AbstractThe onset of a large number of a plant organ infections is linked to air temperature and humidity; according to laboratory studies, the threshold value of leaf-wetness duration is also important for many airborne fungi diseases.Various kinds of electronic equipment can estimate this parameter, which is used in agrometeorological pest control models. With a good degree of approximation, they can forecast the probability of airborne scab on apple trees and are based on precipitation, air temperature and leaf-wetness duration data, obtained at least at two-hour intervals. These models, in use at the Emilia-Romagna Regional Meteorological Service, are based on data from a network of automatic weather stations located in apple-growing areas.Since there are less stations than apple-growing areas, and because of the high cost of automatic stations, a numerical model was developed for deriving lehf wetness duration for use when such data are missing or when there is no electronic sensor.The model is based on stepwise regression analysis applied to 4 years’data collected by two automatic stations belonging to the network. The stepwise regression analysis, utilizing the BMDP statistical package, selects temperature, humidity and precipitation values, which are sufficient to explain more than 75% of the wetness duration variability.The estimated data are used to estimate the probability and the intensity of infection. These estimated probabilities are compared with the values derived from the application of models based on data from the electronic sensors. We find that the results agree.The estimate of airborne infection is based on precipitation and temperature data, while the degree of infection is based on humidity and temperature data. These two variables have a spatial variation law which is more easily computed than those of precipitation or wetness duration. The numerical model can be used to estimate infection in areas not equipped with electronic stations; some results are presented.