Article(id=1304735427693405133, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304735403429356361, articleNumber=null, orderNo=null, doi=10.7501/j.issn.0253-2670.2026.14.025, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1766505600000, receivedDateStr=2025-12-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1789002766774, onlineDateStr=2026-09-10, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789002766774, onlineIssueDateStr=2026-09-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789002766774, creator=13701087609, updateTime=1789002766774, updator=13701087609, issue=Issue{id=1304735403429356361, tenantId=1146029695717560320, journalId=1302319053441957962, year='2026', volume='57', issue='14', pageStart='5353', pageEnd='5788', issueExtLink='null', onlineDate='null', pubDate='1785168000000', pubDateStr='2026-07-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789002760989, creator='13701087609', updateTime=1789002916821, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1304736057073889492, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304735403429356361, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1304736057073889493, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304735403429356361, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=5658, endPage=5666, ext={EN=ArticleExt(id=1304735428066698191, articleId=1304735427693405133, tenantId=1146029695717560320, journalId=1302319053441957962, language=EN, title=Quality evaluation of Heleocharis dulcis based on fingerprint combined with chemical pattern recognition, columnId=null, journalTitle=Chinese Traditional and Herbal Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=Objective To establish the HPLC fingerprint of Heleocharis dulcis and simultaneously determine the contents of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin, and to evaluate the quality of H. dulcis from different regions by chemical pattern recognition method, so that a reference can be provided for quality control of H. dulcis. Methods The fingerprint of H. dulcis was established on a ZORBAX SB C18 (250 mm × 4.6 mm, 5 μm) column using acetonitrile-0.1% phosphoric acid solution as the mobile phase with gradient elution. the “Chinese medicine chromatographic fingerprint pattern similarity evaluation system”(2012.130723 edition) was used for similarity evaluation, SPSS27.0 and SIMCA14.1software was performed for hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to evaluate the quality of H. dulcis from diverse origins. The five chemical constituents were identified and content determined by comparison with the reference substance, and the results were synthesized using chemical pattern recognition and entropy weighted TOPSIS method. Results A total of 15 common peaks were matched to 26 batches of H. dulcis HPLC fingerprints, and five components including chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin were identified. The similarity of fingerprints was between 0.865 and 0.995. The 26 batches of H. dulcis were clustered into two classes by HCA. PCA analysis yielded a cumulative variance contribution of 83.283% for the three primary constituents. Four components, including luteolin and chlorogenic acid, were screened by OPLS-DA as the indicator components for the quality difference of H. dulcis from different regions. The mass fractions of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin in 26 batches of H.dulcis were 5.43—60.65 , 0.44—2.27, 1.65—6.46, 2.58—59.94 and 0.31—24.40 μg/g, successively. Both PCA and entropy weighted TOPSIS results indicated that samples from Hubei Province exhibited the best quality. Conclusion The established HPLC fingerprinting method is characterised by its stability, reliability, and reproducibility. which can be used for the quality evaluation of H. dulcis in combination with chemical pattern recognition, and