NC1210: Frontiers in On-Farm Experimentation

(Multistate Research Project)

Status: Active

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Annual/Termination Reports:

[03/10/2022] [03/07/2023] [02/26/2024] [03/06/2025]

Date of Annual Report: 03/10/2022

Report Information

Annual Meeting Dates: 01/04/2022 - 01/06/2022
Period the Report Covers: 01/01/2021 - 01/01/2022

Participants

Brief Summary of Minutes

Please see attached file below for NC1210's annual report.

Minutes Attachment:

NC-1210 Report - January 2022 Meeting.pdf

Accomplishments

Publications

Impact Statements

Date of Annual Report: 03/07/2023

Report Information

Annual Meeting Dates: 01/04/2023 - 01/06/2023
Period the Report Covers: 01/31/2022 - 12/31/2022

Participants

Brief Summary of Minutes

Please see attached file below for NC1210's 2022/23 annual report.

Minutes Attachment:

NC1210_2023 Report_Appendix 3 March 2023.pdf

Accomplishments

Publications

Impact Statements

Date of Annual Report: 02/26/2024

Report Information

Annual Meeting Dates: 01/10/2024 - 01/11/2024
Period the Report Covers: 01/05/2023 - 01/11/2024

Participants

Bullock, David S - dsbulloc@illinois.edu
Boerngen, Maria - maboern@ilstu.edu
Griffin, Terry - twgriffin@ksu.edu
Vanderplas, Susan - svanderplas2@unl.edu
Jung, Jinha - jinha@purdue.edu
Miao, Yuxin - ymiao@umn.edu
Miguez, Fernando - femiguez@iastate.edu
Brorsen, Wade - wade.brorsen@okstate.edu
Ashworth, Amanda - Amanda.Ashworth@ars.usda.gov
Li, Xiaofei - xiaofei.li@msstate.edu
Sheppard, John - john.sheppard@montana.edu
Maxwell, Bruce - bmax@montana.edu
Sun, Xin - xin.sun@ndsu.edu
Guo, Wenxuan - wenxuan.guo@ag.tamu.edu
Tao, Haiying - haiying.tao@uconn.edu
Mieno, Taro - tmieno2@unl.edu
Longchamps, Louis - ll928@cornell.edu
Jha, Gaurav - gjha@ksu.edu
Ransom, Curtis - Curtis.Ransom@usda.gov
Sellars, Sarah - sarah.sellars@sdstate.edu

Brief Summary of Minutes

The 2024 Annual Meeting was held on January 10-11^th in South Padre Island, Texas at the Hilton Garden Inn & Suites Conference Center. See below for an overview of the meeting agenda or view a more detailed agenda at: ICOFPE_2024_Program_aa67d7eab0.pdf (s3.us-east-1.amazonaws.com)

Accomplishments

Outputs: Viable Trial Design Software, Database Development, International Conference for On-Farm Precision Experimentation (ICOFPE 24’), Publications, Presentations. Activities: The NC-1210 Group wrote a proposal and was awarded a $50,000 grant from the USDA National Institute of Food and Agriculture’s Agricultural and Food Research Initiative (NIFA-AFRI, award number 2023-67021-40615) to organize and hold an International Conference for On-Farm Precision Experimentation. The conference was largely successful, bringing together researchers, crop consultants, and farmers from across the world. More can be found about the ICOFPE 24’ at this website: <a href="https://2024.ofpe.org/">https://2024.ofpe.org/</a>. Total registered: 115 Virtual: 15 Students: 19 Countries: 12   - Brazil (2)  - Canada (13)  - China (1)  - Colombia (1)  - Germany (1)  - Italy (1)  - Japan (3)  - Nigeria (2)  - Korea (1)  - South Africa (3)  - Uruguay (1)  - USA (86) Academia: 63 Industry: 52.   Activities: The trial design software of the DIFM cyber-infrastructure is up and running.  Work is proceeding apace with the database development, data processing, reporting and analytical engine components. <h3>Milestones:  Trial Design Integration</h3> Recent improvements to the website include integrating trial design, data processing, and report generation into the single system. Users can now design trials with new software that is based on the excellent prior work from the DIFM team at Purdue. Tools are also now in place to upload and process the applied and yield data through the website. Users can upload the results of a trial, process their data, and get reports automatically. These reports are being constantly improved, and these updates will mean farmers and consultants can get detailed information on the outcomes of the trials without requiring manual creation of the reports. Development is also proceeding with integrating the feedback from ICOFPE to better support users.  <h2>Indicators:  </h2> In preparation for the conference, resources for the servers were increased to help make sure they could handle many simultaneous users. Despite the increased costs in this period, there were still over $20,000 unused free credits at the end of the month. The following figure shows the daily cost to run the services in the Oracle for Research DIFM CIG tenancy. At its peak, the daily cost was $99.17 for this period. To improve efficiency and security, data was transferred to a new tenancy. This allowed DIFM to archive older tools and data that was no longer in use. After transferring all of the data to the new tenancy, multiple cost-saving measures were taken to lower the cost of running the services. With the reduced compute, archived data, and additional adjustments the daily cost was significantly lowered to under $22 per day as seen in the following graph. The same period in January in 2023 had an average daily cost over $120. These savings will help ensure long-term viability of the project.

