Article(id=1304406837151953734, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304406818550206926, articleNumber=null, orderNo=null, doi=10.7501/j.issn.0253-2670.2026.01.008, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1758124800000, receivedDateStr=2025-09-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1788924424684, onlineDateStr=2026-09-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1788924424684, onlineIssueDateStr=2026-09-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1788924424684, creator=13701087609, updateTime=1788924424684, updator=13701087609, issue=Issue{id=1304406818550206926, tenantId=1146029695717560320, journalId=1302319053441957962, year='2026', volume='57', issue='1', pageStart='1', pageEnd='389', issueExtLink='null', onlineDate='null', pubDate='1768147200000', pubDateStr='2026-01-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1788924420249, creator='13701087609', updateTime=1788924674802, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1304407886289986387, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304406818550206926, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1304407886289986388, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304406818550206926, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=64, endPage=72, ext={EN=ArticleExt(id=1304406837483303752, articleId=1304406837151953734, tenantId=1146029695717560320, journalId=1302319053441957962, language=EN, title=Quality evaluation of Angelicae Sinensis Radix before and after wine processing based on HPLC fingerprints combined with chemical pattern recognition and multi-component quantification, columnId=null, journalTitle=Chinese Traditional and Herbal Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=Objective To establish HPLC fingerprint profiles of raw Dɑnggui (Angelicae Sinensis Radix, ASR) and ASR processed with wine, and to study the changes in chemical components before and after wine processing by combining multivariate statistical analysis and quantitative determination, providing a reference for the quality evaluation of ASR. Methods HPLC was used to establish the fingerprint profiles of raw ASR and ASR processed with wine, and the contents of 5-hydroxymethylfurfural (5-HMF), chlorogenic acid, vanillin, ferulic acid, and ligustilide were determined. The similarity of the profiles was calculated using the Chinese herbal medicine chromatographic fingerprint similarity evaluation system. Common peaks were calibrated, identified, and assigned.. The peak areas of the common peaks before and after wine processing were used as indicators. Hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed to evaluate the intrinsic quality differences between raw and wine-processed ASR and identify the main differential components. Results HPLC fingerprint profiles of ten batches of raw ASR and ASR processed with wine were established. A total of 11 common peaks were identified in raw ASR and 12 common peaks were calibrated in ASR processed with wine. The similarity of the profiles was greater than 0.960. Chemical pattern recognition indicated that peaks 12 (ligustilide), 7, 11, and 6 (ferulic acid) might be the markers of the quality differences before and after wine processing. The content determination results showed that 5-HMF was newly generated after wine processing, while the contents of ferulic acid, chlorogenic acid, and vanillin slightly decreased, and the content of ligustilide increased. Conclusion The established fingerprint profiles and multi-component quantitative determination methods for ASR before and after wine processing are stable and reliable, providing a reference for the quality