Article(id=1304388121081176258, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388108988997783, articleNumber=null, orderNo=null, doi=10.7501/j.issn.0253-2670.2026.12.025, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1770048000000, receivedDateStr=2026-02-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1788919962424, onlineDateStr=2026-09-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1788919962424, onlineIssueDateStr=2026-09-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1788919962424, creator=13701087609, updateTime=1788919962424, updator=13701087609, issue=Issue{id=1304388108988997783, tenantId=1146029695717560320, journalId=1302319053441957962, year='2026', volume='57', issue='12', pageStart='4509', pageEnd='4948', issueExtLink='null', onlineDate='null', pubDate='1782576000000', pubDateStr='2026-06-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1788919959542, creator='13701087609', updateTime=1788923461082, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1304402795579330582, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388108988997783, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1304402795579330583, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388108988997783, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4835, endPage=4844, ext={EN=ArticleExt(id=1304388121399943364, articleId=1304388121081176258, tenantId=1146029695717560320, journalId=1302319053441957962, language=EN, title=Quality evaluation of Rehmannia glutinosa leaves from various origins by HPLC fingerprinting and multi-component quantification combined with chemometric analysis, columnId=null, journalTitle=Chinese Traditional and Herbal Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=Objective To establish a fingerprinting method and multi-component quantification approach for Rehmannia glutinosa leaves from different geographical origins, and to evaluate the quality of these samples using chemometric analysis. Methods The HPLC fingerprint of R. glutinosa leaves was developed and analyzed for similarity using the Traditional Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System (Version 2012.130723). Chemical constituents were identified and quantified by comparison with reference standards. Hierarchical clustering analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed using Origin 2025, IBM SPSS Statistics 27.0, and SIMCA 14.1 software to evaluate the quality of R. glutinosa leaves samples and screen for differential markers. Results A characteristic HPLC fingerprint of R. glutinosa leaves from different origins was developed. In this fingerprint, 19 common peaks were calibrated, and 13 components were unequivocally identified using reference standards. The similarity evaluation of the 23 batches yielded results ranging from 0.879 to 0.997. The cluster heatmap analysis demonstrated a clear classification, dividing the samples into two groups. Principal component analysis (PCA) yielded five principal components with a cumulative variance contribution rate of 83.545%, and the score plot revealed that samples originating from Henan province clustered separately, suggesting their superior quality. Subsequently, OPLS-DA was employed, which successfully screened four compounds-catalpol, acteoside, luteolin, and apigenin-as critical markers for quality discrimination. The quantitative analysis showed that the contents of these markers were 25.474—61.784 mg/g, 11.633—47.462 