Classification and Adulteration Detection of Vegetable Oils Based on Fatty Acid Profiles

文献类型： 外文期刊

第一作者： Zhang, Liangxiao

作者： Zhang, Liangxiao;Li, Peiwu;Sun, Xiaoman;Wang, Xuefang;Xu, Baocheng;Wang, Xiupin;Ma, Fei;Zhang, Qi;Ding, Xiaoxia;Ma, Fei;Zhang, Qi;Li, Peiwu;Zhang, Qi;Zhang, Liangxiao;Li, Peiwu;Ding, Xiaoxia;Zhang, Liangxiao;Li, Peiwu;Sun, Xiaoman;Wang, Xuefang;Xu, Baocheng;Wang, Xiupin;Ma, Fei

作者机构：

关键词： fatty acid profiles;adulteration identification;edible oil;GC/MS;chemometrics

期刊名称：JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY （ 影响因子：5.279； 五年影响因子：5.269 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： The detection of adulteration of high priced oils is a particular concern in food quality and safety. Therefore, it is necessary to develop authenticity detection method for protecting the health of customers. In this study, fatty acid profiles of five edible oils were established by gas chromatography coupled with mass spectrometry (GC/MS) in selected ion monitoring mode. Using mass spectral characteristics of selected ions and equivalent chain length (ECL), 28 fatty acids were identified and employed to classify five kinds of edible oils by using unsupervised (principal component analysis and hierarchical clustering analysis), supervised (random forests) multivariate statistical methods. The results indicated that fatty acid profiles of these edible oils could classify five kinds of edible vegetable oils into five groups and are therefore employed to authenticity assessment. Moreover, adulterated oils were simulated by Monte Carlo method to establish simultaneous adulteration detection model for five kinds of edible oils by random forests. As a result, this model could identify five kinds of edible oils and sensitively detect adulteration of edible oil with other vegetable oils about the level of 10%.

分类号： R15`S

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