Publications

Publications   Amanda Ashworth, Phillip Owens, Edwin Winzeler, Tulsi Kharel, Darya Abbasi, Ammar Abdul Motaleb, Yuan Zhou. Tentative title: Site-specific zone management using machine learning. Currently status: working on the analysis and draft. Plan to submit it in August 2024.   Amy Peerlinck and John Sheppard.  Addressing Sustainability in Precision Agriculture via Multi-Objective Factored Evolutionary Algorithms URL: https://www.cs.montana.edu/sheppard/pubs/mic-2022.pdf   Amy Peerlinck and John W. Sheppard. Influence of Variable Grouping on Large-Scale Multi- and Many-Objective Optimization. in preparation (submission by December 23).   Amy Peerlinck and John W. Sheppard. Managing Objective Archives for Solution Set Reduction in Many-Objective Optimization. to appear IEEE Symposium Series on Computational Intelligence, December 2023   Chishan Zhang, Chunyuan Diao, David Bullock, Xiaofei Li, Taro Mieno. Economic Evaluation of Site-specific Nitrogen Management using Extended Geographically Weighted Regression (GWR) Analysis. Status: In progress, with a focus on writing and revising the manuscript. Estimated Timeframe for Submission: Dec 2023   Du, Q., T. Mieno, and D.S. Bullock. Economically Optimal Nitrogen Side-Dressing Based on Vegetation Indices from Satellite Images through On-farm Experiments. Working Paper.   Duff, H., L. Carlisle, P.B. Hegedus, S. Loewen and B.D. Maxwell. 202_. When less is more: A case for converting low-yielding areas to ecological refugia in crop fields. Nature Sustainability (In Review, submitted 4/6/2023)    Duff, H., D. Debinski and B.D. Maxwell. 202_. Ecological refugia enhance biodiversity and crop production in dryland grain production systems URL: https://www.sciencedirect.com/science/article/pii/S0167880923004103?ssrnid=4325712&dgcid=SSRN_redirect_SD   Duff, H., D. Debinski and B.D. Maxwell. 202_. Landscape context affects patch habitat contributions to biodiversity in agroecosystems. J. Applied Ecology (In review, submitted 4/3/2023)   Giorgio Morales and John Sheppard. Counterfactual Explanations of Neural Network-Generated Response Curves URL: https://arxiv.org/abs/2304.04063   Giorgio Morales and John W. Sheppard, ``Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation,'' re-submitted to IEEE Transactions on Neural Networks and Learning Systems, March 2023.   Giorgio Morales and John W. Sheppard, ``Univariate Functional Form Identification in Multivariate Systems Using Transformers," in preparation (submission by January 24)   Giorgio Morales, John Sheppard, Paul Hegedus, and Bruce Maxwell. Improved Yield Prediction of Winter Wheat Using a Novel Two-Dimensional Deep Regression Neural Network Trained via Remote Sensing URL: https://www.mdpi.com/1424-8220/23/1/489   Hegedus, P.B., Maxwell, B.D., Ewing, S.E., & Bekkerman, A. (2023). Development and evaluation of site-specific optimized nitrogen fertilizer management based on maximized profit and minimization of pollution. Paper. Precision Agriculture, Submitted.   Hans Edwin Winzeler, Phillip R. Owens, Tulsi Kharel, Amanda Ashworth, and Zamir Libohova.  Identification and Delineation of Broad-Base Agricultural Terraces in Flat Landscapes in Northeastern Oklahoma, USA  URL: https://www.mdpi.com/2073-445X/12/2/486   Jaeseok Hwang, David S Bullock, Taro Mieno. "What is the Value of On-Farm Precision Experiment Data as a Public.” Working paper, 2025.   Khanal, B., T. Mieno, K. Schoengold, and D.S. Bullock. 2023. Optimizing Precision Conservation with On-Farm Precision Experiment Data: The Role of Crop Insurance and Spatially Variable Profit.   Li, X., Mieno, T. & Bullock, D.S. The economic performances of different trial designs in on-farm precision experimentation: a Monte Carlo evaluation. Precision Agric (2023). https://doi.org/10.1007/s11119-023-10050-8   Loewen, S. and B.D. Maxwell. 202_. Optimizing Cover crop seeding rates and following cash crops to maximize net return in organic grain farming. Ecosphere. In review Submitted 8/29/2023    Loewen, S. and B.D. Maxwell. 202_. Optimizing Crop Seeding Rates On Organic Grain Farms Using On Farm Precision Experimentation. Field Crops Research. In Review. Submitted 9/17/2023   Mills, B.E., B.W. Brorsen, D. Poursina, and D.B. Arnall. Optimal grid size for site-specific nutrient application URL: https://doi.org/10.1111/agec.12802   Mieno, T., X. Li, and D.S. Bullock. 2023. Bias in Economic Evaluation of Variable Rate Application based on Geographically Weighted Regression Models with Mis-specified Functional Form.    Mieno, T., Li, X., and Bullock, D. S. “Economic Evaluation of Misspecified Geograph-ically Weighted Regression Models for Site-specific Nitrogen Management.” Journal of the Agricultural and Applied Economics Association. (Revise & Resubmit)   Nan Li, David Bullock, Carrie Butts‐Wilmsmeyer, Laura Gentry, Greg Goodwin, Jaeyeong Han, Nathan Kleczweski, Nicolas F. Martín, Patricia Paulausky, Pete Pistorius, Nicholas Seiter, Nathan Schroeder, and Andrew J. Margenot. Distinct soil health indicators are associated with variation in maize yield and tile drain nitrate losses URL: https://ui.adsabs.harvard.edu/abs/2023SSASJ..87.1332L/abstract   Negrini, R., Mizuta, K. Miao, Y., Stueve, K., Lacerda, L., Anthony, P., Coulter, J. Evaluating the potential of variable rate sulfur management for corn in Minnesota, in preparation, to be submitted in 2024.   