mg/g, 0.096—0.848 mg/g, and 0.100—1.268 mg/g, respectively. Conclusion The developed method, integrating HPLC fingerprinting and multi-component assay, proved to be simple, accurate, and reproducible. It can systematically reflect the differences among samples of R. glutinosa leaves from different producing areas, thereby providing a reference for their quality control., authors=ZHANG Yiming, ZHANG Yumei, LIU Qianxi, WANG Fengjiao, LIU Mengyun, KANG Le, CAO Yangang, FENG Weisheng, LI Kai, LI Hongwei, authorsList=ZHANG Yiming, ZHANG Yumei, LIU Qianxi, WANG Fengjiao, LIU Mengyun, KANG Le, CAO Yangang, FENG Weisheng, LI Kai, LI Hongwei, 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=1304388121324445891, articleId=1304388121081176258, tenantId=1146029695717560320, journalId=1302319053441957962, language=CN, title=基于HPLC指纹图谱和多成分定量结合化学模式识别法评价不同产地地黄叶的质量, columnId=1304140203967410414, journalTitle=中草药, columnName=药材与资源, runingTitle=null, highlight=null, articleAbstract=目的 建立不同产地地黄R. glutinosa叶的指纹图谱及多成分含量测定方法,结合化学模式识别法评价不同产地地黄叶的质量。方法 采用中药色谱指纹图谱相似度评价系统(2012.130723版本)建立地黄叶高效液相色谱法(HPLC)指纹图谱并分析相似度,同时通过对照品指认化学成分并进行定量测定。通过Origin 2025、IBM SPSS Statistics 27.0和SIMCA 14.1软件进行聚类分析(hierarchical clustering analysis,HCA)、主成分分析(principal component analysis,PCA)及正交偏最小二乘法判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA),对地黄叶饮片进行质量评价,筛选差异性标志物。结果 建立了不同产地地黄叶HPLC指纹图谱,共标定了19个共有色谱峰,指认出13个成分;23批样品相似度在0.879~0.997;聚类热图分析将23批地黄叶分为2类;PCA提取了5个主成分,其方差累积贡献率为83.545%,且结果显示河南产地的地黄叶质量最优;OPLS-DA筛选出梓醇、毛蕊花糖苷、木犀草素、芹菜素4个质量差异标志物,4种成分的质量分数分别为25.474~61.784 mg/g、11.633~47.462 mg/g、0.096~0.848 mg/g、0.100~1.268 mg/g。结论 建立的地黄叶HPLC指纹图谱及多成分含量测定方法简单、准确、重复性好,能系统地反映不同产地的地黄叶样品差异,可为其质量控制提供参考。, authors=张壹明1, 张玉梅1, 刘仟禧1, 王凤娇1, 刘梦云1,2,3, 康乐1,2,3, 曹彦刚1,2,3, 冯卫生1,2,3, 李凯1,2,3, 李红伟1,2,3, authorsList=张壹明, 张玉梅, 刘仟禧, 王凤娇, 刘梦云, 康乐, 曹彦刚, 冯卫生, 李凯, 李红伟, authorCompany=1 河南中医药大学药学院,河南 郑州 450046;
2 豫药全产业链研发河南省协同创新中心,河南 郑州 450046;
3 河南省中药特色炮制技术工程研究中心,河南 郑州 450046, correspAuthors=刘梦云, authorNote=张壹明: 张壹明,硕士研究生,研究方向为中药炮制机制及饮片标准化。E-mail:15956438411@163.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=KaocT2RxiBERUTZokV55kg==, pdfFileSize=1790288, 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=河南省科技研发计划联合基金(优势学科培育类)项目 (242301420021); 河南省杰出青年科学基金资助项目 (252300421028); 河南省高校科技创新团队支持计划 (26IRTSTHN018))}, authors=[Author(id=1307452387455689462, tenantId=1146029695717560320, journalId=null, articleId=1304388121081176258, orderNo=null, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=null, email=null, emailSecond=null, emailThird=null, correspondingAuthor=null, 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detailUrlEn=https://castjournals.cast.org.cn/joweb/zcy/EN/10.7501/j.issn.0253-2670.2026.12.025, pdfUrlCn=https://castjournals.cast.org.cn/joweb/zcy/CN/PDF/10.7501/j.issn.0253-2670.2026.12.025, pdfUrlEn=https://castjournals.cast.org.cn/joweb/zcy/EN/PDF/10.7501/j.issn.0253-2670.2026.12.025, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, previewStatus=0, delFlag=0, hasFullText=0, orderTime=1788919962424, fullTextJson=null, articleText=null, reference=河南省药品监督管理局. 河南省中药饮片炮制规范[M]. 郑州: 河南科学技术出版社, 2022: 282.
郭敏, 杜跃亮, 林静. 地黄叶总苷胶囊治疗糖尿病肾病的随机对照研究[J]. 辽宁中医杂志, 2024, 51(9): 67-71.
张壹明, 闫洪建, 李三原, 等. 地黄叶化学成分、药理作用与药性和功能主治的关联性研究[J]. 中华中医药学刊, 2026, 44(5): 148-153.
程梦娟, 耿晓桐, 张宝, 等. 不同种质怀地黄生育期根际土壤挥发性有机物变化分析[J]. 西北农林科技大学学报: 自然科学版, 2022, 50(10): 87-96.
郭晨宁, 李晶晶, 杨灏, 等. 涝渍胁迫对地黄生理生化特性及活性成分的影响[J]. 江苏农业科学, 2025, 53(11): 118-126.
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.
