Mathematical Modeling of Alpha-Tocopherol Early Degradation Kinetics to Predict the Shelf-Life of Bulk Oils.

The kinetics of lipid oxidation includes a lag phase followed by an exponential increase in oxidation products, which cause rancidity. Current models focus on the slope of this exponential curve for shelf-life estimation, which still requires the measurement of full oxidation kinetics. In this paper, we analyzed the formation of lipid oxidation products in stripped soybean oil containing different levels of α-tocopherol. The lag phases of lipid hydroperoxides and headspace hexanal formation were found to have a strong positive correlation with the α-tocopherol depletion time. We propose that the kinetics of antioxidant (α-tocopherol) depletion occur during the lag phase and could serve as an early shelf-life indicator. Our results showed that α-tocopherol degradation can be described by Weibull kinetics over a wide range of initial concentrations. Furthermore, we conducted in silico investigations using Monte Carlo simulations to critically evaluate the feasibility and sensitivity of the shelf-life prediction using early antioxidant degradation kinetics. Our results revealed that the shelf life of soybean oil may be accurately predicted as early as 20% of the overall shelf life. This innovative approach provides a more efficient and faster assessment of shelf life, ultimately reducing waste and enhancing product quality.