Extensible framework for analysis of farm practices and programs

Sandeep Puthanveetil Satheesan, Rabin Bhattarai, Shannon Bradley, Jonathan Coppess, Lisa Gatzke, Rishabh Gupta, Hanseok Jeong, Jong S. Lee, Gowtham Naraharisetty, Michal Ondrejcek, Gary Donald Schnitkey, Yan Zhao, Christopher M. Navarro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the Practice and Experience in Advanced Research Computing
Subtitle of host publicationRise of the Machines (Learning), PEARC 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450372275
DOIs
StatePublished - Jul 28 2019
Event2019 Conference on Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019 - Chicago, United States
Duration: Jul 28 2019Aug 1 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2019 Conference on Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019
CountryUnited States
CityChicago
Period7/28/198/1/19

Keywords

  • Agricultural Risk Coverage (ARC) program
  • Cover crop management
  • Crop commodity programs analysis
  • Crop modeling
  • Decision Support System for Agrotechnology Transfer (DSSAT)
  • Farm bill
  • Farm practices analysis
  • Farm programs analysis
  • Gulf of Mexico hypoxia zone
  • Nitrate nitrogen
  • Nitrogen leaching
  • Nutrient runoff
  • Price Loss Coverage (PLC) program
  • Web framework
  • Web-based decision support system
  • Workflow management system

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Satheesan, S. P., Bhattarai, R., Bradley, S., Coppess, J., Gatzke, L., Gupta, R., Jeong, H., Lee, J. S., Naraharisetty, G., Ondrejcek, M., Schnitkey, G. D., Zhao, Y., & Navarro, C. M. (2019). Extensible framework for analysis of farm practices and programs. In Proceedings of the Practice and Experience in Advanced Research Computing: Rise of the Machines (Learning), PEARC 2019 [3337063] (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3332186.3337063