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The Value of Plant Disease Early-Warning Systems: A Case Study of USDA's Soybean Rust Coordinated Framework

Author

Listed:
  • Roberts, Michael J.
  • Schimmelpfennig, David E.
  • Ashley, Elizabeth
  • Livingston, Michael J.
  • Ash, Mark S.
  • Vasavada, Utpal

Abstract

Early-warning systems for plant diseases are valuable when the systems provide timely forecasts that farmers can use to inform their pest management decisions. To evaluate the value of the systems, this study examines, as a case study, USDA’s coordinated framework for soybean rust surveillance, reporting, prediction, and management, which was developed before the 2005 growing season. The framework’s linchpin is a website that provides real-time, county-level information on the spread of the disease. The study assesses the value of the information tool to farmers and factors that influence that value. The information’s value depends most heavily on farmers’ perceptions of the forecast’s accuracy. The study finds that the framework’s information is valuable to farmers even in a year with a low rust infection like that of 2005. We estimate that the information provided by the framework increased U.S. soybean producers’ profits by a total of $11-$299 million in 2005, or between 16 cents and $4.12 per acre, depending on the quality of information and other factors. The reported cost of the framework was between $2.6 million and almost $5 million in 2005.

Suggested Citation

  • Roberts, Michael J. & Schimmelpfennig, David E. & Ashley, Elizabeth & Livingston, Michael J. & Ash, Mark S. & Vasavada, Utpal, 2006. "The Value of Plant Disease Early-Warning Systems: A Case Study of USDA's Soybean Rust Coordinated Framework," Economic Research Report 7208, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uersrr:7208
    DOI: 10.22004/ag.econ.7208
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    Citations

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    Cited by:

    1. Michael J. Roberts & David Schimmelpfennig & Michael J. Livingston & Elizabeth Ashley, 2009. "Estimating the Value of an Early-Warning System," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(2), pages 303-329.
    2. Ranjan, Ram, 2007. "Technology Adoption Against Invasive Species," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 39(Special), pages 1-14, October.
    3. Gomez, Miguel I. & Nunez, Hector M. & Onal, Hayri, 2009. "Economic Impacts of Soybean Rust on the US Soybean Sector," Working Papers 51177, Cornell University, Department of Applied Economics and Management.
    4. Joseph Walls & Edwin Rajotte & Cristina Rosa, 2019. "The Past, Present, and Future of Barley Yellow Dwarf Management," Agriculture, MDPI, vol. 9(1), pages 1-16, January.
    5. Bekkerman, Anton & Goodwin, Barry K. & Piggott, Nicholas E., 2008. "Spatio-temporal Risk and Severity Analysis of Soybean Rust in the United States," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(3), pages 1-21.
    6. Lee, Donna J. & Kim, C.S. & Schaible, Glenn D., 2006. "Estimating the Cost of Invasive Species on U.S. Agriculture: The U.S. Soybean Market," 2006 Annual meeting, July 23-26, Long Beach, CA 21113, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Thakur, Tiesta & Homans, Frances R. & Haight, Robert G. & Hurley, Terrance M., 2018. "Valuing Monitoring Networks for New Pathogens: The Case of Soybean Rust," 2018 Annual Meeting, August 5-7, Washington, D.C. 273870, Agricultural and Applied Economics Association.
    8. Malcolm, Scott A. & Marshall, Elizabeth P. & Aillery, Marcel P. & Heisey, Paul W. & Livingston, Michael J. & Day-Rubenstein, Kelly A., 2012. "Agricultural Adaptation to a Changing Climate: Economic and Environmental Implications Vary by U.S. Region," Economic Research Report 127734, United States Department of Agriculture, Economic Research Service.
    9. Kiker, Greg & Ranjan, Ram, 2006. "Decision Support System for Soybean Rust (Phakopsora pachyrhizi) Management using QnD," 2006 Annual meeting, July 23-26, Long Beach, CA 21248, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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