Abstract

The sunflower oil-oleoresin rosemary (Rosmarinus officinalis L.) blends (SORB) at 9 different concentrations (200 to 2000 mg/kg), sunflower oil-tertiary butyl hydroquinone (SOTBHQ ) at 200 mg/kg and control (without preservatives) (SO control ) were oxidized using Rancimat (temperature: 100 to 130 °C; airflow rate: 20 L/h). The oxidative stability of blends was expressed using induction period (IP), oil stability index and photochemiluminescence assay. The linear regression models were generated by plotting ln IP with temperature to estimate the shelf life at 20 °C (SL20 ; R(2) > 0.90). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to classify the oil blends depending upon the oxidative stability and kinetic parameters. The Arrhenius equation adequately described the temperature-dependent kinetics (R(2) > 0.90, P < 0.05) and kinetic parameters viz. activation energies, activation enthalpies, and entropies were calculated in the range of 92.07 to 100.50 kJ/mol, 88.85 to 97.28 kJ/mol, -33.33 to -1.13 J/mol K, respectively. Using PCA, a satisfactory discrimination was noted among SORB, SOTBHQ , and SOcontrol samples. HCA classified the oil blends into 3 different clusters (I, II, and III) where SORB1200 and SORB1500 were grouped together in close proximity with SOTBHQ indicating the comparable oxidative stability. The SL20 was estimated to be 3790, 6974, and 4179 h for SO control, SOTBHQ, and SORB1500, respectively. The multivariate kinetic approach effectively screened SORB1500 as the best blend conferring the highest oxidative stability to sunflower oil. This approach can be adopted for quick and reliable estimation of the oxidative stability of oil samples.

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