control, comprehensive utilization, and clinical application of ASR and ASR processed with wine., authors=ZHAO Meixi, YAO Xuelian, YANG Ming, ZHU Jing, LU Tulin, GUAN Yongmei, LAN Zhihui, LIU Leling, ZHAO Zibo, ZANG Zhenzhong, authorsList=ZHAO Meixi, YAO Xuelian, YANG Ming, ZHU Jing, LU Tulin, GUAN Yongmei, LAN Zhihui, LIU Leling, ZHAO Zibo, ZANG Zhenzhong, 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=1304406837407806279, articleId=1304406837151953734, tenantId=1146029695717560320, journalId=1302319053441957962, language=CN, title=基于HPLC指纹图谱结合化学模式识别及多成分定量测定的当归酒炙前后质量评价, columnId=1304140189132149234, journalTitle=中草药, columnName=药剂与工艺, runingTitle=null, highlight=null, articleAbstract=目的 建立生当归Angelicae Sinensis Radix及酒当归HPLC指纹图谱,并结合多元统计分析和定量测定研究当归酒炙前后化学成分的变化,为当归质量评价提供参考。方法 采用HPLC法建立生当归及酒当归指纹图谱,并测定其中5-羟甲基糠醛(5-hydroxymethylfurfural,5-HMF)、绿原酸、香草醛、阿魏酸、藁本内酯的含量。采用中药色谱指纹图谱相似度评价系统计算相似度,标定共有峰并进行指认及归属,以当归酒炙前后共有峰峰面积为指标,运用层次聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)及正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA),评价当归酒炙前后内在质量差异,寻找其主要差异性成分。结果 建立了10批次生当归和酒当归HPLC指纹图谱,其中生当归共标定了11个共有峰,酒当归共标定了12个共有峰,生、酒当归指纹图谱相似度均>0.960。化学模式识别筛选出色谱峰12(藁本内酯)、7、11、6号峰(阿魏酸)可能是影响当归酒炙前后质量差异的标志物。含量测定结果表明,当归酒炙后新生成5-HMF成分,阿魏酸、绿原酸、香草醛成分含量整体略微下降,藁本内酯成分含量整体有所上升。结论 建立的当归酒炙前后指纹图谱及多成分定量测定方法稳定、可靠,可为生当归及酒当归的质量控制和综合利用提供参考。, authors=赵美茜1, 姚雪莲1, 杨明2, 祝婧1, 陆兔林3, 管咏梅2, 兰智慧4, 刘乐灵2, 赵子波2, 臧振中2, authorsList=赵美茜, 姚雪莲, 杨明, 祝婧, 陆兔林, 管咏梅, 兰智慧, 刘乐灵, 赵子波, 臧振中, authorCompany=1 江西中医药大学药学院, 江西 南昌 330004;
2 江西中医药大学, 现代中药制剂教育部重点实验室, 江西 南昌 330004;
3 南京中医药大学药学院, 江苏 南京 210023;
4 江西中医药大学附属医院, 江西 南昌 330006, correspAuthors=臧振中, authorNote=赵美茜: 赵美茜,硕士研究生,研究方向为中药炮制与质量标准研究。E-mail:2113016447@qq.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=4aS4QScQfipmp5D3aKz9AA==, pdfFileSize=1769512, 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=国家重点研发计划项目 (2023YFC3504204); 全国重点实验室自主部署重点研发计划项目 (20243BCC31010); 博士科研启动基金项目 (2023WBZR007); 2023年度中药学重点学科项目 (2023jzzdxk016); 江西中医药大学科技创新团队项目 (CXTD22006))}, authors=null, keywords=[Keyword(id=1304406837642687305, tenantId=1146029695717560320, journalId=1302319053441957962, articleId=1304406837151953734, language=CN, orderNo=1, keyword=当归), Keyword(id=1304406839223939914, tenantId=1146029695717560320, journalId=1302319053441957962, 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provinceName=null, collectFlag=false, interPubPlatform=, interPubPlatformUrl=null), detailUrlCn=https://castjournals.cast.org.cn/joweb/zcy/CN/10.7501/j.issn.0253-2670.2026.01.008, detailUrlEn=https://castjournals.cast.org.cn/joweb/zcy/EN/10.7501/j.issn.0253-2670.2026.01.008, pdfUrlCn=https://castjournals.cast.org.cn/joweb/zcy/CN/PDF/10.7501/j.issn.0253-2670.2026.01.008, pdfUrlEn=https://castjournals.cast.org.cn/joweb/zcy/EN/PDF/10.7501/j.issn.0253-2670.2026.01.008, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, previewStatus=0, delFlag=0, hasFullText=0, orderTime=1788924424684, fullTextJson=null, articleText=null, reference=中国药典[S]. 一部. 2025:142.
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马燕,张育贵,石露萍,等.当归炮制品及其化学成分和药理作用研究进展[J]. 中国中药杂志, 2023, 48(22):6003-6010.
陆美霞,邓红,施林峰,等.天麻姜制前后的HPLC指纹图谱比较以及6种成分含量测定[J]. 时珍国医国药, 2023, 34(2):333-337.
李鹏飞,岳倩侠,孙叶芬,等.基于指纹图谱与化学计量学的白芍酒炙前后差异性标志物研究[J]. 中草药,2023, 54(8):2398-2407.
王淑,张翠翠,郭凤丹,等.基于UPLC多指标含量测定和指纹图谱的不同种质金银花药材质量评价研究[J]. 中草药, 2024, 55(3):947-955.
崔艺彤,王乐,王朝慧,等.基于HPLC指纹图谱和多成分定量结合化学模式识别的槐枝药材质量评价[J]. 药物评价研究, 2025, 48(4):928-935.
王永春,刘宇心,孟珈同,等.经典名方温经汤中酒当归炮制工艺优化及其指纹图谱的研究[J]. 中国新药杂志, 2023, 32(3):283-293.
严维花,曹虹虹,郭爽,等.当归不同炮制品的UPLC指纹图谱与多成分含量测定研究[J]. 中国中药杂志,2019, 44(12):2499-2510.
刘彩凤,梁军,杨海菊,等.基于指纹图谱及化学模式对当归酒洗前后的比较分析[J]. 北京中医药大学学报, 2020, 43(3):234-241.
张明惠,朱田田,晋玲,等.基于HPLC多指标成分测定及指纹图谱多模式识别的不同产地不同品种当归质量差异分析[J]. 中草药, 2022, 53(19):6187-6199.
