Identifying physiological and genetic bases of grapevine adaptation to climate change with maintained quality: Genome diversity as a driver for phenotypic plasticity  (‘PlastiVigne’ project)

The vineyard is capable of fixing carbon in its permanent structure from atmospheric carbon dioxide, through the process of gas exchange and the performance of photosynthesis. The photosynthetic capacity of the vineyard depends on the water resources that the plant may have at its disposal, so the amount of dry matter, derived from the processed photosynthates, that it can store will depend on the water regime of the crop, both in the annually renewable organs as in permanent parts.

In the concept of sustainable viticulture proposed by the OIV, it can be noted that enhancing terroir is also one measure of sustainability. Thus, the territorial approach may offer an interesting viewpoint from which to consider this issue in a multi-perspective way.

Evidence indicates that climate change affects the environment, human health, and well-being via drought, increasing greenhouse effect, and climatic catastrophes. As the wine sector is also negatively affected by climate change, the role of climate change mitigation and adaptation policies is important in wine production. One example of an adaptation policy is the implementation of grapevine genetics (duchene, 2016), while organic farming may be used as an approach to mitigate the consequences of climate change (vinci et al., 2022). To this end, the european commission’s objective is to reach the european green deal target of at least 25% of the european union’s agricultural land under organic farming by 2030.

Open geospatial data and advanced GIS technologies are rapidly transforming terroir science, providing the wine sector with unprecedented capabilities for spatial analysis, monitoring, and decision-making.

The assessment of wine authenticity is of great importance for consumers, producers and regulatory agencies to guarantee the geographical origin of wines and grape variety as well. Since mid-infrared (MIR) spectroscopy with chemometrics represent a suitable tool to ascertain the wine composition, including features associated with the polyphenolic compounds, the aim of this study was to generate MIR spectra of red wines to be exploited for classification of red wines based on the relationship between grape variety and wine composition. Several multivariate data analyses were used, including Principal Component Analysis (PCA), Discriminant Analysis (DA), Support Vector Machine (SVM), and Soft Intelligent Modelling of Class Analogy (SIMCA).