通过高效液相色谱法结合多元化学计量学分析,建立化学指纹图谱并确定积雪草的主要活性成分

IF 1.3 Q4 CHEMISTRY, ANALYTICAL
Duan Yu, Zhongjing Guo, Zhimin Zhao, Yang Depo, xinjun Xu
{"title":"通过高效液相色谱法结合多元化学计量学分析,建立化学指纹图谱并确定积雪草的主要活性成分","authors":"Duan Yu, Zhongjing Guo, Zhimin Zhao, Yang Depo, xinjun Xu","doi":"10.1002/sscp.202400021","DOIUrl":null,"url":null,"abstract":"In this paper, a simple and efficient high‐performance liquid chromatography method was established to analyze the chemical composition fingerprint of Centellae Herba (CHA) and determine five triterpenoid active components in CHA, namely, asiaticoside B (AB), madecassoside, asiaticoside, madecasic acid, and asiaticoic acid. The separation of the compounds was carried out on an XD‐C18 column (250 mm × 4.6 mm, 5 µm), the wavelength of the ultraviolet detector was set to 205 nm, and the mobile phase was composed of acetonitrile −0.05% phosphoric acid, 2 mmol/L β‐cyclodextrin aqueous solution, and gradient elution at the flow rate of 1.0 mL/min. A general chromatographic fingerprint consisting of 20 characteristic peaks of 18 batches of CHA samples was established, and the samples were classified and evaluated by similarity analysis, hierarchical cluster analysis, and principal component analysis combined with multivariate econometric analysis. In quantitative analysis, all calibration curves showed good linear regression in the test range (r > 0.999), the average recovery was 96.12%–104.63%, and the relative standard deviations of repeatability and stability were less than 2.00%. The results show that the method is accurate and effective and can be used for the comprehensive quality control of CHA.","PeriodicalId":21639,"journal":{"name":"SEPARATION SCIENCE PLUS","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Establishment of chemical fingerprint and determination of main active ingredients in Centellae Herba by HPLC combined with multivariate chemometrics analysis\",\"authors\":\"Duan Yu, Zhongjing Guo, Zhimin Zhao, Yang Depo, xinjun Xu\",\"doi\":\"10.1002/sscp.202400021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a simple and efficient high‐performance liquid chromatography method was established to analyze the chemical composition fingerprint of Centellae Herba (CHA) and determine five triterpenoid active components in CHA, namely, asiaticoside B (AB), madecassoside, asiaticoside, madecasic acid, and asiaticoic acid. The separation of the compounds was carried out on an XD‐C18 column (250 mm × 4.6 mm, 5 µm), the wavelength of the ultraviolet detector was set to 205 nm, and the mobile phase was composed of acetonitrile −0.05% phosphoric acid, 2 mmol/L β‐cyclodextrin aqueous solution, and gradient elution at the flow rate of 1.0 mL/min. A general chromatographic fingerprint consisting of 20 characteristic peaks of 18 batches of CHA samples was established, and the samples were classified and evaluated by similarity analysis, hierarchical cluster analysis, and principal component analysis combined with multivariate econometric analysis. In quantitative analysis, all calibration curves showed good linear regression in the test range (r > 0.999), the average recovery was 96.12%–104.63%, and the relative standard deviations of repeatability and stability were less than 2.00%. The results show that the method is accurate and effective and can be used for the comprehensive quality control of CHA.\",\"PeriodicalId\":21639,\"journal\":{\"name\":\"SEPARATION SCIENCE PLUS\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SEPARATION SCIENCE PLUS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/sscp.202400021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SEPARATION SCIENCE PLUS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/sscp.202400021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

摘要

本文建立了一种简便高效的高效液相色谱法,用于分析积雪草的化学成分指纹图谱,并测定了积雪草中的5种三萜类活性成分,即积雪草苷B(AB)、积雪草苷、积雪草苷、积雪草酸和积雪草酸。采用XD-C18色谱柱(250 mm × 4.6 mm, 5 µm)进行分离,紫外检测器波长为205 nm,流动相为乙腈-0.05%磷酸、2 mmol/Lβ-环糊精水溶液,梯度洗脱,流速为1.0 mL/min。建立了由 18 批 CHA 样品的 20 个特征峰组成的通用色谱指纹图谱,并通过相似性分析、层次聚类分析和主成分分析结合多元计量经济学分析对样品进行了分类和评价。定量分析结果表明,所有定标曲线在检测范围内线性回归良好(r>0.999),平均回收率为96.12%~104.63%,重复性和稳定性的相对标准偏差均小于2.00%。结果表明该方法准确、有效,可用于CHA的全面质量控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishment of chemical fingerprint and determination of main active ingredients in Centellae Herba by HPLC combined with multivariate chemometrics analysis
In this paper, a simple and efficient high‐performance liquid chromatography method was established to analyze the chemical composition fingerprint of Centellae Herba (CHA) and determine five triterpenoid active components in CHA, namely, asiaticoside B (AB), madecassoside, asiaticoside, madecasic acid, and asiaticoic acid. The separation of the compounds was carried out on an XD‐C18 column (250 mm × 4.6 mm, 5 µm), the wavelength of the ultraviolet detector was set to 205 nm, and the mobile phase was composed of acetonitrile −0.05% phosphoric acid, 2 mmol/L β‐cyclodextrin aqueous solution, and gradient elution at the flow rate of 1.0 mL/min. A general chromatographic fingerprint consisting of 20 characteristic peaks of 18 batches of CHA samples was established, and the samples were classified and evaluated by similarity analysis, hierarchical cluster analysis, and principal component analysis combined with multivariate econometric analysis. In quantitative analysis, all calibration curves showed good linear regression in the test range (r > 0.999), the average recovery was 96.12%–104.63%, and the relative standard deviations of repeatability and stability were less than 2.00%. The results show that the method is accurate and effective and can be used for the comprehensive quality control of CHA.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
SEPARATION SCIENCE PLUS
SEPARATION SCIENCE PLUS CHEMISTRY, ANALYTICAL-
CiteScore
1.90
自引率
9.10%
发文量
111
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信