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基质辅助激光解吸/电离飞行时间质谱联用化学计量学用于鉴定中药材的产地。

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with chemometrics to identify the origin of Chinese medicinal materials.

作者信息

Fang Huan, Chen Yue, Wu Hai-Long, Chen Yao, Wang Tong, Yang Jian, Fu Hai-Yan, Yang Xiao-Long, Li Xu-Fu, Yu Ru-Qin

机构信息

State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University Changsha 410082 PR China

Hunan Key Lab of Biomedical Materials and Devices, College of Life Sciences and Chemistry, Hunan University of Technology Zhuzhou 412008 PR China.

出版信息

RSC Adv. 2022 Jun 7;12(26):16886-16892. doi: 10.1039/d2ra02040h. eCollection 2022 Jun 1.

DOI:10.1039/d2ra02040h
PMID:35754890
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9171747/
Abstract

Geographical origin and authenticity are two core factors to promote the development of traditional Chinese medicine (TCM) herbs perception in terms of quality and price. Therefore, they are important to both sellers and consumers. Herein, we propose an efficient, accurate method for discrimination of genuine and non-authentic producing areas of TCM by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Take Koidz (AMK) of compositae as an example, the MALDI-TOF MS spectra data of 120 AMK samples aided by principal component analysis-linear discriminant analysis (PCA-LDA), partial least squares discriminant analysis (PLS-DA) and random forest (RF) successfully differentiated Zhejiang province, Anhui province and Hunan province AMK according to their geographical location of origin. The correct classification rates of test set were above 93.3%. Furthermore, 5 recollected AMK samples were used to verify the performance of the classification models. The outcome of this study can be a good resource in building a database for AMK. The combined utility of MALDI-TOF MS and chemometrics is expected to be expanded and applied to the origin traceability of other TCMs.

摘要

地理来源和真伪性是从质量和价格方面推动中药药材认知发展的两个核心因素。因此,它们对买卖双方都很重要。在此,我们提出一种通过基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF MS)鉴别中药正品和非正品产地的高效、准确方法。以菊科的款冬(AMK)为例,借助主成分分析-线性判别分析(PCA-LDA)、偏最小二乘判别分析(PLS-DA)和随机森林(RF),120个AMK样品的MALDI-TOF MS光谱数据成功根据其产地地理位置区分了浙江省、安徽省和湖南省的AMK。测试集的正确分类率高于93.3%。此外,使用5个回收的AMK样品验证分类模型的性能。本研究结果可为建立AMK数据库提供良好资源。预计MALDI-TOF MS和化学计量学的联合应用将得到扩展并应用于其他中药的产地溯源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/e0d863889f21/d2ra02040h-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/1a4f04499586/d2ra02040h-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/0caf540ae6c7/d2ra02040h-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/f7c6e1b36da4/d2ra02040h-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/7bc3a25f0033/d2ra02040h-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/e0d863889f21/d2ra02040h-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/1a4f04499586/d2ra02040h-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/0caf540ae6c7/d2ra02040h-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/f7c6e1b36da4/d2ra02040h-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/7bc3a25f0033/d2ra02040h-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2718/9171747/e0d863889f21/d2ra02040h-f5.jpg

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