朱静平, 刘梦云, 贾梦雪, 等. 基于HPLC指纹图谱和多成分定量结合化学模式识别法评价不同产地小茴香饮片质量[J]. 中草药, 2024, 55(24): 8564-8573.
罗梦香, 张森, 周旺, 等. 地黄连作障碍研究进展[J]. 河南农业大学学报, 2024, 58(1): 15-22.
田梦平, 杜权, 谢小龙, 等. 地黄资源化学研究进展[J]. 安徽农业科学, 2021, 49(9): 22-24.
Ren L, Xu Y P, Qin G J, et al. Effects of water extracts of Rehmannia glutinosa on antioxidant system of Nrf2 in paraquat-induced insulin resistance diabetic rat model [J]. Exp Ther Med, 2017: 14(6): 5847-5850.
Li X Y, Liu Z L, He Z X, et al. Acteoside protects podocyte against apoptosis through regulating AKT/GSK-3β signaling pathway in db/db mice [J]. BMC Endocr Disord, 2023, 23(1): 230.
Zhu Y, Wang Y M, Jia Y C, et al. Catalpol promotes the osteogenic differentiation of bone marrow mesenchymal stem cells via the Wnt/β-catenin pathway [J]. Stem Cell Res Ther, 2019, 10(1): 37.
Li S M, Cui Y J, Li M, et al. Acteoside derived from Cistanche improves glucocorticoid-induced osteoporosis by activating PI3K/AKT/mTOR pathway [J]. J Investig Surg, 2023, 36(1): 2154578.
Zhang H, Wu Z M, Yang Y P, et al. Catalpol ameliorates LPS-induced endometritis by inhibiting inflammation and TLR4/NF-κB signaling [J]. J Zhejiang Univ SCIENCE B, 2019, 20(10): 816-827.
Wang J, Ma C H, Wang S M. Effects of acteoside on lipopolysaccharide-induced inflammation in acute lung injury via regulation of NF-κB pathway in vivo and in vitro [J]. Toxicol Appl Pharmacol, 2015, 285(2): 128-135.
王晶晶, 倪睿, 李紫薇, 等. 负载木犀草素纳米粒的壳聚糖/海藻酸钠水凝胶伤口敷料研究[J]. 中国药学杂志, 2025, 60(8): 856-865.
Si N, Kanazawa H, Okuyama K, et al. Involvement of catechols in acteoside in the activation of promatrix metalloproteinase-2 and membrane type-1-matrix metalloproteinase expression via a phosphatidylinositol-3-kinase pathway in human dermal fibroblasts [J]. Biol Pharm Bull, 2018, 41(10): 1530-1536.)
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基于HPLC指纹图谱和多成分定量结合化学模式识别法评价不同产地地黄叶的质量
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张壹明, 张玉梅, 刘仟禧, 王凤娇, 刘梦云, 康乐, 曹彦刚, 冯卫生, 李凯, 李红伟
中草药 | 药材与资源 2026,57(12): 4835-4844
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中草药 |药材与资源 2026 , 57 (12) : 4835 -4844
基于HPLC指纹图谱和多成分定量结合化学模式识别法评价不同产地地黄叶的质量
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张壹明, 张玉梅, 刘仟禧, 王凤娇, 刘梦云, 康乐, 曹彦刚, 冯卫生, 李凯, 李红伟
作者信息
通讯作者:
刘梦云
作者简介:
张壹明: 张壹明,硕士研究生,研究方向为中药炮制机制及饮片标准化。E-mail:15956438411@163.com
Quality evaluation of Rehmannia glutinosa leaves from various origins by HPLC fingerprinting and multi-component quantification combined with chemometric analysis
ZHANG Yiming, ZHANG Yumei, LIU Qianxi, WANG Fengjiao, LIU Mengyun, KANG Le, CAO Yangang, FENG Weisheng, LI Kai, LI Hongwei
Affiliations
doi: 10.7501/j.issn.0253-2670.2026.12.025
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目的 建立不同产地地黄R. glutinosa叶的指纹图谱及多成分含量测定方法,结合化学模式识别法评价不同产地地黄叶的质量。方法 采用中药色谱指纹图谱相似度评价系统(2012.130723版本)建立地黄叶高效液相色谱法(HPLC)指纹图谱并分析相似度,同时通过对照品指认化学成分并进行定量测定。通过Origin 2025、IBM SPSS Statistics 27.0和SIMCA 14.1软件进行聚类分析(hierarchical clustering analysis,HCA)、主成分分析(principal component analysis,PCA)及正交偏最小二乘法判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA),对地黄叶饮片进行质量评价,筛选差异性标志物。结果 建立了不同产地地黄叶HPLC指纹图谱,共标定了19个共有色谱峰,指认出13个成分;23批样品相似度在0.879~0.997;聚类热图分析将23批地黄叶分为2类;PCA提取了5个主成分,其方差累积贡献率为83.545%,且结果显示河南产地的地黄叶质量最优;OPLS-DA筛选出梓醇、毛蕊花糖苷、木犀草素、芹菜素4个质量差异标志物,4种成分的质量分数分别为25.474~61.784 mg/g、11.633~47.462 mg/g、0.096~0.848 mg/g、0.100~1.268 mg/g。结论 建立的地黄叶HPLC指纹图谱及多成分含量测定方法简单、准确、重复性好,能系统地反映不同产地的地黄叶样品差异,可为其质量控制提供参考。
