Assessment of oxidative behaviour in polyunsaturated fatty acid-rich oils using spectroscopic techniques and multivariate analysis

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 . • FTIR and Raman with multivariate analysis monitor PUFA oxidation at ~50 °C, reagent-free. • FTIR showed oxidation markers (~1740 cm −1 ) and 100% accuracy, beating Raman's 79–84%. • Raman was less accurate early but revealed unsaturation and double-bond degradation. • SVM outperformed PLS-DA and RF, stressing algorithm choice in spectral classification. • This method enables fast, scalable PUFA oil QC for food, pharma, and health industries.