期刊名称:药物分析杂志 主管单位:中国科学技术协会 主办单位:中国药学会承办:中国食品药品检定研究院 主编:金少鸿 地址:北京天坛西里2号 邮政编码:100050 电话:010-67012819,67058427 电子邮箱:ywfx@nifdc.org.cn 国际标准刊号:ISSN 0254-1793 国内统一刊号:CN 11-2224/R 邮发代号:2-237
|
中药砂仁质量的化学模式识别研究
Quality assessment of the traditional Chinese medicine Amomum villosum by chemical pattern recognition techniques
作者:
王洋1, 申丽1, 江坤2,3,4, 殷果2,3,4, 王珏2,3,4, 鲁艺2, 项荣武5, 王铁杰1,2,3,4
作者(英文):WANG Yang1, SHEN Li1, JIANG Kun2,3,4, YIN Guo2,3,4, WANG Jue2,3,4, LU Yi2, XIANG Rong-wu5, WANG Tie-jie1,2,3,4
单位(英文):1. School of Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, China; 2. Shenzhen Institute for Drug Control, Shenzhen 518057, China; 3. Shenzhen Key Laboratory of Drug Quality Standard Research, Shenzhen 518057, China; 4. Shenzhen Engineering Laboratory of Exploitation and Utilization of Medicinal Material Resources in Lingnan, Shenzhen 518057, China; 5. School of Medical Devices, Shenyang Pharmaceutical University, Shenyang 110016, China
分类号:
出版年·卷·期(页码):2016,36 (10):0-0
DOI:
10.16155/j.0254-1793.2017.01.01
-----摘要:-------------------------------------------------------------------------------------------
目的:建立砂仁的化学模式识别方法,用于区分砂仁正品及其伪品,为寻找其代用品提供依据。方法:本文首先通过HPLC法获得64批样品的化学成分信息,建立共有模式并进行相似度计算,采用逐步判别分析方法提取特征峰,运用判别分析和主成分分析方法对砂仁及其伪品进行分类。结果:以提取的6个特征峰为变量,通过判别分析和主成分分析可将砂仁及其伪品进行准确的分类,判别准确率为100%,化学模式识别所得结果与性状鉴别结果一致。结论:本文所建立的模式识别方法能够准确有效地区分砂仁及其伪品,为砂仁的鉴别分类及质量控制提供依据。
-----英文摘要:---------------------------------------------------------------------------------------
Objective: To establish a method for identification of Amomum villosum and its adulterants by pattern recognition techniques. Methods: The high performance liquid chromatography(HPLC)fingerprints of 64 batches of samples were obtained and the chromatographic data were analyzed using similarity evaluation, hierarchical principal component analysis and discriminant analysis. The software" Similarity Evaluation System for Chromatographic Fingerprint of TCMs(Version 2012.1)" was employed to carry out the similarity analysis of the samples. The entire dataset was then divided into a training set and a test set. With supervised pattern recognition techniques, the discriminant analysis was performed by SPSS 21.0. Simca 11.5 Demo was employed to carry out the principal component analysis. Results: The results showed that the HPLC fingerprints of Amomum villosum was obviously different from its adulterants. Discriminant analysis and principal component analysis precisely predicted the whole test set. Conclusion: Fingerprint analysis assisted by pattern recognition techniques is a potential strategy for the authentication and differentiation of Amomum villosum and its adulterants. This research provided a basis for the classification and quality control of Amomum villosum.
-----参考文献:---------------------------------------------------------------------------------------
[1] 中国药典2010年版. 一部[S]. 2010:236 ChP 2010. Vol Ⅰ[S]. 2010:236 [2] 王铁杰,罗旭,王玺,等. 中药龙胆质量的化学模式识别[J]. 药学学报,1992,27(6):456 WANG TJ,LUO X,WANG X,et al. Quality assessment of the traditional Chinese medicine gentian by chemical pattern recognition[J]. Acta Pharm Sin,1992,27(6):456 [3] 安熙强,李宗主,沈连刚,等. 阳春砂仁的化学成分研究[J]. 天然药物研究与开发,2011,23(6):1021 AN XQ,LI ZZ,SHEN LG,et al. Chemical constituents of Amomum villosum Lour.[J]. Nat Prod Res Dev,2011,23(6):1021 [4] 黄月纯,魏刚. 阳春砂仁HPLC指纹图谱的研究[J]. 中草药, 2007,37(8):1251 HUANG YC,WEI G. Methodology for HPLC fingerprint analysis on fruits of Amomum villosum[J]. Chin Tradit Herb Drugs,2007,37(8):1251 [5] 张明发,沈雅琴. 砂仁临床药理作用的研究进展[J]. 抗感染药学,2013,10(1):8 ZHANG MF,SHEN YQ. Research advances in clinical pharmacological effects on Amomi Fructus[J]. Anti Infect Pharm, 2013,10(1):8 [6] WANG LB,WANG XB,KONG LY. Automatic authentication and distinction of Epimedium koreanum and Epimedium wushanense with HPLC fingerprint analysis assisted by pattern recognition techniques[J]. Biochem Syst Ecol,2012,40:138 [7] 刘江,陈兴福,邹元锋. 基于中药指纹图谱多维信息的化学模式识别研究进展[J]. 中国中药杂志,2012,37(8):1081 LIU J,CHEN XF,ZOU YF. Progress on chemical pattern recognition in traditional Chinese medicines by multidimensional information of metabolic fingerprinting analysis[J]. China J Chin Mater Med 2012,37(8):1081 [8] 苏碧茹,邓慧敏,马宏亮,等. HPLC-DAD-ELSD指纹图谱的化学模式识别用于黄芪质量评价[J]. 中国中药杂志,2013,38(19): 3319 SU BR,DENG HM,MA HL,et al. Quality evaluation of Astragali Radix through chemical pattern recognition of fingerprint by HPLCDAD-ELSD[J]. China J Chin Mater Med,2013,38(19): 3319 [9] 刘颖,王青,王放,等. 苦碟子注射液HPLC指纹图谱与化学模式识别分析[J]. 中国药学杂志,2013,48(24):2097 LIU Y,WANG Q,WANG F,et al. HPLC Fingerprint and chemical pattern recognization of Kudiezi injection[J]. Chin Pharm J,2013, 48(24):2097 [10] 吴忠. 中药物质基础整体特征的表达:中药色谱指纹特征的化学模式识别研究[D]. 广州:南方医科大学,2004 WU Z. Expression of Comprehensive Characteristics of Material Foundation of Traditional Chinese Medicine(TCM):Studies on Chemical Pattern Recognition of Chromatographic Fingerprint of TCM[D]. Guangzhou:Southern Medical University,2004
欢迎阅读《药物分析杂志》!您是该文第 1474位读者!
|