基于UPLC指纹图谱和化学模式识别的不同产地金银花药材质量评价OA
Quality Evaluation of Lonicera Japonica Thunb.from Different Origins Based on UPLC Fingerprint and Chemical Pattern Recognition
目的:建立不同产地金银花药材超高效液相色谱(UPLC)指纹图谱,并进行化学模式识别与相关性分析,为金银花药材的质量评价提供参考.方法:采用超高效液相色谱仪,Thermo Accucore TM C18色谱柱(100.0 mm×4.6 mm,2.6 μm),流动相为乙腈-0.1%磷酸水溶液,体积流量为0.3 mL/min,梯度洗脱,分段检测波长324 nm(0～14 min)、238 nm(14～20 min)、354 nm(20～29 min)、324 nm(29～55 min),柱温30℃,进样量2 μL;通过对照品比对,对特征峰进行鉴定,采用《中药色谱指纹图谱相似度评价系统(2012版)》软件构建指纹图谱,进行相似度评价.通过聚类热图分析、主成分分析(PCA)、正交偏最小二乘法-判别分析(OPLS-DA)比较不同产地金银花药材的质量差异.结果:建立了20批不同产地金银花指纹图谱,标定特征峰16个,并指认10个化学成分,分别为新绿原酸(1号峰)、绿原酸(2号峰)、隐绿原酸(3号峰)、马钱苷(4号峰)、当药苷(5号峰)、断氧马钱子苷(8号峰)、木犀草苷(12号峰)、异绿原酸B(13号峰)、异绿原酸A(14号峰)、异绿原酸C(16号峰).相似度评价结果显示,20批金银花指纹图谱相似度为0.898～1.000,除S8相似度为0.898以外,其余金银花相似度均>0.974.聚类热图分析、PCA和OPLS-DA分析将20批金银花分为3组,筛选出4个差异性标志物,根据变量投影重要度(VIP)值排序,分别为峰10>异绿原酸A>绿原酸>异绿原酸C.Pearson相关分析显示,产地与分组显著正相关,相关系数最大,其次依次为品种、加工方式.结论:产地环境和品种是影响金银花药材质量的重要因素,UPLC指纹图谱与多成分化学模式识别相结合分析可有效评价不同产地金银花药材的质量差异性.
Objective:To establish ultra-performance liquid chromatography(UPLC)fingerprints for Lonicera Japonica Thunb.from different origins,and to conduct chemical pattern recognition and correlation analysis,in order to provide a reference for quality evaluation of Lonicera Japonica Thunb.Methods:An ultra-performance liquid chromatography(UPLC)system was employed with a Thermo Accucore TM C18 column(100.0 mm×4.6 mm,2.6 μm).The mobile phase consisted of acetonitrile-0.1%phosphoric acid aqueous solution at a flow rate of 0.3 mL/min,with gradient elution.Detection wavelengths were segmented as follows:324 nm(0-14 min),238 nm(14-20 min),354 nm(20-29 min),and 324 nm(29-55 min).Column temperature was maintained at 30℃,with an injection volume of 2 μL.Characteristic peaks were identified through reference standard comparison.UPLC fingerprints were constructed using the Chinese Herbal Medicine Chromatographic Fingerprint Similarity Evaluation System(2012 Edition)software for similarity assessment.Quality variations among Lonicera Japonica Thunb.from different origins were compared via cluster heatmap analysis,principal component analysis(PCA),and orthogonal partial least-squares discrimination analysis(OPLS-DA).Results UPLC fingerprints were established for 20 batches of Lonicera Japonica Thunb.from different origins.A total of 16 characteristic peaks were calibrated,and 10 chemical components were identified,namely neochlorogenic acid(peak 1),chlorogenic acid(peak 2),cryptoclorogenic acid(peak 3),loganin(peak 4),sweroside(peak 5),secoxyloganin(peak 8),luteoloside(peak 12),isochlorogenic acid B(peak 13),isochlorogenic acid A(peak 14),and isochlorogenic acid C(peak 16).Similarity evaluation results showed that the UPLC fingerprint similarity of the 20 honeysuckle batches ranged from 0.898 to 1.000.Except for S8 with a similarity of 0.898,the similarity of the remaining samples exceeded 0.974.Cluster heatmap analysis,PCA,and OPLS-DA analysis grouped the 20 Lonicera Japonica Thunb.batches into three clusters,and 4 differential markers were identified.Ranked by VIP values,these were Peak 10>Isoclorogenic acid A>Chlorogenic acid>Isoclorogenic acid C.Pearson correlation analysis revealed a significant positive correlation between origin and grouping,with the highest correlation coefficient.Variety showed the second-highest correlation,followed by processing method.Conclusion:Origin environment and cultivar are key factors influencing the quality of Lonicera Japonica Thunb.Integrating UPLC fingerprinting with multi-component chemical pattern recognition effectively evaluates quality variations among Lonicera Japonica Thunb.from different origins.
管仁伟;王淑;冉志芳;郭瑞齐;孙新茹;智婷;李圣波;许丽丽
山东省中医药研究院,山东 济南 250014山东省中医药研究院,山东 济南 250014山东省中医药研究院,山东 济南 250014山东省中医药研究院,山东 济南 250014山东省中医药研究院,山东 济南 250014山东中医药大学药物研究院,山东 济南 250355山东亚特生态技术股份有限公司,山东 临沂 276017山东省创新发展研究院,山东 济南 250101
医药卫生
金银花产地超高效液相色谱指纹图谱质量评价化学模式识别品种加工方式
Lonicera japonica Thunb.place of originUPLCfingerprint spectrumquality evaluationchemical pattern recognitionvarietiesprocessing method
《中医药导报》 2026 (6)
55-60,6
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