The role of endogenous lipid components on vegetable oil stability
Zambiazi, Rui C.
Thirty-three vegetable oils were evaluated in this study to determine the effects of effect of the major and minor endogenous components on the storage stability of vegetable oils. Initially the oils were analysed for fatty acid composition, triacylglycerol species, lipid classes, tocopherols, tocotrienols, sterols, chlorophylls, carotenoids, phenolics and metals. The stability of the oils was monitored by measuring oxygen consumption and chemical indices during storage with and without light a 35$\sp\circ$C and 65$\sp\circ$C, respectively. Changes in the amounts of fatty acids, tocopherols, tocotrienols, chlorophylls, carotenoids, sterols and phenolic acids were determined. The stability of the oils was dependent on a complex interaction among their endogenous components. During storage without light, the more saturated oils such as coconut and palm kernel were the most stable while the most highly unsaturated oil, conventional flax, was the least stable during storage without light. During storage with light, oil rich in carotenoids, palm golden oil, was the most stable among the oils analysed, while virgin olive oil containing the highest amount of chlorophyll was the least stable among the oils analysed, while virgin olive oil containing the highest amount of chlorophyll was the least stable. Fatty acid composition of oils had a significant effect on oil stability, but the minor components also greatly affected the stability. Chlorophylls acted as pro-oxidants in olive, soybean, canola and cottonseed oils when stored with light. Carotenoids accelerated the oxidation of palm golden oil when stored without light. Metals acted as pro-oxidants when present at trace amounts in palm and coconut oils. Tocopherols and tocotrienols had an antioxidant effect in oils, and their effectiveness was concentration dependent. Phospholipids and phenolic compounds improved the oxidative stability of oils, while a high content of sterols was accompanied by a faster oxidation. Application of Artificial Neural Networks was effective to predict the stability of oils using composition data. Utilization of fatty acids, tocopherols and tocotrienols composition was sufficient to accurately predict the stability of oils stored without light. The amounts of fatty acids, tocopherols, tocotrienols, chlorophylls and metals was necessary to predict the stability of oils stored in the presence of light.