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Predictive mechanistic modelling of vegetable oil autoxidation using a parametrised kinetic network
Vincent J P Boerkamp1, Khoa A Nguyen1, Jean-Paul Vincken1
1Laboratory of Food Chemistry, Wageningen University & Research, Bornse Weilanden 9, Wageningen, 6708 WG, The Netherlands.
Current Research in Food Science
|November 24, 2025
Summary
This study introduces a predictive model for vegetable oil oxidation, simplifying shelf-life testing. The model accurately forecasts oil degradation under various conditions, aiding antioxidative strategy development.
Area of Science:
- Food Chemistry
- Chemical Kinetics
- Predictive Modeling
Background:
- Current shelf-life testing for vegetable oils is empirical and time-consuming.
- Rationalizing antioxidative strategies requires a more efficient approach.
- Understanding oxidation kinetics is crucial for food preservation.
Purpose of the Study:
- To develop a predictive model for vegetable oil oxidation.
- To account for environmental and compositional factors influencing oxidation.
- To enable accurate in silico shelf-life predictions.
Main Methods:
- Constructed a kinetic network of 23 oxidation reactions.
- Parametrized the model using activation energies for key fatty acids (triolein, trilinolein, trilinolenin).
- Validated the model against various vegetable oils and environmental conditions.
Main Results:
- The predictive model accurately forecasted autoxidation reactions (normalized root mean square errors < 0.05).
- The model successfully integrated environmental parameters (oxygen pressure, temperature, headspace ratio).
- Compositional factors (fatty acids, antioxidants, metals) were effectively incorporated.
Conclusions:
- The developed model enables reliable in silico shelf-life predictions for vegetable oils.
- The model can be adapted for other edible oils and extended to emulsified food systems.
- This approach streamlines the design of effective antioxidative strategies.
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