provides a reference for the quality control and resource development of H. dulcis., authors=ZOU Lina, ZOU Shitao, TANG Haiming, LIN Huaqing, LI Shimei, LI Ai, HE Haibo, authorsList=ZOU Lina, ZOU Shitao, TANG Haiming, LIN Huaqing, LI Shimei, LI Ai, HE Haibo, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1304735427982812110, articleId=1304735427693405133, tenantId=1146029695717560320, journalId=1302319053441957962, language=CN, title=基于指纹图谱结合化学模式识别法对不同产地荸荠的质量评价, columnId=1304140203967410414, journalTitle=中草药, columnName=药材与资源, runingTitle=null, highlight=null, articleAbstract=目的 建立不同产地荸荠Heleocharis dulcis的HPLC指纹图谱及同时测定绿原酸、咖啡酸、阿魏酸、木犀草素、棕矢车菊素的方法,并结合化学模式识别法对不同产地荸荠进行质量评价。方法 采用ZORBAX SB C₁₈(250 mm×4.6 mm,5 μm)色谱柱,以乙腈-0.1%磷酸水溶液作为流动相,梯度洗脱,建立荸荠HPLC指纹图谱。运用“中药色谱指纹图谱相似度评价系统(2012.130723版本)”软件进行相似度评价,使用SPSS27.0软件、SIMCA14.1软件,结合聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)和正交偏最小二乘判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)来评价不同产地荸荠质量;同时测定其中5个成分的含量,运用化学模式识别和熵权TOPSIS法对结果进行综合评价。结果 26批荸荠HPLC指纹图谱匹配出15个共有峰,指认了绿原酸、咖啡酸、阿魏酸、木犀草素和棕矢车菊素5个成分,指纹图谱的相似度在0.865~0.995;HCA将26批荸荠聚为2类;PCA得到3个主成分的累积方差贡献率为83.283%;OPLS-DA筛选出木犀草素和绿原酸等4个成分是不同产地荸荠药材质量差异的标志性成分;26批荸荠中绿原酸、咖啡酸、阿魏酸、木犀草素、棕矢车菊素的质量分数分别为5.43~60.65 μg/g、0.44~2.27 μg/g、1.65~6.46 μg/g、2.58~59.94 μg/g、0.31~24.40 μg/g;PCA与熵权TOPSIS分析均表明湖北产地的荸荠质量较优。结论 建立的HPLC指纹图谱方法稳定、可靠、重复性好,结合化学模式识别可用于荸荠的质量评价,为荸荠质量控制与资源开发提供参考。, authors=邹丽娜1,2, 邹时涛1,2, 唐海明3,2, 林华清2, 李诗梅2, 黎爱4, 贺海波1, authorsList=邹丽娜, 邹时涛, 唐海明, 林华清, 李诗梅, 黎爱, 贺海波, authorCompany=1 三峡大学天然产物研究与利用湖北省重点实验室, 药食同源大健康产品开发利用宜昌市重点实验室, 湖北 宜昌 443002;
2 湖北恒安芙林药业股份有限公司, 宜昌市中医药传承创新重点实验室, 湖北 宜昌 443100;
3 华中农业大学食品科学技术学院, 湖北 武汉 430070;
4 宜昌市夷陵人民医院, 湖北 宜昌 443100, correspAuthors=唐海明, authorNote=邹丽娜: 邹丽娜,女,硕士研究生,研究方向为中药质量控制研究。E-mail:zlnexo20120408@163.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=9x3Y55V0KnWdsUDvyzjCrw==, pdfFileSize=1136635, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=湖北省科技厅重点研发项目 (2025BCB067); 湖北省科技厅重点研发大健康计划项目 (2022BCE017); 湖北省卫生健康委员会中医药重点项目 (ZY2023Z015); 湖北省科技厅自然科学基金项目 (2025AFB805,2025AFB839,2025AFD301,2025AFD294,2023AFB600,2022CFB357,2022CFB427); 宜昌市医疗卫生研究项目 (A22-2-059,A23-1-061); 湖北省卫生健康委员会科研资助项目 (WJ2023M153); 湖北省功能性消化系统疾病中医临床医学研究中心开放基金 (SXZ202303,SXZ202308,SXZ202311))}, authors=null, keywords=[Keyword(id=1304735428200915920, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=1, keyword=荸荠), Keyword(id=1304735428272219089, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=2, keyword=指纹图谱), Keyword(id=1304735428347716562, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=3, keyword=化学模式识别), Keyword(id=1304735428427408339, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=4, keyword=绿原酸), Keyword(id=1304735428486128596, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=5, keyword=咖啡酸), Keyword(id=1304735428544848853, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=6, keyword=阿魏酸), Keyword(id=1304735428616152022, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=7, keyword=木犀草素), Keyword(id=1304735428683260887, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=8, keyword=棕矢车菊素), Keyword(id=1304735428809090008, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=CN, orderNo=9, keyword=质量评价), Keyword(id=1304735428964279257, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304735427693405133, language=EN, orderNo=1, keyword=Heleocharis dulcis (Burm. f.) 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detailUrlEn=https://castjournals.cast.org.cn/joweb/zcy/EN/10.7501/j.issn.0253-2670.2026.14.025, pdfUrlCn=https://castjournals.cast.org.cn/joweb/zcy/CN/PDF/10.7501/j.issn.0253-2670.2026.14.025, pdfUrlEn=https://castjournals.cast.org.cn/joweb/zcy/EN/PDF/10.7501/j.issn.0253-2670.2026.14.025, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, previewStatus=0, delFlag=0, hasFullText=0, orderTime=1789002766774, fullTextJson=null, articleText=null, reference=刘旭, 周忠光, 安柏松, 等. 荸荠药理学研究进展[J]. 中医药信息, 2010, 27(6): 106-108.
