Modeling the impact of residual fat-soluble vitamin (FSV) contents on the oxidative stability of commercially refined vegetable oils

• Fatty acids, fat-soluble vitamins (FSVs), and lipid oxidation data were collected on 50 fats/oils.
• A new parameter (‘All Area’) was introduced to capture the total lipid oxidation of stored samples.
• Multi-regression fitting enabled strong correlations between fat composition and stability.
• Addition of FSV improved models built on OSI (R2 = 0.93) and the ‘All Area’ parameter (R2 = 0.96).

Fat-soluble vitamins (FSVs) may prevent or delay bulk lipid oxidation by exerting antioxidant action. However, literature data obtained from storage tests on commercial edible oils do not necessarily confirm a direct correlation between FSV contents of bulk oils and their measured oxidative stability. This, of course, may be predominantly due to their refining history, which can strip them of much of their FSV contents and/or standardize these values. The main goal of this study was to quantify the magnitude of the role of FSVs in hindering commercial edible lipid oxidation. Fatty acid composition and FSV content data were collected on a large mixed set of commercial vegetable oils devoid of added antioxidant stabilizers (n = 123) in order to establish baseline values for these constituents. Next, a random subset of these oils (n = 50) was then subjected to the oil stability index test (OSI at 120 °C), as well as accelerated storage testing over time (60 °C) whilst monitoring a host of classical methodologies used to monitor oxidation progress. A new aggregate parameter (i.e., a sum area under the lipid oxidation curves, or ‘All Area’) was introduced to better capture the total quantity of primary and secondary oxidation products accumulated in the samples tested over the storage period. Multivariate regression modeling was used to correlate the fatty acid composition of the samples with their oxidative stability data both including and excluding FSV contents in order to determine a magnitude for this relationship. As noted herein, the addition of FSV data improved the fitting of the model from R2Adj. 0.877 to 0.925 using OSI data alone and from R2Adj. 0.938 to 0.960 using the ‘All Area’ parameter. Correlations between specific FSVs and fatty acid compositional parameters exhibited a strong relationship with lipid category. Furthermore, principal component analysis of FSV contents revealed clustering of lipids based both on lipid category and refining history.

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