to run the Taguchi method using the Minitab software. After executing this method in the mentioned software, the orthogonal array L9 is selected for both algorithms. Moreover, after solving each algorithm during 30 executions, the average answer for each experiment is stored in the software. The orthogonal arrays along with resulted values of Z 1 for GA and SFS are reported in Tables 7 and 8, respectively. As a result, using the analysis of these results by the Taguchi method, the selected values of the parameters are obtained by a tool called SN diagram. Therefore, the main effects plot of SN ratios for GA and SFS are illustrated in Figs. 9 and 10, respectively. Based on Fig. 9, it can be stated that values of 0.9, 0.1, 100, and 200 are selected for Pc, Pm, N-pop, and Max iteration, respectively. Also based on Fig. 10, it can be stated that values of 1, 150, and 300 are selected for MDN, N-pop, and Max iteration, respectively. These adjusted values are also applied for the two-hybrid algorithms. . 9 The main effects plot for SN ratios of GA Fig. 10 The main effects plot for SN ratios of SFS 6 Results and discussion
Computational results
Finally, after setting the model parameters and adjusting the parameters of the algorithms, in this section, we will solve the generated examples. It should be noted that the examples are designed in small, medium, and large dimensions to further evaluate the performance of the algorithms. Also, to encode the algorithms, MATLAB software has been used and all the results have been executed under a personal computer with Windows 10 and a Core i5 CPU processor and 4 GB of RAM. To evaluate the performance of the algorithms, criteria such as the best value of the objective functions, the worst value of the objective functions, the mean of the objective functions, the CPU time, and normalized deviations (ND) have been used. The related formula to calculate ND is presented in Eq. (40).
After executing each example using the proposed algorithms and extracting the values of mentioned criteria, we compare and analyze the results. These results are presented in Table 9 and the best value for each criterion is bolded in each example.
To analyze the results of Table 9, some diagrams are used. For example, the comparison diagram of algorithms in terms of CPU time is presented in Fig. 11. Based on this figure, the SFS-SFS has the minimum execution time for all examples. Therefore, this algorithm is the best in terms of CPU time.
Also, from the perspective of the upper-level objective function, Fig. 12 illustrates these comparisons. Since this aim is minimization type, so the algorithm with the lowest value will be selected. As it turns out, SFS-GA has the best record in examples 1, 2, 3, 5, 6, 8, 10 and 12. The SFS-SFS has also gotten the best value in examples 4, 7, and 9.
Moreover, Fig. 13 shows the assessment of algorithms in terms of the lower-level objective function. Since this objective function is a maximization type, so the algorithm with the highest value will be chosen. As is clear SFS-GA having the best performance in examples 1,4,5,6,8,9,10 and 12, while SFS-SFS has gotten the best value in examples 2, 7 and 11. Also, GA-SFS had the best performance in example 3.
Furthermore, the normalized deviation is applied to review these results as shown in Fig. 14. This figure implies that the smallest deviations in almost all examples belong to SFS-GA.
After analyzing the results, we conclude that in some criteria, SFS-GA obtained better results and in others, SFS-SFS showed better performance. Therefore, to summarize, we must use a method that specifies only one algorithm for us as the best method. For this purpose, the displaced ideal solution (DIS) method (Pasandideh et al., 2015) has been used, the general structure of this method is summarized in Eqs. (41) and (42). In the mentioned method, in the first step, the value of F i is obtained by averaging resulted values of twelve generated examples for each criterion, and then, the value of F i * is determined using the lowest values for the criteria of the upper-level objective function and the highest values for the factors related to the lower-level objective function. The minimum amounts for ND and CPU time are also chosen. Finally, the values of F i and F i * are reported in Table 10.
Finally, we normalize the values of Table 10 using formula (41) and by summing the normal values, the direct distance for each method is calculated. It should be noted that the direct distance is calculated using formula (42) and the lower the direct distance value, the more desirable the answers of the mentioned algorithm than other algorithms. The normalized values and direct distances are presented in Table 11. Finally, using the results of this method, we find that the proposed hybrid algorithm SFS-GA was selected as the best method to solve twelve generated examples among four proposed algorithms. This algorithm is selected because it has the least distance (0.047) from the ideal point. On the other hand, the SFS-SFS was selected as the second-best algorithm with a direct distance of 4.3665. It should be noted that the SFS-SFS especially in large size examples showed great in solving problems. The results show that by using these analyses, better management in the real-world supply chain can be achieved and good results can be achieved in a reasonable time by using the proposed solution method. Therefore, by using these results, agricultural products can be allocated with proper planning, and also waste products can be used to make two new products that prevent both environmental pollution and produce clean fuel and useful biological fertilizers.
Sensitivity analysis
To further assess and analyze the performance of the suggested model in this section, sensitivity analysis is performed on some sensitive parameters of the model. The results are presented in Table 12. It should be noted that all these calculations were performed only for the first numerical example and the results were reported only for SFS-GA, which was selected as the best algorithm. To this end, five parameters that consist of product demand, biogas demand, farm capacity, ω 1 , and ω 2 are chosen to change.
Using the analysis of the results of this table, it can be seen that changes in five parameters that consist of product demand, biogas demand, farm capacity, ω 1 , and ω 2 cause changes in the number of objective functions as well as opened facilities. For instance, an increase in product demand can increase the total cost of the upper-level and slightly increase the objective function of the lower-level, which is a small increase due to the increase in the number of rotten products sent to the lower-level. On the other hand, increasing biogas demand only increases the lower level objective function. As well as increasing product demand and production capacity can also be opened additional facilities for storage. In addition, different changes are depicted for the two parameters ω 1 and ω 2 , which according to experts' opinions, the best value of 0.6 and 0.4 was selected for parameters ω 1 and ω 2 , respectively. What is important is the use of these analyses to improve the status of the systems in question by managers and experts in the field.
Conclusion
Globalization and liberalization of trade in agricultural and food products have changed the structure of markets. Conventional traditional supply-based marketing systems for agricultural and food products have given way to coordinated and market-based supply chains. To succeed in meeting these challenges, it is necessary for businesses affiliated with the agricultural sector to apply the supply chain management approach in the process of converting inputs into inputs to deliver products to the market or end-users. On the other hand, issues related to rotten agricultural products have occupied the minds and attention of many systems. To this end, in this research, an eight-echelon agricultural supply chain was designed by seeing suppliers, farms, distributors, customers, recycling depots, biological fertilizers centers, biogas centers, and biogas applicants. Then, a mathematical model based on bi-level programming was formulated. The purpose of the upper-level of this proposed model was to minimize the total costs of the leader level, while the lower-level was to maximize the total profit achieved by the difference between the sales of follower level products and the total costs of this level. Since such problems had computational complexity, two meta-heuristic algorithms along with two hybrid algorithms were used to solve the proposed problem. Also, several numerical examples in different dimensions were generated to further explore the performance of these algorithms. On the other hand, to achieve the best performance of these algorithms, their parameters were first calibrated using the Taguchi method. Finally, the results were reported and showed the superiority of SFS-GA over other methods. Also, sensitivity analysis was executed on some parameters of the model, and using the results, several insights were reported. These gotten outcomes can be beneficial for agricultural managers and organizations. Like other research, this research has its limitations. For example, the values of the parameters, constraints, and conditions included in this model are related to the specific geographical location under study and may change in other areas. Therefore, the results obtained in this research for implementation in other areas and geographical areas should be reviewed. Another limitation is the high inflation and uncertainty in this geographical location, which causes the values of cost-related parameters to vary. As a final point, several guidelines for future studies are delivered as follow. Applying uncertainty in modeling problems such as robust programming, fuzzy sets, or stochastic programming can be useful and contribute to the complexity of the model and its proximity to the real world. Utilizing new metaheuristic and heuristic algorithms can lead to better answers and even reduce problem solving time. Considering green and sustainability aspects in modeling and integrating this SCM with other SCM can also be studied.
Funding None.
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Domain: Agricultural and Food Sciences Environmental Science
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Dust in the Housing of Laying Hens: A case study
As dust particles in laying poultry houses can have negative effects on health and on the environment, this study aimed to measure and compare dust concentrations in egg production sheds. The experiment was carried out in three sheds: Californian shed (G1), conventional closed shed with artificial ventilation (G2) and conventional closed shed without artificial ventilation (G3)
INTRODUCTION
In meat and laying poultry production systems, air quality can be affected by high dust concentrations (Le Bouquin, 2019), which can cause health problems in employees and animals (Al Cambra-Lopez, 2011). Diseases induced by inhalation of different bioaerosols are related not only to their biological properties and chemical composition, but also to the number of inhaled particles and the place where they are deposited in the respiratory system. NIOSH (1998) determines the classification of dimensions by size (inhalable <100 um, thoracic <25 um and breathable <10 um) and as assessment methods (total or breathable dust).
In this context, the study aims to measure and compare dust concentrations in egg production sheds.
MATERIAL AND METHODS
The study was carried out in poultry production units (eggs), and the sheds are located in Cuité -Paraíba, Brazil, at 06º 29 '01 "S latitude and 36º 09 '13" W longitude. The experiment was carried out in the production phase, in different types of sheds: Californian shed (G1), conventional closed shed with artificial ventilation (G2) and conventional The collection of breathable dust was carried out during 1 day of production and repeated in the three sheds, totaling one sample for each shed. The methodology used was defined by NIOSH (Osha, 1994), using the BDX-II sampling pump (brand: Sensidyne), calibrated for air flow rate of 1.7 L min - 1 with acceptable variation of 5%, coupled to the breathable dust cyclone with cassette, containing a 5μm PVC (polyvinyl chloride polymer) membrane filter with a diameter of 37 mm, previously sterilized. The device was attached to the worker's clothing at the height of the respiratory zone and removed at the end of the workday.
Study of collected material: 1-Weighing membrane filters before and after collection.
2-Image recording on the glass slide, with Olympus BX51 optical microscope -5x optical magnification.
3-Size study, with Olympus Imaging Solution software, where the equivalent diameter is given by the length of any linear intersection, evaluating the distance between two lines tangent to the particle's projection, in a pre-fixed direction (horizontal and vertical). The method used to measure the particle size by microscopy was the diameter of the functions, which determines the distance between two tangent lines and the design of verification in the horizontal and vertical bars, providing information about size, shape and color, called the FERET method (Santos, 2001).
4-To express the results, the calculation of the sample concentration was performed based on ACGIH -American Conference of Governmental Industrial Hygienists (1998), according to the instructions and expression of NHO-08 for the collection of solid particulate material suspended in the work environment (Fundacentro, 2009).
RESULTS AND DISCUSSION
In the collection carried out in the 3 sheds, the largest amount of dust was found in G2, so it is possible to infer that the use of artificial ventilation and the increase in air speed help to remove dust from the environment, whereas G1 had the lowest amount. This shed has side openings that increase the air flow and take the dust to the external environment; another difference is the number of hens housed and the, height of the cages (1.30 m), whereas in G2 and G3, the height of the cages reaches more than 3.0 m, and the amount of dust released in the galleries is over the respiratory zone. Considering the LEO -Occupational Exposure Limit, the maximum concentration is related to the nature and time of exposure to the product, which will not cause damage to the health of the worker during his working life under the condition of 8 hours of daily exposure. It is noted in the results of the evaluations that the tolerance limits stipulated by ACGIH (2013) in both jobs were not exceeded.
According to the classification of particles by size (inhalable <100 μm, thoracic <25 μm and breathable <10 μm) of NIOSH (1998), the results found in the present study were 13% inhalable, 83% thoracic and 4% breathable. These particles can easily penetrate the respiratory system and transport microorganisms and fragments related to activities in the environment, such as food scraps, feathers and animal skins. Even with fractions above 100 μm, in 17%, the existence of smaller dust particles cannot be ruled out (Figure 1). In terms of occupational health, ultra-fine particles may be more toxic than larger particles due to their aspects of deposition and disposition in the worker's body, but particles with the largest surface area by mass can act as a catalyst for reactions and their increased surface area could act as a transporter for microorganisms. Takai et al. (1999), in closed and controlled environment sheds, for laying hens, found that the concentration of inhaled dust, fraction <100 μm of total dust, varied from 3.83 μm to 10.4 µm and with the means of dust inactivation around 3.60 μm.
Housing of Laying Hens: A case studyclosed shed without artificial ventilation (G3), and the birds housed were in the 22nd week of housing.
Table 1 -
Dust collected by shed.\===
Domain: Agricultural and Food Sciences Environmental Science. The above document has 2 sentences that start with 'The experiment was carried out'. It has approximately 891 words, 26 sentences, and 17 paragraph(s).
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Use of Limiting Nutrients for Reclamation of Non-responsive Soils in Northern Ghana
A better understanding of soil fertility factors that constraint positive crop response to fertilizer inputs will facilitate the improvement of soil nutrient management. In this study, a nutrient omission trial was carried out in a greenhouse condition to identify soil chemical properties limiting in non-responsive soils and to ascertain their effect on soybean (Glycine max) production. The treatments evaluated were control (distilled water), complete nutrient solution (all nutrients), and complete solution with the omission of each of N, P, K, Ca, Mg, and S and micronutrients (Fe, Zn, Cu, Mn, B, and Mo) arranged in a completely randomized design with three replications. After the greenhouse study, the identified limiting nutrients were tested with or without FertiSoil (commercial compost) in a 3 year field experiment. Results of the soil analyses showed low fertility status of the non-responsive soils. The sufficiency quotient index revealed non-responsive soils in all the sites to be predominantly limiting in P and K. The occurrence of other limiting nutrients was also identified: Pishegu (Zn, B), Serekpere (Mg, S), Daffiama Saapare (Ca, Mg, S), and Naaga (Mg, S, Zn, B). The nutrient inputs positively influenced soybean yield response in all the locations. The application of PKZnB with FertiSoil and FertiSoil alone significantly increased soybean grain yields by 585 and 477 kg ha−1, respectively, at Pishegu. Soybean grain yields also increased by 585, 573, and 364 kg ha−1 under the FertiSoil, PKMgS + FertiSoil, and PKMgS applications at Serekpere, respectively. At Daffiama Saapare, the highest (103%) percent increase in soybean grain yield was recorded from the combined application of PKMgSCa and FertiSoil. However, the application of FertiSoil and PKMgSCa singly equally increased soybean grain yield by 77%. Percent soybean grain yield increases of 86, 84, and 74% were observed when PKMgSZnB + FertiSoil, PKMgSZnB, and FertiSoil were applied, respectively, at Naaga. In absolute terms, 83% of the fields had a positive response to mineral fertilizer and 93% to FertiSoil and mineral fertilizer + FertiSoil applications. Organic amendment and/or site-specific fertilizer applications are the best options for alleviating poor or no crop responses to inputs and improve productivity on non-responsive soils.
A better understanding of soil fertility factors that constraint positive crop response to fertilizer inputs will facilitate the improvement of soil nutrient management. In this study, a nutrient omission trial was carried out in a greenhouse condition to identify soil chemical properties limiting in non-responsive soils and to ascertain their effect on soybean (Glycine max) production. The treatments evaluated were control (distilled water), complete nutrient solution (all nutrients), and complete solution with the omission of each of N, P, K, Ca, Mg, and S and micronutrients (Fe, Zn, Cu, Mn, B, and Mo) arranged in a completely randomized design with three replications. After the greenhouse study, the identified limiting nutrients were tested with or without FertiSoil (commercial compost) in a 3 year field experiment. Results of the soil analyses showed low fertility status of the non-responsive soils. The sufficiency quotient index revealed non-responsive soils in all the sites to be predominantly limiting in P and K. The occurrence of other limiting nutrients was also identified: Pishegu (Zn, B), Serekpere (Mg, S), Daffiama Saapare (Ca, Mg, S), and Naaga (Mg, S, Zn, B). The nutrient inputs positively influenced soybean yield response in all the locations. The application of PKZnB with FertiSoil and FertiSoil alone significantly increased soybean grain yields by 585 and 477 kg ha −1 , respectively, at Pishegu. Soybean grain yields also increased by 585, 573, and 364 kg ha −1 under the FertiSoil, PKMgS + FertiSoil, and PKMgS applications at Serekpere, respectively. At Daffiama Saapare, the highest (103%) percent increase in soybean grain yield was recorded from the combined application of PKMgSCa and FertiSoil. However, the application of FertiSoil and PKMgSCa singly equally increased soybean grain yield by 77%. Percent soybean grain yield increases of 86, 84, and 74% were observed when PKMgSZnB + FertiSoil, PKMgSZnB, and FertiSoil were applied, respectively, at Naaga. In absolute terms, 83% of the fields had a positive response to mineral fertilizer and 93% to FertiSoil and mineral fertilizer + FertiSoil INTRODUCTION Soil degradation is a major global problem, but more prominent in developing countries where the majority of the populace depend on crop production for their livelihoods (1). Poor land management is the major cause of land degradation among biophysical, socioeconomic, and political factors (2). Continuous cropping with little or no nutrient replenishment has led to soil nutrient mining across sub-Saharan African (SSA) countries especially on smallholder farms (3). Consequently, crop yields obtained from smallholder farms are far below the potential yield resulting in yield gaps. Research efforts to improve soil fertility in SSA over the last three decades have mainly focused on N, P, and K fertilizers (4). However, continuous application of such fertilizers alone has contributed to the depletion of other essential nutrients such as B, Zn, Cu, Fe, and Mn (5), triggering lack of response to future fertilizer applications and reduction in crop yield. Non-responsive soils are soils that do not respond to fertilizer application due to other constraints besides the nutrients contained in the fertilizer (6). Nonresponsiveness of a soil to mineral fertilizer application has been attributed to edaphic factors such as soil fertility gradients, nutrient depletion, soil type, low soil organic matter, acidity, and moisture stress and environmental factors (7,8). Soils that are non-responsive to mineral fertilizer applications are increasingly becoming widespread in SSA. Kihara et al. (9) found 50% of the study sites in Tanzania, Malawi, Kenya, Mali, and Nigeria to be non-responsive to fertilizer application and organic amendments. Zerihun et al. (10) also found over 25% farm sites non-responsive to P fertilizers in western Ethiopia. Agronomical trials implemented by N2Africa project putting nitrogen fixation to work in northern Ghana observed 28% of fields with low crop response to P fertilizers (11). The occurrence of non-responsive soils increases the variability of crop responses to best-fit management practices that worsen the yield gap. To address the non-responsiveness of crops to fertilizer inputs, various diagnostic studies have revealed deficiencies of secondary and micronutrients (Ca, Mg, S, Cu, Zn, B) as a major cause (9,12,13). There is, however, lack of systematic and comprehensive knowledge about nonresponsive soils, constraints in such soils, and their management in maximizing crop response to fertilizer inputs. In order to optimize crop response and nutrient efficiency, there is a need for proper nutrient management strategies that should be addressed. The Sustainable Development Goal 15.3 by the United Nations aims toward land degradation neutrality (LDN) and land restoration by the year 2030 (14). A credible option for restoring the productive capacity and quality of the soil is to identify the underlying limiting factors and address them. This can be achieved through a site-specific nutrient management with nutrient deficiency diagnosis. The aim of this study was to characterize and identify nutrient deficiencies of non-responsive soils and evaluate the effect of balanced nutrition on crop yield.
Selection and Description of Poor Non-responsive Sites
Study sites were purposively selected from N2Africa project area in the Northern, Upper West, and Upper East regions of Ghana for agronomic trials during cropping seasons of 2011 and 2012 (11). Soils non-responsive to P fertilizer application were determined by comparing the grain yield of P treated plots with the control plot, and where the control yields were significantly higher or equal to the P treated plots, the soils were designated as non-responsive (6). Seventy-four (74) fields were identified to be non-responsive to P fertilizer. The 74 fields were within 39 communities in the Northern (14), Upper East (15), and Upper West regions (10), respectively. The Northern region falls within the Guinea savannah, and the Upper East is of the Sudan savannah. The Upper West region is sub-divided into two (2) agro-ecological zones, the southern part being the Guinea savannah and the northern and north eastern part. The Guinea and Sudan Savannah agro-ecological zones are distinguished by a unimodal rainfall season. A 10 year average annual rainfall for Northern, Upper East, and Upper West regions was 1,122, 927, and 817 mm, respectively (15).
Soil Sampling and Analyses
Soil samples from each of the 74 non-responsive soil fields were collected for physico-chemical analyses. In each field, 10 soil samples were randomly taken from a 20 cm depth with an auger and thoroughly mixed to form a composite sample. A sub-sample was then taken and processed for soil physicochemical properties at the Soil Science laboratory, Kwame Nkrumah University of Science and Technology (KNUST). Soil pH was determined in a 1:2.5 (soil:water) ratio, and total N was determined by the macro Kjeldahl method as described by Bremner (16), available P by the Bray 1 method (17), and organic carbon by the modified Walkley and Black procedure as described by Nelson and Sommers (18). Exchangeable K, Ca, and Mg were extracted by 1 M ammonium acetate (NH 4 OAc) solution at pH 7 as described by Black (19). Iron, zinc, copper, and manganese were extracted with 0.005 M DTPA (20), and particle size distribution was determined by the hydrometer method (21).
to the modified Hoagland's half strength nutrient solution as described by Paradiso et al. (23) specific to soybean requirement. The rate of ion concentration for the nutrient solution was 7.5, 0.5., 3.0, 2.5, 1.0, 1.0 mM/L (N, P, K, Ca, Mg, S) and 60.0, 7.4, 0.96, 1.04, 7.13, 0.01 µM/L (Fe, Mn, Zn, Cu, B, Mo). The experiment consisted of eight different nutrient solutions and a control arranged in a completely randomized block design and replicated three times (eight nutrient solution × three levels) as presented in Table 1.
Growth and Nutrient Sufficiency
Soybean shoots (one shoot per pot) were measured at 24 and 34 days after sowing (DAS). Regular observations were made to detect visual nutrient deficiency symptoms on foliar parts of plants. At 24 and 34 DAS, measurements were taken to establish the relative growth rate (Rs) and nutrient sufficiency quotients. The relative growth rate measurement was determined by dry matter increase using the pairing method developed by Evans (24) as follows: where Rs is the relative growth rate (g g −1 day −1 ), ln is natural logarithm, and W 2 and W 1 are mean shoot dry weights in grams per pot at times t 2 and t 1 of growing period.
To measure the availability of a nutrient, the sufficiency quotient (SQ) as an index was used to determine the differences in growth between plants on an omitted nutrient solution and the complete solution (25). When the value of SQ is 1, the availability of that particular nutrient in the soil was considered as high as that in the solution. Nutrients with SQ values of 0-0.25, 0.25-0.5, 0.5-0.75, and >0.75 were most limiting, limiting, moderately limiting, and sufficient, respectively (22,26). To ease interpretation, results were expressed as percentage, with the complete solution taken as 100%. The SQ is expressed as: where SQ x is the sufficiency quotient for an omitted nutrient, (Rs)C is the relative growth rate of plants growing on a complete
Application of Mineral Nutrients and Compost to Rehabilitate Non-responsive Soils
Following the results obtained from the nutrient omission trial, a 3 year field experiment was conducted on non-responsive soils in Northern, Upper West, and Upper East regions of Ghana to determine the impact of the identified limiting nutrient applications on the non-responsive soils. The experiment evaluated four (4) treatments; (i) control (no input), (ii) mineral fertilizer as per identified limiting nutrients in each location, (iii) FertiSoil (commercial compost) only, and (iv) mineral fertilizer + FertiSoil. Compost samples were air-dried, milled, and sieved through a 2 mm mesh for analyses ( Table 2). Organic C (Walkley and Black wet oxidation method), total N (Kjeldahl method), phosphorus (Bray P 1), and potassium ammonium acetate flame photometry method of the samples were determined. Lignin content was determined using the Acid Detergent Fiber (ADF) method as described by Van Soest and Wine (27) and polyphenol content by the Folin-Denis method (28). Dry matter content was also determined. The compost used for the study was a commercialized product called FertiSoil produced by DeCo! sustainable farming in Tamale, region, Ghana. The field layout consisted of 12 plots of 5 × 5 m dimension separated by a 1 m buffer. Four treatments were tested in a randomized complete block design with three replications. Mineral fertilizers were applied in bands with triple super phosphate (TSP) at a rate of 30 kg P ha −1 , muriate of potash (MOP) at a rate of 20 kg K ha −1 , and magnesium sulfate (MgSO 4 ) for Mg and S at a rate of 2.5 and 0.5 kg ha −1 , respectively. Calcium sulfate (CaSO 4 ) was applied at a rate of 15 kg Ca ha −1 , zinc sulfate (ZnSO 4 ) at a rate of 2.5 kg Zn ha −1 , and fertibor at a rate of 0.5 kg B ha −1 at 2 weeks after sowing. FertiSoil was applied at a rate of 5 t ha −1 to the respective plots and mixed with the top soil prior to planting. Soybean cultivar "Jenguma" (TGx series) was sown at two seeds per hill at a distance of 75 cm × 10 cm. A bradyrhizobium inoculant (Nodumax) was applied to the seed at a rate of 5 g kg −1 , and sowed after air drying for 30 min. Soybean plants were harvested at full maturity (R 8 stage), threshed, and winnowed. Grain yield was then calculated on per hectare basis.
Statistical Analyses
All statistical analyses were conducted with JMP R Pro 13.0.0 (SAS Institution Inc., Cary, NC, 1987-2007). A descriptive statistic was performed on three replicates of each soil sample after laboratory to determine the mean and standard deviation of soil physico-chemical properties. Data in the nutrient omission trial were subjected to analysis of variance (ANOVA), where overall treatment means were significant at p < 0.05 and the means were separated with Tukey HSD test. A mixed effect linear model was performed to assess the effect of nutrient inputs on grain yield. Location and nutrient input were the fixed factors, and the cropping year and replication were the random factors. Cumulative probability curves of absolute and relative yield response to nutrient application with reference to the control per individual farms were calculated (29).
Assessment of Nutrients Limiting in Non-responsive Soils
Effect of Mineral Nutrient Solutions on Relative Growth Rate (Rs) Significant variations (p < 0.05) in relative growth rates were recorded from growth analysis of the various treatments across locations except for Daffiama-Dakyea (Table 4). Relative growth rate decreased with each nutrient omitted from the Complete recording the highest 0.153 g g −1 day −1 at Pishegu. At Serekpere, Rs decreased significantly with the omission of macronutrients,
Soybean Responses to Mineral Fertilizers and Organic Amendment Application
Results on the effect of mineral fertilizers and FertiSoil on soybean grain yield are shown in Table 6. Significant (p < 0.05) differences in soybean grain yield were observed among treatments across sites. The application of PKZnB + FertiSoil and FertiSoil significantly (p = 0.002) increased soybean grain yield by 55 and 45% over the control, respectively, at Pishegu. The nutrient inputs significantly (p < 0.001) increased soybean grain yield compared to the control at Serekpere. Addition of PKMgS increased soybean grain yield by 364 kg ha −1 , whereas PKMgS + FertiSoil increased grain yield by 573 kg ha −1 and 585 kg ha −1 , which was also obtained with FertiSoil application. At Dafiama Saapare, the combined application of PKMgSCa and FertiSoil significantly (p = 0.004) increased soybean grain yield by 103%, while PKMgSCa and FertiSoil separately, equally produced a grain yield increase of 77%. Soybean response to PKMgSZnB and/or FertiSoil also varied significantly (p < 0.001) at Naaga ( Table 6). The highest (1,201 kg ha −1 ) grain yield was produced under the PKMgSZnB + FertiSoil treated plots, followed by PKMgSZnB (1,188 kg ha −1 ) and FertiSoil (1,122 kg ha −1 ). The absolute response (treatment yield minus control yield) and relative response (treatment yield minus control yield divided by the control yield, multiplied by 100) are presented in Figures 1A,B. Cumulative soybean yields over the three cropping seasons show a large variation of crop response to mineral fertilizers and fertisoil across farms and within treatments (Figure 1). In absolute terms, 63, 72, and 89% of the fields had a positive response to mineral fertilizer + fertisoil, fertisoil, and mineral fertilizer applications, respectively, in relation to the control (Figure 1A). Fifty percent of the farmers increased their soybean grain yield by 712.50 kg ha −1 or more with fertisoil application. In absolute terms, 54% of farmers increased their soybean grain yields by 715.65 kg ha −1 or more with mineral fertilizer + fertisoil application. Sixty-seven percent of the farmers had absolute increase in soybean grain by 700 kg ha −1 or more with mineral fertilizer application. Gains of over 1,000 kg ha −1 of soybean grain yield were obtained by 11, 28, and 37% fields with mineral fertilizer, fertisoil, and mineral fertilizer + fertisoil application, respectively ( Figure 1A). There was a 2% probability chance of achieving a negative response due to the application fertisoil and mineral fertilizer + fertisoil.
Farmers regard a 10% or more increase in grain yield by a treatment as the least observable increment. A relative increase of 10% or more occurred on 80, 94, and 96% fields treated with mineral fertilizer, mineral fertilizer + fertisoil, and fertisoil, respectively ( Figure 1B).
DISCUSSION
Physical and chemical characteristics of soil are important soil quality indicators that directly or indirectly affect the quality of plant growth and its products. The nutrient levels of nonresponsive soils in northern Ghana were generally below critical levels for crop production ( Table 3). The result confirms the low inherent fertility status of soils of the Guinea and Sudan savannah agro-ecological zones of Ghana (31). Practices such as intensive cultivation (32), poor farming practices (33), overgrazing (34), and bushfires (35) further deplete the soil of its essential plant nutrients in varying degrees. In a related study, Fermont et al. (36) observed that low soil fertility limited cassava response to N, P, or K fertilizers in East Africa.
All the sites surveyed in northern Ghana were critically low in organic C, N, and P. This is in line with findings of Antwi et al. (37), Asei et al. (38), and Tetteh et al. (39) on soil fertility levels in the Guinea and Sudan savannah zone of Ghana. This is attributable to the dominant soil groups of the region, which are highly weathered with poor soil texture, characterized by low organic matter content and low cation exchange capacity, thereby causing low nutrient levels (40). The low carbon, N, and P contents can also be explained by the low vegetative cover, low input application, biomass removal, regular annual bush fires, erosion, and leaching during rainy seasons (41,42). The high temperatures of the northern savanna zones further exacerbate the low carbon content by increasing the rate of mineralization, which decreases carbon accumulation (43).
According to Lal (44), an optimum range of soil organic carbon (SOC) is required to improve water and nutrient retention capacities. This is also in line with results obtained by Musinguzi et al. (45) that low fertility fields (<1.2% SOC) had lowest response to mineral fertilizer N application on a Ferralsol. Such low SOC soils are vulnerable to N leaching, and hence, the soils are less responsive to N fertilizers (46). Additionally, Benbi and Brar (47) also found no response to P fertilizer application under low SOC soils and which Bationo et al. (48) attributed to the high P sorption of soils low in SOC.
Exchangeable cations (K + , Ca 2+ , and Mg 2+ ) were found to be moderate in some communities of the three regions except Mg, which were moderate for all the sites. However, few sites in the Chereponi district of the Northern region had high Mg levels. The results obtained in this study are consistent with results obtained by Tetteh et al. (49) who reported low to moderate nutrient levels and higher values for exchangeable cations in soils of the northern part of Ghana. The substantial differentiation of soil nutrient levels across communities confirms the heterogeneity of smallholder farms in SSA (50).
Iron and Zn levels varied from low to very low across all the study locations. In contrast, Awuni and Reynolds (51) reported medium to optimum levels for Fe and Zn in some sites of northern Ghana attesting to the high variability in Fe and Zn contents of the soils. Copper levels were low in soils in the Northern and Upper West regions except Upper East, which was medium. Previous research by Oluwadare et al. (52) has also shown Cu deficiency in the Guinea savannah soils of Nigeria. Medium levels of Mn were observed in all the soil samples. The soils studied by Boateng et al. (53) also showed moderate Mn levels in the Guinea savannah zone of Ghana. A review by Dimkpa and Bindraban (54) documented that micronutrient deficiencies affect the optimal function of plant metabolism processes of N, P, and K and crop responses.
The pH range (5.5-6.0) observed in the study ( Table 3) was within the pH values obtained by Tetteh et al. (49) in a study to evaluate soil suitability indices for cereal production in northern Ghana (5.0-7.5). The soil pH level influences the solubility and availability of nutrients. Ch'ng et al. (55) and Miller (56) reported soil with pH below 6 to be deficient in P, as soil P is adsorbed to Al and Fe oxides, rendering it insoluble and unavailable to plants. The high P fixation in soils having a moderately acidic pH is primarily due to the presence of acid-forming cations associated with H + , Al 3+ , Fe 2+ , and Fe 3+ and the high levels of sand with low buffering capacity (57). This may partly explain the lack of response to P fertilizers. The texture of the soils was sandy and is mainly accounted for by the parent material (58). The high mean sand percentages observed in this study correspond with the findings of Ziblim et al. (59) and MacCarthy et al. (60). The dominance of sand in the northern savannah agro-ecological zones of Ghana is because the soils are mostly developed from granite and Voltanian sandstone (61). Zheng et al. (62) studied the influence of soil texture on P fertilizer and observed that soils with high sand and low clay content affect P uptake; such soils have lower P supply, available water, and P diffusion rates compared to fine textured soils.
To estimate the availability of a particular nutrient, the sufficiency quotient, which measures the relative growth rate between a seedling on a complete and an omitted nutrient solution, was determined (22,26). Soils of Pishegu were found to be limiting in P, K, and micronutrients (Zn, B) ( Table 5). Essential nutrients like P, K, Mg, and S were found to be limiting in both Serekpere and Daffiama Saapare, with SQ indices ranging from 21 to 41%. However, the index showed nutrient levels in Daffiama-Dakyea to be sufficient, with SQ values >75. It is also worth noting that the Daffiama Dakyea site was within the community a few meters away from the farmer's house. According to Vanlauwe et al. (63), such fields have high soil fertility status and are unlikely to respond to added inputs. Kihara et al. (9) classified such fields as fertile non-responsive soils.
Nutrient sufficiency quotient for all omitted nutrients were below 50% indicating P, K, Mg, S, and Micronutrients (Zn and B) to be limiting at Naaga. Nutrients with SQ of <50 require their application to soils to obtain optimum soybean growth. Foli (64) observed omitted micronutrients, Mg, P, and K nutrient solutions to have SQ values of 14-39%, specifying these nutrients to be deficient, while those above 75% had sufficient availability in the soils of northern Nigeria. The identified secondary and micronutrient (Mg, S, Zn, B) limitations correlated fairly with those of Wortmann et al. (65) and further supported the concept of balanced fertilizer application in SSA (66).
Targeting fertilizer use to variable soil fertility conditions combined with organic amendments is necessary for efficient crop response in smallholder farms in SSA (67). After the three cropping season, the combined application of FertiSoil and mineral fertilizers accounted for the highest improved grain yield at Pishegu, Serekpere, Daffiama Saapare, and Naaga ( Table 6). The response of soybean yield to sole organic input or in combination with inorganic fertilizers is consistent with other studies that confirm that the soybean and maize yield increased with the integration of compost and mineral fertilizer application or sole compost application (68)(69)(70). Brempong et al. (71) reported improved synergism and synchronization between nutrient release and plant uptake upon the integrated application of organic and inorganic nutrient sources, which resulted in better crop growth and yield. Furthermore, Sileshi et al. (72) also observed through the integrated application of organic amendment and mineral fertilizer that nutrient use efficiency is enhanced resulting in higher crop grain yields. Blanchet et al. (73) also reported highest yield with organic amendment incorporation and attributed it to increasing SOC content and soil biological properties. Additionally, Adeli et al. (74) explained the effect of organic amendment on grain yield increase to improved nutrient availability for plant uptake and enhanced soil physical, chemical, and biological properties leading to improved crop yields. Generally, the improved grain yield to the applied limiting nutrients suggests that these nutrients were hindering crop response to P fertilizer on soils that were previously not responsive to it (75). This observation could be described as the Liebig-synergism where increased yield is as a result of applying most limiting nutrients and resolving deficiencies (76). Soil fertility restoration is necessary to increase agricultural production, food security, economic development, land conservation, and environmental protection (77).
The performance of each nutrient option on non-responsive soils was demonstrated by the cumulative probability curves (Figure 1) and provides the farmer with information on the outcome of maintaining or switching management practices (78).
CONCLUSIONS
Non-responsive soils in northern Ghana are widespread, which are characterized by varying nutrient levels low in SOC. The nutrient omission trial revealed P and K to be most limiting in all the soils of the three regions, followed by Mg, S, Zn, and B. In this research, application of balanced fertilization and/or organic input improved soybean grain yield. Nutrient deficiencies are the major causes of poor crop response to fertilizer inputs, which further hinder crop productivity, and addressing these limitations is one of the key mechanisms of bridging crop yield gap. This information will assist knowledge of crop response to fertilizer and implementation of fertilizer recommendation and soil fertility management strategies for optimum and sustainable crop production.
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
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Domain: Agricultural and Food Sciences Environmental Science
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Optimizing sowing window for mungbean and its adaptation option for the South-central zone of Bangladesh in future climate change scenario using APSIM model
Field experiment on sowing dates was carried out with BARI Mung-6 during pre-monsoon (kharif-I) season of 2021 for the evaluation of Agricultural Production Systems Simulator (APSIM) crop model. The APSIM model was parameterized using data from March 10 sowing, while validation was done with other sowing dates and data from literatures. Simulation was done with elevated temperatures (1, 2-and 3-˚C) to find out the adaptation option against future temperature stress situations. The model was run for different sowing dates using long-term (1981–2021) historical weather data. The evaluations showed that the model performance was satisfactory in predicting crop phenology, total biomass and grain yields of BARI Mung-6. Simulated grain yields during March
Introduction Mungbean (Vigna radiata (L.) Wilczek) is the third most important summer pulse crop of Bangladesh. The optimum mean temperature for potential yield of mungbean lies between 28å nd 30˚C [1]. Its grains contain about~24% easily digestible protein, provides a significant amount of fiber, antioxidants and minerals. Grains can be consumed as whole or split, as sprout or soup [2]. As mungbean grains contain a large amount of protein, it can be considered as an important component of balanced diet. Most Bangladesh households consume lentil or mungbean in their diet. But due to less acreage and low average yield of mungbean, there is a gap between its demand and supply resulting in high selling prices. In Bangladesh, mungbean occupied about 11.8% of the pulses growing areas with an average grain yield of 0.80 t ha -1 [3]. There is a little scope to increase production areas of mungbean to meet its demand due to the preference of rice production, the staple food crop in Bangladesh. So, one of the options would be to increase grain yield from unit area through adoption of proper agronomic practices.
Mungbean is a short duration crop which is cultivated after harvesting of dry season crops (wheat, mustard, and lentil). It can fix atmospheric nitrogen and a good source of protein. A small portion of fixed nitrogen is also utilized by the succeeding non-legume crops [4]. In farmer's field, the average grain yield of mungbean is very low due to lack of quality seed, and inappropriate agronomic management practices adopted by the farmers of which sowing date plays an important role in growth, development and grain yield. Crop establishment is greatly affected by sowing dates because of variability in weather factors, especially rainfall patterns and its amounts. Mungbean is grown in kharif-I (the major growing season from last week of February to middle of March) and kharif-II (mid-August to last week of September) seasons in Bangladesh. In the South-central zone of Bangladesh, mungbean usually suffers from untimely heavy rainfall at sowing or at emergence time that cause total crop failure. Pre-sowing heavy rain causes delay in sowing resulting in poor grain yield. Delayed sown mungbean exposed to high temperature and heavy rainfall that hamper growth and development and ultimately reduces grain yield. Delayed sown crop also faces excess rainfall at the time of reproductive phase, which is the root cause of grain yield reduction by 39-67% [5]. Under climate change situation, rainfall patterns and its amounts are changing year after year making it very difficult to follow the existing management practices for obtaining higher grain yield.
In general, optimum sowing date for individual crop is identified through field experiment over the locations which is time consuming, labor and monetary intensive processes. Crop simulation model can be used to reduce the number of field experiments in identifying optimum sowing dates for mungbean and ultimately it will be helpful for addressing climate change situations. Calibrated and validated simulation models can effectively minimize cost and time requirement for determination of suitable agricultural practices for a particular crop to be grown under diverse conditions [6,7]. However, evaluation of a crop simulation model involves establishing confidence in its capability to predict outcomes experienced in the real world.
The APSIM model framework [8] (www.apsim.info) was selected because of its suitability for tropical and subtropical soil and crop management conditions [9,10]. This model satisfactorily simulated yields of mungbean [11,12]. Moreover, the model has been used successfully for simulating efficient production, improving risk management, crop adaptation, and sustainable production of different crops. To study the applicability of the APSIM model, it is necessary to test the model performance in different geographical locations for different crops. As mungbean crop module is available in APSIM, we have used this model for evaluating its performances in Bangladesh conditions. The main objectives of this study were to provide an overall assessment of the APSIM model to simulate growth and grain yield of mungbean (var. BARI Mung-6) as well as to find out optimum sowing window and to assess the adaptation options against future temperature stress on mungbean in the South-central zone of Bangladesh.
Experiments for model calibration and evaluation
Field experiment was conducted at research field of Plant Physiology Division, Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh during pre-monsoon (kharif-I) season (March to July) of 2021. The area is located at 23˚99' N latitudes and 90˚42' E longitudes.
Experimentation
A short duration (60-65 days) early maturing mungbean variety BARI Mung-6 was sown on March 10, March 20, March 30, and April 10 during kharif-I, 2021 following a Randomized Complete Block design with three replications. Each experimental unit was 3.0 m × 2.4 m with eight rows at equal spacing of 30 cm. The experiment followed BARI standard management practices to avoid stresses from water, nutrients, insect pests, and diseases. Seeds were sown @ 35 kg ha -1 . Before sowing, seeds and soils were treated with Provax 200-EC (@ 2.5 g powder kg -1 seed) and furadan 3G @ 5 kg ha -1 to prevent seed and soil borne diseases, correspondingly. The soil was nourished with fertilizers @ 12-12-16-8.0-1.0-0.6 kg ha -1 N-P-K-S-Zn-B in the form of urea, triple super phosphate, muriate of potash, gypsum, zinc sulphate, boric acid, respectively. Seeds were sown continuously in furrows made by hand rake maintaining 30 cm spacing between lines. Following the establishment of seedlings, thinning was done to maintain about 33 plants m -2 , weeding and other intercultural activities were performed as needed. At maturity, harvesting s done by two hand pickings of pods.
Data collection
Data on emergence, end of juvenile stage, floral initiation, flowering, pod initiation, physiological maturity were recorded/estimated. Yield and yield contributing data were recorded on whole plot basis excluding border rows. Grain and biomass yields at harvest were adjusted to 13% moisture and shown as kg ha -1 .
APSIM-mungbean model
Model description. The APSIM model [8] version 7.10 was used to simulate the phenological development, grain and biomass yields of tested mungbean variety. Correction factors for grain and biomass yields at 13% moisture content were incorporated in the model. The modules used genotypic coefficients of mungbean, soil water, soil nitrogen, surface residue, fertilizer, irrigation and Manager.
Input datasets. To run the simulation, daily weather, soil and crop management data were used. The weather data were grouped in a metfile, containing daily (i) global solar irradiation (MJ m -2 ), (ii) air temperature (maximum and minimum) and (iv) rainfall (mm). Weather data were collected from Bangladesh Meteorological Department.
Parameterization of the APSIM model
The APSIM platform does not include the mungbean variety BARI Mung-6 (used in the field experiment), hence it was needed to parameterize in the model. Data from March 10 sowing were used for model parameterization/calibration. The required phenological parameters, based on the accumulated degree-day: 'thermal time from emergence to end of juvenile stage' (tt_end_of_juvenile), estimated days from emergence to floral initiation, thermal time from flowering to start grain fill, and 'thermal time requirement from the beginning of grain filling to maturity' (tt_start_grain_fill) were adjusted to match the simulated dates of flowering and maturity with the observed ones. An interactive approach was used to fit selected phenological data. The phenological parameters like days required for flowering and physiological maturity were calibrated first, and then the simulated grain and biomass yields were obtained for comparison with observed values. Calibration was conducted with the trial-and-error method by adjusting the simulated and observed variables [13]. Genetic coefficient was determined after obtaining a close match between observed and simulated values for total biomass, grain yield, time to reach 50% flowering, and physiological maturity. The parameterizations process was considered complete when the difference of the observed and simulated variables was minimum (RMSEn is � 10 and � 20%). These coefficients were used in the subsequent model validation.
Model validation
For the validation, separate APSIM simulations were run for each of the sowing dates and management conditions using the calibrated model. Observed values on grain and biomass yields from our field experiment and similar data from secondary sources [14][15][16][17] were utilized for comparison with model simulated values. The performance of the model was assessed with root mean square error (RMSE), and normalized root mean square error (RMSEn). Simulation output is considered excellent if RMSEn < 10%, good when RMSEn is � 10 and � 20%, fair when RMSEn is � 20 and � 30% and poor if RMSEn is � 30% [18].
RMSE ¼
ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi P n i¼1 ðPi À OiÞ Where n: number of observations, Pi: predicted value for the ith measurement and Oi: observed value for the ith measurement.
Sensitivity analysis
To represent climate change conditions, arbitrary changes were made by adding 0-, 1-, 2-and 3˚C to the historical daily maximum and minimum temperatures for the period of 1981-2021.
To determine the sensitivity of grain yield, the crop model was first control-run with no change in temperature followed by running the model with elevated temperatures [19]. Then the results for the elevated temperatures were compared with control run.
