Abstract:

Grape phenolic assessment is fundamental to predict sensory attributes of wines, however, it is commonly destructive, time-consuming, and costly. This study aimed at developing a new method for in-field phenolic maturity estimation from high-resolution RGB images acquired by unmanned aerial vehicle (UAV) platform on Sangiovese cultivar. It was compared to the anthocyanin indices provided by the Multiplex proximal sensor and traditional destructive analysis on the very same bunches. The UAV approach demonstrated similar results to the consolidated Multiplex sensor, in detail the colour index of vegetation extraction (CIVE) reached R²=0.44 and RMSE=307.73 mg/kg in anthocyanin content estimation. This fast and objective UAV application can provide a promising solution for winemakers’ support in the critical choice of harvest scheduling.