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[Study on LC-MS fingerprint for quality assessment of Aristolochia manshuriensis with chemical pattern recognition]
Xia-Lei Fan1, Yi-Bing Ding, A Ji-Ye
1China Pharmaceutical University, Nanjing 210009, China.
Objective:
To analyze LC-MS fingerprints of Aristolochia manshuriensis for quality assessment with two different chemical pattern recognition models.
Method:
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.
Result:
Two methods had good consistency, while they reflected the inherent sample information from different perspectives, respectively.
Conclusion:
Modern equipment analysis technology and multivariable chemical pattern recognition would be an efficient way for quality control and variety identification of A. manshuriensis.