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Ma Q G, Wei R R, Sang Z P, et al. Structural characterization, neuroprotective and hepatoprotective activities of flavonoids from the bulbs of Heleocharis dulcis [J]. Bioorg Chem, 2020, 96: 103630.
杨炳辉, 张一兵, 黄建华, 等. 荸荠中一种生物碱(MTC)的鉴定和绝对构型的确定[J]. 天然产物研究与开发, 1995, 7(1): 1-4.
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刘欣, 赵力超, 周爱梅. 荸荠产粉废浆中功能组分及其功能效果的初步研究[J]. 食品科学, 2006, 27(2): 251-256.
Wei R R, Ma Q G, Sang Z P. Hypolipidemic phenanthraquinone derivatives from Heleocharis dulcis [J]. Biochem Syst Ecol, 2019, 83: 17-21.
赵广河, 陈振林. 荸荠活性成分与功能作用研究进展[J]. 食品研究与开发, 2011, 32(9): 235-237.
Baehaki A, Herpandi H, Andri Putra A. Antibacterial activity of extract from swamp plant of Eleocharis dulcis [J]. Orient J Chem, 2018, 34(1): 573-575.
You Y L, Duan X W, Wei X Y, et al. Identificationof major phenolic compounds of Chinese water chestnut and their antioxidant activity [J]. Molecules, 2007, 12(4): 842-852.
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文阳, 海来约布, 蔡晓霞, 等. 基于指纹图谱结合化学模式识别对接骨草的质量评价[J]. 中草药, 2023, 54(24): 8206-8213.
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刘仟禧, 刘梦云, 曹素芹, 等. 基于指纹图谱、化学计量学及熵权TOPSIS-GRA融合模型法评价不同产地大青叶的质量[J]. 中草药, 2025, 56(6): 2148-2157.
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中草药 |药材与资源 2026 , 57 (14) : 5658 -5666
基于指纹图谱结合化学模式识别法对不同产地荸荠的质量评价
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邹丽娜1,2, 邹时涛1,2, 唐海明3,2, 林华清2, 李诗梅2, 黎爱4, 贺海波1
作者信息
    1 三峡大学天然产物研究与利用湖北省重点实验室, 药食同源大健康产品开发利用宜昌市重点实验室, 湖北 宜昌 443002;
    2 湖北恒安芙林药业股份有限公司, 宜昌市中医药传承创新重点实验室, 湖北 宜昌 443100;
    3 华中农业大学食品科学技术学院, 湖北 武汉 430070;
    4 宜昌市夷陵人民医院, 湖北 宜昌 443100
通讯作者:
唐海明
作者简介:
邹丽娜: 邹丽娜,女,硕士研究生,研究方向为中药质量控制研究。E-mail:zlnexo20120408@163.com
Quality evaluation of Heleocharis dulcis based on fingerprint combined with chemical pattern recognition
  • ZOU Lina, ZOU Shitao, TANG Haiming, LIN Huaqing, LI Shimei, LI Ai, HE Haibo
  • Affiliations
    doi: 10.7501/j.issn.0253-2670.2026.14.025
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    目的 建立不同产地荸荠Heleocharis dulcis的HPLC指纹图谱及同时测定绿原酸、咖啡酸、阿魏酸、木犀草素、棕矢车菊素的方法,并结合化学模式识别法对不同产地荸荠进行质量评价。方法 采用ZORBAX SB C₁₈(250 mm×4.6 mm,5 μm)色谱柱,以乙腈-0.1%磷酸水溶液作为流动相,梯度洗脱,建立荸荠HPLC指纹图谱。运用“中药色谱指纹图谱相似度评价系统(2012.130723版本)”软件进行相似度评价,使用SPSS27.0软件、SIMCA14.1软件,结合聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)和正交偏最小二乘判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)来评价不同产地荸荠质量;同时测定其中5个成分的含量,运用化学模式识别和熵权TOPSIS法对结果进行综合评价。结果 26批荸荠HPLC指纹图谱匹配出15个共有峰,指认了绿原酸、咖啡酸、阿魏酸、木犀草素和棕矢车菊素5个成分,指纹图谱的相似度在0.865~0.995;HCA将26批荸荠聚为2类;PCA得到3个主成分的累积方差贡献率为83.283%;OPLS-DA筛选出木犀草素和绿原酸等4个成分是不同产地荸荠药材质量差异的标志性成分;26批荸荠中绿原酸、咖啡酸、阿魏酸、木犀草素、棕矢车菊素的质量分数分别为5.43~60.65 μg/g、0.44~2.27 μg/g、1.65~6.46 μg/g、2.58~59.94 μg/g、0.31~24.40 μg/g;PCA与熵权TOPSIS分析均表明湖北产地的荸荠质量较优。结论 建立的HPLC指纹图谱方法稳定、可靠、重复性好,结合化学模式识别可用于荸荠的质量评价,为荸荠质量控制与资源开发提供参考。
    荸荠  /  指纹图谱  /  化学模式识别  /  绿原酸  /  咖啡酸  /  阿魏酸  /  木犀草素  /  棕矢车菊素  /  质量评价
