Sulfites (SO2) are commonly used in the wine industry to preserve products during storage for antiseptic and antioxidant purposes (Oliveira et al., 2011).

Environmental factors like soil and climate influence grape quality potential. Their impact is often mediated through vine water and nitrogen status. Depending on the color of the grapes (red or white) and the type of wine produced, the desired level of vine water and nitrogen status for optimum wine quality is different. Little investigation has been carried out concerning these factors and their potential influence on sparkling wine quality on two vintages. In this study vine water and nitrogen status were assessed at a very high density and related to grape composition and berry weight. Through statistical analyses, the major factors driving grape quality potential on Pinot noir in Champagne were highlighted.

Production, demand, and brand awareness of dealcoholized wine (<0.5% v/v) is steadily increasing worldwide. However, there have been few studies to date investigating and comparing the different physical processes for dealcoholizing wine.

Grapevine yield has been historically overlooked, assuming a strong trade-off between grape yield and wine quality. At present, menaced by climate change, many vineyards in Southern France are far from the quality label threshold, becoming grapevine yield-gaps a major subject of concern. Although yield-gaps are well studied in arable crops, we know very little about grapevine yield-gaps. In the present study, we analysed the environmental component of grapevine yield-gaps linked to climate and soil resources in the Languedoc Roussillon. We used SAFRAN data and IGP Pays d’Oc wine yields from 2010 to 2018. We selected climate and soil indicators proving to have a significant effect on average wine yield-gaps at the municipality scale. The most significant factors of grapevine yield were the Soil Available Water Capacity; followed by the Huglin Index and the Climatic Dryness Index. The Days of Frost; the Soil pH; and the Very Hot Days were also significant. Then, we clustered geographical zones presenting similar indicators, facilitating the identification of resources yield-gaps. We discussed the number of zones with the experts of IGP Pays d’Oc label, obtaining 7 zones with similar limitations for grapevine yield. Finally, we analysed the main resources causing yield-gaps and the grapevine varieties planted on each zone. Mapping grapevine resource yield-gaps are the first stage for understanding grapevine yield-gaps at the regional scale.

Artificial intelligence (AI) for winegrowers refers to robotics, smart sensor technology, and machine learning applied to solve climate change problems. Our research group has developed novel technology based on AI in the vineyard to monitor vineyard growth using computer vision analysis (VitiCanopy App) and grape maturity based on berry cell death to predict flavor and aroma profiles of berries and final wines.