Patterson, G. Cole. 2023. Using Informative Bayesian Priors and On-Farm Experimentation to Predict Optimal Site-Specific Nitrogen Rates URL: file:///C:/Users/jbruner9/Downloads/Poster_Ngombe_Brorsen.pdf   Paul Hegedus, Bruce Maxwell, John Sheppard, Sasha Loewen, Hannah Duff, Giorgio Morales-Luna, and Amy Peerlinck. Towards a Low-Cost Comprehensive Process for On-Farm Precision Experimentation and Analysis URL: https://www.mdpi.com/2077-0472/13/3/524   Paul Hegedus, Stephanie Ewing, Claim Jones, and Bruce Maxwell. Using spatially variable nitrogen application and crop responses to evaluate crop nitrogen use efficiency URL: https://ui.adsabs.harvard.edu/abs/2023NCyAg.126....1H/abstract   Poursina, D., and B.W. Brorsen. 2023. Fully Bayesian Economically Optimal Design for Spatially Varying Coefficient Linear Stochastic Plateau Model. Submitted to Stochastic Environmental Research and Risk Assessment. In second review    Poursina, D., and B.W. Brorsen. Site-Specific Nitrogen Recommendation: Fast, Accurate, and Feasible Bayesian Kriging. To be submitted to Precision Agriculture    Qeiroz, P.W., R.K. Perrin, L.E. Fulginiti, and D.S. Bullock. 2023. Expected Payoff from a Variable Rate Nitrogen Application:  an Expect Value of Sample Information (ESVI) Approach. Submitted to the American Journal of Agricultural Economics.   Tanaka, T.S.T., G.B.M. Heufelink, T. Mieno, and D.S Bullock. 2023. Provide Accurate Fertilizer Recommendations.    Tibbs, R.G. and M.A. Boerngen. "Understanding Farmers’ Views of On-Farm Precision Experimentation Through Interviews” to be submitted to Agricultural & Environmental Letters, within the next month or so.   Tibbs, R.G., M.A. Boerngen, and N. Heller. "Farmers’ Perceptions of and Interest in Conducting On-Farm Precision Experimentation" to be submitted to Precision Agriculture in Spring 2024   Zhang, C., Li, X., Mieno, T., and Bullock, D. S. 2024. Performances of Quadratic-Plateau Geographically Weighted Regression Model in Site-specific Yield Response Estimation. Target Journal: Precision Agriculture.   Zhang, C., X. Li, T. Mieno, C. Diao, and D.S. Bullock. 2024. Use of a Quadratic-plateau Geographically Weighted Regression Model for Estimating Site-specific Economically Optimal Input Rates.       Presentations   Amanda Ashworth. Machine Learning for Site-Specific Management in Precision Agriculture, April 2023, Innovation Day, University of Text at Arlington. Video Link: https://uta.engineering/innovationday/project-2023.php?p=78&h=63201076a0a47964cfa8837f30a8805a.   Brorsen, B.W. 2023. Nitrogen Use Efficiency and Economic Hurdles. Nitrogen Use Efficiency Meeting 2023, Stillwater, OK. Poursina, D., and B.W. Brorsen. 2023.   Bullock, D.S., Conducting Field Trials with the Iowa Nitrogen Initiative and the Data-Intensive Farm Management Project. Iowa Nitrogen Initiative Farmers. Washington, Iowa. February 24 2023.    Bullock, D.S., The Data-Intensive Farm Management Project. Researchers and administrators at the Quebec Ministry of Agriculture and Fisheries. Quebec City Canada. March 29 2023.   Bullock, D.S., The Data-Intensive Farm Management Project. Quebec farmers, consultants and researchers, in cooperation with the Quebec Ministry of Agriculture and Fisheries. Trois Rivieres Quebec Canada. March 31 2023.   Bullock, D.S., The Data-Intensive Farm Management Project. Quebec farmers, consultants and researchers, in cooperation with the Quebec Ministry of Agriculture and Fisheries. St. Cesaire Quebec Canada. March 30 2023.    Bullock, D.S., The Data-Intensive Farm Management Project:  Progress, Challenges, and Results in On-Farm Precision Experimentation. ACE Weekly Seminar Series. Urbana, Illinois. April 7 2023.   Bullock, D.S., Discussion: Agrithority and DIFM. Agrithority Virtual Presentation. January 16 2023.    Bullock, D.S., Discussion: Amplify-Brookside and DIFM. Amplify-Brookside Virtual Presentation. January 31 2023.    Bullock, D.S., Discussion: Minnesota Crop Production Retailers and DIFM. Minnesota Crop Production Retailers Association Virtual Presentation. February 13 2023.    Bullock, D.S., La Experimentación a de Precisión a Campo:  Una Oportunidad de Colaboración entre el Proyecto DIFM y los Productores Uruguayos. Annual Meeting of ProNutrion Producers. Colonia del Sacramento Uruguay. September 1 2023.    Bullock, D.S., Improving Outcomes through On-farm Precision Experimentation" (*Invited Speaker). KATCON 2023, sponsored by the Kansas Agricultural Research and Technology Association (KARTA). Junction City Kansas. January 19 2023.    Bullock, D.S., On-farm Precision Experimentation:  An Opportunity for Collaboration between Brazilian Farmers and DIFM. Rumo Agro (25 Brazilian farmers visiting the U.S.). Urbana, Illinois. August 28 2023.    Bullock, D.S., On-farm Precision Experimentation with the Data-Intensive Farm Management Project. Presentation before Alberta and Saskatchewan commodity groups. Olds College Alberta. November 20 2023.    