Yeast cell walls (CWs) may adsorb wine components with a significant impact on wine quality. When dealing with red wines, this adsorption is mainly related to physicochemical interactions between wine polyphenols and cell wall mannoproteins. However, mannoproteins are a heterogeneous family of complex peptidoglycans including long and highly branched N-linked oligosaccharides and short linear O-linked oligosaccharides, resulting in a huge structural diversity.

Temperature control is crucial in wine production, starting from grape harvest to the bottled wine storage. Climate change and global warming affect the timing of grape ripening, and harvesting is often done during hot summer days, influencing berry integrity, secondary metabolites potential, enzyme and oxidation phenomena, and even fermentation kinetics. To curb this phenomenon, pre-fermentative cold storage can help preserve the grapes and possibly increase the concentration of key secondary metabolites. In this study, the effect of grape pre-fermentative cold storage was assessed on the ‘Moscato bianco’ white grape cultivar, known for its varietal terpenes (65% of free terpenes represented by linalool and its derivatives) and widely used in Piedmont (Italy) to produce Asti DOCG wines.

The objective of this study was to develop a methodology capable of modeling the effect of viticultural climate on wine sensory characteristics.

AIM: High pressure technologies represent a promising alternative to thermal treatments for improving quality and safety of liquid foods.

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.