An Optimal Control Model For Integrated Weed Management Under Herbicide Resistance
AbstractThe presence of weeds which have developed resistance to chemical herbicides is a problem of rapidly growing importance in Australian agriculture. We present an optimal control model of herbicide resistance development in ryegrass, the weed for which resistance is most commonly reported. The model is used to select the optimal combination of chemical and non-chemical control measures taking account of the trade off between short term profits and the long term level of herbicide resistance. Results indicate that given the threat of resistance there are benefits from integrating a combination of chemical and non-chemical control measures. The optimal strategy is found to include a declining herbicide dosage as resistance develops, with compensatory increases in the level of non-chemical control.
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Bibliographic InfoArticle provided by Australian Agricultural and Resource Economics Society in its journal Australian Journal of Agricultural Economics.
Volume (Year): 39 (1995)
Issue (Month): 01 (April)
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Other versions of this item:
- 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, 04.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- repec:ags:aare05:137931 is not listed on IDEAS
- 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.
- Mitchell, Paul D., 2011. "Economic Assessment of the Benefits of Chloro-s-triazine Herbicides to U.S. Corn, Sorghum, and Sugarcane Producers," Staff Paper Series 564, University of Wisconsin, Agricultural and Applied Economics.
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