Abstract
Multi-season management of Verticillium wilt, a serious soil borne fungal pathogen in California cotton, is assessed using dynamic programming. The model assumes that maximization of long run present value of profits may be achieved by choosing among a finite set of pre-season pathogen control actions. The time evolution of pathogen density and virulence is the basis in the dynamic model for selecting among treatment alternatives. The treatments differently affect immediate as well as long run profits via their effects on future density and virulence of the pathogen. The model considers both deterministic and stochastic economic environments. The deterministic short run model suggests that no actions are required, while long term policy suggests the use of crop rotation rather than chemical treatments. The effects of uncertainty are examined via the use of hypothetical uncertainty parameters.
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