Quality assessment of cortex cinnamomi by HPLC chemical fingerprint, principle component analysis and cluster analysis.
HPLC fingerprint analysis, principle component analysis (PCA), and cluster analysis were introduced for quality assessment of Cortex cinnamomi (CC). The fingerprint of CC was developed and validated by analyzing 30 samples of CC from different species and geographic locations. Seventeen chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression of the HPLC fingerprints. The correlation coefficients of similarity in chromatograms were higher than 0.95 for the same species while much lower than 0.6 for different species. Besides, two principal components (PCs) have been extracted by PCA. PC1 separated Cinnamomum cassia from other species, capturing 56.75% of variance while PC2 contributed for their further separation, capturing 19.08% variance. The scores of the samples showed that the samples could be clustered reasonably into different groups corresponding to different species and different regions. The scores and loading plots together revealed different chemical properties of each group clearly. The cluster analysis confirmed the results of PCA analysis. Therefore, HPLC fingerprint in combination with chemometric techniques provide a very flexible and reliable method for quality assessment of traditional Chinese medicines.
Yang
Jie
J
Department of Chinese Materia Medica Analysis, China Pharmaceutical University, Nanjing, China.
Chen
Li-Hong
LH
Zhang
Qin
Q
Lai
Mao-Xiang
MX
Wang
Qiang
Q
D002851:Chromatography, High Pressure Liquid / Q000379:methods; D032904:Cinnamomum aromaticum / Q000737:chemistry*; D016000:Cluster Analysis; D004365:Drugs, Chinese Herbal / Q000737:chemistry*; D024301:Plant Bark / Q000737:chemistry; D028321:Plant Preparations / Q000737:chemistry*; D025341:Principal Component Analysis; D011786:Quality Control; D013045:Species Specificity
D004365:Drugs, Chinese Herbal; D028321:Plant Preparations