Geographical origin identification of camellia oil based on fatty acid profiles combined with one-class classification

文献类型： 外文期刊

第一作者： Dou, Xinjing

作者： Dou, Xinjing;Wang, Xuefang;Ma, Fei;Yu, Li;Mao, Jin;Jiang, Jun;Zhang, Liangxiao;Li, Peiwu;Zhang, Liangxiao;Mao, Jin;Zhang, Liangxiao;Li, Peiwu;Li, Peiwu

作者机构：

关键词： Camellia oil; Fatty acid profiles; Geographical origin traceability; One-class classification

期刊名称：FOOD CHEMISTRY （ 影响因子：8.8； 五年影响因子：8.6 ）

ISSN： 0308-8146

年卷期： 2024 年 433 卷

页码：

收录情况： SCI

摘要： Geographical Indication (GI) agricultural products possess specific geographical origins and high qualities, which require an effective geographical origin traceability method for the important protective trademarks. In this study, authentication models for Changshan camellia oil were developed by fatty acid profiles and one-class classification methods including data-driven soft independent modeling of class analogy (DD-SIMCA) and one-class partial least squares (OCPLS), and compared with traditional two-class classification models. The results indicated that the prediction errors of three two-class classification models were 63.8%, 12.1%, and 65.2% for the samples out of targeted geographical origins, respectively. By contrast, the one-class classification models could completely differentiate Changshan from non-Changshan camellia oils, even from the adjacent counties. Moreover, compared with traditional indicators of mineral elements, the model built by fatty acid profiles possessed higher sensitivity and specificity. It also offered a reference strategy for the geographical origin identification of other high-value oils or foods.

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