[Study on LC-MS fingerprint for quality assessment of Aristolochia manshuriensis with chemical pattern recognition].
OBJECTIVE
To analyze LC-MS fingerprints of Aristolochia manshuriensis for quality assessment with two different chemical pattern recognition models.


METHODS
LC-MS fingerprints of A. manshuriensis were established from 24 batches of samples from different habitats. SIMCA and Clustering analysis were used to compare the parameters of the 29 common peaks.


RESULTS
Two methods had good consistency, while they reflected the inherent sample information from different perspectives, respectively.


CONCLUSIONS
Modern equipment analysis technology and multivariable chemical pattern recognition would be an efficient way for quality control and variety identification of A. manshuriensis.
Fan
Xia-Lei
XL
China Pharmaceutical University, Nanjing 210009, China.
Ding
Yi-Bing
YB
Ji-Ye
A
A
Zhao
Xun
X
Liu
Wen-Ying
WY
D030022:Aristolochia / Q000737:chemistry* / Q000145:classification; D002853:Chromatography, Liquid; D016000:Cluster Analysis; D004365:Drugs, Chinese Herbal / Q000737:chemistry; D013058:Mass Spectrometry; D010802:Phylogeny; D011786:Quality Control
D004365:Drugs, Chinese Herbal