Electrochemical approaches in wine analysis 

Recent developments in satellite technology have yielded a substantial volume of data, providing a foundation for various machine learning approaches. These applications, utilizing extensive datasets, offer valuable insights into Earth’s conditions. Examples include climate change analysis, risk and damage assessment, water quality evaluation, and crop monitoring. Our study focuses on exploiting satellite thermal and multispectral imaging, and vegetation indexes, such as NDVI, in conjunction with ground truth information about soil type, land usage (forest, urban, crop cultivation), and irrigation water sources in the Trentino region in North-East of Italy.

Introduction: Major depressive disorder is associated with abnormalities in the brain and the immune system. Chronic stress in animals showed that epigenetic and inflammatory mechanisms play important roles in mediating resilience and susceptibility to depression.

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].

Sustainable viticulture and winemaking continue to represent huge challenges, where a better knowledge about the functional role of biodiversity in the vineyard and wine ecosystems is required, as well as the varieties plasticity. Particular attention should be devoted to the spatial and temporal interactions between authorized or recommended varieties for a specific demarcated region and clime and vineyard conditions (such as soil type, orientation of the lines, age of the vine, density of planting, harvesting practices, among others).

In a previous work1, it was suggested that the different contents in delphinidin and catechin of the grapes were determinant on the O2 consumption and Strecker aldehyde (SAs) accumulation rates. Higher delphinidin seemed to be related to a faster O2 consumption and a smaller SAs accumulation rate, and the opposite was observed regarding catechin.
In the present paper, these observations were fully corroborated by adding synthetic delphinidin to a wine model containing polyphenolic fractions (PFs) extracted from garnacha and synthetic catechin to a wine model containing PF extracted from tempranillo: The delphinin-containing garnacha model consumed O₂ significantly faster and accumulated significantly smaller amounts of SAs than the original garnacha model, and the catechin-containing tempranillo model, consumed O2 significantly slower and accumulated significantly higher amounts of SAs than the original tempranillo model.