Wireless meteorological sensors in the Sulcis territory to run predictive models of vine diseases

In the last forty years, several plant disease models have been developed for the main fungal and oomycete diseases of grapevine. The current study aims to structure a platform for wireless collection of meteorological data to feed the joint use of predictive models. To this purpose, the territory of Sulcis, in South-West Sardinia, has been selected, where 14 agrometeorological stations have been operational since 2018 in locations exposed to various weather conditions, inhomogeneous altitudes and different soil textures. Based on literature search, models with different characteristics, available for four grape diseases (downy and powdery mildews, grey mould, and black rot) have been selected and translated in R to be connected to the meteorological data source. Models’ evaluation has been performed highlighting differences and similarities in data input and output. In perspective, model output consistency will be evaluated with data collected by Cantina Santadi, a relevant grape producer in the territory to define model performances and suitability to support farmers and technicians in crop protection decision making.