Des enjeux individuels à l’action collective

Understanding grapevine responses to increasing atmospheric CO2 (aCO2) concentrations is crucial for assessing the impact of climate change on viticulture. Previously, at the VineyardFACE (Free Air Carbon dioxide Enrichment) experiment in Geisenheim, leaf gas exchange measurements were made as Vitis vinifera cv. Cabernet Sauvignon established from planting (2014 to 2016) under aCO2 or elevated CO2 (eCO2, aCO2 + 20%) concentrations. Contrary to many preceding observations with grapevines and other perennial plant species the young vines showed an increased intrinsic water use efficiency (WUEi) that was mainly associated with an increase in net assimilation (A) rather than a decrease in stomatal conductance (gs) under eCO2.

Diverse ripening disorders affect grapevine resulting in high economic losses worldwide. The common obvious symptom is shriveling berries, however the shriveling pattern and the consequences for berry quality traits are distinct in each disorder. Among them, the disorder berry shrivel is characterized by a reduced sugar accumulation short after the onset of berry ripening leaving the clusters unsuitable for wine processing. Although our knowledge on BS increased recently, potential internal or external triggers contributing to the induction of BS are yet to be explored.

The interaction between wine and landscapes is of an unsuspected richness. On the one side, the vineyards form part of the landscapes which they model. On the other side, the wines are related in their perception to the image of a region, a landscape and are at the origin of a cultural richness.

Depuis 2002, le CIVAM de la région Corse, a entrepris une étude des terroirs viticoles de l’appellation AOC Corse-Calvi (Balagne), comprenant la cartographie des terroirs à potentialité viticole

Estimation of vineyard leaf area index (LAI) is an important aspect for the winegrowers. However, tracking and monitoring are difficult tasks due to time constraints. Satellite and unmanned aerial vehicle (UAV) imaging have become a practical monitoring method for LAI. Nevertheless, for a proper LAI determination, the image’s spatial resolution is a key factor, since low-resolution images are incapable of distinguishing between adjacent vines due to the large area covered in each pixel, this leads to misinterpretation or generalisation of vineyard information.