Elaboration des cartes conseils pour une gestion du terroir à l’échelle parcellaire: utilisation d’algorithmes bases sur des paramètres physiques du milieu naturel

Traceability of wine is today a consumer demand and a scientific challenge. The methods of analysis must be able to control three fundamental parameters: the geographical origin, the grape varieties, and the vintage.

Grapevine is a plant that holds significant socioeconomic importance due to its production of grapes for fresh consumption, wines, and juices. However, climate changes and susceptibility to diseases pose a threat to the quality and yield of these products. The breeding of new genotypes that are resistant/tolerant to biotic and abiotic stresses is essential to overcome the impact of climate changes. In this regard, Marker-assisted selection (MAS), which uses DNA markers, is a crucial tool in breeding programs. The efficiency and economy of this method depend on finding rapid DNA isolation methods.

Acid aspergillopepsins-i (ap-i) have been suggested for use in winemaking due to their ability to degrade proteins, which reduces haze formation and the necessity for bentonite to achieve protein stability. These endopeptidases cleave non-terminal amino acid bonds of proteins, resulting in their degradation.

Soil and climate of 3 vineyards have been characterised in order to determine their influence on grape quality. These vineyards are located in Conca de Barberà (Catalonia, NE Spain) and belong to Cabernet sauvignon and Grenache noir cultivars. All 3 plots are very close, so only interannual climatic data of the nearest meteorological station have been considered.

Grapevine leaf removal (LR) in the cluster area is typically done between fruit set and cluster closure to create an unfavorable microclimate for fungal diseases, such as Botrytis cinerea and powdery mildew. Grape growers are now turning their attention to pre-flowering LR, which has additional benefits under certain conditions. When applied before flowering, LR strongly affects fruit set and thus the number of berries per cluster. It is therefore a good yield control tool, replacing time-consuming manual cluster thinning (Poni et al. 2006). It also improves berry structure, that is, skin thickness, skin-to-pulp ratio, and berry composition (total soluble solids, titratable acidity, and polyphenols) (Palliotti et al. 2012; Komm and Moyer 2015). By exacerbating competition for assimilates between reproductive and vegetative organs, pre-flowering LR also poses some risks. Excessive yield loss at the same year’s harvest due to a too low fruit set rate is the main concern: intensive pre-flowering LR (100% of the cluster area) can induce up to 50% yield loss in potted vines (Poni et al. 2005). Other parameters, such as cool climatic conditions during flowering, also affect fruit set rate and make it difficult to predict potential yield at harvest. Repeated and overly intensive preflowering LR can have repercussions over time and induce a decline in bud fruiting and plant vigor (Risco et al. 2014).