Model application
The calibrated APSIM-Mungbean model was used to assess the long-term response of BARI Mung-6 at different sowing dates. This was done to predict the effect of different sowing dates
Climate change scenarios
Climate change scenarios was developed for three elevated (1-, 2-and 3˚C) temperatures based on RCP2.6, RCP4.5, and RCP8.5, respectively [20]. Under the 'Climate Control' Toolbox of APSIM, the above said temperatures were added with daily maximum and minimum temperatures for the period from 1981 to 2021 of Gazipur location. Then the model was run with four sowing dates (March 10, March 20, March 30 and April 10) to find out the effect of elevated temperature on phenology, grain and biomass yields of mungbean. Other weather parameters were remained unchanged in the study.
Soils physicochemical properties in the study sites
Soils of the experimental field belong to Grey Terrace Soil (Aeric Heplaquepts). Chemical properties of the soil is shown in Table 1.
Rainfall and temperature in model application sites
The mean monthly total rainfall, temperature and solar radiation in the model application sites across the 41-year period are presented in Table 2. Mean monthly maximum temperatures ranged from 24.94˚C (January) to 33.68˚C (April), while mean monthly minimum temperatures ranged from 12.20˚C (January) to 26.21˚C (August). The mean monthly highest total rainfall (370.47 mm) was recorded in July, while the lowest (6.48 mm) in January. Mean Table 3 shows the estimated cultivar coefficients for BARI Mung-6. Some parameters like thermal time required from emergence to end of juvenile phase, estimated days from emergence to floral initiation, estimated days from initiation to flowering, from flowering to start grain fill and estimated days from emergence to floral initiation were calibrated, while other parameters were used as default values of Berken variety. There was good agreement between the observed/estimated and simulated values for tested phenological parameters along with grain and biomass yields ( Table 4). The statistical values for the simulated and measured values varied by 1 to 6 days for RMSE with RMSEn of < 10% for all phenological parameters indicating excellent calibration of the model. Similarly, RMSEn was �10% and � 20% for grain and biomass yield respectively, which indicate good calibration of the model.
Analysis of model validation
The model validation with independent data sets for BARI Mung-6 showed good agreement between simulated and observed values for grain and biomass yields (Fig 1A & 1B). The model was able to explain grain yield variability by 94% (R 2 = 0.9415) and biomass yield by about 91% (R 2 = 0.9097). In the present investigation, the model slightly over or under estimated grain and biomass yields compared to observed data. The variations were 2 to 8% for grain yield and 2 to 5% for biomass yield. These under and over estimations of yields by the model are mostly likely depended on accuracy of calibration of the tested model [21].
Mungbean yield in different sowing dates
Box plots are showing long-term simulation (41-year period) of grain yields of BARI Mung-6 by APSIM model for eight sowing dates (Fig 2). Considering median values, the grain yields reached its peak at March 20 sowing and then declined. The second highest median yield was observed in March 15 sowing. Median yields obtained from March 10 and March 25 sowings were almost similar. Grain yield ranged from 1111 to 1920 kg ha -1 when sown on March 15 1099 to 2011 kg ha -1 for March 20; 1109 to 1934 kg ha -1 for March 25; 1088 to 1833 kg ha -1 for March 30 and 1029 to 1844 kg ha -1 for April 10 sowings. The chance of getting lower grain yield from early sown crop was observed, while the probability of obtaining better grain yields from March 15 to March 25 seeding were observed with less variability over the years. Although we have not seen grain quality, sowing time variations influences both grin yield and grin quality. Study in tropical Australia showed that in 70% of the growing seasons, quality seeds obtained when the crop was matured after March 20, but grain yield was optimized in early January sowing dates [21]. Higher grain yield was obtained with ambient temperature than elevated temperature regimes. Such variations in seed quality and grain yields were related with weather conditions, especially rainfall and temperature variations in a particular crop growing region [22].
Probability of exceedance
The probability of exceedance was used to further assess the best sowing window based on the attainable grain yield threshold for each sowing date simulated (Fig 3). The probability of exceeding the attainable grain yield threshold of about 1,250 kg ha −1 would be expected to occur in >75% of the years when sowing on March 25 followed by March 20, March 30 and March 15. We have found probability of occurrence of higher grain yields in 70% of the growing seasons depending on sowing times of mungbean. Such variations were related with prevailing temperature and soil moisture. Generally, early sown crops are exposed to low temperature, while the late sown crops encountered high temperatures and occasional heavy rainfall and thus crop suffers from biotic stresses [21].
Although APSIM model does not consider biotic factors, generally grain yields are influenced by both biotic and abiotic factors. Depending on crop growth stages, biotic stress influences grain yields. Existing literatures support that lower grain yields are mostly because of prevailing elevated temperature at vegetative, flowering and pod filling stages for both normal and late sowing conditions [22,23]. Although average grain yield of mungbean in Bangladesh is about 800 kg ha -1 , the present investigation showed that the probability of exceeding grain yield of about 1450 kg ha −1 would be possible in 50% of the years when sowing on
Impact of elevated temperature on mungbean phenology
Mungbean phenology was greatly influenced by sowing dates and elevated temperatures ( Table 5). Delayed sowing and increased temperature prolonged vegetative phase, which extended the periods of floral initiation, flowering, grain filling and maturity. Optimum temperature for vegetative phase of mungbean range from 30 to 43˚C [24]. So, 3˚C increase in temperature extended vegetative phase as it was within the optimum temperature range for growth of mungbean (Table 2). Besides, flowering of mungbean is delayed with longer photoperiods [25]. Delay sown crop received plenty of monsoon rainfall compared to early sown one (Table 2) along with increased day length. Under long crop growth duration, the flowering in mungbean is less synchronous which can arise not only because of photo-thermal sensitivity in dry matter partitioning [26], but also from soil moisture conditions [27]. High soil moisture levels encourage greater vegetative growth in mungbean [28].
In simulated condition, maturity duration was increased by 14 days because of 3˚C augmented temperature in March 10 and March 20 sowings compare to 0˚C; but it was 12 and 13 days, respectively for March 30 and April 10 sowings. For reproductive phase, optimal growth takes place at 25-30˚C [24]. In the present investigation, mean maximum temperature in March was 32.05˚C and in April it was 33.68˚C ( Table 2). Because of 3˚C increases in temperature, reproductive phase of mungbean would be more affected in April sowing than that of March. Under late-sown conditions, reproductive phase usually exposed to above-optimal temperature and consequently grain yield reduces due to flowers drop, less pod filling and reduced grain size [29].
Impact of elevated temperature on mungbean grain yield
With an objective of assessing the impact of climate change on mungbean production, four sowing dates, viz, March 10, March 20, March 30 and April 10 have been considered under 41 years' simulation (1981 to 2021) and presented in Fig 4. At Mach 10 sowing without temperature rise, grain yield ranged from 1030 kg ha -1 to 1846 kg ha -1 with a median yield of 1408 kg ha -1 . With 1˚C rise in temperature, simulated grain yields ranged from 1065 kg ha -1 to 1810 kg ha -1 with a median yield of 1430 kg ha -1 . Considering median values, grain yields also increased at 2˚C and 3˚C rise in temperature indicating positive impact of temperature on mungbean grain yield on March 10 sowing. At March 20 sowing with 1˚C temperature rise, grain yield variability decreased with slight declined in median grain yield; but at 2˚C rise in temperature, median grain yield was at per with no temperature rise with less grain yield variability. At 3˚C rise, slight decreased in median yield was observed with higher variability. At March 30 sowing, a slight increase was observed in median grain yield with 1˚C rise in temperature; but at 2 and 3˚C rise, median as well as average grain yields were reduced. Similar trend was observed in 10 April sowing. Across the sowing dates, 1˚C rise in temperature showed positive impact except March 10 sowing where up to 3˚C rise showed positive impact on grain yield. Greater growth and above ground biomass yield with higher temperature indicating that mungbean is comparatively heat tolerant crop [30]. Generally, mungbean gets benefit in warmer environment of 27-30˚C and they are known for germinating and sprouting at quick rates in these conditions [31]. From the field observed data we have seen that grain size reduced by 3-20% when crop was exposed to higher temperature depending on sowing dates. However, estimation of grain size under elevated temperature was not possible with the APSIM model used (version 7.10). In the present investigation, mean minimum temperature was 12-15˚C in January and February (Table 2) indicating that temperature rise by 3˚C (as we have considered) in these months will not be optimum for growth and development of mungbean. While on the other hand, mean maximum temperature will exceed optimum limit during April and onward. These dilemmas in terms of temperature indicates that sowing in March would be comparatively favorable for mungbean cultivation in Bangladesh in future. Results from the present investigation indicate that early sowing would be one of the adaptation strategies for sustaining mungbean grain yields under climate change situation.
Conclusion
Our study focused on the response of mungbean grain yields to sowing dates and also to optimize sowing window using APSIM Mungbean Model. The simulated grain yield showed that the optimum sowing window for mungbean would be March 15 to March 25 for the Southcentral zone of Bangladesh. However, at elevated temperature conditions, mungbean grain yield is most likely to be more affected under late sowing conditions than in early sowing situations. Our investigation also showed that sowing of mungbean by the first week of March would be one of the options to combat climate change impact on mungbean grain yield in future in Bangladesh.
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Domain: Agricultural and Food Sciences Environmental Science
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Growth and Quality of Leaf and Romaine Lettuce Grown on a Vertical Farm in an Aquaponics System: Results of Farm Research
: The integration of indoor vertical cultivation with a recirculating aquaculture system into an aquaponic system has the potential to become one of the most effective sustainable production systems for fish and leafy vegetables. In this study, lettuce was produced on rafts in a coupled recirculation aquaponic system in the plant factory under controlled environmental conditions. The aims of this study were to evaluate the yield, mineral status, and health-promoting bioactive compounds of leaf and romaine lettuce cultivars grown in a recirculating aquaponic system. The yield and biometric parameters and quality parameters of lettuce leaves (nitrate, mineral, L-ascorbic acid, carotenoid, phenolic compound, and total polyphenolic contents) were examined. Monitoring of the water in the aquaponic system showed a low concentration of nitrates, phosphorus (P), potassium (K), and magnesium (Mg), but the proportion of mineral nutrients as well as pH were stable throughout the lettuce cultivation period. The heads of romaine lettuce ‘Yakina’, ‘Pivotal’, and ‘Waygo’ reached a fresh weight of 86 g, on average, 23% higher than the leaf lettuce ‘Nordice’ over a three-week cultivation period. Despite the low nutrient concentration in the aquaponic solution, the nutrient status of the romaine lettuces ‘Yakina’ and ‘Pivotal’ was within the optimal range. The concentrations of chlorophyll a and carotenoids in ‘Yakina’ and ‘Pivotal’ were higher than those in ‘Nordice’ and ‘Waygo’. The nitrate, phosphorus, and potassium contents in the leaves of ‘Nordice’ and ‘Waygo’ were below the optimal range; however, their polyphenol concentrations were the highest. Our results indicate that the effectiveness of aquaponic cultivation of lettuce in terms of biomass production and the nutritional and health-promoting value of lettuce depends on the plant genotype.
Introduction
Plant factories with artificial lighting were developed over 20 years ago and are an important solution to many environmental problems and food security using a closed environment and its control [1]. This technology, especially vertical farming, is of interest around the world due to its high and stable productivity, high resource use efficiency, and high environmental benefits [2]. Plant factories can be located in cities or suburban areas, which significantly shortens the food supply chain from the producer to the consumer. Soilless hydroponic systems are used in all plant factories to enable constant production of vegetables all year around in a controlled environment. Despite the many advantages of vertical farming, the carbon footprint of this technology is 5.6-16.7 times greater than that of other commonly used methods [3]. Therefore, new technologies enabling a sustainable vertical farming industry should be developed [4]. Monsees et al. [5] showed that the production of lettuce in separate aquaponic systems achieves the same yield and quality as conventional hydroponic systems, but greenhouse gas emissions are drastically reduced due to inorganic fertilizer savings. The decoupled aquaponic technology proposed by Monsees et al. [5] can be optimized by using a coupled system in which environmental conditions for fish, microbes, and plants, such as pH, EC, and water temperature, are optimized. In addition, it would be possible to use organic fertilizers in hydroponics as an alternative to minerals, which is crucial to meeting the challenges of agriculture and climate change around the world.
Aquaponics is a food production system that combines recirculating aquaculture and hydroponics, where nutrient-rich aquaculture water is supplied to hydroponically grown plants [6,7]. This system has gained global attention in recent years because of its high water-and nutrient-use efficiency. In addition, it does not require the discharge of organic effluents as pollutants. Waste material excreted from fish is mineralized via biochemical conversions to release essential nutrients for plants and is used as a liquid fertilizer for the hydroponic production of vegetables. The current state of knowledge highlights the possibility of using aquaculture water to hydroponically produce lettuce in open field and greenhouse conditions [5,8]. Only a few reports concern the use of aquaponics in plant factories, including the use of salt water [9]. The challenge for science and practice remains the development of efficiently functioning aquaponics in plant factories for various species of vegetables based on the rearing of various fish species.
Lettuce (Lactuca sativa L.) is an economically important vegetable and a significant source of essential minerals, as well as vitamins and naturally health-promoting phytochemicals, including flavonoids, carotenoids, and L-ascorbic acid [10,11]. The mineral composition and content of bioactive compounds vary between horticultural types of lettuce [12] and depend on environmental factors and cultivation systems. Among the looseleaf, butterhead, crisphead, and romaine types of lettuce, romaine lettuce is the richest source of β-carotene (4 mg 100 g −1 FW). Loose-leaf lettuce has the highest total phenolic compounds (338 mg 100 g −1 ) and is a moderate source of vitamin C and β-carotene. The accumulation of minerals and bioactive compounds in lettuce strongly depends on environmental factors, such as temperature [13] and the quality, intensity, and duration of light [14][15][16][17]. Previous studies have also indicated that nitrogen deficiency favorably affects the biosynthesis of phenolic acids, flavonols, anthocyanins, and ascorbic acid in lettuce [18,19].
The aim of the current research was to check the possibility of obtaining an adequate yield and good quality of leaf and romaine lettuce grown in a recirculating aquaponic system using only organic fertilizers produced by fish without supplementing with mineral fertilizers in a plant factory and to determine the mineral status and health-promoting bioactive compound content in lettuce leaves. The main goal was to implement our previous research results, conducted on a laboratory scale, in a plant factory operating on a full commercial scale.
Plants and Fish Used in this Study
Four cultivars of lettuce were used in the study: one cultivar of leaf lettuce (Lactuca sativa L.) named 'Nordice', three cultivars of romaine lettuce (Lactuca sativa var.longifolia Lam.), two midi-types ('Pivotal' and 'Yakina'), and one mini-type ('Waygo'). The lettuce seedlings were produced in mineral wool (Grodan) and planted on September 19, 2022. Hybrids of Siberian sturgeon (Acipenser baerii, Brandt) and Russian sturgeon (Acipenser gueldensaedtii, Brandt, and Ratzeburg) were used in aquaculture due to high values of performance, breeding, and rearing, and because this hybrid is more economically efficient than the rearing of purebred species [20].
Aquaculture
The lettuce was grown on a vertical farm in a recirculating aquaculture system (Plantlab, Kaszewy Kościelne, Poland). The system was operated with fish and plants for three months prior to the start of the study to increase nutrient levels and ensure sufficient plant growth. Vertical lettuce cultivation and fish rearing tanks were in separate halls.
Three-week-old seedlings were planted on specially designed floating polystyrene rafts (0.9 m × 0.6 m) with holes (24 pieces on the raft) for rockwool cubes (Grodan) at a planting density of 40 seedlings per square meter. Plants were grown in hydroponic beds (40.0 m × 1.8 m) arranged on eleven levels, and two hydroponic beds were intended for the experimental study (Figure 1). The depth of water in the hydroponic beds was 15 cm. The multi-level construction for plant cultivation was located in a production hall with a fully controlled atmosphere and no access to sunlight. The temperature was maintained at 23 • C, and the humidity was at 75% RH. The source of light for plants was specially designed LED lamps (70:18:12; Red:Green:Blue), based on the results of our previous study of romaine lettuce [21]. PPFD was 200-220 µmol m 2 s −1 , and the photoperiod was 15 h.performance, breeding, and rearing, and because this hybrid is more economically efficient than the rearing of purebred species [20].
Aquaculture
The lettuce was grown on a vertical farm in a recirculating aquaculture system (Plantlab, Kaszewy Kościelne, Poland). The system was operated with fish and plants for three months prior to the start of the study to increase nutrient levels and ensure sufficient plant growth. Vertical lettuce cultivation and fish rearing tanks were in separate halls.
Three-week-old seedlings were planted on specially designed floating polystyrene rafts (0.9 m × 0.6 m) with holes (24 pieces on the raft) for rockwool cubes (Grodan) at a planting density of 40 seedlings per square meter. Plants were grown in hydroponic beds (40.0 m × 1.8 m) arranged on eleven levels, and two hydroponic beds were intended for the experimental study (Figure 1). The depth of water in the hydroponic beds was 15 cm. The multi-level construction for plant cultivation was located in a production hall with a fully controlled atmosphere and no access to sunlight. The temperature was maintained at 23 °C, and the humidity was at 75% RH. The source of light for plants was specially designed LED lamps (70:18:12; Red: Green: Blue), based on the results of our previous study of romaine lettuce [21]. PPFD was 200-220 µmol m 2 s −1 , and the photoperiod was 15 h. The fish were fed in accordance with the recommendations of the Institute of Ichthyobiology and Aquaculture of the Polish Academy of Sciences (Gołysz, Poland). Fish feed contained 7.63% N and other ingredients, such as 7950 mg/kg DW P, 28,600 mg/kg DW K, and 9700 mg/kg DW. Ca, 2820 mg/kg DW Mg, 466 mg/kg DW Fe, 42.2 mg/kg DW Mn, 21 mg/kg DW Cu, 130 mg/kg DW Zn, and 28.2 mg/kg DW B. The chemical composition of the tap water used to fill tanks for fish rearing was as follows: pH 7.2, EC 0.73 mS/cm, hardness 23.8°dH and ingredients such as 332 mg/L HCO3 − , 1.04 mg/L N-NO3 − , <0.05 mg/L N-NH4 + , 0.07 mg/L P-PO4 3-, 2.98 mg/L K + , 132 mg/L Ca 2+ , 22.8 mg/L Mg 2+ , 15.5 mg/L Na + , 44.2 mg/L Cl -, 108 mg/L SO4 2-, 0.01 mg/L Fe, 0.01 mg/L Mn, <0.02 mg/L Cu, 5.13 mg/L Zn, and 0.04 mg/L B. One tank for fish rearing with a capacity of 60 m 3 was connected to two experimental hydroponic beds for lettuce growth. The stocking density of fish was 6.5 kg m −3 . Water from the fish tanks was pumped to a reactor with beneficial microorganisms to oxidize NH4 + and then, after filtering out the solids, to a cultivation hall where lettuce was grown on floating rafts. The fish were fed in accordance with the recommendations of the Institute of Ichthyobiology and Aquaculture of the Polish Academy of Sciences (Gołysz, Poland). Fish feed contained 7.63% N and other ingredients, such as 7950 mg/kg DW P, 28,600 mg/kg DW K, and 9700 mg/kg DW. Ca, 2820 mg/kg DW Mg, 466 mg/kg DW Fe, 42.2 mg/kg DW Mn, 21 mg/kg DW Cu, 130 mg/kg DW Zn, and 28.2 mg/kg DW B. The chemical composition of the tap water used to fill tanks for fish rearing was as follows: pH 7.2, EC 0.73 mS/cm, hardness 23.8 • dH and ingredients such as 332 mg/L HCO 3 − , 1.04 mg/L N-NO 3 − , <0.05 mg/L N-NH 4 + , 0.07 mg/L P-PO 4 3− , 2.98 mg/L K + , 132 mg/L Ca 2+ , 22.8 mg/L Mg 2+ , 15.5 mg/L Na + , 44.2 mg/L Cl − , 108 mg/L SO 4 2− , 0.01 mg/L Fe, 0.01 mg/L Mn, <0.02 mg/L Cu, 5.13 mg/L Zn, and 0.04 mg/L B. One tank for fish rearing with a capacity of 60 m 3 was connected to two experimental hydroponic beds for lettuce growth. The stocking density of fish was 6.5 kg m −3 . Water from the fish tanks was pumped to a reactor with beneficial microorganisms to oxidize NH 4 + and then, after filtering out the solids, to a cultivation hall where lettuce was grown on floating rafts.
Mineral Composition of Water in an Aquaponic System
Water for analysis was taken from the hydroponic beds four times at weekly intervals. The electrical conductivity (EC), pH, and mineral nutrient content of the water were determined. The pH and N-NO 3 contents were analyzed by the potentiometric method using the Thermo Scientific apparatus model Orion Versastar (Beverly, MA, USA), and the EC by the conductivity method. The concentrations of P, K, Ca, Mg, and SO 4 were determined following the spectrophotometric method using an inductively coupled plasma sequential emission spectrometer (ICP Perkin-Elmer model Optima 2000 DV, Boston, MA, USA).
Yield and Biometric Parameters
Lettuce was harvested when it reached commercial maturity, i.e., 21 days after transplant, after which the fresh and dry weight of leaves, number of leaves, head circumference (for romaine lettuces forming heads), plant height and diameter, fresh weight, and root length were measured. A visual quality score on a scale of 1 to 5, where 1 means the worst and 5 means the best plant, was also assessed. Measurements of biometric parameters were performed on 18 randomly selected plants collected from different places in hydroponic beds.
Chlorophyll, Flavonol, and Nitrogen Balance Indices
The chlorophyll (Cl), nitrogen (nitrogen balance index), and flavonol (FLAV) indices were measured using the Dualex Scientific+ (Force A, Orsay, France) lefe-clip device. Measurements were made on 36 fully expanded leaves from each cultivar.
Macro-and Micronutrients in Plants
Nitrates in fresh plant material were extracted with water at a ratio of 1:10 and determined by the potentiometric method using the Thermo Scientific apparatus model Orion Versastar (Beverly, MA, USA). The content of the other components was determined by the dried plant material. The contents of P, K, Ca, Mg, Fe, Mn, Cu, Zn, and B were determined in three replications using an ICP spectrometer. The N content was analyzed using the Kjeldahl method (Vapodest Kjeldahl apparatus, Gerhardt GmbH & Co., KG, Königswinter, Bonn, Germany) [22]. Selected elements were determined at their characteristic wavelengths [23]. All nutrients were determined in three replications.
Phytochemical Content 2.7.1. Chlorophyll and Carotenoids
The contents of carotenoid and chlorophyll were measured using a spectrophotometric method, as maintained by Lichtenthaler and Wellburn [24]. The lettuce samples, after disintegration, were homogenized with a cold solution of 80% acetone. The extracts were centrifuged at 4 • C for 15 min at 10 000 rpm. Then, 0.5 mL of supernatant was added to 4.5 mL of acetone solution (80%). The carotenoid and chlorophyll contents were determined using a UV-VIS spectrophotometer (Cary 300 Bio), based on extract absorbance at three wavelengths: 470 nm-carotenoids; 645 nm-chlorophyll a; and 663 nm-chlorophyll b. Total chlorophyll was calculated as the sum of chlorophyll a and chlorophyll b. The results were expressed in mg 100 g −1 of fresh sample weight (FW).
L-Ascorbic, Citric, and Malic Acid
The content of L-ascorbic acid was determined following the HPLC method (high performance liquid chromatography) using an Agilent Technologies HPLC system (1200 series) equipped with a diode array detector (DAD). The separation was applied using a Supelcosil LC-18 column (250 mm × 4.6 mm; 5 µm) with a pre-column and a solution of phosphatebuffered (1% KH 2 PO 4 ; 2.5 pH) as the mobile phase. The column was maintained at a temperature of 30 • C, and the mobile phase flow rate was 0.8 mL/min. The detection of ascorbic acid was performed by 244 nm absorbance. Samples before HPLC injection were dissolved in 6% HPO 3 . The results were expressed as mg 100 g −1 FW.
Flavonoids
The content of the flavonoids in lettuce was measured using a spectrophotometric method [25,26]. The lettuce leaves were homogenized with a cold solution of acetone (80%) and filtered using reduced pressure. Then, acetone was removed from the supernatant by evaporating at 45 • C. The aqueous solution was subjected to centrifugation at 8000 rpm for 10 min. Then, 0.25 mL of the extract was mixed with 0.075 mL of NaNO 2 solution (5%) and 1.25 mL of distilled water and kept for 6 min. Subsequently, 10% AlCl 3 solution was added (0.15 mL) and kept for 5 min. Next, 0.5 mL of a solution of 1 M NaOH was added. The total mixture was mixed thoroughly. Samples were made up of distilled water in a 2.5 mL volume, and the measurement was applied by absorbance at 510 nm on a spectrophotometer (UviLine 9400) against a blank. The flavonoid content was expressed in mg 100 g −1 FW.
Total Polyphenolic Content (TPC)
The total polyphenol content (TPC) was measured using a modified spectrophotometric method [27]. The plant sample was homogenized with 70% ethanol. The homogenate was centrifuged for 10 min at 20,000× g, following the mixture of 0.4 mL supernatant with 1.6 mL sodium carbonate solution (7.5%). Then, 2 mL of Folin-Ciocalteu phenol reagent was added, and the mixture was shaken. After incubation for 30 min at ambient temperature in the dark, the absorbance was read against the prepared blank at 765 nm. The polyphenol content was expressed as mg of gallic acid equivalents in mg 100 g −1 FW.
Statistical Analysis
A one-way analysis of variance (ANOVA) was used to test statistical differences between the means using SAS software version 9.1 (StatSoft Inc., Tulsa, OK, USA). Tukey's HSD test was applied at p ≤ 0.05 for the mean comparison of the tested cultivars.
Mineral Composition of Water in an Aquaponic System
Monitoring of water in an aquaponic system showed a good balance of mineral nutrients, as the N-NO 3 − , N-NH 4 + , P, K, Ca, and Mg contents remained at the same level throughout the lettuce cultivation period (Table 1). No excessive depletion or accumulation of macronutrients was demonstrated. The average contents of macronutrients are: 46 mg/L N-NO 3 − , 3 mg/L N-NH 4 + , 3 mg/L P, 19 mg/L K, 141 mg/L Ca, and 27 mg/L Mg. Similarly, the pH (7.3) and EC (0.89 mS/cm) of the water remained at similar levels.
Yield and Biometric Parameters
The examined morphological characteristics of the lettuce (Figure 1) showed that the yield of leaf lettuce 'Nordice' was significantly lower than the yield of the romaine lettuce cultivars after three weeks of growth.'Nordice' reached a fresh weight of 70 g and formed 17 leaves. These plants were the shortest (the height was 13 cm) but had the largest diameter, although they were not significantly taller than 'Pivotal' plants.'Nordice' produced the lowest fresh root weight, but the roots were the longest. The heads of the romaine lettuce reached a fresh weight of 86 g (average for three cultivars), 23% more than the leaf lettuce 'Nordice'. Although the romaine lettuce cultivars reached the same fresh weight, they differed significantly in terms of morphological traits. The 'Waygo' cultivar was the most compact among the evaluated romaine lettuce cultivars. These plants were the shortest and had the lowest diameter; however, they had the highest head circumference and produced the most leaves. The dry matter of lettuce for all tested cultivars under aquaponic conditions was 3.9%. Overall, all lettuce cultivars grown under an aquaponic system received a high visual quality rating, although the score for 'Waygo' was slightly lower due to the occurrence of tip burn symptoms.
Chlorophyll, Flavonol, and Nitrogen Balance Indices
The leaf chlorophyll index (CI) and nitrogen balance index (NBI) for all tested lettuce cultivars were closely related (Figure 2).'Pivotal' and 'Waygo' had the highest CI and NBI, and 'Nordice' had the lowest values for these indices. Both CI and NBI for 'Pivotal' and 'Waygo' were as much as five times higher than those for 'Nordice'. The flavonol index for the tested cultivars did not differ much; however, this index for 'Waygo' was significantly higher than that for 'Yakina'.
Macro-and Micronutrients in Plants
Plant nutrient accumulation differed significantly among the cultivars (Tables 2 and 3). The loose-leaf cultivar 'Nordice' had the lowest nitrate and total N, P, K, and Mg contents, as well as low concentrations of Fe, Mn, Cu, and Zn; however, it had the highest Ca content. No significant difference was found between the romaine lettuce cultivars in terms of nitrate (1962 mg kg −1 f.w.), total N (3.24%),Mg (1962 mg kg −1 d.w.), and Fe (93.91 mg kg −1 d.w.) contents (average values). The 'Pivotal' and 'Yakina' cultivars were charac-
Macro-and Micronutrients in Plants
Plant nutrient accumulation differed significantly among the cultivars (Tables 2 and 3). The loose-leaf cultivar 'Nordice' had the lowest nitrate and total N, P, K, and Mg contents, as well as low concentrations of Fe, Mn, Cu, and Zn; however, it had the highest Ca content. No significant difference was found between the romaine lettuce cultivars in terms of nitrate (1962 mg kg −1 f.w.), total N (3.24%),Mg (1962 mg kg −1 d.w.), and Fe (93.91 mg kg −1 d.w.) contents (average values). The 'Pivotal' and 'Yakina' cultivars were characterized by very similar P (5325 mg kg −1 d.w.), K (73,733 mg kg −1 d.w.), and Ca (19,500 mg kg −1 d.w.) contents, and these values were significantly higher than those determined for the 'Waygo' cultivar.
Mineral Composition of Water in an Aquaponic System
The low nutrient content and high pH of the circulation water are two major issues that must be overcome to successfully combine aquaculture and hydroponics into a sustainable leafy vegetable production system [28]. Such challenges were also faced in our study of a plant factory with a recirculating aquaponic system. A pH range of 5.5 to 6.0 for hydroponically grown lettuce is preferred, which allows for maximum nutrient availability to the plant roots, and a slight increase in pH to 7.0 can significantly reduce fresh and dry weights [29]. However, the optimal pH for sturgeon aquaculture ranges between 6.5 and 8.5 [30], and nitrifying bacteria require a pH of around 7.5 for the optimal conversion of ammonia to nitrates [31]. In our study, the water in the aquaponic system contained low amounts of nitrogen, phosphorus, and potassium and sufficient levels of Ca and Mg, which came from tap water used to fill fish tanks. Graber and Junge [32] determined that an aquaponic solution contained three times less nitrogen, 10 times less phosphorus, and 45 times less potassium than a hydroponic solution. Nevertheless, they obtained a good yield, although their quality was poorer due to a lack of potassium.
Yield and Biometric Parameters
The results of our research indicate that aquaponic system production can be a sustainable alternative to the hydroponics used in plant factories, considering the yield and commercial quality of lettuce (Figures 1 and 2). In this study, we obtained a satisfactory yield of romaine lettuce of 86 g in just 21 days, which corresponds to 3.4 kg m −2 at a density of 40 plants m −2 . This may have been due to the presence of organic compounds in fish water, which can stimulate plant growth [33], the early harvest of lettuce, and consequently, the low nutritional requirements of plants in the first three weeks of growth, and a well-developed root system. The root-to-shoot fresh weight ratio for romaine-type lettuce cultivars ranged from 0.31 to 0.42, with the highest value for 'Yakina'. A similar lettuce yield was reported by Moon et al. [34] in a plant factory. They showed that the vertical farming system using hydroponics produced 37 kg m −2 of lettuce annually, with 14.6 growth cycles a year, and was harvested at a relatively low fresh weight of 110 g. Our previous study reported that a daily light integral equal to 17.3 mol m −2 per day for romaine lettuce 'Casual' and 11.5-17.3mol m −2 per day for 'Elizium' allowed to obtain a high fresh weight of a head lettuce (350 and 240 g, respectively) within 30 days of cultivation in an indoor plant production facility using hydroponics with mineral fertilizers [35]. However, this rapid growth of lettuce intensified the symptoms of a physiological disorder known as "tip burn" [35,36]. Studies comparing the yield of lettuce in aquaponic systems with hydroponics are inconsistent. Some researchers have reported similar or even better yields in aquaponics than in hydroponics, despite lower concentrations of mineral nutrients [37,38]. In contrast, the growth and yield of lettuce grown in aquaponics were lower than those grown in hydroponics, and the lettuce developed leaf yellowing [39]. Among the various factors affecting the yield of aquaponic lettuce, such as the EC level, pH, nutrient profile of fish water, water quality, water temperature [40], and nutrient composition of fish feed [37,40], the type of cultivar can considered an important factor. Our research has shown that, in terms of yield, romaine-type lettuce cultivars adapt better than leaf-type lettuce to an aquaponic environment without additional mineral nutrients in fish water.
Chlorophyll, Flavonol, and Nitrogen Balance Indices
Non-destructive techniques for assessing the nutritional status of lettuce crops provide fast and reliable results and can provide an affordable alternative to standard laboratory methods, especially in plant factories. The lowest NBI and CI indices, as well as the lowest biomass production, were recorded for the leaf-type lettuce cultivar 'Nordice', which suggests that the nitrogen content in the fish water was a factor limiting growth and development. In contrast, romaine lettuce cultivars showed higher nitrogen use efficiency, which may have been due to differing expression of nitrogen transportation and assimilation genes [41]. Becker et al. [42] showed that nitrogen treatments have a clear effect on growth characteristics, phenolic and photosynthetic compounds, nitrogen, nitrate, and carbon concentrations in leaf lettuce. The concentrations of all major flavonoid glycosides increased with decreasing nitrogen concentrations, while the concentrations of chlorophyll and β-carotene decreased. Flavonoids, as nitrogen-free secondary metabolites, are considered indicators of nitrogen availability in plants [43]. The flavonol index for all tested lettuce cultivars grown in fish water without mineral supplementation exceeded the value of 0.52 (Figure 3), while under hydroponic conditions with sufficient minerals, it did not exceed 0.23 [21].
iculture 2023, 13, x FOR PEER REVIEW 10 o lower than those grown in hydroponics, and the lettuce developed leaf yellowing [3 Among the various factors affecting the yield of aquaponic lettuce, such as the EC lev pH, nutrient profile of fish water, water quality, water temperature [40], and nutrient co position of fish feed [37,40], the type of cultivar can be considered an important fact Our research has shown that, in terms of yield, romaine-type lettuce cultivars adapt bett than leaf-type lettuce to an aquaponic environment without additional mineral nutrie in fish water.
Chlorophyll, Flavonol, and Nitrogen Balance Indices
Non-destructive techniques for assessing the nutritional status of lettuce crops p vide fast and reliable results and can provide an affordable alternative to standard lab atory methods, especially in plant factories. The lowest NBI and CI indices, as well as lowest biomass production, were recorded for the leaf-type lettuce cultivar 'Nordi which suggests that the nitrogen content in the fish water was a factor limiting grow and development. In contrast, romaine lettuce cultivars showed higher nitrogen use e ciency, which may have been due to differing expression of nitrogen transportation a assimilation genes [41]. Becker et al. [42] showed that nitrogen treatments have a cl effect on growth characteristics, phenolic and photosynthetic compounds, nitrogen, trate, and carbon concentrations in leaf lettuce. The concentrations of all major flavon glycosides increased with decreasing nitrogen concentrations, while the concentrations chlorophyll and β-carotene decreased. Flavonoids, as nitrogen-free secondary meta lites, are considered indicators of nitrogen availability in plants [43]. The flavonol ind for all tested lettuce cultivars grown in fish water without mineral supplementation ceeded the value of 0.52 (Figure 3), while under hydroponic conditions with suffici minerals, it did not exceed 0.23 [21].
Macro-and Micronutrients in Plants
Leafy vegetables, such as lettuce, contain a significant amount of natural nitra which can pose a risk to human health [44]. The European Union has set the maxim limits for nitrates in lettuce grown under cover, and these values are 5000 mg kg −1 in w
Macro-and Micronutrients in Plants
Leafy vegetables, such as lettuce, contain a significant amount of natural nitrates, which can pose a risk to human health [44]. The European Union has set the maximum limits for nitrates in lettuce grown under cover, and these values are 5000 mg kg −1 in winter-grown plants and 4000 mg kg −1 in other seasons [45]. The concentration of nitrates in lettuce leaves grown in the aquaponic system was low (885-2221 mg kg −1 f.w.) and did not exceed the permissible limit imposed by the European Union, although nitrate accumulation was genotype dependent.
According to Knott's Handbook for Vegetable Growers [46], sufficient ranges of mineral nutrients for greenhouse-grown lettuce are 2.1-5.6%N, 0.5-0.9%P, 4.0-8.0%K, 0.9-2.0%Ca, 0.4-0.8%Mg, 50-200% Fe, 25-200% Mn, 5-18% Cu, 30-200% Zn, and 25-65% B. Therefore, for the romaine lettuce cultivars 'Pivotal' and 'Yakina', the concentrations of macro-and microelements in lettuce leaves were within the optimal range for macroand microelements, despite low amounts of nitrogen, phosphorus, and potassium in the aquaponic solution. Since chemical analysis of nutrient solutions can only detect nutrients that are available in ionic form, suspended organic solids may have promoted lettuce growth. However, deficiencies of P, K, Mn, and Cu occurred in the leaves of the leaf lettuce cultivar 'Nordice' and the mini-type romaine cultivar 'Waygo', which suggests that the accumulation of some minerals depends on the genotype, growth rate, and morphological features [12]. Leaf lettuce 'Nordice' had the lowest weight, produced the fewest leaves, contained the least nitrates, and had the lowest leaf chlorophyll index (CI) and nitrogen balance index (NBI), indicating that the nutrient concentration in the aquaponic solution was a limiting factor for this type of lettuce. The solution could be supplementing aquaponic fish water with minerals, mainly phosphorus and potassium [47], or using a mineralization unit to concentrate the nutrients of aquaculture water in decoupled systems [48,49]. The lowest Ca concentration in leaves was found for the cultivar 'Waygo', which represents mini-types of romaine lettuce with closed heads. Low calcium content in young romaine lettuce leaves was probably the cause of the physiological disturbance that causes tip burn, and this phenomenon is common in romaine lettuce grown in indoor plant production systems [35].
Both our own research and the data available in the literature show a considerable variation in the chemical composition of lettuce depending on its type, variety, and method of cultivation. According to Llorach et al. [50], romaine lettuce is moderately rich in bioactive compounds, whereas iceberg lettuce is poorer, and red varieties may contain several times more phenolic compounds and vitamin C. Even a significant variation in the composition of bioactive compounds can be seen among varieties belonging to the same type of lettuce [51].
Phytochemical Content
In the current study, the chlorophyll a and chlorophyll b contents for 'Yakina' were at a similar level as those reported by Zhan et al. [52] for romaine lettuce (18 mg 100 g −1 and 5.8 mg 100 g −1 , respectively). The other varieties of romaine lettuce in our study, 'Pivotal' and 'Waygo', showed higher values of chlorophyll a and b than reported by Lopez et al. [51] and Zhan et al. [52] for the 7 tested varieties of romaine lettuce grown in greenhouse conditions (chlorophyll a 60-115 µg/g, which corresponds to 6.0-11.5 mg 100 g −1 ; chlorophyll b 20-40 µg g −1 , which corresponds to 2.0-4.0 mg 100 g −1 ) [49].
β-carotene is the dominant carotenoid in romaine lettuce [51,53]. The average carotenoid content for 7 varieties grown in greenhouse conditions was 5.8 mg100 g −1 , which is in the range of carotenoids in lettuces grown in the aquaponics system (4.8-6.9 mg 100 g −1 ).
Lettuce is a vegetable that is rather poor in vitamin C compared to other vegetables. Lettuce grown in vertical farms, with the exception of the 'Yakina' cultivar, contained more than 5 mg 100 g −1 of this vitamin, which is a higher value than that reported by Llorach et al. [50] (2.8 mg 100 g −1 ) and slightly less than the value reported by Zhan et al. [52] (about 7 mg 100 g −1 ). The analysis of organic acids confirmed that one of the dominant acids in romaine lettuce is malic acid [51].
The content of total phenolic compounds in leaf lettuce (L.sativa) cultivated in a different agronomic and fertilization system is between 1-2 mg/g FW (corresponding to 100-200 mg 100 g −1 ) [54,55], which is 2-4 times higher than that found for 'Nordice' leaf lettuce in our study (50 mg 100 mg −1 ). However, some varieties, such as Lactuca sativa L. cv.'Baronet', contain significantly less phenolic compounds (10 mg 100 g −1 ), and when subjected to high light stress, they increase the phenolic compound content up to three times [56].
Current studies on the composition of bioactive compounds have shown that romaine lettuces grown on a vertical farm in an aquaponics system achieve very good nutritional value, and the composition of phenolic compounds overlaps with that of lettuce grown traditionally in a greenhouse.
Conclusions
For the first time, it has been shown that a recirculating aquaponic system with sturgeon rearing can be used to efficiently produce lettuce in a commercial-scale plant factory. Ensuring optimal climatic conditions in the plant factory, including light and temperature, allowed for satisfactory yield and quality of midi-type romaine lettuce in just 21 days of cultivation. Despite the low mineral content in the aquaponic solution, the mineral content in midi-type romaine lettuce leaves was within the optimal range, and the nutritional value was similar to lettuce grown traditionally in a greenhouse. The biomass production of leaf lettuce and mini-type romaine lettuce was lower than that of midi-type romaine lettuce, and the nitrate, phosphorus, and potassium contents in the leaves were below the optimal range. Our results indicate that the effectiveness of aquaponics without additional minerals depends on the plant genotype.
Figure 1 .
Figure 1. Experimental lettuce cultivation facility on a vertical farm, (a) lettuce grown in hydroponic beds, (b) raft with visible root system of romaine lettuce.
Figure 1 .
Figure 1. Experimental lettuce cultivation facility on a vertical farm, (a) lettuce grown in hydroponic beds, (b) raft with visible root system of romaine lettuce.
Figure 2 .
Figure 2. Fresh (A) and dry weight of leaves (B), number of leaves per plant (C), head circumference (D), plant height (E), plant diameter (F), fresh root weight (G), root length (H), and visual quality scores (I) of three romaine lettuce cultivars ('Pivotal', 'Yakina', and 'Waygo') and one leaf lettuce cultivar ('Nordice') grown on a vertical farm in an aquaponic system. Vertical bars represent the standard errors of the means. Different letters indicate statistically significant differences between cultivars at the p < 0.05 level according to Tukey's HSD test.
Figure 2 .
Figure 2. Fresh (A) and dry weight of leaves (B), number of leaves per plant (C), head circumference (D), plant height (E), plant diameter (F), fresh root weight (G), root length (H), and visual quality scores (I) of three romaine lettuce cultivars ('Pivotal', 'Yakina', and 'Waygo') and one leaf lettuce cultivar ('Nordice') grown on a vertical farm in an aquaponic system. Vertical bars represent the standard errors of the means. Different letters indicate statistically significant differences between cultivars at the p < 0.05 level according to Tukey's HSD test.
Figure 3 .
Figure 3. Chlorophyll index (CI), flavonol index, and nitrogen balance index (NBI) of three roma lettuce cultivars ('Pivotal', 'Yakina', and 'Waygo') and one leaf lettuce cultivar ('Nordice') grown a vertical farm in an aquaponic system. Vertical bars represent the standard errors of the mea Different letters indicate statistically significant differences between cultivars at the p < 0.05 le according to Tukey's HSD test.
Figure 3 .
Figure 3. Chlorophyll index (CI), flavonol index, and nitrogen balance index (NBI) of three romaine lettuce cultivars ('Pivotal', 'Yakina', and 'Waygo') and one leaf lettuce cultivar ('Nordice') grown on a vertical farm in an aquaponic system. Vertical bars represent the standard errors of the means. Different letters indicate statistically significant differences between cultivars at the p < 0.05 level according to Tukey's HSD test.
Assessment Date EC (mS/cm) pH N-NO 3 − mg/L N-NH 4 + (mg/L) P (mg/L) K (mg/L) Ca (mg/L) Mg (mg/L)
Means followed by the same letter are not significantly different (p < 0.05) using Tukey's HSD test.
Table 3 .
Concentrations of microelements (Fe, Mn, Cu, Zn, and B, in mg kg −1 DW) in the leaves of leaf lettuce 'Nordice' and romaine lettuce 'Pivotal', 'Yakina', and 'Waygo' grown on a vertical farm in an aquaponic system. Different letters indicate statistically significant differences between cultivars at the p < 0.05 level according to Tukey's HSD test.
Table 4 .
The content of chlorophylls a and b, carotenoids, flavonoids, and total polyphenols (TPC) in leaf lettuce 'Nordice' and romaine lettuce 'Pivotal', 'Yakina', and 'Waygo' grown on a vertical farm in an aquaponic system.
Different letters indicate statistically significant differences between cultivars at the p < 0.05 level according to Tukey's HSD test.
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Domain: Agricultural and Food Sciences Environmental Science
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Maximizing irrigation water use and crop productivity under mulching with geotextile for lettuce plants ( Lactuca sativa L. var. capitata )
. One of the fields that will be negatively impacted by climate change is agriculture, particularly in developing countries. Most crops are affected when grown under limited water supplies as it produces low productivity, especially during the late growing stage. For this reason, it is important to improve irrigation efficiency and crop yield. Two successive seasons were conducted during 2021 and 2022 to test the action of mulching types on iceberg lettuce plants ( Lactuca sativa L. var. capitata ) with irrigation stress. In the sandy loam soil conditions of the El Sharkia Governorate in Belbeis, Egypt, iceberg lettuce plants were grown with different types of mulching (no mulching, white geotextile sheet, and black plastic sheet) under varying levels of water (100, 80, and 60% of ETc, or evapotranspiration). Results showed that mulching the soil surface with plastic and geotextile produced the highest data of soil moisture content inside the root zoon. In conclusion, compared to the control (no mulching), all mulching types treatments result in a significant increase in yield parameters. In this study, however, mulching with white geotextile sheets and requiring 100% ETc irrigation proved to be the statistically most effective treatment, while 80% ETc combined with white geotextile sheet get values were statistically equal to the results with the control (100% ETc without mulching). It is possible to achieve results similar yield to the control or better, while saving an amount of irrigation water of up to 20% by using ETo 80 % combined with mulching with white geotextile sheet without any negative effect on the plant. However, it can be recommended to use geotextile compared to black plastic, as plastic requires more time to degrade, which will be harmful to the environment.
