Wine identity through phenolics: authentication of Spanish red wines by geographical origin and grape variety

Introduction The characterization and authentication of natural products are often achieved through the combination of analytical techniques capable of generating high-quality, information-rich, and discriminative data with chemometric methods that can effectively exploit such information. Methods In this context, a novel methodology for the exploratory analysis and classification of red wines based on the profiling of phenolic compounds is here assessed. An extensive set of Spanish wines from several Protected Designations of Origin (PDOs) was collected for the study, including Montsant, Somontano, Rioja, and Ribera del Duero. The wines also differed in terms of grape variety, with monovarietal Tempranillo, Garnacha, and Syrah wines being well represented. Phenolic compounds belonging to the most abundant families, namely, hydroxycinnamic acids, catechins, flavonols, and benzoic acids, were determined by high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). Results The resulting compositional profiles of 22 relevant compounds were initially explored using unsupervised methods, such as principal component analysis (PCA), revealing broad sample distributions with substantial overlap among classes. Nevertheless, despite the complexity and multifactorial nature of the dataset, the polyphenolic profiles proved to be a rich source of discriminative markers. Classification and authentication methods, such as Partial Least Squares Discriminant Analysis (PLS- DA) and Soft Independent Modeling of Class Analogy (SIMCA) were investigated. Conclusions Overall, multiclass PLS-DA provided the best classification performance on the held-out prediction sets, with wine assignment errors ranging from 6.4% to 11.7% for PDO classification and from 4.3% to 16.0% for grape variety discrimination.