Progress 01/15/24 to 01/14/25
Outputs
Target Audience:The target audience for this project was underrepresented students as trainees that will become leaders in digital agriculture. Three PhD students from underrepresented backgrounds continue being supported by this project. By the end fo Fall 2024, the 3PhD students funded by this projects are now PhD Candidates as they have succesfully defended the PhD Preliminary exam (oral and written) in their respective programs: Electrical & Computer Engineering, Biological & Agricultural Engineering, and Geospatial Analytics. In addition, all three PhD stduents have either published or submitted manuscripts for publication: Peer-Reviewed Journal Articles from Work Performed Since Initial Appointment at North Carolina State University E Pena Martinez, M Kudenov, H Nguyen, DS Jones, C Williams. (2024). Evaluating two high-throughput phenotyping platforms at different stages of the post-harvest pipeline of sweetpotatoes. Smart Agricultural Technology, 100469. link. . Manuscripts submitted and under review: Bloom, J Larsen, EE Pena Martinez, CM Williams, DS Jones, MW Kudenov. (2025). High-Throughput Classification and Quantification of Skinning Phenotype in Sweetpotatoes. Submitted to The Plant Phenome Journal. S McDowell, DS Jones, S Carpenter, RS Hunt, M Kudenov, C Williams. (2025). Machine Learning for Predicting Sweetpotato Growth and Quality: Integrating In-Season Root Imaging with Environmental and Agronomic Insights. Submitted to Computers and Electronics in Agriculture on Jan 11, 2025. Preprint link. Additionally, this project targeted stakeholders in agriculture to help develop translational research in rural communities in North Carolina. Through this project we have engaged multiple stakeholders in agriculture and showcased how data science techniques can facilitate decisions in agriculture. Through the work of the students supported by this project, we have increased the adoption of AI/ML technologies in the Sweetpotato and Peanut industries in North Carolina. Research Presentations by students funded by this grant: S McDowell, DS Jones, RS Hunt, S Carpenter, Kudenov, M, Williams, C. The Development of Machine Learning Models for Assessing In-season Sweetpotato Root Growth and Crop Yield Estimates. 2024 INFORMS Annual Meeting in the Multi-Objective Decision Support Systems for Coping with Deep Uncertainties session. Seattle, WA. Oct 2024. S McDowell. An Introduction to SAS Visual Analytics using Agricultural. North Carolina A&T University. Greensboro, NC. Feb 2024. S McDowell, DS Jones, RS Hunt, S Carpenter, Kudenov, M, Williams, C. The Development of Machine Learning Models for the Assessment of In-season Sweetpotato Root Growth and Crop Yield Estimates. Applied AI in Engineering & Computer Science Symposium. Raleigh, NC. Sep 2024. S McDowell, DS Jones, RS Hunt, S Carpenter, M Kudenov, C Williams. The Development of Machine Learning Models for the Assessment of In-season Sweetpotato Root Growth and Crop Yield Estimates. ASABE Annual International Meeting. Anaheim, CA. E Pena, M Kudenov, C Williams, DS Jones, H Nguyen. Scaling up phenotyping research through industry partnerships in sweetpotato production. 2024 8th International Plant Phenotyping Symposium. Lincoln, NE. Oct 2024. R Butler, R Rejesus, DS Jones, NG Nelson, Assessing Climate- and Weather-Driven Impacts to Crops of the U.S. National Crop Yields and Losses: Which Data Source is Best? Annual Fall Meeting, American Geophysical Union (AGU), Washington, DC, 2024. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?All three students were provided with opportunities to showcase their research at several professional societies international and national conferences. As a graduate peer-mentor, one of the students also was also trained on best practices to mentor peers. Another student had the opportunity to attend entrepreneurial training for the student's research application through I-Corps at NC state. How have the results been disseminated to communities of interest?Through oral presentations in professional conferences such as the ASABE Annual International Meeting, in speciatly crops workshops such as the National Sweetpotato Collaborators Group Conference, or through workshops organized at Historically Black Colleges and Universities, such as NC A&T University. What do you plan to do during the next reporting period to accomplish the goals?This year we anticipate that the three fellows will graduate in Spring 2025 and secure great job opportunities in academia, industry, or federal agencies.
Impacts
What was accomplished under these goals?