Bullock, D.S., On-farm Precision Experimentation with the Data-Intensive Farm Management Project. Presentation before the Ontario Ministry of Agriculture, Food and Rural Affairs (and various farmer and commodity groups). Virtual. November 30 2023.   Bullock, D.S., Progress and Status of the Data-Intensive Farm Management Project. Researchers in and Administrators of the NRCS-Conservation Innovation Grant Program. Des Moines Iowa. August 7 2023.    Bullock, D.S., Some Thoughts on On-farm Precision Experimentation with Cover Crops. Researchers and administrators at the Quebec Ministry of Agriculture and Fisheries. Quebec City Canada. March 20 2023.   Bullock, D.S., The State of the DIFM Project.” DIFM/NC-1210 Annual Meeting. Corpus Christi Texas, January 5 2023.    Bullock, D.S., Some Thoughts on On-farm Precision Experimentation with Cover Crops. Quebec farmers, consultants and researchers, in cooperation with the Quebec Ministry of Agriculture and Fisheries. Trois Rivieres Quebec Canada. March 31 2023.   Bullock, D.S., Une rencontre d’information sur les possibilités de démarrer des essais à la ferme en 2023, utilisant l’agriculture de précision (Bullock attended to answer audience questions.) Quebec farmers, consultants and researchers, in cooperation with the Quebec Ministry of Agriculture and Fisheries. Virtual. April 27 2023.   Bullock, D.S., Using the (free!) Data-Intensive Farm Managment Project’s Tools to Design and Analyze Your On-Farm Trials. Kansas Agricultual Technologies Conference. Manhattan Kansas. January 26 2024.    Bullock, D.S., Using On-farm Precision Experimentation for Improved Nitrogen Fertilizer Efficiency and Mitigation of Greenhouse Gas Emissions. Presentation at the Journée d´échanges Scientifiques:  Utilisation déngrais azoté et réduction GES conference, sponsored by the Quebec Minsitry of Agriculture, Fisheries and Food. Virtual. Novemebr 28 2023.    Bullock, D.S., Why Agriculture Big Data Needs On-Farm Precision Experimentation (and Vice-Versa). International Conference for On-Farm Precision Experimentation. South Padre Island Texas. January 8 2024.    Bullock, D.S., Working with the Data-Intensive Farm Management Project to Conduct On-Farm Precision Experiments. Virtual Symposium:  Harvesting Insights with Data-Driven On-Farm Precision Experimentation. February 13, 2024.    Bullock, D.S., You May Not Want to Use "Yield Potential" to Make Input Management Decisions.  Instead:  Conduct On-Farm Precision Experiments! Michigan State University Field Crops Webinar. February 27 2023.    Bullock, D.S., B. Edge, and T.Mieno. A Microeconomic Perspective on the Value of OFPE Data in Management Zone Delineation. 6th Symposium on Agri-Tech Economics for Sustainable Futures. Harper Adams University, England. September 18 2023.    Bullock, D.S., B. Edge, and T.Mieno. A Microeconomic Perspective on the Value of OFPE Data in Management Zone Delineation. Second International Conference on Farmer-centric On-farm Experimentation. Virtual. December 5 2023.    Brorsen, B.W. 2023. “Fully Bayesian Economically Optimal Design for Spatially Varying Coefficient Linear Stochastic Plateau Model.” Presentation. StanCon 2023, St. Louis, MO, June.   Du, Q. 6th Symposium on Agri-Tech Economics for Sustainable Futures. 18-19 September 2023, Harper Adams University, Newport, U.K.    Duff. H., PhD Dissertation Defense Presentation Talk 4/13/2023    Hwang. J., 6th Symposium on Agri-Tech Economics and Sustainable Future. https://store.harper-adams.ac.uk/product-catalogue/on-campus-events/on-campus-events/6th-giate-symposium   Li, X., Mieno, T., Bullock, D. S., Gong, A., Edge, B., Du, Q., and Hwang, J. “Economic Evaluation of Variable Rate Application using On-Farm Precision Experimentation Data.” AI in Agriculture: Innovation and Discovery to Equitably Meet Producer Needs and Per-ceptions, Orlando, FL, April 17-19, 2023    Loewen. S,- PhD Dissertation Defense Presentation 4/14/2023 talk begins at 12:08, it is labeled. Recording link: https://montana-student.webex.com/montana-student/ldr.php?RCID=4617a4980f06f032f3a8219991d8cb8f Password: Ye6rzm4Y   Loewen. S, LRES Seminar 2/27/2023 link: https://montana.webex.com/montana/ldr.php?RCID=c1e6e2f69d37cb50eaad671214db70d8    Morales. G., Counterfactual Explanations of Neural Network-Generated Response Curves, IEEE International Joint Conference on Neural Networks, July 2023.    Sheppard, J., Demystifying Machine Learning through eXplainable Artificial Intelligence (XAI). Optical Technology Center Colloquium, Montana State University, February 10, 202   Sheppard, J., Insurance Innovation, Artificial Intelligence, & What to Watch For In Montana. CSI Insurance Summit, Butte, MT, September 13, 2023 (included DIFM as a case study).   Tibbs. R, and M. Boerngen. Examining the Perceptions of Precision Agriculture Technologies and On-Farm Precision Experimentation - Rural Sociological Society Annual Meeting, August 1-6, 2023, Burlington, VT. https://www.dropbox.com/scl/fi/twyolv3gl654mlgozxgq9/Revised-Final-RSS-Program-2023.pdf   Vanerplas. S, "Redesigning Yield Maps for Comprehension and Usability". Symposium on Data Science and Statistics. https://ww3.aievolution.com/AMSTATevents/index.cfm?do=cnt.appLoader&routerAction=runCustomSearch#/searches/load/Sessions_SDSS

