Viticultural agroclimatic cartography and zoning at mesoscale level using terrain information, remotely sensed data and weather station measurements. Case study of Bordeaux winegrowing area

The analysis of structurally diverse proanthocyanidins in grapes and wine is challenging. Comprehensive two-dimensional liquid chromatography (LC×LC) and ion mobility spectrometry-mass spectrometry (IMS-MS) are increasingly used to address the challenges associated with the analysis of highly complex samples such as wine and grapes

Brazil is one of the few countries where vineyards of Vitis labrusca and Vitis vinifera coexist in the same geographical spaces, due to complex processes of territorial occupation by successive waves of European settlers.

Choosing the rootstock, the scion variety and the training system best suited to the local soil and climate are the key elements for an economically sustainable production of wine. The choice of the rootstock/scion variety best adapted to the characteristics of the soil is essential but, by changing climatic conditions, ongoing climate change disrupts the fine-tuned local equilibrium. Higher temperatures induce shifts in developmental stages, with on the one hand increasing fears of spring frost damages and, on the other hand, ripening during the warmest periods in summer. Expected higher water demand and longer and more frequent drought events are also major concerns. The genetic control of the phenotypes, by genomic information but also by the epigenetic control of gene expression, offers a lot of opportunities for adapting the plant material to the future. For complex traits, genomic selection is also a promising method for predicting phenotypes. However, ecophysiological modelling is necessary to better anticipate the phenotypes in unexplored climatic conditions Genetic approaches applied on parameters of ecophysiological models rather than raw observed data are more than ever the basis for finding, or building, the ideal varieties of the future.

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. 

Climate is a key parameter when the modulation of berry and subsequent wine composition is considered. Recent decades have already seen an increase in global surface temperatures