| 胡伯凯1,2，王纪辉1,2，刘亚娜1,2，耿阳阳1,2，王港2，张东亚3.GC和LF-NMR结合化学计量学方法检测掺假油茶籽油[J].中国油脂,2023,48(8):.[HU Bokai1,2, WANG Jihui1,2, LIU Yana1,2, GENG Yangyang1,2,
WANG Gang2, ZHANG Dongya3.Detection of adulterated oil-tea camellia seed oil by GC and LF-NMR combined with chemometrics methods[J].China Oils and Fats,2023,48(8):.] |
| GC和LF-NMR结合化学计量学方法检测掺假油茶籽油 |
| Detection of adulterated oil-tea camellia seed oil by GC and LF-NMR combined with chemometrics methods |
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| DOI： |
| 中文关键词: 油茶籽油 脂肪酸组成 横向弛豫特性 化学计量学 掺假识别 |
| 英文关键词:oil-tea camellia seed oil fatty acid composition transverse relaxation characteristics chemometrics method adulteration identification |
| 基金项目:贵州省基础研究计划（\[2020\]1Y145）；贵州省林业科研项目（\[2020\]10）；贵州省科技创新人才团队（\[2020\]5003）；贵州省基础研究计划（\[2020\]1Y141）；贵州省优秀青年科技人才项目（2019\[5643\]) |
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| 中文摘要: |
| 为了对油茶籽油品质控制及评价提供支撑，以纯油茶籽油和掺假油茶籽油（分别掺入菜籽油、花生油、棕榈油和高油酸花生油）为试验材料，采用气相色谱法（GC）分析其脂肪酸组成，采用低场核磁共振技术（LF-NMR）测定其横向弛豫特性数据，结合主成分分析（PCA）、偏最小二乘判别分析（PLS-DA）和偏最小二乘分析（PLS）等化学计量学方法建立油茶籽油掺假的定性和定量分析模型。结果表明：5种植物油的脂肪酸组成和LF-NMR横向弛豫特性数据存在显著区别；油茶籽油和其他4种植物油在PCA得分图上可清晰区分；PLS-DA模型可有效区分油茶籽油和掺假油茶籽油，判别正确率均可达100%；建立的油茶籽油中掺入菜籽油、花生油、棕榈油、高油酸花生油的PLS定量预测模型，真实值与预测值的相关系数（R2）分别为0.994 1、0.998 6、0.997 6、0.978 1。综上，GC和LF-NMR结合PCA、PLS-DA以及PLS等化学计量学方法可用于油茶籽油掺假类别判定及掺假量分析。 |
| 英文摘要: |
| In order to provide support for the quality control and evaluation of oil-tea camellia seed oil, pure oil-tea camellia seed oil and adulterated oil-tea camellia seed oil (adulterated with rapeseed oil, peanut oil, palm oil,high olelc acid peanut oil respectively) were used as experimental materials, their fatty acid composition was analyzed by gas chromatography (GC) and transverse relaxation characteristic data was measured by low field nuclear magnetic resonance (LF-NMR), and then the qualitative and quantitative analysis models for distinguishing adulteration of oil-tea camellia seed oil were established by combining chemometric methods such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and partial least squares analysis (PLS). The results showed that there were significant differences in fatty acid composition and LF-NMR transverse relaxation characteristic data of the five vegetable oils. Pure oil-tea camellia seed oil and the other four vegetable oils could be clearly distinguished on the PCA score chart, the PLS-DA model could effectively distinguish oil-tea camellia seed oil from adulterated oil with a discrimination accuracy up to 100%. The PLS quantitative prediction models established for the adulteration of rapeseed oil, peanut oil, palm oil and high oleic acid peanut oil in oil-tea camellia seed oil showed R2 of 0.994 1, 0.998 6, 0.997 6 and 0.978 1 for the true and predicted values, respectively. In summary, GC and LF-NMR combined with chemometrics methods such as PCA, PLS-DA and PLS can be used to determine the adulteration category and analyze the adulteration amount in oil-tea camellia seed oil. |
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