The pyramidal organization of AOC in France: a process of identification and valorisation of terroirs

The presence of acetic acid bacteria in wine can lead to the appearance of acetic acid at concentrations above the perception threshold, causing the wine rejection by the consumer. During the winemaking process, avoiding the presence of acetic acid bacteria is very difficult, as there is always a residual population accompanying the wine[1], and the problem arises with the significant development of these microorganisms that metabolizes large amounts of acetic acid.
The concern of wineries to control the presence of acetic acid bacteria in wines during their conservation is due to the absence of simple and effective analyses that allow the detection of these microorganisms in the initial stages.

Dans des travaux précédents sur le zonage, on a traité de la « Grande Filière », du « terroir », du « territoire », de la «″Terra »″ (« Terre »”), des « Petits zonages ou sub-zonages », du « Grand Zonage », de la qualité (nous en avons classifié plus de quatre-vingt-dix), des « Grands Objectifs » (GO) de l’activité vitivinicole et des moyens utilisés pour les atteindre. Dans le « GRAND ZONAGE » (GZ) nous avons précisé que pour zoner, nous partons des aspects

Many farming operations aim at controlling the leaf area of the vine according to its load. There are several techniques, direct and indirect, of estimate of this leaf area in a specific way, but impossible to implement at great scales. These last years, research in airborne and satellite remote sensing made it possible to show that a multispectral index of vegetation, computed from measurements of reflectances (red and near infrared), the « Normalised Difference Vegetation Index » (NDVI), is well correlated to the « Leaf Area Index » (leaf area per unit of ground) of the vine. Nevertheless these methods of acquisition and processing data are rather constraining and complex.

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

Vegetative growth and yield are reported to affect grape and wine quality. They can be controlled through different techniques linked to vine management. The objective of this research was to determine the effect of vine vigour and number of clusters per vine on physicochemical composition and phenolic profile of red wines. The experiment was carried out during two vegetative cycles, with cv. Cabernet Sauvignon grafted onto Paulsen 1103. Three vine vigour were defined, according to shoot weight at previous harvests, being low, medium and high. Five treatments of number of clusters were used for each vigour, with 15, 22, 29, 36, and 45 clusters per vine. Grapes from all treatments were harvested in the same day from Brix and total acidity criteria. Thirty days after bottling, classical analyzes and phenolic compounds were performed. As results, different responses were obtained from each vintage. In 2020, a dry season from veraison to harvest, grapes and wines obtained from low vigour treatment and 45 clusters per vine was the highest in sugar and alcohol content respectively, while grapes and wines from high vigour and 15 clusters presented the lowest sugar and alcohol content. Total anthocyanins were higher in treatment with low vigour and 15 clusters, while the lowest amounts were found in low vigour with 45 clusters, as well as medium and high vigour with 36 clusters per vine. Total tannins were higher in high vigour with 22 clusters and medium vigour with 29 clusters, while were lower in low vigour with 36 clusters. In 2021, a wet season at harvest, responses were different, and great variations were observed between treatments. As conclusions, yield and vine vigour had strong influence on grape and wine quality, promoting different enological potentials on which can be indicated/used for aging strategies of red and even rosé wines.