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Discrimination and feature selection of geographic origins of traditional Chinese medicine herbs with NIR spectroscopy
作者姓名:LIUShuhua  ZHANGXuegong  SUNSuqin
作者单位:[1]DepartmentofAutomation/MOEKeyLaboratoryofBioinformatics,TsinghuaUniversity,Beijing100084,China [2]Departmentofchemistry,TsinghuaUniversity,Beijing100084,China
摘    要:With the traditional Chinese medicine herbs angelicae dahuricae radix (ADR or Baizhi) and salviae miltiorrhizae radix (SMR or Danshen) as two examples, this work studies the automatic discrimination of the geographic origins of the herbs using near infrared (NIR) reflectance spectroscopy. Multi-class support vector machine (SVM) is utilized for the purpose, and recursive SVM is utilized to select the feature spectral segments that are decisive for the discrimination. With only 5 and 8 short spectral segments, discriminative accuracies of 92% are achieved on independent test sample sets. This work not only provides a prototype of accurate rapid discriminating systems for quality control of herbal medicines, but also opens new possibilities in studying subtle differences in the chemical compositions of herbs from different cultivation conditions and investigating their associations with the effectiveness of the herbs.

关 键 词:特征选择  特征识别  中草药  近红外线光谱学分析  识别模式  支持向量机
收稿时间:22 June 2004

Discrimination and feature selection of geographic origins of traditional Chinese medicine herbs with NIR spectroscopy
LIUShuhua ZHANGXuegong SUNSuqin.Discrimination and feature selection of geographic origins of traditional Chinese medicine herbs with NIR spectroscopy[J].Chinese Science Bulletin,2005,50(2):179-184.
Authors:Shuhua Liu  Xuegong Zhang  Suqin Sun
Affiliation:e-mail: zhangxg@tsinghua.edu.cn
Abstract:With the traditional Chinese medicine herbs angelicae dahuricae radix (ADR or Baizhi) and salviae miltiorrhizae radix (SMR or Danshen) as two examples, this work studies the automatic discrimination of the geographic origins of the herbs using near infrared (NIR) reflectance spectroscopy. Multi-class support vector machine (SVM) is utilized for the purpose, and recursive SVM is utilized to select the feature spectral segments that are decisive for the discrimination. With only 5 and 8 short spectral segments, discriminative accuracies of 92% are achieved on independ- ent test sample sets. This work not only provides a prototype of accurate rapid discriminating systems for quality control of herbal medicines, but also opens new possibilities in studying subtle differences in the chemical compositions of herbs from different cultivation conditions and investigating their associations with the effectiveness of the herbs.
Keywords:traditional Chinese medicine  discrimination of geo-  graphic origin  near infrared  pattern recognition  feature selection    support vector machine  
本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录!
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