title: [Study on LC-MS fingerprint for quality assessment of Aristolochia manshuriensis with chemical pattern recognition].
abstract: 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.
authors.affiliation: China Pharmaceutical University, Nanjing 210009, China.
authors.forename: Xia-Lei
authors.initials: XL
authors.lastname: Fan
authors.forename: Yi-Bing
authors.initials: YB
authors.lastname: Ding
authors.forename: A
authors.initials: A
authors.lastname: Ji-Ye
authors.forename: Xun
authors.initials: X
authors.lastname: Zhao
authors.forename: Wen-Ying
authors.initials: WY
authors.lastname: Liu
mesh_terms: 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
chemical_list: D004365:Drugs, Chinese Herbal