基于稳定同位素和矿质元素的决明子产地特征与溯源判别研究

为了更加精确高效地对中药决明子产区进行判别,本研究采用稳定同位素比质谱(IR-MS)和电感耦合等离子体质谱(ICP-MS)技术分别检测不同产地决明子稳定同位素比值和多种矿质元素含量特征,并结合化学计量学模型主成分分析(PCA)和人工神经网络(ANN)对决明子产地进行判别。方差统计结果表明,在优质产区(浙江新昌)决明子区别于普通产区决明子方面,19种矿质元素含量存在显著差异(P<0.05);PCA分析(同位素+矿物元素)显示,前2个主成分累计方差贡献率为45.23%,且该模型可显著区分道地产区决明子;ANN模型分析对浙江新昌产区的决明子判别正确率高达100%,且产地判别总体正确率高于90%。以上结果表明,稳定同位素比值和矿质元素含量结合化学计量学模型分析可有效判别决明子不同产区。本研究结果为决明子产地溯源提供了一种新的方法。

Origin Characteristics and Traceability Discrimination of Cassiae Semen Based on Stable Isotope and Mineral Element

In order to identify the producing areas of traditional Chinese medicine of Cassiae Semen accurately and efficiently, stable isotope ratio and mineral element content of Cassiae Semen from different producing areas were measured using stable isotope ratio mass spectrometry (IR-MS) and inductively coupled plasma mass spectrometry (ICP-MS), respectively. Chemometrics models like principal component analysis (PCA) and artificial neural network (ANN) were established to clarify the producing areas of Cassiae Semen. It was found that there were significant differences in the contents of 19 kinds of mineral elements between high-quality production area (Xinchang, Zhejiang) and common production areas (P<0.05). Meanwhile, the cumulative variance contribution rate of the first two principal components comprised 45.23% in the PCA model based on stable isotope ratio combining with mineral element content of Cassiae Semen, that the PCA model can distinguish Cassiae Semen from quality region obviously. ANN model based on stable isotope ratio and mineral element content showed a high accuracy rate (100%) in determination of Cassiae Semen from Xinchang, Zhejiang province, and the overall accuracy rate of origin discrimination was higher than 90%. The results above show that stable isotope ratio and mineral element content combined with chemometrics model analysis can effectively identify the authentic area of Cassiae Semen, which provides a new method for accurate and efficient traceability of Cassiae Semen.