Unravel the underlying mechanisms of delaying ripening techniques in grapevine

With growing consumer interest in products without chemical additives, limiting the use of sulfites is a priority for the wine industry. Bioprotection is a biological alternative that avoids or reduces the risks of alterations that have a negative impact on the organoleptic quality of wines and, ultimately, on their acceptability to consumers. bioprotection can also provide a response to the risks of microbiological deviations, which are increased both by climate change and by the organization of harvesting operations, which increasingly include the use of multi-bins filled at the vine, exposing the harvest to sometimes high temperatures for longer periods of time.

The Columbia Valley American Viticultural Area (AVA) of the Pacific Northwest, USA is the world’s largest officially recognized viticultural area with basalt bedrock.

Regenerative agriculture (RA) practices aim to minimize soil disturbance, keep soil covered, maintain living roots underground, and integrate livestock to improve soil health and sustainability.

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.

Sangiovese is one of the main cultivar in the Italian ampelographic outline and it occupies more than 60% of total vineyard surface in the Tuscany region. It is also well known that the environmental