不同植物源的蜂胶物质组成不同, 其生理和药理活性也存在着一定的差异。 目前主要是根据蜂胶中物质组成及其含量的不同来鉴别蜂胶植物源, 存在着一些局限性。 因此, 建立一种快速、 准确鉴别蜂胶植物源的方法具有重要的意义。 以三种不同植物源的蜂胶(杨树型蜂胶、 桦树型蜂胶和橡树型蜂胶)为研究对象, 利用傅里叶变换近红外光谱仪对蜂胶的无水乙醇溶液进行光谱扫描, 采用主成分分析结合马氏距离判别法和典型判别分析分别建立蜂胶品种的判别模型并对其性能进行检验。 结果表明: 在经过光谱预处理和主成分分析后, 得到最佳的光谱建模波段为4　500～12　000　cm-1,最佳的光谱预处理方法为一阶导数+Savitzky-Golay(7)平滑; 主成分分析结合马氏距离判别法建立的判别模型校正集和检验集的判别准确率分别为93.62%和82.61%; 典型判别分析建立的判别模型的判别准确率为91.4%, 交叉检验的判别准确率为88.6%。 由此可知, 主成分分析结合马氏距离判别法与典型判别分析对蜂胶样品的分类效果均较好。 近红外光谱技术结合化学计量学方法应用于蜂胶植物源的快速、 准确鉴别具有一定的可行性和实用性。

Botanical origins of propolis are significant factors affecting biological and pharmacological activities because of different components in propolis. Until now, the determination of propolis botanical origins is mainly based on different varieties and the content of the compositions with great limitations. Therefore, it is important to discriminate different botanical origins of propolis quickly and accurately. In this study, Near-infrared (NIR) spectra of propolis varieties based on principal component analysis mahalanobis distance (PCA-mahalanobis distance) model and canonical discriminant analysis model were built for the classification of three botanical origins (poplar propolis, brich propolis and rubber propolis). The models were built based on the optimal pretreatment method and bands of first derivative + Savitzky-Golay (7) filter and 4500~12 000-1, which were selected in advance. After the principal component analysis, the correct classification rates of calibration sets and validation sets in analysis mahalanobis distance models were 93.62% and 82.61%, respectively. The discrimination rate and the cross-validation rate of canonical discrimination models were 91.4% and 88.6%, respectively. Therefore, NIR spectroscopy with chemometric methods is not only feasible but also practical for rapid and accurate identification of varieties of propolis.