Impact Statements

NC1210 members wrote a grant proposal and won a $4-million grant from USDA-NRCS, and has used the funding to promote on-farm precision experimentation throughout the world. • NC1210 and its DIFM affiliates have development a “minimum viable product” of its promised cyber-infrastructure, which was debuted at its January 2024 International Conference for On-farm Precision Experimentation. Over 200 on-farm precision experiments have been run with participating farmers in approximately 20 states on three continents • Dozens of farmers and crop consultants are now working with that cyber-infrastructure to design OFPEs for the 2024 growing season. • NC1210 and its DIFM members have agreed to begin conducting collaborative research with the companies Microsoft, Precision Planting, and Trilogy Networks.

Date of Annual Report: 03/06/2025

Report Information

Annual Meeting Dates: 01/09/2025 - 01/10/2025
Period the Report Covers: 01/01/2024 - 01/01/2025

Participants

Abban-Baidoo, Emmanuel Auburn University
Adotey, Nutifafa University of Tennessee
Ashworth, Amanda USDA-ARS
Augarten, Abby University of Wisconsin-Madison
Baath, Gurjinder Texas A&M
Boerngen, Maria Illinois State University
Brorsen, Wade Oklahoma State University
Bugingo, Collins Oregon State
Bullock, David University of Illinois
Chandel, Abhilash Virginia Tech
Clark, Jason South Dakota State University
Delport, Marion BFAP
Dey, Sourajit Kansas State University
Dhillon, Jagmandeep Mississippi State University
Dos Santos, Caio Iowa State
Du, Qianqian University of Illinois
Edge, Brittani University of Illinois
Felehgari, Shilan Montana State
Gabbard, Daniel (Scott) Purdue
Griesbaum, Brett Montana State
Griffin, Terry Kansas State University
Islam, Md. Sayemul Montana State
Jones, Carli University of Illinois
Kumar, Hemendra University of Maryland
Lanza, Phillip Cornell
Leise, Adam University of Nebraska-Lincoln
Li, Johnny University of Idaho
Li, Xaiofei Mississippi State University
Liu, Guodong University of Florida
Miao, Yuxin University of Minnesota
Mieno, Taro University of Nebraska-Lincoln
Miguez, Fernando Iowa State
Mousavi, Mona University of Nebraska-Lincoln
Negrini, Renzo University of Minnesota
Nugent, Paul Montana State
Pinto, Ricardo Montana State
Pires, Carlos North Dakota State University
Proulx, Rob North Dakota State University
Ransom, Curtis USDA-ARS
Schwarck, Lauren Iowa State
Setiyono, Tri Louisiana State University
Shajahan, Sunoj University of Illinois
Sheppard, John Montana State
Stechschulte, Logan University of Illinois
Sundquist, Aaron Mitchell Tech
Tao, Haiying University of Connecticut
Van Der Westhuizen, Divan BFAP
Wahl, Scott University of Illinois
Won, Sunjae Auburn University
Yost, Matt Utah State University
Zheng, Yiling University of Connecticut
Zhou, Congliang Louisiana State University
Owens, Phillip USDA-ARS
Sun, Rex North Dakota State University

Brief Summary of Minutes

See attached meeting minutes.

Accomplishments

Short-term Outcomes: As part of NC-1210, in 2016 DIFM scholars submitted and received $4 million from USDA-NRCS, with the purpose of working with famers to run several hundred on-farm precision experiments and creating a "cyber-infrastructure" that enables users to create OFPE designs, to import, process, and analyze OFPE data, and to write reports on the agronomic and economic implications of the data analysis.  DIFM and NC-1210 have accomplished these goals. This system is freely available to the public at <a href="https://difm.farm">https://difm.farm</a>.  The sytem is now being used by dozens of farmers, crop consultantsj, extension personnel and agronomic researchers  to run OFPEs and evaluate the economic implications for crop production management.  From some of the trials, data-driven insights are leading to dramatic increases in profits.  Other trials have provided mixed results.  We expect the insights and social benefits derived for the OFPE data we are working with farmers to generate will only grow as the development and use of the difm.farm cyber-infrastructure progress and goals have been accomplished. Outputs: A major insight from the data the DIFM project has generated is that producers’ corn and soybean seed planting densities are often higher than economically optimal.  On some farms, particularly those in the drier parts of the Corn & Soy Belt, the planting rates recommended by seed companies and university extension guidelines seem often to be higher than is economically optimal.  Another insight is that farmers’ nitrogen fertilizer application rates, in contrast to wide speculation, are not in general higher than the economically optimal rates. This means that there is no “win-win” opportunity available in which farmers increase profits by cutting their fertilization rates and thereby reduce drop nutrient losses into the nations’ water systems.  The implication is that the environmental costs of fertilizer application aren’t just going to go away.  Government policies that change farmers’ production management incentives are necessary. The DIFM project is just beginning to work with trials to examine the economic effects of various kinds of eco-friendly crop production practices.    Activities: NC1210 and DIFM have been working closely with farmers, crop advisors, extension personnel using the cyber-infrastructure to conduct on-farm research.  We expect for the system to be used to run at least 150 OFPEs in the 2025 growing season.  This collaboration involves daily communication among NC1210 personnel and difm.farm users.  Held weekly "trouble-shooting" sessions to help users with the system.  We are continuing to develop the background computer code and user-interface that are key to the difm.farm system. In January 2025, NC1210 and DIFM held a conference titled "Opportunities for Extension for On-farm Precision Experimentation," in which we provided training in use of the difm.farm cyber-infrastructure to over fifty extension agents, specialists, and university faculty, many of whom are beginning to work with farmers in their states to run OFPEs in 2025. In Janary 2025, held the DIFM/NC1210 meeting, attended by approximately 70 scholars conducting OFPE research.  They made dozens of presentations to report the results of OFPE research.   Milestones: Finished the creation a fully working cyber-infrastructure, freely and publicly accessible through difm.farm.  The system was used to run nearly 100 OFPEs in 2024, and we expect it to be used to run over 150 OFPEs, on fields in over twenty U.S. states, four Canadian provinces, South Africa and Brazil in 2025.