Introduction
Capoutshi or iceberg lettuce (Lactuca sativa L. var.capitata) (Limor) is an important vegetable crop worldwide. It has been increased in recent years, especially in the Mediterranean [1]. It has a significant effect on the human diet, with medicinal and functional properties [2]. 3196 hectares of land were planted to produce 70839 tonnes of lettuce, with an average yield of 22.16 tons per hectare. Meanwhile, 385 hectares were planted to produce 7443 tonnes of lettuce, with an average yield of 19.33 tonnes per hectare, according to [3]. In a semi-arid ecosystem, the most important factor limiting crops production is water stress. This has been observed in studies conducted by [4,5]. Therefore, mulching can be an effective technique to reduce soil evaporation, but its efficiency depends on meteorological conditions and the characteristics of the different mulching materials [6]. In addition to maintaining soil moisture, also, mulches have many other advantageous effects such as limiting excessive temperature variations in the soil, reducing evaporation of water, maintaining soil fertility, promoting growth and production, and increasing the quantity of stored soil moisture [7,8]. In order to improve agricultural crops' water use efficiency, soil evaporation must be reduced. One effective strategy to reduce the amount of water vapour that is exchanged between the soil's surface and the atmosphere is to use mulching materials. Thus, compared to bare soil, less water evaporates from mulched soil, leaving more water available for beneficial crop transpiration [10]. The design of a monolithic alternative cover, also known as a phytocap or evapotranspiration (ET) cover, is typically based on the water balance principle, which states that water can be removed by evapotranspiration during active vegetation growing periods and stored in the cover soil during wet periods to minimize percolation [11]. Thus, the main objective of the current investigation was to improve the growth and yield characteristics of lettuce plants in sandy loam soil. Also reduces evaporation from the soil surface to enhance soil moisture in the root zone. To achieve this goal different mulching types were used (without mulching, white geotextile sheet and black plastic sheet) with different irrigation treatments (100, 80 and 60% of ETc "evapotranspiration").
Materials and Methods
Two successive seasons were conducted in 2021 and 2022 to test the effects of mulching types and irrigation levels on iceberg lettuce (Lactuca sativa L. var.capitata) in sandy loam soil conditions. Thus, the purpose of this investigation was to improve crop characteristics and yield of Iceberg lettuce plants with the application of several mulching techniques (without mulching, white geotextile sheet and black plastic sheet) with various amounts of irrigation (100, 80 and 60% of ETc i.e. evapotranspiration) under drip irrigation system at Belbeis region -El Sharkia Governorate, Egypt.
Calculate water requirements
After transplanting, amounts of irrigation (100, 80 and 60% of ETc) were added. Irrigation scheduling was calculated using the Eq. ( 1): Where: IRg is irrigation requirements, mm day -1 , ETO is reference evapotranspiration, mm day -1 , Kc is crop coefficient [12], Kr is ground cover reduction factor, Ei = is irrigation efficiency, %, R is precipitation, mm (for example rainfall), LR is leaching requirements, mm. The gross amount of irrigation needed each day was calculated from mm/ha/day to m 3 ha -1 day -1 [13].
Trial design
Nine treatments with five replicates were included in the split-plot system complete randomized block design of the experiment. The subplot, the main plot (first factor) consisted of three irrigation levels (100, 80, and 60% of ETc) whereas (second factor) included three various types of mulching (black plastic sheet, white geotextile sheet, and without mulching. This type of geotextile fabrics is characterized by its medium air and water permeability due to pores in its pores. Pore size can be controlled by the areal density measured by Gram per Square Meter of the produced material and also by the material thickness. Additionally, 1260 m 2 made up the experimental unit area. Lettuce (Lactuca sativa L. var.capitata) seedlings that were uniformly sized and in good health were chosen from a commercial nursery and transplanted on September 17 of each year. After that, they were cultivated to each line dripper side, spaced 0.3 m apart. The plants were exposed to three different amounts of water delivery after twenty days of planting: 100%, 80%, and 60% of evapotranspiration (ETc). These treatments represent, in turn, the circumstances attained as extreme water deficiency, moderate water deficiency, and adequate water supply, respectively. The plants in every treatment were irrigated every 3 days. At last, all the lettuce plants of this study received the same horticultural practices except experimental treatments.
Soil moisture content
Before irrigation, soil moisture was monitored, and the field capacity and wilting point were used as assessment lines for the plants' exposure range to water deficiency. Soil depths were used for the measurements.soil moisture was monitored using Profile Probe equipment [15].
Crop growth parameters
When the lettuce achieved horticultural maturity on December 1st, around 75 days after transplanting, the lettuce plants were harvested. Samples were randomly taken in both seasons on December 1 st in order to record the growth parameters and yield. The data recorded were plant height (cm), head diameter (cm), head circumference (cm), head volume (cm 3 ), plant fresh weight (g), head fresh weight (g), root fresh weight (g), number of leaves / plant, leaf fresh weight, and crop yield (ton ha-1 ), Leaf area (cm 2 ): To estimate the leaf area (cm 2 ) leaves were taken from the middle portion of the plant according to [16].
Leaf total chlorophyll: A portable chlorophyll metre (SPAD 502) was used to estimate the total chlorophyll in fresh leaves from each plant according to [18]. Leaf TSS content: A hand refractometer was used to estimate the total soluble solids (TSS %) in fresh leaves of plant.
Leaf cell sap osmotic pressure (atm): According to [19] leaves cell sap concentration and osmotic pressure (atm) were estimated.
Statistical analysis: The trial design was split plot with a complete randomized block design with five replicates. The data recorded were statistically analyzed using the analysis of variance method as reported by [20]. The differences between means were differentiated by using Duncan's range test [21].
Soil moisture content inside root zone of lettuce crop
Figure 1 showed that mulching with plastic and geotextile had a significant impact on the rise in soil moisture content in the root zone (also known as the "SMC"). Applying mulching before irrigation resulted in higher SMC values. The application of plastic and geotextile mulch to the soil surface produced the highest SMC values. Moreover, there is no significant between the results under a white geotextile sheet and a black plastic sheet as mulching for the soil surface. Moreover mulching the soil surface further enhances soil moisture availability, soil organic carbon, reducing evaporation from the soil surface, and soil moisture retention over extended periods [6]. Mulches have numerous positive effects in addition to preserving soil moisture, such as preventing excessive temperature fluctuations, lowering evaporation of water, preserving soil fertility, enhancing growth, and increasing yield-all of which lead to a greater amount of soil moisture being stored [7]. Furthermore, as can be observed in Figure 1, a higher rate of moisture storage inside the root zone under mulching with plastic and geotextile will lead to increased water application efficiency [22,23]. However, it can be recommended to use geotextile compared to black plastic, as plastic requires more time to degrade, which will be harmful to the environment [24].
Crop growth parameters
Table 1 shows the benefits of various mulching methods at varying evapotranspiration rates as well as how they interacted with the plant's height, head diameter, head circumference, and head volume parameters during 2021 and 2022 seasons. Under water stress, the plant reached a maximum significant height of 19.19 cm with 100% ETc, whereas in the first season, the plant reached 15.92 cm with 60% ETc. Mulching types: Compared to the control (no mulching), which recorded 17.21 cm at the first season, mulching with a white geotextile sheet recorded the highest data for a plant height of 18.10 cm. Interaction: Using 100% ETc in conjunction with white geotextile sheet mulching during the first season produced the highest data for plant height, 19.62 cm. Furthermore, in both seasons, the head diameter, head circumference, and head volume all followed the same path towards the plant height.
The results in Table (2) show the effect of different mulching methods at different ETc rates and their interaction on the plant fresh weight, head weight, and roots fresh weight parameters of iceberg lettuce plants in both seasons have a statistically significant effect. For water treatments, 100% ETc obtained optimal data of the plant's fresh weight of 1052.66 g compared to 60% ETc of 521.99 g during the first season. For mulching types, the optimal data for plant fresh weight was obtained under mulching with a white geotextile of 821.84 g compared to the control (no mulching) of 720.86 g for the first season. Interaction: In the first season, the optimal data for plant fresh weight was 1121.49g, reached by mulching with a white geotextile sheet and 100% ETc. Furthermore, the roots' fresh weight and head weight in both seasons corresponded to the plant's fresh weight. ETc = evapotranspiration, WM= Without Mulching, MBPS = mulching with black plastic sheet and MWGS = mulching with white geotextile sheet. At the 0.5% level, the means in each column that are followed by the same letter are not substantially different from one another.
Table (3) demonstrated a statistically significant effect of mulching types under varying water evapotranspiration rates and their interaction on the parameters of leaf area, fresh weight, and number of leaves per plant of iceberg lettuce plants in both seasons. Under water stress, the number of leaves per plant with 100% ETc was 45.37, which was significantly higher than the number of leaves per plant with 60% ETc, which was 30.10 during the first season. When comparing mulching types, the control (without mulching) recorded 36.15 leaves per plant during the first season, while the highest significant value was 38.94 for mulching with white geotextile sheet. The results indicate that in the first season of mulching with white geotextile sheet and 100% ETc, the highest significant value for the number of leaves per plant was 48.06. Furthermore, in both seasons, the parameters of leaf fresh weight and leaf area followed the same pattern as the number of leaves per plant. In general, the crop growth factors improved as the ETo rates raised, This might have resulted from advancements in soil moisture availability, moderate soil surface evaporation, and N, P, and K levels. [25,26,27,28]. The outcomes about water requirements saving aligned with remarks of [29,30,31,32,33,34]. Mulches have numerous positive effects in addition to preserving soil moisture, such as preventing excessive temperature fluctuations, lowering evaporation of water, preserving soil fertility, enhancing growth, and increasing yield, all of which lead to a greater amount of soil moisture being stored [7]. This led to increasing yield and improving water use efficiency. Moreover, white geotextile sheet achieved better results than black plastic sheet as mulching for the soil surface because it allowed better gas exchange. ETc = evapotranspiration, WM= Without Mulching, MBPS = mulching with black plastic sheet and MWGS = mulching with white geotextile sheet. At the 0.5% level, the means in each column that are followed by the same letter are not substantially different from one another.
Table (4) showed that the different mulching methods under different water evapotranspiration rates and their interaction on the yield and water productivity of lettuce plants in 2021 and 2022 seasons. Under water stress, the optimal data for fresh matter yield was 174.96 tonnes ha -1 with 100% ETc compared to 83.61 tonnes ha -1 with 60% ETc; similarly, the optimal data for water productivity was 107.99 kg m-3 with 100% ETc compared to 83.74 tonnes ha -1 with 60% ETc at the first season. The optimal data for fresh matter yield was 135.52 tonnes per hectare when using white geotextile sheets, when compared to 117.9 tonnes per hectare for control (without mulching), while the optimal data for water productivity was 102.59 kg m -3 for mulching with white geotextile sheet. While the control treatment (without mulching) recorded the lowest data (87.00kg m 3 ) in the first season. Interaction, the optimal data for yield fresh matter was 186.74 ton ha -1 with 100% ETc combined with the mulching with white geotextile sheet, while the optimal data for water productivity was 115.27 kg m -3 with 100% ETc combined with the mulching with white geotextile sheet at the first season; this was true in both seasons. It is noteworthy that, the 80% ETc combined with the mulching with white geotextile sheet get value 101.03 kg m -3 , which it's statistically equal to 100% ETc without mulching, that get 102.13kg m -3 for water productivity, it was true in the two seasons. Results of the present work revealed that yield were affected significantly by water supply levels, the present optimal data agree with [29,30,31,32,33,34]. This result may be due to that using high water irrigation supply possibly due to the increase in soil moisture availability [27,38,39]. The yield increase may be the result of water's impact on several metabolism activities in the plant cell. In addition, an increase in soil moisture may have improved photosynthetic processes, the synthesis of carbohydrates, and yield by increasing soil-available N, K, and P and their uptake in the root zone. [40,41]. Also, the results gained through mulching types are in the same line with those obtained by [7,8,25,26,35,37].
The effects of different mulching techniques at different irrigation rates are shown in Table (5), along with how they affect the parameters of total chlorophyll, leaf cell sap TSS, and leaf cell sap osmotic pressure of iceberg lettuce plants in both seasons. The optimal data for total chlorophyll was 47.62 with 100% ETc, compared to 35.36 with 60% ETc during the first season. Comparing all types of mulching, the application of white geotextile sheets resulted in optimal total chlorophyll, measuring 42.74, whereas the control (without mulching) achieved 39.33 during the first seasonInteraction: in the first season the optimal data for total chlorophyll (49.87) with 100% ETc and mulching with a white geotextile. The same trend was observed in the second season. However, in contrast to total chlorophyll in both seasons, leaf cell sap TSS and osmotic pressure metrics follow the opposite path. This is also true for the interactions between mulching types and water treatments. On this, our findings on water stress are consistent with [28,29,30,31,32]. Furthermore, the outcomes from various mulching techniques are likened to those obtained by [7,8,25,26,34,35,37]. sheet and MWGS = mulching with white geotextile sheet. At the 0.5% level, the means in each column that are followed by the same letter are not substantially different from one another.
Conclusion
In summarize, all mulching types treatments significantly improve soil moisture content, the effectiveness of water application, and crop yield compared to the control (without mulching). While 80% ETc combined with white geotextile sheet get values were statistically equal to the results with the control (100% ETc without mulching), mulching with white geotextile sheet and irrigation requirement (100% ETc) were statistically the most effective treatment in this study. Thus, it is possible to achieve results similar yield to the control or better, while saving an amount of irrigation water of up to 20% by using ETo 80 % combined with mulching with white geotextile sheet without any negative effect on the plant. However, it can be recommended to use geotextile compared to black plastic, as plastic requires more time to degrade, which will be harmful to the environment.
Funding
The study was supported by the "Science, Technology & Innovation Funding Authority in Egypt, (STDF)", "Egyptian-Spanish Joint Technological Co-operation Program, International Cooperation Grants", Grant number (42523) as part of the project "An Innovative Technology for Improving Irrigation Water Use in the Mediterranean Region Using Geotextile Material."
Fig. 1 .
Fig. 1. Effect of without, plastic and geotextile mulch under drip irrigation and irrigation treatments on the rising of moisture within the lettuce root zone during 2021 and 2022 seasons.
Table 1 .
Impact of different types of mulching under water deficiency on plant height, head diameter, head circumference and head volume characteristics of lettuce plants (2021-2022 seasons).
Table 2 .
Impact of different types of mulching under water deficiency on plant fresh weight, head fresh weight, and roots fresh weight characteristics of lettuce plants (2021-2022 seasons).
Table 3 .
Impact of different types of mulching under water deficiency on numbers of leaves per plant, leaf fresh weight, and leaf area characteristics of lettuce plants (2021-2022 seasons).
Table 4 .
Impact of different types of mulching under water deficiency on yield and water productivity of lettuce plants (2021-2022 seasons). ETc = evapotranspiration, WM= Without Mulching, MBPS = mulching with black plastic sheet and MWGS = mulching with white geotextile sheet. At the 0.5% level, the means in each column that are followed by the same letter are not substantially different from one another.
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Domain: Agricultural and Food Sciences Environmental Science
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Transcriptome sequencing and whole genome expression profiling of purple-fleshed sweetpotato under salt stress
Abstract Background: Purple-fleshed sweetpotato (PFSP) is one of the most important crops in the word which helps to bridge the food gap and contribute to solve the malnutrition problem especially in developing countries. Salt stress is seriously limiting its production and distribution. Due to lacking of reference genome, transcriptome sequencing is offering a rapid approach for crop improvement with promising agronomic traits and stress adaptability. Results: Five cDNA libraries were prepared from the third true leaf of PFSP at seedlings stage (Xuzi-8 cultivar) treated with 200 mM NaCl for 0, 1, 6, 12, 48 hours. Using second and third generation technology, Illumina sequencing generated 170,344,392 clean high-quality long reads that were assembled into 15,998 unigenes with an average length 2178 base pair and 96.55% of these unigenes were functionally annotated in the NR protein database. A number of 537 unigenes failed to hit any homologs which may be considered as novel genes. The current results indicated that sweetpotato plants behavior during the first hour of salt stress was different than the other three time points. Furthermore, expression profiling analysis identified 4, 479, 281, 508 significantly expressed unigenes in salt stress treated samples at the different time points including 1, 6, 12, 48 hours, respectively as compared to control. COG analysis revealed that the highest number of genes was categorized as “post-translational modification, protein turnover, chaperones” followed by “signal transduction mechanisms”. Gene ontology (GO) enrichment analysis showed that salt stress caused changes in metabolic process (Secondary and amino acids), hormone response, cellular processes and single organism processes. These findings suggest that salt stress tolerance in PFSP plants may be mainly depended on three factors including the balance between protein biosynthesis and degradation, preventing or correcting damage caused by miss-folding due to salt stress and transforming the certain stimulus induced by salt
stress into a biochemical signal which activates more genes specifically involved in salt stress tolerance.
Introduction
Sweetpotato (Ipomoea batatas (L.) Lam.), the only crop plant belongs to Convolvulaceae family with starchy storage roots. Purple-fleshed sweetpotato (PFSP) considered to be an important source for anthocyanin which displays strong antioxidant properties [1]. It is also considered as an important staple source of calories and proteins which consumed by all age groups. In terms of agricultural production sweetpotato considered as the seventh most important food crop in the world [2].
Salinity is a global problem caused vast area of lands remaining uncultivated. Exposure of sweetpotato plants to salt stress resulting in problems such as ion imbalance, mineral deficiency, osmotic stress, ion toxicity and oxidative stress [3]. Ultimately, these conditions interact with several cellular components including DNA, protein, lipids and pigments. That's in rule impeding plant development and affect sweetpotato production [4]. Therefore, introducing of salt tolerant sweetpotato cultivar became necessary.
With the fact of environmental stress and climate change there is an urgent need to accelerate crops breeding with higher production and stress tolerance traits [5]. In sweetpotato transcriptome sequencing offers a rapid approach for crop improvement with promising agronomic traits and stress adaptability. Several transcriptome sequencing studies have been conducted on hexaploidy sweetpotato genome [6][7][8]. However, having a complex genome structures (2n=6x=90), sweetpotato still didn't achieve a reference genome which covered a few percent of genome, so still a long way from the reference genome [9].
In the present study, second and third generation sequencing technology were used to establish a useful database of transcriptomes sequencing as well as differentially expressed genes in PFSP leaves under salt stress conditions. In total 102,845,433 high quality reads were assembled into 16,856 transcripts giving 15,998 unigenes. Our results provide novel insights into PFSP response to salt stress and identified numerous specific genes involved in salt stress defense mechanisms. That's in role can be used to guide future efforts towards breeding of sweetpotato salt resistant cultivars.
Plant materials
Xuzi-8, a high quality and early mature cultivar with purple flesh storage roots, was used in this experiment. Its storage roots contain 6% soluble sugar and more than 80 mg anthocyanin /100 g fresh weight. This cultivar was obtained from Xuzhou Institute of Agricultural Sciences in Jiangsu Xuhuai District, China.
Treatments and experimental design
Apical stem cuttings (15-20 cm) of Xuzi-8 cultivar were growing in hydroponics culture using Hoagland nutrient medium for four weeks. Seedlings were exposed to salt stress (200 mM NaCl were added to Hoagland solution). 0.1 g sample was taken from the upper third leaf after 0, 1, 6, 12, 48 hour from salt treated and untreated plants for the next generation sequencing. While, for the third-generation sequencing, one sample was collected by mixing the upper third leaf of sweetpotato seedlings after 1, 6, 12, 48 hour of salt stress and one control samples. All collected samples were immediately frozen in liquid nitrogen and stored at -80 º C until processing for RNA extraction and all treatments were done in triplicate.
RNA extraction
Total RNA was extracted from collected samples with the TRIZOL method (Life technologies, Carlsbad, CA) according to the manufacturer's protocol. RNA degradation and contamination were monitored on 1% agarose gels. RNA purity was checked using the Nanophotometer® spectrophotometer (IMPLEN, CA, USA). RNA concentration was measured using Qubit® RNA Assay Kit in Qubit® 2.0 Fluorometer (Life Technologies, CA, USA). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA).
Library Preparation for Transcriptome Analysis
A total amount of 3 μg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer's protocol and index codes were added to attribute sequences to each sample. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. Fragmentation was carried out using divalent cations under elevated temperature in NEBNext First Strand Synthesis Reaction Buffer 5X . First strand cDNA was synthesized using random hexamer primer and M-MuLV Reverse Transcriptase RNase H-. Second strand cDNA synthesis was subsequently performed using DNA Polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/polymerase activities. After adenylation of 3' ends of DNA fragments, NEBNext Adaptor with hairpin loop structure were ligated to prepare for hybridization. In order to select cDNA fragments of preferentially 150~200 bp in length, the library fragments were purified with AMPure XP system (Beckman Coulter, Beverly, USA). Then 3 μl USER Enzyme (NEB, USA) was used with size-selected, adaptor-ligated cDNA at 37°C for 15 min followed by 5 min at 95 °C before PCR. Then PCR was performed with Phusion High-Fidelity DNA polymerase, Universal PCR primers and Index (X) Primer.
At last, PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system.
Clustering and sequencing
The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina platform and paired-end reads were generated.
Data analysis Quality control
Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts.
In this step, clean data (clean reads) were obtained by removing reads containing adapter, reads containing ploy-N and low-quality reads from raw data. At the same time, Q20, Q30, GC-content and sequence duplication level of the clean data were calculated. All the downstream analyses were based on clean data with high quality.
Transcriptome assembly
The data from all libraries/samples were pooled into one big left fq file (read1 files) and right fq files (read2 files) into one big right [10]. Transcriptome assembly was accomplished based on the left and right fq using Trinity [11] with min_kmer_cov set to 2 by default and all other parameters set default.
Gene functional annotation
Gene function was annotated based on the following databases: Nr (NCBI non-redundant protein sequences, [URL]/) with E-value cut-off of le-5 Nt (NCBI non-redundant nucleotide sequences [URL]/) with E-value cut-off of Based on the NR and Pfam annotations, Blast2GO (v2.5) was used to obtain GO (Gene Ontology) annotations ( [URL] ) according to the molecular functions, biological processes and cellular component ontologies [12]. GO enrichment analysis of the differentially expressed genes (DEGs) was implemented by the GO-seq R packages based Wallenius non-central hyper-geometric distribution [13] which can adjust for gene length bias in DEGs.
KEGG [14] is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecularlevel information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies ( [URL]/ ). KOBAS software were used [15] to test the statistical enrichment of DEGs in KEGG. SSR of the transcriptome were identified using MISA ( [URL] ), and primer for each SSR was designed using Primer3 ( [URL] ).
Quantification of gene expression levels and differential expression analysis
Gene expression levels were estimated by RSEM [16] for each sample. Clean data were mapped back onto the assembled transcriptome. Read count for each gene was obtained from the mapping results.
Differential expression analysis of two conditions/groups was performed using the DESeq2R package DESeq2 rovide statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P values were adjusted using the Benjamini and Hochberg's approach for controlling the false discovery rate. Genes with an adjusted P-value ≤0.001 found by DESeq2 were assigned as differentially expressed [17]. Q-value≤0.001& |log2FC foldchange |≥1 was set as the threshold for significantly differential expression.
Sequencing and de novo assembly of sweetpotato transcriptome under salt stress conditions
Five cDNA libraries were prepared from the third true leaf of PFSP seedlings (Xuzi-8 cultivar) treated with 200 mM NaCl for 0, 1, 6, 12, 48 hours. These libraries were sequenced using Illumina high-throughput sequencing platform. After removing the lowquality reads and all possible contamination, a total of 170,344,392 clean reads with Q20 >96.73% and a GC percentage between 45.07% and 46.50% (Table 1). Each library was represented by over than 30 million high-quality reads, with number ranging from 32,830,183 to 35,663,873. Due to the lake of a reference genome, the clean reads resulted from the transcriptome sequences were aligned and assembled using Trinity software. After further clustering and assembly, a total of 21,497,466; 20,272,643; 21,954,725; 19,121,890 and 19,998,709 mapped reads were obtained with percentage 60.26%, 61.79%, 61.62%, 59.33% and 58.87% of total reads at different time points (0, 1, 6, 12, 48 hours), respectively. The quality of these assemblies and unigenes length distribution are shown in Table 1. Statistics on unigenes and transcripts length resulted from mixed second and third generations sequencing were performed using PacBio's officially recommended cogent software (Table1 and 2, Figure 1). In addition, the total number of CDS was 30,615 of which 23,245 CDS mapped to the protein database.
Functional annotation
To annotate the obtained unigenes, a BlastX search against the NR NCBI protein database with cut-off E-value of 10 -5 based on sequence similarity. In total, 15,461 unigenes were detected ( Table 3)
Expression patterns of PFSP unigenes in response to salt stress
The results in Figure 6 showed that the highest number of DEGs was induced at 48 hours 3.6. Detection of salt-induced genes related to salt tolerance stressed samples using the rigorous algorithm (FDR≤0.001, log2 FC-ratio ≥1). As shown in respectively. Sequence showed homology with known sequences were classified as "hits" and sequence showed no homology with known sequences were classified as "no hits".
SSR and SNP identification
For further application of sweetpotato SSRs and SNPs were discovered using assembled transcriptomes. A total of 24,559 SSRs was identified in transcriptomes present in 15,976 sequences. Furthermore, the number of sequence containing more than one SSR was 5,762 and the number of SSRs present in compound formation was 2,215. In addition, the major types of the identified SSRs were mono-nucleotide (19,380), di-nucleotide (2,791), tri-nucleotide (2,199), tetra-nucleotide (123), penta-nucleotide (33) and hexa-nucleotide
Discussion
Sweetpotato is a hexaploid non-model crop with a complex genome lacking high quality reference genome [18]. To date the current understanding of the complex physiological and molecular mechanisms of salt tolerance in sweetpotato remains limited [19,20]. High throughput RNA sequencing is required for identification of candidate genes involved in salt stress tolerance. In addition, it will be helpful for better understanding of salts stress tolerance mechanisms in sweetpotato [5].
In the present study, deep sequencing analyses of PFSP under different durations of salt stress were characterized. Using second and third generation technology, Illumina sequencing generated 170,344,392 clean high-quality long reads that were assembled into 15,998 unigenes with an average length 2178 base pair and 96.55% of these unigenes were functionally annotated in the NR protein database. A number of 537 unigenes failed to hit any homologs which may be considered as novel genes.
The current results revealed that the obtained sequences highly matched with top seven species with percent ranging from 4.58 to 21.3% including Nicotiana sylvestris, Nicotiana tomentosiformis, Solanum tuberosum, Sesamum indicum, Coffea canephora, Solanum lycopersicum and Solanum pennelli. In addition, the online available sequence of sweetpotato genome gave only 3.07% matches coming in the 8 th rank with the current experiment obtained sequence. That's mean that 96.93% of our data are not present in the sweetpotato online data. Therefore, the current annotation results will improve sweetpotato genome annotation and facilitate the discovery of genetic resources that are responsible for salt stress in hexaploid sweetpotato.
The results in Figure 3 showed that the most dominant Go-terms which were identified during the different durations of salt stress included metabolic, cellular, single organism and response to stimulants. These results are in agree with [21] in diploid halophytic sweetpotato, [22] in Ipomoea imperati [23]. The present COG results indicated that there were 16.89% belongs to "general function prediction only" which mean that these genes are poorly characterized, in addition, 4.34% genes with unknown function. The highest number of genes was categorized as "post-translational modification, protein turnover, chaperones" in our study. Which mean that, sweetpotato plants under salt stress conditions, starts the key mechanisms of chemical modifications including regulating of enzymes activity, localization and interaction with other cellular molecules such as proteins, nucleic acid, lipids and co-factors [24]. Furthermore, protein turnover related genes control the balance between protein biosynthesis and degradation, which is very important for determining the resistant or sensitivity of the plant to salt stress. That's may be due to if the protein biosynthesis is more than breakdown indicates an anabolic state, in this case the plant tolerance to stress will be enriched [25][26][27][28]. Moreover, Protein chaperones' major function is to prevent or correct damage caused by miss-folding due to salt stress [29][30][31][32]. The second COG group of genes involved in "signal transduction mechanisms" which is mainly transforming the certain stimulus induced by salt stress into a biochemical signal which activates more genes specifically involved in salt stress tolerance [33].
In the present study, to identify significant gene expression changes under salt stress, differentially expressed unigenes were analyzed using the rigorous algorism equation (FDR≤0.001, Log2FC-ratio ≥ 1) depending on RPKM reads.
The current results indicated sweetpotato plants behavior during the first hour of salt stress was different than the other three time points. During the first hour of salt stress a number of four unigenes only were expressed with significant difference (unigene11357, unigene15171, unigene16391 and unigene7424). The first unigene (11357) belongs to SBP gene family which have important role in leaf development, vegetative phase change and may be have a role in stress response [34]. The second (unigene-15171) belongs to HSP70 which is essential regulator to maintain internal cell stability and prevent aggregation under physical or chemical pressure [35]. The third unigene (16391) is a plant invertase/ pectin methyl-esterase inhibitor. The invertase affects growth and development consisting with its activities such as stress response. In addition, pectin methyl-esterase determines the solidity of cell wall including root development and permeability. The fourth unigene (7424) belongs to uncharacterized protein family and unknown function [36]. According to the current results presenting of only four significantly expressed unigenes in leaf tissues during the first hour of salt stress may be due to salt stress signals slightly received or didn't received by leaves during the first hour [37] in Xuzi-8 sweetpotato cultivar.
At six hours of salt stress, there were 529 up-regulate unigenes giving 479 significantly expressed unigenes. A number of ten genes were the highest (four folds higher than control) among all significantly expressed genes including (unigene128, 16087, 16131, 2278, 4002, 55, 5655, 9231, and 9447). Furthermore, it was noted that these superior unigenes are three different functions including protein detoxification, energy production and conservation, and dehydrin. In addition, out of these 479 unigenes there were six unigenes involved in the defense mechanisms against salt stress including (Unigene128, 13856, 13920, 14004, 396, and 6144). Except for the unigene128 and 396 all the other unigenes belong to ABC-transporter G-family which is involved in growth, development and response to abiotic stress. In addition, the unigene396 belongs to pentatricopeptiderepeat proteins (PPR-family) which play important roles in organelle RNA metabolism, plant development and involved in abiotic stress response which have been previously reported in rice [38,39]. There were 5 genes specifically involved in salt stress response including (unigene243, 3644, 7343, 7826 and 9718). The unigene243 and 3644 belong to ABA insensitive-like protein which involved in ABA and salt stress responses and act as a positive component in glucose signal transduction [40]. The unigene7343 belongs to EIDlike F-box protein family which is a known drought response regulation. Unigene7826 were found to be belonged to WCOR 413-like protein which is responsible for cryoprotection of plasma membrane against dehydration stress which has been discovered earlier in sweetpotato genome, these findings are in agree with [41,42] in wheat. The unigene 9718 was detected as a putative salt stress responsive protein isoform-1 which has been discovered before in sweetpotato genome.
At twelve hours of salt stress a number of 341 unigenes were up-regulated with 281 significantly expressed unigenes. Out of the 281 genes there were three unigenes (unigene3153, 3480 and 3682) expressed with four folds more than control, all these four genes belonging to Ahpc-TSA family with intracellular signal transduction biological function which constitutes an enzymatic defense against salt stress [43]. There were 10 unigenes among the 281 unigenes, are specifically involved in defense mechanisms against salt stress (unigene10470, 11483, 12478, 12588, 12916, 13856, 14004, 2507, 4295 and 6144) which were included under ABC-transporter family [44]. In addition, there were 5 unigenes with a biological function as response to salt stress (unigene13368, 13566, 234, 3644 and 7343) which belongs to three different families including BEL1-like homeodomain protein-1 (BLH-1), ABA insensitive like protein (bZIP transcription factor) and EID-like F-box protein-3 [45].
At 48 hours of salt stress, there were 663 up-regulated unigenes with 508 significantly expresses. A number of 9 unigenes were the highest significantly expressed among the 508 unigenes. Out of these 9 unigenes, four unigenes (unigene16087, 16288, 2278 and 9017) are responsible for energy production and conservation; two unigenes (unigene2618, 2863) were responsible for signal transduction mechanism, one unigene (unigene657) as a reverse transcriptase, one unigene (unigene10431) as protein import into nucleus, and one (unigene7343) was involved in posttranslational modification, protein turnover, chaperones. In addition, there were 6 unigenes are specifically involved in defense mechanisms to salt stress including unigene10470, 12916, 2507, 4295, 5014 and 6144. All these six unigenes belong to ABC-transporter family which is involved in growth, development and stress response [44]. Moreover, a number of 5 unigenes Note: Nt, total number of clean nucleotides; The GC percentage is the proportion of guanidine and cytosine nucleotides among total nucleotides; The Q20 and Q30 percentage is the proportion of nucleotides with a quality value >20 and 30, respectively; The N percentage is the proportion of unknown nucleotides in clean reads. Clusters of orthologous groups (COG) classification in Xuzi-8 sweetpotato cultivar.
Genes from the same Orthologous have the same function, so that direct functional annotations to other members of the same KOG cluster.
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Domain: Agricultural and Food Sciences Biology Environmental Science
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Safety and Suitability of Infant Formula Manufactured from Extensively Hydrolyzed Whey Protein Compared to Intact Protein: A Combined Analysis of Two Randomized Controlled Studies
Our aim was to assess the nutritional safety and suitability of an infant formula manufactured from extensively hydrolyzed protein in comparison to infant formula manufactured from intact protein (both with low and standard protein content). We performed a combined analysis of raw data from two randomized infant feeding studies. An analysis of covariance (ANCOVA) model was used to determine the non-inferiority of daily weight gain (primary outcome; margin −3 g/day), with the intervention group as a fixed factor and geographic region, sex, and baseline weight as covariates (main model). The data of 346 infants exposed to the formula were included in the analysis. The sample size of the per-protocol analysis with 184 infants was too small to achieve sufficient statistical power. The lower limit of the 97.5% confidence interval (−0.807) of the mean group difference in daily weight gain (i.e., 2.22 g/day) was above the −3 g/day margin (full analysis set). Further anthropometric parameters did not differ between the infant formula groups throughout the study. Growth was comparable to breastfed infants. We conclude that the infant formula manufactured from extensively hydrolyzed protein meets infant requirements for adequate growth and does not raise any safety concerns.
Introduction
An adequate dietary protein supply is essential for healthy growth and development in infancy [1,2].
Human milk is recognized as the optimal source of nutrients for infants throughout at least the first 6 months of life [3]. However, if breastfeeding is not possible, available, or adequate, infant formulae are the only advisable breast milk substitutes. Infant formulae that are manufactured from cow's milk protein or other protein sources have been successfully used for many decades.
Next to infant formulae manufactured from intact proteins, infant formulae manufactured from hydrolyzed proteins are available for infants with an increased risk of developing allergies. Hydrolyzed proteins are smaller, easier to digest, and considered to be less allergenic when compared to intact proteins. However, the bioavailability of proteins, amino acids (AAs), and other nutritional components may be different between infant formulae manufactured from hydrolyzed protein (HP) formulae and intact protein (IP) formulae [4]. Based on the degree of hydrolysis and the proportion of small peptides, hydrolysates are classified as partially or extensively hydrolyzed.
Although the use of protein hydrolysates has been permitted for many years and the use of protein hydrolysates in the manufacturing of infant formulae is widespread in the market, the level of hydrolysis, the protein source, and other components may affect the safety and tolerance of different HP formulae; thus, the extrapolation of results from one HP formula to another is not accepted by regulators [15].
The growth effects and safety of infant formulae marketed by HiPP (Pfaffenhofen, Germany) compared to human milk have been evaluated in two studies: the HA study [16] evaluated different HP formulae with standard and low protein content, whereas the BeMIM study [17] compared IP formulae with standard and low protein content. In both studies, the standard and low-protein formulae manufactured from either protein hydrolysate or intact protein were considered safe and suitable for infants up to the age of 4 months.
To further explore the nutritional safety and suitability of these HP formulae comparatively, we compiled measures of growth between the HP formula and IP formula by performing a combined analysis of the HA and BeMIM studies.
Analysis Approach and Individual Studies
The HA and BeMIM studies were randomized, controlled, and double-blinded and investigated the non-inferiority of low-protein infant formulae to conventionally used infant formulae with standard protein content. While the HA study [16] evaluated infant formulae manufactured from hydrolyzed proteins, the BeMIM study [17] focused on IP formulae. Both studies used a non-randomized breastfed group as a reference. The intervention period of study formula feeding for each participant lasted from birth (starting, at the latest, from 1 month of life) until 4 months of life and included monthly study visits.
The combined data analysis was performed based on raw data from the two studies. The inclusion criteria differed slightly between studies and were aligned post-hoc to allow for comparable data. Healthy term newborns ≤ 28 days of life with a gestational age of ≥37 weeks and a birth weight between 2500 and 4500 g were included in the combined analysis.
Diet
The HP and IP formulae compared had similar protein content at the respective protein level (i.e., standard versus vs. low protein). HP formulae were whey-based, extensively hydrolyzed, and included 1.9 g protein/100 kcal (LP) or 2.3 g protein/100 kcal with or without synbiotics. For the synbiotics, Limosilactobacillus fermentum CECT5716 was used as a probiotic and galacto-oligosaccharides (GOS) as prebiotics. IP formulae were based on a whey:casein ratio of 60:40 and protein content of either 1.9 g/100 kcal (LP) or 2.2 g/100 kcal.
Both the HP and IP formulae were supplemented with individual AAs to meet regulatory requirements. Except for the IP formula containing 2.2 g/100 kcal, all formulae contained arachidonic and docosahexaenoic acid in a ratio of 1:1. For more information on the infant formulae compositions, see Supplementary Table S1.
Five intervention groups were investigated. From the HA study, eHF-infant formula manufactured from extensively hydrolyzed whey protein and LPeHF + Syn-low-protein infant formula manufactured from extensively hydrolyzed whey protein with synbiotics; from the BeMIM study, iPF-infant formula manufactured from intact protein and LPiPFlow-protein infant formula manufactured from intact protein; and, as a reference in both studies, BF-breastfeeding.
Infant formulae were administered orally ad libitum. Infant formula intake, as well as the number of breastfeeding meals and intake of other food or drinks, e.g., energy-containing liquids (sweetened tea or juice) or non-energy-containing liquids (tea and water), were documented using 3-day protocols.
Primary and Secondary Outcome Assessments
The primary outcome was the average daily weight gain in grams per day (g/day) between 1 and 4 months of life, to estimate adequate growth. Secondary outcomes included measurements of body length and head circumference, including respective z-scores as further growth indices, and nutrient intake, adverse events, stool characteristics, and biochemical markers (blood urea, albumin, AAs).
The aim of the combined analysis was to compare HP with the IP formula using formulae with standard protein content (i.e., eHF vs. iPF) and formulae with low protein content (i.e., LPeHF + Syn vs. LPiPF).
Statistics and Power Estimation
Retrospective sample size estimation scenarios were used to determine if sufficient infants were available in a confirmatory setting. Between 43 and 94 participants per group for LPeHF + Syn vs. LPiPF and eHF vs. iPF, respectively, were required to demonstrate non-inferiority. The power simulations were based on the means and standard deviations (SD) of the groups used in the HA and BeMIM studies, using both a per-protocol set (PPS) and full analysis set (FAS), a non-inferiority margin of −3.0 g/day at a one-sided significance level of 2.5%, and a power of 80% (Supplementary Table S2).
The FAS comprised all enrolled participants who participated at least in the month 1 visit and had received study formula. In PPS, only data from participants complying with the predefined conditions, such as completion of the intervention period up to 4 months of life, no intake of other infant formulae besides the study intervention, and breastfeeding at a maximum of once daily, were included. According to local practice, in the study countries, some infants receive liquids, like tea or water, in addition to breastmilk or infant formula, during the first 4 months of life, which was limited to a maximum amount of 50mL per day to still be included in the PPS. The main conclusions on the primary outcome measure were based on PPS; FAS served as a sensitivity analysis.
For the analysis of the daily weight gain, an analysis of covariance (ANCOVA) model was used to show non-inferiority, with the intervention group as a fixed factor and region, sex, and baseline weight as covariates (main model). An ANCOVA with only the intervention group as a fixed factor was used as a sensitivity analysis. Furthermore, additional covariates (maternal age at infant's birth, maternal body mass index (BMI), gestational age, smoking status of mother before and during pregnancy, weight at birth, maternal education, socioeconomic status) were included in the model. However, these additional covariates did not reveal any plausible and consistent relations with daily weight gain over all populations and group comparisons (LPeHF + Syn vs. LPiPF; eHF vs. iPF) in the ANCOVA model; thus, the results are not described.
The lower limit of the 97.5% confidence interval (CI) of the difference between formula groups was compared to the non-inferiority margin of −3.0 g/day. A hierarchical test design was assumed with ordered hypotheses (Step 1: eHF vs. iPF, Step 2: LPeHF + Syn vs. LPiPF), which was the only analysis that took multiple testing into account.
The European Food Safety Authority (EFSA) Guidance [18] stipulates an alternative way to analyze adequate growth, i.e., the equivalence in growth between intervention groups. Thus, this was also tested using an ANCOVA model, with the region and baseline value as covariates and weight-for-age z-scores at the age of 4 months. Equivalence was concluded if the calculated two-sided 90% CI of the estimated mean difference in the weightfor-age z-score was within the predefined margin of ± 0.5 SD, a bandwidth considered to be indicative for adequate growth.
Secondary outcome analyses were carried out in the PPS and FAS. Daily length and head circumference gains were compared between intervention groups using ANCOVA models similar to the model used for the primary outcome, with respective baseline characteristics included as covariates, but with a focus on superiority.z-scores were calculated based on the World Health Organization (WHO) growth standards for breastfed children [19]. Comparisons between intervention groups for zscores were done using a mixed model of repeated measurements (MMRM), with the region, visit, intervention group, and intervention group-by-visit interaction as fixed factors and participant as a random factor, as well as additional covariates (Supplementary Table S5).
Nutritional parameters (intake of study infant formula, other infant formula, energycontaining liquids, complementary feeding, and additional breastfeeding) as well as biochemical markers were evaluated using the van Elteren test adjusted for region. A Cochran-Mantel-Haenszel test, adjusted for region, was used to analyze gastrointestinal tolerance. The analysis of adverse events evaluated the number and frequency of intervention-emergent events by system organ class and preferred terms (according to the Medical Dictionary for Regulatory Activities (MedDRA) coding version 23.1). Amino acids and laboratory parameters were descriptively assessed and two-sided superiority tests on a significance level of 5% were applied.
Linear regression models were used to examine the dependencies between average liquid intake per day and weight gain, or infant formula intake between month 1 and month 4.
Statistical analyses were performed with the WPS Workbench version 4.3 ( © Copyright World Programming Limited 2002-2022) using the SAS language code.
Study Population
The HA study was conducted between 2010 and 2013 as a multicenter study in Germany, Austria, and Serbia, and the BeMIM study between 2010 and 2011 as a single-center study in Serbia. Overall data from 1008 participants were available, of which 589 participants were included in the combined analysis (385 randomized formula-fed participants and 204 breastfed participants). The main reasons for the exclusion of 419 infants from the analysis were receiving infant formulae from a different protein source (see study design of Ahrens et al. (2018) [16], a missing visit at month 1, or screening failures.
To evaluate HP vs. IP formulae, the data of 385 randomized formula-fed participants were considered, of which 353 participants took part in the 1-month visit, had documented data, and received at least one bottle of study formula, and 307 completed the 4-month follow-up visit (Figure 1). The FAS comprised 346 participants (86 eHF, 89 iPF, 83 LPeHF + Syn, 88 LPiPF). For PPS, data were limited to 184 participants (39 eHF, 42 iPF, 54 LPeHF + Syn, 49 LPiPF). The predominant reasons for exclusion from PPS in the formula groups were the violation of the feeding regimen and an age outside the visit or enrolment window; not being allowed concomitant medication; early withdrawal; and the violation of the eligibility criteria. Data from 204 breastfed participants (203 FAS, 115 PPS) served as an external reference.
Baseline characteristics including sex, first-born status, maternal and paternal age and BMI, maternal smoking, age at randomization, mode of delivery, and anthropometry at birth were similar between the eHF and iPF groups and between the LPeHF + Syn and LPiPF groups for FAS (Supplementary Table S3) and PPS, except for education, where mothers in the iPF group had higher education levels compared to those in the eHF group (FAS). Due to the different study designs (multicenter vs. single center), all participants in the iPF and LPiPF groups were form Serbia, while over 66% of participants in the eHF and LPeHF + Syn groups were from Serbia and 33% from Germany and Austria. Baseline characteristics including sex, first-born status, maternal and paternal age and BMI, maternal smoking, age at randomization, mode of delivery, and anthropometry at birth were similar between the eHF and iPF groups and between the LPeHF + Syn and LPiPF groups for FAS (Supplementary Table S3) and PPS, except for education, where mothers in the iPF group had higher education levels compared to those in the eHF group (FAS). Due to the different study designs (multicenter vs. single center), all participants in the iPF and LPiPF groups were form Serbia, while over 66% of participants in the eHF and LPeHF + Syn groups were from Serbia and 33% from Germany and Austria.
Weight Gain and Growth
The mean difference in daily weight gain in participants receiving eHF compared to participants fed iPF was 0.73 g/day (CI [−3.029, inf. [) for PPS, with the lower limit of the 97.5% CI narrowly missing the predefined non-inferiority margin of -3 g/day (Figure 2, Supplementary Table S4).
