title: Rapid identification of the quality decoction pieces by partial least squares -based pattern recognition: grade classification of the decoction pieces of Saposhnikovia divaricata.
abstract: Herbal medicines are commonly used in many countries after they undergo processing. Quality decoction pieces are a guarantee of the efficacy and safety of the herbal medical products. Here, a strategy based on chemical analysis combined with chemometric techniques was proposed for the classification and prediction of the different grades of the decoction pieces. Considering the necessity for a shared and simple method for the grade classification for the public, in this paper, the characterization of the chemical constituents was determined by utilizing high-performance liquid chromatography (HPLC)/diode array detection. HPLC was first established for the characterization of the chemical constituents of the different grade decoction pieces. Furthermore, a simultaneous quantification of several of the marker compounds in these decoction pieces was obtained. Finally, a partial least squares-based pattern recognition method was utilized to obtain a predictive model for the grade classification of the decoction pieces. Saposhnikovia divaricata (Turcz.) Schischk was used as a case study. The partial least squares -based pattern recognition for the grade classification of the decoction pieces of S. divaricata demonstrated good sensitivity, specificity and prediction performance, which may efficiently validate the identification results of appearance assessment. The proposed strategy is expected to provide a new insight for the grade classification and quality control of the decoction pieces. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Li
authors.initials: L
authors.lastname: Li
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Yongqing
authors.initials: Y
authors.lastname: Xiao
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Jiaqi
authors.initials: J
authors.lastname: Yao
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Pengyuan
authors.initials: P
authors.lastname: Li
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Liang
authors.initials: L
authors.lastname: Chen
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Dingrong
authors.initials: D
authors.lastname: Yu
authors.affiliation: Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiao Lane, Dongzhimennei, Beijing, 100700, People's Republic of China.
authors.forename: Yinlian
authors.initials: Y
authors.lastname: Ma
mesh_terms: D019661:Apiaceae / Q000737:chemistry*; D002138:Calibration; D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D016018:Least-Squares Analysis; D057230:Limit of Detection; D012015:Reference Standards; D015203:Reproducibility of Results; D013056:Spectrophotometry, Ultraviolet
keywords: HPLC-DAD; PLS-based pattern recognition; Saposhnikovia divaricata; grade classification; herbal medicines; quality decoction pieces