title: Spectral correlative chromatography and its application to analysis of chromatographic fingerprints of herbal medicines.
abstract: A signal-processing method known as spectral correlative chromatography (SCC) for two-dimensional data obtained from hyphenated chromatography is developed and applied to chemical chromatographic fingerprint data sets of herbal medicine under specific experimental conditions. The method can judge the presence or absence of a spectral correlative peak among the spectrochromatograms. A local least squares regression model (LLS) is constructed in a piecewise manner to correct the shifts of retention time of some peaks of interest in the chromatograms of various test samples. The results compare favorably with those obtained by a two-point calibrated algorithm. It is shown that performing SCC and LLS on the piecewise clusters of various chromatographic fingerprints is more helpful in practice in revealing their common nature and for characterizing the chemical constituents. This approach holds great potential for facilitating quality control of herbal medicines.
authors.affiliation: College of Chemistry and Chemical Engineering, Research Center of Modernization of Chinese Herbal Medicines, Central South University, Changsha 410083, P.R. China.
authors.forename: Bo-Yan
authors.initials: BY
authors.lastname: Li
authors.forename: Yun
authors.initials: Y
authors.lastname: Hu
authors.forename: Yi-Zeng
authors.initials: YZ
authors.lastname: Liang
authors.forename: Lan-Fang
authors.initials: LF
authors.lastname: Huang
authors.forename: Cheng-Jian
authors.initials: CJ
authors.lastname: Xu
authors.forename: Pei-Shan
authors.initials: PS
authors.lastname: Xie
mesh_terms: D002845:Chromatography / Q000379:methods; D002851:Chromatography, High Pressure Liquid / Q000379:methods; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods; D016018:Least-Squares Analysis; D028321:Plant Preparations / Q000737:chemistry*; D012997:Solvents
chemical_list: D028321:Plant Preparations; D012997:Solvents