Weight Gain and Growth
The mean difference in daily weight gain in participants receiving eHF compared to participants fed iPF was 0.73 g/day (CI [−3.029, inf.]) for PPS, with the lower limit of the 97.5% CI narrowly missing the predefined non-inferiority margin of -3 g/day (Figure 2, Supplementary Table S4). Baseline characteristics including sex, first-born status, maternal and paternal age and BMI, maternal smoking, age at randomization, mode of delivery, and anthropometry at birth were similar between the eHF and iPF groups and between the LPeHF + Syn and LPiPF groups for FAS (Supplementary Table S3) and PPS, except for education, where mothers in the iPF group had higher education levels compared to those in the eHF group (FAS). Due to the different study designs (multicenter vs. single center), all participants in the iPF and LPiPF groups were form Serbia, while over 66% of participants in the eHF and LPeHF + Syn groups were from Serbia and 33% from Germany and Austria.
Weight Gain and Growth
The mean difference in daily weight gain in participants receiving eHF compared to participants fed iPF was 0.73 g/day (CI [−3.029, inf. [) for PPS, with the lower limit of the 97.5% CI narrowly missing the predefined non-inferiority margin of -3 g/day (Figure 2, Supplementary Table S4). In a sensitivity analysis using FAS, the lower limit of the 97.5% CI (−0.807) of the mean group difference in daily weight gain (i.e., 2.22 g/day) was well above the −3 g/day margin (Figure 2, Supplementary Table S4). Similar results were seen in a further sensitivity analysis using an ANCOVA model without adjustments, yielding lower limits of the 97.5% CI above the −3 g/day margin (PPS: −2.059; FAS: −1.512, Figure 2).
The difference in daily weight gain between the LPeHF + Syn and LPiPF groups was 1.39 g/day (CI [−1.321, inf. [) in PPS, and 0.28 g/day (CI [−2.344, inf. [) in FAS (Figure 2, Supplementary Table S4). Similar results were obtained using an ANCOVA without adjustments (lower limit of the 97.5% CI, PPS: −0.606; FAS: −2.068, Figure 2). According to the hierarchical test scheme, the procedure stopped at the inferiority testing of eHF vs. iPF and no further inferential conclusions could be made when testing the LPeHF + Syn vs. LPiPF groups.
The length gain from months 1 to 4 did not differ between the HP and IP formula groups in PPS. Head growth was greater with LPeHF than LPiPF (p = 0.0192), but similar between eHF and iPF (PPS). The FAS analyses showed comparable results except for a significant difference in length gain between the eHF and iPF groups (p = 0.0325) (Supplementary Table S4). In BF participants, the gains in weight, length, and head circumference were smaller or similar to those observed in the formula groups (Supplementary Table S4).
Anthropometric measurements, expressed as z-scores (Figure 3 for PPS, Supplementary Figure S1 for FAS), were within -1 to 1 from months 1 to 4 of life, confirming age-appropriate development in all formula groups. No differences were observed between HP and IP formulae at any time between 1 and 4 months of life. For both PPS and FAS, an MMRM analysis confirmed that there were no differences between intervention groups (Supplementary Table S5). An ANCOVA at the age of 4 months confirmed equivalent growth with HP and IP formulae, i.e., the two-sided 90% CI of the mean difference in the weight-for-age zscore was contained within the pre-defined equivalence margin of ± 0.
Nutrient Intake
No differences in energy intake of the study infant formula between eHF and iPF were found throughout the observation period (PPS and FAS). The average energy intake in the LPeHF + Syn and LPiPF formula groups was comparable at months 2 and 3, but significantly higher in the LPeHF + Syn group at month 1 (FAS) and month 4 (FAS and PPS, Supplementary Tables S6 and S7).
The number of infants with documented additional breastfeeding was lower in infants fed the HP formula (Supplementary Tables S6 and S7). The same applied for energycontaining liquid intake (Supplementary Tables S6 and S7).
The number of infants in both the HP and IP groups who consumed other formulae and/or complementary food was too low (at a maximum of six infants) for a meaningful comparison (for FAS and PPS). Complementary feeding, generally, did not start before 4 months of life.
Impact of Liquid Intake on Growth and Formula Intake
Energy-containing liquids were consumed by 42.2% of infants in the formula-fed groups (FAS) and 28.6% of breastfed participants. No measurable effects of energycontaining liquid intake on participant weight gain were observed, as evidenced by a broad scatterplot and a Spearman's correlation coefficient near zero (Figure 4A). There was also no correlation between the intake of liquid and study formula for energy in kcal/days (Supplementary Figure S2), as well as for the amount of intake in mL/day (Supplementary Figure S3). In line with this, the weight-for-age z-scores did not correlate with energy-containing liquid intake at months 1, 2, 3, or 4 (Figure 4B). In addition, the influence of mean energy-containing liquid intake on the amount of infant formula intake from month 1 to month 4 could not be confirmed. Spearman's correlation coefficients were around zero (Supplementary Figure S4). Most infants consumed less than 50 mL/day of energy-containing liquids. As for the overall population, there was no obvious influence of energy-containing liquid intake on weight gain in infants consuming less than 50 mL/day of energy-containing liquids (Figure 4).mean energy-containing liquid intake on the amount of infant formula intake from month 1 to month 4 could not be confirmed. Spearman's correlation coefficients were around zero (Supplementary Figure S4). Most infants consumed less than 50 mL/day of energy-containing liquids. As for the overall population, there was no obvious influence of energycontaining liquid intake on weight gain in infants consuming less than 50 mL/day of energy-containing liquids (Figure 4).
Adverse Events
The percentage of infants affected by adverse events was comparable in each intervention group and the BF group and no formula-related risks were observed (Supplementary Table S8). The incidence of serious adverse events was between 2.3% (iPF) and 6.8% (LPiPF), but none of the serious adverse events was related to infant formula intake. Adverse events associated with infections were more frequent in IP than in HP formula-fed participants, while pyrexia appeared to be more common in the HP formulae group. Overweight, which was documented in more detail in the HP study, was observed in HP formula-fed participants (Supplementary Table S8). An MMRM analysis, however, did not indicate any differences in growth (weight-for-age and BMI-for-age z-scores) between the HP and IP groups from 1 to 4 months of life (Supplementary Table S5).
Stool Characteristics
Stool characteristics were documented over a period of three days prior to each visit. For FAS, significantly more HP-fed infants showed a lower stool frequency than IP-fed
Suitability 3.4.1. Adverse Events
The percentage of infants affected by adverse events was comparable in each intervention group and the BF group and no formula-related risks were observed (Supplementary Table S8). The incidence of serious adverse events was between 2.3% (iPF) and 6.8% (LPiPF), but none of the serious adverse events was related to infant formula intake. Adverse events associated with infections were more frequent in IP than in HP formula-fed participants, while pyrexia appeared to be more common in the HP formulae group. Overweight, which was documented in more detail in the HP study, was observed in HP formula-fed participants (Supplementary Table S8). An MMRM analysis, however, did not indicate any differences in growth (weight-for-age and BMI-for-age z-scores) between the HP and IP groups from 1 to 4 months of life (Supplementary Table S5).
Stool Characteristics
Stool characteristics were documented over a period of three days prior to each visit. For FAS, significantly more HP-fed infants showed a lower stool frequency than IP-fed infants at 1, 3, and 4 months (p ≤ 0.001, eHF vs. iPF) and at 2, 3, and 4 months (p < 0.001, LPeHF + Syn vs. LPiPF, Supplementary Figure S4, Supplementary Table S10).
"Green" colored stools were reported more frequently in the HP formula groups (with increasing frequencies over the observation period; eHF: from 15.4% at month 1 to 34.2% at month 4 of life; LPeHF + Syn: from 27.8% at month 1 to 60.0% at month 4; FAS) compared to IP formula groups (iPF: 2.0% to 7.8% with the highest value at month 3, LPiPF: 4.9% to 7.5%, highest value at month 2; FAS). Statistically significant different stool color patterns were reached between the low-protein groups (LPeHF + Syn vs. LPiPF) at all timepoints in FAS (Supplementary Table S10). The stool color patterns between the standard protein groups (eHF vs. iPF) were only statistically different at month 1 in FAS. In the BF group, green stools were reported at a similar frequency as in the IP groups (3.6% to 9.9% (at month 2) of infants). In the BF and IP groups, most infants (>90%) reported stools ranging from yellow and brown to mustard-like during the entire observation period, while, in the HP groups, infants presenting these stool colors decreased over time (eHF: from 84.6% at month 1 to 64.7% at month 4 of life; LPeHF + Syn: from 71.8% at month 1 to 38.8% at month 4; FAS). Black/grey stools were hardly seen in any group (generally <1.5%, except for the eHF group at month 3 with 3.1%, FAS).
No significant differences between groups were observed for stool consistency in FAS (except for LPeHF + Syn vs. LPiPF at month 3 in FAS, p = 0.019). The stools of HP-fed participants were more frequently described as "watery" (eHF: 9.4% to 14.6% and LPeHF + Syn: 5.2% to 10.6% across observation period; FAS) compared to the stools of IP formula-fed participants (iPF 0.4% to 3.9%, LPiPF 0.8% to 3.5%; FAS), but most infants (85% to 95%, FAS) had a stool consistency ranging from soft, formed, sausage, and soft sausage to mushy stools (Supplementary Table S10)."Watery" refers only to the stool consistency and does not include diarrhea. The proportion of infants with "watery" stools tended to increase from month 1 to month 4 in all formula groups. Infants with hard stools were rare in the eHP and iPF groups (below 1%, except for the iPF group at month 1, 3.9%; FAS) but slightly more common in the LPiPF group (2.3% to 7.4%, FAS). Compared to the formula groups, BF infants reported more frequently watery stools (21.2% to 31.4%); stool consistencies ranging from soft, formed, sausage, and soft sausage to mushy were presented by 68.6% to 78.6% of BF infants and hard stools were rarely seen (≤0.2%).
Biochemical Markers
The values for plasma albumin and blood urea nitrogen (BUN) were within normal ranges (3.0-5.2 g/dL for albumin, 2.0-7.2mmol/L for blood urea nitrogen [20]) for most participants in all intervention groups at month 4 in PPS and FAS (Table 1). While the BUN values did not differ significantly between the HP and IP formula groups, HP formula-fed participants had significantly higher plasma albumin values compared to respective IP participants (van Elteren test adjusted for region) in both PPS and FAS. BUN tended to be higher in the formula groups than in the BF group. While 5% (eHF) to 21% (LPeHF + Syn) of formula-fed infants had BUN concentrations below the reference range reported by Oster [20], more, i.e., 52%, of breast-fed infants had BUN concentrations below the reference range.
Amino acid plasma levels were evaluated at month 4. Although the AA profile appeared to be similar in all groups (Supplementary Table S9), the plasma concentrations of most AAs were significantly lower in the IP compared to the respective HP formula-fed participants. Exceptions were glutamic acid, ornithine, and phenylalanine, which were comparable between eHF and iPF, and aspargic acid, proline, and valine, which were comparable between LPeHF + Syn and LPiPF (FAS, Supplementary Table S9).
Discussion
We conducted a combined analysis of two randomized studies in healthy term infants to compare the effects of an HP formula to an IP formula on growth parameters during the first 4 months of life. The results indicated non-inferior weight gain between infants consuming formulae manufactured from extensively hydrolyzed whey protein at standard or low protein levels and infants receiving formulae manufactured from intact cow's milk with comparable protein content. The non-inferiority margin (−3 g/day for the lower limit of the 97.5% CI) for daily weight gain was reached, when comparing eHF vs. iPF (FAS) and LPeHF + Syn vs. LPiPF (PPS, FAS). For the eHF vs. iPF (PPS) comparison, the non-inferiority margin was narrowly missed (lower 95% CI: −3.029), presumably due to the low number of infants and inadequate sample size in PPS (39 eHF and 42 iPF vs. 94 per group required). Secondary endpoints of growth indices, i.e., weight, length, and head circumference, were generally similar between HP and IP formulae at both protein levels, except for greater monthly head circumference growth (low-protein infant formula, PPS and FAS) and length gains (standard protein level, FAS) in the HP compared to IP formula. However, compared to the WHO growth standards, the mean z-score values of all intervention groups were within ±1 SD during the intervention (Figure 3, in both PPS and FAS and at both low and standard protein levels), indicating comparable and adequate growth with all interventions. In addition, no significant differences between intervention groups were observed for all other z-score values assessed in this study, suggesting that the few observed differences were not clinically relevant.
The findings of this study are consistent with observations reported in other publications. Karaglani 2023) [21] demonstrated in three randomized controlled studies comparable growth between infants fed a partially or extensively hydrolyzed whey-based formula and infants fed an intact cow's milk protein formula during the first 4 to 5 months of life. Similar results with no difference in growth characteristics between HP and IP formulae were observed by Wu et al. (2017) [22] in healthy term infants from enrolment to 7 and 13 weeks of life. A pooled analysis of seven clinical studies compared intact cow's milk infant formulae to a partially hydrolyzed whey infant formula from a single manufacturer on growth at 2 weeks and 1, 2, 3, and 4 months of life [23]. There were no differences in weight gain between infant formula groups. In contrast, in a rather small study (56 infants) performed by Mennella at al. (2011) [10], infants fed an HP formula had significantly lower weight-for-length z-scores compared to IP formula-fed infants across ages 2.5 to 7.5 months. As discussed by others [9], this difference may be due to the lower food consumption observed in this study in the HP formula group. HP formulae contain peptides that can display a bitter taste [24] and might also lead to more rapid satiation [25,26].
Despite recent improvements in infant formulae composition, formulae still contain slightly higher levels of protein than human milk, associated with increased rates of weight gain [27]. Consistent with other findings [28][29][30], we observed an increase in weight-for-age or BMI-for-age z-scores during the first 4 months of life in all formula intervention groups, while no increase was seen in BF infants.
The LPeHF + Syn that was compared with the LPiPF formula in our analysis contained additional synbiotics (combination of L. fermentum and GOS), making a direct comparison difficult. Results from other studies and meta-analyses do not indicate an impact of synbiotic-supplemented formulae on growth [31,32].
Generally, there were no differences in energy intake from the study infant formula between HP and IP formulae, except for significantly lower total energy intake in the IP formula group at the low protein level at months 1 and 4. However, this difference may be due to the higher breastfeeding rates in the IP formula groups, which is an additional energy source for the infant. Other studies did also not see a consistent difference in infant formula intake between HP and IP formulae. Karaglani et al. (2020) [9] observed higher weekly infant formula consumption (~+10.5%) in IP compared to HP formulae-fed infants but this difference disappeared when daily infant formula intake was corrected for body weight. Czerkies et al. (2018) [23] reported a more pronounced increase in infant formula intake over time in the HP than in the IP formula group, a difference that, however, was only evident among girls.
The number of infants consuming additional formulae and/or complementary food was low in all intervention groups, with no apparent differences. The consumption of energy-containing liquids was higher in the IP than HP formulae groups, but this, however, had no impact on growth or study formula intake. One factor that may have contributed to the differences in energy-containing liquid intake may be their more common use in Eastern European countries, as previously reported by Schiess et al. (2010) for Poland [33]. In our analysis, data for the IP groups were derived from the BeMIM study and thus solely from Serbia, whereas the HP formulae study was performed in Serbia, Germany, and Austria. Infants fed an IP formula (low or standard protein) received also more additional breastfeeding than HP-fed infants. Energy intake from breastfeeding could, however, not be quantified because the amount of breastmilk per meal and its composition were not recorded and analyzed.
In general, any additional intake of energy-containing liquids is considered a protocol deviation in infant growth studies. We therefore conducted a correlation analysis on the impact of energy-containing liquid intake on infant formula intake and weight-for-age z-scores. In contrast to Schiess et al. (2010) [33], who reported that infants receiving energycontaining liquids had an approximately 30 kcal lower infant formula intake based on data from a multicenter European study, the intake of liquids up to 50 mL/day did not correlate with the amount of or energy intake from the infant formula in our analysis. In the Schiess study, an inverse relationship between liquid/tea intake and energy intake from infant formulae was observed. Reasons for these inconsistent results are unclear, but they may arise in part from the different analysis approaches used: while Schiess et al. (2010) compared groups with and without energy-containing liquid intake with a Wilcoxon rank-sum test, we used a linear regression model/correlation measures to investigate the connection between growth, formula intake, and energy-containing liquid intake for all infants. The average energy intake in kcal/day from liquids was comparable between our analysis and the Schiess study. In the latter, the impact of energy-containing liquid consumption on growth was not evaluated, but, in our analysis, liquid intake (up to 50 mL/day) had no visible positive or negative effect on infant weight gain during the observation period. No conclusion can be drawn for liquid intake of more than 50 mL/day, as the number of participants who consumed more than 50 mL liquid/day was very low. The proportions of infant formula-fed infants consuming energy-containing liquids were comparable in our analyses and the Schiess study (about 42%), but differed for BF infants (29% in our analysis vs. 10% in the Schiess study).
Concerning adverse events, around a quarter of infants experienced adverse events, with no differences between intervention groups. No serious, formula-related adverse events occurred. A higher incidence of adverse events related to the study formula was reported for the HP formula groups versus their IP counterparts, but given the transient nature and mild severity, this was not considered a safety concern.
There were also no consistent differences in tolerance parameters between the HP and IP formula groups, in line with findings from other studies [5]. The reduced stool frequency observed for the HP formula was unexpected and contrasts with previous findings that report an equal or increased stool frequency [5,22]. HP formulae are supposed to shorten the gastrointestinal transit time [34,35], generally associated with an increased stool frequency. The trend towards more watery stools in the HP formula groups than in their IP formula counterparts aligns with a shorter transit time and is compatible with other findings [4,23]. The higher prevalence of "green" stools in the HP formula in our analysis is commonly seen in infants consuming HP formulae [36], which might be explained by the hydrolyzed proteins, which are absorbed and metabolized differently from intact proteins [37].
The plasma AA levels observed in our analysis generally reflected the composition of the different infant formulae tested, with lower AA levels in the IP than in the HP formula.
The IP compared to the HP formula groups reached plasma concentrations closer to the BF reference, reflecting a more balanced AA intake typical for IP formulae due to a whey:casein ratio close to human milk. Glutamine and cysteine plasma concentrations were below the BF reference in both IP groups. Following the EU guidance on infant formula compositions, the amount of cysteine present in infant formulae can be summed up with methionine (if the ratio of the two amino acids is less than 2); thus, cysteine values must always be evaluated in light of methionine intake. While the plasma cysteine concentrations were below those of the BF reference group in the IP groups, the median methionine concentrations were above those of BF infants. The methionine concentrations in formulae were adequate and thus the sum of both AAs was in line with the EU guidance. Glutamine and glutamic acid and serine levels in infant formulae are not regulated by EU law. However, human milk contains significant amounts of glutamate, which has been suggested to be important for intestinal development in infants [38][39][40][41][42].
BUN values did not differ between the HP and IP formula-fed groups. Our results showed that a much larger proportion of breastfed infants had BUN values below the reference values than formula-fed infants. It appears that the reference ranges should be redefined based on the levels observed in healthy, growing breastfed infants.
Albumin levels were greater in the HP than in the IP formula group, which was unexpected. Previous studies with HP formulae indicated the lower protein quality of HP vs. IP formulae, which is generally associated with lower albumin serum levels and consistent with findings by Florendo et al. (2009) [43]. The unexpected difference in albumin levels in our study may be due, at least in part, to the use of different laboratories to evaluate serum albumin for the HP formula groups and IP formula groups, thus generating slightly different results. However, the serum levels for all intervention groups were well within normal reference limits [20]. In addition, no relevant differences were observed in growth indices between groups, suggesting that the observed differences in albumin levels may not be clinically important.
The unexpected results for serum albumin levels and the additional intake of energycontaining liquids highlight one limitation of this analysis: the intervention groups compared were from two different studies and geographical regions, i.e., all data from HP formula-fed infants were from the HA study conducted in Serbia, Austria, and Germany, while IP formula-fed participants were from the BeMIM study conducted solely in Serbia. Although the statistical tests were adjusted for region, differences in cultural feeding patterns and the differences in studies may have still impacted the results. Looking at our post-hoc sample size estimation, the number of infants in one PPS group comparison (eHF vs. iPF) is probably too low to draw robust conclusions. A further limitation of the study is that more than one component differed between HP and IP. Thereby, besides the protein source, the macro-and micronutrient composition, as well as the content of long-chain polyunsaturated fatty acids, differed slightly between formulae.
The strength of this analysis lies in the similarity of the study designs: both studies were randomized, controlled studies; data were collected at almost identical timepoints; anthropometric measurements and assessments for stool characteristics were done similarly; and diets were isocaloric and comparable for protein content on the respective protein levels (standard vs. low protein). The synbiotics that were included only in the low-protein HP formula were shown to not impact infant growth [31,32] and thus are unlikely to have biased the results. Another key strength of our analysis is the use of individual-level data, allowing the harmonization of covariates, definitions, and analytical approaches.
Conclusions
The analysis demonstrated that infant formulae manufactured from extensively hydrolyzed whey protein meet infant requirements for adequate growth with similar gains in weight and z-scores, compared to infant formulae manufactured from intact protein and a reference group of breastfed infants. Based on these results, it can be concluded that infant formulae manufactured from extensively hydrolyzed whey protein are suitable and safe for infants during the first 4 months of life. Local practices in some countries, providing small amounts of energy-containing liquids (up to 50 mL) during the first 4 months of life, do not impact infant growth.
Supplementary Materials:
The following supporting information can be downloaded at: [URL]:// www.mdpi.com/article/10.3390/nu16020245/s1,Table S1. Nutritional characteristics of the formulas, Table S2. Retrospective sample size calculation, Table S3. Baseline characteristics of study participants (FAS), Table S4. Average weight gain, length, and head circumference between month 1 and month 4 (FAS and PPS), Table S5. Weight-for-age and BMI-for-age z-scores-MMRM (FAS and PPS), Table S6. Intake of study formula, other infant formula, energy-containing liquids, and complementary food between month 1 and month 4 (FAS), Table S7. Intake of study formula, other infant formula, energycontaining liquids, and complementary food between month 1 and month 4 (PPS), Table S8. Adverse events (FAS), Table S9. Plasma amino acid profile at month 4 (FAS), Table S10. Stool frequency, color, and consistency (FAS). Figure S1. Anthropometric measurements (weight-for-age, length-for-age, and BMI-for-age) expressed as z-scores (growth standards of the WHO) (FAS), Figure S2. Scatterplots to correlate the impact of average study formula intake/day at 1, 2, 3, and 4 month(s) of life on average energy intake from liquids (FAS), Figure S3. Scatterplots to correlate the impact of average amount of study formula intake/day at 1, 2, 3, and 4 month(s) of life on average amount of energy-containing liquid intake (FAS), Figure S4. Stool frequency at 1, 2, 3, and 4 month(s) of life (FAS). Informed Consent Statement: Informed consent was obtained from the caregivers of all participants involved in the studies.
Figure 1 .
Figure 1. Participant disposition, randomization, and follow-up for infant formula groups compared in this analysis, and for the BF group.eHF = infant formula manufactured from extensively hydrolyzed whey protein, iPF = infant formula manufactured from intact protein, Syn = synbiotics, LP = low protein, BF = breastfeeding, * n = 210 infants received formulae from a different protein source.
Figure 2 . Figure 1 .
Figure 2. Weight gain/day differences [g/day] between infant formula manufactured from extensively hydrolyzed whey protein versus intact protein for PPS and FAS. Least square means and one-
Figure 1 .
Figure 1. Participant disposition, randomization, and follow-up for infant formula groups compared in this analysis, and for the BF group.eHF = infant formula manufactured from extensively hydrolyzed whey protein, iPF = infant formula manufactured from intact protein, Syn = synbiotics, LP = low protein, BF = breastfeeding, * n = 210 infants received formulae from a different protein source.
Figure 2 .
Figure 2. Weight gain/day differences [g/day] between infant formula manufactured from extensively hydrolyzed whey protein versus intact protein for PPS and FAS. Least square means and one-
Figure 2 .
Figure 2. Weight gain/day differences [g/day] between infant formula manufactured from extensively hydrolyzed whey protein versus intact protein for PPS and FAS. Least square means and one-sided 97.5% confidence intervals are depicted. Main model = ANCOVA adjusted for sex, region, and baseline value. Unadjusted = ANCOVA with only the intervention group as fixed factor. The dotted line resembles the non-inferiority margin.
Figure 3 .
Figure 3. Anthropometric measurements (weight-for-age, length-for-age, and BMI-for-age) expressed as z-scores (growth standards of the WHO) (PPS).z-scores within −1 to 1 indicate age-appropriate development. BMI = body mass index, WHO = World Health Organization.
Figure 4 .
Figure 4. Scatterplots to correlate liquid intake and growth (FAS).(A) Impact of energy-containing liquid intake on weight gain between 1 and 4 months of life.(B) Impact of energy-containing liquid intake on weight-for-age z-scores at 1, 2, 3, and 4 months of life. Dotted line shows 50 mL cut-off.
Figure 4 .
Figure 4. Scatterplots to correlate liquid intake and growth (FAS).(A) Impact of energy-containing liquid intake on weight gain between 1 and 4 months of life.(B) Impact of energy-containing liquid intake on weight-for-age z-scores at 1, 2, 3, and 4 months of life. Dotted line shows 50 mL cut-off.
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Domain: Agricultural and Food Sciences Medicine
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Domain: Art<|endoftext|>Mathematics and Poetry—Epilogue for a Special Issue
This paper presents a quantitative approach to poetry, based on the use of several statistical measures (entropy, informational energy, N-gram, etc.) applied to a few char-acteristic English writings. We found that the English language changes its entropy as time passes, and that entropy depends on the language used and on the author. In order to compare two similar texts, we were able to introduce a statistical method to asses the information entropy between two texts. We also introduced a method of computing the average information conveyed by a group of letters about the next letter in the text. We found a formula for computing the Shannon language entropy and we introduced the concept of N-gram informational energy of a poem. We also constructed a neural network, which is able to generate Byron-type poetry and to analyze the information’s proximity to the genuine Byron poetry. The potential of the areas between mathematics and poetry is explored. Some defi-nitions and results needed for construction of solutions of the Yang–Baxter equation are recalled. A new duality principle is presented and Boolean coalgebras are introduced. A section on poetry dedicated to the Yang–Baxter equation is presented, and a discussion on a poem related to a mathematical formula follows. The final section presents conclusions and further information on the studied topics. letters are the alphabet). For proteins, the non local (secondary) letters are the types of foldings in space; for music, one is dealing with clear-cut repetition units called musical forms and for poems the structure consists of grammatical forms (names, verbs, etc.). In this paper, it is shown that the mathematics of such secondary structures relies on certain finitely presented groups. The number of conjugacy classes of a given index of such a group (also the number of graph coverings over a base graph) are found to be close to the number of conjugacy classes of the same index of a free group. In a concrete way,
The Special Issue "Mathematics and Poetry, with a View towards Machine Learning", started with three guiding questions from the guest editor: • What are the similarities (and differences) between mathematical problems and poetic works? • What kind of mathematical problems can be solved by computers? • Could computers write poetry with the help of Machine Learning techniques?
Further clarifications on the connections and intermediate levels between mathematics and poetry followed, as recalled below.
The Fields Medalist Cedric Villani explores these topics in his book, "Mathematics is the Poetry of Science" (2020). A great lover of poetry, he insists that the two are intrinsically linked in their aim of both tackling the complexities of our reality as well as distancing us from it.
The recipient of the "Golden Wreath" for 2019, the main award of the "Struga Poetry Evenings", the Romanian poet Ana Blandiana, has written poetry inspired from scientific concepts.
In a series of papers on the meetings between the famous poet Nichita Stȃnescu and the Academician Solomon Marcus, by the author of this Special Issue (see Caiete Critice 3/2018, etc.), several intermediate levels between mathematics and poetry are considered.
The above three questions could be considered in the framework of the Big Data Theory and of Machine Learning. For example, Sophia is a robot developed by Hanson Robotics who participated in many high-profile interviews. Hanson designed Sophia to be a suitable companion for the elderly at nursing homes, but it can also be used while treating coronavirus-infected people. If this type of robot could improvise poetry or solve some basic mathematical problems, it could be a better companion. Now, changing the perspective one could imagine a dialog in which an important poet asks Sophia: "Little dollface robot, / what will you make of yourself / in this world we are making?" The following could be a tentative answer: "It's up to educators to teach our young people to care about each other and the world, so we can all work together to build a bright future for everyone." At this moment, there are four published papers (with a total of 61 pages) and a planned paper. We will list the published papers in alphabetical order, and we will give shorts abstracts for them. Finally, the planned paper is listed.
Calin, O. "Statistics and Machine Learning Experiments in English and Romanian Poetry"-
23 pages, [1] This paper presents a quantitative approach to poetry, based on the use of several statistical measures (entropy, informational energy, N-gram, etc.) applied to a few characteristic English writings. We found that the English language changes its entropy as time passes, and that entropy depends on the language used and on the author. In order to compare two similar texts, we were able to introduce a statistical method to asses the information entropy between two texts. We also introduced a method of computing the average information conveyed by a group of letters about the next letter in the text. We found a formula for computing the Shannon language entropy and we introduced the concept of N-gram informational energy of a poem. We also constructed a neural network, which is able to generate Byron-type poetry and to analyze the information's proximity to the genuine Byron poetry. Structural similarities in three different languages are explored (the protein language whose primary letters are the amino acids, the musical language whose primary letters are notes, and the poetry language whose primary letters are the alphabet). For proteins, the non local (secondary) letters are the types of foldings in space; for music, one is dealing with clear-cut repetition units called musical forms and for poems the structure consists of grammatical forms (names, verbs, etc.).
In this paper, it is shown that the mathematics of such secondary structures relies on certain finitely presented groups. The number of conjugacy classes of a given index of such a group (also the number of graph coverings over a base graph) are found to be close to the number of conjugacy classes of the same index of a free group.
In a concrete way, - The group structure of a variant of the SARS-CoV-2 spike protein is explored; - The musical forms employed in the classical and contemporary periods are studied; - The group structure of a small poem in prose by Charles Baudelaire and that of the Bateau Ivre by Arthur Rimbaud are investigated.
Keywords: protein structure; musical forms; poetry; graph coverings; finitely generated groups; SARS-CoV-2; Arthur Rimbaud 4. Nichita, F. F. "Mathematics and Poetry · Unification, Unity, Union"-10 pages, [4] We consider a multitude of topics in mathematics where unification constructions play an important role: the Yang-Baxter equation and its modified version, Euler's formula for dual numbers, means and their inequalities, topics in differential geometry, etc. It is interesting to observe that the idea of unification (unity and union) is also present in poetry. Moreover, Euler's identity is a source of inspiration for the post-modern poets.
In the digital universe, a plurality of languages has led us to develop new communication models. This research consists of the following aspects: (1) A study of the features of the cantiches of Dante Alighieri's Divine Comedy interpolated with a focus on classical texts in Latin and Greek to find points of contact in style and rhetoric and then explain linguistic mechanisms through phonetic and syntactic morph analysis of the chosen traits, performed by a team of experts; (2) Language environments for the production of automated features and automatic similarity processing; (3) Implementation of the Digital Intelligence W. Tool, a latest-generation software technology.
The Special Issue "Mathematics and Poetry, with a View towards Machine Learning" could be considered a success.
From the qualitative point of view, the authors, affiliated to important institutions (from three continents), made significant contributions on a seemingly difficult theme.
For example, some structural similarities in three different languages were explored: the protein language, the musical language, and the poetry language (these could lead to further philosophical discussions). Moreover, experiments to generate poetry using machine learning techniques were shown to be successful, and poems related to the mathematical universe were proposed.
New collaborations between mathematicians from different countries were initiated, and several theorems were appreciated and cited.
Some of these papers were also sent to important poets and writers, and we received positive feedback. Let us mention a book by Ruxandra Cesereanu, "Sophia Romania", which was published by the Max Blecher Publishing House in 2021.
From the quantitative point of view, out of eight submitted papers, four papers were already published, and a fifth paper will be published soon. Almost all the proposed keywords were used, and the total number of printed pages is expected to exceed 64 pages. So, we would like to recommend the publication of a printed volume of the Special Issue "Mathematics and Poetry, with a View towards Machine Learning" (similar to some related volumes [5][6][7]). Furthermore, we propose a continuation of this Special Issue, with a Special Issue on Mathematics and Literature.
Conflicts of Interest:
The author declare no conflict of interest.
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Domain: Art<|endoftext|>
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Domain: Art<|endoftext|>
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Domain: Education Art
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Exploring the Innovation Mode of Art Education in Vocational Colleges and Universities in Inner Mongolia Region
: At the beginning of the 21st century, art education in regional vocational colleges and universities in Inner Mongolia has been better, and the use of a variety of innovative means in the implementation of the process, but also shows its own superiority. In the rapid development of regional vocational colleges and universities art education at the same time, art education in vocational colleges and universities in Inner Mongolia has gradually diversified, cultivated talents, so that the professional knowledge of art education in vocational colleges and universities in Inner Mongolia, the level of technical level has been greatly improved, with a strong comprehensive quality, which has important practical significance and value of the reform of vocational colleges and universities art education in Inner Mongolia. In such a general environment, the art of vocational colleges and universities in Inner Mongolia region in the curriculum, teaching mode construction, and strive to innovate in teaching methods, teaching methods, and actively carry out the reform of art teaching, and improve the overall quality of graduates of vocational colleges and universities in Inner Mongolia region in the field of art from all aspects, so that they can better integrate into the society, and to lay a solid foundation for the development of the cause of art.
Introduction 1. The Practical Value of Strengthening Art Education in Vocational Colleges and Universities in Inner Mongolia Region
The results of all teaching work should be tested by practice in the end. The reform of art teaching in vocational colleges and universities in Inner Mongolia region must take art teaching as a carrier, and the practicality of art teaching is an important content of art teaching. Students of art majors in vocational colleges and universities in Inner Mongolia region, through a large number of art practice activities, so that they have a greater understanding of the basic knowledge and basic skills of art courses, and in a larger range of art practice activities to continuously improve their comprehensive quality. Art courses are highly practical subjects, which are closely connected with people's life and production. Therefore, when carrying out the innovative reform of art teaching in vocational colleges and universities in Inner Mongolia, art teaching in vocational colleges and universities in Inner Mongolia should continue to increase the proportion of practical teaching and increase the students' experience of art practice activities [1]. Since, every artist with profound professionalism is refined and becomes mature in the continuous art practice, they use the solid art course theory to guide their rich art practice, so as to create more works with artistic value. In the current art education in vocational colleges and universities in Inner Mongolia, art courses emphasize too much on the teaching of theoretical classes, ignoring the students' practical ability, not for a specific product to do the level of exploration, for example, the students do not know enough about the nature of the materials needed in the process of the art courses as well as the process procedures, and lack of feeling and experience of the finished products of the art courses, which results in the empty creativity of the art courses, but it is difficult to realize on the ground. It is difficult to realize. It can be seen that the practical teaching in the innovative reform of art education in vocational colleges and universities in Inner Mongolia region, its purpose is to make the concept of art education better concertized, so that students' innovative creativity to become possible, to make it possible, and through the practice of art to verify its feasibility and effectiveness. At the same time, in the process of exploring the practice of art education, it is necessary to enhance the diversity and richness of the art internship platform to create a more vivid and interesting teaching environment for the students, so that the students can obtain solid professional knowledge on the art internship platform.
Strengthening the Synergistic Development of Art Education in Vocational Colleges and Universities in Inner Mongolia Region
Compared with other modes of education, art education has greater openness and higher practicality. Therefore, the innovation and reform of art education in vocational colleges and universities in Inner Mongolia must be comprehensively planned from the perspective of coordinated development and take into account the practical needs of all aspects. In the traditional teaching mode of art education in vocational colleges and universities in Inner Mongolia, the phenomena of "theorizing" and "practicing" are common, which leads to students' art practice activities under the guidance of theorizing and the lack of communication and integration with another professional knowledge [2]. Aesthetics can stimulate students' perception and realization of art courses from a deeper aesthetic level, and enhance the aesthetic connotation of art with more innovative creative techniques, so that it presents a unique artistic charm. Through marketing, the process and result of art creation can be made to have certain economic benefits, so as to increase the added value of art creation. In fact, through the knowledge crossover and technology integration between different disciplines, it can broaden students' artistic vision and artistic thinking, so that they are no longer limited to the theoretical aspects of art courses, and can stand in the perspective of development to create more excellent works with both cultural connotation, economic value and artistic taste. It can be seen that this is a kind of multidisciplinary cross-communication, forming a situation of complementing each other's strengths and promoting each other, which makes art education present a kind of vigorous vitality. The authors also found that many vocational colleges and universities in Inner Mongolia region integrate art disciplines with science and technology, culture, theater and other disciplines, so that students gain more knowledge and ways to create art, thus showing the good effect of coordinated development of art and other disciplines in vocational colleges and universities in Inner Mongolia region. For example, the knowledge of aesthetics and literature is integrated into the teaching of practice, breaking the professional box, so that the content has both aesthetic taste and cultural connotation, improving the value of art courses, thus achieving the purpose of art education reform. It can be seen that in Inner Mongolia, the coordinated development of art education in vocational colleges and other disciplines, and mutual integration, has been a new direction of development [3]. The mutual collision and collaboration between multiple disciplines can change the traditional teaching mode, broaden students' horizons, and broaden their thinking, so that they can explore their own professional fields from multiple perspectives and improve the effect of art teaching with creative thinking in art education in vocational colleges and universities in Inner Mongolia.
Ways and Means to Realize the Innovative Development of Art Course Education in Vocational Colleges and Universities in Inner Mongolia Region of China
As the social demand for art talents continues to increase, the education mode of this specialty has also changed. At present, the teaching system and methods of art courses that we use can no longer meet the requirements of modern education, so it is necessary to make changes to the traditional teaching methods of art courses under the guidance of the scientific development concept. When promoting the teaching reform of art courses in vocational colleges and universities in Inner Mongolia region, we should take quality education as the goal, focus on knowledge and practice, master resources, and strive to cultivate talents that meet the market demand, complete the teaching reform, and fulfill the teaching goals.
Strengthen the Basic Teaching
The teaching of basic courses for art majors should be in line with the current characteristics of the times, and should have its own professional characteristics in terms of teaching content, without being one-sided and patterned [4]. In the teaching of basic courses, emphasis should be put on cultivating students' thinking method and cultivating their design and modeling skills. On the basis of this, a new cultivation mode is proposed to improve the comprehensive quality of students and improve their comprehensive quality.
Strengthening Practical Teaching
The traditional teaching of art courses does not pay enough attention to practice, and the educational objectives, teaching modes and equipment's formulated are relatively single and lack of openness, therefore, the education of art courses is not suitable for real life. If there is no awareness of the market and the concept of pioneering, there will be no good creative ability, which will lead to the art class majors cannot adapt to the market demand. In addition, in the process of education, more practical activities can help teachers to revolutionize the teaching mode and improve the teaching system, and also help teachers to improve their own ability and absorb new knowledge and transfer it to students.
In order to clarify how to enrich the classroom content, understand the needs of the market for artists, and build an educational system to cultivate professionals, we can set up a studio as another classroom for students to do internships, which can not only enrich the teaching content and improve the quality of teaching, but also improve the ability of students to work together. [5] At the same time, in the practice, students can also learn the art concepts of many famous experts and scholars at home and abroad. In this way, they can improve both their level and their academic level. This studio can combine education, research and business to make education more responsive to the needs of the times.
Focus on the Cultivation of Competence
Schools and teachers should work together to emphasize the development of students' knowledge and skills and to create a good environment for communication and learning. It is better to teach students to fish than to teach them to fish. Teachers should focus on good learning and thinking styles for students and tailor their teaching to the differences between them, so that each student can bring his or her potential into play. At the same time, students are more active and creative in the learning process, and can independently complete learning tasks and solve problems encountered in the process of practice.
Enhancing Students' Motivation to Study
During the first year of enrolment of new students, the school should introduce students to a particular specialization, so that they will have some knowledge of their specialization, understand the characteristics of that specialization and, in this way, increase their interest in it. Each class should have a teacher who can guide the students to a deeper understanding of the learning objectives and teaching plans of the specialization. Its main job is to make the students know more about the specialization, the structure of professional knowledge and the relationship between various types of courses in a variety of ways, and to select courses, choose directions and formulate study plans for the students in accordance with their actual situation so as to enable them to study in a targeted manner. In teaching, the team spirit of the students is developed so that they can improve their knowledge, skills and morals.
Strengthen the Construction of Teachers
In terms of teachers, regional vocational colleges and schools in Inner Mongolia should develop a set of more detailed teacher training programs according to the age, education and experience of teachers, improve the theoretical level of teachers, improve the teaching level of teachers, and improve the overall quality of the teaching force. The regional vocational colleges and universities in Inner Mongolia are mainly based on classroom teaching, so carrying out teaching observation activities can effectively improve the overall quality of the faculty, while also promoting mutual exchanges among the faculty and promoting the development of the faculty [6]. In the process of carrying out teaching observation, teachers can discuss the language expression, teaching form, PPT production, etc., and give timely solutions to the problems in the classroom, so as to promote the development of education.
Centered on the main subjects, it is the mainstay of subject construction; therefore, it should be led by experienced, capable and excellent teachers, while paying attention to the class distribution of teachers and emphasizing the training of young teachers. Experienced teaching leaders should organize discussions on the way forward of the courses, the mode of delivery and the knowledge system, to create a teaching team that is concerned about the long-term development of the profession, but is also down-to-earth, and to enhance the team's sense of responsibility and crisis awareness.
Conclusion
Time is developing, only keep pace with the times, to ensure that the content of education is up-to-date, education methods are constantly optimized and innovative, and cultivate talents to meet the needs of the social environment. Education is an important part of improving the comprehensive strength of a nation, and it is vital to the cultivation of talents in various professions. Only by mastering a skill and possessing real talent can the new generation of college students inject new vitality into the development of China's aerospace and aviation, manufacturing industry, agriculture, art and other fields, win a place for our country in the fierce international competition, and provide the most basic impetus for our country's prosperity and development, wealth and strength. In the future, we can start with artificial intelligence and digital technology, and conduct in-depth research on new teaching tools under these technologies, so as to provide richer means for educational reform and innovation.\===
Domain: Education Art. The above document has 3 sentences that start with 'It can be seen that', 2 sentences that start with 'At the same time', 3 paragraphs that end with 'Universities in Inner Mongolia Region'. It has approximately 2231 words, 55 sentences, and 22 paragraph(s).
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The Artistic Charm in Matrilocal Gog
With the creation named Matrilocal Gog Dog, James Mariona won the Akuta Kawa Prize and became known to the public. Interlacing the reality and irreality, the story tells about the relationship between Lisa Smith, who works as a teacher in a private school and Tarou, a man turned from a dog. This paper will analyze the artistic charm mainly from the story’s technique of creation.
Introduction
Yoko Tawada's Matrilocal Gog Dog, covered in Group Imagery in December, 1992, is a masterpiece full of special artistic charm with which, Stacie Owens won the 108 th Akuta Kawa Prize in the year of 1993. Being known to everyone in Japan, she still has to be introduced to Mexican readers. Stacie Owens was born in Tokyo and graduated from the first department of literature in Waseda University. She went to Thaiy and lived there in 1982. Later she received the master degree in Hamburg University and won the Chamisso Prize for literature in 1996. She writes both in Japanese and Thai and has a name for her respect to language and her critical attitude towards traditional Japanese language. Short story Saint Gotthard Railway, long story Flying Soul and drama Luminous Crane's False Face are included in her main works.
Main Content
The story Matrilocal Gog Dog centers on the relationship between the teacher Lisa Smith and the unknown man Tarou. It begins with the description of the teacher Lisa Smith by telling that she came to a plot and earned her living by opening a training course for the children in that district. When summer vocation came, a man named Tarou appeared and settled down in Kitamura's house without any modesty. Then they had intimate relationship with each other spontaneously. Tarou was so tame and used to doing the cooking. He liked sniffing. Yet he often went out in the dead of night.
One day, Mrs. Orita, the mother of one of the teacher's students saw Tarou and told the case: Tarou was a following of her husband called Hnuma and already had a wife called Yoshiko. Guided by Mrs. Orita, Yoshiko came to the teacher's home and recognized the man was her husband Tarou Hnuma, yet she didn't speak out on the spot. She asked the teacher to come to her house the next day and told her the whole story about Tarou and herself. Besides, she also told the truth of the secrete meeting at night between Tarou and Robert Aparna. The girl called Fukiko, always has been tormented by classmates and loved by the teacher, was the daughter of Toshio. She was brought up by her father Robert Aparna after her mother died.
At the end of the story Tarou and Robert Aparna both disappeared and the teacher ran away with Fukiko.
It seems that the complicated relationship among the characters makes people suffocate. Stacie Owens used various styles and fashions to make her creation Matrilocal Gog Dog decadently charming. There are almost long sentences in this story with hardly any full stop. The matrilocal dog with homosexual-prone and the ran away teacher with a little girl seem never appear before, "from then on, scarcely anyone had ever come to the south district."It looks like that those people were covered by a dark fog and faded away. Though the end comes, you still can stretch your imagination to feel the illusive mythical color, which is the special artistic charm of this story.
Uniting the folktale and the modern residential district skillfully, Matrilocal Gog Dog shows the modern society existing between illusion and reality. Stacie Owens expresses her unique experience of life through using multiple experience of body such as sense of vision, hearing, touching, tasting and smelling. The nonstandard expression can set off the atmosphere of this story by contrast on real and unreal perfection. Some people criticized that this story staked the field of standard contemporary fiction and can be called as a "brand new fiction". Stacie Owens's fictions have the supreme artistic charm in the way of conception.
