Abstract

This work investigates the application of Fourier Transform Infrared spectroscopy (FTIR) combined with chemometrics as a rapid and non-destructive tool for monitoring the thermal stability of pure sesame oil (SeO) as well as SeO blends with adulterants, including corn, soybean, and sunflower oils in different proportions (99 + 1, 95 + 5, 90 + 10, and 80 + 20 in volume). The oil samples were subjected to thermal treatment at five temperatures (25, 60, 100, 150, and 180 °C) as a function of time up to 96 h. FTIR provided sensitive approach for analysing thermal degradation and compositional changes of pure and adulterated SeO under controlled temperature conditions during varied heating times. Principal component analysis (PCA) was used to discriminate pure SeO at different treatment conditions. In addition, soft independent modelling class analogy (SIMCA) was useful to differentiate between pure and adulterated samples, and the results showed high precision and accuracy, enabling successful discrimination, with a maximum error rate of 6.00%. Finally, partial least squares regression (PLSR) models were developed and showed a good linear correlation between the FTIR signals at different conditions and the proportion of pure SeO. The root mean square of prediction (RMSEP) ranges between 0.8802 and 2.3827 with a coefficient of determination (R2) between 0.9841 and 0.8834, respectively. These findings demonstrate the efficacy of FTIR combined with chemometrics in detecting adulteration in SeO, thus offering a solution for quality control and food safety assessments in the food industry.

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