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Integrated Pest Management Strategies for Approximately Optimal Control of Corn Rootworm and Soybean Cyst Nematode

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  • Thomas P. Zacharias
  • Arthur H. Grube

Abstract

A dynamic programming model is used to determine approximately optimal management strategies for control of corn rootworm and soybean cyst nematode in Illinois. Decision alternatives for rootworm control include nontreatment, application of a soil insecticide, and rotation to soybeans. Alternatives for cyst nematode control are nontreatment, soil nematicide, resistant cultivars, and rotation to corn. State variables in the dynamic programming model are infestation levels of both pests, previous land use decisions, and expected product prices.

Suggested Citation

  • Thomas P. Zacharias & Arthur H. Grube, 1986. "Integrated Pest Management Strategies for Approximately Optimal Control of Corn Rootworm and Soybean Cyst Nematode," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(3), pages 704-715.
    • Handle: RePEc:oup:ajagec:v:68:y:1986:i:3:p:704-715.
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    File URL: http://hdl.handle.net/10.2307/1241554
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    Citations

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    Cited by:

    1. Lichtenberg, Erik & Zilberman, David & Archibald, Sandra O., 1990. "Economics and Pesticides," Working Papers 197750, University of Maryland, Department of Agricultural and Resource Economics.
    2. Regmi, Anita, 1990. "The value of information in integrated pest management of corn rootworm and European corn borer in Minnesota," Faculty and Alumni Dissertations 307267, University of Minnesota, Department of Applied Economics.
    3. Zhang, Wei & Swinton, Scott M., 2009. "Incorporating natural enemies in an economic threshold for dynamically optimal pest management," Ecological Modelling, Elsevier, vol. 220(9), pages 1315-1324.
    4. Hoque, Ziaul & Farquharson, Robert J. & Dillon, Martin & Kauter, Greg, 2000. "An economic assessment of Insecticide Resistance Management strategies in the Australian Cotton Industry," 2000 Conference (44th), January 23-25, 2000, Sydney, Australia 123662, Australian Agricultural and Resource Economics Society.
    5. Young, Douglas L. & Van Kooten, G.C., 1988. "Incorporating Risk Into A Dynamic Programming Application: Flexcropping," Regional Research Projects > 1988: S-180 Annual Meeting, March 20-23, 1988, Savannah, Georgia 272781, Regional Research Projects > S-180: An Economic Analysis of Risk Management Strategies for Agricultural Production Firms.
    6. Blackwell, Melanie & Pagoulatos, Angelos, 1990. "Measuring the Specification Bias of the Cobb Douglas Functional Form for Alfalfa Production," Agricultural Economics Research Reports 140070, University of Kentucky, Department of Agricultural Economics.
    7. Fuller, Kate Binzen & Sanchirico, James N. & Alston, Julian M., 2017. "The Spatial-Dynamic Benefits from Cooperative Disease Control in a Perennial Crop," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(2), May.

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