Berry shrivel causes – summarizing current hypotheses

Measurements of parameters spatialy positionned, with on line sensors mounted on classical machinery or airborne imagery is no more a problem in viticulture. In a short time, high resolution data dedicated to the assessment of the vine characteristics, the soil, the harvest, etc. will become a reality.

Grapevine cultivars are vegetatively propagated to maintain their varietal attributes. However, spontaneous somatic variation emerges during prolonged periods of vegetative growth, providing an opportunity for the natural improvement of traditional grapevine cultivars. Notably, reduction in bunch compactness is a favorable trait in viticulture, offering advantages such as decreased susceptibility to bunch fungal diseases, and a more uniform ripening of berries. To unravel the genetic and developmental mechanisms behind bunch compactness variation, we examined a somatic variant of Tempranillo Tinto cultivar with loose bunches. We found that the mutant clone exhibits a ~50% reduction in pollen viability compared to typical Tempranillo clones.

The study of technologic and phenolic maturation is very efficient to determinate quality potential of red grapes cultivars and clones under different maturity levels or geographic origins

At a time when the world’s winegrowing industry is having to adapt to a number of challenges, winegrowers are wondering about the consequent changes they will have to make (grape varieties, changes in vineyard and cellar techniques). For winegrowers and consumers alike, there is also the question of how these changes will affect the taste of their wines. This research, based on the study of numerous sources and archives from the 20th century, some of which have never been published before, aims to show that, in the recent past, the winegrowing world has shown incredible resilience in the face of crises, and that the taste and perception of fine wines has changed considerably in 100 years.

Aims: The aims of this study were to i) characterize the impact of geographical origin and viticulture treatments on Chilean Cabernet-Sauvignon, and ii) develop machine learning models to predict its quality.