Space-time prediction of wine productivity for multi-actor usability: integration of remote optical-photonic sensors, artificial intelligence and climate scenarios
Wine4Cast aims to integrate remote optical-photonic sensors, artificial intelligence, and climate scenario modelling to develop a spatio-temporal productivity forecasting system for the wine sector. By combining ultra-early bud fertility analysis, digital phenotyping, and regional yield projections, the project enables precise vineyard management, optimises resource use (e.g., water and fertilisers), and supports sustainable practices. This innovative approach strengthens the resilience of viticulture against climate variability, enhances economic stability, and fosters decision-making at both local and regional scales.
Wine4Cast Goals
Operationalisation of instrumentation
Ultra-early forecasting
In-cycle forecasting
Regional forecasting and projection
Certification, capacity-building, and implementation
