Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/1731
Title: HPLC fingerprints combined with principal component analysis, hierarchical cluster analysis and linear discriminant analysis for the classification and differentiation of Peganum sp. indigenous to China
Author(s): Bligh, Annie Sim Wan 
Author(s): Cheng, X.-M.
Zhao, T.
Yang, T.
Wang, C.-H.
Wang, Z.-T.
Issue Date: 2010
Publisher: Wiley
Journal: Phytochemical Analysis 
Volume: 21
Issue: 3
Start page: 279
End page: 289
Abstract: 
Introduction – Seeds of wild Peganum harmala Linn., P. multisectum (Maxim) Bobr., P. nigellastrum Bunge and a probable indeterminate species, herein referred to as P. variety, are commonly used in Chinese medicine. These seeds cannot be differentiated based on morphology.

Objective – Seeds of P. harmala Linn., P. multisectum (Maxim) Bobr., P. nigellastrum Bunge and P. variety were collected in different provinces in China and their HPLC profiles were recorded for statistical analysis and pattern recognition.

Methodology – HPLC chromatograms of seed extracts were recorded under the same conditions. Individual HPLC chromatograms for each species were evaluated against the mean chromatogram for the same species generated using a similarity evaluation computer program. Data from chromatographic fingerprints were also processed using principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA).

Results – The Peganum sp. seed extracts had similar HPLC fingerprints but with some inter-specific differences. The chromatographic fingerprints combined with PCA, HCA and LDA could distinguish the seeds of the different species of Peganum investigated.

Conclusion – HPLC fingerprints can be used to authenticate and differentiate the seeds of three different species of genus Peganum indigenous to China. The results indicated that the unidentified P. variety might indeed be a new species or variety.
URI: https://repository.cihe.edu.hk/jspui/handle/cihe/1731
DOI: 10.1002/pca.1198
CIHE Affiliated Publication: No
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