Our goal was to foster cultural, academic, and professional capital in a three-fellow cohort, which was accomplished using three strategic objectives: Cohesively training students who addressed complementary but independent research questions aimed at improving agricultural production through data science within three doctoral programs: Biological & Agricultural Engineering (BAE), Electrical & Computer Engineering (ECE), and Geospatial Analytics. Nurturing transferable skills in these Fellows to prepare them for the agricultural workforce in the Targeted Expertise Shortage Area (TESA) of data science. Providing Fellows with extensive opportunities for hands-on research and networking with academia, industry, and government agencies. What was accomplished under these goals? The three fellows, from historically underrepresented backgrounds, who were initially hired through this grant, progressed through their PhD programs and addressed independent research questions in the areas of agriculture and data science. The three fellows neared the end of their academic programs, are all now PhD Candidates, and are expected to graduate in Spring 2025. The three fellows entered their third and final year in the FFAR Fellows Program. Throughout their tenure in the program, they heard from and networked with PhD scientists working outside of academia. Aside from the transferable skills gained through their respective academic programs and participation as FFAR Fellows, all of the students were involved in communications and networking opportunities with industry and government staff working on research topics similar to their own. One of the fellows was awarded as the 2024 College of Agriculture and Life Sciences (CALS) Student of the Year Award. In addition, the student was chosen as a CALS Graduate Peer-Mentor for the 2023-2024 academic year.
Publications
- Type:
Peer Reviewed Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
E Pena Martinez, M Kudenov, H Nguyen, DS Jones, C Williams. (2024). Evaluating two high-throughput phenotyping platforms at different stages of the post-harvest pipeline of sweetpotatoes. Smart Agricultural Technology, 100469. l
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Progress 01/15/23 to 01/14/24
Outputs
Target Audience:The target audience for this project was underrepresented students as trainees that will become leaders in digital agriculture. Three PhD students from underrepresented backgrounds continue being supported by this project. In Fall 2023, one of the PhD students succesfully defended the PhD Preliminary exam and became a PhD candidate. In addition, the student submitted their first PhD manuscript for peer-reviewto Smart Agricultural Technology on October, 2023. Another PhDstudent funded by this projectsuccessfully passed her written exam in Fall 2023. Furthermore,two of the students supported by this grant graduated from theCollege of Agriculture and Life Sciences Graduate Agriculture Data Science Certificate Program. Additionally, this project targeted stakeholders in agriculture to help develop translational research in rural communities in North Carolina. Through this project we have engaged multiple stakeholders in agriculture and showcased how data science techniques can facilitate decisions in agriculture. Through the work of the students supported by this project, we have increased the adoption of AI/ML technologies in the Sweetpotato and Peanut industries in North Carolina. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In September and October of 2023 they had optional virtual meetings with Corteva and Bayer scientists who talked about their experiences managing teams, complementing the fellows virtual workshop on this topic. They also learned about roles for scientists within NGOs, hearing from scientists at the World Wildlife Fund, Environmental Defense Fund, and the Land Institute. A third virtual webinar featured two FFAR Fellow alumni who shared their experiences and advice on working in startup companies. Fellows are able to have follow up conversations with these guests, adding them to their professional networks. In addition, fellows participated in workshops that taught them skills for having crucial conversastions, contributing to succesful teams, and preparing for the job search. How have the results been disseminated to communities of interest?Through oral presentations in professional conferences such as the ASABE Annual International Meeting, in speciatly crops workshops such as theNational Sweetpotato Collaborators Group Conference, or through online webinars such as Farms.com. In addition, Shana McDowell shared her work using machine learning in agriculture to rural high school students in a mini data challenge event organized at NC State University. She also gave instructional hourson visual analtyicsto graduate students that participated in a weekend-longHackathon at NC State University. What do you plan to do during the next reporting period to accomplish the goals?This year we anticipate that one of the fellows will graduate in Spring 2024, and another one in Fall 2024. The third PhD student is expected to graduate in Spring 2025.
Impacts
What was accomplished under these goals?
1) The three fellows from historically underrepresented backgrounds that were initially hired for through this grant are continuing to progress through their PhD programs and addressing independent research questions in the area of agriculture and data science. The three fellows are nearing the end of their academic programs, with one of them expected to graduate in Spring 2024. 2)The three fellows are are entering their third and final year in the FFAR Fellows Program.Throughout their tenure in the FFAR Fellows Program students heard from and networked with PhD scientists working outside of academia. 3) Asside from the transerable skills gained from their respective academic programs and their participation as FFAR fellows, all of the students have being involved with communications and networking opportunities with industry and goverment staff that are working on similar problems to their research topics.
Publications
- Type:
Journal Articles
Status:
Submitted
Year Published:
2024
Citation:
E Pena Martinez, M Kudenov, H Nguyen, DS Jones, C Williams. (2024). Evaluating two high-throughput phenotyping platforms at different stages of the post-harvest pipeline of sweetpotatoes. Submitted to Smart Agricultural Technology on Oct 12, 2023.