党文飞,张红伟,周洁,等.基于HPLC指纹图谱及色度值的当归与油当归比较研究[J]. 中国中医药信息杂志, 2024, 31(5):112-117.
李天媛,李坤玉,李爽,等. HPLC指纹图谱-化学计量学筛选岷当归质量评价因子研究[J]. 辽宁中医药大学学报, 2025, 27(4):49-53.
孟子盈,杨倩倩,石玉存,等. HPLC指纹图谱结合化学计量学研究当归土炒前后主要成分变化[J]. 中国药学杂志, 2025, 60(5):522-531.
林秀敏,张振凌,王胜超,等.白芍饮片的HPLC指纹图谱建立及聚类分析、主成分分析[J]. 中国药房,2019, 30(24):3375-3382.
Zheng C, Li W T, Yao Y, et al. Quality evaluation of Atractylodis Macrocephalae Rhizoma based on combinative method of HPLC fingerprint, quantitative analysis of multi-components and chemical pattern recognition analysis[J]. Molecules, 2021, 26(23):7124.
刘宇婷,赵梦薇,王玉霞,等. HPLC指纹图谱和多成分定量结合化学模式识别法对地骨皮饮片的质量评价[J]. 时珍国医国药, 2025, 36(6):1070-1075.
Ma Q D, Chen X X, Zhang K, et al. Chemical fingerprint analysis for discovering markers and identifying Saussurea involucrata by HPLC coupled with OPLS-DA[J]. J Anal Methods Chem, 2020, 2020:7560710.
Huang B M, Zha Q L, Chen T B, et al. Discovery of markers for discriminating the age of cultivated ginseng by using UHPLC-QTOF/MS coupled with OPLS-DA[J]. Phytomedicine, 2018, 45:8-17.
王莹,孙嘉辰,李霞,等.基于建立成分活性权重函数的当归酒炙工艺评价研究[J]. 中草药, 2022, 53(10):3014-3021.
Liu W J, Xiao K M, Ren L, et al. Leukemia cells apoptosis by a newly discovered heterogeneous polysaccharide from Angelica sinensis(Oliv.)Diels[J]. Carbohydr Polym,2020, 241:116279.
Liu W J, Li Z Z, Feng C X, et al. The structures of two polysaccharides from Angelica sinensis and their effects on hepatic insulin resistance through blocking RAGE[J]. Carbohydr Polym, 2022, 280:119001.)
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中草药 | 药剂与工艺 2026,57(1): 64-72
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中草药 |药剂与工艺 2026 , 57 (1) : 64 -72
基于HPLC指纹图谱结合化学模式识别及多成分定量测定的当归酒炙前后质量评价
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赵美茜1, 姚雪莲1, 杨明2, 祝婧1, 陆兔林3, 管咏梅2, 兰智慧4, 刘乐灵2, 赵子波2, 臧振中2
作者信息
    1 江西中医药大学药学院, 江西 南昌 330004;
    2 江西中医药大学, 现代中药制剂教育部重点实验室, 江西 南昌 330004;
    3 南京中医药大学药学院, 江苏 南京 210023;
    4 江西中医药大学附属医院, 江西 南昌 330006
通讯作者:
臧振中
作者简介:
赵美茜: 赵美茜,硕士研究生,研究方向为中药炮制与质量标准研究。E-mail:2113016447@qq.com
Quality evaluation of Angelicae Sinensis Radix before and after wine processing based on HPLC fingerprints combined with chemical pattern recognition and multi-component quantification
  • ZHAO Meixi, YAO Xuelian, YANG Ming, ZHU Jing, LU Tulin, GUAN Yongmei, LAN Zhihui, LIU Leling, ZHAO Zibo, ZANG Zhenzhong
  • Affiliations
    doi: 10.7501/j.issn.0253-2670.2026.01.008
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    目的 建立生当归Angelicae Sinensis Radix及酒当归HPLC指纹图谱,并结合多元统计分析和定量测定研究当归酒炙前后化学成分的变化,为当归质量评价提供参考。方法 采用HPLC法建立生当归及酒当归指纹图谱,并测定其中5-羟甲基糠醛(5-hydroxymethylfurfural,5-HMF)、绿原酸、香草醛、阿魏酸、藁本内酯的含量。采用中药色谱指纹图谱相似度评价系统计算相似度,标定共有峰并进行指认及归属,以当归酒炙前后共有峰峰面积为指标,运用层次聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)及正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA),评价当归酒炙前后内在质量差异,寻找其主要差异性成分。结果 建立了10批次生当归和酒当归HPLC指纹图谱,其中生当归共标定了11个共有峰,酒当归共标定了12个共有峰,生、酒当归指纹图谱相似度均>0.960。化学模式识别筛选出色谱峰12(藁本内酯)、7、11、6号峰(阿魏酸)可能是影响当归酒炙前后质量差异的标志物。含量测定结果表明,当归酒炙后新生成5-HMF成分,阿魏酸、绿原酸、香草醛成分含量整体略微下降,藁本内酯成分含量整体有所上升。结论 建立的当归酒炙前后指纹图谱及多成分定量测定方法稳定、可靠,可为生当归及酒当归的质量控制和综合利用提供参考。
    当归  /  酒当归  /  HPLC  /  指纹图谱  /  化学计量学  /  5-羟甲基糠醛  /  绿原酸  /  香草醛  /  阿魏酸  /  藁本内酯  /  质量评价  /  层次聚类分析  /  主成分分析  /  正交偏最小二乘-判别分析
