For several years, the development of computer resources, and in particular of Geographic Information Systems, have allowed the emergence of a new approach to the analysis and characterization of wine-growing areas (Morlat, 1989; Laville, 1990). These methods, which make it possible to identify homogeneous areas or units of terroir, are based on crossing, statistical analysis (in particular Principal Component Analysis: PCA) and the integration of parameters describing the natural environment in which develop the vine.

Today’s viticulture is facing a new climatic scenario with temperature increases and rainfall deficits, generated by the effect of climate change. As a result of these new conditions, there are earlier harvests, increased plant water stress and higher disease risk in wetter wine-growing regions.

The Intergovernmental Panel on Climate Change (IPCC) forecasts an increase in global temperature and a decrease in relative humidity (RH) in the coming decades, which may have implications for berry ripening and composition.

Storage temperature and bottling parameters are among the most important factors, which influence the development of wine after bottling. It is well studied that higher storage temperatures speed up chemical reactions and results in faster wine aging [1,2]. It is also known that higher SO2 level and lower oxygen content provide better protection and longer shelf-life for the wine. At the same time, the mechanisms of chemical transformations of wine aromas during the aging process are not fully understood. In particular, how oxidation reactions contribute to the transformations of varietal aroma compounds.In the present study [3], we investigated the development of Riesling wine depending on a series of bottling conditions, which differed in the free SO2 level in wine (low—13 mg/L, medium—24 mg/L, high—36 mg/L), CO2 treatment of the headspace.

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.