    Objective To establish the HPLC fingerprint of Heleocharis dulcis and simultaneously determine the contents of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin, and to evaluate the quality of H. dulcis from different regions by chemical pattern recognition method, so that a reference can be provided for quality control of H. dulcis. Methods The fingerprint of H. dulcis was established on a ZORBAX SB C18 (250 mm × 4.6 mm, 5 μm) column using acetonitrile-0.1% phosphoric acid solution as the mobile phase with gradient elution. the “Chinese medicine chromatographic fingerprint pattern similarity evaluation system”(2012.130723 edition) was used for similarity evaluation, SPSS27.0 and SIMCA14.1software was performed for hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to evaluate the quality of H. dulcis from diverse origins. The five chemical constituents were identified and content determined by comparison with the reference substance, and the results were synthesized using chemical pattern recognition and entropy weighted TOPSIS method. Results A total of 15 common peaks were matched to 26 batches of H. dulcis HPLC fingerprints, and five components including chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin were identified. The similarity of fingerprints was between 0.865 and 0.995. The 26 batches of H. dulcis were clustered into two classes by HCA. PCA analysis yielded a cumulative variance contribution of 83.283% for the three primary constituents. Four components, including luteolin and chlorogenic acid, were screened by OPLS-DA as the indicator components for the quality difference of H. dulcis from different regions. The mass fractions of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin in 26 batches of H.dulcis were 5.43—60.65 , 0.44—2.27, 1.65—6.46, 2.58—59.94 and 0.31—24.40 μg/g, successively. Both PCA and entropy weighted TOPSIS results indicated that samples from Hubei Province exhibited the best quality. Conclusion The established HPLC fingerprinting method is characterised by its stability, reliability, and reproducibility. which can be used for the quality evaluation of H. dulcis in combination with chemical pattern recognition, and provides a reference for the quality control and resource development of H. dulcis.
    Heleocharis dulcis (Burm. f.) Trin. ex Henschel  /  fingerprint  /  chemical pattern recognition  /  chlorogenic acid  /  caffeic acid  /  ferulic acid  /  luteolin  /  jaceosidin  /  quality evaluation
    邹丽娜, 邹时涛, 唐海明, 林华清, 李诗梅, 黎爱, 贺海波. 基于指纹图谱结合化学模式识别法对不同产地荸荠的质量评价. 中草药, 2026 , 57 (14) : 5658 -5666 . DOI: 10.7501/j.issn.0253-2670.2026.14.025
    ZOU Lina, ZOU Shitao, TANG Haiming, LIN Huaqing, LI Shimei, LI Ai, HE Haibo. Quality evaluation of Heleocharis dulcis based on fingerprint combined with chemical pattern recognition[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (14) : 5658 -5666 . DOI: 10.7501/j.issn.0253-2670.2026.14.025

      湖北省科技厅重点研发项目 (2025BCB067); 湖北省科技厅重点研发大健康计划项目 (2022BCE017); 湖北省卫生健康委员会中医药重点项目 (ZY2023Z015); 湖北省科技厅自然科学基金项目 (2025AFB805,2025AFB839,2025AFD301,2025AFD294,2023AFB600,2022CFB357,2022CFB427); 宜昌市医疗卫生研究项目 (A22-2-059,A23-1-061); 湖北省卫生健康委员会科研资助项目 (WJ2023M153); 湖北省功能性消化系统疾病中医临床医学研究中心开放基金 (SXZ202303,SXZ202308,SXZ202311)

    参考文献 引证文献
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    中国药典[S]. 一部. 2025: 568.
