UHPLC–UV Fingerprinting for Wine Characterization by Geographical Origin and Grape Variety

The characterization and authentication of wines are essential to ensure quality and traceability, as well as to protect the added value linked to geographical origin, vinification processes, and grape variety. This study develops a non-targeted approach based on ultra-high-performance liquid chromatography with ultraviolet detection (UHPLC-UV) to obtain chromatographic fingerprints at 280 nm, mainly reflecting phenolic acids and flavanols. Data preprocessing, including correction of peak shifts, baseline drifts, and other artifacts, was carried out using open-source software further adapted in-house. Principal Component Analysis (PCA) revealed clear sample clustering according to Protected Designation of Origin (PDO) and grape variety, demonstrating the discriminative potential of the fingerprints. Supervised classification methods, including Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modelling of Class Analogies (SIMCA), provided good predictive performance, with mean classification errors below 20.6%. Misclassifications were mainly associated with geographically close PDOs and multivarietal blends. Somontano PDO and Tempranillo wines were the most accurately classified categories.