A MODEL PREDICTING PRIMARY INFECTIONS OF PLASMOPARA VITICOLA IN DIFFERENT GRAPEVINEGROWING AREAS OF ITALY
T. Caffi, V. Rossi, R. Bugiani, F. Spanna, L. Flamini, A. Cossu, C. Nigro
A dynamic model for Plasmopara viticola primary infections was evaluated by comparing model predictions with disease onset in: (i) 100 vineyards of northern, southern and insular Italy (1995 to 2007); (ii) 42 groups of potted grapevine plants exposed to inoculum (2006 to 2008). The model simulates the development of any oospore cohort during the primary inoculum season, including oospore germination, production and survival of sporangia, release, survival and dispersal of zoospores, and infection and incubation. The model showed high sensitivity, specificity, and accuracy both in vineyards and in potted plants. The true positive and negative proportions were TPP=0.99 and TNP=0.87, respectively. Because of a certain proportion of false positive predictions (FPP=0.13), confidence in prediction of non-infections was higher than in prediction of infections. These wrong predictions occurred early in the season or when oospore inoculum was low, or were triggered by isolated weak rain events. In only one case (a group of potted plants) there was infection when infection was not predicted (FNP=0.005). The model can be considered an accurate and robust predictor of P. viticola oospore infections and could be used to reduce or improve the timing of fungicide sprays.