Proteomic profiling of grape berry presenting early loss of mesocarp cell vitality

The European wine industry is facing multiple challenges derived from climate change and the pressure of different fungal diseases that are compromising the production of traditional varieties. A sustainable alternative maybe the adoption of resistant varieties.
In this study, we have evaluated the enological potential of 9 resistant varieties (5 white and 4 red varieties) in La Rioja. Microvinifications were carried out with three biological replications. Oenological parameters were very diverse with acid content varying from 2.6 g/L to 6.6 g/L.

In plants, stress due to nutrient deficiency can significantly impair their development and productivity.

Phenolic compounds are very important in crop plants and have been the subject of a large number of studies. Three main reasons can be cited for optimizing the level of phenolic compounds in crop plants: their physiological role in plants, their technological significance for food processing, and their nutritional characteristics1 Indeed, an enormous diversity of phenolic antioxidants is found in fruits and vegetables, and their presence and roles can be affected or modified by several pre- and postharvest cultural practices and/or food processing technologies (Ruiz-García et al. 2012, Goldman et al. 1999, Tudela et al. 2002). In winegrapes, the technological importance of phenolic compounds, mainly flavonoids, is well-known.

Climatic variability studies at fine scale have been developed in recent years with the reduction of material cost and the development of competitive miniaturized sensors. This work is forming part the LIFE-ADVICLIM project, of which one of the objectives is to model spatial temperature variability at vineyard scale. In the Bordeaux pilot site, a large network of data loggers has been set up to record temperature close to the vine canopy. The reduced distance between plant foliage and measurement equipment raises specific issues and leads to an increased rate of outliers compared to data retrieved from classical weather stations. Some of these were detected during data analysis, but others could not be easily identified. The present study aims to address the issue of data quality control and provide recommendations for data processing in climatic studies at fine scale.

For several years, the development of computer resources, and in particular of Geographic Information Systems, have allowed the emergence of a new approach to the analysis and characterization of wine-growing areas (Morlat, 1989; Laville, 1990). These methods, which make it possible to identify homogeneous areas or units of terroir, are based on crossing, statistical analysis (in particular Principal Component Analysis: PCA) and the integration of parameters describing the natural environment in which develop the vine.