Simulating climate change impact on viticultural systems in historical and emergent vineyards

Right after the pouring of champagne in a glass, thousands of rising and bursting bubbles convey gas-phase CO2 and volatile organic compounds in the headspace above the champagne surface, thus progressively modifying the gaseous chemical space perceived by the consumer [1]

Aim: Through machine-learning modelling of plant water status from environmental characteristics, this work aims to develop a model able to predict grape phenolic composition in space and time to guide selective harvest decisions at the estate scale.

Schiava cv. (germ. Vernatsch) is a group of grape varieties used for winemaking (e.g. Kleinvernatsch-Schiava gentile, Grauvernatsch-Schiava grigia, Edelvernatsch-Schiava grossa) historically reported in Northern Italy, Austria, Germany and Croatia. Beside common phenotypic traits, these varieties have been also hypothesized to share a common geographical origin in Slavonia (Eastern Croatia). Nowadays, Schiava cv. are considered historical grape varieties of northern regions of Italy such as Lombardy, Trentino and South Tyrol. Traditionally widely consumed locally and also exported, over the past decades there has been a steady drop in production of these grapes, although with a parallel increase in wine quality. In this report, the effects of three main enological variables on the chemical components of Schiava produced in South Tyrol (var. Schiava grossa) are investigated from grape to bottle.

The C-glycosidic ellagitannins constitute a subclass of hydrolyzable tannins of remarkable structural diversity. In this work we first achieved the hemisynthesis of flavano-ellagitannins, then we used them to develop a new efficient detection and quantification procedure for the C-glycosidic ellagitannins as well as flavano-ellagitannins.

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.