Camellia oil adulteration model 6 was established by using any two kinds of vegetable oils (soybean oil,peanut oil and rapeseed oil) with different proportions in pure camellia oil.The content of fatty acids in each sample was measured by gas chromatography-mass spectrometry (GC-MS).Correlation and significance analysis were used to screen out the appropriate symbolic fatty acid to establish the multiple regression equation model of camellia oil adulteration.The results showed that some fatty acids in camellia oil adulteration model changes significantly,and has a high correlation with the camellia oil adulteration model.At the same time,the correlation coefficient(R2 vaule) of the regression equationswere high,which indicated that the regression equation was true and reliable.The results could provide theoretical basis for quality control and adulterate detection of camellia oil.%以纯茶油中掺伪不同比例大豆油、花生油和菜籽油中任意两种植物油脂来建立茶油掺伪模型,通过气质联用技术测得各样品脂肪酸的含量,并通过相关性、显著性分析来筛选出合适的标志性脂肪酸建立茶油掺伪的多元回归方程模型.结果表明:某些脂肪酸含量在茶油掺伪模型中变化显著,且与茶油掺伪模型间具有高的相关性,选取该部分脂肪酸建立的相应回归模型方程的相关系数(R2值)均较高,说明本实验获得的回归方程模型真实、可靠.研究结果可以为茶油的产品质量监控和掺假检测提供借鉴.
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