核磁共振技术结合化学计量学方法用于蜂蜜的掺假鉴别

Identification of Honey Adulteration by Nuclear Magnetic Resonance Technology and Chemometrics Method

采用核磁共振技术(NMR)结合化学计量学分析手段研究了真蜂蜜和掺假蜂蜜的指纹图谱变化情况。采用无监督的主成分分析(PCA)和有监督的偏最小二乘判别分析(PLS-DA)、正交偏最小二乘判别分析(OPLS-DA)等多元统计分析方法从核磁信号中提取各组的分类信息。结果表明:建立的OPLS-DA模型能够区分真假蜂蜜,所建模型对蜂蜜真假判别的解释能力为90.5%,对未知样本的预测能力为75.5%、识别率为89.7%。置换测试验证表明,化学计量学模型具有很好的稳定性和预测性,可信赖性强,且模型稳健。通过OPLS-DA模型的载荷图和相关系数分析找到了对区分掺假蜂蜜有显著作用的标志物。结合相关系数分析,建立了辨别真假蜂蜜的多元线性回归方程。该方法可简单、快速地用于未知蜂蜜的掺假鉴别,为规范蜂蜜市场提供有利的依据。

Currently existing national standards for honey adulteration are based on one type or cer tain types of compounds. Therefore, it is necessary to develop a multi-component and multi-index method to identify the honey adulteration. In this research, the changes of fingerprint between pure and adulterated honey were explored based on the NMR fingerprinting analysis and chemometric method. Unsupervised method of principal component analysis （PCA） , supervised method of partial least squares discriminant analysis （ PLS - DA） and orthogonal - PLS - DA （ OPLS - DA） were all used to extract the useful information from NMR signals. The results showed that OPLS -DA model could distinguish the adulterated honey from pure honey. The explanation abilities based on the OPLS 4 i DA model was 90. 5%. The prediction and recognition abilities were 75.5% and 89.7% , respect tively. Through permutation test, the chemometric model showed good stability, accurate predictability and high reliability. Several significant markers were found to distinguish honey from the loading plot and correlation coefficient analysis of OPLS - DA model. Combined with the correlation coef- ficient analysis, multiple linear regression equation was established to distinguish the adulterated honey from pure honey. The proposed method was simple and sensitive. This method provided an effective approach to control the honey quality and detect the honey adulteration.