Discrimination/Classification of Edible Vegetable Oils from Raman Spatially Solved Fingerprints Obtained on Portable Instrumentation
Metadatos
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Jiménez Hernández, Guillermo; Ortega Gavilán, Fidel; Bagur González, María Gracia; González Casado, AntonioEditorial
MDPI
Materia
Raman fingerprints Edible vegetable oils Sunflower oil
Fecha
2024-01-05Referencia bibliográfica
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
Resumen
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.