Parcours de découverte des terroirs viticoles

Grape cane is a viticultural by-product that is currently underused or not used at all. Therefore, it bears a high potential for valorization due to the presence of anti-microbially active stilbenoids, being biologically relevant for plant defense. These compounds are highly interesting for applications in the agricultural sector as well as for the food and feed industry.

The concept of terroir or sense of place is almost as old as the wine industry. It is generally used as an all-encompassing term to reflect the effects of the biophysical environment in which grapes and their resultant wines are produced on the character of those wines. Historically, terroir has generally been considered at the regional or property scale.

Œnococcus oeni is a wine-associated lactic acid bacterium performs the malolactic fermentation, which improves the taste and aromatic complexity of many wine.

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