A model predicting primary infections of Plasmopara viticola in different grapevine-growing areas of Italy

Tito Caffi, Vittorio Rossi, R. Bugiani, F. Spanna, L. Flamini, A. Cossu, C. Nigro

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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; 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 in early season or when the oosporic 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). Considering that: i) the data used for evaluation were not used in model development, ii) the grape-growing areas considered represent the different climatic zones of grape cultivation in Italy, iii) both early and late primary infections were observed in the vineyards, iv) both first seasonal and further infections were observed in the potted plants, v) neither calibration nor empirical adjustment of model parameters were necessary, the model can be considered an accurate and robust predictor of P. viticola oosporic infections.
Original languageEnglish
Pages (from-to)535-548
Number of pages14
JournalJournal of Plant Pathology
Publication statusPublished - 2009


  • downy mildew
  • dynamic modelling
  • grapevine
  • primary infections


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