The Bergerac guaranteed vintage area « terroirs »

Aroma diversity is one of the most important features in the expression of the varietal and geographic identity and sensory uniqueness of a wine. Italy has one of the largest ampelographic heritages of the world, with more than five hundred different varieties. Among them, many are used for the production of dry still white wines, many classified as Protected Designation of Origins and therefore produced in specific geographical areas with well-defined grape varieties. Chemical and sensory characteristics of the aroma of these wines have never been systematically studied, and the relative diversity has never been described and classified.

‘Cabernet sauvignon’ and ‘Merlot’ are among the most recognized red wine grape cultivars. This work is aimed at investigating the proanthocyanidin composition of skins and seeds to determine the grape variety and the vintage effects on the phenolic composition of Bordeaux grapes.

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

Un programme de recherche concernant les facteurs naturels et humains des terroirs viticoles a été développé dans le vignoble A.O.C. de l’Anjou, sur une surface d’environ 30.000 Ha

Studies on wineomics (wine’s metabolome) have increased considerably over the last two decades. Wine results from many environmental, human and biological factors leading to a specific metabolome for each terroir. NMR metabolomics is a particularly effective tool for studying the metabolome since it allows the rapid and simultaneous detection of major compounds from several chemical families.1 Quantitative NMR has already proven its effectiveness in monitoring the authenticity of still wines.