Zhang Yu, Guo Xiaohan, Wan Lizhi, Zhang Jiating, Jing Wenguang, Li Minghua, Cheng Xianlong, Wei Feng
Institute for Control of Traditional Chinese Medicine and Ethnic Medicine, National Institutes for Food and Drug Control, Beijing 102629, China.
Faculty of Functional Food and Wine, Shenyang Pharmaceutical University, Shenyang 110016, China.
Foods. 2025 Aug 27;14(17):3005. doi: 10.3390/foods14173005.
Angelica sinensis radix (AS), the dried root of (Oliv.) , is widely used in Chinese medicine and food products. However, after conducting market research, at least a quarter of AS on the market is commonly adulterated by W. D. J. Koch (LO), (Sieb. et Zucc.) Kitagawa (AA), and Nakai (AG), to varying degrees, which significantly affects its clinical efficacy and food safety. Therefore, there is a pressing need to establish safe and reliable methods for identifying illicit adulteration. In this study, the mass spectrometry (MS) information of AS, LO, AA, and AG was collected and converted into the data matrix for [-I]. The proprietary ions of AS, AG, AA, and LO were output as their molecular "matrix characteristics". Test samples were also analyzed, transformed into data matrices, and their own matrix characteristics were matched sequentially. For matching credibility (MC) results, a significant difference was found between the MC of the four herbs compared to their own matrix characteristics, as well as between the MC of the four herbs compared with their non-self matrix characteristics. Research results showed that based on matrix characteristics, AS and its adulterations can be identified with a matching credibility (MC) ≥ 78.0%; 3% adulterations can also be identified, and two market-blind samples were identified as exhibiting adulterations. In addition, chemometrics analysis demonstrated that adulteration identification based on matrix characteristics is reasonable and reliable. The matrix characteristics of AS and its adulterants contribute to adulteration analysis. The identification method, based on matrix characteristics, is safe and reliable which is conducive to AS's quality control and market supervision.
当归(Angelica sinensis radix,AS),即伞形科植物当归(Angelica sinensis (Oliv.) Diels)的干燥根,广泛应用于中药和食品中。然而,经市场调研发现,市场上至少四分之一的当归普遍不同程度地掺假有刺果甘草(Glycyrrhiza pallidiflora W. D. J. Koch,LO)、白芷(Angelica dahurica (Fisch. ex Hoffm.) Benth. et Hook. f. ex Franch. et Sav. var. formosana (Boiss.) Kitagawa,AA)和紫花前胡(Peucedanum decursivum (Miq.) Maxim.,AG),这显著影响了其临床疗效和食品安全。因此,迫切需要建立安全可靠的方法来鉴别非法掺假。本研究收集了当归、刺果甘草、白芷和紫花前胡的质谱(MS)信息,并将其转换为用于[ -I]的数据矩阵。当归、紫花前胡、白芷和刺果甘草的特征离子作为它们的分子“基质特征”输出。对测试样品也进行了分析,转换为数据矩阵,并依次匹配它们自身的基质特征。对于匹配可信度(MC)结果,发现四种药材与其自身基质特征相比的MC之间,以及四种药材与其非自身基质特征相比的MC之间存在显著差异。研究结果表明,基于基质特征,当归及其掺假品能够以匹配可信度(MC)≥78.0%进行鉴别;还能够鉴别出3%的掺假品,并且鉴定出两个市场盲样存在掺假情况。此外,化学计量学分析表明基于基质特征的掺假鉴别是合理可靠的。当归及其掺假品的基质特征有助于掺假分析。基于基质特征的鉴别方法安全可靠,有利于当归的质量控制和市场监管。