Publications

Manuscripst published or forthcoming:  Negrini, R., Miao, Y., Mizuta, K., Stueve, K., Kaiser, D., & Coulter, J. (2024). Spatial and temporal variability in optimal sulfur rates for corn in Minnesota: implications for Precision sulfur management. Negrini, R., Miao, Y., and Stueve, K. (2024). Identifying key factors influencing corn responses to sulfur fertilizer application under on-farm conditions using machine learning. dos Santos, Caio and Miguez, Fernando E., Pacu: Precision Agriculture Computational Utilities. Available at SSRN: https://ssrn.com/abstract=4946676 or http://dx.doi.org/10.2139/ssrn.4946676 Working paper on using satellite images for estimating planting and harvest date. Tentative. Authors: Caio dos Santos, Laila Puntel, David Bullock, others, Fernando Miguez Poursina, D., and B.W. Brorsen. 2024.  “Site-Specific Nitrogen Recommendation: Fast, Accurate, and Feasible Bayesian Kriging.” Computational Statistics. In Press Poursina, D., and B.W. Brorsen. 2024. “Fully Bayesian Economically Optimal Design for Spatially Varying Coefficient Linear Stochastic Plateau Model.” Stochastic Environmental Research and Risk Assessment. 38:1089-1098. Poursina, D., B.W. Brorsen, and D.M. Lambert. 2024. “Optimal Treatment Placement for On-Farm Experiments: Pseudo-Bayesian Optimal Designs with a Linear Response Plateau Model.” Precision Agriculture. In Press Park, E., B.W. Brorsen, and X. Li. 2024. “Using Data from Uniform Rate Applications for Site-Specific Nitrogen Recommendations.” Journal of Agricultural and Applied Economics. 56: 138-154. Zhang, Y., and B.W. Brorsen. 2024. “Optimizing Nitrogen Rates in Corn Production: A Multi-Degree Spline Approach.” Selected paper. Agricultural and Applied Economics Association annual meeting. T Mieno, J Hwang, DS Bullock. Learning about Optimal Corn Seed Rate Management Via On-farm Experimentation: Are Farmers Over-planting? M Mousavi, T Mieno, DS Bullock. A new model selection approach based on local economically optimal input rate. Q Du, T Mieno, DS Bullock. Measuring the Estimation Bias of Yield Response to N Using Combined On-Farm Experiment Data. Tanaka, T. S., Heuvelink, G. B., Mieno, T., & Bullock, D. S. (2024). Can machine learning models provide accurate fertilizer recommendations?. Precision Agriculture, 1-18. Mieno, T., Li, X., & Bullock, D. S. (2024). Bias in economic evaluation of variable rate application based on geographically weighted regression models with misspecified functional form. Journal of the Agricultural and Applied Economics Association, 3(1), 135-151. Qianqian Du, Taro Mieno, and David S. Bullock. Measuring the Estimation Bias of Yield Response to N Using Combined On-Farm Experiment Data. Under revision (JAAEA). Farmers’ perceptions of and interest in conducting on-farm precision experimentation, in preparation, anticipated submission December 2024.  Authors Tibbs, Bullock, Heller, Boerngen Evaluating the Profitability of Corn Seeding1 Decisions: Insights from On-Farm Precision Experiments Data (Jaeseok Hwang , David S Bullock, Taro Mieno). Giorgio Morales and John W. Sheppard, "Univariate Skeleton Prediction in Multivariate Systems Using Transformers," Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Vilnius, Lithuania, September 2024. Giorgio Morales and John W. Sheppard, "Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones," Proceedings of the International Joint Conference on Neural Networks, Yokohama, Japan, July 2024. Giorgio Morales and John W. Sheppard, "Adaptive Sampling to Reduce Epistemic Uncertainty Using Prediction Interval-Generation Neural Networks," submitted to the 39th Annual AAAI Conference on Artificial Intelligence, Philadelpha, PA, 2025. Edge, Brittani; Taro Mieno, and David S. Bullock. Impact of Machinery Misalignment on Economic Results through Jensen’s Inequality in On-Farm Precision Experiments. Status: Needs updating and revisions. Estimated publication: within 2025 if time permits more time to work on this after January conference. Duff, H., D. Debinski and B.D. Maxwell. 2024. Ecological Refugia Enhance Biodiversity, Ecosystem Services, and Crop Production in Agroecosystems. Agriculture, Ecosystems and Environment. 359: 108751 <a href="https://urldefense.com/v3/__https:/doi.org/10.1016/j.agee.2023.108751__;!!DZ3fjg!5v7mBKoK2-81u27p6RW_9QEkLPc0mwRxEf8WAP3Pd5vL8zlVghSwF7P-51OVpuLddiWaLpjQCygT-2Rl2dM$">https://doi.org/10.1016/j.agee.2023.108751</a> Duff, H., D. Debinski and B.D. Maxwell. 2024. Landscape context affects patch habitat contributions to biodiversity in agroecosystems. Ecosphere. <a href="https://urldefense.com/v3/__https:/doi.org/10.1002/ecs2.4879__;!!DZ3fjg!5v7mBKoK2-81u27p6RW_9QEkLPc0mwRxEf8WAP3Pd5vL8zlVghSwF7P-51OVpuLddiWaLpjQCygTtBGU4vE$">https://doi.org/10.1002/ecs2.4879</a> Maxwell, B. D., & Duff, H. (2024). Increasing the scope and scale of agroecology in the Northern Great Plains [Commentary]. Journal of Agriculture, Food Systems, and Community Development. Advance online publication. <a href="https://urldefense.com/v3/__https:/doi.org/10.5304/jafscd.2024.133.0XX__;!!DZ3fjg!5v7mBKoK2-81u27p6RW_9QEkLPc0mwRxEf8WAP3Pd5vL8zlVghSwF7P-51OVpuLddiWaLpjQCygTfrsJPb8$">https://doi.org/10.5304/jafscd.2024.133.0XX</a> Loewen, S. and B.D. Maxwell. 