Characterization of Mesoclimatic zones competent for the culture of vine (vitis vinifera l.) in the province of San Juan, Argentina

The structural diversity is one of the most remarkable characteristics of proanthocyanidins (PA). Indeed, PA in wines may vary in the B-ring and C-ring substitutes, the C-ring stereochemistry, the degree of polymerization (DP) and the linkage between the monomers. Knowing in detail the structural characteristics of the PA of a wine can help us to understand and modulate several sensorial characteristics of the wine, such as color, antioxidant properties, flavor, and mouthfeel properties. In the last years was discovered and confirmed the presence of sulfonated monomeric and oligomeric flavan-3-ols in wine [1], as well as was pointed out their importance in wine quality [1,2].

Winemaking is a complex microbial process involving the co-existence and interactions of various microorganisms [1].

Modern grapevine breeding programs have overcome many challenges using genomic selection, which has allowed breeders to make targeted selections at earlier stages in the breeding process. However, the cost of genetic testing may present a burden for some programs, and markers often struggle to accurately predict quantitative traits. Recent advances in high throughput, high-dimensional data have provoked investigation into the use of high-dimensional phenomics as a low-cost addition to the grape breeder’s toolkit that may offer advantages in predicting quantitative traits. High-dimensional secondary trait (HDST) data has been employed in annual crops for prediction of agriculturally important traits such as yield.

Global change in climate affect regional climates and hold implications for viticulture worldwide. Despite numerous studies on the impact of projected global warming on different regions

Grapevine (Vitis vinifera L.) is a globally cultivated crop and economically significant, particularly in the wine industry (Varela et al., 2024). Climate change is already affecting vineyards and is expected to worsen (Averbeck et al., 2019; Dupuis and Knoepfel, 2011).