2026-04-13T03:08:03Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1737462025-12-05T14:55:36Zcom_2072_1057col_2072_478917col_2072_478924

00925njm 22002777a 4500 dc Barbieri, Sara author Cevoli, Chiara author Bendini, Alessandra author Quintanilla-Casas, Beatriz author García González, Diego Luís author Gallina Toschi, Tullia author 2021-02-09T08:15:30Z 2021-02-09T08:15:30Z 2020-07-02 2021-02-09T08:15:30Z This research aims to develop a classification model based on untargeted elaboration of volatile fraction fingerprints of virgin olive oils (n = 331) analyzed by flash gas chromatography to predict the commercial category of samples (extra virgin olive oil, EVOO; virgin olive oil, VOO; lampante olive oil, LOO). The raw data related to volatile profiles were considered as independent variables, while the quality grades provided by sensory assessment were defined as a reference parameter. This data matrix was elaborated using the linear technique partial least squares-discriminant analysis (PLS-DA), applying, in sequence, two sequential classification models with two categories (EVOO vs. no-EVOO followed by VOO vs. LOO and LOO vs. no-LOO followed by VOO vs. EVOO). The results from this large set of samples provide satisfactory percentages of correctly classified samples, ranging from 72% to 85%, in external validation. This confirms the reliability of this approach in rapid screening of quality grades and that it represents a valid solution for supporting sensory panels, increasing the effciency of the controls, and also applicable to the industrial sector. Oli d'oliva Cromatografia de gasos Traçabilitat Olive oil Gas chromatography Traceability Flash Gas Chromatography in Tandem with Chemometrics: A Rapid Screening Tool for Quality Grades of Virgin Olive Oils