Grapevine bud fertility under elevated carbon dioxide

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.

The wine sector is one of the most significant industries worldwide, with Spain being a leading country in wine production and export. A key factor in wine quality is its aroma, which is directly influenced by the volatile compounds present in the grape, with terpenes being among the most significant contributors.

Cet article propose la formalisation d’un modèle paramétrique pour représenter l’accumulation des sucres dans les baies de raisin durant la maturation. Le test de ce modèle sur des jeux de données réels a permis de valider l’approche proposée. Une seconde partie est axée sur l’adaptation de la méthode pour permettre la simulation du comportement du millésime en cours dès les premiers relevés de maturité. Ce travail possède de multiples applications dans le domaine de l’aide à la décision.

Wine yeast strains Saccharomyces ellipsoideus have important applications in food industry and in this regard is sought isolation as pure cultures and selecting those strains, which in laboratory investigations which have great biotechnological properties This study was intended as the ratio of live cells and autolysates cells also the influence of culture medium on this report. Yeasts selected for this study were isolated from industrial strains of indigenous grape varieties, namely: Feteasca Royal (FR) Feteasca White (FA), black Feteasca (FN), Romanian Tamaioasa (TR), Babeasca Black (BN) and Cotnari Grasa (GC).

The ’Furmint’ is the most important grape variety in the Tokaj Wine Region, constituting around 65% of its vineyard area. Before the phylloxera disease many types were grown, but as selection started in the 20th century, its diversity dramatically narrowed. As a result, the cultivation of Furmint was based mainly on two heavy-cropping clones, T.85 and T.92 at the end of the ’80s. Aims of present clone research take into account that after solely quantity as target, quality emerged in the 1990’s and most recently, typicity appeared as more private estates began their own selection program.