地黄  /  HPLC  /  指纹图谱  /  梓醇  /  毛蕊花糖苷  /  木犀草素  /  芹菜素  /  化学模式识别  /  质量评价  /  化学计量学
Objective To establish a fingerprinting method and multi-component quantification approach for Rehmannia glutinosa leaves from different geographical origins, and to evaluate the quality of these samples using chemometric analysis. Methods The HPLC fingerprint of R. glutinosa leaves was developed and analyzed for similarity using the Traditional Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System (Version 2012.130723). Chemical constituents were identified and quantified by comparison with reference standards. Hierarchical clustering analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed using Origin 2025, IBM SPSS Statistics 27.0, and SIMCA 14.1 software to evaluate the quality of R. glutinosa leaves samples and screen for differential markers. Results A characteristic HPLC fingerprint of R. glutinosa leaves from different origins was developed. In this fingerprint, 19 common peaks were calibrated, and 13 components were unequivocally identified using reference standards. The similarity evaluation of the 23 batches yielded results ranging from 0.879 to 0.997. The cluster heatmap analysis demonstrated a clear classification, dividing the samples into two groups. Principal component analysis (PCA) yielded five principal components with a cumulative variance contribution rate of 83.545%, and the score plot revealed that samples originating from Henan province clustered separately, suggesting their superior quality. Subsequently, OPLS-DA was employed, which successfully screened four compounds-catalpol, acteoside, luteolin, and apigenin-as critical markers for quality discrimination. The quantitative analysis showed that the contents of these markers were 25.474—61.784 mg/g, 11.633—47.462 mg/g, 0.096—0.848 mg/g, and 0.100—1.268 mg/g, respectively. Conclusion The developed method, integrating HPLC fingerprinting and multi-component assay, proved to be simple, accurate, and reproducible. It can systematically reflect the differences among samples of R. glutinosa leaves from different producing areas, thereby providing a reference for their quality control.
Rehmannia glutinosa Libosch.  /  HPLC  /  fingerprint  /  catalpol  /  acteoside  /  luteolin  /  apigenin  /  chemometric analysis  /  quality evaluation  /  chemometrics
张壹明, 张玉梅, 刘仟禧, 王凤娇, 刘梦云, 康乐, 曹彦刚, 冯卫生, 李凯, 李红伟. 基于HPLC指纹图谱和多成分定量结合化学模式识别法评价不同产地地黄叶的质量. 中草药, 2026 , 57 (12) : 4835 -4844 . DOI: 10.7501/j.issn.0253-2670.2026.12.025
ZHANG Yiming, ZHANG Yumei, LIU Qianxi, WANG Fengjiao, LIU Mengyun, KANG Le, CAO Yangang, FENG Weisheng, LI Kai, LI Hongwei. Quality evaluation of Rehmannia glutinosa leaves from various origins by HPLC fingerprinting and multi-component quantification combined with chemometric analysis[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (12) : 4835 -4844 . DOI: 10.7501/j.issn.0253-2670.2026.12.025

    河南省科技研发计划联合基金(优势学科培育类)项目 (242301420021); 河南省杰出青年科学基金资助项目 (252300421028); 河南省高校科技创新团队支持计划 (26IRTSTHN018)

参考文献 引证文献
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河南省药品监督管理局. 河南省中药饮片炮制规范[M]. 郑州: 河南科学技术出版社, 2022: 282.
