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Modelling the Dynamics of Weed Management Technologies


  • Jones, Randall E.
  • Cacho, Oscar J.
  • Sinden, Jack A.


An appropriate economic framework for valuing the benefits of weed management technologies is to treat weeds as a renewable resource stock problem. Consequently, the weed seed bank is defined as a renewable resource that changes through time due to management and seasonal conditions. The goal of decision-makers is to manage this (negative) resource so as to maximise returns over some pre-specified period of time. A modelling framework is presented for evaluating the biological and economic effects of weed management. The framework includes population dynamics, water balance, crop growth, pasture growth and crop/pasture rotation models for measuring the physical interactions between weeds and the environment. These models link in with numerical optimal control, dynamic programming and stochastic dynamic programming models for determination of optimal decision rules and measuring economic impact over time of policy scenarios.

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  • 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.
  • Handle: RePEc:ags:aare03:57902
    DOI: 10.22004/ag.econ.57902

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    References listed on IDEAS

    1. 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.
    2. Gorddard, Russell J. & Pannell, David J. & Hertzler, Greg, 1996. "Economic evaluation of strategies for management of herbicide resistance," Agricultural Systems, Elsevier, vol. 51(3), pages 281-298, July.
    3. Russell J. Gorddard & David J. Pannell & Greg Hertzler, 1995. "An Optimal Control Model For Integrated Weed Management Under Herbicide Resistance," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(1), pages 71-87, April.
    4. Pandey, Sushil & Medd, R. W., 1991. "A stochastic dynamic programming framework for weed control decision making: an application to Avena fatua L," Agricultural Economics, Blackwell, vol. 6(2), pages 115-128, December.
    5. Pandey, Sushil & Medd, R. W., 1990. "Integration of seed and plant kill tactics for control of wild oats: An economic evaluation," Agricultural Systems, Elsevier, vol. 34(1), pages 65-76.
    6. C. Robert Taylor & Oscar R. Burt, 1984. "Near-Optimal Management Strategies for Controlling Wild Oats in Spring Wheat," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(1), pages 50-60.
    7. S. Pandey & R. K. Lindner & R. W. Medd, 1993. "Towards An Economic Framework For Evaluating Potential Benefits From Research Into Weed Control," Journal of Agricultural Economics, Wiley Blackwell, vol. 44(2), pages 322-334, May.
    8. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
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