Optimizing weed management using stochastic dynamic-programming to take account of uncertain herbicide performance

A stochastic dynamic programme determines the farmer’s long-term weed control strategy incorporating decisions of crop, autumn cultivation, timing of planting and herbicide treatments. A previous paper describes the one-step transition probabilities due to variable weed control from year to year. This paper describes the costing of the decision options and shows the results from the model for the optimal control of one difficult grass weed in cereals. The model is shown to give reasonable results and shows that the control strategy which optimizes costs is to use half-rate herbicide over a wide range of seedbanks. A simulation of the optimum strategy over 10 years shows that the total overall use of herbicide is also reduced.