2024. Optimizing cover crop seeding rates and following cash crops to maximize net return in organic grain farming. Field Crop Research. Accepted 9/13/2024  Loewen, S. and B.D. Maxwell. 2024. Site Specific Weed Management on Organic Grain Farms using Variable Rate Seeding and Data Driven Simulation. Weed Research  Accepted 10/28/2024  Flávia Luize Pereira de Souza, Maurício Acconcia Dias, Tri Deri Setiyono, Sérgio Campos, Haiying Tao, Luciano Shozo Shiratsuchi. Identification of soybean planting gaps using machine learning. Journal Smart Agricultural Technology. Submitted.  Flávia Luize Pereira de Souza, Luciano Shozo Shiratsuchi, Haiying Tao, Maurício Acconcia Dias, Marcelo Rodrigues Barbosa Júnior, Tri Deri Setiyono, Sérgio Campos. Counting soybean plants by UAV RGB Imagery: an effective approach during phenological changes. Agrosystems, Geosciences & Environment. Submitted.  Flávia Luize Pereira de Souza, Luciano Shozo Shiratsuchi, Haiying Tao, Maurício Acconcia Dias, Marcelo Rodrigues Barbosa Júnior, Tri Deri Setiyono, Sérgio Campos. Soybean plant count based on multisensor images. Precision Agriculture. Under Review.  Flávia Luize Pereira de Souza, Haiying Tao, David Bullock, Brittani Edge. Spatial variability of optimum chloride application rate in a soft white winter wheat field. Agronomy Journal. Under Prep.   Presentations & Interviews:  Bullock, D.S.  "Why Agricultural Big Data Needs On-farm Precision Experimentation (and Vice-versa).” International Conference for On-farm Precision Experimentation.  South Padre Island, TX.  1/8/24.   Bullock, D.S.  "Using the (free!) Data-Intensive Farm Management Project’s Tools to Design and Analyze Your On-farm Trials".  Kansas Agricultural Technologies Conference.  Manhattan, KS.  1/26/24.   Bullock, D.S.  "Working with the Data-Intensive Farm Management Project to Conduct On-Farm Precision Experiments". Virtual Symposium:  Harvesting Insights with Data-Driven On-Farm Precision Experimentation.  2/13/24. Bullock, D.S.  “Working with DIFM and Trilogy on On-farm Precision Experimentation.”  Trilogy Corporation.  Fargo, North Dakota.  3/19/2024.   Bullock, D.S., R.E. Dunker, and S. Wahl.  "Improving the Economic and Ecological Sustainability of US Crop Production through On-farm Precision Experimentation."  NRCS SNTSC Technology Advisory Board Meeting.  Virtual.  3/26/24.   Bullock, D.S.  "On-Farm Precision Experimentation: Methods and Results.  Univesity of Illinois Dept of Agricultural and Consumer Economics FACS Workshop.  Urbana, Illinois.  4/3/24. Bullock, D.S.  “What DIFM Can Offer Microsoft and Project FarmVibes.”  Virtual.  Meeting with Ranveeer Chandra, Managing Director and Chief Technology Officer of Agri-Food at Microsoft.  4/13/24.   Bulllock, D.S.  "On-Farm Precision Experimentationand the Data-Intensive Farm Management Program: Methods and Results" (*Invited speaker).  IoT4Ag Group.  Purdue University, W. Lafayette, IN.  4/5/24. ‘ Bullock, D.S.  "New Opportunities for U of I Extension:  On-Farm Precision Experimentation with DIFM, Farmers and CCA.”  Meeting of the Illinois Extension Commercial Agriculture Team.  Virtual.  4/12/24.   Bullock, D.S,  "An Opportunity for Illinois Farmers: On-farm Research with the Data-Intensive Farm Management Project."  Interview for WILL radio with Todd Gleason.  University of Illinois Extension.  4/26/24.   Bullock, D.S., and J. Jung.  "Using On-farm Precision Experimentation to Incentivize Cost-effective Climate-friendly Crop Research, Policy, and Production."  Presentation to Tim Pilwkowski, NRCS National Nutrient Management Discipline Lead.  Virtual.  5/23/24.   Bullock, D.S.  "Conducting On-farm Precision Experimentation with U of I Extension and the Data-Intensive Farm Management Project."  University of Illinois Extension Ewing Field Day.  Illinois Extension Ewing Demonstration Center.  7/25/24.   Bullock, D.S.  "The Data-Intensive Farm Management Project:  On-Farm Nitrogen Rate Experiments."  The Nitrogen Use Efficiency Workshop.  Urbana, Illinois.  8/5/24. Bullock, D.S.  "Vayda-DIFM Discussion:  On-farm Precision Experimentation and Regenerative Agriculture."  Virtual.  8/27/24.   Bullock, D.S.  "Opportunities for Data-intensive Farm Management in Africa" United Nations Science Summit:  "4IR Opportunities for Agriculture in Africa."  Virtual (*invited speaker*).  9/25/24.   Bullock, D.S.  "The Data-Intensive Farm Management Project and Opportunities for On-farm Precision Experimentation."  Interview with Matthew Grassi, Technology & Machinery Editor of Farm Journal.  Telephone.  9/26/24.   Bullock, D.S.  "The Data-Intensive Farm Management Project and Opportunities for On-farm Precision Experimentation."  Auburn University Dept of Crop, Soil and Environmental Sciences.  Auburn, Alabama.  10/18/24.   Bullock, D.S.  "YARA-DIFM Discussion:  Opportunities for On-farm Precision Experimentation." Representatives for YARA North America.  Virtual.  10/28/24.   