Natural Product Sciences

  • 제24권3호
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  • Pages.164-170
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  • 2018
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  • 1226-3907(pISSN)
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  • 2288-9027(eISSN)
한국생약학회 (The Korean Society of Pharmacognosy)
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Classficiation of Bupleuri Radix according to Geographical Origins using Near Infrared Spectroscopy (NIRS) Combined with Supervised Pattern Recognition

  • Lee, Dong Young (College of Pharmacy and Research Institute of Pharmaceutical Science, Seoul National University) ;
  • Kang, Kyo Bin (College of Pharmacy, Sookmyung Women's University) ;
  • Kim, Jina (College of Pharmacy and Research Institute of Pharmaceutical Science, Seoul National University) ;
  • Kim, Hyo Jin (College of Pharmacy, Dongduk Women's University) ;
  • Sung, Sang Hyun (College of Pharmacy and Research Institute of Pharmaceutical Science, Seoul National University)
  • 투고 : 2017.12.18
  • 심사 : 2018.04.04
  • 발행 : 2018.09.30
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초록

Rapid geographical classification of Bupleuri Radix is important in quality control. In this study, near infrared spectroscopy (NIRS) combined with supervised pattern recognition was attempted to classify Bupleuri Radix according to geographical origins. Three supervised pattern recognitions methods, partial least square discriminant analysis (PLS-DA), quadratic discriminant analysis (QDA) and radial basis function support vector machine (RBF-SVM), were performed to establish the classification models. The QDA and RBF-SVM models were performed based on principal component analysis (PCA). The number of principal components (PCs) was optimized by cross-validation in the model. The results showed that the performance of the QDA model is the optimum among the three models. The optimized QDA model was obtained when 7 PCs were used; the classification rates of the QDA model in the training and test sets are 97.8% and 95.2% respectively. The overall results showed that NIRS combined with supervised pattern recognition could be applied to classify Bupleuri Radix according to geographical origin.

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