Predicting Infection Risk of Hop by Pseudoperonspora humuli

Downy mildew, caused by Pseudoperonospora humuli, is one of the most destructive diseases of hop. Weather factors associated with infection risk by P. humuli in the maritime region of western Oregon were examined for 24- and 48-h periods and quadratic discriminant function models were developed to classify periods as favorable for disease development on leaves. For the 24-h data sets, the model with superior predictive ability included variables for hours of relative humidity >80%, degree-hours of wetness, and mean night temperature. The same variables were selected for the 48-h data sets, with the addition of a product variable for mean night temperature and hours of relative humidity >80%. Cut-points (p(T)) on receiver operating characteristic curves that minimized the overall error rate were identified by selecting the cut-point with the highest value of Youden's index. For the 24- and 48-h models these were p(T) = 0.49 and 0.39, respectively. With these thresholds, the sensitivity and specificity of the models in cross validation by jackknife exclusion were 83.3 and 88.8% for the 24-h model and 87.5 and 84.4% for the 48-h model, respectively. Cut-points that minimized the average costs associated with disease control and crop loss due to classification errors were determined using estimates of economic damage during vegetative development and on cones near harvest. Use of the 24- and 48-h models was estimated to reduce average management costs during vegetative development when disease prevalence was