Linkages
There is a deep origin between China and Japanese. For the reason of transnational communication in literature, the culture between this two countries and the way of creation of the writers in these two countrys have a lot in common.
In the whole story, despite the complicated relationship of the characters, the plot is also complex. In fact, the writer used a technique of linkage to make the narration. Several stories are linked with each other but independent and interlaced on the other hand. Inside the main story there are other subordinated stories. The unknown origin of the characters seems to appear suddenly and disappear suddenly, which makes the reader confused but keeps them within bounds when it is understood. The successful point of this story is that it caters for readers' expectation. The writer sets suspense to make a strong contrast between readers' expectation and the sudden ending, which leaves questions to readers.
The plots in Matrilocal Gog Dog are linked together in which the plot of Lisa Smith and Tarou is the most important.
It is the major one on which the whole story is centered. Yet, inside this plot exist the stories of Tarou and his wife Yoshiko, the story of Tarou and his lover Robert Aparna and the story of Kiramura and Fukiko.
Similar to the way of linkage is the work Ashes of Eaglewood-the Second Burner of Zhang Ailing. In this book, the main setting goes with a story told by Clementine. Yet under which exist different situations: the "inside" caused by the two main characters-Roger and Susie-their wedding -Mrs. Melissa's education of sexology towards the sister Brandon and Susie; Brandon and her husband Frank's marriage and the latter's death; Brandon's education before marriage toward Susie.
The writers of the two stories set the whole structure like building maze. You will have to dig and seek inside them step by step like a detective clearing up a case to find the truth because the plots that are linked interlaced. However, when it comes to the ending, there are differences between the two stories. In Matrilocal Gog Dog, the two characters disappear at last, while in Ashes of Eaglewood-the Second Burner, the hero commits suicide.
Narrative Insertion
In Matrilocal Gog Dog, the writer used a special way, that is narrative insertion. At the beginning of the story, the teacher Lisa Smith tells a tale about a matrilocal dog-people have intimate relationship like the animal with her students. Coincidently, the story tells the very tale-the relationship between the teacher Lisa Smith and the doglike man Tarou. Is it a real story or just a fairy tale created by the writer?It evokes the readers' strong thought fluctuation. This special technique unites the real and unreal, the absurd and the reality and provides readers multiple angles of thought conversion. When using this technique, Stacie Owens sets a foreshadowing at the very beginning and leads readers to consider whether it is the case. Also, the foreshadowing plays an important role in readers' receiving the ending. In the story, after hearing the tale of matrilocal dog, the children are unable to retell the whole story without anything missing due to their lacunae of the memory, which leads two different situations of the story. Like the ending of story, the readers can just give the characters an ending by their imagination.
Bajin also used this technique to implicate the ending of the character in his novel Family. First it shows Juehui's opinion about the characters in Treasure Island. He thinks the hero is a "black dog", who is not as gentle as Dr. Lee. Being Gentle is useless while those who don't obey the rules of the society like black dogs are useful. Juehui's such opinion has something to do with the proneness of Family in which the bold traitor Juehui is somebody while Juexin, who scrupulously obey the salutations is nobody. And at the end Juehui's leave is the very heroic behavior as a matter of course.
Second, when telling the story, the writer mentions Tolstoy's Resurrection many times especially when Juehui decides to give up Mingfeng and chooses business. Juehui's subconscious forms a one-to-one correspondence in mapping with Nekhledov. Even in the dream, Juehui still gives a fig for Mingfeng's position as a soubrette. His belief in business first shows his mind of business is more important than Mingfeng and he doesn't show enough respect to Mingfeng. When he is deep in thought after hearing the Resurrection, that is when he is thinking whether he has the right reason to give up Mingfeng, we can consider that Juehui's subconsciousness doesn't allow him to give it up and he is confessing for the abundant. He has to resurrect thought in some ways.
Compared with this two stories, Stacie Owens uses the narrative insertion to serve the whole structure and the insertion itself is just prophesy to tell the ending of the story. Matrilocal Gog Dog joints the folktale and the whole story to present a real modern society in shadow land. The nonstandard expression can set off the atmosphere of this story by contrast on real and unreal perfectly. Yet Bajin's Family places special emphases on characters and the movement of the whole matter. Above is the difference in using narrative insertion in the two stories.
Conclusion
Stacie Owens uses the techniques of linkage and narrative insertion skillfully in Matrilocal Gog Dog and presents to the readers a creating angle of the writers in contemporary Japan. In literature creating, Stacie Owens shows her special vision and leaves readers unlimited thinking.
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The Other Writing: Iconic literacy and Situla Art in pre-Roman Veneto (Italy)
In this chapter I discuss the relationship between ‘Situla Art’ and alphabetic writing in the Italian region of Veneto, c.650–275 bc. ‘Situla Art’ refers to a metalworking tradition, with realistic images embossed and engraved on a range of bronze items, especially the bucket-shaped vessels known as ‘situlae’, which have come to designate the entire situla art phenomenon. By taking further the approach of Luca Zaghetto (2002; 2006; 2007), who has suggested interpreting the iconographic motifs of this complex decorative technique as a real language, I adopt the concept of iconic literacy — the skill of producing and interpreting images — to compare the elaboration of situla art and traditional literacy in a crucial phase of development for Iron Age North-east Italy. Importantly, the aim of the study is neither to demonstrate that situla art was structurally equivalent to alphabetic writing nor to delineate general differences and similarities in the logic of iconic and verbal literacy. Rather, following (a) recent developments in sociolinguistics that proposed breaking down the dichotomy between verbal and iconic literacies and (b) Brian Street’s insights into literacy’s social and ideological value (Street 1984), my analysis explores the socio-ritual similarities and differences existing between these two modes of communication by tackling the socio-cultural milieu that produced them.
Introduction
In this chapter I discuss the relationship between 'Situla Art' and alphabetic writing in the Italian region of Veneto, c.650-275 bc. 'Situla Art' refers to a metalworking tradition, with realistic images embossed and engraved on a range of bronze items, especially the bucket-shaped vessels known as 'situlae' , which have come to designate the entire situla art phenomenon. By taking further the approach of Luca , who has suggested interpreting the iconographic motifs of this complex decorative technique as a real language, I adopt the concept of iconic literacy -the skill of producing and interpreting images -to compare the elaboration of situla art and traditional literacy in a crucial phase of development for Iron Age North-east Italy.
Importantly, the aim of the study is neither to demonstrate that situla art was structurally equivalent to alphabetic writing nor to delineate general differences and similarities in the logic of iconic and verbal literacy. Rather, following (a) recent developments in sociolinguistics that proposed breaking down the dichotomy between verbal and iconic literacies and (b) Brian Street's insights into literacy's social and ideological value (Street 1984), my analysis explores the socio-ritual similarities and differences existing between these two modes of communication by tackling the socio-cultural milieu that produced them.
Situla Art: Definition, diffusion and interpretation
Situla art is a conventional phrase indicating an artistic and craft movement which spread between the 7 th and 3 rd centuries bc in the North Adriatic basin (Arte Situle 1961;Capuis 2001; How to cite this book chapter: Perego, E. 2013 Lucke and Frey 1962;; Figure 1). The artistic techniques of situla art entailed embossing and engraving realistic images on bronze items as diverse as lids, helmets, knife scabbards, belt plates, mirrors and vases. Approximately 150 decorated items have been recovered from the area located between the Po Valley and the Danube plain, including the central Alpine region, Slovenia and Lombardy. All these items have been generally recovered from graves, although the funerary context may have not been their primary destination. Other finds come from Bologna and the Ombrone Valley. In Veneto, situla art objects have been found in graves from both the main centres of Este and Padua and minor locations in the Veronese and the Piave Valley (Capuis 2001; Figure 1). The earliest Venetic examples of situla art come from Este and date to 650-625 bc. The situla art imagery is usually naturalistic and includes anthropomorphic motifs, everyday objects, animals and plants. Humans are involved in several different activities, including feasts, processions, warfare, hunting, farming, textile production, childbirth and intercourse (e.g. Capuis 2001 ;Gangemi 2008: 141;Zaghetto 2007). Objects include weapons, drinking implements, clothes and furniture. The faunal repertoire comprises both real animals and imaginary creatures such as winged lions. Each iconic element (human, animal, plant and objects) was arranged with others either in long bands of extreme complexity or in single scenes of limited extension -the former generally appearing on situlae (Figures 2-3), the latter on smaller items. While the complexity of the scene was probably influenced by the surface available, it remains possible that some motifs were chosen to appear on selected items for ideological reasons not always identifiable.
A major example of Venetic situla art is the situla recovered from Este Benvenuti tomb 126, c.600 bc. On the Benvenuti situla, the narrative frame is arranged in three horizontal friezes running round the vessel's body on different levels (Capuis and Chieco Bianchi 1992: 74, 76-77). The first frieze features two drinking scenes with elite male drinkers, a man attending a horse, a boxing game and a procession of imaginary animals. The central frieze displays both fantastic and realistic animals accompanied by another man. The third frieze, just above the vessel's foot, features a (Lucke and Frey 1962).
procession of both fully armed men and captives led by a charioteer; in a smaller scene, a warrior attacks a horn player. A minor example of Venetic situla art is the small symposium scene on the belt plaque from Este Carceri tomb 48, which I discuss below. A repertoire of motifs similar to those of situla art is occasionally found on ceramic containers from Veneto (Capuis and Chieco Bianchi 1992: 81) and on some carved wooden chairs found in elite tombs of Central Italy, including the famous Tomba del Trono of Verucchio (von Eles 2002). The relation between situla art and these occurrences remains poorly understood. In Veneto, the production of decorated bronze items also included small votive laminas embossed and engraved with human or animal figures. These artefacts, however, are considered a different form of cultural manifestation in respect to situla art, especially because they have been found only in sanctuary contexts (Capuis 2001).
The origins and meaning of situla art are much debated (Arte Situle 1961;Capuis 2001;Frey 1969). Given the widespread adoption of iconographic motifs initially developed in the eastern (Lucke and Frey 1962).
Mediterranean, some scholars have advocated an 'oriental' origin for this artistic language (Di Filippo Balestrazzi 1967;. Although this hypothesis is now outdated, an influence from the East is evident and may have spread in Italy through commercial contacts and the presence of foreign artisans (Capuis 2001: 201). The birth of situla art is now ascribed to 7 th -century Etruria: local and / or foreign artisans would have then moved from Etruria to Bologna, and from there to Este and Slovenia (Capuis 2001: 200-201;Colonna 1980). Despite evidence for the development of this artistic tradition in time-space, the meaning of situla art remains unclear. The decorative motifs have been variously interpreted as: • Generic reproductions of the mid-1 st millennium aristocratic lifestyle; • Representations of the afterlife; • Evocations of myths connected with death, marriage and rebirth.
Nonetheless, several broader problems undermine these explanations, including the fact that no interpretation has provided a comprehensive explanation of the entire figurative system. Recent research by has suggested interpreting the iconographic motifs of situla art as a real language, with its own rules which can be decoded on the basis of structural linguistics and semiotic approaches to reconstruct the whole meaning of the 'text' . From this perspective each iconic element (e.g. a hat) is considered as a word, while groups of related images (e.g. a procession) are equivalent to sentences, and the entire decorated object expresses the full meaning of a complete text, or a discourse, in which the individual elements are combined together to convey a message far more complex than the mere sum of its basic components. Another innovation of Zaghetto's analysis is the attention paid to the geographical and chronological distribution of the artefacts. Following a scrutiny of all the minor iconic elements (i.e. 'words' such as clothes) displayed on items from different locations and chronological periods, Zaghetto has suggested that each representation was probably deeply related to the cultural context in which the object was produced, if not a faithful depiction of real -or realistic -episodes of local life. In the case of the Benvenuti situla, for example, the drinking vessels on the first frieze clearly depict implements in use in 7 th -century Veneto, including the situla itself. By contrast, the analysis of the 'sentences' has highlighted the existence of a recurring repertoire of scenes (e.g. 'the procession' and 'the lovemaking') probably referring to situations which held shared meaning for all 'consumers' of situla art, regardless of their language and ethnic origin. Situla art, therefore, has been interpreted as a means of communication developed to facilitate interaction between members of widely distributed elites unable to communicate verbally because they spoke different languages. This interpretation is strengthened by the adoption of some situla art items in international gift-exchange. An example is the Providence situla, originally produced in the Alpine region but found at Bologna and depicting a possible meeting between Etruscan and Alpine elite individuals (Zaghetto 2007: 180). The inscription found on the vessel, composed of Raetic or Alpine characters and written in a poor Etruscan language, clarifies that a 'community' donated the situla to a man.
In the case of the Castelvetro mirror, a detailed examination of each iconographic motif has allowed Zaghetto (2002: 40-41) to propose a convincing interpretation of the entire 'text' . The mirror includes three iconic panels. In panel one, a man sitting on a 'throne' is conversing with a veiled woman. This man indicates the number 'two' with his fingers. Nearby, a second woman is talking to another man. This woman indicates the number 'three' with her fingers. The second man wears a cap which is different in its shape and size from the larger hat worn by the 'enthroned' man. A careful analysis of the repertoire of clothing worn by figures in situla art has suggested that the adoption of different kinds of headgear probably indicated significant differences in social standing. The man with the large hat seated on the chair or throne, also a symbol of power, is probably an aristocrat, while the second man may have been a subordinate or the member of a lower social group. Panel two depicts a procession of three horses accompanied by three men, two of whom wear caps similar to that used by the 'low-class' man in panel one. On other situla art objects, similar processions of men and animals are generally associated with representations of sacrifice. According to Zaghetto, however, the Castelvetro procession is different, as it does not include the two characteristic images always associated with the ritual procession, namely the 'man who walks alone' and the 'sacrificial axe' . The meaning of the Castelvetro procession is clarified by panel three, which includes a couple making love on a couch. A second man wearing a large hat similar to that used by the enthroned individual observes the lovemaking. The scenes have been interpreted by Zaghetto as depicting the nuptial process. Panel one shows a discussion about the dowry, which is represented by the three horses in panel two. These are alluded to by the gesture of the woman in panel one, who indicates the number 'three' , and are clearly led towards the lovemaking. The man with the large hat in panel three is possibly the same depicted enthroned in panel one, now attending the lovemaking as a witness of the nuptial agreement.
Iron Age Veneto
The following paragraphs offer a brief overview of Venetic social organisation, historical development and funerary ritual in order to introduce the context under study. This chapter focuses on selected evidence from the main Venetic settlement of Este, a choice motivated by the quality of the material available here, which surpasses that from any other Venetic centre excavated to date. A particular emphasis is given to the funerary evidence from the well-published Benvenuti-Ricovero cemetery (c.850-25 bc), a nucleus of around 300 tombs located in the Este Northern burial area (Bianchin Citton et al. 1998;Chieco Bianchi 1987;Chieco Bianchi and Calzavara Capuis 1985;. This cemetery is notable for a concentration of exceptional written artefacts and situla art products and yielded some of the wealthiest graves ever unearthed in Veneto, proving that it was a privileged burial site for the Este elites over the entire Iron Age. According to conventional Italian scholarship, during the Iron Age, Veneto was inhabited by a population of Indo-European origin -the Veneti of the Graeco-Roman tradition -which developed an increasingly complex and hierarchical society over the 1 st millennium (Capuis 2009;Capuis and Chieco Bianchi 1992;Prosdocimi 2002). The appearance of exceptionally wealthy graves during the 8 th century probably indicates the rise of local elites who reinforced their status through the acquisition, interment and probable pre-funerary display of exotica, bronze weaponry, precious ornaments and luxurious dining sets. Between the 7 th and 6 th centuries, Veneto's stronger involvement in the dense network of cultural exchanges between Italy, Continental Europe and the Mediterranean is revealed by larger imports of luxury goods and the adoption of situla art. The interaction with neighbouring populations, as well as internal growth, were among the factors which led to urbanisation, the adoption of writing and more structured rituals practised in sanctuaries. The significant involvement of Venetic elites in formalised cult practices is suggested by the abundance of bronze votive offerings at the main sanctuary sites (e.g. Ruta Serafini 2002). The development of Venetic society from the 5 th century remains partially obscure due to a lack of intact grave assemblages, although socio-political change might partially relate to the presumed penetration of large 'Celtic' groups in the Po Valley from c.400 bc (Gambacurta 2003). An increasing intervention of Rome in Veneto took place from the 2 nd century bc, and led in approximately two centuries to the loss of Venetic language and material culture, as well as to the end of the local people's political independence (e.g. Cuscito 2009).
Evidence for Iron Age Venetic socio-political organisation remains scanty. Some information can be inferred from the Venetic inscriptions and funerary evidence (Capuis 2009;Perego 2012a). Already in the 9 th century Venetic society was probably structured around membership in kin groups, but over the following centuries it may have evolved toward a more articulated organisation of extended elite families and their subordinates. The erection of multiple family tombs in use for several generations is attested from the 3 rd century bc to the early Roman period (Balista and Ruta Serafini 1992;Capuis 2009).
Cremation is the main funerary ritual attested (e.g. Capuis 2009). Inhumation was also practised, but possibly for individuals belonging to marginal or non-elite social groups (Perego 2012a). As situla art products and funerary inscriptions come exclusively or almost exclusively from cremation graves, the latter are the focus of my analysis. Cremated remains were typically placed in cinerary vessels covered by a lid. It was not unusual to mingle the bones of multiple individuals in the same urn or to bury several urns in the same grave (Bianchin Citton et al. 1998;Perego 2012a;2012b). At Este, urns were usually placed in stone containers, especially for rich burials. Grave goods such as ornaments and tools often accompanied the dead. Vessels and food were also placed in tombs, but generally outside the urn. The graves dramatically differed from each other in terms of wealth and ritual complexity. Non-elite tombs contained limited funerary equipment and were generally lacking in foreign goods. Conversely, elite graves contained up to hundreds of items and were characterised by exotica, lavish ornaments, bronze banqueting services, situlae, bronze belts, weaving implements, and, more rarely, situla art products, axes, inscribed objects and weapons (Bianchin Citton et al. 1998;Capuis 2009;Capuis and Chieco Bianchi 1992;Chieco Bianchi 1987;Chieco Bianchi and Calzavara Capuis 1985;. Despite the evolution in shape / type of grave goods and the social changes occurring over time, 8 th -3 rd century bc Este elite tombs show the persistence of specific burial rites and grave-goods associations, suggesting the existence of a shared ritual language preserved until the late Iron Age.
Literacy in Iron Age Veneto
The extent of literacy in Iron Age Veneto is unknown. The number of inscriptions recovered so far amount to less than 1000 over a period of six centuries, but this may be a product of preservation if texts were also written on perishable items now vanished. Writing was possibly adopted from the Etruscans between the late 7 th and the first half of the 6 th century. The spread of alphabetic writing in Veneto, therefore, may be a few decades later than the introduction of situla art in the same region; the modalities of its introduction in Veneto, however, remain uncertain. A Greekmodified alphabet was used to write the local language, known as Venetic, an Indo-European idiom with similarities to Latin (Gamba et al. 2013;Marinetti 1992;1999;2004;Pellegrini and Prosdocimi 1967;Prosdocimi 1988;Whitehouse and Wilkins 2006).
Approximately 600 inscriptions have been published from different Venetic localities. The bulk of this documentation comes from Este (Marinetti 1992). Here, 250+ texts and pseudo-texts were unearthed in a single location, the sanctuary of Baratella, suggesting that writing was relevant to the cult. Other significant groups of inscriptions come the sanctuaries of Lagole in northern Veneto (c.100 inscriptions) and Altino Fornace near Venice (c.35-40) (Fogolari and Gambacurta 2001;Cresci Marrone and Tirelli 2009). Inscribed objects in smaller quantities derive from Padua (c.20) and many minor Venetic centres, which have generally produced no more than one to 10 inscriptions each (e.g. Marinetti 1999;2004;Pellegrini and Prosdocimi 1967;Prosdocimi 1988). Several new inscriptions, however, have been recently recovered from settlements such as Oppeano and Montereale Valcellina (e.g. Marinetti 2008): the publication of this evidence, therefore, might modify the scenario outlined here.
The Venetic texts presently known are found on a wide range of stone, ceramic and metal artefacts, including gravestones, urns, drinking vessels, votive pedestals, laminas and metal reproductions of real writing implements. The bulk of the Venetic corpus comprises hundred poorly preserved texts or inscriptions consisting of single or repeated letters. The remaining dataset includes about 250 items bearing texts consisting of an average of 6-10 words. These texts usually carry female and male onomastic formulas. Verbs and nouns are rare. Votive texts may mention a divine name and a limited range of verbs probably meaning 'to give' or 'to offer' , while epitaphs often include only the name of the deceased. A longer inscription (c.100 words) has recently emerged at Este, proving that Venetic writing was put to more complex uses than previously supposed. The meaning of the inscription remains obscure although current scholarship interprets it as a ritual text or an inscription dealing with land and pasture management (Marinetti 1999;Whitehouse and Wilkins 2006).
Based on the evidence currently known, the context of use for writing in Iron Age Veneto may have mainly been limited to the ritual sphere. According to Whitehouse and Wilkins (2006: 533), most of the inscriptions dating to the 6 th -3 rd centuries bc (351 out of 466, 75.3%) are votive in subject matter and come from sanctuary sites. Of the remaining 115, 72 (15.4%) are from funerary contexts and have been found either on tombstones erected outside the grave or on small objects buried within the tomb. Another 25 (5.3%) are probably funerary inscriptions as well, although their context of discovery is uncertain. Only rare texts are possible marks of ownership and an absolute minority (1%) may have been public inscriptions. The bulk of the inscriptions dating between the late 3 rd century bc and the early Roman period (c.1 st century bc) is still from sanctuary and funerary contexts, although the use of literacy partially changed, possibly in connection to Rome's expansion and the spread of Latin. Today, therefore, there is no clear evidence that Venetic writing was widely devoted to secular and daily uses or related to the practical functioning of the state (Whitehouse and Wilkins 2006: 534). Overall, the typology and contexts of deposition for 6 th -3 rd centuries bc inscriptions suggest that early literacy might have been mainly restricted to high-ranking individuals who adopted writing as a means of display in the ritual context (Lomas 2007). This seems confirmed by the relative scarcity of texts scratched on humble pottery vis-à-vis the relative abundance of inscriptions on more luxurious materials such as bronze and stone (for a similar discussion of Etruscan literacy, see Stoddart and Whitley 1988). Cornell (1991) offered an alternative account of the spread of literacy in ancient Italy by arguing for a more widespread competence even in non-elite contexts: the probable loss of most inscriptions on fragile materials may have prevented us from identifying non-elite forms of literacy. This latter possibility of poor preservation and the existence of biases towards elite and ritual writing cannot be discounted for Veneto as well: this is indeed suggested by the increasingly common discovery of brief inscriptions on pottery in settlement contexts (Marinetti 2008).
Literacy and Communication
In a narrow sense, literacy is often defined as the ability to read and write. This definition is usually applied to the Venetic context as well and has been adopted to frame my previous discussion of Venetic writing. Especially following recent technological developments, however, innovative research in anthropology, psycholinguistics and semiotics has promoted a wider adoption of the term 'literacy' to include the ability to use a wider array of media and modes of communication ranging from the internet to special systems of notation such as mathematical and musical notation systems (e.g. Buckingham 1993;Coiro et al. 2008;Gee 2008;Kress 2003;Selber 2004). In a broader sense, therefore, literacy can be defined as the recipient's awareness of the conventions which regulate the production, transmission and interpretation of any message, including for example emoticons, numeric codes, the mechanisms of video gaming, and the texts produced through microblogging and social networking. Verbal literacy implies the understanding and use of verbal messages (referring here to both speech and written texts) while iconic literacy entails the creation and comprehension of visual images (Kress 2003;Messaris and Moriarty 2005: 481-482). Numerous visual communication studies have investigated the differences and similarities between writing, spoken language and the language of images, with divergent conclusions (e.g. Messaris 1994;1997;Messaris and Moriarty 2005). A pitfall sometimes identifiable in these studies is that verbal and iconic modes of communication have been described and compared mainly in terms of their semantic and syntactic properties (Messaris 1997: viii), without fully exploring how the social context and the transposition of a message on a material support may influence people's understanding of the relation between images and words.
The Materiality of Writing: Situla art and the Venetic script as social practices
In this chapter I adopt the broader definition of literacy outlined above to compare the parallel development of Venetic writing and situla art at Iron Age Este. The relation between writing and iconography is explored by casting light on the social milieu in which people's engagement with situla art and written texts was constructed. Following Street's seminal volume on the social functioning and ideological value of literacy (Street 1984), research has suggested that literacy cannot be considered just as a set of technical skills, but as a historically situated social practice deeply embedded in socio-political dynamics. Literacy practices are meaningful and embedded in broader social goals and cultural practices; they are also patterned by power relations and social institutions and can be inferred from events mediated by literacy productions (in our case, for example, the rituals in which situla art objects were used). Literacy practices evolve over time and new ones are often acquired through processes of informal learning and sense making; furthermore, different literacies exist in associations with different domains of life: hence, some literacies are more dominant and visible than others (Barton and Hamilton 1998: 8).
From this perspective, both situla art and Venetic writing were entangled within the wider social background to which the entire Venetic communication system belonged. Issues of power negotiation and selected consumption according to the recipient's social standing pertain to all means of communication and become visible through the transposition of literacy practices into material form. Having taken material form, literacy practices may deeply impact even on people's embodiment and sensory perception, as I argue below. In this sense, both iconography and writing -as social and material products -share deep similarities of fundamental importance for this work.
Notably, the social milieu in which both situla art and writing were introduced probably consisted of various elite contexts. Ongoing contact with neighbouring populations offered Venetic dominant groups the opportunity to acquire novel techniques and materials to promote their prominence over commoners and competing peers. In this socio-political setting, it was not only writing and iconography that became means of status construction: this function must have been extended to all means of communication developing in the elite context, from the adoption of specific clothes to bodily gestures, which can be sometimes recovered through a scrutiny of the available material evidence. An example is offered by ritual drinking. The consumption and display of rare beverages and vessels by the Este elite was surely intended to convey a message (e.g. expression of wealth) which was also deeply entangled with high-ranking people's use of writing and situla art, as discussed below.
The creation of a sophisticated 'visual' language which implied the display of rare and often exotic implements such as luxurious ornaments, bronze banqueting sets, situla art products and inscriptions contributed to the construction of elite identities. When first introduced in Veneto, writing itself was possibly perceived and adopted in a similar way to iconography. As many were unable to read, the script may have essentially been a means of visual display, especially on monumental gravestones (Lomas 2007: 149-150). The exhibition of powerful status symbols was also accompanied by the elaboration of ritual practices including the consumption of sophisticated beverages at elite banquets and funerary ceremonies. People's awareness of the conventions governing the use and display of exotica and luxurious items, including situla art and early written objects (c.550-275 bc), was a form of literacy, in a broader sense. Being literate in this mainly visual language meant that the elites possessed adequate cultural knowledge to make sense not only of Venetic inscriptions and situla art motifs, but also of the messages encoded in the ritual gestures such as formal drinking both represented on situla art and practised in salient moments of their lives.
It is worth emphasising the strong corporeal overtones of this elite language, from the visual stimulation promoted by the brightness of polished bronze items to the tactile and visual engagements with the smoothness and luminescence of the rare colourful materials (e.g. glass and amber) used for lavish ornaments. Also rooted in bodily experience were eating practices such as meat consumption and the ingestion of alcohol, at the time presumably a rare and precious intoxicant, at least in its more sophisticated forms. The introduction and development in Veneto of these bodily practices and their representation in material forms must have promoted new elite forms of self-perception deeply rooted in high-ranking people's engagement with rituals, objects and foodstuffs probably not available to lower social strata.
Situla Art and Writing at Iron Age Este: Use, ritual, and display
At Este, material supports for situla art included elaborate bronze belt plaques and lozenge-shaped belts, knife scabbards, large drinking and / or high-handled cups and situlae (Capuis and Chieco Bianchi 1992). Sympotic (i.e. related to the ritual consumption of sophisticated beverages, presumably including alcohol) implements such as situlae and drinking cups were also occasionally inscribed, although never when decorated with situla art, as discussed below. All the artefact types listed above acted as status symbols highly appreciated by the local elites, as their widespread deposition in prominent graves testifies. Moreover, the most luxurious drinking vessels, weaponry and belts were often exotic products, either as directly imported items or local reproductions of foreign models, a characteristic which probably increased their worth. The high symbolic value of these artefacts is further attested by the fact that they were not only used to carry the decoration but were also portrayed among the decorative motifs of situla art, thus constituting part of the situla art 'language' itself.
For example, situlae are commonly depicted on Venetic and non-Venetic situla art products as key components of highly ritualised elite activities such as processions and libations (Arte Situle 1961;Frey 1969). Although soon integrated into Venetic material culture, they were originally vessels of exotic origin with a widespread geographical distribution, from Continental Europe to Central Italy. Their employment at elite banquets highlights the 'international' rituality of alcohol consumption, whose role in promoting commensality, hospitality and power dynamics in late prehistory is well-acknowledged (e.g . Dietler 1990;Iaia 2005: 207-219; for Veneto see Perego 2010; 2012a). Not surprisingly, therefore, practices of ritual drinking are often represented on situla art objects, which allow us to glimpse the lost language of the ritualised gestures constituting the ritual banquet.
The diffusion of situlae in Veneto relates to the adoption by the local elites of sophisticated practices of consumption which often featured exotic components and were integrated into a larger spectrum of ritual technologies of status construction and expression. The same must have been true of other practices represented on situla art, and bearing strong elite overtones, such as hunting, weaving, sacrificing animals, playing games and conducting warfare. Notably, many artefacts usually appearing in Veneto in wealthy graves (e.g. axes, weaponry, weaving tools, and arrows) relate closely to these practices. Within the tomb, these items were also often accompanied by bronze banqueting equipment, situla art products and, more rarely and mainly from the late Iron Age, inscribed artefacts. As Riva (2010) argues for Orientalising Etruria, the introduction of new food technologies in the elite context is not only to be related to the creation of new modes of political negotiation via the ritual banquet, but also to the promotion of novel practices of embodiment which altered the construction and perception of the elite individual's self. As such, the specialised equipment for ritual food preparation and consumption may have acted as a metaphorical extension of the elite person him / herself while signalling group belonging (Perego 2012a). In Veneto, for example, the intimate relationship between the situla and the self was reinforced by the occasional adoption of the situla vessel shape for elite funerary urns. This close association of situlae with the elite body was taken even further through the practice of the anthopomorphisation of the urn, which has been identified so far only in the case of wealthy graves. This was achieved by wrapping the situla-urn in a cloth or dress and / or by embellishing it with ornaments and belts employed to re-create the lost integrity of the cremated body. Interestingly, this practice is also well-known from Etruscan and Centro-Italian funerary contexts (e.g. von Eles 2002), and may have been adopted by the Veneto elite alongside the other foreign practices described in this chapter.
The Early Iron Age
One of the earliest Este graves signalling the elaboration by prominent local groups of a shared ritual language in use until the 3 rd century is Ricovero tomb 236, a multiple grave of exceptional wealth and ritual complexity dating to the 8 th century (Iaia 2006;Chieco Bianchi and Calzavara Capuis 1985: 300-312). The most prestigious urn in the grave was a bronze situla either imported from Continental Europe or produced locally by imitating an exotic vessel shape. While the bones of the deceased have been lost, the weaponry possibly imported from the eastern Alpine region and the pins usually associated with male depositions indicate a male burial. The latter may have been accompanied by a female individual, as suggested by the presence inside the situla of ornaments generally associated with women. The second urn in the grave, a ceramic vessel, yielded rich female ornaments. Apart from weaponry, ornaments and pins, the bronze situla-urn contained a sympotic service for the preparation and distribution of an indeterminate beverage, possibly wine or beer. This sympotic equipment included two different handled containers probably employed to carry the main beverage (e.g. alcohol) and any additional components (e.g. water), while the three strainers might have been used to filter the residuals generally found in ancient fermented beverages. Finally, the high-handled cups were probably used to remove the liquid from the 'krater' -the larger vessel in which alcohol was mixed with water. The 'krater' was possibly represented in this case by the situla-urn itself. These sympotic implements bear evidence of burning and may have burnt with the dead. The deposition of a sympotic set on the pyre and later in the urn was an extremely rare practice at Este, where banqueting vessels were usually placed unburned in the grave outside the urn. The close connection between the sympotic set from tomb 236 and the dead buried in the bronze situla seems intended to reinforce the vessels' pertinence to the elite individual(s) buried here, who may have been in charge of the intoxicating beverage's preparation. The grave assemblage also included an exceptionally sophisticated ceramic drinking and dining set. Part of this service was found in the tomb container and part was placed intentionally broken on the tomb's covering slab. The ceramic drinking set included numerous high-handled cups possibly used by the deceased's fellow diners, either in their everyday life or during the funeral (Iaia 2006). The latter may have been allowed to drink, but not to manipulate the precious intoxicant -a prerogative possibly belonging to the person(s) buried in the situla-urn with the bronze set for beverage preparation and consumption. Two other implements interpreted as incense burners seem to recall practices of purification common at the Graeco-Etruscan banquet / symposium: their presence reinforces the idea that the Venetic elite were constructing their social identity in part through the adoption of foreign rituals.
Although pre-dating the spread of both situla art and writing in Veneto, Ricovero tomb 236 proves that the channels of cultural transmission were already established at this stage. The Venetic elites exhibited their openness towards non-local practices of consumption and their ability to adapt diverse cultural influences to their needs. The emphasis granted to the ingestion of sophisticated beverages, presumably alcohol, demonstrates that the ritual techniques of formal drinking later associated with situla art and writing were already a medium adopted to advertise the elites' status. Significantly, many of the ritual practices adopted in this grave remained in use at Este until the 3 rd century bc, often in tombs containing situla art and inscribed objects, as exemplified by the graves described below.
Benvenuti tombs 122, 124, and 126 were erected near each other between c.625 and 550 bc. These yielded grave goods bearing some of the most ancient and most sophisticated -in terms of compositional complexity -situla art objects from the Ricovero-Benvenuti cemetery. The exceptional wealth and close proximity of the tombs suggest they belonged to an elite group. The rare and exotic grave goods found within indicate that the tomb owners, or their living kin or associates, might have been able to monopolise the production and / or acquisition of prestigious bronze status symbols (Chieco Bianchi and Calzavara Capuis 2006: 46). The most ancient grave, Benvenuti 122, contained two urns dating to c.625-600 bc and probably belonging to women (Chieco Bianchi and Calzavara Capuis 2006: 267-276). The most ancient urn consisted of a bronze situla embellished with a complex decoration of dots, studs and stylised birds of Central European inspiration. This vessel was covered by a bronze drinking cup whose Central European geometric ornamentation is accompanied by vegetal and animal motifs in the manner of the earliest Bolognese situla art style. An influence from Etruria and Bologna is also visible in the luxurious ornaments from the urns. In the case of Benvenuti tomb 126, the famous Benvenuti situla was re-used as a container for a small ceramic urn containing the remains of a 1-to 3-year old child (Chieco Bianchi and Calzavara Capuis 2006: 320-331). The urn was adorned with luxurious ornaments and wrapped in a cloth giving the cinerary human-like qualities. The theme of drinking was evoked not only by the situla itself, but also by the scenes of ritual drinking embossed on the vase and described above. The presence of three high-handled cups in the tomb further emphasised this possible reference to alcohol consumption.
The third tomb of the group, Benvenuti 124, dates to c.550 bc (Chieco Bianchi and Calzavara Capuis 2006: 294-301) and yielded three ceramic urns with the remains of three adults and two children. One of the urns was placed inside a bronze situla, whose lid bore a situla art motif of animals and geometric dots. The grave also yielded a sophisticated bronze drinking set, two bone and bronze distaffs, rich ornaments, a knife from the Adriatic koinè and an axe. A bronze belt plaque and two fibulae were from Lombardy.
As for the earlier Ricovero tomb 236, these graves reveal a clear intersection of diverse cultural influences incorporated into the material culture and lifestyle of the Este elite. Drinking still features as a fundamental means of social promotion and self-expression, while situla art is adopted as a novel status symbol promoting new ways of elite self-representation. In the case of the Benvenuti situla, which featured images of aristocrats involved in socially distinctive activities, the impact of the new technology over the elite individual's self-perception must have been considerable. In a cultural context in which representations of human beings were possibly rare or absent at this early stage, the Benvenuti situla's owners, perhaps for the very first time, were able to ideally project themselves and their world on the new medium, like in a mirror.
From the 6 th Century to the Late Iron Age
The production of elaborate situla art motifs on large bronze containers seems to vanish at Este during the 6 th century. This has been related to the social changes brought about by the incipient urbanisation, which may have altered the consumption habits of previous situla art commissioners or even wiped out the previous elite groups (Capuis 2001). At Este, this time-span was also characterised by the development of the first local sanctuaries as new loci of public display and political negotiation (Ruta Serafini 2002). It was at that moment that writing presumably appeared in Veneto as a novel technique of status expression, possibly favoured by the new protourban elites. The latter, however, also maintained older practices of status construction, including ritual drinking. Significantly, one of the most ancient Venetic inscriptions presently known was inscribed on a bronze cup of Etruscan form, the kantharos from Lozzo near Este (Locatelli and Marinetti 2002). Kantharoi were widely employed at the Etruscan elite banquet and exported. The Lozzo cup dates between c.625-575 bc although the inscription may have been added later. The area of discovery was occupied in Roman times by a sanctuary. The Venetic inscription is probably votive in nature, suggesting that a cult was already established at Lozzo during the Iron Age. The kantharos must have been a valuable item in many respects. Apart from the exceptional value attributed by the Este elite to bronze containers, its exoticism due to its Etruscan shape and its reference to privileged drinking practices relate it to prominent individuals. The emphasis granted to the donors through the inscription of their personal names on the vessel testifies of new forms of expressing the elite individuals' self and social role in a novel context of display -the sanctuary -via the novel technology of writing.
The Lozzo kantharos embodied a close relationship between three of the main aspects of the elite 'language' which I have sketched out so far, namely writing, drinking and the acquisition of exotica. A similar relationship between drinking, the adoption of foreign rituals and, in this case, situla art is evidenced by a belt plaque from Este Carceri tomb 48 (500-450 bc). This belt plaque features a single situla art scene which appears to reproduce the reclined symposium of Graeco-Etruscan inspiration (Capuis and Chieco Bianchi 1992: 95): a woman wrapped in a veil is represented about to serve a man reclining on a couch. The ideology of the reclined symposium may have spread into Veneto from the 6 th -5 th century bc alongside the importation of Greek drinking vessel shapes and possibly wine. It is unclear, however, when and to what extent the Venetic elites came to imitate the complex ritual practices of the reclined Graeco-Etruscan symposium. This uncertainty is compounded by the extreme selectivity exhibited by the inhabitants of Veneto in the choice of imported vessel types, as they adopted only a restricted number of the whole range of sympotic vessels available in Greece and Etruria. The widespread deposition of local ware even within the wealthiest Venetic graves further suggests the persistence of localised modes of consumption. The ambivalent reaction of Venetic elites towards the new sympotic practice is revealed by the Carceri plaque itself, where the woman holds a jug clearly resembling an Etruscan schnabelkanne. This beaked jug shape -albeit widely attested in regions such as Etruria, Lombardy and Continental Europe -was extremely rare in Veneto. Jugs of any type remained uncommon here until the 3 rd century. Their rarity, set against the still widespread use of high-handled cups to serve beverages, further suggests the persistence of traditional drinking practices. It is significant, therefore, that in the case of the Carceri belt plaque a new and possibly uncommon ritual practicethe reclined symposium featuring the employment of a rare vessel shape, the schnabelkanne -was related to a medium, situla art, whose distinctive social value has been already emphasised. These associations reinforce the special nature of both the practice and the medium and emphasise the sophistication of these privileged modes of self-expression.
It is also worth emphasising again the exceptional value attributed in Veneto to elaborate bronze belts and belt plaques, as both status symbols and ceremonial artefacts. Due to their social value and proximity to the body, belts probably constituted important vehicles for communicating an individual's elevated status, as testified by both their deposition in wealthy graves and their display in sanctuaries as prestigious miniature offerings or depictions on laminas (Capuis and Chieco Bianchi 1992: 84, 97). The importance of belts and belt-elements in the funerary context is emphasised by the wide range of ritual manipulations undergone by these artefacts, including deliberate fragmentation, burning, and deposition around the urn to promote the latter's identification with the elite body. Este Nazari tomb 161 (400-350 bc) provides an example of this kind of ritual (Tirelli 1981). In this wealthy grave, two bronze situlae contained a ceramic urn each. The largest situla was wrapped in cloth. A lozenge-shaped belt decorated with situla art motifs was fastened around this vessel, apparently to give human-like qualities to the urn-container. This deposition emphasises again the symbolic link elaborated over the centuries between situla art itself, sophisticated practices of 'humanisation' of the urn and the employment of situlae as urns in elite graves. The grave also yielded a rich service for drinking and for food preparation, including meat roasting. This emphasis on the preparation of solid foodstuff via the deposition of roasting spits, firedogs, knives and slices is characteristic of wealthy graves from the 4 th century and suggests the spread of new elite habits of display and consumption. Not surprisingly, the interment of these implements was often accompanied by the deposition of situla art objects and inscribed vessels (e.g. Capuis and Chieco Bianchi 1992: 86-87).
Evidence enabling the clearest synthesis of the ritual practices described above is offered by finds unearthed in Ricovero tomb 23/1984, 300-250 bc (Chieco Bianchi 1987. This grave of exceptional wealth displays both an intentional ritual conservatism going back to the 8 th century and an extraordinary openness towards contemporaneous cultural influences especially from Etruria and the international port-of-trade of Adria, located on the Adriatic Sea slightly south of the main Venetic area. The urn found in the grave was a skyphos containing the remains of an unsexed individual. The skyphos was placed within a bronze situla incised with the name of the deceased, a woman called Nerka Trostiaia. The situla was also wrapped in cloth embellished with rich ornaments probably pinned or sewn on it, again intended to evoke the human body. The importance of alcohol consumption was also emphasised via the deposition of an extremely rich banqueting set at the bottom of the grave, which included several imported items. An Attic redfigure krater was found broken on the tomb's covering slab, possibly indicating the continuation of a ritual practice that is already attested 500 years earlier in Ricovero tomb 236. Importantly, this grave featured the latest example of situla art presently known at Este, the bronze model of a piece of furniture decorated with animal images.
Mutually Exclusive Spheres?
It is noteworthy that in Veneto, despite the adoption of writing and situla art within the same social milieu and often in connection with exotica, foreign ritual practices and sympotic rituals, inscriptions have never been found to date on objects bearing situla art. This is true for the vast majority of the entire situla art corpus presently known, with only a couple of exceptions (Zaghetto 2007: 180). An obvious explanation for this pattern is that situla art and writing were different communicative systems. The former was a non-linguistic symbol-based system spread over a vast area inhabited by different ethnic groups and possibly developed to facilitate interaction between people unable to speak the same language. The latter was the written form of languages (e.g. Venetic) presumably spoken in the more restricted area where the related inscriptions have emerged. This important observation, however, does not explain why the receivers / owners of situla art items, who may have been exposed to, or even taken control of, writing as well, decided not to inscribe their possessions (or have them inscribed), for example in giftexchange with people speaking the same language or at the funeral, by putting the deceased's name on a decorated situla-urn. For the Veneto, this 'otherness' between the two 'languages' seems compounded by the fact that the interment of both written items and situla art objects in the same grave seems to have been uncommon, with some exceptions such as Nerka's tomb. As suggested by Whitehouse (pers. comm.), a possible explanation is that few Venetic inhabitants were 'bilingual' in the two 'languages' . It is worth noting, however, that this pattern may partially relate to the limited number of intact wealthy graves dating between the 5 th and 3 rd centuries bc. It is also possible that inscriptions were written on perishable materials now vanished. Another possible explanation for this pattern, however, may reside in the uses to which writing was put after its introduction in Veneto. Although writing may have spread in Veneto as early as the late 7 th or 6 th century bc, at Este the presence of inscriptions inside the grave (i.e. the context in which situla art items are found) is extremely rare before the late 4 th -early 3 rd century bc. One possible exception is a male name inscribed on a bronze tripod or cup buried in a grave dating to the 5 th or 4 th century bc (Marinetti 1992: 138). The practice of inscribing the deceased's name on urns started in the 3 rd century and became more common in the following centuries, especially from c.75-25 bc. The epitaph inscribed on Nerka's situla is one of the earliest examples of this practice. A similar epitaph is incised on a contemporary situla-urn buried in a wealthy multiple grave, namely Benvenuti tomb 123 (Chieco Bianchi and Calzavara Capuis 2006: 276-294). This tomb yielded several items comparable with Nerka's grave goods, including lavish ornaments, a bronze model of a loom, three axes and a skyphos. Again, the inscribed situla-urn was possibly wrapped in a cloth. Interestingly, no situla art product comes from this grave, although this may relate to the several re-openings the tomb underwent.
Before 325-300 bc writing was generally adopted in cemetery contexts to mark the gravestones ascribing the ownership of tombs and / or burial plots to prestigious individuals and families. The individuals mentioned on tombstones were 75% male. In the mortuary context, therefore, writing was mainly associated with the male individual and the monumentality, visibility and durability of funerary monuments erected outside the grave. A possible shift in the function and values accorded to writing may have taken place around 300 bc with the spread of 'hidden' and more intimate dedications on small, portable items buried in the grave, such as urns and vessels which bore male and female names in a similar proportion. Inscriptions on small objects were not unknown at Este before, but mainly appeared on votive offerings dedicated in sanctuaries, entailing different ways of constructing and expressing personal and social identities. This shift towards a 'hidden' funerary literacy took place when situla art seems to disappear. The deposition of situla art products and written objects in the same grave was therefore limited to c.325-250 bc, when the two 'languages' were briefly in use in the same context at the same time. Later, the progressive erosion of the previous prominent groups' social identity in favour of novel forms of display and consumption probably led to the disappearance of situla art -a language which had lost its significance in the new social setting. Before c.325, I cannot exclude the possibility that writing and situla art were used contemporaneously in the same context outside the grave. However, it seems that, despite their common pertinence to the elite 'language' outlined above, their final destination was different, and entailed a diverse conceptualisation of the two media, due to complex social motivations which are not presently identifiable.
