Article(id=1304388092023042812, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388047747969563, articleNumber=null, orderNo=null, doi=10.7501/j.issn.0253-2670.2026.10.024, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1762012800000, receivedDateStr=2025-11-02, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1788919955496, onlineDateStr=2026-09-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1788919955496, onlineIssueDateStr=2026-09-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1788919955496, creator=13701087609, updateTime=1788919955496, updator=13701087609, issue=Issue{id=1304388047747969563, tenantId=1146029695717560320, journalId=1302319053441957962, year='2026', volume='57', issue='10', pageStart='3685', pageEnd='4088', issueExtLink='null', onlineDate='null', pubDate='1779897600000', pubDateStr='2026-05-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1788919944940, creator='13701087609', updateTime=1788923403989, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1304402556332037104, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388047747969563, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1304402556332037105, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388047747969563, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3963, endPage=3973, ext={EN=ArticleExt(id=1304388092295672574, articleId=1304388092023042812, tenantId=1146029695717560320, journalId=1302319053441957962, language=EN, title=Comprehensive quality evaluation of Lilii Bulbus from different regions based on intelligent sensory combined with chemical composition, columnId=null, journalTitle=Chinese Traditional and Herbal Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=Objective To establish a detection method that combines the appearance characteristics (color, odor, taste) and internal chemical components of Baihe (Lilii Bulbus ) to conduct a comprehensive evaluation of the overall quality of lily medicinal materials. Methods Using intelligent sensory technology to detect the color, odor, and taste of 15 batches Lilii Bulbus from the perspectives of vision, smell, and taste. At the same time, HPLC fingerprint spectra and multi-index content determinations were established to compare the content differences of specific components (regaloside C, regaloside A, 2-acetate regaloside A and regaloside E) among medicinal materials from the perspective of chemical composition. Multivariate statistical analysis methods such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) were used to analyze the color, odor, taste, and fingerprint spectra of Lilii Bulbus from different origins, and screen for differential components. Pearson correlation analysis was used to reveal the correlation between appearance color, odor, taste, and exclusive ingredients. Results The results of the colorimeter showed that the colors of the 15 batches of Lilii Bulbus medicinal materials were all bright white and lighter, and Zhejiang and Hunan were whiter than those of Jiangsu. The electronic nose analysis results indicated that sensors W3S, W5C, W6S, and W1S, corresponding to 15 batches of Lilii Bulbus medicinal materials contained relatively high levels of alkanes and aromatic compounds. However, Zhejiang Lilii Bulbus also exhibited elevated hydrides. Electronic tongue results revealed that all taste indicators showed obvious responses except sourness. Intelligent sensory analysis demonstrated that Lilii Bulbus from different regions exhibited