Mining microbiome data to identify antagonists of grapevine downy mildew (Plasmopara viticola)

he use of high-power ultrasound (US) is proving of great interest to the oenological industry due to its effects in the improvement of wine organoleptic characteristics, especially in terms of color [1, 2].

Le territoire de Suzette se développe sur un grand coteau viticole et boisé situé au cœur du site naturel des Dentelles de Montmirail (40km au nord d’Avignon). Ce site est à la fois l’un des pôles d’attraction touristique du département et le lieu d’une production viticole renommée (Gigondas, Vacqueyras, Beaumes de Venise, … ). Cet ensemble remarquable de terrasses viticoles et de crêtes rocheuses et boisées, forme un des paysages emblématiques du Vaucluse. La commune est actuellement soumise à une importante pression foncière due à une forte demande résidentielle. Le paysage du coteau forme et possède de ce fait un patrimoine culturel de valeur et une image de marque importante pour la production viticole locale.

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.

In the production of sparkling wines, during the second fermentation, mannoproteins are released by yeast autolysis, which affect the quality of the wines. The effect of mannoproteins has been extensively studied, and may affect aroma and foam quality. However, there are no studies on the effect of other polysaccharides such as those from grapes. Considering the large production of waste from the wine industry, it was proposed to obtain polysaccharide-rich extracts from some of these by-products[1].

AIM: Volatile compounds joint to aromatic precursors form the aroma of grape must that will provide a characteristic aroma to the wine.