TY - GEN
T1 - Extensible framework for analysis of farm practices and programs
AU - Satheesan, Sandeep Puthanveetil
AU - Bhattarai, Rabin
AU - Bradley, Shannon
AU - Coppess, Jonathan
AU - Gatzke, Lisa
AU - Gupta, Rishabh
AU - Jeong, Hanseok
AU - Lee, Jong S.
AU - Naraharisetty, Gowtham
AU - Ondrejcek, Michal
AU - Schnitkey, Gary Donald
AU - Zhao, Yan
AU - Navarro, Christopher M.
N1 - Funding Information:
This material is based upon work supported by the Illinois Nutrient Research and Education Council (NREC), the McKnight Foundation, the Gardner Agricultural Policy Program (GAPP) in the Department of Agricultural and Consumer Economics (ACE) at the University of Illinois at Urbana-Champaign and by a cooperative agreement
Publisher Copyright:
© 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2019/7/28
Y1 - 2019/7/28
N2 - We present an open source extensible web framework for the analysis of different farm practices and programs and easy dissemination of their results to the users. Currently, this framework is being applied to two use cases — a web-based decision support system for cover crop management and a web-based farm program analysis tool to assist farmers, academics, and policymakers to understand programs and policies surrounding the Farm Bill. Through the first use case, we address the problem of bridging the gap between the scientific research that happens in labs and experimental plots and the day to day practices and decisions taken by the farmers in the fields. Specifically, this use case focuses on the practice of cover crops, their management, and the impact on reducing nutrient runoff into water bodies. Through the second use case, we address the problem of predicting the expected payment amounts and measured risk or probability of payment for different government insurance programs authorized by the 2018 Farm Bill, namely the Agriculture Risk Coverage (ARC) and Price Loss Coverage (PLC). This helps the farmers compare these programs based on forecasted crop yields and prices. In this paper, we describe the overall architecture of the framework and its major components, the use cases that are currently benefiting from using this framework and share screenshots of the web applications developed using this framework for those use cases. We also share our plans for future work and conclusions about applying this framework to the two use cases.
AB - We present an open source extensible web framework for the analysis of different farm practices and programs and easy dissemination of their results to the users. Currently, this framework is being applied to two use cases — a web-based decision support system for cover crop management and a web-based farm program analysis tool to assist farmers, academics, and policymakers to understand programs and policies surrounding the Farm Bill. Through the first use case, we address the problem of bridging the gap between the scientific research that happens in labs and experimental plots and the day to day practices and decisions taken by the farmers in the fields. Specifically, this use case focuses on the practice of cover crops, their management, and the impact on reducing nutrient runoff into water bodies. Through the second use case, we address the problem of predicting the expected payment amounts and measured risk or probability of payment for different government insurance programs authorized by the 2018 Farm Bill, namely the Agriculture Risk Coverage (ARC) and Price Loss Coverage (PLC). This helps the farmers compare these programs based on forecasted crop yields and prices. In this paper, we describe the overall architecture of the framework and its major components, the use cases that are currently benefiting from using this framework and share screenshots of the web applications developed using this framework for those use cases. We also share our plans for future work and conclusions about applying this framework to the two use cases.
KW - Agricultural Risk Coverage (ARC) program
KW - Cover crop management
KW - Crop commodity programs analysis
KW - Crop modeling
KW - Decision Support System for Agrotechnology Transfer (DSSAT)
KW - Farm bill
KW - Farm practices analysis
KW - Farm programs analysis
KW - Gulf of Mexico hypoxia zone
KW - Nitrate nitrogen
KW - Nitrogen leaching
KW - Nutrient runoff
KW - Price Loss Coverage (PLC) program
KW - Web framework
KW - Web-based decision support system
KW - Workflow management system
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UR - http://www.scopus.com/inward/citedby.url?scp=85071002133&partnerID=8YFLogxK
U2 - 10.1145/3332186.3337063
DO - 10.1145/3332186.3337063
M3 - Conference contribution
AN - SCOPUS:85071002133
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the Practice and Experience in Advanced Research Computing
PB - Association for Computing Machinery
T2 - 2019 Conference on Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019
Y2 - 28 July 2019 through 1 August 2019
ER -