    Objective To establish HPLC fingerprint profiles of raw Dɑnggui (Angelicae Sinensis Radix, ASR) and ASR processed with wine, and to study the changes in chemical components before and after wine processing by combining multivariate statistical analysis and quantitative determination, providing a reference for the quality evaluation of ASR. Methods HPLC was used to establish the fingerprint profiles of raw ASR and ASR processed with wine, and the contents of 5-hydroxymethylfurfural (5-HMF), chlorogenic acid, vanillin, ferulic acid, and ligustilide were determined. The similarity of the profiles was calculated using the Chinese herbal medicine chromatographic fingerprint similarity evaluation system. Common peaks were calibrated, identified, and assigned.. The peak areas of the common peaks before and after wine processing were used as indicators. Hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed to evaluate the intrinsic quality differences between raw and wine-processed ASR and identify the main differential components. Results HPLC fingerprint profiles of ten batches of raw ASR and ASR processed with wine were established. A total of 11 common peaks were identified in raw ASR and 12 common peaks were calibrated in ASR processed with wine. The similarity of the profiles was greater than 0.960. Chemical pattern recognition indicated that peaks 12 (ligustilide), 7, 11, and 6 (ferulic acid) might be the markers of the quality differences before and after wine processing. The content determination results showed that 5-HMF was newly generated after wine processing, while the contents of ferulic acid, chlorogenic acid, and vanillin slightly decreased, and the content of ligustilide increased. Conclusion The established fingerprint profiles and multi-component quantitative determination methods for ASR before and after wine processing are stable and reliable, providing a reference for the quality control, comprehensive utilization, and clinical application of ASR and ASR processed with wine.
    Angelicae Sinensis Radix  /  Angelicae Sinensis Radix processed with wine  /  HPLC  /  fingerprint  /  chemometrics  /  5-hydroxymethylfurfural  /  chlorogenic acid  /  vanillin  /  ferulic acid  /  ligustilide  /  quality evaluation  /  hierarchical cluster analysis  /  principal component analysis  /  orthogonal partial least squares-discriminant analysis
    赵美茜, 姚雪莲, 杨明, 祝婧, 陆兔林, 管咏梅, 兰智慧, 刘乐灵, 赵子波, 臧振中. 基于HPLC指纹图谱结合化学模式识别及多成分定量测定的当归酒炙前后质量评价. 中草药, 2026 , 57 (1) : 64 -72 . DOI: 10.7501/j.issn.0253-2670.2026.01.008
    ZHAO Meixi, YAO Xuelian, YANG Ming, ZHU Jing, LU Tulin, GUAN Yongmei, LAN Zhihui, LIU Leling, ZHAO Zibo, ZANG Zhenzhong. Quality evaluation of Angelicae Sinensis Radix before and after wine processing based on HPLC fingerprints combined with chemical pattern recognition and multi-component quantification[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (1) : 64 -72 . DOI: 10.7501/j.issn.0253-2670.2026.01.008

      国家重点研发计划项目 (2023YFC3504204); 全国重点实验室自主部署重点研发计划项目 (20243BCC31010); 博士科研启动基金项目 (2023WBZR007); 2023年度中药学重点学科项目 (2023jzzdxk016); 江西中医药大学科技创新团队项目 (CXTD22006)

    参考文献 引证文献
    排序方式:
    中国药典[S]. 一部. 2025:142.
    丁羽,戴慧莲,姜德利,等.基于智能感官和近红外光谱技术结合化学计量学的酒当归炮制程度快速辨识研究[J]. 中草药, 2025, 56(1):68-78.
    张玲.中药当归经不同炮制方法炮制后对其化学成分的影响分析[J]. 中国处方药, 2019, 17(11):18-19.
