This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

L’entreprise viticole Concha y Toro S.A. gère environ 600 ha de vignes dans la Vallée du Maipo (A.O. Valle del Maipo). L’objectif est celui de caractériser spatialement ces vignobles et leur occupation du sol environnante. Le choix s’est porté vers la démarche de zonage viticole par l’analyse spatiale, utilisant des traitements d’images satellitaires afin d’avoir une vision synoptique de la zone à moindres coûts et délais. Un système d’informations géographiques (SIG) est construit à partir des données suivantes : cartes topographiques, géologique, fond cadastral numérique, images satellitaires. Un modèle numérique de terrain est par ailleurs construit à une résolution de 25 m à partir des cartes topographiques.

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

Stilbenes are natural bioactive polyphenols produced by grapevine. Recently, we have reviewed the na- tural presence of these compounds in wines [1]. This study showed that the resveratrol and its glycoside, the piceid, are the most abundant stilbenes in wines. Resveratrol is a well-known stilbene with a wide range of biological activities. Due to its specific structure, resveratrol can be oxidized in wines to form various derivatives including oligomers [2]. In this study, we investigate the resveratrol and piceid transformation in wines.

Some wood substances such as ellagitannins (vescalagin, castalagin, grandinin, roburins (A, B, C, D, E)…) can be extracted during wine ageing in oak barrels. The level of these hydrolysable tannins in wine depends of the species and origin of oak wood as well as its treatment during barrel realization.