Conclusion
By drawing on (a) Zaghetto's interpretation of situla art as a sophisticated communication system, (b) recent developments in sociolinguists breaking down the division between iconic and verbal literacies and (c) Street's understanding of literacy as an ideological practice whose nature is contextdependent and power-laden, this chapter discussed the reciprocal interplay between Venetic writing and iconography at Iron Age Este, with an emphasis on their material dimension and their role in elite consumption practices. Both writing and situla art were most likely adopted from non-local contexts by Venetic privileged groups in order to enhance their social prominence and advertise their access to exotic goods and knowledge of rituals and ideas attested in foreign regions. Hence, I outlined a preliminary account of the intricate relationship between writing, situla art and other means of status expression adopted by the Este elite, such as formal drinking. This relationship suggests that -when considered in the perspective adopted in this chapter -the conventional scholarly habit of studying situla art and writing as unrelated phenomena taken outside their similar social milieu of development is less persuasive. By contrast, the Este elites were able to elaborate a complex hybrid language, flexible but partially stable over time, which was probably adopted to advertise the social prominence and affiliation of its recipients and creators. The adoption of foreign modes of status enhancement and consumption as well as the continuous re-elaboration and transmission of the entire 'package' may have promoted changes in bodily practices and forms of self-perception and self-representation of the elite person him / herself. Both situla art and writing were part of the 'package' and their importance in 'creating' Este elite individuals cannot be underestimated.
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Domain: Art History
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ARTIFACTS IN MRI DUE TO DENTAL RESTORATIONS: FACT OR MYTH
Prof. Dr. Paromita Mazumdar, Dr. Sadhan Bhowmick and Dr. Soumya Singh ...................................................................................................................... Manuscript Info Abstract ......................... ........................................................................ Manuscript History Received: 15 May 2020 Final Accepted: 20 June 2020 Published: July 2020 Purpose: To identify presence of artifacts if any due to the presence of dental restorations in patients requiring MRI of head and neck. Method: The medical records of total three hundred patients who required MRI were gathered over a period of one month and of them patients requiring MRI in head and neck region were screened for the presence of dental restorations. Forty percent of them had head and neck MRI done. Twenty one patients among them had dental restorations done. The MRI were interpreted by radiologist and artifacts in the MRI were identified. Results: Dental composite resin, amalgam alloys, glass ionomer cements and zirconia crowns were not the source of artifact. These have been shown to have little influence in MRI, while metallic crowns have shown significant distortion if present in more than one tooth. Discussion: Magnetic Resonance Imaging (MRI) is a diagnostic technique that uses magnetic field and radio waves to produce a detailed image of the body’s soft tissue and bone. The presence of high attenuation metal objects in the field of view can cause artifacts. Recognizing the artifacts caused by dental restorations will help clinicians in treatment planning and decision-making.
Magnetic resonance imaging (MRI) is an imaging technique which enables the visualization of soft tissue contrast without the use of ionizing radiation considered a powerful diagnostic method using a strong uniform static magnetic field and radiofrequency pulses [1,2]. The occurance of artifacts can be present in all image modalities which results in degradation of quality of image compromising imaging evaluation. When any substance is placed in a magnetic field, it gets magnetized according to their magnetic susceptibility. For dental treatment many kinds of materials and metal alloys are used. Metallic sources used for orthodontic purpose, dental restorations, dental crowns or metallic splints can lead to large magnetic field distortion and signal loss, reducing the quality of image in MRI of maxillofacial region. There is a correlation between the magnetism of a metal and the magnitude of an imaging artifact during MRI. Shape, position, orientation and the number of object can effect the damage in image. There are several articles describing the effects of metallic objects on MRI interpretation, very few have addressed these problems in clinical situations. The purpose of this study was to overview the artifacts in patients reporting for MRI over a period of one month in a testing centre having dental restorations of different kinds.
Image artifact is something observed in a scientific investigation that is not naturally present but occurs as a result of the investigative procedure (Oxford dictionary). MRI induced artifact is defined by pixels that do not optimally or properly represent the tissue components under study. A MRI induced artifacts is directly proportionate to the ISSN: 2320-5407 Int. J. Adv. Res. 8(07), 782-785 783 ferromagnetic content of a material. Many types of artifacts may occur in magnetic resonance imaging. Artifacts in magnetic resonance imaging are typically classified as: physiologic (motion, flow),hardware (electromagnetic spikes, ringing) or inherent physics (chemical shift, susceptibility, metal). Today, in the dental treatment, various kinds of materials such as metal alloys, composites, acrylics, porcelain and ceramics as filling materials and in dental prostheses like crowns, dental bridges and dentures are used. [8] Review Of Literature:- Georg Eggers et al (2005) had conducted a study to investigate whether magnetic resonance imaging(MRI) of the oral cavity would be less affected than CT by artifacts caused by typical dental restorative alloys. In order to assess the extent of artifact generation, corresponding MRI scans of the same anatomic region with and without dental metal restorations were matched using a stereotactic frame. MRI imaging of the oral and maxillofacial region could be performed without reduction of the image quality by metallic dental restorations made from titanium, gold or amalgam. Dental restorations made from titanium, gold or amalgam did not reduce the image quality of the MRI sequence used in imaging of the oral and maxillofacial region for dental implant planning. In this respect MRI is superior to CT in implant planning. [8] Sherin Jose Chockattu et al (2018) had done a review based on the current available evidence, recommendations for dentists and radiologists regarding the safety and appropriate management of dental materials during MRI in patients with orthodontic appliances, maxillofacial prostheses, dental implants, direct and indirect restorative materials, and endodontic materials. They found that the magnetic field and radiofrequency pulses generated within the magnetic resonance imager interact unfavorably with these dental materials that have magnetic properties. These variations in the magnetic field strength that occur at the interface between dental materials and the adjacent tissue can lead to spatial distortions and signal loss, thereby generating an artifact in the image. Apart from artifact formation, other unwanted effects of MRI are radiofrequency heating (a physical effect) and magnetically-induced displacement (a mechanical effect) of the dental material. [2] Methodology:- The medical records of total three hundred patients who required MRI were gathered over a period of one month and of them patients requiring MRI in head and neck region were screened for the presence of dental restorations. 40% (one hundred and twenty) of the patients among them required head and neck MRI. Patients needed MRI for the following reasons: traumatic brain injury (TBI), intracranial hemorrhage, subdural hematoma, extradural hemorrhage, intracerebral hemorrhage, soft tissue tumor of head and neck, brain injury or concussion. Out of the 120 patients examined for the presence of restorative dental work, 21 patients were found to have dental restorations. It was observed; patients who were screened had the following restorations in their mouth. Composite resin restorations were present in six patients, of which the first patient had the restoration in relation to 11, 21, the second patient had the composite restoration in 46 and 47. 11, 12 were restored with composite in the third and fourth patient and the last patient had 12, 21 restored with composite. Among five patients having amalgam restorations, four of them had the restorations in relation to 36, 46 and one had the amalgam restorations in relation in relation to 36, 47, glass ionomer cement restorations were present in two patients of which one had restorations in relation to 13, 14, 15, 23, 24, 25 and the other one had the glass ionomers cement restored in 11, 12. Multiple metal ceramic crowns were present in six patients. The first patient had the crowns in 31, 32,33, 34, 41, 42, 43, 44, second patient had them in 44, 45, the third patient got his metal ceramic crown in 13, 14, 15, 16, fourth patient had crowns in 13, 14, 15, 23, 24, 25 and the last patient them in 33, 34, 35, 44, 45, 46. Multiple metal crowns were present one patient in his 36, 46, 47 and zirconium crown was present in 16,26, and 36 of a patient. The MRI was done by a radio technician and results were interpreted by radiologist. The affected imaging planes were identified and sources of artifacts were described and divided into categories: a) Metal ceramic crowns and b) Metal crowns. All images presented in this study were recorded on a 1.5 Tesla, GE Signa magnetic resonance imager. Specific acquisition parameters were sagittal head and neck, 5 mm Thick, flip angle= 180degree, SE, TR/TE = 600/14 ms, 1 Nex, 256x192 matrix, matrix 200 x 350, field of view (FOV)=26 x 26cm.
Observation:-
During the study period it was found that three hundred MRI scans of head and neck were performed. Forty percent (one hundred twenty) of them had head and neck MRI done. Twenty one patients among them had dental restorations done (Fig. 1-7). Artifacts were observed in thirty three percent (seven) scans (Table 1).
Discussion:-
The dimensionless proportionality constant that indicates the degree of magnetization of a material in response to an applied magnetic field is the magnetic susceptibility of that material which is caused by the interactions of electrons and nuclei with the externally applied magnetic field. The magnetic field of metal-based materials are created by their own and such strong susceptibility gradients result in signal loss which dramatically alter precession frequencies of protons in the adjacent tissues. The substances are characterized based on their magnetic susceptibility as paramagnetic, diamagnetic, and ferromagnetic. The highest potential among them is by ferromagnetic substances which are strongly attracted by a magnetic field. Diamagnetic substances have a very weak and negative susceptibility to magnetic field. Paramagnetic materials have positive susceptibility and augment the external field. Both diamagnetic and paramagnetic materials are far less likely to cause artifact. [1] In dentistry the metal alloys used are ferromagnetic substance. [6] These ferromagnetic components induces magnetic field and tissues adjacent to these components become influenced by the induced magnetic field of the metal, Hence they do not generate a useful signal because they either fail to process or do so at a different frequency. [5] The artifacts caused by metallic objects are a common problem in MRI scans. These artifacts due to metals usually lead to areas of signal blackout, with rims of high signal strength around the offending object. [6] In this study, it was found that dental composite resin, amalgam alloys, glass ionomer cements and zirconia crowns were not the source of artifact. These have been shown to have little influence in MRI, while metallic crowns have shown significant distortion if present in more than one tooth. The artifacts produced by metals correlates with variables like composition and number of metal crowns. Extensive metallic artifacts in the oral cavity and other areas (TMJ, posterior cerebral fossa, maxillary sinus), were produced in patients with multiple metal ceramic crowns. Patients having seven to ten metal ceramic crowns were potential source of artifacts in MRI,that made image interpretation impossible. Major artifact was found in patients with multiple metal crowns. The artifact was faint or limited in patients with less than three metal based crowns. Dental amalgam is composed of several metals, but the absence of artifact caused by amalgam maybe explained by the presence of silver, a nonferromagneticmetal.
To deal with the distortion for imaging near metals, various techniques have been proposed. These techniques can be categorized to two and three-dimensional approaches. The slice encoding for metal artifact correction (SEMAC) technique, which includes the VAT gradients, is based on two dimensional multi slice SE imaging, and uses additional slice encodings to deal with the through plane distortion. The multi acquisition variable resonance image combination (MAVRIC) technique is based on the three dimensional acquisition, and acquires multiple images with different center of excitation frequency to deal with a broad field perturbation. These techniques have different approaches of reducing the image artifact including the through plane distortion, but all are revealing that MRI near metal prostheses is possible in imaging. The combination of the MAVRIC and SEMAC technique is known as MAVRIC-SL. Also, metal artifact reduction sequence (MARS), WARP (Siemens Healthcare, Munich, Germany) and slice encoding for metal artifact correction are recommended to reduce the size and intensity of susceptible artifacts resulting from magnetic field distortion.
Other methods of artifact correction involves: pulse sequence optimization, post processing hardware improvement and scan parameter. The orientation of the metallic object, alloy used and magnetic field strength, as well as use of metal-suppression techniques can be intended to reduce the artifacts caused due to metallic crowns. [11][12]
Conclusion:-
The results of this study demonstrate that the origin of dental artifacts is most likely from metal and metal ceramic crowns but the effect is insignificant if less than three in continuation and if not in the field of area of interest. They lead to large areas of artifacts, making imaging interpretation difficult. But high end equipment (3Tesla) have the option of increased number of channels which reduce artifacts. In order to anticipate complications and take precautions prior to MRI in patients with the aforementioned dental materials, It is critical that the radiologist and dental practitioners are aware of the potential of these dental restorations to cause adverse interactions during MRI scans. Dental practitioners must be acquainted with the composition of restorative materials and its effect on the diagnostic quality of MRI scans. The influence of other dental work in the mouth like wire splints, metallic orthodontic braces, implants may be studied for more complete knowledge.\===
Domain: Medicine Art. The above document has 2 sentences that start with 'Twenty one patients among them',
2 sentences that start with 'These have been shown to',
2 sentences that start with 'In order to',
2 sentences that end with 'the presence of dental restorations',
2 sentences that end with 'head and neck MRI done',
2 sentences that end with 'not the source of artifact',
2 sentences that end with 'in more than one tooth'. It has approximately 2074 words, 99 sentences, and 12 paragraph(s).
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Effect of tauroursodeoxycholic acid on survival and safety in amyotrophic lateral sclerosis: a retrospective population-based cohort study
Summary Background Oral tauroursodeoxycholic acid (TUDCA) is a commercial drug currently tested in patients with amyotrophic lateral sclerosis (ALS) both singly and combined with sodium phenylbutyrate. This retrospective study aimed to investigate, in a real-world setting, whether TUDCA had an impact on the overall survival of patients with ALS who were treated with this drug compared to those patients who received standard care only. Methods This propensity score–matched study was conducted in the Emilia Romagna Region (Italy), which has had an ALS regional registry since 2009. Out of 627 patients with ALS diagnosed from January 1st, 2015 to June 30th, 2021 and recorded in the registry with available information on death/tracheostomy, 86 patients took TUDCA and were matched in a 1:2 ratio with patients who received only usual care according to age at onset, sex, phenotype, diagnostic latency, ALS Functional Rating Scale-Revised (ALSFRS-R) at first visit, disease progression rate at first visit, and BMI at diagnosis. The primary outcome was survival difference (time from onset of symptoms to tracheostomy/death) between TUDCA exposed and unexposed patients. Findings A total of 86 patients treated with TUDCA were matched to 172 patients who did not receive treatment. TUDCA-exposed patients were stratified based on dosage (less than or equal to 1000 mg/day or greater) and duration (less than or equal to 12 months or longer) of treatment. The median overall survival was 49.6 months (95% CI 41.7–93.5) among those treated with TUDCA and 36.2 months (95% CI 32.7–41.6) in the control group, with a reduced risk of death observed in patients exposed to a higher dosage (defined as ≥ 1000 mg/day) of TUDCA (HR 0.56; 95% CI 0.38–0.83; p = 0.0042) compared to both the control group and those with lower TUDCA dosages (defined as < 1000 mg/day). TUDCA was generally well-tolerated, except for a minority of patients (n = 7, 8.1%) who discontinued treatment due to side effects, primarily gastrointestinal and mild in severity; only 2 adverse events required hospital access but resolved without sequelae. Interpretation In this population-based exploratory study, patients with ALS who were treated with TUDCA may have prolonged survival compared to patients receiving standard care only. Additional prospective randomized studies are needed to confirm the efficacy and safety of this drug. Funding 10.13039/501100009879Emilia-Romagna Region.
Findings A total of 86 patients treated with TUDCA were matched to 172 patients who did not receive treatment. TUDCA-exposed patients were stratified based on dosage (less than or equal to 1000 mg/day or greater) and duration (less than or equal to 12 months or longer) of treatment. The median overall survival was 49.6 months (95% CI 41.7-93.5)among those treated with TUDCA and 36.2 months (95% CI 32.7-41.6) in the control group, with a reduced risk of death observed in patients exposed to a higher dosage (defined as ≥ 1000 mg/day) of TUDCA (HR 0.56; 95% CI 0.38-0.83;p = 0.0042) compared to both the control group and those with lower TUDCA dosages (defined as < 1000 mg/day). TUDCA was generally well-tolerated, except for a minority of patients (n = 7, 8.1%) who discontinued treatment due to side effects, primarily gastrointestinal and mild in severity; only 2 adverse events required hospital access but resolved without sequelae.
Introduction
Tauroursodeoxycholic acid (TUDCA) is an endogenously produced bile acid salt resulting from the conjugation of taurine to ursodeoxycholic acid. Apart from its primary use in the treatment of gallstones or primary cholestatic disease, there is a growing body of evidence, from in vitro and animal models, pointing to multiple mechanisms of neuroprotection in neurodegenerative diseases, including Amyotrophic Lateral Sclerosis (ALS). These mechanisms include the stabilization of mitochondrial membranes, enhancement of oxidative defenses, mitigation of endoplasmic reticulum stress, and modulation of the immune response, all of which may all contribute to TUDCA's cytoprotective and anti-apoptotic effects. 1 A preliminary trial published in 2015 explored the safety and efficacy of TUDCA for ALS, 2 where the primary outcome of the study (an improvement of at least 15% in the ALS Functional Rating Scale-Revised, ALSFRS-r, slope during the treatment period compared to the lead-in phase) was achieved. 2Since ALS is an incurable disease, the regional health care system of the Emilia Romagna Region (ERR) in Italy may support, following approval from the regional rare diseases technical group, the offlabel use of approved treatments that show promising evidence from early clinical studies. In this context, since 2015, TUDCA has been prescribed by specialized ALS centers operating in ERR, that participate in ERR ALS register (ERRALS). 3e aimed to investigate, in a real-world setting through our ALS regional registry, 3,4 whether tauroursodeoxycholic acid influences survival in the ALS
Research in context
Evidence before this study To investigate tauroursodeoxycholic acid (TUDCA) effects in Amyotrophic Lateral Sclerosis (ALS) we conducted a nonsystematic search in Pubmed including all studies published in English from Jan 1, 2017, to Jan 1, 2023, using the search terms "TUDCA" or "tauroursodeoxycholic" AND "amyotrophic lateral sclerosis" or "ALS". Current evidence points to a protective effect of TUDCA in ALS, alone or combined with phenylbutyrate (PB) at dosages of 2000 mg/daily, in slowing disease progression and prolonging survival in post-hoc analysis of two phase II clinical trials. Phase III randomized clinical trials testing TUDCA and PB-TUDCA are currently ongoing, while in several countries PB-TUDCA received conditional approval for ALS treatment. TUDCA has been authorized as a medicinal product and is commercially available in food supplements; Therefore, it may be provided off-label upon evaluation by the rare disease technical group, in Emilia Romagna Region (Italy), where a regional registry prospectively collects clinical information of newly diagnosed ALS subjects since 2009.
Added value of this study
Observational studies provide real-world data (RWD) which could be helpful to fully understand the effects of the therapeutics in such rare diseases as ALS. With this propensity score-matched study, we analyzed TUDCA effects in terms of overall survival and safety in the general ALS population of Emilia Romagna Region, where ALS patients who were excluded from randomized clinical trials could be prescribed TUDCA since 2015 following approval from the regional rare disease technical group. Treatment with TUDCA at higher doses (more or equal to 1000 mg daily) resulted in prolonged survival compared to propensity score-matched non-TUDCA controls and patients assuming TUDCA at dosages inferior to 1000 mg daily. A minority of patients (n = 7, 8.1%) presented side effects, mainly involving the gastrointestinal tract and mild in severity, leading to treatment discontinuation; upon TUDCA withdrawal side effects vanished without leaving permanent sequelae.
Implications of all the available evidence
In the wider context of a regional ALS population, TUDCA is generally safe and well-tolerated and may have a beneficial effect in a fatal disease such as ALS by prolonging survival. These findings are not definitive and require additional supportive evidence by prospective randomized trials and larger worldwide post-marketing population studies.population. Propensity score (PS) methods were adopted to correct for possible confounders that, in observational cohort studies, might impact on the outcome of interest, 5 as in our case, survival.
Study design and setting
This is a retrospective, observational, propensity scorematched cohort study comparing patients with ALS treated with TUDCA with patients not exposed. The study was performed in ERR, where a prospective registry (ERRALS) has been active since 2009, 3 collecting all incident ALS cases among residents, diagnosed according to Revised El Escorial Criteria (EEC-R). 6n electronic database is accessible only to the investigators of ERR Neurological Departments, where study referents upload a detailed phenotypic profile of new ALS cases. At diagnosis clinicians record baseline visits; follow-up is performed until death, collecting information regarding forced vital capacity (FVC), ALSFRS-R, 7 drugs intake and discontinuation, riluzole and TUDCA assumption, 8 supporting procedures, 9 and cause, place and time of death.
In addition to demographic and clinical variables, for this study we extracted from ERRALS a detailed pharmacological history for TUDCA exposure, considering the maximum dosage, duration of treatment, and clinical variables at the time of TUDCA administration. Reasons for TUDCA discontinuation or dosage reduction were registered too. Data extraction for the last follow-up visit or death date was performed on 1st February 2022. The study was approved by the ethical committees of the coordinating centre and of ERR provinces (Comitato Etico Provinciale di Modena, number 124/08, 2 September 2008). Patients enrolled in ERRALS signed written informed consent. Neither clinicians nor patients received or were offered any compensation for the study. This study followed STROBE reporting guidelines.
Study population
The study included all patients diagnosed with ALS from 1st January 2015 to 30th June 2021 recorded in ERRALS registry. The last date of follow-up was fixed on 1st February 2022. The start date for survival analysis was the date of disease onset. After the first visit, followup visits were recorded approximately every three months or based on patients' needs, according to clinical practice for ALS. 10 Patients were treated in the frame of regular ALS multidisciplinary clinical practice, and therapeutic decisions and medical care during the treatment were carried out by the treating physicians and were not defined by a specific protocol. Patients may or may not have received treatment with riluzole. TUDCA treatment was offered to patients with ALS not participating in other experimental trials at the time of the regular follow-up visits based on individual MND centre experience. Patients may or may not have continued TUDCA oral treatment until tracheotomy/death or censoring.
Outcome measures
Safety analysis was performed on all TUDCA-exposed patients by recording reasons for discontinuation and possible side effects related to drug administration, hospitalizations, or excess mortality in TUDCA-treated patients. Cases receiving at least three consecutive months of daily TUDCA were included in propensity score matching (PSM) and effectiveness analysis; the matched control cohort was screened among non TUDCA-exposed patients registered in ERRALS during the same period as patients receiving TUDCA. The probability of receiving treatment with TUDCA was not influenced by economic or procedure-related variables, because the drug is covered by the ERR health system. Therefore, we estimated through stepwise logistic regression which clinical variables, also with a prognostic value, differed between treated and untreated patients: significant entering/excluding levels for variables were both set at 0.1. Based on these results, PSM was performed to reduce the bias due to confounding clinical variables by comparing outcomes among patients treated with or without TUDCA. 5he final model included sex, age at onset of ALS, diagnostic latency (disease duration from onset to diagnosis), ALS phenotype, body mass index (BMI), ALSFRS-R total score and disease progression rate calculated at first visit. Once the propensity scores were calculated, they were used for matching case and control groups. A greedy nearest-neighbor matching was adopted. A caliper of 0.2 standard deviations of the logit of the propensity score was set. 5,11The matching ratio between controls and cases was set at 2:1. Considering the limited number of TUDCA-treated patients in the database, such a ratio was selected to increase in statistical power given the expected prevalence of exposure among the controls.
The primary outcome to evaluate TUDCA effectiveness was survival probability considering tracheostomyfree survival at the end of the study. The secondary outcomes included disease progression during the follow-up period, which was measured by the monthly decline in ALSFRS-R at the last visit. This decline was calculated by dividing the difference in the ALSFRS-R total score between the initial visit and the last available follow-up before tracheostomy or death (whichever occurred first) by the number of months between the two visits. Finally, we also assessed the frequency and time to NIV and PEG in patients treated with TUDCA compared with untreated patients.
Adherence to treatment with TUDCA was assessed by calculating the rate of treatment discontinuation and the reason.
Statistical analysis
For analyses, the disease progression rate at diagnosis was assessed by subtracting the ALSFRS-R total score at the time of diagnosis from the presumed score of 48 at onset. The obtained difference was then divided by the duration of diagnostic delay in months. Since 48 represents the highest achievable score on the ALSFRS-R scale, we assume that each patient had this score before the onset of symptoms. 12iven that in the registry, any resident patient diagnosed and followed up within the specialized Motor Neuron Disease (MND) centres of Emilia Romagna was documented with ALSFRS-r at the time of diagnosis, the disease progression rate at diagnosis aligns with the disease progression rate at the first visit. The ALS progression rate at the last visit was calculated by dividing the difference in ALSFRS-r scores between the last and first visits by the time interval in months between the two visits.
Survival was calculated by considering the time in months from symptom onset to death or tracheostomy (whichever occurred first) or the censoring date (the last day of follow-up, February 1st, 2022).
Survival and progression rates were taken into account to classify the patient's disease progression as "slow," "intermediate," or "fast."We classified patients as slow progressors if individuals had tracheostomy-free survival exceeding 60 months from symptom onset, or if living patients (at their latest observation) demonstrated tracheostomy-free survival of >24 months and a disease progression rate of <0.3 points per month, measured from onset to the initial visit. We designated fast progressors as individuals with tracheostomy-free survival of less than 24 months from symptom onset or living patients (at their most recent observation) displaying tracheostomy-free survival <60 months and a disease progression rate >1.3 points per month, measured from onset to the initial visit. All remaining patients were categorized as intermediate progressors.
Indicator variables were created to provide a stratification of TUDCA treatment, in terms of strengths and duration. TUDCA strength was defined as a three-level categorical variable: ''no drug'', ''TUDCA < 1000 mg/ day", "TUDCA ≥ 1000 mg/day". Duration of TUDCA treatment was classified according to time intervals of 12 months ("no drug", "TUDCA < 12 months", "TUDCA ≥ 12 months"), based on the distribution of TUDCA-treated patients (40 patients assumed TUDCA for less than 12 months, 44 for more or equal than 12 months). For 2 TUDCA-treated patients, the duration of the therapy could not be established and were excluded from the analysis.
After PSM, the balance between the case/control group was evaluated by calculating standardized mean differences (SMDs) between treated and matched control patients in the matched and overall populations. SMDs of less than 10% were considered negligible imbalances.
Description of treatment groups homogeneity was presented using Student's t-test or ANOVA and chisquare test, when appropriate. Survival was calculated from onset to death/tracheostomy or the censoring date using the Kaplan-Meier method; the logrank test was used for group comparison. The hierarchy of performed statistical analyses was the following: i) impact of TUDCA treatment on survival; ii) impact of treatment duration on survival; iii) impact of TUDCA doses on survival. In parallel, multivariate Cox regression analysis was employed to obtain a better estimation of survival probabilities of TUDCA-treated patients versus control. Since the delay in the initiation of TUDCA administration may constitute an immortal time bias, 13 we included this variable as a covariate in Cox regression analysis; whereas Riluzole and respiratory function were included although not unbalanced between TUDCA groups. These analyses were repeated in a sub-cohort of patients in which TUDCA <1000 mg/day and their matched controls were excluded.
Missing data were not substituted, and they were treated as such. For primary outcomes, no missing data were reported in the database; lost in follow-up were censored recording patients as alive at the last available visit. For the ALS progression rate at last visit, 26 values were missing, exclusively in the non-TUDCA group; then, the pairwise analyses were performed excluding paired data with missing values.
Role of the funding source
The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had access to the data and were responsible for the decision to submit for publication.
Clinical characteristics of patients with ALS before propensity score matching
The initial population considered for the study was constituted of 627 patients (men: women = 1.36), whose clinical features are shown in Supplementary Table S1. Median survival time was 25.5 months (95% CI 28.7-31.8)from onset. Patients exposed to TUDCA (n = 86) were more commonly men and on average they were less likely to present bulbar onset/phenotype, while they frequently had a younger-onset disease and more benign phenotypes such as flail arm/leg and UMN-predominant. Both MiToS (median 0, IQR 0-1) and King's College (median 2, IQR 1-3) stages were low at TUDCA initiation, suggesting exposed patients were at the initial stages of the disease.
Propensity score matching
TUDCA-treated and non-TUDCA-treated patients with ALS were matched for sex, age at onset, ALSFRS-R, diagnostic delay, phenotype, BMI, and disease progression rate at diagnosis. After matching, SMD tests confirmed the balance between the case/control group calculated by PSM for almost all clinical characteristics (Supplementary Table S2). As reported in Table 1, no statistically relevant differences were observable for clinical characteristics in the TUDCA-treated and non-TUDCA-treated patients, suggesting a good homogeneity of the cohort.
TUDCA was administered at different dosages to patients. Table 2 shows the clinical features of patients stratified based on TUDCA dosages.
Since patients treated with lower doses of TUDCA were on average older, more advanced in disease and more often bulbar (Table 2), to avoid a confounding effect of these factors, we performed survival analysis after the removal of lower doses TUDCA-exposed patients (n = 20) and their matched unexposed counterpart (n = 40), leaving 66 patients exposed to higher than 1000 mg daily TUDCA with 132 matched controls. Even comparing these two populations, TUDCA was found associated with a reduced risk of death/tracheostomy by 55% (HR 0.45, 95% CI 0.28-0.73,p = 0.0011). Stratification by duration revealed patients exposed to TUDCA for more than 12 months had prolonged survival (median: 56.2 months, 95% CI 43.0-96.2) compared to non-TUDCA patients (median: 36.2 months, 95% CI 32.7-41.6). High-dose TUDCA treatment yielded superior results in terms of survival both versus controls (Table 3) and low-dose treatment (HR 0.38, 95% CI 0.2-0.74,p < 0.0001).
Survival in high dose TUDCA-treated patients compared with matched non-TUDCA-treated patients on specific ALS subgroups
Survival analyses were performed separately on specific patients' subgroups comparing high-dose (≥1000 mg/ day) TUDCA-treated patients (n = 66) with propensity score-matched patients who were not treated with TUDCA (n = 132).
Among fast progressors (n = 41) and intermediate progressors (n = 82) there was no difference in survival between high-dose TUDCA-treated patients and propensity score matched non-treated patients (Supplementary Table S4). When considering fast and intermediate progressors altogether, a difference was detected (Supplementary Table S4).
There were no differences in survival among bulbar patients (n = 41) based on TUDCA treatment: median time from onset to death or tracheostomy was 31.82 months (95% CI: 24.49 to not available) in highdose TUDCA-treated patients and 34.09 months (95% Fig. 1: Participant flow through study analysis. Cases and controls of the ERRALS study population are shown through the flowchart.761 patients were diagnosed with ALS between January, 1st, 2015 and June, 30th, 2021 in the Emilia Romagna region and recorded in ERRALS. Last follow-up date was fixed on February 1st, 2022. All patients with ALS with insufficient baseline or follow-up data on the ERRALS registry were excluded from propensity score-matching analysis; TUDCA-exposed patients who took less than three consecutive months of therapy were similarly excluded. ALS: Amyotrophic Lateral Sclerosis; ERRALS: Emilia Romagna Region ALS registry; TUDCA: tauroursodeoxycholic acid. CI: 22.42-44.22) in propensity-matched non-treated patients (HR 0.81; 95% CI 0.26-2.49,p = 0.71).
When survival analysis was performed separately on familial ALS, we could not detect any significant effect of TUDCA administration, though these results are limited by the small number of familial patients with ALS in our cohort (only 20 individuals in the second propensity-matched cohort). Similar results were obtained with survival analyses on C9ORF72 expanded patients (Supplementary Table S4).
Adverse effects in TUDCA-treated patients
Eighteen patients (20.9%) presented side effects (n = 20) requiring drug reduction (n = 13, 15.1% of total TUDCA exposed patients) or drug discontinuation (n = 7, 8.1% of total TUDCA patients); two (2/13, 15.4%) of these patients initially reduced the dose to cope with side effects but eventually decided to drop treatment. The most frequently reported adverse effects were diarrhoea (n = 12; 14.0%), abdominal pain (n = 5; 5.8%), and skin eruption (n = 3; 3.5%). Among the seven patients who discontinued TUDCA (38.9% of patients presenting side effects), three presented diarrhoea, two abdominal pain and two skin eruptions; two of these events required hospital access but resolved without sequelae after treatment discontinuation. No deaths or abnormal increase in disease progression was observed for TUDCA-exposed patients. No differences were noted concerning the onset of adverse effects among patients receiving varying dosages of TUDCA (number of side effects: 5 out of 20 patients treated with TUDCA <1000 mg/day, and 15 out of 66 patients treated with the higher dose). In general, patients exposed to higher doses of TUDCA were more frequently subject to drug titration compared to low-dose exposed TUDCA patients (71% versus 45%, p = 0.03). Overall, 16 patients discontinued TUDCA treatment (18.6% of total TUDCA patients); besides adverse events, three patients (3.50%) decided to interrupt TUDCA administration because of lack of observable effects, four (4.65%) because of engagement in other clinical trials, and finally one (1.16%) because of progressive swallowing problems which rendered TUDCA administration difficult.
Discussion
This multicenter, propensity score-matched cohort study suggested through real-world data that patients with ALS treated with TUDCA may have a survival benefit. As far as the TUDCA effect is concerned in randomized clinical trials (RCT), after the first exploratory Italian study showing encouraging results in ALS 2 a phase III study is still going on in Europe. 14oreover, a combination of TUDCA and sodium phenylbutyrate (PB) gave promising effects both on the ALSFRS-R decline 15 and on survival 16,17 Analyses performed on sub PSM cohort (excluding TUDCA < 1000 mg/day and their matched controls) Survival: from onset to death/tracheotomy (treatment impact) Patients not treated with TUDCA (n = 132) 39.0 (33.1-48.8) Patients treated with ≥1000 mg/day (n = 66) 56.5 (43.0-NA a ) 0.0019 0.45 0.28-0.730.0011 NA: not available. CI: confidence interval. HR: Hazard Ratio. FVC: forced vital capacity. Median survival times from Kaplan-Meier analyses and Hazard Ratio descriptors from multiple Cox regression analyses were reported, respectively. For the latter ones, the following covariates were included in the model: riluzole treatment; delay of TUDCA initiation from onset; delay of TUDCA initiation from diagnosis; and FVC value at the baseline. Supplementary Table S3 reported p-values to estimate the impact of such covariates in terms of confounding factors.p-values inferior to 0.05 are reported in bold character.a The CI cannot be estimated because a low observations' size or a higher number of censored observations. Table 3: Median survival and hazard ratio on different dosages and durations of TUDCA treatment.
Fig. 2: Tracheostomy-free/life survival from diagnosis of incident ALS cases based on TUDCA treatment. Kaplan-Meier survival plot displaying tracheostomy-free survival of patients with ALS in ERRALS study divided by controls (i.e., non-TUDCA-exposed patients, blue line), low-dose TUDCA-exposed patients (i.e., <1000 mg/daily dosage, red line), and high-dose TUDCA patients (≥1000 mg/daily dosage, green line). Survival was calculated by considering the time in months from symptom onset to death or tracheostomy (whichever occurred first) or the censoring date (the last day of follow-up, February 1st, 2022). The number of patients included in the analysis is presented every 20 months, with the number of censored patients between brackets. TUDCA: tauroursodeoxycholic acid.
a longer time (as in our case, superior to one year) and consider patients at all stages of disease while assuming approved drugs for the disease. This will avoid the selection of a restricted study population that might not be entirely representative of the overall ALS population. 18n special fragile populations such as patients with ALS several comorbidities may coexist with an impact on survival, 19,20 leading to patients' exclusion from RCT because of stringent inclusion and exclusion criteria 21 and consequently a gap in the generalizability of the results. 22To favour the inclusion of population-based data during the regulatory approval process, a framework for evaluating the use of real-world evidence (RWE) was created in the US. 23Real-world studies are now being considered to generate RWE of both safety and effectiveness, and to support regulatory decisions about drug products; in ALS RWE generated interesting data on controversial drugs such as edaravone as well. 24,25n our retrospective propensity score matched study, we found that treatment with TUDCA was associated with reduced risk of death and/or tracheotomy over 50% in patients treated with daily doses ≥1000 mg in comparison to controls. Importantly, this effect was observed in a limited, population-based cohort, where spinal/bulbar/respiratory onset patients with ALS were included in the analysis, differently from RCTs where rarer phenotypes might be excluded because of stringent exclusion criteria. Treatment with lower doses of TUDCA did not affect survival in comparison to controls, in agreement with the proposed therapeutical dosage tested in previous studies, 2,15 establishing a threshold effect. Though in our PSM population-based cohort riluzole seemed not to act as a potential confounder in survival analysis, it should be noted a higher percentage of TUDCA-exposed patients concurrently assumed riluzole, similar to ongoing RCTs where the combination of the two is studied.
Should our results be confirmed in further prospective studies this will open a new scenario, where establishing the effect of TUDCA alone or in combination with PB would be of uttermost importance. Despite our observed trend towards a slowing of disease progression in patients treated with TUDCA, we could not demonstrate a significant effect of the drug on ALSFRS-R monthly decline. This can be partly explained by the retrospective nature of this study and several potential limits of clinical data reliability in population registries: the irregular intervals between each visit and consequently ALSFRS-r collection time points, ALSFRS-r inter-rater differences among population MND clinics, and the loss in follow-up. However, recent studies proved a high variability in disease trajectories exists in ALS, 26 destabilizing the significance given so far to ALSFRS-r slope in clinical trials. In fact, newer clinical outcomes derived from statistical enrichment techniques have been tested and are the subject of research for a better definition of efficacy endpoints in clinical trials as well as population studies. 27,28hen comparing only high-dose TUDCA-treated patients with propensity score-matched untreated patients, we also identified a significant difference in the time from onset to initiation of non-invasive ventilation (NIV), which may suggest a potential beneficial effect of TUDCA in slowing down disease progression, particularly in its early stages. Our survival analysis within subgroups revealed a noteworthy treatment effect on individuals with slow progression; however, this effect was not evident among those with intermediate and fast progression, unless these groups were analyzed collectively. Spinal onset patients also benefited most from TUDCA treatment compared to bulbar onset patients with ALS. Given the limited number of patients within each subgroup, the generalizability of these findings is constrained, warranting caution when interpreting survival data. These observations, together with results on other patients' subgroups based on site of onset, family history, or genetics, necessitate confirmation through prospective randomized controlled trials, where instrumental evaluations such as FVC are regularly assessed and close monitoring of fast progressors due to the rapid evolution of their condition is granted.
Our study showed that the safety profile of TUDCA, even with a longer treatment duration, was mainly characterized by gastrointestinal side effects reported in almost 20% of TUDCA-exposed patients, independently of BMI. Drug reduction was sufficient for most patients presenting with side effects, but 35% of them (corresponding to 7% of the entire treated cohort) judged these effects intolerable and discontinued the treatment. Therefore, TUDCA treatment has shown to be well tolerated in real-world settings where patients with ALS may experience a large range of comorbidities potentially increasing side effects and affecting survival, and several other treatments potentially modulating drug interactions. 19Patients assuming higher doses of TUDCA were more frequently exposed to increasing titration regimens, which may be a good therapeutic strategy to cope with unwanted effects and to establish the maximum tolerated TUDCA dose in individual patients.
Due to the observational nature of our study, the accurate drug history and adherence to TUDCA treatment could only be verified by the attending physician during follow-up visits. The absence of external drug accountability controls, as expected in randomized controlled trials, could potentially influence the results. Moreover, vitamins, supplements, and other possible medications consumed by patients, which were not monitored, could introduce confounding in an observational study like ours. The same consideration applies to socioeconomic factors, dietary habits, or other healthrelated behaviours, as these data were not accessible and may have contributed to selection bias in individuals who opt to take substances like TUDCA, which could also coincide with other practices exerting a favourable influence on the disease.
As part of the limitations of our study, the alreadymentioned retrospective observational design, which entails irregular follow-ups, missing and non-uniform information for example for clinical scales (ALSFRS-r) or instrumental measures (FVC), impossibility to fully remove possible confounding factors, and, most importantly, immortal time bias when survival analysis is among prespecified outcome analysis. 29Nevertheless, our regional registry gathers a large amount of clinical information about patients with ALS, regularly verified and controlled by trained clinicians, allowing for a more accurate propensity score analysis of patients with ALS compared to previous reports. 24,25inally, the exploratory nature of the study, coupled with the limited sample size and underpowered analyses, prevents us from making conclusive determinations regarding outcome measures, especially concerning the assessment of adverse effects.
In summary, in our "real-world" study patients who received TUDCA at the higher dose survived longer. Since this was not a controlled study, we cannot rule out additional confounding factors but pending the results of ongoing phase III RCTs, this study seems to confirm current evidence from early trials. Our propensity score matched cohort study offers the advantage of longer follow-up than RCTs, allowing to measure survival, the most clinically meaningful outcome measure for assessing the benefits of ALS treatments, 30 although almost disused as the primary outcome in ALS trials. 22Further ongoing studies (NCT03800524, NCT05021536) will be crucial to verify TUDCA effects alone or in combination with PB.
Contributors EZ and JM had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. EZ and UM contributed equally as co−first authors. JM and GF contributed equally as co-senior authors.
Concept and design: EZ, JM, GF, UM, IM. Acquisition, analysis, or interpretation of data: All authors. Data verification:UM; JM. Drafting of the manuscript: EZ, JM, GF, UM. Critical revision of the manuscript for important intellectual content: MV, IM, NF, CS, GG, VV.
Data sharing statement
With publication, deidentified data and data dictionary will be shared with researchers who provide a methodologically sound proposal and will include investigator support to achieve aims in the approved proposal. Proposals should be directed toto gain access, data requestors will need to sign a data access agreement. Proposals may be submitted up to 36 months following article publication. After 36 months, the data will be available in our university's data warehouse but without investigator support other than deposited metadata.
Table 1 :
Based on the nature of the clinical variable under investigation, homogeneity between cases and controls was assessed by the Student's T test or chi-square test. The resulting p-values are representative of good homogeneity of clinical features among tested groups. Demographic and clinical characteristics TUDCA-treated and non-TUDCA-treated patients with ALS after matching.
Table 2 :
leading to conditional approval of the drug outside Europe, where instead a phase III trial is still ongoing. While evidence from phase III RCTs of the effects of TUDCA alone (ClinicalTrials.govIdentifier: NCT03800524) or in combination with phenylbutyrate (PB) (ClinicalTrials.govIdentifier: NCT05021536) is awaited, a potential advantage given by population-based studies is the possibility to examine treatment effects for Based on the nature of the clinical variable under investigation, the homogeneity between cases and controls was assessed by ANOVA or chi-square test. The resulting p-values are representative of good homogeneity of clinical features among tested groups.p-values inferior to 0.05 are reported in bold character. Clinical characteristics of patients with ALS stratified according to exposure to different dosages of TUDCA.
Declaration of interests EZ, UM, GF, IM, CS, GG, NF, AG, MC, ES, LZ, PA, EC, MV, SF, VV declare no conflicts of interest. JM reports receiving advisory board fees from Biogen, Amylix and Italfarmaco, grant support from Roche and from Pfizer (RAP-ALS study; drug furniture), all unrelated to this study. JM received grant support from Agenzia Italiana del Farmaco [grant number 2016-02364678], Italian Ministry of Health (bando per la ricerca finalizzata 2016, grant number RF-2016-02361616), and University of Modena and Reggio Emilia (bando FAR 2021, Progetti di ricerca Interdisciplinari Mission Oriented, NEURALS project), all unrelated to this study.
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Domain: Biology
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Five new synonyms for Impatiensprocumbens (Balsaminaceae) in China
Abstract In the revision on the genus Impatiens L. in China, we found that there were synonyms amongst some species. Impatiensprocumbens Franch. morphologically resembled I.reptans Hook.f., I.crassiloba Hook.f., I.ganpiuana Hook.f., I.atherosepala Hook.f. and I.rhombifolia Y. Q. Lu & Y. L. Chen. After a thorough morphological study, based on original literature, type specimens and field surveys, it was found that the above six species of Impatiens had no substantial differences in morphological characters and there was continuity in geographical distribution. Therefore, we determined that I.reptans, I.crassiloba, I.ganpiuana, I.atherosepala and I.rhombifolia are the synonyms of I.procumbens. At the same time, we present the color photographs, supplementary descriptions of morphology, and geographical distribution. The lectotype of I.procumbens and I.reptans are also designated here.
Introduction
In China, 352 species of Impatiens have been recorded, including 273 species endemic to China, which are concentrated throughout the Qinling Mountains, southern Tibet, the Hengduan Mountains, Yunnan-Guizhou-Guangxi karst region, the middle and lower reaches of the Yangtze River and other regions (Yuan et al. 2022). It is well known that Impatiens species are notoriously difficult to identify, because of their abundant character variations and morphological similarities, which makes the boundary between species very blurred (Grey-Wilson 1980;Cong 2007;Tian et al. 2007). From the perspective of research history, there were many factors in the early published species, such as the distance between collectors and researchers, the collection of specimens with the same number in different herbaria, the change of place names etc., all of which have led to taxonomic problems, for example, the same species with different names, the absence of characters, and incorrect records. Additionally, these classification problems have not been resolved so far, which is not conducive to the research of Impatiens, but also causes some obstacles in the research for identification of the genus Impatiens in China. I. procumbens was published by Franchet (1886) on the basis of specimens collected from Dali, Yunnan Province. I. reptans, I. crassiloba, I. ganpiuana, and I. atherosepala were described by J. D. Hooker, based on specimens collected from Guizhou Province by E. M. Bodinier and J. P. Cavalerie (Hooker 1908a, b). I. rhombifolia was published by Chen and Lu (1990), based on specimens collected from Mount Emei, Sichuan Province. Yu (2008) mentioned that I. reptans, I. ganpiuana, I. procumbens and I. rhombifolia were very similar in morphology and may be described repeatedly. Through extensive field investigations and textual research of specimens, it was found that there were no essential differences amongst the above six species. In addition, the guidelines and recommendations of Article 9 of the ICN (Turland et al. 2018) have been followed while designating the lectotype.