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    Zhang Y, Xu H, Hu Z B, et al. Eleocharis dulcis corm: Phytochemicals, health benefits, processing and food products [J]. J Sci Food Agric, 2022, 102(1): 19-40.
    魏连会, 刘宇峰, 姬妍茹, 等. 荸荠功能活性成分研究进展[J]. 农产品加工, 2016(4): 52-54.
    Ma Q G, Wei R R, Sang Z P, et al. Structural characterization, neuroprotective and hepatoprotective activities of flavonoids from the bulbs of Heleocharis dulcis [J]. Bioorg Chem, 2020, 96: 103630.
    杨炳辉, 张一兵, 黄建华, 等. 荸荠中一种生物碱(MTC)的鉴定和绝对构型的确定[J]. 天然产物研究与开发, 1995, 7(1): 1-4.
    汪建红, 袁伟, 韩平东. 荸荠皮中多糖的提取、纯化及抗氧化性研究[J]. 食品与机械, 2016, 32(7): 156-160.
    刘欣, 赵力超, 周爱梅. 荸荠产粉废浆中功能组分及其功能效果的初步研究[J]. 食品科学, 2006, 27(2): 251-256.
    Wei R R, Ma Q G, Sang Z P. Hypolipidemic phenanthraquinone derivatives from Heleocharis dulcis [J]. Biochem Syst Ecol, 2019, 83: 17-21.
    赵广河, 陈振林. 荸荠活性成分与功能作用研究进展[J]. 食品研究与开发, 2011, 32(9): 235-237.
    Baehaki A, Herpandi H, Andri Putra A. Antibacterial activity of extract from swamp plant of Eleocharis dulcis [J]. Orient J Chem, 2018, 34(1): 573-575.
    You Y L, Duan X W, Wei X Y, et al. Identificationof major phenolic compounds of Chinese water chestnut and their antioxidant activity [J]. Molecules, 2007, 12(4): 842-852.
    Wang J, Hu X, Shan T, et al. Aquatic vegetable extract inhibits the proliferation of human hepatoma HepG2 and human gastric cancer SGC7901 cells [J]. Mod Food Sci Technol, 2020, 36(9): 9-16.
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    马权, 海来约布, 文阳, 等. 基于指纹图谱结合化学模式的坡柳皮质量评价研究[J]. 中药材, 2024, 47(1): 2569-2579.
    文阳, 海来约布, 蔡晓霞, 等. 基于指纹图谱结合化学模式识别对接骨草的质量评价[J]. 中草药, 2023, 54(24): 8206-8213.
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    王梦蝶, 卓越, 邹丽娜, 等. 基于HPLC指纹图谱及多成分定量的金钱草质量评价[J]. 中草药, 2025, 56(3): 998-1007.
    刘仟禧, 刘梦云, 曹素芹, 等. 基于指纹图谱、化学计量学及熵权TOPSIS-GRA融合模型法评价不同产地大青叶的质量[J]. 中草药, 2025, 56(6): 2148-2157.
    王继双, 何焱, 张文静, 等. 木犀草素的药理作用研究进展[J]. 生命科学, 2013, 25(6): 560-565.
    严永旺, 肖兰, 周旭, 等. 绿原酸的药理作用及药用研发对策[J]. 中国药房, 2017, 28(19): 2729-2732.
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    小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
    多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
    红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
    小菇属 Mycena 11 5.26
    光柄菇属 Pluteus 5 2.39
    红菇属 Russula 17 8.13
    栓菌属 Trametes 5 2.39
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