Negrini, R., Miao, Y. (Corresponding Author), Mizuta, K., Stueve, K., Kaiser, D., & Coulter, J. (2024). Within-field Spatial Variability in Optimal Sulfur Rates for Corn in Minnesota: Implications for Precision Sulfur Management. ISPA; Kechchour, A., Miao, Y. (Corresponding Author), Folle, S., & Mizuta, K. (2024). On-farm Evaluation of the Potential Benefits of Variable Rate Seeding for Corn in Minnesota. 16th International Conference on Precision Agriculture, Manhattan, KS. (July 21-24, 2024); Negrini, R., Miao, Y., (Advisor) "Optimizing Sulfur Management in Corn through On-Farm Experimentation and Machine Learning in Minnesota: A Study on Within-Field Variability and Limiting Factors," 2024 ASABE North Central Regional Section Meeting, Brookings, South Dakota. (April 12, 2024). Miguez, Fernando E. Integrating Nonlinear Models and Remotely Sensed Data to Estimate Crop Cardinal Dates. <a href="https://www.ispag.org/proceedings/?action=abstract&id=10092">https://www.ispag.org/proceedings/?action=abstract&id=10092</a> Patterson, C., B.W. Brorsen, D. Poursina, T. Mieno, B.K. Edge, and E.D. Nafziger. 2024. “Using Informative Bayesian Priors and On-Farm Experimentation to Predict Optimal Site-Specific Nitrogen Rates.” Presentation. International Society of Precision Agriculture, Manhattan, KS.  "A new model selection approach based on local economically optimal input rate" by Mona Mousavi at the annual AAEA conference. <a href="https://www.aaea.org/UserFiles/file/aaea_202407_agenda_pdf_daily.pdf">https://www.aaea.org/UserFiles/file/aaea_202407_agenda_pdf_daily.pdf</a> John Sheppard, Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones, International Joint Conference on Neural Networks, Yokohama, Japan, 9/9/24. Giorgio Morales, "Decomposable Symbolic Regression Using Transformers and Neural Network-Assisted Genetic Algorithms," PhD Forum, European Conference on Machine Learning, Vilnius, Lithuania Giorgio Morales, "Discovery Challenge: Seismic Monitoring and Analysis Challenge," First-Place Award, European Conference on Machine Learning, Vilnius, Lithuania. Giorgio Morales, "Univariate Skeleton Prediction in Multivariate Systems Using Transformers," Paper Presentation, European Conference on Machine Learning, Vilnius, Lithuania Giorgio Morales, AI and Agriculture, INBRE Workshop on Artificial Intelligence, Butte, MT, 10/21/24 John Sheppard, "AI and Society: Why It Matters," Gallatin Valley Friends of the Sciences, Bozeman, MT, 10/16/24 Edge, Brittani. Presentation at AgSmart 2024 at Old's College to present the DIFM tools and discuss what we have learned implementing OFPE's for seven years. SOUZA, F. L. P.; SHIRATSUCHI, L. S; TAO, H.; DIAS, M. A.; JÚNIOR, M. R. B.; SETIYONO, T.; CAMPOS, S.  Computer vision by UAVs for estimate soybean population across different physiological growth stages and sowing speeds. 16th International Conference on Precision Agriculture. Manhattan, Kansas, United States, 2024. SOUZA, F. L. P.; SHIRATSUCHI, L. S; TAO, H.; DIAS, M. A.; JÚNIOR, M. R. B.; SETIYONO, T.; CAMPOS, S.  Optimizing soybean management with UAV RGB and multispectral imagery: A Neural Network method and image processing. 16th International Conference on Precision Agriculture. Manhattan, Kansas, United States, 2024. SOUZA, F. L. P.; NEGRINI, R.; TAO, H.  Optimizing Chloride (Cl) Application for Enhanced Agricultural Yield. 16th International Conference on Precision Agriculture. Manhattan, Kansas, United States, 2024. SOUZA, F. L. P.; DIAS, M. A.; SETIYONO, T.; CAMPOS, S.; TAO, H.; SHIRATSUCHI, L. S. How can machine learning assist in identifying issues in soybean planting? Conference for On-farm Precision Experimentation 2024. Hilton Garden Inn South Padre Island Beachfront; City: South Padre Island, Texas; Sponsor: Data-Intensive Farm Management Project (DIFM). SOUZA, F.L.P. Automatic counting of soybean plants with computer vision and Artificial Intelligence and data from Remotely Piloted Aircraft – RPA. Brazil. UNESP. PhD thesis. 2024. <a href="https://hdl.handle.net/11449/255297">https://hdl.handle.net/11449/255297</a>

Impact Statements

NC1210 Impact Statement NC1210’s work resulted in farmers and their advisors running of approximately one hundred OFPEs in 2024. Those field trials were run in approximately twenty U.S. states, four Canadian provinces, and South Africa. The data generated by the field trials were gathered, processed, organized, managed and analyzed using the difm.farm, and each grower received detailed reports on the management implications of their trials. Many farms will make management changes based on their data, and some will generate significant increase in profits as a result. NC1210’s work created the difm.farm cyber-infrastructure, and trained over fifty U.S. Extension personnel in its use. As of March 2025, this training has resulted in Extension personnel beginning to work with dozens of U.S. farmers and crop consultants to conduct on-farm research in 2025.j NC1210’s work in 2024 and earlier has resulted in a “snowballing” effect in on-farm precision experimentation. Interest is rapidly increasing all over the world. Indicators include the dozens of new farms, crop advising companies and extension personnel who have recently agreed to run OFPEs in 2025.