Oil stability prediction by high-resolution (13)C nuclear magnetic resonance spectroscopy

(13)C NMR spectra of oil fractions obtained chromatographically from 66 vegetable oils were obtained and analyzed to evaluate the potential use of those fractions in predicting oil stabilities and to compare those results with oil stability prediction by using chemical determinations. The oils included the following: virgin olive oils from different cultivars and regions of Europe and north Africa; "lampante" olive, refined olive, refined olive pomace, low-erucic rapeseed, high-oleic sunflower, corn, grapeseed, soybean, and sunflower oils. Oils were analyzed for fatty acid and triacylglycerol composition, as well as for phenol and tocopherol contents. By using stepwise linear regression analysis (SLRA), the chemical determinations and the (13)C NMR data that better explained the oil stability determined by the Rancimat were selected. These selected variables were related to both the susceptibility of the oil to be oxidized and the content of minor components that most contributed to oil stability. Because (13)C NMR considered many more variables than those determined by chemical analysis, the predicted stabilities calculated by using NMR data were always better than those obtained by using chemical determinations. All these results suggest that (13)C NMR may be a powerful tool to predict oil stabilities when applied to chromatographically enriched oil fractions.