Observatoire Grenache en Vallée du Rhône: incidence du terroir sur la composition polyphénolique des raisins et des vins

The use of the term bioprotection in winemaking refers to the use of non-chemical methods to prevent the development of undesirable microorganisms (yeasts and/or bacteria). The reason for studying this method is mainly as a natural alternative to the addition of sulfites during the pre-fermentation stages. In winemaking, the addition of s02 has multiple functions, the main ones being antiseptic and antioxidant power.

High concentration of sugars in grapes and alcohols in wines is one of the consequences of climate change on viticulture production in several wine regions. One of the options to alleviate this potential problem is to perform severe shoot trimming of the vines to limit the production of carbohydrates. Two different studies were performed in order to investigate the effects of severe shoot trimming on the composition of Merlot grapes; in a first study severe shoot trimming was performed at three different phenological stages (at berry set, at the beginning of veraison and at the end of veraison), while in a second study two trimming treatments (standard shoot trimming and severe shoot trimming performed at the end of veraison) were combined with two shoot densities in order to evaluate the relative impact of these treatments on Merlot grape composition.

Hydrolysable tannins resulted effective against the formation of light-struck taste (LST) in model wine [1]. The first activity of Enofotoshield project is to evaluate the effectiveness of tannins

Dans une approche globale, nous proposons la définition suivante du zonage : “représentation cartographique associée à une sectorisation du territoire en zones unitaires homogènes à partir de facteurs discriminants établis sur la base d’indicateurs quantifiables et d’avis d’experts”. La première application de cette méthode a porté sur la caractérisation du terroir en liaison avec les aspects qualitatifs des vins. Il est également possible d’envisager d’appliquer cette démarche dans les stratégies environnementales et paysagères liées aux approches territoriales et aux pratiques viticoles. Cette méthode peut servir de base dans la mise en œuvre des outils financiers associés aux mesures environnementales (CTE, aides spécifiques).

Aim: Through machine-learning modelling of plant water status from environmental characteristics, this work aims to develop a model able to predict grape phenolic composition in space and time to guide selective harvest decisions at the estate scale.