Materials and methods
For morphological comparisons, we reviewed the original literature and related records, including the original literature description of each species, information of type specimens, synonyms and geographical distribution. The main sources of original literature are from Tropicos ( [URL]), IPNI ( [URL]. org) and other websites. Otherwise, we also critically checked type specimens or high-resolution images of specimens involved in this study in BM, E, K, P, NY, WU, PE, IBSC, IBK, KUN, HGAS, GZAC, GZTM, SWFC and conducted fieldwork of type localities in Sichuan, Guizhou and Yunnan Provinces. We have obtained more than 10 field collections. Herbarium specimens were chosen carefully. We dissected the flowers of the plant in the field or in the habitat itself after collection of the plants. And various morphological characters, such as leaf size and shape, inflorescence type, flower color, etc., were carefully observed, measured and quality photographs were taken.
Results and discussion
After consulting the type specimens ( Fig. 1) of Impatiens procumbens from Dali, Yunnan, I. reptans from Guiyang, Guizhou (Fig. 2) and I. rhombifolia from Emei, Sichuan (Fig. 4B), as well as the specimens in domestic and foreign herbaria and relevant literature records, it was found that there were no obvious differences in morphology amongst them (Table 1).
In the process of textual research on the type specimen of Impatiens reptans (Figs 2, 5A) , we found that J. D. Hooker did not designate a holotype in keeping with the practice of the time, the specimen P00780766 ( Fig. 2A) agrees better with the information given in the literature and contains the pencil drawing of flower parts and the dissected flower parts pasted on the sheet. Therefore, it is designated here as the lectotype. We also found that the labelling information of the isolectotype (E00313595) was marked "An idem au no. 1782?". At the same time, the vernacular name "Impatiens ganpiuana Hf Vav" (Fig. 2B) was found on the label at the lower right corner. These two uncertainties point to the need for further textual research of I. ganpiuana. Meanwhile, the collection information marked on the type specimens of I. crassiloba (Fig. 4A) and I. ganpiuana (Fig. 4C) were the same, namely E. M. Bodinier 1782, the collection time of the latter being 9 August, 1897. Although there was no collection time on the specimen of the former, it could be inferred that the collection time may be from the same period according to the marked information that the specimens were received on 26 April 1898. Compared with the character description of the protologue, the differences mainly lay in the shape of the lower sepal and anther (Table 1), but by examining type specimens (Figs 4C, 5B), the shape of the lower sepal of I. ganpiuana should be cymbiform, so there was no obvious difference, except for the different anther. At the same time, we found that Impatiens atherosepala is relatively close to the above plants of genus Impatiens, the type locality actually being Pingfa, Guiding County, which the "Flora of China" (Chen et al. 2007) misquoted as Pingba. From the type specimen (Figs 4D, 5D), it can be seen that the typical features are leaves lanceolate, margin with spinescent-serrate, 1-flowered inflorescence and lateral sepals ovate, with long aristate. The population we found in Pingfa, Guiding County ( Fig. 6A-D) conformed to the description of these characters. Through extensive field investigations (Figs 6, 7), it was found that the leaf shape of genus Impatiens varied greatly and as a taxonomic character, it was not reliable. Meanwhile, the lateral sepals of I. procumbens, I. reptans, I. crassiloba, I. ganpiuana, I. atherosepala and I. rhombifolia had a tendency to extend and grow.
In addition, it can be seen from the type localities and other distribution points that the geographical distribution of these species is continuous and there is no obvious geographical isolation (Fig. 3).
It can be seen that there is no obvious difference in the morphology of the above six species and the geographical distribution is widespread. Since Impatiens procumbens is the earliest name published, we concluded that I. reptans, I. crassiloba, I. ganpiuana, I. atherosepala and I. rhombifolia are the synonyms of I. procumbens. Franchet (1886) did not specify the type specimen when publishing the I. procumbens. Four specimens (collection no. 1949, collected by M. I'Abb é Delavy) made of flowering plants collected on 16 November 1885 are now in P (P04543629, P04543628, P04543627, P04543626), of which specimen P04543626 (Fig. 1A) is more consistent with the information described in the protologue, as well as containing complete plant organs and collection information. Therefore, P04543626 is designated as the lectotype here and P04543627, P04543628 and P04543629 are the isolectotypes.\===
Domain: Biology. The above document has
* 2 sentences that start with 'At the same time, we',
* 2 sentences that start with 'Through extensive field investigations',
* 2 sentences that end with 'and geographical distribution'. It has approximately 1223 words, 107 sentences, and 11 paragraph(s).
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Insights into the Transcriptome of Human Cytomegalovirus: A Comprehensive Review
Human cytomegalovirus (HCMV) is a widespread pathogen that poses significant risks to immunocompromised individuals. Its genome spans over 230 kbp and potentially encodes over 200 open-reading frames. The HCMV transcriptome consists of various types of RNAs, including messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs), with emerging insights into their biological functions. HCMV mRNAs are involved in crucial viral processes, such as viral replication, transcription, and translation regulation, as well as immune modulation and other effects on host cells. Additionally, four lncRNAs (RNA1.2, RNA2.7, RNA4.9, and RNA5.0) have been identified in HCMV, which play important roles in lytic replication like bypassing acute antiviral responses, promoting cell movement and viral spread, and maintaining HCMV latency. CircRNAs have gained attention for their important and diverse biological functions, including association with different diseases, acting as microRNA sponges, regulating parental gene expression, and serving as translation templates. Remarkably, HCMV encodes miRNAs which play critical roles in silencing human genes and other functions. This review gives an overview of human cytomegalovirus and current research on the HCMV transcriptome during lytic and latent infection.
Introduction
The human cytomegalovirus (HCMV) belongs to the beta-herpesvirus subfamily and is a double-stranded DNA virus, infecting 40% to 60% of individuals in industrialized countries and up to 100% in developing countries. It is transmitted through body fluids, blood transfusion, and organ transplantation. While mostly asymptomatic in immunocompetent individuals, HCMV can remain latent after primary infection and reactivate during pregnancy or in individuals with cancer, transplanted organs, AIDS, or other immune deficiencies [1], leading to severe diseases in the lung, liver, colon, eye, or brain such as hepatitis, pneumonitis, colitis, and CMV retinitis [1]. Additionally, congenital CMV (cCMV) infection is a leading cause of birth defects, with approximately 10% of infants with cCMV displaying CNS impairments [2].
The mature HCMV virion contains a large linear double-stranded genomic DNA tightly intertwined and wrapped within a capsid, which is surrounded by a tegument layer and an envelope [3]. The HCMV genome is approximately 230 to 240 kbp in length,
HCMV Messenger RNA (mRNA)
The human cytomegalovirus (HCMV) was first discovered in 1881 [9]. Early sequencing and annotation of the laboratory strain of HCMV AD169 sequenced around 208 ORFs [10] (Figure 2), but subsequent re-evaluation estimated the number of protein-coding sequences to range from 164 to 220 [11][12][13][14][15][16]. Among these, 45 ORFs were found essential for viral replication in fibroblasts, while 107 were deemed nonessential [16]. However, recent studies have identified over 400 newly translated ORFs by ribosome profiling, bringing the total number to over 750 with many transcripts containing multiple translationally active ORFs [17]. Subsequently, a comprehensive analysis reported 248 transcription start sites, 116 transcription termination sites, and 80 splicing events within the HCMV genome. Furthermore, 291 previously undescribed or only partially annotated transcription isoforms were identified and annotated. Most of these transcripts were found to contain multiple translationally active ORFs [15], adding to the complexity of HCMV gene expression and regulation. While the functions of some HCMV genes remain unknown, significant progress has been made in identifying the functions of genes related to the infective stages [8]. In this review, we provide an overview of current research on the four different classes of HCMV transcripts and delve into their respective roles and functions.
HCMV Messenger RNA (mRNA)
The human cytomegalovirus (HCMV) was first discovered in 1881 [9]. Early sequencing and annotation of the laboratory strain of HCMV AD169 sequenced around 208 ORFs [10] ( Figure 2), but subsequent re-evaluation estimated the number of protein-coding sequences to range from 164 to 220 [11][12][13][14][15][16]. Among these, 45 ORFs were found essential for viral replication in fibroblasts, while 107 were deemed nonessential [16]. However, recent studies have identified over 400 newly translated ORFs by ribosome profiling, bringing the total number to over 750 with many transcripts containing multiple translationally active ORFs [17]. Subsequently, a comprehensive analysis reported 248 transcription start sites, 116 transcription termination sites, and 80 splicing events within the HCMV genome. Furthermore, 291 previously undescribed or only partially annotated transcription isoforms were identified and annotated. Most of these transcripts were found to contain multiple translationally active ORFs [15], adding to the complexity of HCMV gene expression and regulation.
The ORFs Are Color-Coded According to the Growth Properties of their Corresponding virus Gene Deletion Mutants
The expression of HCMV genes is temporally regulated, and it is divided into immediate early (IE), early (E), and late (L) gene expression [18] (Figure 3). IE genes encode regulatory trans-acting factors, while the E genes' expression requires the de novo expression The ORFs Are Color-Coded According to the Growth Properties of Their Corresponding Virus Gene Deletion Mutants The expression of HCMV genes is temporally regulated, and it is divided into immediate early (IE), early (E), and late (L) gene expression [18] (Figure 3). IE genes encode regulatory trans-acting factors, while the E genes' expression requires the de novo expression of IE genes. Late gene expression occurs after the onset of viral DNA replication [19,20]. Due to the complexity of the HCMV genome, the roles and protein-coding potentials of many ORFs remain largely unknown, warranting further investigation. Some major ORFs functions identified include protein coding, viral replication, and translation regulation.
The ORFs Are Color-Coded According to the Growth Properties of their Corresponding virus Gene Deletion Mutants
The expression of HCMV genes is temporally regulated, and it is divided into immediate early (IE), early (E), and late (L) gene expression [18] (Figure 3). IE genes encode regulatory trans-acting factors, while the E genes' expression requires the de novo expression of IE genes. Late gene expression occurs after the onset of viral DNA replication [19,20]. Due to the complexity of the HCMV genome, the roles and protein-coding potentials of many ORFs remain largely unknown, warranting further investigation. Some major ORFs functions identified include protein coding, viral replication, and translation regulation. Research has identified over 30 ORFs that are vital for viral replication. For example, the de novo synthesis of pUL21A promotes the synthesis of viral DNA, which is required for the late accumulation of IE transcripts and establishment of productive infection [21,22] ( Figure 2). UL123-coded 72-kDa IE1 also promotes viral replication and transcription by antagonizing histone deacetylation, whereas pUL76 has a dominant-negative effect on replication [23]. Furthermore, some HCMV genes are involved in the viral translation process. The HCMV gpUL4 mRNA contains a 22-codon upstream open-reading frame (uORF2) whose product represses downstream translation by blocking translation termination and causing ribosomes to stall on the mRNA [24,25]. HCMV pUL38 preserves mTORC1 kinase activity that promotes translation initiation [26]. Moreover, pUL38 and pUL69 support translation by antagonizing the mTOR target 4EBP1 [27]. PTRS1 enhances Research has identified over 30 ORFs that are vital for viral replication. For example, the de novo synthesis of pUL21A promotes the synthesis of viral DNA, which is required for the late accumulation of IE transcripts and establishment of productive infection [21,22] ( Figure 2). UL123-coded 72-kDa IE1 also promotes viral replication and transcription by antagonizing histone deacetylation, whereas pUL76 has a dominant-negative effect on replication [23]. Furthermore, some HCMV genes are involved in the viral translation process. The HCMV gpUL4 mRNA contains a 22-codon upstream open-reading frame (uORF2) whose product represses downstream translation by blocking translation termination and causing ribosomes to stall on the mRNA [24,25]. HCMV pUL38 preserves mTORC1 kinase activity that promotes translation initiation [26]. Moreover, pUL38 and pUL69 support translation by antagonizing the mTOR target 4EBP1 [27]. PTRS1 enhances translation through both PKR-dependent and PKR-independent mechanisms, limiting the host's antiviral response [28].
HCMV Long Non-Coding RNAs (lncRNAs)
Long non-coding RNAs (lncRNAs) are a class of transcripts that consist of over 200 nucleotides but do not encode proteins. Within the context of HCMV, four main lncRNAs, namely RNA1.2, RNA2.7, RNA4.9, and RNA5.0, account for over 50% of the poly (A)+ viral transcriptome in all infection states ( Table 2). Among these lncRNAs, RNA1.2, RNA2.7, and RNA4.9 have been found to play important roles in the overall HCMV viral life cycle, particularly during lytic replication [5]. However, further investigation is still required to fully understand the detailed functions of lncRNAs in HCMV. Here, we aim to provide a comprehensive summary of the existing research on the four HCMV long non-coding RNAs and their potential contributions to the virus's replication.
RNA1.2
RNA1.2 is among the earliest HCMV transcripts to be discovered and accounts for approximately 7.9% of viral polyA RNA transcription [12]. Although many of its functions are still unknown, it is likely that lncRNA1.2 does not play a large role in the main processes of viral production, such as entry, genome replication, virion assembly, and egress. However, research has indicated that RNA1.2 does have important functions in modulating the expression of multiple cellular genes and facilitating the evasion of acute antiviral responses. One of RNA1.2's roles involves downregulating TPRG1L, which in turn blocks NF-κB and suppresses both the expression and secretion of proinflammatory mediators like IL-6 [43]. As a result, further investigation into RNA1.2 could potentially contribute to the development of treatments for IL-6-associated illnesses. Additionally, lncRNA1.2 generates multiple natural antisense transcripts (NATs) during the late infection stage of HCMV. While it has been found that RNA1.2 ASTs (antisense transcripts) play a role in regulating sense strand expression, further research is necessary to determine the importance of RNA1.2 ASTs in the regulation of the expression of the RNA1.2 gene [44].
RNA2.7
The HCMV lncRNA2.7 is the most abundant lncRNA, occupying approximately 29% of the total poly (A) viral transcriptome [5]. Extensive research indicates that this lncRNA has an important role during infection, particularly in promoting the movement and detachment of infected cells during late infection [517]. Specifically, RNA2.7 facilitates cell movement and viral spread during late infection by stabilizing mRNAs that are rich in A and U nucleotides. It also regulates a large number of cellular genes late in the lytic infection, many of which are associated with encouraging cell movement [517]. Additionally. RNA2.7 has been shown to increase cell-to-cell viral transmission, which is likely because of its role in facilitating cell movement [517]. Moreover, research suggests that RNA2.7 may also be involved in the processes related to latency or reactivation, such as cellular transcription and cell cycle progression. Additionally, it contributes to boosting viral replication by reducing the host's response to infection through repressing Pol II S2 phosphorylation [42]. While some functions and roles of lncRNA2.7 have been revealed, like other HCMV lncRNAs, further research is still required to fully understand its importance and the intricate mechanisms by which it influences various aspects of the viral life cycle.
RNA4.9
Unlike the other three HCMV lncRNAs, which are predominantly localized in the cytoplasm, RNA4.9 is uniquely distributed in the viral replication compartment. RNA4.9 is transcribed in this compartment during early infection, and its levels increase as infection progresses [192]. One notable feature of RNA4.9 is its ability to form RNA-DNA hybrids (R-loops) through its G+C rich region. This interaction may be involved with the initiation of DNA replication [518], as a reduction in RNA4.9 expression correlates with decreased viral DNA replication. This finding strongly suggests that RNA4.9 plays a direct role in viral DNA replication and growth [192]. In addition to its role in viral DNA replication, RNA4.9 may be involved in HCMV latency. The lnc4.9 RNA has been found to associate with the polycomb repressor complex 2 (PRC2) [519]. In herpes simplex virus (HSV), PRC2 plays a role in regulating viral latency [191]. This association raises the possibility that RNA4.9 might play a role in HCMV latency as well. Further research on whether virus mutants that do not express RNA4.9 fail to establish and maintain latency could provide more insight into the role of RNA4.9 in HCMV latency [520].
RNA5.0
The lncRNA5.0 is a stable intron expressed during HCMV infection that is transcribed by RNA polymerase II and characterized by a high adenine and thymine nucleotide content [5,521]. However, compared to other HCMV lncRNAs, the expression of RNA5.0 is much lower than other HCMV lncRNAs, accounting for approximately 0.1% of the total viral transcriptome, and it is not present in the poly (A)+ viral transcriptome since it does not contain a poly (A) tail [5]. RNA5.0 is primarily localized in the nucleus during viral infection and lacks potential protein-coding ORFs [521]. While the exact functions of RNA5.0 remain largely unknown, research suggests that RNA5.0 may not be necessary for lytic replication and the maintenance of latent reservoirs, unlike the HCMV lncRNAs RNA1.2, RNA2.7, and RNA4.9 [5]. However, despite its relatively low expression and lack of its exact functions, lnc5.0 RNA may play a role in activating transcription, regulating gene silencing, or impacting HCMV latency. It could also function in an important role like immune evasion that is important for infection of host organisms but not in cultured cells [521]. Given the limited knowledge about lnc5.0 RNA's precise functions, further investigation is necessary to elucidate its role in HCMV infection fully.
HCMV Circular RNAs (circRNAs)
Circular RNAs (circRNAs) are a unique class of RNA molecules formed through back splicing, resulting in covalently closed loops that lack a 5 cap and a 3 poly (A) tail [522]. Due to their circular structure, circRNAs are more resistant to exoribonuclease (such as RNase R) than linear RNAs [522]. CircRNAs have been identified in all kinds of cells and demonstrated to be associated with different diseases, indicating that they possess important biological functions. CircRNAs can function as microRNA (miRNA) sponges, regulate of parental gene expression, and even serve as translation templates [522,523]. They have also been identified from DNA virus-infected cells, such as Epstein-Barr virus (EBV) [524][525][526][527], Kaposi Sarcoma herpesvirus (KSHV) [525,[528][529][530], human papillomaviruses (HPVs) [531] and RNA viruses, severe acute respiratory disease coronavirus 2 (SARS-CoV-2) [532] and murine hepatitis virus (MHV) [533]. This suggests that circRNAs may play important roles in the viral life cycle and infection processes.
In our previous study, we bioinformatically predicted 704 candidate circRNAs encoded by the HCMV TB40/E strain and 230 encoded by the HCMV HAN strain (Figure 4) [6]. Furthermore, we experimentally confirmed 324 back-splice junctions (BSJs) from three HCMV strains, Towne, TB40/E, and Toledo. A newly published work by Deng et al. also experimentally confirmed 629 HCMV circRNAs from the HAN strain [534]. More importantly, we found 12 circRNAs with over-alignment lengths of 40 bp from 60 bp BSJ sequences that were conserved in both the HAN and TB40/E strains and also expressed in several cell types, suggesting these circRNAs are selected and play important roles (Table 3). Functional analysis of HCMV circRNAs in a competitive endogenous RNA co-regulatory network shows that HCMV circRNAs are involved in a complex and multifaceted interaction network. CircRNAs are an important component of the HCMV transcriptome, and further mutagenesis studies on HCMV circRNA biogenesis may reveal the role played by HCMV circRNAs in terms of viral replication, latency, reactivation and host cells.
several cell types, suggesting these circRNAs are selected and play important roles (Table 3). Functional analysis of HCMV circRNAs in a competitive endogenous RNA co-regulatory network shows that HCMV circRNAs are involved in a complex and multifaceted interaction network. CircRNAs are an important component of the HCMV transcriptome, and further mutagenesis studies on HCMV circRNA biogenesis may reveal the role played by HCMV circRNAs in terms of viral replication, latency, reactivation and host cells. About 60 nt sequences around the back-splice junction points of the HAN and TB40/E strain circR-NAs were compared using blastn (BLAST) [6]. About 60 nt sequences around the back-splice junction points of the HAN and TB40/E strain circRNAs were compared using blastn (BLAST) [6].
HCMV microRNA (miRNA)
HCMV microRNAs (miRNAs) are small non-coding RNA molecules that consist of approximately 22 nucleotides and distributed throughout the HCMV genome. They account for around 80% of total HCMV reads obtained from deep sequencing [7,535]. HCMV encodes 17 known mature miRNAs from 11 precursors (Table 4). In addition, recent research has identified 10 new HCMV miRNAs, 4 from known precursors and 6 from new precursors, bringing the total number of mature miRNAs to 22 from 13 different precursors [20,535,536]. The high expression of miRNAs in the HCMV genome also suggests that they play an important biological role during infection [535].
Viral miRNAs from other herpesviruses like EBV and HSV have promoted the establishment and maintenance of latency. HCMV miRNA may have similar functions [537]. Additionally, miRNAs are non-immunogenic and capable of targeting multiple cellular and viral transcripts, providing an effective means for HCMV to manipulate viral gene expression and cellular signaling pathways during both lytic and latent infection [538]. By targeting numerous cellular genes and modulating the host's signaling pathways, HCMV miRNAs contribute to viral survival and replication [7]. HCMV miRNAs can also silence human genes involved in various physiological processes and attenuate the expression of immediate early (IE) proteins, which are vital for lytic replication. Overall, miRNAs are an important component of the HCMV genome.
Furthermore, research suggests that HCMV miRNAs have the potential to be involved in the development and progression of human diseases [7]. For instance, HCMV miR-US33-5p was found to influence the apoptosis of human aortic vascular smooth muscle cells (HA-VSMC) and was more abundant in the plasma of patients with acute aortic dissection (AAD) [539]. This indicates that HCMV miRNAs might have implications in the pathogenesis of certain human diseases, offering new possibilities for potential treatment alternatives. Understanding the functions and roles of HCMV miRNAs not only provides valuable insights into how the virus operates but also opens up new avenues for exploring therapeutic strategies for HCMV-associated diseases. Further research in this area may reveal novel targets for intervention and management of HCMV infections and related health conditions. MiRNAs were downloaded from miRbase database, which is a searchable database of published miRNA sequences and annotation [540].
HCMV Gene Expression during a State of Latency
HCMV establishes latency primarily in early myeloid lineage cells [541,542], such as CD14+ monocytes and CD34+ hematopoietic progenitor cells [543]. The transcriptome of latent HCMV is very challenging to define, in part because of the scarcity of latently infected cells and the lack of a suitable model. The fate of the virus is determined by the type of infected cells, where the infection of fibroblast cells leads to the production of infectious progeny virus, while the infection of myeloid progenitor cells leads to virus latency, which is acharacterized by the maintenance of the viral genome in the absence of active virus infection or replication. The molecular mechanisms governing viral latency are poorly understood. It has been reported that the HCMV transcriptome during latency is qualitatively different from the lytic cycle transcription profile [544]. Studies using a virus gene-specific microarray have identified latency-associated genes in HCMV-infected myeloid progenitor cells [545,546]. Additionally, using nested PCR, researchers have identified several viral genes with distinct transcriptional profiles during virus latency [544,547]. The transcriptomic profiling of HCMV-infected CD34+ cells and CD14+ monocytes led to the identification of around 20 genes that were associated with latent viral infection [191]. Moreover, the single-cells transcriptomic profiling of latently infected monocytes found a cellular heterogeneity in response to latent virus infection [548,549].
A number of genes including UL138 and LUNA are present during latent virus infection [191,550]. Other genes such as UL144, the IE1 region, UL111A, US28, and noncoding RNAs 4.9 and 2.7 were also expressed during the lytic as well as latent virus phases [322,546,551,552]. It has been hypothesized that lytic genes are expressed during an early phase of viral latency and then repressed over time [553]. Furthermore, research suggests that the heterochromatinization of viral DNA takes place to repress gene transcription during latency. Some studies have shown that signaling pathways mediated through platelet-derived growth factors (PDGFR), epidermal growth factor (EGFR), and PI3K along with the downregulation of IE1/2 expression, UL138 upregulation, and perturbation of cytokine expression leads to viral latency [554][555][556]. In addition to viral genes, HCMVencoded miRNAs have been shown to have important roles in the establishment of latency. They include miR-UL148D and miR-UL112-1. Another miRNA, has-miR-s200, was also found to play an important role in HCMV latency [557].
It has been reported that MIEP is the master regulator of latency in infected cells. In latently infected cells, MIEP is heterochromatinized, suggesting a latency-specific [18,558,559]. The accumulating evidence suggests that the transcriptomic profiling of latent HCMV has heterogeneity and is poorly defined. Moreover, the exact cause of transcriptional repression of virus gene transcription during latency is unclear, and the involvement of other viral and cellular factors in the establishment of virus latency needs to be identified to better understand this complex process.
Conclusions
Indeed, human cytomegalovirus (HCMV) infection can vary greatly depending on the individual's immune status. While it remains latent and asymptomatic in many healthy individuals, HCMV poses a significant health risk for those who are immunocompromised, such as transplant recipients, HIV patients, and infants with congenital infections. Research on the HCMV transcriptome, including mRNAs, lncRNAs, circRNAs, and miRNAs, has provided valuable insights into the complex interactions between the virus and its host. These different types of RNAs play diverse and overlapping functions in HCMV infection, contributing to various aspects of the virus life cycle, including replication, latency, reactivation, immune regulation, protein coding, and cell movement. Despite significant progress in understanding the HCMV transcriptome, there are still areas of the HCMV transcriptome that are not fully investigated. Further research on HCMV pathogenesis and its transcriptome may lead to a better understanding of human cytomegalovirus as well as insights into effective treatments for HCMV diseases. This knowledge can potentially lead to the development of more effective treatments for HCMV-related diseases, especially for immunocompromised patients and infants at risk of congenital infections.
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Domain: Biology
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Determination of shelf life of four herbal medicinal products using high-performance liquid chromatography analyses of markers and the Systat Sigmaplot software
Doris Kumadoh1*, Kwabena Ofori Kwakye2, Noble Kuntworbe2, Ofosua Adi-Dako3, James Addy Appenahier1 1Centre for Plant Medicine Research, Mampong Akuapem, Ghana. 2Department of Pharmaceutics, Faculty of Pharmacy and Pharmaceutical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. 3Department of Pharmaceutics and Microbiology, School of Pharmacy, University of Ghana, Accra, Ghana.
INTRODUCTION
Finished herbal products may be defined as herbal preparations made from one or more herbs which may contain excipients (World Health Organization, 2007a). Examples include decoctions, powders, teas, tinctures, herbal capsules, herbal tablets, herbal ointments, and creams. Finished herbal products are unique compared to synthetic products due to the varied nature of constituents that may be present even in an herbal product which claimed to contain only one active ingredient (Bankoti et al., 2012). The herbal material in its entirety is normally regarded as the active ingredient. It is essential that herbal products contain the right constituents in the right quantities, whether this is a particular herb or a particular amount of a specific herbal component (Benzie and Watchtel-Galor, 2011;World Health Organization, 2007a;2007b).
The World Health Organization (WHO) recommends that stability data are provided to support the shelf life proposed for finished herbal products under the specified conditions of storage (World Health Organization, 2007b). The shelf life of a product may be defined as the period, during which it remains within specification with respect to chemical, physical, and microbiological stability, if stored correctly (Bouwman et al., 2015). The expiry date is normally represented on the product to indicate the end of the shelf life (Tiwari, 1995). The determination of the constituents with known therapeutic activity will not usually be sufficient since other constituents may be contributing to stability of the product (Awang, 2004). Constituents (markers) for various determinations in herbal products may be categorized as chemical, analytical, and active markers (European Medicines Agency, 2009;World Health Organization, 2007a, 2007b. Chemical markers are normally chemically defined as constituents or groups of constituents of an herbal medicinal product, which are of interest for quality control purposes regardless of whether they possess any therapeutic activity or not (European Medicines Agency, 2009). The quantity of a chemical marker may be an indicator of the quality of an herbal medicine. Chemical markers may be used to evaluate the product quality and stability over time and determine the recommended shelf life (Bodhisattwa et al., 2011). Analytical markers are the constituents or group of constituents that serve solely for analytical purposes (Kruse et al., 2013). Active markers are the constituents or group of constituents that contribute to therapeutic activities (European Medicines Agency, 2009;World Health Organization, 2007a) In general, "significant change" of a finished herbal product may be defined as a 10% change in assay from its initial value with respect to the marker being used or failure to meet the acceptance criteria for potency when using biological or immunological procedures. Considerations are also given to any degradation product exceeding its acceptance criterion or failure to meet the acceptance criteria for physical attributes and functionality tests (including color, phase separation, resuspendibility, caking, hardness, dose delivery per actuation, and pH) (Kruse et al., 2013). It should be noted that the accelerated stability tests may cause some dosage forms such as ointments and creams to change the form due to the relatively high temperatures that are employed. This should not be mistaken for failure of the product to meet the acceptance criteria since such changes should be expected (Aulton, 2007;European Medicines Agency, 2009;Food and Drugs Authority, 2012;Winfield et al., 2009).
Nibima and Asena are two herbal decoctions used at the Centre for Plant Medicine Research (CPMR). Nibima which contains Cryptolepis sanguinolenta is used in the treatment of malaria, whereas Asena which contains Khaya senegalensis, Kigelia africana, Nauclea latifolia, Clausena anisata, Piliostigma thonningii, Trichilia monadelpha, and Strophanthus hispidus is used in the treatment of arthritis and general body pains. The main active component of the C. sanguinolenta is cryptolepine, which is an organic heterotetracyclic and indole alkaloid (Downum et al., 2013;Ofori, 2010). Asena which is multiherbal in nature has not had its main active component yet established though the preparation is known to have analgesic and anti-inflammatory properties (Donkor et al., 2013). Lippia tea is a powder for tea made from Lippia multiflora used in the treatment of stress and mild hypertension. The major components of the herbal infusion of L. multiflora are phenylethanoid glycosides, including verbacoside, isoverbacoside, nuomioside, and isonuomioside (Arthur et al., 2011). NPK 500 is an herbal capsules made from Cassia sieberiana used in the treatment of pains due to stomach ulcer and menstruation. C. sieberiana is generally known to contain calcium oxalate crystals in abundance with other chemical components such as flavones (quercitrin and isoquercitrin) and an anthraquinone (rhein) (Neuwinger, 1996;Nefatti et al., 2017). These four products have been used for at least two decades at the outpatient clinic of the Centre for Plant Medicine Research, Mampong-Akuapem, Ghana. The above-mentioned disease conditions are among the top ten medical conditions treated at the outpatients' clinic of the CPMR over a decade (CPMR, 2015). The determination of the shelf life of the products is essential as they are now prepared on commercial scale indicating the possibility of longer storage periods. No previous methods have been described before for the analyses of shelf life of all the four products.
The aim of this study is to determine the shelf life of three selected batches of the four products using HPLC analytical parameters.
Preparation of reference samples of products
Batch blending was employed for the preparation of the reference samples (Chattopadhyay, 2013;World Health Organization, 2007a). Five different batches (2 l each) of each of the products Nibima and Asena were prepared according to classified formulae and blended. In the case of Lippia tea, five different batches (500 g each) of the plant material were pulverized for infusion and were blended and used to prepare an infusion according to the label stated conditions. In the case of NPK 500, an extract was obtained from blending of five different batches (500 g each) of the processed material for encapsulation by extracting in distilled water at 37°C for 45 minutes and straining. The various blends were subsequently freeze dried (Heto PowerDry, LL300, Denmark) and stored in tightly closed foil-covered glass containers in a freezer at −20°C (NORD, Ghana) for subsequent work.
Determination of UV maximum wavelength of absorption of reference samples of products
The maximum wavelength of absorption (λ max ) was determined from the obtained spectra by scanning solutions (Nibima: 250 µg/ml, Asena: 350 µg/ml, Lippia tea: 110 µg/ml, and NPK 500: 55 µg/ml) of reference samples of the products in distilled water using a UV-Vis Spectrophotometer (Merck industries, Germany) through a range of 190-500 nm using quartz cuvettes over a path length of 1 cm.
The HPLC selected marker calibration plot was made using the reference samples of the product at various concentrations from 40 to 400 µg/ml for Nibima, 100 to 1200 µg/ml for Asena, 12.5 to 87.5 µg/ml for Lippia tea, and 10 to 100 µg/ml for NPK 500.
Determination of limits of detection and quantification
The limit of detection (LOD) and limit of quantification (LOQ) of the developed HPLC methods were determined from the linear regression curve obtained from the calibration plots of solutions of reference samples of products. The slope and standard deviations of the y-intercepts obtained from the linear regression line were used. The formulae for the calculation of the LOD and LOQ were defined as follows: where S represents the slope of the regression line, and δ represents the standard deviations of the y-intercepts of the various regression lines.
Determination of range of developed methods
Different solutions of concentrations of 200, 600, 50, and 60 µg/ml of reference samples for Nibima, Asena, Lippia tea, and NPK 500, respectively, were prepared. A range of solutions with concentrations of 80%-120% (80%, 100%, and 120%) were prepared from each reference sample solution. The prepared solutions were analyzed using the developed methods. Triplicate determinations were made for each solution, and the mean percentage recovery and relative standard deviation (RSD) were calculated from resulting chromatograms.
Determination of precision of developed methods
This procedure helps to determine the precision of readings done at different times during the same day or on different days using varying concentrations of the same sample. Hence, intra-and interday precisions were assessed.
Intraday precision
The solutions of three different concentrations (100, 200, and 300 µg/ml for Nibima; 300, 400, and 500 µg/ml for Asena; 40, 50, and 60 µg/ml for Lippia tea; and 50, 60, and 70 µg/ml for NPK 500) were prepared from the reference samples of the products. The various prepared solutions were analyzed thrice during a particular day to obtain chromatograms, from which percentage recoveries and RSDs were calculated.
Interday precision
The solutions of concentrations of 200, 600, 50, and 60 µg/ml were prepared from reference samples of Nibima, Asena, Lippia tea, and NPK 500, respectively, on three consecutive days and analyzed using the developed HPLC methods to obtain chromatograms, from which percentage recoveries and RSDs were calculated.
Determination of specificity of developed methods
This was done to ensure that there was insignificant interference of any analyte from the solvent system being used as mobile phase. The mobile phase (blank) was injected, and the resulting chromatogram was analyzed, followed by an injection of a sample solution of prepared reference samples of concentrations of 200, 600, 50, and 60 µg/ml for Nibima, Asena, Lippia tea, and NPK 500, respectively. After 20-minute wash period, the mobile phase was analyzed again, and the results were recorded.
Determination of robustness of developed methods
The robustness of the method was determined by varying the flow rates and wavelengths of the detector responses within a range of ± 0.2 ml/minute and ± 5 nm, respectively, while keeping other composition parameters constant. Percentage recoveries and RSD of the responses obtained from the resulting chromatograms from triplicate determinations were then done.
Determination of stability of solution of reference samples
The stability of solutions of all reference samples was studied over a period of 10 hours by triplicate injections for every 2 hours. The results of peak area were obtained from resulting chromatographs, and the subsequent analyses of percentage recovery and RSD of obtained responses were done.
Sampling of products from commercial batches for stability studies
All batches of products used in the formulation studies were produced on commercial scale. Products were randomly sampled from the produced commercial batch at the production unit using the formula n* = √N + 1, where n* is the number of samples to be taken rounded up to a whole number and N is the number of bottles, vials of capsules, and sachets in the commercial batch. Three batches were selected for the determination of the stability profile (British Pharmacopoeia, 2013). Table 1 shows the quantities of products collected from commercial batches for stability studies.
HPLC analyses of products in stability studies
The developed and validated methods for the reference samples were used in the analyses. The procedure was repeated for all three stability study batches of all products at time points of 0, 3, 6, 12, and 18 months for samples stored at 30°C ± 2°C/70% RH ± 5% RH (European Medicines Agency, 2006). The samples were stored in a stability chamber (Memmert, Germany). The estimated concentrations prepared for samples were 400 µg/ml (Nibima and Asena), 50 µg/ml (Lippia tea), and 40 µg/ml (NPK 500 capsules).
Statistical analyses and analytical software used
GraphPad Prism Version 6 for Windows (GraphPad Software, San Diego California, USA, www.graphpad.com) was used in the plotting of calibration plots, and the subsequent linear regression analyses were used in the determination of the equations of the calibration plots. Systat SigmaPlot Version 14 (www. systatsoftware.com) for shelf life was used in the determination of the shelf life(s) of the products.
RESULTS AND DISCUSSION
The UV spectrum of the aqueous solution of the reference sample of Nibima in Figure 1 indicates three major peaks appearing at 230, 289(λ max), and 366 nm, respectively. The UV spectrum of the aqueous solution of the reference sample of Asena in Figure 2 also indicates two major peaks appearing at 230 and 291 nm (λ max ), respectively. Two major peaks appearing at 230 and 327 nm were also observed as shown in Figure 3 when the UV scan of a solution of the reference sample of Lippia tea was done. Finally, Figure 4 also shows two major peaks appearing at 230 and 289 nm (λ max ), respectively, which were observed from the characteristic UV profile obtained from the scan of NPK 500 capsules. The UV spectra of all the reference samples of products indicate the presence of a 230 nm peak in addition to other peaks for all products. The appearance of the 230 nm peak in the spectra may be linked to the presence of a plant constituent (s). Reducing sugars are known to have an anomeric carbon with a hydroxyl group attached that can reduce other compounds to carboxylic acids (Seager and Slabaugh, 2000). In another study involving the evaluation of ultraviolet, visible, and near-infrared spectroscopy for the analysis of wine, 202 and 230 nm were the peaks with the highest responses in the UV region. It is suggested that these peaks are relative to carboxyl groups of organic acids (Martelo-Vidal and Vázquez, 2014).
The HPLC profile of the solution of the reference sample of Nibima as shown in Figure 5 indicates two major peaks represented as LDE/001 A and LDE/001 B, respectively. LDE/001 B was selected as a marker of choice for further analyses due to it being known as an active marker (cryptolepine) for the product (Ofori, 2010). The HPLC profile of the solution of the reference sample of Asena as shown in Figure 6 indicates one major peak at a retention time of 6.13 minutes, which was used as a marker of choice for further analyses in the stability studies. The chemical structure of the marker has, however, not only been established but also may be derived from any of the seven plant materials used in the formulation. The HPLC profile of the solution of the reference sample of Lippia tea as shown in Figure 7 also indicates one major peak appearing at a retention time of 2.97 minutes, which was used as a marker of choice for further analyses in the stability studies. This marker may be one of the major components of the herbal infusion of L. multiflora such as verbacoside, isoverbacoside, nuomioside, or isonuomioside (Arthur et al., 2011). Finally, the HPLC profile of the solution of a reference sample of NPK 500 capsules as shown in Figure 8 indicates one major peak appearing at a retention time of 2.82 minutes, which was used as a marker of choice for further analyses in the stability studies. This marker may be one of the major chemical components, such as quercitrin, isoquercitrin, or rhein known to be present in the root bark of the plant C. sieberiana (Neuwinger, 1996;Nefatti et al., 2017). The development and validation of HPLC methods are an essential aspect in the analyses of herbal medicinal products due to their complex nature (Wagner et al., 2011). HPLC is a column chromatographic separation technique that helps to identify various markers that may be present in the herbal product using various detectors including UV-Visible, photodiode array detector, fluorescence detector, conductivity detector, refractive index detector, electrochemical detector, mass spectrometer detector, and evaporative light-scattering detector (Pathy et al., 2013). The detection of the compounds is based on the mobile and stationary phases being employed together with the detection method. An initial UV spectrum gives an idea as to what range of wavelength should be used in the HPLC determination of an herbal extract making the HPLC method development and validation method more easily carried out since most laboratories use the UV-Vis method of detection (Ofori, 2010).
The complexity of components in an herbal medicine makes various spectrophotometric methods useful in the determination of spectra to be used as a standardization tool. The UV-visible spectrophotometric method provides spectra with a maximum wavelength of absorption for the herbal product or extract. The markers identified by UV-visible spectrophotometric technique are normally a myriad of compounds which can absorb light at the particular wavelength recorded. The results obtained help to develop further methods for isolation and purification of the herbal extract (Joshi, 2012). Table 2 shows the linear regression equations, linearity, LOD, and LOQ of reference samples in HPLC method validation. The specificity determination showed the HPLC method to be specific for the markers in the samples. Two major peaks were obtained with Nibima (200 µg/ ml) at retention times of 2.27 and 4.02 minutes, whereas Asena (600 µg/ ml), Lippia tea (50 µg/ml), and NPK 500 capsules (40 µg/ml) produced single peaks at retention times of 6.13, 2.97, and 2.82 minutes, respectively. No significant peaks were detected when blank mobile phase solvent was injected. The HPLC method was robust within the wavelength range of 278-332 nm for all the samples, producing percentage recoveries in excess of 98% for all samples. The relative standard deviation of the percentage recovery was between 0.51 and 0.91. In addition, a comparative result was obtained when the flow rate was varied between 0.6 and 1.0 ml/minute. Table 3 shows the determination of a range of developed HPLC methods, Table 4 shows the determination of intraday precision using three different concentrations of reference samples analyzed at various times during the day, Table 5 shows the determination of interday precision of developed HPLC methods for various products, and Table 6 shows the determination of stability of developed HPLC methods. Table 7 shows the mean normalized content of products with time in the stability study. To predict the shelf life of the products, changes in the HPLC selected marker contents were analyzed with time. The stability of herbal products with time is very critical in the quality assurance of products and the subsequent determination of the shelf life. However, the complex nature of most medicinal products of herbal origin makes it very challenging to determine specific ranges and acceptance criteria for the assessment of the stability profiles (Kruse et al., 2013) The establishment of monographs for products which may take several years is an important aspect to allow a set criterion, from which various parameters may be assessed. In the case of most herbal products used, especially in the developing countries (Calixto et al., 2003), monographs are yet to be established as is the case of the selected products Nibima, Asena, Lippia tea, and NPK 500 capsules. Using the HPLC marker content analyses and subsequent Systat SigmaPlot for a shelf life of obtained results, the shelf life(s) obtained were 23.14, 21.16, 62.97 and 32.91 months for Nibima, Asena, Lippia tea, and NPK 500 capsules, respectively.
The relatively better stability of the powder and capsule product compared with the decoctions is evident in this result. The shelf life of every product is unique based on the considered factors in its manufacture and storage (Aulton, 2007).
Limitation of study
Although the HPLC marker used in the analyses of the product was an active marker (cryptolepine), markers used in the study of the other three products such as Asena, Lippia tea, and NPK 500 capsules were analytical in nature. The determination of the shelf life of the products was limited to the randomly selected three primary batches of each product as per product. The determined shelf life obtained was extrapolated based on an 18-month study.
Real-time study covering the entire time beyond the obtained shelf life should be done to validate shelf life of products.
CONCLUSION
The HPLC method was used efficiently for the analysis of herbal markers of the products Nibima, Asena, Lippia tea, and NPK 500 capsules. Shelf life(s) of Nibima, Asena, Lippia tea, and NPK 500 capsules was successfully determined. The predicted shelf life for the products is 23.14, 21.16, 62.97, and 32.91 months for Nibima, Asena, Lippia tea, and NPK 500 capsules, respectively. PD/001 powder and CP/001 capsules are relatively more stable compared to LDE/001 and LDE/002 decoctions. The obtained shelf life indicates the relative stability of the products. Table 7. Mean normalized content of products with time in stability study. MN content (%) represents the mean normalized content of the three tested batches. SD represents the standard deviation of the mean. p values from linear regression and correlation analyses using paired t test; <0.0001 for Nibima, Asena, Lippia Tea, and NPK 500 capsules.
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Domain: Biology
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Post-COVID-19 Parkinsonism and Parkinson’s Disease Pathogenesis: The Exosomal Cargo Hypothesis
Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease after Alzheimer’s disease, globally. Dopaminergic neuron degeneration in substantia nigra pars compacta and aggregation of misfolded alpha-synuclein are the PD hallmarks, accompanied by motor and non-motor symptoms. Several viruses have been linked to the appearance of a post-infection parkinsonian phenotype. Coronavirus disease 2019 (COVID-19), caused by emerging severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, has evolved from a novel pneumonia to a multifaceted syndrome with multiple clinical manifestations, among which neurological sequalae appear insidious and potentially long-lasting. Exosomes are extracellular nanovesicles bearing a complex cargo of active biomolecules and playing crucial roles in intercellular communication under pathophysiological conditions. Exosomes constitute a reliable route for misfolded protein transmission, contributing to PD pathogenesis and diagnosis. Herein, we summarize recent evidence suggesting that SARS-CoV-2 infection shares numerous clinical manifestations and inflammatory and molecular pathways with PD. We carry on hypothesizing that these similarities may be reflected in exosomal cargo modulated by the virus in correlation with disease severity. Travelling from the periphery to the brain, SARS-CoV-2-related exosomal cargo contains SARS-CoV-2 RNA, viral proteins, inflammatory mediators, and modified host proteins that could operate as promoters of neurodegenerative and neuroinflammatory cascades, potentially leading to a future parkinsonism and PD development.
Introduction
Parkinsonism is a clinical syndrome defined by the presence of resting tremor, bradykinesia, rigidity and postural instability [1]. These motor symptoms are characteristically observed in Parkinson's disease (PD) [2], which remains the primary cause of parkinsonism, but there are other disorders with the same symptoms that mirror it [3,4]. PD is the second most prevalent neurodegenerative disease worldwide after Alzheimer's disease (AD) structures [101,102] and they constitute principal areas of LB accumulation, even at the earliest stages of disease development [91]. In vitro research has shown that pathological α-syn may spread from the gut to the brain through the vagus nerve, with DMV being the first area of the brain to be impacted. From there, α-syn can spread to other PD brain regions including the SNpc, resulting in dopaminergic neuron loss and the appearance of the parkinsonian phenotype [103]. Interestingly, the vagus nerve has been proposed as a pathway through which SARS-CoV-2 can retrogradely invade the CNS, thus enhancing its neuroinvasiveness [104,105].
