Polyunsaturated fatty acid (PUFA)-rich oils, such as fish oil (FO), borage oil (BO), and evening primrose oil (EPO), are highly susceptible to oxidative degradation, which compromises their nutritional value. This study applies Fourier-transform infrared (FTIR) and Raman spectroscopy combined with multivariate data analysis to develop a non-destructive, reagent-free approach for monitoring fatty acid composition and oxidation induced by mild thermal stress (∼50 °C), which simulates degradation. FTIR provides clear spectral markers of oxidation and achieved up to 100% classification accuracy, while Raman spectroscopy offered complementary information on unsaturation but showed lower performance (79-84%) and greater oil-type dependency. These findings highlight the importance of algorithm choice in multivariate modelling of spectroscopic data, with Support Vector Machines consistently outperforming other methods. Overall, the spectroscopy-only workflow demonstrated here offers a rapid, scalable, and non-invasive platform for oxidation detection and authenticity testing in PUFA-rich oils under realistic storage conditions.
山东省济南市章丘区文博路2号
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