Le pays du Brulhois

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.

Context and purpose of the study. Nitrogen (N) limitation enhances the production of phenolic compounds in grapes due to the downregulation of the flavonoid biosynthesis pathway.

Variations in average growing season and ripening season temperatures within the Walla Walla Valley American Viticultural Area are related to elevation and regional and local topography.

The creation of disease-resistant varieties adapted to climate change is a key challenge for the future of the wine industry. At present, the selection of these new varieties is essentially based on screening for genetic markers of resistance and agronomic criteria, due to the small number of vines available per genotype. Integrating screening for oenological criteria into the early stages of selection would speed up this process.

Table grapes (Vitis labrusca and hybrids) are widely cultivated in Brazil [1] due to the climate, their resistance to disease and the way they are consumed and commercialized, either in-natura or for processing, producing whole juices, jams and table wines.