郭敏, 杜跃亮, 林静. 地黄叶总苷胶囊治疗糖尿病肾病的随机对照研究[J]. 辽宁中医杂志, 2024, 51(9): 67-71.
张壹明, 闫洪建, 李三原, 等. 地黄叶化学成分、药理作用与药性和功能主治的关联性研究[J]. 中华中医药学刊, 2026, 44(5): 148-153.
程梦娟, 耿晓桐, 张宝, 等. 不同种质怀地黄生育期根际土壤挥发性有机物变化分析[J]. 西北农林科技大学学报: 自然科学版, 2022, 50(10): 87-96.
郭晨宁, 李晶晶, 杨灏, 等. 涝渍胁迫对地黄生理生化特性及活性成分的影响[J]. 江苏农业科学, 2025, 53(11): 118-126.
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.
朱静平, 刘梦云, 贾梦雪, 等. 基于HPLC指纹图谱和多成分定量结合化学模式识别法评价不同产地小茴香饮片质量[J]. 中草药, 2024, 55(24): 8564-8573.
罗梦香, 张森, 周旺, 等. 地黄连作障碍研究进展[J]. 河南农业大学学报, 2024, 58(1): 15-22.
田梦平, 杜权, 谢小龙, 等. 地黄资源化学研究进展[J]. 安徽农业科学, 2021, 49(9): 22-24.
Ren L, Xu Y P, Qin G J, et al. Effects of water extracts of Rehmannia glutinosa on antioxidant system of Nrf2 in paraquat-induced insulin resistance diabetic rat model [J]. Exp Ther Med, 2017: 14(6): 5847-5850.
Li X Y, Liu Z L, He Z X, et al. Acteoside protects podocyte against apoptosis through regulating AKT/GSK-3β signaling pathway in db/db mice [J]. BMC Endocr Disord, 2023, 23(1): 230.
Zhu Y, Wang Y M, Jia Y C, et al. Catalpol promotes the osteogenic differentiation of bone marrow mesenchymal stem cells via the Wnt/β-catenin pathway [J]. Stem Cell Res Ther, 2019, 10(1): 37.
Li S M, Cui Y J, Li M, et al. Acteoside derived from Cistanche improves glucocorticoid-induced osteoporosis by activating PI3K/AKT/mTOR pathway [J]. J Investig Surg, 2023, 36(1): 2154578.
Zhang H, Wu Z M, Yang Y P, et al. Catalpol ameliorates LPS-induced endometritis by inhibiting inflammation and TLR4/NF-κB signaling [J]. J Zhejiang Univ SCIENCE B, 2019, 20(10): 816-827.
Wang J, Ma C H, Wang S M. Effects of acteoside on lipopolysaccharide-induced inflammation in acute lung injury via regulation of NF-κB pathway in vivo and in vitro [J]. Toxicol Appl Pharmacol, 2015, 285(2): 128-135.
王晶晶, 倪睿, 李紫薇, 等. 负载木犀草素纳米粒的壳聚糖/海藻酸钠水凝胶伤口敷料研究[J]. 中国药学杂志, 2025, 60(8): 856-865.
Si N, Kanazawa H, Okuyama K, et al. Involvement of catechols in acteoside in the activation of promatrix metalloproteinase-2 and membrane type-1-matrix metalloproteinase expression via a phosphatidylinositol-3-kinase pathway in human dermal fibroblasts [J]. Biol Pharm Bull, 2018, 41(10): 1530-1536.
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doi: 10.7501/j.issn.0253-2670.2026.12.025
  • 接收时间:2026-02-03
  • 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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