Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics

文献类型： 外文期刊

第一作者： Shi, Ting

作者： Shi, Ting;Dai, Tenghui;Dai, Tenghui;Wu, Gangcheng;Jin, Qingzhe;Wang, Xingguo

作者机构：

关键词： Camellia oil; Different grade adulteration; Volatile components; Chemometrics

期刊名称：FOOD CONTROL （ 影响因子：6.3； 五年影响因子：6.1 ）

ISSN： 0956-7135

年卷期： 2025 年 169 卷

页码：

收录情况： SCI

摘要： The volatile compounds combined with chemometrics, were used for different grade camellia oil adulterated detection. Using unsupervised models with fatty acids or triglycerides as input variables, the first-grade camellia oils (CAO I) and second-grade camellia oils (CAO II) occurred severely overlay in principle component analysis (PCA), for their almost quite identical compositions. While based on volatile components, hierarchical clustering analysis (HCA) presented a clear boundary between CAO I and CAO II samples. Subsequently, using our selected 15 volatile components by the variable importance in projection (VIP), both orthogonal projections to latent structure-discriminant analysis (OPLS-DA) and support vector machines (SVM), could be utilized as complementary models for camellia oil grade authentication with good classification rate (>= 91.67%). In addition, according to those above characteristic variables with auto-scaling pretreatment, the optimized OPLS model could be recommended for adulterated level prediction (5%-100%, w/w).

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