基于脂肪酸组成甄别油茶籽油掺伪的研究

以植物油的特征信息——脂肪酸组成为依据,结合化学计量学,运用主成分法、偏最小二乘判别因子分析法来研究甄别油茶籽油的可行性,并运用偏最小二乘回归分析法来定量预测分析不同掺伪比例的油茶籽油。结果显示:主成分法(Principal Component Analysis,PCA)、偏最小二乘判别因子分析法(Partial Least-squares Analysis-Discriminat Factor Analysis,PLS-DFA)都能将油茶籽油样品与其他几种植物油样品区分开来,并且PLS-DFA要比PCA区分效果稍好;掺伪比例和脂肪酸组成具有较好的线性关系,偏最小二乘回归分析法(Partial Least-squares Analysis,PLS)能够定量预测分析掺伪比例为5%~60%的掺伪样品,且相关系数都能达到0.98以上,说明脂肪酸组成结合化学计量学方法能够很好的甄别油茶籽油掺伪,为快速甄别油茶籽油掺伪提供技术支撑。

The Adulterating Research of Identifying Camellia Oil Based On Fatty Acids

In this paper, the feasibility of identifying camellia oil is researched with the method of Principal Component Analysis and Partial Least-squares Analysis - Discriminat Factor Analysis, which is combined with stechiometry on the basis of fatty acids, which is one of characteristic information in vegetable oil. The result is as follows. Camellia oil can be clearly distinguishable from other vegetable oil with the method of PCA and PLS-DA, especially PLS-DA is better than PCA. There is high correlation between fatty acid and the adulteration ratio of camellia. PLS could efficiently identity the experimental samples of camellia oil adulterated with 0%- 60% other vegetable oil ( correlation coefficient is all above 0.98 ). It proved in the test that the method of stechiometry could be applied in adulteration recognition of camellia oil on the basis of fatty acids, which can provide technical support to identify camellia oil rapidly.