Discrimination/Classification of Edible Vegetable Oils from Raman Spatially Solved Fingerprints Obtained on Portable Instrumentation Jiménez Hernández, Guillermo Ortega Gavilán, Fidel Bagur González, María Gracia González Casado, Antonio Raman fingerprints Edible vegetable oils Sunflower oil Currently, the combination of fingerprinting methodology and environmentally friendly and economical analytical instrumentation is becoming increasingly relevant in the food sector. In this study, a highly versatile portable analyser based on Spatially Offset Raman Spectroscopy (SORS) obtained fingerprints of edible vegetable oils (sunflower and olive oils), and the capability of such fingerprints (obtained quickly, reliably and without any sample treatment) to discriminate/classify the analysed samples was evaluated. After data treatment, not only unsupervised pattern recognition techniques (as HCA and PCA), but also supervised pattern recognition techniques (such as SVM, kNN and SIMCA), showed that the main effect on discrimination/classification was associated with those regions of the Raman fingerprint related to free fatty acid content, especially oleic and linoleic acid. These facts allowed the discernment of the original raw material used in the oil’s production. In all the models established, reliable qualimetric parameters were obtained. 2024-04-22T10:50:59Z 2024-04-22T10:50:59Z 2024-01-05 journal article Jiménez-Hernández, G.; Ortega-Gavilán, F.; Bagur-González, M.G.; González-Casado, A. Discrimination/Classification of Edible Vegetable Oils from Raman Spatially Solved Fingerprints Obtained on Portable Instrumentation. Foods 2024, 13, 183. https://doi.org/10.3390/foods13020183 https://hdl.handle.net/10481/91003 10.3390/foods13020183 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional MDPI