Application of satellite-derived vegetation indices for frost damage detection in grapevines

Volatile organic compounds (VOCs) are very important for the characterisation and quality of the final white wine. An oenological practice to increase the extraction of aroma compounds is the cold pre-fermentative maceration [1,2], although it may also release phenolic compounds that confer darker chromatic traits to white wines, not appreciated by consumers. This practice could be improved by the use of enzymes in order to facilitate the release of the odorous molecules. In this study, the effect of different enzyme treatments during skin contact on the chromatic characteristics and volatile composition of white musts from four winegrape varieties was evaluated.

Grapevine (Vitis vinifera L.) is a globally cultivated crop and economically significant, particularly in the wine industry (Varela et al., 2024). Climate change is already affecting vineyards and is expected to worsen (Averbeck et al., 2019; Dupuis and Knoepfel, 2011).

Varietal thiols are considered for years as key aroma compounds in many wines. Their main origin is the cleavage during alcoholic fermentation of S-conjugate precursors present in grapes and musts, even if the levels of precursors already identified struggle to completely explain the levels of thiols found in wine.

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well altered grape ripening and composition at ripeness. This study aims to (i) detect weather anomalies within a long-term time series, (ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and (iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009-2021 in North-Eastern Italy. Non-linear models for the DOY to reach the specified ripeness thresholds were assessed for model efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. Long-term meteorological series monitored at ground weather station by means of hourly air temperature and rainfall data were analyzed. Climate statistics were obtained and for each time period (month, bimester, quarter and year) weather anomalies were identified. A linear regression analysis was performed to assess a possible correlation that may exist between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time period in the vintage. Precipitation of the warmest month and spring quarter are key to understanding the effect of climate change on sugar ripeness. Minimum temperatures of May-June bimester and maximum temperatures of spring quarter best correlate with altered total acidity evolution and pH increment during the ripening process, respectively.

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