- Type:
Websites
Status:
Published
Year Published:
2023
Citation:
E Pena Martinez, M Kudenov, H Nguyen, DS Jones, C Williams. (2024). Phenotyping Sweet Potatoes Using Two High-Throughput Scanners Across The Post-Harvest Pipeline. Link: https://www.youtube.com/watch?v=WTsa-ELMnaY
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Progress 01/15/22 to 01/14/23
Outputs
Target Audience:The target audience for this projectwas underrepresented students as trainees that will become leaders in digital agriculture. Additionally, thisproject targeted stakeholders in agriculture to help develop translational research in rural communities in North Carolina. Through this project we have engaged multiple stakeholders in agriculture and showcased how data science techniques can facilitate decisions in agriculture. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?We have provided extensive professional develpoment for the three fellows. These include, opportunities to showcase their research progress at national conferences, to our sweetpotatopartners, etc. How have the results been disseminated to communities of interest?Fellows have presented at the 2022 National Sweetpotato Collaborators group meeting in New Orleans, LA, and brought the 3rd place for PhD presentations at the conference. Fellows have also presented at the American Society of Agricultural and Biological Engineers, at Idaho National Laboratory, and monthly presentations of their progress to our industry partners.One of the fellows won the 2022 Farms.comag scholarship. Another oneof the fellows placed first for the NC State University PackPics competition in the Homegrown category with aninfographics explaining the fellow's research to the community. What do you plan to do during the next reporting period to accomplish the goals?The fellows will continue pursuing the required courses to earn their doctorates and the agriculture data science certificate. Additionally, the fellows are progressing with their research and are in route to submit manuscripts for peer-review. Additionally, our research to phenotype sweetpotatos to reduce waste and increase profit for sweetpotato stakeholders has proven to have a lot of potential and benefits for our rural communities. We plan to expand our research by pursuing additional funding.
Impacts
What was accomplished under these goals?
?1) We have continued to cohesively train three students from historically underrepresented backgrounds that are pursuing doctorate degrees in three different programs: Biological & Agricultural Engineering (BAE), Electrical & Computer Engineering (ECE), and Geospatial Analytics. Each student is currentlyaddressing complementary but independent research questions to improve the production of sweetpotatoes in North Carolina. 2) Through the FFAR program, a network of diverse mentors, and the professional development programs offered by the University, these fellows are developingtransferable skills that will prepare them as leaders in the intersection of agriculture and data science. 3) The three fellows have experiencedextensive opportunities for hands-on research and networking with academia, industry, and government agencies. They have created meaningful relationships with mentors in academia, the sweetpotato industry, and other agtech companies.
Publications
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Progress 01/15/21 to 01/14/22
Outputs
Target Audience:
Nothing Reported
Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?We identified three tangible training and professional development opportunities to encourage cohort-building among the three Sweet-Fellows: 1) All three students took a coursetogether titled Geospatial Grand Challenges in their first semester. This course incentivates student's problem solving skills to tackle grand societal challenges using geospatial analytics by empasizng the roles that location, spatial interaction, and multi-scale processes play in scientific discovery and communication. 2) The Sweet-Fellows are also Rockey FFAR Fellows. Through the FFAR program, they have access to professional development and career guidance to become the next generation of food and agriculture scientists. 3) The Sweet-Fellows are also enrolled to earn the Agricultural Data Science Certificate during their training at North Carolina State University. This certificate is designed to train the next generation of data-driven climate-smart agriculture workforce. How have the results been disseminated to communities of interest?The ongoing research project that the Sweet-Fellows are a part of can be found at sweetpotatoanalytics.com. Even though their findings are at an early stage given their Fall 2021 start, their research findings are continuously shared with pertinent stakeholders to solicit their feedback. We anticipate that scientificpeer-reviewed manuscripts will be published by next year. Additionally, three news articles were published on the research the Sweet-Fellows are working on: "Digging Deep into Interdisciplinary Agricultural Research", "Exploring New Avenues", and "Student Finds Family and High-Flying Fulfillment in BAE". What do you plan to do during the next reporting period to accomplish the goals?We will continue working with the Sweet-Fellows to advancesensing technologies, acquirein-field and post-harvest data, andstructureanintegrated database and decision support system that helps stakeholders understand the factors that affect produce quality and quantity.
Impacts
What was accomplished under these goals?
We have successfully ran a competitive recruitment process on a search for three talented PhD students from historically underrepresented backgrounds. The Sweet-Fellows are two african american women and one hispanic male with different academic backgrounds: Mathematics, Agricultural & Biological Engineering, and Geoscience. And, started PhD Programs in different departments and colleges in Fall 2021: Biological & Agricultural Engineering in the College of Agricultural Life Sciences, Electrical and Computer Engineering in the College of Engineering, and Geospatial Analytics in the College of Natural Resources. They work synergistically to advance modeling techniques, database development, optical sensing and remote sensing technologies to help optimize management strategies to resolve inconsistencies in sweetpotato quality. These research efforts have the potential to improve outcomes and increase produce value for growers, producers, and packers.
Publications
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