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A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L

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  • Sushil Pandey
  • R.W. Medd

Abstract

This paper develops a stochastic multi‐period decision model to analyse a continuous wheat cropping system infested by wild oats (Avena fatua L.), in southern Australia. The multi‐period solutions is obtained by employing a dynamic programming model in conjunction with a bioeconomic simulation model. An empirically estimated dose response function is used to derive the optimal herbicide rate. Uncertainties due to environmental effects on the performance of herbicide and crop yields are modelled and optimal decision rules derived. The results indicate that substantial economic gains can be realised if herbicide dose decisions are taken by considering future profit effects of current decisions, as opposed to the more common approach of only considering the current‐period effect.

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  • Sushil Pandey & R.W. Medd, 1991. "A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L," Agricultural Economics, International Association of Agricultural Economists, vol. 6(2), pages 115-128, December.
    • Handle: RePEc:bla:agecon:v:6:y:1991:i:2:p:115-128
    DOI: 10.1111/j.1574-0862.1991.tb00175.x
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    Cited by:

    1. 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.
    2. Jones, Randall E. & Cacho, Oscar J. & Sinden, Jack A., 2003. "Modelling the Dynamics of Weed Management Technologies," 2003 Conference (47th), February 12-14, 2003, Fremantle, Australia 57902, Australian Agricultural and Resource Economics Society.
    3. Gallagher, Nicholas James, 2024. "Dynamic Programming Methods for Characterizing In-Season Farm Management Decisions," Dissertations and Theses 344827, Ekiti State University, Ado-Ekiti, Department of Agricultural Economics and Extension Services.
    4. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
    5. Jones, Randall E., 2005. "Sustainability and integrated weed management in Australian winter cropping systems: a bioeconomic analysis," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137930, Australian Agricultural and Resource Economics Society.
    6. Rohan Jayasuriya & Randall Jones & Remy Ven, 2011. "A bioeconomic model for determining the optimal response strategies for a new weed incursion," Journal of Bioeconomics, Springer, vol. 13(1), pages 45-72, April.
    7. Robert, Marion & Thomas, Alban & Bergez, Jacques Eric, 2016. "Processes of adpatation in farm decision-making models. A review," TSE Working Papers 16-731, Toulouse School of Economics (TSE).
    8. Jayasuriya, Rohan T. & Jones, Randall E., 2008. "A bioeconomic model for determining the optimal response to a new weed incursion in Australian cropping systems," 2008 Conference (52nd), February 5-8, 2008, Canberra, Australia 6015, Australian Agricultural and Resource Economics Society.
    9. Pandey, Sushil & Hardaker, J. Brian, 1995. "The role of modelling in the quest for sustainable farming systems," Agricultural Systems, Elsevier, vol. 47(4), pages 439-450.
    10. Woongchan Jeon & Kwansoo Kim, 2017. "Optimal Weed Control Strategies in Rice Production under Dynamic and Static Decision Rules in South Korea," Sustainability, MDPI, vol. 9(6), pages 1-11, June.
    11. 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.
    12. Chalak-Haghighi, Morteza & Ruijs, Arjan & van Ierland, Ekko C., 2009. "Biological control of invasive plant species: stochastic economic analysis," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 48153, Australian Agricultural and Resource Economics Society.
    13. repec:ags:aare05:137931 is not listed on IDEAS

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