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A Dynamic Programming Approach to the Economic Control of Weed and Disease Infestations in Wheat

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  • Fisher, Brian S.
  • Lee, R.R.

Abstract

Weeds and fungal diseases cause significant losses to grain crops in Australia. In many cases cultural methods of control are effective. However, it is often difficult for farm decision-makers to select the optimum crop rotation, from an economic point of view, given the technical constraints they face. A decision to plant a particular crop will have implications for both current and future profitability because the current decision will alter the constraints faced by the decision-maker in subsequent periods. Dynamic programming is used to solve the rotation problem faced by grain growers in north-western New South Wales in areas where the weed, wild oats (A vena falua or A vena ludoviciana), and the disease, crown rot (Fusarium graminearum Group I), have a significant effect on wheat yields. The solutions to the dynamic programming problem suggest that in many circumstances a stable rotational pattern is appropriate. In the present case the model is solved for a set of conditions which is relevant to only a small part of the wheat-belt of New South Wales. However, the method can be applied to aid decision-making in individual cases where the user may wish to change the underlying agronomic assumptions of the model.

Suggested Citation

  • Fisher, Brian S. & Lee, R.R., 1981. "A Dynamic Programming Approach to the Economic Control of Weed and Disease Infestations in Wheat," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 49(03), pages 1-13, December.
    • Handle: RePEc:ags:remaae:12237
    DOI: 10.22004/ag.econ.12237
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    References listed on IDEAS

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    1. Dillon, John L., 1966. "Economic Considerations in the Design and Analysis of Agricultural Experiments," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 34(02), pages 1-12, June.
    2. Oscar R. Burt & John R. Allison, 1963. "Farm Management Decisions With Dynamic Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 45(1), pages 121-136.
    3. Oscar R. Burt & Ralph D. Johnson, 1967. "Strategies for Wheat Production in the Great Plains," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 49(4), pages 881-899.
    4. Anderson, Jock R., 1971. "Guidelines for Applied Agricultural Research: Designing, Reporting and Interpreting Experiments," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(03), pages 1-12, September.
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    Cited by:

    1. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
    2. Harper, David C. & Lambert, Dayton M. & Larson, James A. & Gwathmey, C. Owen, 2012. "Potassium carryover dynamics and optimal application policies in cotton production," Agricultural Systems, Elsevier, vol. 106(1), pages 84-93.
    3. Wallinga, Jacco, 1998. "Analysis of the rational long-term herbicide use: Evidence for herbicide efficacy and critical weed kill rate as key factors," Agricultural Systems, Elsevier, vol. 56(3), pages 323-340, March.
    4. Finnoff, David & Tschirhart, John, 2005. "Identifying, preventing and controlling invasive plant species using their physiological traits," Ecological Economics, Elsevier, vol. 52(3), pages 397-416, February.
    5. Sells, J. E., 1995. "Optimising weed management using stochastic dynamic programming to take account of uncertain herbicide performance," Agricultural Systems, Elsevier, vol. 48(3), pages 271-296.

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