title: Discriminant analysis of Chinese patent medicines based on near-infrared spectroscopy and principal component discriminant transformation.
abstract: Principal component discriminant transformation was applied for discrimination of different Chinese patent medicines based on near-infrared (NIR) spectroscopy. In the method, an optimal set of orthogonal discriminant vectors, which highlight the differences between the NIR spectra of different classes, is designed by maximizing Fisher's discriminant function. Therefore, a model for discriminating a class and the others can be obtained with the tiny differences between the NIR spectra of different classes. Furthermore, because NIR spectra contain a large amount of redundant information, principal component analysis (PCA) is employed to reduce the dimension. On the other hand, continuous wavelet transform (CWT) is taken as the pretreatment method to remove the variant background. For identifying the method, different medicines and the same medicine from different manufactures were studied. The results show that all the models can provide 100% discrimination.
authors.affiliation: Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300071, China.
authors.forename: Zhihong
authors.initials: Z
authors.lastname: Xu
authors.affiliation: Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300071, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300071, China.
authors.forename: Xiaoyong
authors.initials: X
authors.lastname: Li
authors.affiliation: Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300071, China.
authors.forename: Wensheng
authors.initials: W
authors.lastname: Cai
authors.affiliation: Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300071, China. Electronic address: xshao@nankai.edu.cn.
authors.forename: Xueguang
authors.initials: X
authors.lastname: Shao
mesh_terms: D002138:Calibration; D016002:Discriminant Analysis; D004365:Drugs, Chinese Herbal / Q000032:analysis*; D004366:Nonprescription Drugs / Q000032:analysis*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D019265:Spectroscopy, Near-Infrared
chemical_list: D004365:Drugs, Chinese Herbal; D004366:Nonprescription Drugs
keywords: Chinese patent medicine; Discrimination; Near-infrared spectroscopy; Principal component analysis; Principal component discriminant transformation