|
|
|
|
|
|
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.
|
Received: 2022-03-23
Accepted: 2022-06-06
|
|
Corresponding Authors:
HUANG Xian-zhang
E-mail: nylgxyhxz@126.com
|
|
[1] Chinese Pharmacopoeia Commission(国家药典委员会). Pharmacopoeia of the People’s Republic of China·Part 1(中华人民共和国药典·1部). Beijing:China Medical Science Press(北京:中国医药科技出版社),2020. 91.
[2] Song X,Wen X,He J,et al. Journal of Functional Foods,2019,52:648.
[3] CAO Ling,YU Dan,CUI Lei,et al(曹 玲,于 丹,崔 磊,等). Drug Evaluation Research(药物评价研究),2018,41(5):216.
[4] Xiao J,Liu W,Sun H,et al. Bioorganic Chemistry,2019,92:103268.
[5] HUANG Xian-zhang,KANG Li-ping,GAO Li,et al(黄显章,康利平,高 丽,等). China Journal of Chinese Materia Medica(中国中药杂志),2017,42(18):3504.
[6] HU Ji-qing,WAN Ding-rong,PU Rui,et al(胡吉清,万定荣,蒲 锐,等). China Journal of Traditional Chinese Medicine and Pharmacy(中华中医药杂志),2019,34(2):123.
[7] LI Chao,CUI Zhan-hu,HUANG Xian-zhang,et al(李 超,崔占虎,黄显章,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2021,41(5):1350.
[8] LI Chao,GAO Li,KANG Li-ping,et al(李 超,高 丽,康利平,等). Jiangsu Agricultural Sciences(江苏农业科学),2021,49(22):186.
[9] TIAN Sheng-ni,LI Ya-nan,HU Yi-xuan,et al(田胜尼,李亚楠,胡艺璇,等). Journal of Biology(生物学杂志),2021,38(6):65.
[10] ZHENG Si-hao,ZHAO Sha,ZENG Yan,et al(郑司浩,赵 莎,曾 燕,等). Modern Chinese Medicine(中国现代中药),2021,23(12):2037.
|
[1] |
CHENG Jia-wei1, 2,LIU Xin-xing1, 2*,ZHANG Juan1, 2. Application of Infrared Spectroscopy in Exploration of Mineral Deposits: A Review[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 15-21. |
[2] |
LI Jie, ZHOU Qu*, JIA Lu-fen, CUI Xiao-sen. Comparative Study on Detection Methods of Furfural in Transformer Oil Based on IR and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 125-133. |
[3] |
YANG Cheng-en1, 2, LI Meng3, LU Qiu-yu2, WANG Jin-ling4, LI Yu-ting2*, SU Ling1*. Fast Prediction of Flavone and Polysaccharide Contents in
Aronia Melanocarpa by FTIR and ELM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 62-68. |
[4] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
[5] |
LIU Jia, ZHENG Ya-long, WANG Cheng-bo, YIN Zuo-wei*, PAN Shao-kui. Spectra Characterization of Diaspore-Sapphire From Hotan, Xinjiang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 176-180. |
[6] |
BAO Hao1, 2,ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
[7] |
GUO Ya-fei1, CAO Qiang1, YE Lei-lei1, ZHANG Cheng-yuan1, KOU Ren-bo1, WANG Jun-mei1, GUO Mei1, 2*. Double Index Sequence Analysis of FTIR and Anti-Inflammatory Spectrum Effect Relationship of Rheum Tanguticum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 188-196. |
[8] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
[9] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
[10] |
DANG Rui, GAO Zi-ang, ZHANG Tong, WANG Jia-xing. Lighting Damage Model of Silk Cultural Relics in Museum Collections Based on Infrared Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3930-3936. |
[11] |
SUN Wei-ji1, LIU Lang1, 2*, HOU Dong-zhuang3, QIU Hua-fu1, 2, TU Bing-bing4, XIN Jie1. Experimental Study on Physicochemical Properties and Hydration Activity of Modified Magnesium Slag[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3877-3884. |
[12] |
LI Xiao-dian1, TANG Nian1, ZHANG Man-jun1, SUN Dong-wei1, HE Shu-kai2, WANG Xian-zhong2, 3, ZENG Xiao-zhe2*, WANG Xing-hui2, LIU Xi-ya2. Infrared Spectral Characteristics and Mixing Ratio Detection Method of a New Environmentally Friendly Insulating Gas C5-PFK[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3794-3801. |
[13] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
[14] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
[15] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
|
|
|
|