Wine4Cast
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
