A method for the determination of triacylglycerols (TAGs) in vegetable oils from different botanical origins by HPLC with UV–vis detection has been developed. Using a core-shell particle packed column (C18, 2.6 micron), TAG separation was optimized in terms of mobile phase composition and column temperature. Using isocratic elution with acetonitrile/n-pentanol at 10 °C, excellent efficiency with good resolution between most of the TAG peak pairs, within a total analysis time of 15 min, was achieved. Using mass spectrometry detection, a total of 15 peaks, which were common to oils of six different botanical origins (corn, extra virgin olive, grapeseed, hazelnut, peanut and soybean) were identified. These peaks were used to construct linear discriminant analysis (LDA) models for botanical origin prediction. Ratios of the peak areas selected by pairs were used as predictors. All the oils were correctly classified with assignment probabilities higher than 95%.

Use of triacylglycerol profiles established by high performance liquid chromatography with ultraviolet–visible detection to predict the botanical origin of vegetable oils

CERRETANI, LORENZO;BENDINI, ALESSANDRA;
2011

Abstract

A method for the determination of triacylglycerols (TAGs) in vegetable oils from different botanical origins by HPLC with UV–vis detection has been developed. Using a core-shell particle packed column (C18, 2.6 micron), TAG separation was optimized in terms of mobile phase composition and column temperature. Using isocratic elution with acetonitrile/n-pentanol at 10 °C, excellent efficiency with good resolution between most of the TAG peak pairs, within a total analysis time of 15 min, was achieved. Using mass spectrometry detection, a total of 15 peaks, which were common to oils of six different botanical origins (corn, extra virgin olive, grapeseed, hazelnut, peanut and soybean) were identified. These peaks were used to construct linear discriminant analysis (LDA) models for botanical origin prediction. Ratios of the peak areas selected by pairs were used as predictors. All the oils were correctly classified with assignment probabilities higher than 95%.
M.J. Lerma-García; R. Lusardi; E. Chiavaro; L. Cerretani; A. Bendini; G. Ramis-Ramos; E.F. Simó-Alfonso
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/105793
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