基于指纹图谱及化学模式识别方法优选蜜枇杷叶药材产地
Fingerprinting and chemical pattern recognition methods for preferential selection of the habitat of honeyed Eriobotryae Folium
张新博 1汪芸兰 1雷璇 1张颖 1宋逍2
作者信息
- 1. 陕西中医药大学,咸阳 712046
- 2. 陕西中医药大学,咸阳 712046;中药制药与新药开发教育部工程研究中心,北京 100029
- 折叠
摘要
目的:基于高效液相色谱指纹图谱和化学模式识别方法,评价不同产地蜜枇杷叶的质量,优选出蜜枇杷叶的最佳产地.方法:采用AcclaimTM 120A C18(250 mm × 4.6 mm,5 μm)色谱柱进行检测,流动相为0.2％磷酸水溶液(A)-乙腈(B),梯度洗脱(0～5 min,5％B;5～6 min,5％B→10％B;6～20 min,10％B;20～50 min,10％B→25％B;50～60 min,25％B),体积流量 1.0 mL·min1,检测波长 327 nm,柱温 30 ℃,进样量10 μL.建立30批不同产地蜜枇杷叶的指纹图谱,采用指纹图谱结合化学模式识别的方法对不同产地蜜枇杷叶进行综合分析,对不同产地蜜枇杷叶进行聚类分析(cluster analysis.CA)、主成分分析(principal component analysis.PCA)及综合评分,采用正交偏最小二乘判别分析(orthogonal partial least squares-dis-criminant analysis,OPLS-DA)筛选出不同产地蜜枇杷叶的差异标志物,根据综合评分优选出蜜枇杷叶的产地.结果:建立了 30批蜜枇杷叶的指纹图谱,标定出12个共有峰,根据对照品指认出4个色谱峰,确定为新绿原酸、绿原酸、隐绿原酸、金丝桃苷;CA将30批蜜枇杷叶样品分为6类;经PCA提取出3个主成分,累计方差贡献率为84.315％;根据OPLS-DA筛选得到6个差异标志物,其中2个确定为金丝桃苷、绿原酸;根据综合评分筛选出蜜枇杷叶的较优产地为四川、广西、广东、陕西.结论:指纹图谱及含量测定过程中的精密度、重复性和稳定性均良好.指纹图谱与化学模式识别相结合方法可全面综合评价蜜枇杷叶质量,此方法稳定、可靠,可为蜜枇杷叶的产地研究提供有效的参考依据.
Abstract
Objective:To evaluate the quality of honeyed Eriobotryae Folium from different habitats and to select the best habitat of honeyed Eriobotryae Folium preferentially based on high performance liquid chromatography fin-gerprinting and chemical pattern recognition methods.Methods:The detection was performed on an AcclaimTM 120A C18(250 mm ×4.6 mm,5 μm)column with the mobile phase of 0.2％aqueous phosphoric acid(A)-acetonitrile(B)in gradient elution(0-5 min,5％B;5-6 min,5％B→10％B;6-20 min,10％B;20-50 min,10％B→25％B;50-60 min,25％B).The volume flow rate was 1.0 mL·min-1,the detection wavelength was 327 nm,the column temperature was 30 ℃,and the injection volume was 10 μL.The fingerprint profiles of 30 batches of honeyed Eriobotryae Folium from different habitats were established,and the fingerprint profiles combined with chemical pattern recognition were used to conduct comprehensive analysis of honeyed Erio-botryae Folium from different habitats.And cluster analysis(CA),principal component analysis(PCA)and com-prehensive scoring were performed on honeyed Eriobotryae Folium from different habitats.Orthogonal partial least squares-discriminant analysis(OPLS-DA)was used to screen out the differential markers of honeyed Eriobot-ryae Folium from different habitats,and the habitats of honeyed Eriobotryae Folium were selected based on the comprehensive scoring.Results:The fingerprint profiles of 30 batches of honeyed Eriobotryae Folium were estab-lished.Twelve common peaks were identified,and 4 peaks were identified as neochlorogenic acid,chlorogenic acid,cryptochlorogenic acid and auriculoside according to the control finger.CA divided the 30 batches of Hon-eyed Eriobotryae Folium samples into 6 categories.By PCA,3 principal components were extracted,with a cumu-lative variance contribution of 84.315％.Six differential markers were obtained according to OPLS-DA,two of which were identified as chrysoside and chlorogenic acid.The better habitats of honeyed Eriobotryae Folium were screened as Sichuan,Guangxi,Guangdong and Shaanxi according to the comprehensive score.Conclusion:Good precision,repeatability and stability results are obtained for fingerprinting and content determination.The combi-nation of fingerprinting and chemical pattern recognition can comprehensively evaluate the quality of honeyed Erio-botryae Folium,and this method is stable and reliable,which can provide an effective reference basis for the habi-tat study of honeyed Eriobotryae Folium.
关键词
蜜枇杷叶/指纹图谱/化学模式识别/主成分分析/新绿原酸/绿原酸/隐绿原酸/金丝桃苷Key words
honeyed Eriobotryae Folium/Fingerprinting/chemical pattern recognition/principal component analy-sis/neochlorogenic acid/chlorogenic acid/cryptochlorogenic acid/auriculoside引用本文复制引用
基金项目
陕西省教育厅项目(21JC011)
陕西省中医药管理局(2021-04-ZZ-007)
国家重点研发计划(2019YFC1711204)
出版年
2024
NETL
NSTL
万方数据