A.O.C. taureau de Camargue

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.

In Spain, the wide diversity of red grapevine varieties represents an advantage when choosing the most suitable one for cultivation based on different climatic conditions, without implying a loss of their enological potential.

Aims: The aims of this study were (1) to measure the vertical temperature gradient in the vine canopy in parcels with different vineyard floor management practices and (2) to analyze the factors influencing this gradient. The objective was to investigate whether the increase of trunk height could be an adaptation strategy to reduce air temperature in the bunch zone in a context of climate change. 

The interest in understanding the water balance of terrestrial plants under drought has led to the creation of the isohydric/anisohydric terminology. The classification was related to an implication-driven framework, where isohydric plants maintain a constant and high leaf water potential through an early and intense closure of their stomata, hence risking carbon starvation. In contrast, anisohydric plants drop their leaf water potential to low values as soil drought is establishing due to insensitive stomata and thus risk mortality through hydraulic failure, albeit maximizing carbon intake. When applied to grapevines, this framework has been elusive, yielding discrepancies in the classification of different wine grape varieties around the world.

Geospatial technologies have significant contribution to viticulture, especially in small-scale vineyards, which require precise management. Geospatial data collected by modern technologies, such as Unmanned Aerial Vehicle (UAV) and satellite imagery, can be processed by modern software and easily be stored and transferred to GIS environments, highlighting important information about the health of vine plants, the yield of grapes and the wine, especially in wine-making varieties. The identification of field variability is very important, particularly for the production of high quality wine. Modern geospatial data management technologies are used to achieve an easy and effortless localization of the fields’ variability.