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

Bayram İ., Parra-Escudero C., Decker E. A., Lu J.

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY, cilt.72, sa.9, ss.4939-4946, 2024 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 72 Sayı: 9
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1021/acs.jafc.3c08272
  • Dergi Adı: JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Analytical Abstracts, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Chimica, Compendex, Environment Index, Food Science & Technology Abstracts, Pollution Abstracts, Veterinary Science Database, DIALNET
  • Sayfa Sayıları: ss.4939-4946
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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 alpha-tocopherol. The lag phases of lipid hydroperoxides and headspace hexanal formation were found to have a strong positive correlation with the alpha-tocopherol depletion time. We propose that the kinetics of antioxidant (alpha-tocopherol) depletion occur during the lag phase and could serve as an early shelf-life indicator. Our results showed that alpha-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.