Effets de l’application d’acide gibbérellique (GA3) sur la qualité de raisins et de vins produits en climat tropical au Nord-Est du Brésil

the phenological evolution is a crucial aspect of grapevine growth and development. Accurate detection of phenological stages can improve vineyard management, leading to better crop yield and quality traits. However, traditional methods of phenological tracking such as on-site observations are time-consuming and labour-intensive. This work proposes a scalable data-driven method to automatically detect key phenological stages of grapevines using satellite data. Our approach applies to vast areas because it solely relies on open and satellite data having global coverage without requiring any in-field data from weather stations or other sensors making the approach extensible to other areas.

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

L’histoire de viticulture de l’Afrique du Sud embrasse 340 ans, et a commencé, à la province du Cap, où les colonisateurs hollandais ont planté les premières vignes. L’arrivée des Huguenots français en 1688 a avancé, le développement.

The wine spoilage yeast Brettanomyces bruxellensis can be found at several steps in the winemaking process due to its resistance to multiple stress conditions. Among the resistance strategies, one could be the formation of biofilm, a lifestyle known to enhance persistence of microorganisms. In this study, we propose to characterize biofilm of B. bruxellensis in wine, especially through several microscopic analyses.

The wine yeast Saccharomyces cerevisiae can highly affect wine aromatic profile by producing and/or mediating the release of a whole range of metabolites (such as thiols, esters, and terpenes), which in turn contribute to enhanced aroma and flavor. These metabolites depend on yeast metabolism activated during fermentation which can constitute the ‘’metabolic footprint’’ of the yeast strain that carried out the process.