Deciphering the function and regulation of VviEPFL9 paralogs to modulate stomatal density in grapevine through New Genomic Techniques

Decrease of chemical inputs during vine management and winemaking is of great importance from a political and societal point of view. In our ongoing project we propose alternative tools to chemicals in the vineyard and the cellar. We have compared a conventional vineyard protection strategy to an alternative strategy using copper and biocontrol products (Biocontrol) against downy

Chardonnay is the world’s most planted white grape variety and has met a great commercial success for decades.

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

Wine lees are quantitatively the second most important wine by-product after grape stems and marc [1]. In order to recycle, distilleries recovered ethanol and tartaric acid contained in wine lees but yeast biomass is often unused. It has already been demonstrated that this yeast biomass could be upcycled to produce yeast extracts of interest for wine chemical stabilization [2]. In addition, it is well known that lees, during aging, release compounds that preserve wine from oxidation.

Non-targeted analysis is applied in many different domains of analytical chemistry such as metabolomics, environmental and food analysis. In contrast to targeted analysis, non-targeted approaches take information of known and unknown compounds into account, are inherently more comprehensive and give a more holistic representation of the sample composition.