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基于超高效液相色谱-质谱指纹图谱及多指标成分含量测定的芦笋质量评价研究

Quality evaluation of asparagus by UPLC-MS fingerprints and multi-component content determination
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摘要 目的建立不同产地芦笋药材的超高效液相色谱-质谱联用(UPLC-MS)指纹图谱,同时测定芦笋中8种成分的含量,结合化学模式识别法评价不同批次芦笋的质量。方法利用UPLC-MS技术并结合《中药色谱指纹图谱相似度评价系统》建立芦笋指纹图谱,进行相似度评价和共有峰确认,结合层次聚类分析(HCA)、主成分分析(PCA)和正交偏最小二乘法-判别分析(OPLS-DA)等化学模式识别方法对不同批次的芦笋进行质量分析。并采用超高效液相色谱-三重四极杆串联质谱(UPLC-MS/MS)同时测定芦笋中原儿茶酸、香草酸、阿魏酸、芦丁、柚皮苷、橙皮苷、肉桂酸、原薯蓣皂苷8种成分的含量。结果建立的芦笋药材的UPLC-MS指纹图谱有20个共有峰;指纹图谱相似度在0.625~0.951;HCA将43批芦笋样品分为4类;PCA得到6个主成分;OPLS-DA筛选出原薯蓣皂苷、香草酸、芦丁、原儿茶酸、橙皮苷、峰11、峰6等7种差异成分。43批芦笋中原儿茶酸、香草酸、阿魏酸、芦丁、柚皮苷、橙皮苷、肉桂酸、原薯蓣皂苷8种成分含量分别为0.0838~3.1222、0.8462~11.0452、0.4529~29.6468、0.0054~527.1102、0.0809~17.3159、0.0439~320.8445、6.9906~84.8560、0.1934~2384.4689μg·g^(-1)。结论本文建立了芦笋药材UPLC-MS指纹图谱并同时测定其中8种成分含量的UPLC-MS/MS方法,可为芦笋的质量控制、综合评价及进一步开发利用提供参考。 Objective To establish UPLC-MS fingerprints to determine the content of 8 components,and evaluate the quality of asparagus from different habitats combined with chemical pattern recognition method.Methods The fingerprints of asparagus were established by UPLC-MS and“Chinese Chromatographic Fingerprint Similarity Evaluation System”.The similarity was evaluated and the shared peaks were identified.Hierarchical cluster analysis(HCA),principal component analysis(PCA),and orthogonal partial least square-discriminant analysis(OPLS-DA)were used to analyze the quality of fingerprints.An UPLC-MS/MS method was developed to determine protocatechuic acid,vanillic acid,ferulic acid,rutin,naringin,hesperidin,cinnamic acid,and protodioscin in asparagus.Results The UPLC-MS fingerprints of asparagus matched 20 shared peaks;the similarity of the fingerprints ranged from 0.625 to 0.951;43 batches of asparagus were divided into 4 categories by HCA;6 principal components were obtained by PCA.OPLS-DA indicated that protodioscin,vanillic acid,rutin,protocatechuic acid,naringin,peak 11 and peak 6 might be the differential markers for the quality of asparagus.The content of protocatechuic acid,vanillic acid,ferulic acid,rutin,naringin,hesperidin,cinnamic acid,and protodioscin in the 43 samples ranged 0.0838~3.1222,0.8462~11.0452,0.4529~29.6468,0.0054~527.1102,0.0809~17.3159,0.0439~320.8445,6.9906~84.8560,and 0.1934~2384.4689μg·g^(-1),respectively.Conclusion UPLC-MS fingerprints of asparagus from different habitats are established and the content of 8 components is determined,which combines with chemical pattern recognition and provides a scientific basis for quality control,comprehensive evaluation for further development of asparagus.
作者 窦传浩 张秋红 张会敏 DOU Chuan-hao;ZHANG Qiu-hong;ZHANG Hui-min(Shandong University of Traditional Chinese Medicine,Jinan 250355;Shandong Academy of Chinese Medicine,High-Level Key Discipline of Traditional Chinese Medicine Analysis,State Administration of Traditional Chinese Medicine,Jinan 250014;Jinan Supervision and Inspection Center for Food and Drug Control,Jinan 250102)
出处 《中南药学》 CAS 2024年第11期3006-3013,共8页 Central South Pharmacy
基金 山东省重点研发计划(重大创新工程)项目(No.2021SFGC1205) 国家中医药管理局高水平中医药重点学科建设项目(No.zyyzdxk-2023121) 甘肃省科技计划项目(技术创新引导计划:No.22CX8NA024) 山东省中医药科技项目(No.M-2022173) 山东省食品药品监督管理局山东省中药材及饮片标准研究(No.2020-211)。
关键词 芦笋 UPLC-MS 指纹图谱 化学模式识别 定量分析 Asparagus officinalis L. UPLC-MS fingerprinting chemical pattern recognition quantitative analysis
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