Consideration of latent infections improves the prediction of Botrytis bunch rot severity in vineyards

The current study validated a mechanistic model for Botrytis cinerea on grapevine with data from 23 independent Botrytis bunch rot (BBR) epidemics (combinations of vineyards x year) that occurred between 1997 and 2018 in Italy, France, and Spain. The model was operated for each vineyard by using weather data and vine growth stages to anticipate, at any day of the vine-growing season, the disease severity (DS) at harvest (severe, DS >/= 15%; intermediate, 5 87%. This result showed that the model correctly accounts for latent infections, which is important because latent infections can substantially increase DS. The model was sensitive and specific, with the false-positive and false-negative proportion of model predictions equal to 0.24 and 0, respectively. Therefore, the model may be considered a reliable tool for decision-making for BBR control in vineyards.