中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Reliable origin identification of Scutellaria baicalensis based on terahertz time-domain spectroscopy and pattern recognition

文献类型:期刊论文

作者Liang, Jie1; Guo, Qijia1; Chang, Tianying1,2; Li, Ke2; Cui, Hong-Liang1,3
刊名OPTIK
出版日期2018
卷号174页码:7-14
关键词Terahertz Time-domain Spectroscopy (Thz-tds) Principal Component Analysis Support Vector Machines Particle Swarm Optimization Scutellaria Baicalensis
ISSN号0030-4026
DOI10.1016/j.ijleo.2018.08.050
英文摘要

An effective approach for identification of the origin of Scutellaria baicalensis, an essential member of the family of Chinese herbal medicine and known to be an effective anti-inflammatory, is proposed based on terahertz time-domain spectroscopy (THz-TDS) and pattern recognition. Terahertz absorption spectra of Scutellaria baicalensis collected from its main growth areas in China, including Inner Mongolia, Shanxi and Shaanxi are investigated using the proposed method, in the frequency range from 0.2 to 1.7 THz. To reduce the dimensionality of the original spectral data and extract useful features of the data, principal component analysis is employed. The matrix of the selected principal component scores is fed into a classification model established by support vector machines. We use the particle swarm optimization to optimize the parameters of the classification model to achieve an identification rate of 95.56% for the samples, demonstrating that terahertz time-domain spectroscopy combined with particle swarm-support vector machines approach can be efficiently utilized for automatic identification of the origin of Scutellaria baicalensis.

资助项目Ministry of Science and Technology of the Peoples Republic of China[2015CB755401] ; National Natural Science Foundation of China[61705120] ; Innovation Program of Shandong Academy of Sciences ; Department of Science & Technology of Shandong Province[2016GGX101010] ; Innovation Program of Shandong Academy of Sciences ; Department of Science & Technology of Shandong Province[2017GGX10108] ; Youth Science Funds of Shandong Academy of Sciences[2017QN0015]
WOS研究方向Optics
语种英语
WOS记录号WOS:000447247700002
出版者ELSEVIER GMBH, URBAN & FISCHER VERLAG
源URL[http://119.78.100.138/handle/2HOD01W0/6831]  
专题中国科学院重庆绿色智能技术研究院
作者单位1.Jilin Univ, Coll Instrumentat & Elect Engn, Changchun 130061, Jilin, Peoples R China
2.Qilu Univ Technol, Shandong Acad Sci, Inst Automat, Jinan 250014, Shandong, Peoples R China
3.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
推荐引用方式
GB/T 7714
Liang, Jie,Guo, Qijia,Chang, Tianying,et al. Reliable origin identification of Scutellaria baicalensis based on terahertz time-domain spectroscopy and pattern recognition[J]. OPTIK,2018,174:7-14.
APA Liang, Jie,Guo, Qijia,Chang, Tianying,Li, Ke,&Cui, Hong-Liang.(2018).Reliable origin identification of Scutellaria baicalensis based on terahertz time-domain spectroscopy and pattern recognition.OPTIK,174,7-14.
MLA Liang, Jie,et al."Reliable origin identification of Scutellaria baicalensis based on terahertz time-domain spectroscopy and pattern recognition".OPTIK 174(2018):7-14.

入库方式: OAI收割

来源:重庆绿色智能技术研究院

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