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Impact of Management Practices on Prevalence of Soybean Sclerotinia Stem Rot in the North-Central United States and on Farmers' Decisions Under Uncertainty

September 2003 , Volume 87 , Number  9
Pages  1,048 - 1,058

A. L. Mila , Department of Plant Pathology ; A. L. Carriquiry , Department of Statistics , J. Zhao , Department of Economics , and X. B. Yang , Department of Plant Pathology, Iowa State University, Ames 50011



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Accepted for publication 3 April 2003.
ABSTRACT

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. Logistic regression analysis was used to estimate the probability of stem rot prevalence with disease data from 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 observed frequency of occurrence. The relationship of management practices and weather variables with soybean yield was examined using multiple linear regression (R 2 = 0.27). Variables significant to SSR prevalence, including average air temperature during July and August, precipitation during July, tillage, seed treatment, liquid manure, fertilizer, and herbicide applications, were also 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. Farmers' decisions about SSR management, when the effect of management practices on disease prevalence and expected attainable yield was taken into account, were examined. Bayesian decision procedures were used to combine information from our model (prediction) with farmers' subjective estimation of SSR incidence (personal estimate, based on farmers' previous experience with SSR incidence). MAXIMIN and MAXIMAX criteria were used to incorporate farmers' 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.


Additional keywords: Bayesian behavior, white mold

© 2003 The American Phytopathological Society