Regional prevalence of soybean Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum,was modeled using management practices (tillage, herbicide, manure and fertilizer application,and seed treatment with fungicide) and summer weather variables (mean monthly air temperature and precipitation for the months of June, July, August, and September) as inputs. Logisticregression analysis was used to estimate the probability of stem rot prevalence with disease datafrom four states in the north-central region of the United States (Illinois, Iowa, Minnesota, and Ohio). Goodness-of-fit criteria indicated that the resulting model explained well the observedfrequency of occurrence. The relationship of management practices and weather variables withsoybean yield was examined using multiple linear regression (R2 = 0.27). Variables significant to SSR prevalence, including average air temperature during July and August, precipitationduring July, tillage, seed treatment, liquid manure, fertilizer, and herbicide applications, werealso associated with high attainable yield. The results suggested that SSR occurrence in the north-central region of the United States was associated with environments of high potential yield. Farmersï¾’ decisions about SSR management, when the effect of management practices ondisease prevalence and expected attainable yield was taken into account, were examined.Bayesian decision procedures were used to combine information from our model (prediction)with farmersï¾’ subjective estimation of SSR incidence (personal estimate, based on farmersï¾’previous experience with SSR incidence). MAXIMIN and MAXIMAX criteria were used to incorporate farmersï¾’ site-specific past experience with SSR incidence, and optimum actions were derived using the criterion of profit maximization. Our results suggest that management practices should be applied to increase attainable yield despite their association with high disease risk.
