Detailed Information

Cited 0 time in webofscience Cited 2 time in scopus
Metadata Downloads

Classficiation of bupleuri radix according to geographical origins using near infrared spectroscopy (NIRS) combined with supervised pattern recognitionopen access

Authors
Lee D.Y.Kang K.B.Kim J.Kim H.J.Sung S.H.
Issue Date
Sep-2018
Publisher
Korean Society of Pharmacognosy
Keywords
Bupleuri Radix; Geographical classification; Near infrared spectroscopy; Supervised pattern recognition
Citation
Natural Product Sciences, v.24, no.3, pp 164 - 170
Pages
7
Journal Title
Natural Product Sciences
Volume
24
Number
3
Start Page
164
End Page
170
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/4288
DOI
10.20307/nps.2018.24.3.164
ISSN
1226-3907
Abstract
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. © 2018, Korean Society of Pharmacognosy. All rights reserved.
Files in This Item
Appears in
Collections
약학대학 > 약학부 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kang, Kyo Bin photo

Kang, Kyo Bin
약학대학 (약학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE