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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.
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.