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[UPLC fingerprint and multi-components content determination of different processed products of Angelica sinensis]. | LitMetric

AI Article Synopsis

Article Abstract

Ten batches of Angelica sinensis from three producing areas( Tuoxiang,Minxian and Weiyuan of Gansu province) were selected as the research objects,and processed into raw A. sinensis,A. sinensis with alcohol,and A. sinensis with soil respectively through the standard processing methods. Ultra-high performance liquid chromatography( UPLC) was used to establish fingerprint for three processed products of A. sinensis,and determine the contents of 9 phenolic acids and phthalide compounds. The similarity was analyzed with Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine,which showed that the chromatographic peaks of the same processed samples of A. sinensis were basically similar,with all similarities greater than 0. 950. The difference between different processed products and their control spectra was not obvious,with all similarities also higher than 0. 950.On the basis of using principal component analysis( PCA) and OPLS-DA to seek the difference components between groups,the improved distance coefficient method can be used to effectively distinguish the three processed products of A. sinensis by fingerprint similarity. At the same time,the determination method of nine phenolic acids and phthalide in A. sinensis was established by UPLC,and the comparison between different processed products was carried out. The results showed that the content of various components was changed as compared with the raw A. sinensis. The contents of coniferyl ferulate and ligustilide in the A. sinensis with alcohol were increased significantly,and the content of coniferyl ferulate was obviously increased in A. sinensis with soil. The method established in this paper can effectively distinguish different processed products of A. sinensis and determine the content of the main components in them.

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http://dx.doi.org/10.19540/j.cnki.cjcmm.20190321.311DOI Listing

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