Applicability of spectrofluorometry and voltammetry in combination with machine learning approaches for authentication of DOCa Rioja Tempranillo wines

Pomace is one of the main residues generated by the wine industry and represents an environmental problem. Currently, there is a growing interest in the revaluation of these products because different bioactive compounds can be obtained from them, such as polyphenols, grape seed oils and polysaccharides. Red grape pomace can be an important source of polysaccharides, but they are currently little studied and even less with viable and environmental extraction processes (green extraction), such as flash extraction. The residual amount of the fraction rich in pectin (residual pulp) and component rich in hemicellulose in the pomace and the strength of association of the pectin with the cellulose-xyloglucan network depend on the degree of extractability of the polysaccharides in red winemaking and on the winemaking conditions.

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.

Vine growth circumstances are becoming warmer and drier because of climate change. Higher temperatures advance ripening to a point in the season less conducive to the production of fine wine, while drought reduces yields (Van Leeuwen et al., 2019). Several wine-producing regions around the world have already recognized threats to their viticultural viability (Santos et al., 2020). An economical and cost-effective strategy for adaptation is the employment of late-ripening, drought-resistant plant material (varieties, clones, and rootstocks).

Grapevine (Vitis vinifera L.) exhibits a high level of genetic and phenotypic diversity among the approximately 6000 cultivars recorded. This perennial crop is highly vulnerable to numerous fungal diseases, including esca, which is a complex vascular pathology that poses a significant threat to the wine sector, as there is currently no cost-efficient curative method[1]. In this context, an effective approach to mitigate the impact of such diseases is by leveraging the crop’s genetic diversity. Indeed, susceptibility to esca disease appears to vary between cultivars, under artificial or natural infection. However, the mechanisms and varietal characteristics underlying cultivar susceptibility to esca are still unknown.

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins.