Pretreatments of chromatographic fingerprints for quality control of herbal medicines.

Pretreatments of chromatographic fingerprints are important for quality control of herbal medicines and they include data correction and data transformation. The data correction can reduce the variations of experimental procedures, and data transformation can put different weights on the different parts of the fingerprints. In this paper, a new target peak alignment (TPA) procedure has been proposed to correct the retention time shifts, multiplicative scattering correction (MSC) has been introduced for response correction. Then the similarity of the fingerprints with mean and median fingerprints is used to evaluate the quality of herbal medicines (HMs). Furthermore, different data transformation methods with kernel principal component analysis (PCA) have been applied to the data and their effects were discussed. The proposed approaches have been demonstrated by the essential oils data set of a herbal medicine, named Houttuynia cordata (HC), containing samples from different geographic origins. The experimental results indicate that the proposed approaches may be helpful in the quality control of herbal medicines by fingerprints.

[1]  H. R. Keller,et al.  Heuristic evolving latent projections: resolving two-way multicomponent data. 2. Detection and resolution of minor constituents , 1992 .

[2]  S. D. Jong,et al.  The kernel PCA algorithms for wide data. Part I: Theory and algorithms , 1997 .

[3]  D L Massart,et al.  Chemometric treatment of vanillin fingerprint chromatograms. Effect of different signal alignments on principal component analysis plots. , 2006, Journal of chromatography. A.

[4]  Yi-Zeng Liang,et al.  Spectral correlative chromatography and its application to analysis of chromatographic fingerprints of herbal medicines. , 2004, Journal of separation science.

[5]  Paul Geladi,et al.  Principal Component Analysis , 1987, Comprehensive Chemometrics.

[6]  Gene H. Golub,et al.  Matrix computations , 1983 .

[7]  B. Walczak,et al.  Fuzzy warping of chromatograms , 2005 .

[8]  Yi-Zeng Liang,et al.  Correction of retention time shifts for chromatographic fingerprints of herbal medicines. , 2004, Journal of chromatography. A.

[9]  Yi-Zeng Liang,et al.  Subwindow factor analysis , 1999 .

[10]  Edmund R. Malinowski,et al.  Window factor analysis: Theoretical derivation and application to flow injection analysis data , 1992 .

[11]  J. Carstensen,et al.  Aligning of single and multiple wavelength chromatographic profiles for chemometric data analysis using correlation optimised warping , 1998 .

[12]  Yizeng Liang,et al.  Preprocessing of analytical profiles in the presence of homoscedastic or heteroscedastic noise , 1994 .

[13]  D. Massart,et al.  A comparison of two algorithms for warping of analytical signals , 2002 .

[14]  Yizeng Liang,et al.  Heuristic evolving latent projections: resolving two-way multicomponent data. 1. Selectivity, latent-projective graph, datascope, local rank, and unique resolution , 1992 .

[15]  Reduction of error propagation due to normalization: Effect of error propagation and closure on spurious correlations , 1995 .

[16]  R. Aruga Multivariate classification of constrained data: problems and alternatives , 2004 .

[17]  K. Sjoedin Minimizing effects of closure on analytical data , 1984 .

[18]  P. Eilers Parametric time warping. , 2004, Analytical chemistry.

[19]  Jian-Hui Jiang,et al.  Evolving window orthogonal projections method for two-way data resolution , 1999 .

[20]  D. Massart,et al.  Orthogonal projection approach applied to peak purity assessment. , 1996, Analytical chemistry.

[21]  Yi-Zeng Liang,et al.  Quality control of herbal medicines. , 2004, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[22]  P. A. Taylor,et al.  Synchronization of batch trajectories using dynamic time warping , 1998 .

[23]  Edmund R. Malinowski,et al.  Factor Analysis in Chemistry , 1980 .

[24]  S. Mjøs Spectral transformations for deconvolution methods applied on gas chromatography–mass spectrometry data , 2003 .

[25]  Desire L. Massart,et al.  Effect of different preprocessing methods for principal component analysis applied to the composition of mixtures: Detection of impurities in HPLC—DAD , 1994 .

[26]  Yizeng Liang,et al.  Identification of essential components of Houttuynia cordata by gas chromatography/mass spectrometry and the integrated chemometric approach. , 2005, Talanta.

[27]  Rolf Danielsson,et al.  Alignment of chromatographic profiles for principal component analysis: a prerequisite for fingerprinting methods , 1994 .

[28]  R. Manne,et al.  Resolution of two-way data from hyphenated chromatography by means of elementary matrix transformations , 2000 .

[29]  Peter D. Wentzell,et al.  Window target-testing factor analysis: theory and application to the chromatographic analysis of complex mixtures with multiwavelength fluorescence detection , 1999 .

[30]  Yi-Zeng Liang,et al.  Quality evaluation of fingerprints of herbal medicine with chromatographic data , 2004 .