As part of the project’s research activities, and specifically within Use Case 3.1: Disease Forecasting and Detection, a field demonstration was conducted in Messinia, Greece, at the AgriDataValue pilot site.

The field demonstration, organized by the NILEAS Producers Group in a traditional olive grove, showcased how advanced digital technologies can enhance the early detection and management of olive anthracnose (Colletotrichum gloeosporioides). The event demonstrated the value of real-time monitoring and predictive analytics in providing growers with timely warnings, enabling them to optimize the timing of crop protection measures and improve disease management practices.

Use Case 3.1 leverages SynField smart agriculture systems to collect and analyze real-time data for monitoring disease epidemiology and supporting early disease detection. Through the AgriDataValue framework, predictive models are developed to forecast and identify diseases affecting fruit trees. By integrating IoT-based weather, soil, and leaf wetness sensors, the system continuously monitors key environmental parameters, including microclimatic conditions and canopy moisture, and generates automated disease risk indices to support farmers’ decision-making.