The grapevine (Vitis vinifera L.) is one of the most economically valuable horticultural crops worldwide and is cultivated across a wide range of agroclimatic regions. The objective of this study was to develop a predictive model to estimate the yield of the cultivar Treixadura as a function of meteorological, phenological, aerobiological, and phytopathological variables. The study was conducted in a vineyard located within the Ribeiro Designation of Origin (Spain) over 21 consecutive growing seasons. During the period from 2004 to 2023, grapevine yield exhibited pronounced interannual variability, with the lowest yield recorded in 2018 and the highest in 2023. Correlation analysis showed that grapevine yield was significantly and positively associated with temperature, airborne pollen and the Plasmopara viticola pathogen, and negatively with rainfall and the Botrytis pathogen. Yield was predicted using a model that included rainfall in the first ten days of April, airborne pollen concentration, and Plasmopara viticola from the third ten-days of April as explanatory variables. This model accounted for approximately 70% of the observed variability in yield. The achieved predictive performance enables the anticipation of harvest outcomes several months in advance, thereby supporting more effective viticultural planning. Furthermore, the results highlight the importance of disease control in vineyards, as pathogen incidence not only reduces yield directly but may also compromise the accuracy of yield prediction models.
Carrera et al. (Thu,) studied this question.