Data-driven viticulture is not about collecting more data, but better data. Monitoring vines means observing, measuring, and understanding what happens in the vineyard to support informed, timely, and sustainable agronomic decisions. Large quantities of data are useless if not accurate and representative. Efficient data collection must optimize the agronomist’s work and avoid loss of information, which requires effective digital tools.
To achieve this, Perleuve Srl developed 4Grapes, a simple, intuitive, fast, and precise app for vineyard monitoring. It allows recording phenological stages, grape health, yield estimates, vigor, and canopy characteristics directly in the field. Data are instantly synchronized to the cloud and shared in real time, enabling collaborative decisions and avoiding data loss.
Today, vineyard monitoring integrates multiple sources: soil and temperature sensors, weather stations, predictive models, satellite and drone imagery, and physiological sensors for vine stress. All these streams converge into a single decision-support system. However, technology must be complemented by field fine-tuning: direct observation remains essential to calibrate and verify sensor data.
Key agronomic parameters — yield per vine, exposed leaf area (ELA), ELA/yield ratio, grape health, cluster morphology, water stress, vigor, biodiversity, and vineyard age — directly influence grape and wine quality. Their integration defines the Bigot Index, correlating vineyard conditions with potential wine quality.
After over twenty years of fieldwork, we have created the Perleuve method, which merges technology and agronomy, data and sensitivity, prediction and verification. Its goal is to reach the desired oenological target, scientifically described through the Bigot Index.
