A decision algorithm for patch spraying

It has been established that weeds are spatially aggregated with a spatially varying composition of weed species within agricultural fields. Site-specific spraying therefore requires a decision method that includes the spatial variation of the weed composition and density. A computerized decision method that estimates an economic optimal herbicide dose according to site-specific weed composition and density is presented in this paper. The method was termed a 'decision algorithm for patch spraying' (DAPS) and was evaluated in a 5-year experiment, in Denmark. DAPS consists of a competition model, a herbicide dose-response model and an algorithm that estimates the economically optimal doses. The experiment was designed to compare herbicide treatments with DAPS recommendations and the Danish decision support system PC-Plant Protection. The results did not show any significant grain yield difference between DAPS and PC-Plant Protection; however, the recommended herbicide doses were significantly lower when using DAPS than PC-Plant Protection in all years. The main difference between the two decision models is that DAPS integrates crop-weed competition and estimates the net return as a continuous function of herbicide dose. The hypothesis tested is that the benefit of using lower herbicide doses recommended by DAPS would disappear after a few years because weed density will increase and thus require higher doses. However, the results of weed counting every year did not confirm this hypothesis.