    马燕,张育贵,石露萍,等.当归炮制品及其化学成分和药理作用研究进展[J]. 中国中药杂志, 2023, 48(22):6003-6010.
    陆美霞,邓红,施林峰,等.天麻姜制前后的HPLC指纹图谱比较以及6种成分含量测定[J]. 时珍国医国药, 2023, 34(2):333-337.
    李鹏飞,岳倩侠,孙叶芬,等.基于指纹图谱与化学计量学的白芍酒炙前后差异性标志物研究[J]. 中草药,2023, 54(8):2398-2407.
    王淑,张翠翠,郭凤丹,等.基于UPLC多指标含量测定和指纹图谱的不同种质金银花药材质量评价研究[J]. 中草药, 2024, 55(3):947-955.
    崔艺彤,王乐,王朝慧,等.基于HPLC指纹图谱和多成分定量结合化学模式识别的槐枝药材质量评价[J]. 药物评价研究, 2025, 48(4):928-935.
    王永春,刘宇心,孟珈同,等.经典名方温经汤中酒当归炮制工艺优化及其指纹图谱的研究[J]. 中国新药杂志, 2023, 32(3):283-293.
    严维花,曹虹虹,郭爽,等.当归不同炮制品的UPLC指纹图谱与多成分含量测定研究[J]. 中国中药杂志,2019, 44(12):2499-2510.
    刘彩凤,梁军,杨海菊,等.基于指纹图谱及化学模式对当归酒洗前后的比较分析[J]. 北京中医药大学学报, 2020, 43(3):234-241.
    张明惠,朱田田,晋玲,等.基于HPLC多指标成分测定及指纹图谱多模式识别的不同产地不同品种当归质量差异分析[J]. 中草药, 2022, 53(19):6187-6199.
    党文飞,张红伟,周洁,等.基于HPLC指纹图谱及色度值的当归与油当归比较研究[J]. 中国中医药信息杂志, 2024, 31(5):112-117.
    李天媛,李坤玉,李爽,等. HPLC指纹图谱-化学计量学筛选岷当归质量评价因子研究[J]. 辽宁中医药大学学报, 2025, 27(4):49-53.
    孟子盈,杨倩倩,石玉存,等. HPLC指纹图谱结合化学计量学研究当归土炒前后主要成分变化[J]. 中国药学杂志, 2025, 60(5):522-531.
    林秀敏,张振凌,王胜超,等.白芍饮片的HPLC指纹图谱建立及聚类分析、主成分分析[J]. 中国药房,2019, 30(24):3375-3382.
    Zheng C, Li W T, Yao Y, et al. Quality evaluation of Atractylodis Macrocephalae Rhizoma based on combinative method of HPLC fingerprint, quantitative analysis of multi-components and chemical pattern recognition analysis[J]. Molecules, 2021, 26(23):7124.
    刘宇婷,赵梦薇,王玉霞,等. HPLC指纹图谱和多成分定量结合化学模式识别法对地骨皮饮片的质量评价[J]. 时珍国医国药, 2025, 36(6):1070-1075.
    Ma Q D, Chen X X, Zhang K, et al. Chemical fingerprint analysis for discovering markers and identifying Saussurea involucrata by HPLC coupled with OPLS-DA[J]. J Anal Methods Chem, 2020, 2020:7560710.
    Huang B M, Zha Q L, Chen T B, et al. Discovery of markers for discriminating the age of cultivated ginseng by using UHPLC-QTOF/MS coupled with OPLS-DA[J]. Phytomedicine, 2018, 45:8-17.
    王莹,孙嘉辰,李霞,等.基于建立成分活性权重函数的当归酒炙工艺评价研究[J]. 中草药, 2022, 53(10):3014-3021.
    Liu W J, Xiao K M, Ren L, et al. Leukemia cells apoptosis by a newly discovered heterogeneous polysaccharide from Angelica sinensis(Oliv.)Diels[J]. Carbohydr Polym,2020, 241:116279.
    Liu W J, Li Z Z, Feng C X, et al. The structures of two polysaccharides from Angelica sinensis and their effects on hepatic insulin resistance through blocking RAGE[J]. Carbohydr Polym, 2022, 280:119001.
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    doi: 10.7501/j.issn.0253-2670.2026.01.008
    • 接收时间:2025-09-18
    • 首发时间:2026-09-09
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    2种不同金属材料的力学参数

    Family
    属数
    Number of
    genus
    种数
    Number of
    species
    占总种数比例
    Percentage of
    total species (%)

    Genus
    种数
    Number of
    species
    占总种数比例
    Percentage of total
    species (%)
    鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
    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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