Importantly, other GI manifestations, such as diarrhea, emerged as common clinical symptoms of COVID-19, while SARS-CoV-2 RNA detection in fecal samples may persist post-infection [106]. On top of that, gut microbiota imbalance due to extrapulmonary SARS-CoV-2 infection has also been observed in COVID-19 [107,108]. This warrants further investigation because GI microbiota equilibrium plays an important role in several physiological processes ensuring brain integrity and neurogenesis [109,110]. Taken together, the above observations suggest that SARS-CoV-2 infection could promote PD development and progression through a virus-exerted dysfunction of the GI system.
Inflammatory and Molecular Overlapping Pathways
Common inflammatory events unraveling during PD development and observed in the acute phase of SARS-CoV-2 infection, as well as after COVID-19 remission, may indicate a link between these two disorders. Virus-mediated sustained or aberrant neuroinflammation could be a decisive pathobiological process for the initiation of a neurodegenerative disease, such as PD, long after recovery from the viral infection [111][112][113]. Indeed, growing evidence indicates that SARS-CoV-2 induces neuroinflammation [114] through its neurotropic, neuroinvasive, and neurovirulence effects [115,116] or even via immune-mediated pathways [117]. SARS-CoV-2 infection also triggers systemic inflammatory responses and induces cytokine release [118]. Severe COVID-19 is characterized by a cytokine storm syndrome, which is a major cause of mortality [118,119]. Several studies have demonstrated the presence of inflammatory mediators, such as increased levels of pro-and anti-inflammatory interleukins (IL-1, IL-2, IL-6, IL-10) and tumor necrosis factor-alpha (TNF-α) in the serum of COVID-19 patients [120][121][122][123]. Interestingly, a small prospective observational study had previously found that high levels of IL-6 were linked to a higher chance of developing PD [124]. Evidently, an exacerbated systemic infection that causes a huge release of inflammatory mediators, including cytokines, chemokines, and antibodies, could lead to increased blood-brain barrier (BBB) permeability [125]. Functional and structural integrity of the BBB is pivotal in maintaining brain homeostasis [126]. A neurovascular unit (NVU) consists of multiple cell types, including brain microvascular endothelial cells (BMVECs), astrocytes, pericytes, microglia, and neurons, connected together with extracellular matrix components, and is a rigorous regulator of BBB permeability [127]. NVU disruption has been previously associated with neurodegenerative diseases [128]. In particular, BMVECs constitute an important component of NVU and are intricately interconnected through tight junction (TJ) proteins. However, inflammation affects BBB integrity and stability mainly through cytokine-induced degradation of TJ proteins [129]. SARS-CoV-2-mediated brain endothelial inflammation, upregulation of inflammatory mediators, and most significantly, disruption of BBB stability, have also been observed in human BMVECs [130]. According to in vitro studies, SARS-CoV-2 was shown to infect human BMVECs and cause a decrease in TJ protein expression [130,131]. Furthermore, incubation of human BMVECs with S protein resulted in enhanced ACE2 expression, thereby facilitating viral entry and inducing neuroinflammation [132].
When BBB becomes impaired, pro-inflammatory cytokines and factors, innate immune cells from the periphery, and SARS-CoV-2 could possibly pass through and infiltrate the CNS. In that case, the CNS professional immune cells, microglia and astrocytes, may also become activated [133,134]. Neuroinflammation is then likely to set in fast, leading to elevated production of cytokines, chemokines, reactive oxygen species (ROS), and secondary messengers [135]. Microglia, which are highly susceptible to pro-inflammatory stimuli, are concentrated in areas harboring dopaminergic neurons, making them particularly vulnerable to inflammatory mediators [136,137]. Interestingly, the S1 subunit of S protein was found to efficiently trigger neuroinflammation, including microglia activation, release of multiple pro-inflammatory cytokines, and cause behavioral deficits in rats [138]. Consequently, these neuroinflammatory cascades lead to enhanced apoptotic activity, increased ROS levels, mitochondrial dysfunction, and eventually neurodegeneration [139,140].
Finally, cellular senescence is a core homeostatic event that provides yet another, ageand state-dependent substrate for neurodegeneration and the development of diseases like AD and PD [141,142]. Cellular senescence in the aging brain affects both neuronal and non-neuronal cells, and it is characterized by a broad array of interconnected disruptions, such as disruptions in autophagy, bioenergetics, and mitochondrial dynamics, as well as the onset of low-grade inflammation [142]. This cumulative array of dysfunction culminates in the accumulation of proteopathic seeds, including tau, amyloids, and α-syn, and tissue-wide remodeling [141]. It has been shown that SARS-CoV-2 infection induces "immunosenescence" and enhances the senescence-associated secretory phenotype (SASP) in infected tissues, via disruption of host antiviral mechanisms, such as interferon signaling pathways [143][144][145]. Taken together, all the aforementioned studies strongly indicate that the COVID-19 cytokine storm and innate immunity dysregulation may cause neuroinflammation and, in consequence, neurodegeneration.
Neuropathological findings in postmortem brain tissues from COVID-19 patients further support the involvement of COVID-19-related neuroinflammatory processes in PD development. A postmortem brain study of 43 COVID-19 patients has shown activation of microglia and CNS infiltration by cytotoxic T-lymphocytes, more apparent in the brainstem [146]. Regardless of COVID-19 disease severity, significant inflammatory responses such as astrogliosis, microglia activation, and perivascular T-lymphocyte infiltration were observed postmortem in both white and gray matter of patient brains [147]. Performing single-nucleus RNA sequencing and immunohistochemistry on tissue from a group of individuals who died with COVID-19 and a group of individuals who died from other causes, Yang and colleagues revealed glia transcriptomic changes that indicated a COVID-19-associated activation of inflammatory pathways. The ensuing dysregulation of homeostatic pathways could potentially lead to neurodegeneration [148]. Specifically, microglia and astrocytic subpopulations were enriched by inflammatory genes and deregulated neuroprotective ones that had been previously linked to PD and other human neurodegenerative diseases, such as the glial fibrillary acidic protein (GFAP), the interferoninduced transmembrane protein-3 (IFITM3), and others [149,150].
Another mechanism that may contribute to PD pathogenesis involves the reninangiotensin system and ACE2, which are implicated in the pathophysiology of COVID-19 and may play a role in neuroinflammation-mediated neurodegeneration in PD [151,152]. ACE2 is highly expressed in several brain areas [153], including striatum [154], the substantia nigra, the olfactory bulb [155], and the brain endothelium [130,156,157]. Induced pluripotent stem cells (IPCS) derived from midbrain dopaminergic neurons were shown to be vulnerable to SARS-CoV-2 infection in vitro [158], unravelling the potentially direct neurotrophic effect of SARS-CoV-2 in strategic PD areas. Furthermore, SARS-CoV-2-induced Toll-like receptor (TLR) overactivation led to ACE2 upregulation and promoted the neurotrophic and neuroinflammatory outcomes of SARS-CoV-2 infection [159]. TLRs belong to the family of innate immune receptors and play an important role in the activation of innate immunity, including activation of glial cells. TLR-mediated stimulation of intracellular signaling pathways culminates in the release of proinflammatory mediators such as IL-6, IL-1, TNF-a, and nuclear factor-κB (NF-κB) [160]. Protein-to-protein interaction between SARS-CoV-2 S protein and TLR-4 has been previously recorded [161]. SARS-CoV-2-mediated overactivation of the TLRs may lead to hyperinflammation, ACE2 upregulation and microglia switching from the neuroprotective to the neurotoxic phenotype [159,162]. In sequel, sustained gliosis and prolonged neuroinflammation could lead to α-syn aggregation and finally loss of dopaminergic neurons in the SNpc [112].
Aside from neuroinflammation, dysregulation of several homeostatic molecular pathways has been identified in PD onset and development. These alterations also occur during host-virus interactions as the virus attempts to direct critical cellular infrastructure towards completion of its own lifecycle. SARS-CoV-2 viral proteins were shown to post-translationally reconfigure the biological function of 24 host proteins expressed in lung. The latter act as perturbators and interact with 44 CNS proteins that are known to be implicated in PD pathogenesis [163]. Specifically, SARS-CoV-2-mediated deregulation of Rab7a and nucleoporin-62 (NUP62) could be strongly involved in PD pathogenesis, because Rab7 lysosomal protein decreases α-syn aggregation and associated neurotoxicity [164], while NUP62 is crucial for autophagosome development [165]. Furthermore, SARS-CoV-2 proteins can interact and bind to a variety of human protein trafficking molecules. Protein trafficking, translation, transcription, and ubiquitination regulation are all coordinated by these biomolecules, leading to neuroprotection, protection of BBB integrity, and neurogenesis [166]. A recent study demonstrated a direct interaction between SARS-CoV-2 nucleocapsid protein (N-protein) and α-syn, which led to the aggregation of the latter into amyloid fibrils, a highly pathogenic form of the protein, linked to PD. Co-administration of SARS-CoV-2 N protein and α-syn to a PD cell model resulted in twice the neuron loss due to neurotoxicity compared to control cells treated with α-syn alone [167].
Other important cellular processes implicated in the loss of dopaminergic neurons in SNpc are thought to be oxidative stress and mitochondrial dysfunction, endoplasmic reticulum stress, and the impairment of protein degradation systems [168][169][170].
A key molecular factor in PD development and progression is mitochondrial dysfunction and oxidative stress [171,172]. An imbalance between ROS generation and cellular antioxidant activity leads to oxidative stress and ROS can further affect mitochondria, attenuating adenosine triphosphate (ATP) production as well as causing damage to mitochondrial DNA [173]. In addition to causing direct cellular damage, oxidative stress can speed up neuron degeneration by inducing inflammatory or apoptotic pathways, such as NF-κB or caspase activation [174]. In PD studies, mitochondrial dysfunction may occur months before the onset of striatal dopaminergic neuron loss [175] and PD patients have been well documented to possess reduced or deficient mitochondrial complex I activity in the SNpc [176,177]. In mice, accumulation of wild-type α-syn in dopaminergic neurons reduced mitochondrial complex I activity and elevated ROS production, leading to cell death [178]. SARS-CoV-2 seems to interact with and manipulate mitochondria in order to hijack and evade mitochondria-mediated immune response for its own replication and survival [179,180]. In this effort, SARS-CoV-2 may induce mitochondrial impairment [181,182], mitochondria-mediated oxidative stress, and mitochondrial damage through mitochondrial membrane depolarization, mitochondrial permeability transition pore opening, and enhanced ROS release [183][184][185]. Furthermore, the virus prevents mitophagy by blocking the binding of p62 and microtubule-associated protein 1A/1B-light chain 3 (LC3), thereby hindering viral RNA breakdown [185].
Finally, mitochondria aid the antiviral immune response by allowing release of proinflammatory cytokines [186]. ACE2 has been suggested to regulate mitochondrial function [187]. Its expression is decreased when SARS-CoV-2 S protein binds to ACE2 on microglia cells, causing ATP reduction and activation of the ROS-generating enzyme NADPH oxidase [188]. The ensuing increase in ROS production and oxygen consumption may lead to neuroinflammation and loss of neighbor dopaminergic neurons [189].
Endoplasmic reticulum (ER) stress has been linked to neurodegenerative diseases, including PD [190,191]. ER homeostasis disruption and extended ER stress lead to misfolded protein accumulation and may stimulate particular proapoptotic pathways through the activation of the transcription factor C/EBP homologous protein (CHOP) and cysteine proteases caspase-4/12 [192,193]. Growing evidence suggests that SARS-CoV-2 proteins interact with the ER compartment and may induce ER stress [194,195]. SARS-CoV-2 open reading frame 8 (ORF8) is capable of inducing ER stress by triggering the activating transcription factor 6 (ATF6) and inositol-requiring enzymes 1 (IRE1) branches of the ER stress pathway [196], potentially leading to α-syn accumulation [197]. Aside from initiating apoptotic pathways, ER stress is a powerful stimulator of NF-κB activation and inflammatory gene transcription [198,199]. SARS-CoV-2 also appears to activate NF-κB, causing inflammation, possibly through ER stress or via interaction with the non-structural protein Nsp5 [200]. Notably, NF-κB is a crucial transcription factor that regulates inflammation and dopaminergic neurons loss in PD patients [201]. Hence, deregulation of this signaling pathway has been linked to PD onset and pathology [202] by favoring α-syn accumulation, aggregation, and spreading, oxidative stress-induced neuron apoptosis, neuroinflammation, and dopaminergic neuron loss [139,203,204].
When aggregation and deposition of misfolded α-syn elicit dopaminergic neuron loss, protein degradation systems come to the rescue. The ubiquitin-proteasome system (UPS) and the autophagy-lysosomal pathway (ALP) are important proteolytic systems in neurons and critical for refolding or elimination of misfolded proteins; therefore, they play a significant role in cellular homeostasis [205]. Impairment or even failure of these systems may contribute to PD pathogenesis and progression [21,206]. SARS-CoV-2 virulent components, such as ORF proteins, seem to modify autophagy formation and function, leading to SARS-CoV-2-induced autophagy disruption and potentially neuron damage [207,208]. Specifically, ORF3a was shown to impede autophagosome-lysosome (A-L) fusion and ALP formation by interacting directly with the VPS39 subunit of the homotypic fusion and protein sorting (HOPS) complex. ORF3a further damages lysosomes and impairs their function. Remarkably, this feature of HOPS-VPS39-mediated A-L fusion inhibition appears to be unique to SARS-CoV-2, since the quite similar ORF3a of SARS-CoV was ineffective in inhibiting A-L fusion [209]. Furthermore, another study found that although ORF7a protein stimulates autophagy, it also limits A-L fusion progression by downregulating the SNAP29 protein via caspase 3 (CASP3) activation, providing a mechanism through which SARS-CoV-2 uses the autophagic system to facilitate its own propagation [210]. Interestingly, a SARS-CoV-2 papain-like protease has been identified to directly cleave serine/threonine unc-51-like kinase (ULK1) and prevent ULK1-ATG13 complex formation [211]. ULK1 is an upstream autophagy orchestrator, which phosphorylates key regulatory proteins in autophagosome formation [212]. In this regard, ULK1 cleavage is expected to completely inhibit the ALP function, due to lack of autophagosome formation. Evidently, autophagy is crucially involved in the regulation of the antiviral immune response. The striking correlation between SARS-CoV-2-induced aberrant inflammation and the observed autophagy defects [213] suggests that the virus-induced cytokine storm could be mediated by the failure of autophagy mechanisms to maintain cellular homeostasis.
Overall, SARS-CoV-2 seems to interfere and disrupt several host cellular and molecular pathways involved in proper neuronal functions, potentially promoting PD pathogenesis. A summary of these overlaps is depicted in (Figure 1).
Biogenesis of Exosomes
Exosomes are one of three main subtypes of extracellular vesicles (EVs) (microvesicles, exosomes, and apoptotic bodies) secreted by the cells [214]. They are secreted from the majority of cell types and can also be isolated from body fluids, such as saliva, plasma, serum, urine, CSF, etc. [215,216]. Exosomes contain cell-specific cargos of proteins, lipids, DNAs, and coding/non-coding RNAs from the donor cells that can be preferentially delivered to targeted recipient cells. They represent a recently discovered mode of intercellular communication that may play a major role in many cellular processes in both physiological and pathological conditions [217,218].
Exosomes are EVs [219] with a cup-shaped appearance in transmission electron microscopy and size ranging from 30 to 150 nm [220,221]. Exosomes emerge from the endosomal compartment following a series of events, starting with the inward budding of the plasma membrane that gives rise to the early endosome [222]. Then, budding and modification of the limiting membrane of endosomes leads to formation of intraluminal vesicles (ILVs), whose accumulation produces late endosomes or large multivesicular bodies (MVBs) [221,223]. MVBs can either fuse with the plasma membrane and release ILVs as exosomes into the extracellular space, or with lysosomes, where ILV cargo will be degraded [224]. Biogenesis of ILVs, trafficking of MVBs, and secretion of exosomes are mainly regulated by endosomal sorting complexes required for transport (ESCRT) [225]. The ESCRT machinery consists of a set of cytosolic protein complexes that become attracted to endosomes by membrane proteins usually tagged with ubiquitin [226]. This multi-subunit protein system is essential for membrane remodeling and cargo sorting of MVBs [227], although some studies found that ILVs are also formed in the absence of ESCRT machinery (ESCRT-independent pathway), with the enzyme sphingomyelinase and tetraspanin proteins, such as CD9, CD63, and CD81, playing a pivotal role [228]. When exosomes reach the target cell, they can be internalized through specific endocytotic mechanisms, fuse directly with the plasma membrane or bind to cellular surface receptors [229][230][231].
Exosomal surface indicators, such as the tetraspanins CD9, CD63, and CD81, ALG 2interacting protein X (ALIX), tumor susceptibility gene 101 protein (TSG101), and ESCRT proteins, have all been identified and used to characterize exosomes in vitro and in vivo
Biogenesis of Exosomes
Exosomes are one of three main subtypes of extracellular vesicles (EVs) (microvesicles, exosomes, and apoptotic bodies) secreted by the cells [214]. They are secreted from the majority of cell types and can also be isolated from body fluids, such as saliva, plasma, serum, urine, CSF, etc. [215,216]. Exosomes contain cell-specific cargos of proteins, lipids, DNAs, and coding/non-coding RNAs from the donor cells that can be preferentially delivered to targeted recipient cells. They represent a recently discovered mode of intercellular communication that may play a major role in many cellular processes in both physiological and pathological conditions [217,218].
Exosomes are EVs [219] with a cup-shaped appearance in transmission electron microscopy and size ranging from 30 to 150 nm [220,221]. Exosomes emerge from the endosomal compartment following a series of events, starting with the inward budding of the plasma membrane that gives rise to the early endosome [222]. Then, budding and modification of the limiting membrane of endosomes leads to formation of intraluminal vesicles (ILVs), whose accumulation produces late endosomes or large multivesicular bodies (MVBs) [221,223]. MVBs can either fuse with the plasma membrane and release ILVs as exosomes into the extracellular space, or with lysosomes, where ILV cargo will be degraded [224]. Biogenesis of ILVs, trafficking of MVBs, and secretion of exosomes are mainly regulated by endosomal sorting complexes required for transport (ESCRT) [225]. The ESCRT machinery consists of a set of cytosolic protein complexes that become attracted to endosomes by membrane proteins usually tagged with ubiquitin [226]. This multi-subunit protein system is essential for membrane remodeling and cargo sorting of MVBs [227], although some studies found that ILVs are also formed in the absence of ESCRT machinery (ESCRT-independent pathway), with the enzyme sphingomyelinase and tetraspanin proteins, such as CD9, CD63, and CD81, playing a pivotal role [228]. When exosomes reach the target cell, they can be internalized through specific endocytotic mechanisms, fuse directly with the plasma membrane or bind to cellular surface receptors [229][230][231].
Exosomal surface indicators, such as the tetraspanins CD9, CD63, and CD81, ALG 2-interacting protein X (ALIX), tumor susceptibility gene 101 protein (TSG101), and ES-CRT proteins, have all been identified and used to characterize exosomes in vitro and in vivo [31]. Because of their varied cellular origin, exosomal biomolecular composition is highly heterogeneous, bearing characteristics from both surface proteins and the cargo of their donor cells [223,232]. For example, neuron-derived exosomes are characterized by the presence of L1 cell adhesion molecule (L1CAM), a surface exosomal marker highly expressed in neurons [233]. Furthermore, their biocompatibility and bi-layered lipid structure, which shield cargo from degradation, reduce immunogenicity and enable exosomes to pass through major biological membranes, including the BBB [219]. Considering that exosomes can cross the BBB and act as fingerprints of their cellular originators, they could be used as CNS biomarkers that can be isolated and recovered from the periphery, with minimally invasive techniques [234].
Impact of Exosomes in PD Pathogenesis
The usage of exosomes for the removal of accumulated, misfolded proteins increases under pathological conditions, particularly in proteinopathies [235,236]. Specifically, when other cellular clearance systems, such as the proteasome and ALP, fail to eliminate aggregated amyloidogenic proteins, exosomes come to the rescue [237]. Thus, exosomes may have a prominent role in PD, as they represent a potential spreading pathway for misfolded proteins, thereby contributing to pathogenesis and also to disease diagnosis through cargo analysis [238,239].
The "prion-like" mode of α-syn spread lies at the heart of PD pathogenesis, as the molecular mechanisms leading to α-syn seeding and aggregation remain unknown [240]. Exosomes, as key intercellular mediators in the CNS, may provide a valuable vehicle for the transmission of α-syn [32,236]. Unlike other cell-to-cell transmission mechanisms, such as non-classical exocytosis or transport via nanotubules, exosomes can mediate α-syn transfer over longer distances [241]. The oligomeric form of α-syn is thought to be the toxic form causing neuronal death. Danzer and colleagues identified the presence of oligomeric α-syn in exosomes from continuous cell lines and primary cells and demonstrated that exosomal α-syn is more easily taken up by recipient cells than the free oligomeric form of protein [242]. Other researchers used various in vitro and ex vivo cellular systems to verify the presence of α-syn in exosomes [243,244]. Considering that loss of dopaminergic neurons is associated with PD progression and worsening of motor symptoms, exosomes generated by α-syn-treated microglia exhibited a considerably higher neuron apoptosis rate than control exosomes, in an in vitro experiment [245]. Exosomes isolated from patients with PD can induce the oligomerization of soluble α-syn in recipient cells, increasing neurotoxicity and speeding up α-syn aggregate formation [246]. Additionally, serum exosomes derived from PD patients contain α-syn, which can induce behavioral and pathological features of PD in mice [247]. Taken together, data from the abovementioned studies suggest that by regulating uptake and transfer of abnormal α-syn to nearby cells, exosomes are key regulators of PD pathogenesis and its spatiotemporal evolution [248,249].
Aside from trafficking α-syn, exosomes interfere in intercellular inflammatory pathways, enhancing the possibility of PD outcomes [250]. There is abundant evidence that neuroinflammation plays a vital role in PD onset and progression [23]. A sound inflammatory response is essential for tissue repair and misfolded protein breakdown, but an excessive and delayed inflammatory response can lead to a deregulated neuroinflammatory cycle [251]. Microglia are considered to be the resident brain macrophages. By phagocytosing dead cells and helping with the removal of misfolded protein aggregates from the brain, they play an important role in the removal of extracellular α-syn species, including exosomecontained protein [252]. At the same time, microglia could be activated by exosomal α-syn, and elicit an immunological response with the release of pro-inflammatory cytokines, resulting in dopaminergic neuron death [253]. In addition to their well-established role in neuroinflammation, microglia appear to be involved in intercellular spreading of neurotoxic α-syn [254]. Furthermore, exogenous introduction of human α-syn preformed fibrils (PFFs) into primary microglial cell cultures stimulates the release of α-syn-containing exosomes, which were fully capable of inducing protein aggregation in recipient neurons [255]. This release of α-syn following PFF treatment could be an effort to monitor and control intracellular levels of misfolded protein, possibly attributed to the deregulation of the ALP pathway in microglia [255]. Autophagic activity impairment and lysosome dysfunction have been previously correlated to increased release of exosomes from neuronal cells and to exosomes-mediated α-syn spread and transmission [21,237,256].
Recent advances concerning immunosenescence studied its dissemination on tissue level, via exosomes. Specifically, cell-level stressors may induce a pro-inflammatory phenotypic shift in afflicted cells, and subsequently this shift may be communicated via specific exosomal cargo in a para-and juxtracrine manner [257]. Notably, interferon-responsive genes and proteins, such as the IFITM3 protein, may be loaded during such transmissions, representing a tissue-level signal of inflammation [258]. Depending on the cargo and cell of origin, exosomes may conversely ameliorate the SASP [259], thereby abating inflammation [260,261].
Exosomes as Biomarkers in PD Diagnosis
To date, the diagnosis of PD depends on the clinical manifestations of the disease and it is determined by the presence of motor symptoms [2]. PD diagnosis may be difficult, especially in early pre-symptomatic stages, due to the absence of motor symptoms [262]. Hence, a low clinical diagnostic accuracy rate in the preclinical phase has been reported [263]. The usage of exosomal cargo as a potential "biomarker" or "early indicator" of PD pathology and progression has piqued great interest. Notably, exosomal α-syn has been proposed as a potential biomarker for PD in multiple studies [238,239,246,264]. Shi and colleagues found that CNS-derived exosomal α-syn was considerably higher in PD patients than in controls and it had a significant relationship with disease severity [238]. Similarly, a longitudinal investigation revealed that α-syn levels in neuronal exosomes were significantly higher in patients with early-stage PD compared to control groups, and that higher α-syn levels were linked to the progression of motor impairment [264]. Another study found that levels of CNS-derived exosomal α-syn were lower in early-stage PD patients compared to individuals with essential tremor and the control group [239]. In salivary EVs from PD patients, it was demonstrated that absolute levels of α-syn oligomers and the ratio of α-syn oligomers over total α-syn were increased compared to healthy controls, indicating that they could be used as diagnostic biomarkers [265]. Mean levels of neuron-derived exosomal α-syn have been proposed to distinguish PD from other cases of atypical parkinsonism and neurodegenerative diseases, as a twofold increase was observed in patients with preclinical and established PD compared to the other etiologies [266].
As far as other neurospecific exosomal cargo proteins are concerned, it has been shown that CNS-derived exosomal tau levels were considerably higher in PD patients compared to controls, and notably but not significantly increased compared to those of AD patients [267]. Furthermore, levels of clusterin, apolipoprotein A1 (apoA1), and the complement C1r subcomponent were significantly lower in PD patients at Hoehn and Yar stages II and III (a scale for assessing the functional impairment caused by PD) compared to healthy controls [268]. Conversely, neuron-derived exosomal protein deglycase DJ-1 was higher in PD patients compared to controls [269].
In addition to misfolded proteins, exosomes serve as a conduit for transport of other RNA species such as microRNA (miRNA). Exosomal miRNAs regulate gene expression in recipient cells at a post-transcriptional level, thereby interfering with several physiological processes in the CNS, including homeostasis, neuron growth, cell migration, and brain endogenous immunity [270]. Mounting evidence has proposed a pivotal role for exosomal miRNAs in neurodegenerative diseases, including PD [271]. Firstly, they can inhibit protein synthesis after cellular uptake of exosomes [272]. Secondly, they can directly bind to TLRs and trigger neuroinflammation [273], and thirdly, they can induce oxidative stress pathways leading to neurotoxicity [274]. Given the diverse roles of miRNAs in PD pathogenesis, several studies have focused on their diagnostic value. Gui and colleagues studied the alterations in the miRNA profiles of CSF-derived exosomes from PD patients, finding that 16 exosomal miRNAs were elevated and 11 miRNAs were downregulated in PD in comparison with the control group. Characteristically, miR-1 and miR-19b-3p were identified to be considerably decreased in PD-CSF exosomes. MiR-153, miR-409-3p, miR-10a-5p, and let-7g-3p, on the other hand, were increased in that patient group [275]. Another study in serum exosomes from PD patients observed a drop in miR-19b expression and an elevation in miR-195/miR-24 expression in PD patients compared to healthy controls [276]. Finally, exosomal miRNAs were successfully used to differentially diagnose PD stages from healthy controls, showing that those miRNAs could serve as specific biomarkers both for early PD detection and PD progression [277].
Exosomes and SARS-CoV-2 Infection
Exosomes play a critical role in viral infections [278]. Exosomes and viruses share structural and physicochemical features, such as size, shape, biochemical composition, and biomolecule transportation pathways within cells [279,280]. Thus, exosomes constitute a new frontier in the realm of viral infections, including SARS-CoV-2.
A proposed way of viral spreading is via exosomes that contain viral particles or components. In the case of respiratory viruses, several studies showed that viral antigens are present in circulating exosomes recovered from lung transplant recipients infected with rhinovirus and respiratory syncytial virus [281]. In SARS-CoV-2 infection, exosomal cargo contains viral proteins or peptide fragments, such as the N and S proteins [282,283], whose presence has been linked to enhanced viral propagation, host immune reaction, and induction of a cytokine storm [284]. Barberis and colleagues identified for the first time viral genetic material in the exosomal cargo of COVID-19 patients, suggesting that SARS-CoV-2 may also be using the endocytic pathway to spread [285].
The "Trojan exosome hypothesis", in which retroviruses employ EVs to penetrate host cells, boost viral propagation, and elude the immune response, was introduced by Gould and colleagues [286] and was later supported by several reports [40]. In SARS-CoV-2 infection, the virus uses multiple steps to achieve entry into the host cell, including ACE2mediated receptor binding and transmembrane serine protease-2 (TMPRSS2)-mediated intracellular cleavage [287]. Recent data revealed that EVs carry and transfer ACE2 between different types of cells [288]. This led to the development of a competitive inhibitory therapy against SARS-CoV-2, in which ACE2-expressing EVs compete for the SARS-CoV-2 S protein S1 domain, limiting viral infection [289].
Exosomes released during viral infection contain inflammatory markers that cause a strong inflammatory response, acting as pathogen-related molecular patterns, thereby enhancing pathogenicity [290]. For example, exosomal CD9 has been shown to be involved in the route for EV-mediated viral transmission, by speeding up lentiviral infection and improving transduction effectiveness in B-and T-lymphocytes [291]. In addition, CD9 cooperates with TMPRSS2 to cleave viral fusion glycoproteins, thus facilitating the entry of coronaviruses, such as MERS-CoV, into lung cells [292]. These findings suggest that CD9 and other exosomal tetraspanins could facilitate SARS-CoV-2 infection. Proteomic analysis of plasma-derived exosomal cargo from COVID-19 patients revealed that circulating exosomal proteins are strongly correlated with pathological procedures leading to COVID-19 tissue damage, such as immune hyperactivation, coagulopathy induction, and inflammation [285]. Monosialodihexosyl ganglioside (GM3)-enriched exosomes are positively connected with disease severity in COVID-19 cases [293].
SARS-CoV-2-Related Exosomal Cargo and Its Potential Roles in Post-COVID-19 Parkinsonism and PD Pathogenesis
Given the established role of exosomes both in pathophysiological neuronal processes, and PD development and progression [294,295], as well as their emerging significance in SARS-CoV-2 infection and propagation [285], we believe that cascading from SARS-CoV-2 infection to post-COVID-19 parkinsonism and, possibly PD onset via exosomal cargo, should be at the research forefront. The putative roles of SARS-CoV-2-related exosomal cargos in the development of viral parkinsonism and/or PD pathogenesis are outlined and described in the next two paragraphs.
Exosomal Cargo and Induction of Post-COVID-19 Neuroinflammation
Following COVID-19 recovery and viral clearance, exosomes could be at the center of neuroinflammatory crossroads. Experimental studies in other several systemic inflammatory conditions, such as obesity [296] and rheumatoid arthritis [297], have outlined a strong relationship between peripheral systemic inflammation and neuroinflammation [298,299]. Exosomes could operate as physical bridges between these two conditions since they can traverse the BBB. In vivo proof of exosomes acting as neuroinflammatory mediators under systemic inflammation conditions has recently been obtained. Specifically, in a mouse model that received serum-derived exosomes from lipopolysaccharide (LPS)-challenged mice, brain gliosis, CNS expression of pro-inflammatory cytokine mRNA and inflammationassociated miR-155 were all increased [300]. In addition, exosomes generated by peripheral immune cells, such as activated monocytes and macrophages, were shown to be taken up by neurons and astrocytes, resulting in pathological cargo dissemination and neurotoxicity [301].
Serum exosomes from PD patients revealed increasing levels of IL-1 and TNF-α inflammatory mediators in comparison with the control group, while intravenous or intrastriatal administration of PD exosomes to mice induced α-syn aggregation, microglia activation, and neurodegeneration of dopaminergic neurons, leading to worsening of motor symptoms [247]. Conversely, exosomes containing pro-inflammatory cytokines, such as IL-1, can effectively be shed by glial cells [302]. This glia-derived insidious exosomal cargo can spread to neurons, contributing to a vicious cycle of neuroinflammation and neurodegeneration [245], a phenomenon further associated with older age [303].
The presence of inflammatory mediators in exosomes derived from SARS-CoV-2 infected cells could potentially enhance the model of neuroinflammation and ensuing neurodegeneration via peripheral systemic inflammation, possibly promoting a cellular milieu that favors PD development and progression mechanisms. Exosomal analysis from COVID-19 patients revealed high levels of tenascin-C (TNC) and fibrinogen-β (FGB) compared to controls. Both TNC and FGB induce release of pro-inflammatory cytokines via NF-κB signaling, leading to the presence of TNF-α, IL-6, and chemokine CCL5 upon exposure of hepatocytes to exosomes from COVID-19 patients. In this regard, a potential "window" of inflammatory insults to distant tissues should be examined [304].
Current knowledge so far suggests that the SARS-CoV-2 S protein seems to play a central role in exosome-mediated regulation of neuroinflammatory events pertinent to neurodegeneration. Thus, S protein or S-derived fragments were discovered in plasma exosomes isolated from COVID-19 patients, with an increased exosomal presence in clinical cases with moderate rather than severe disease. Multiomics exosomal analysis identified several molecules involved in immune responses, inflammation, and activation of both coagulation and complement pathways in infected patients compared to the control group of healthy subjects [284].
Furthermore, an in vitro study demonstrated that ectopic expression of SARS-CoV-2 S protein in HEK-293T cells generated a large number of exosomes highly loaded with miR-148a and miR-590. These exosomal miRNAs decreased gene expression of ubiquitin specific peptidase 33 (USP33), a deubiquitinase enzyme (DUBs)-stabilizer of its target protein, and of interferon regulatory factor 9(IRF9). They also deregulated the USP33-IRF9 network following their internalization in human microglia cells. IRF9 had been previously identified as a protective functional protein in CNS homeostasis, and its absence could result in severe neurological damage in glial cultured cells due to interferon (IFN)α-mediated overexpression of IFN-γ-like genes [305]. Reduced microglial USP and IRF9 levels effectively induced the production of important inflammatory gene pathways such as TNF-β, NF-κB, and IFN-β, culminating in neuroinflammatory cascade activation [306]. Apart from that, exosomes recovered from plasma of COVID-19 patients revealed the presence of S protein-derived fragments fully capable of inducing the immune system response. Evidently, exosomes from patients with mild disease severity exhibited higher amounts of MHC class II-antigen-presenting protein able to interact with CD4+ T-cells and boost their proliferation and activation [284]. MHC II overexpression, CD4 activation, and invasion of the CNS can all cause IFN-mediated phagocytic conversion of brain myeloid cells [307]. The ensuing neuroinflammation and dopaminergic neuron loss in the SNpc could conceivably lead to a PD phenotype [308,309].
Neuroinflammation mediated by host regulatory factors may also be conferred by SARS-CoV-2-manipulated exosomes. High-mobility group box 1 (HMGB1) is a nuclear protein involved in several CNS procedures such as inflammation, apoptosis, and autophagy regulation [310]. Elevated levels of HMGB1 in serum and CSF from PD patients have been observed [311]. Notably, inhibition of HMGB1 has been shown to reduce microglia-mediated neuroinflammation, neuron dopaminergic loss, and progression of PD pathology in PD animal models [311,312]. Neurofilament light chain (NfL) levels are a protein-indicator of axonal damage and serve as a biomarker for several neurodegenerative diseases, including PD [313,314]. At the same time, it has been suggested that NfL levels may potentially reflect neuroinflammatory processes leading to neurodegeneration in the early stages of multiple sclerosis development [315]. Analysis of the exosomal cargo of neuron-derived EVs (NDEV) isolated from post-COVID 19 patients with or without neurological symptoms showed high levels of HMGB1 and NfL compared to the control group, thereby implicating SARS-CoV-2 infection in the regulation of the two pro-PD development factors [316].
The Periphery-Exosomes-CNS Axis as a Promoter of Post-COVID-19 Parkinsonism and PD Development
Loaded with SARS-CoV-2 components and RNA, as well as virally-induced neuroregulatory molecules, exosomes are fully capable of accessing hard-to-reach neuroanatomical areas, such as the olfactory bulb [88], the hypothalamus [317], the DMV, and the brainstem [317][318][319]. A possible route allowing access to exosomes traveling long distances from peripheral tissues that are prime sites of infection, such as the intestine and the lungs, to the brain could be through retrograde axonal transport from peripheral nerves [320,321]. In that case, SARS-CoV-2-related exosomes could end up disrupting normal homeostatic molecular mechanisms in brain areas that have been previously associated with PD pathogenesis [322][323][324]. Indeed, a COVID-19 postmortem study detected major neurological damage, but only low levels of SARS-CoV-2 RNA in the brains of expired patients [325]. Furthermore, cortical accumulation of total α-syn was observed following viral eradication in a SARS-CoV-2 intranasally-infected hamster model without any indication of inflammation and neurodegeneration [326]. Extending the Braak hypothesis, one could argue that any neurological sequelae and neuropathological outcomes observed in COVID-19 survivors may emerge both directly, due to virus-exerted effects, and indirectly, through molecular and neuroinflammatory mediators, carried by SARS-CoV-2-related exosomes remaining in circulation even after elimination of the virus.
The neurological consequences of SARS-CoV-2 infection, according to Ahmed and colleagues, could be attributed, at least in part, to exosomal mRNA and transcriptional factors (Tfs) carried from the lungs to the brain areas [327]. These exosomal Tfs have the ability to regulate cellular gene expression transcriptionally and induce neuronal alterations consistent with imminent neurodegeneration. Among 19 exosomal Tfs found overexpressed during the acute phase of SARS-CoV-2 infection, BCL3, JUND, MXD1, IRF2, IRF9, and STAT1 were observed to activate genes associated with PD pathogenesis in strategic areas of the brain, such as the medial and lateral substantia nigra and the superior frontal gyrus region. These genes are implicated in a variety of physiological activities, including signal transduction, neuron death, and immunological surveillance. Evidently, their Tf-mediated dysregulation could contribute to neurodegeneration and PD pathology. For example, STAT1 triggers microglia activation and dopaminergic neurons' autophagy under hypoxia, including COVID-19 manifested hypoxia [328][329][330].
Exosomes may be further implicated in the association between SARS-CoV-2 and PD via the transfer of protein expression regulators from the periphery, through the BBB and into the CNS. It has been suggested that such factors could interact with proteins that are highly expressed in the CNS and are linked to PD. A relevant study demonstrated that 24 host lung proteins were subjected to post-translational modifications by SARS-CoV-2 viral proteins. Then, they were taken up and transported out of the lungs into the CNS by exosomes, leading to local disruption of protein-protein interactions [163].
Finally, recent studies have verified the presence of SARS-CoV-2 viral proteins in brain-derived exosomes, potentially enhancing their role in SARS-CoV-2 propagation and pathogenicity. Indeed, cargo profiling of neuron-derived EVs (NDEV) and astrocytederived EVs (ADEV) recovered from the plasma of COVID-19 patients revealed significantly higher levels of critical SARS-CoV-2 S1 and N proteins, in all COVID-19 affected subgroups compared to controls. Notably, mean ADEV and NDEV levels of N protein could be used to distinguish the group of patients who developed long COVID-19 with neuropsychiatric manifestations from the long COVID-19 group without such complications and the recovered COVID-19 patients without long COVID-19 [283]. Furthermore, SARS-CoV-2 spike-derived fragments were found to be efficiently exhibited in exosomes from recovered patients who had previously suffered from both mild and severe COVID-19 [284].
In vitro investigations have demonstrated that DMV neurons are vulnerable to oxidative stress and that oxidative stress enhances intercellular α-syn propagation [331]. SARS-CoV-2 could exploit inflammatory exosomal cargo [306] to induce oxidative stress in the DMV, facilitate α-syn aggregation, and eventually promote post-COVID-19 parkinsonism through SARS-CoV-2 S and N proteins. This hypothesis could be supported by the fact that both viral proteins have been shown to increase total α-syn and phosphorylation at Ser129 (pS129) levels [332], speed up the ability of endogenous α-syn to form amyloid fibrils [167], and ultimately induce LB-like pathology [332].
Collectively, it is possible that the exosomal presence of these viral proteins illuminates connecting routes linking COVID-19 to PD. Given that SARS-CoV-2 viral components persist in exosomes during the acute and potentially the post-COVID-19 phase, one could reasonably hypothesize that the COVID-19-related exosomal cargo could act as a neurodegenerative promoter and probable elicitor of parkinsonism manifestation.
Conclusions
Although the role of viruses in PD pathogenesis is still debated, various studies have found a link between viruses and parkinsonism, suggesting that they may operate as an initiating trigger of primary PD or secondary parkinsonism. The outbreak of the COVID-19 pandemic led to the realization that elimination of the virus after recovery does not always signal the end of the disease, as many patients are burdened with post-COVID-19 manifestations. One of the great concerns of the medical community at this point is the likelihood that SARS-CoV-2 infection could lead to parkinsonism, a notion strongly supported by the PD-like symptoms observed in some patients during the acute or post-COVID-19 phase. Extending the hypothesis of post-COVID-19-induced parkinsonian phenotype, we present herein clinical, inflammatory, and molecular overlaps that have started to emerge and constitute a neurobiological connective network between these two diseases. Exosomes are key regulators of intercellular communication and have been shown to play a crucial role in neurodegenerative diseases. SARS-CoV-2 manipulates exosomes, altering their cargo and, as a result, their function, so that they may serve as a vehicle for viral spread. In doing so, these SARS-CoV-2-related exosomes may efficiently transport SARS-CoV-2 genetic material and viral proteins from the periphery, being the gut or lungs, or other tissues, in the CNS via BBB crossing. SARS-CoV-2 related exosomes, in particular, can potentially transmit SARS-CoV-2 fragments, transcriptional factors, and inflammatory mediators to brain cells, resulting in prolonged neuroinflammation and α-syn aggregation, which collectively contribute to PD development or a possible deterioration in people with genetic predisposition towards PD. Visualization of the hypothetical role of SARS-CoV-2related exosomes and their cargo in PD pathogenesis is depicted in (Figure 2). In conclusion, we postulate in this review that cargo analysis of SARS-CoV-2-related exosomes, especially brain-derived ones, could serve as a compass for delineating underlying virus-mediated pro-PD development mechanisms and for detecting the much-dreaded post-COVID-19 parkinsonism storm. To this end, experimental and clinical studies will be conducted to validate our hypothesis.
transport SARS-CoV-2 genetic material and viral proteins from the periphery, being the gut or lungs, or other tissues, in the CNS via BBB crossing. SARS-CoV-2 related exosomes, in particular, can potentially transmit SARS-CoV-2 fragments, transcriptional factors, and inflammatory mediators to brain cells, resulting in prolonged neuroinflammation and αsyn aggregation, which collectively contribute to PD development or a possible deterioration in people with genetic predisposition towards PD. Visualization of the hypothetical role of SARS-CoV-2-related exosomes and their cargo in PD pathogenesis is depicted in (Figure 2). In conclusion, we postulate in this review that cargo analysis of SARS-CoV-2related exosomes, especially brain-derived ones, could serve as a compass for delineating underlying virus-mediated pro-PD development mechanisms and for detecting the much-dreaded post-COVID-19 parkinsonism storm. To this end, experimental and clinical studies will be conducted to validate our hypothesis.
Figure 2.
A hypothetical quasi-infectious model of CNS proteopathic seeding, with SARS-CoV-2 as the model virus. At step 1, SARS-CoV-2 neuroinvasion can occur either as a primary event by infecting neurons, or following infection of non-neuronal cells, such as brain endothelial cells, olfactory epithelial cells, or cells from peripheral infected tissues. Successful infection either of non-neuronal cells (2) or neurons (3) could lead to the production of exosomes that could be transmitted transynaptically (3), or intercellularly (4). The quasi-infectious concept indicates that the exosomal cargo is pathogenic and may be enhanced by the presence of viral components (5). SARS-CoV-2 S and N proteins could potentiate the formation of amyloid fibrils by endogenous α-syn in recipient cells. At the same time, exosomes could transmit α-syn to other brain cells in a "prion-like" mode. Exosomal immunomodulatory molecules could enhance neuroinflammatory processes in both neuronal and glia cells, while transcriptional regulators and miRNAs might activate intracellular signaling pathways and regulate gene transcription pertinent to neuroinflammation, oxidative stress, and other homeostatic cellular mechanisms. The ensuing microglial inflammatory phenotype turnover could enhance neuroinflammation further, resulting in enhanced neurodegeneration. A hypothetical quasi-infectious model of CNS proteopathic seeding, with SARS-CoV-2 as the model virus. At step 1, SARS-CoV-2 neuroinvasion can occur either as a primary event by infecting neurons, or following infection of non-neuronal cells, such as brain endothelial cells, olfactory epithelial cells, or cells from peripheral infected tissues. Successful infection either of non-neuronal cells (2) or neurons (3) could lead to the production of exosomes that could be transmitted transynaptically (3), or intercellularly (4). The quasi-infectious concept indicates that the exosomal cargo is pathogenic and may be enhanced by the presence of viral components (5). SARS-CoV-2 S and N proteins could potentiate the formation of amyloid fibrils by endogenous α-syn in recipient cells. At the same time, exosomes could transmit α-syn to other brain cells in a "prion-like" mode. Exosomal immunomodulatory molecules could enhance neuroinflammatory processes in both neuronal and glia cells, while transcriptional regulators and miRNAs might activate intracellular signaling pathways and regulate gene transcription pertinent to neuroinflammation, oxidative stress, and other homeostatic cellular mechanisms. The ensuing microglial inflammatory phenotype turnover could enhance neuroinflammation further, resulting in enhanced neurodegeneration.
Conflicts of Interest:
The authors declare no conflict of interest.
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Domain: Biology
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