Untargeted metabolomics approaches are emerging as powerful tools for the quality evaluation and authenticity of food and beverages and have been applied to wine science. However, most fail to report the method validation, quality assurance and/or quality control applied, as well as the assessment through the metabolomics-methodology pipeline. Knowledge of Mexican viticulture, enology and wine science remains scarce, thus untargeted metabolomics approaches arise as a suitable tool. The aim of this study is to validate an untargeted HS-SPME-GC-qTOF/MS method, with attention to data processing to characterize Cabernet Sauvignon wines from two vineyards and two vintages. Validation parameters for targeted methods are applied in conjunction with the development of a recursive analysis of data. The combination of some parameters for targeted studies (repeatability and reproducibility < 20% RSD; linearity > 0.99; retention-time reproducibility < 0.5% RSD; match-identification factor < 2.0% RSD) with recursive analysis of data (101 entities detected) warrants that both chromatographic and spectrometry-processing data were under control and provided high-quality results, which in turn differentiate wine samples according to site and vintage. It also shows potential biomarkers that can be identified. This is a step forward in the pursuit of Mexican wine characterization that could be used as an authentication tool.

Volatilomic and sensory analyses of wine are excellent tools for enologists and winemakers when selecting commercial yeast based on the production of metabolites related to desirable wine characteristics. Integrating this holistic approach could lead to the terroir description, characterization, and quality control improvement of the vinification process. Volatilomic and sensory profiles of Cabernet Sauvignon Mexican wines fermented with three commercial yeasts (WLP740, ICVD254, and ICVD80) were obtained using HS-SPME-GC-qTOF/MS and CATA evaluation. A total of 100 volatile compounds were identified, with unique entities per strain. WLP740 wines were rated as high quality, presenting fruity and minty aromas with fewer off-aromas, while ICVD254 wines showed higher levels of compounds associated with off-notes and were rated as low quality. ICVD80 wines were of medium quality, with fruity esters and higher alcohols descriptors. Volatilomic profiles highlighted the role of specific compounds in differentiating strains and sensory attributes, while yeast selection significantly impacts wine aroma and quality. The authors acknowledge the need for further analyses, including an increased sample size, yeast species, diverse vineyards, and vinification processes, which will result in a solid and robust methodology.