Study on Geographical Traceability of Artemisia argyi by Employing the Fourier Transform Infrared Spectral Fingerprinting
LI Chao1, LI Meng-zhi1, LI Dan-xia1, WEI Shi-bing1, CUI Zhan-hu2, XIANG Li-ling1, HUANG Xian-zhang1*
1. Henan Key Laboratory of Zhang Zhongjing Formulae and Herbs for Immunoregulation, Nanyang Institute of Technology, Nanyang 473000, China
2. College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Abstract：The geographical distribution of medicinal plants significantly affect the quality and safety of Chinese medicinal materials. From the biological point of view, Chinese medicinal materials are formed during the long-term ecological adaptation of species affected by a specific ecological environment. The climate, soil, hydrology, and other ecological factors required for the growth of medicinal materials are closely related to their growth and quality and have fingerprint characteristics of geographical information. In recent years, the rapid development of the Chinese medicine industry has brought about a surge in demand for Chinese medicine resources. However, at the same time, there are also many potential safety hazards. The difficulty in distinguishing and tracing the origin of Chinese medicinal materials has become one of the main bottlenecks restricting the development of traditional Chinese medicine. In this study, 75 A. argyi samples from 5 major producing areas of 4 provinces in China were analyzed by FTIR for characteristic analysis and data mining. Spectral signal preprocessing methods include Gaussian filtering, multivariate scattering correction, standard normal transformation, first/second derivative, etc. and pattern recognition techniques include BP neural network model, random forest, K-nearest neighbor, Bayesian algorithm, particle swarm optimization support vector machine, etc. were applied to explore the feasibility of traceability for A. argyi. The results indicate that the algorithms of K-nearest neighbor, Bayesian, and particle swarm optimization support vector machine show the ideal recognition effect, with an accuracy of 100%. Considering the comprehensive factors of running time, identification accuracy, and model stability, the algorithm of K-nearest neighbor is determined as the best method to trace the origin of A. argyi. In general, FTIR technology combined with appropriate chemometrics methods can be used to trace the origin of A. argyi successfully. The results of this study can provide technical support for the evaluation and quality control of A. argyi, and also contribute useful reference for the isotropic research of other medicinal materials.
李 超，李孟芝，李丹霞，韦诗冰，崔占虎，项丽玲，黄显章. 基于傅里叶变换红外光谱指纹技术的艾叶产地溯源研究[J]. 光谱学与光谱分析, 2022, 42(08): 2532-2537.
LI Chao, LI Meng-zhi, LI Dan-xia, WEI Shi-bing, CUI Zhan-hu, XIANG Li-ling, HUANG Xian-zhang. Study on Geographical Traceability of Artemisia argyi by Employing the Fourier Transform Infrared Spectral Fingerprinting. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2532-2537.
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