Agronomic and qualitative effects of early leaf removal on cv.

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.

We evaluate wine ratings by comparing data from two crowdsourcing platforms – Vivino, which aggregates the opinions of a large number of wine lovers, and Global Wine Medal Rating, which aggregates the scores from more than 1030 international wine competitions since 2020.

Yields in the novel viticulture training system Semi-Minimal-Pruned Hedge (SMPH) are generally higher compared to the traditional Vertical Shoot Positioning (VSP). Excessive yields have a negative impact on the vine and wine quality, which can result in substantial losses in yield in subsequent vintages (alternate bearing) or penalties in fruit quality. Therefore yield regulation is essential. The bunch architecture in SMPH differs from VSP. Generally there is a higher amount but smaller bunches with lower single berry weights in SMPH compared to VSP.

Aims: This work summarizes some of the upmost recent studies and valorization strategies concerning the Prosecco wine production area. After the geographical denomination Prosecco (DO) was strongly reformed in 2009, the newborn DOCG (controlled and guaranteed DO) and DOC (controlled DO) areas have required different and specific strategies to promote and protect the value of their production.

Wine production is a complex biochemical process that involves a heterogeneous microbiota consisting of different microorganisms such as yeasts, bacteria, and filamentous fungi. Among these microorganisms, yeasts play a predominant role in the chemistry of wine, as they actively participate in alcoholic fermentation, a biochemical process that transforms the sugars in grapes into ethanol and carbon dioxide while producing additional by-products. The quality of the final product is greatly influenced by the microbiota present in the grape berry, and the demand for indigenous yeast starters adapted to specific grape must and reflecting the biodiversity of a particular region is increasing. This supports the concept that indigenous yeast strains can be associated with a “terroir”.