significant differences in color, odor and taste. A total of 15 common peaks were identified in the fingerprint spectra. Content determination results indicated obvious quality differences among Lilii Bulbus samples from different origins. Among them, Peak 13, peak 6 (regaloside A) and peak 11 (regaloside E) were the main marker components causing compositional differences of Lilii Bulbus from different producing areas. The correlation analysis results indicated that yellow blue chromaticity(b* ), total color value(E* ab ), W1S, W6S, sweetness, astringency, aftertaste-A in Lilii Bulbus were correlated with regaloside C, regaloside A, 2-acetate regaloside A and regaloside E. Conclusion The method of integrating intelligent sensory technology with chemical composition research for comprehensive quality evaluation of Lilii Bulbus medicinal materials is feasible. It can be used to evaluate the comprehensive quality of Lilii Bulbus from different origins, providing reference for the quality control and application of Lilii Bulbus ., authors=JIANG Xiaoya, LI Ning, ZHANG Zezhao, GAO Le, TIAN Wei, NIU Liying, authorsList=JIANG Xiaoya, LI Ning, ZHANG Zezhao, GAO Le, TIAN Wei, NIU Liying, 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=1304388092220175101, articleId=1304388092023042812, tenantId=1146029695717560320, journalId=1302319053441957962, language=CN, title=基于智能感官结合化学成分的不同产地百合药材综合质量评价, columnId=1304140203967410414, journalTitle=中草药, columnName=药材与资源, runingTitle=null, highlight=null, articleAbstract=目的 建立一种结合百合外观性状(颜色、气味、味道)和内在的化学成分的检测方法,对百合药材进行整体质量的综合评价。方法 利用智能感官技术从视觉、嗅觉和味觉角度检测15批不同产地百合药材的颜色、气味和味道;同时建立HPLC指纹图谱和多指标含量测定,从化学成分角度比较药材之间专属成分(王百合苷C、王百合苷A、2-乙酰王百合苷A、王百合苷E)的含量差异。结合聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)、偏最小二乘法判别分析(partial least squares discriminant analysis,PLS-DA)等多元统计分析方法,对不同产地百合的颜色、气味、味道和指纹图谱进行分析,筛选差异性成分,并利用Pearson相关性分析揭示外观颜色、气味与味道和专属成分之间的相关性。结果 测色仪结果表明15批百合药材的颜色均偏亮白且较浅,且浙江和湖南百合颜色比江苏百合更加洁白。电子鼻结果分析显示,传感器W3S、W5C、W6S、W1S,即15批百合药材均含有较多的烷烃类化合物和芳香类成分,但浙江百合中还含有较多的氢化物。电子舌结果显示,除了酸味,其他的味道均有响应。智能感官结果说明不同产地的百合在颜色、气味和味道均存在差异。指纹图谱中共确定了15个共有峰;含量测定的结果显示不同产地间百合质量存在差异,其中峰13、峰6(王百合苷A)、峰11(王百合苷E)是不同产地百合间成分差异的主要标志性成分。相关性分析结果表明,黄蓝色度(b *)、总色值(E *ab)、传感器W1S、传感器W6S、甜味(Sweetness)、涩味(Astringency)、涩味回味(Aftertaste-A)与王百合苷C、王百合苷A、2-乙酰王百合苷A、王百合苷E之间存在相互关联。结论 智能感官技术关联化学成分研究对百合药材综合质量评价的方法可行,可用于对不同产地百合药材品质的评价,为百合的质量控制及应用提供参考。, authors=姜晓娅1,2,3 , 李宁1,2,3 , 张泽昭1,2,3 , 高乐1,2,3 , 田伟1,2,3 , 牛丽颖1,2,3 , authorsList=姜晓娅, 李宁, 张泽昭, 高乐, 田伟, 牛丽颖, authorCompany=1 河北中医药大学, 河北 石家庄 050091; 2 中药材品质评价与标准化河北省工程研究中心, 河北 石家庄 050091; 3 河北省中药配方颗粒技术创新中心, 河北 石家庄 050091, correspAuthors=牛丽颖, authorNote=姜晓娅: 姜晓娅(1989—),女,硕士研究生,主要从事中药质量控制方面的研究。Tel:18833119160 E-mail:jiangxiaoya@hebcm.edu.cn, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=hr7qfZo2NpcMf3yEmEgRVA==, pdfFileSize=1164417, 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=国家中医药管理局科技项目 (GZY-KJS-2023-030); 河北省重点研发计划项目(中医药创新专项) (23372502D))}, authors=[Author(id=1307431831536689875, tenantId=1146029695717560320, journalId=null, articleId=1304388092023042812, orderNo=null, firstName=null, middleName=null, lastName=null, 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基于智能感官结合化学成分的不同产地百合药材综合质量评价
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姜晓娅, 李宁, 张泽昭, 高乐, 田伟, 牛丽颖
作者信息
通讯作者:
牛丽颖
作者简介:
姜晓娅: 姜晓娅(1989—),女,硕士研究生,主要从事中药质量控制方面的研究。Tel:18833119160 E-mail:jiangxiaoya@hebcm.edu.cn
Comprehensive quality evaluation of Lilii Bulbus from different regions based on intelligent sensory combined with chemical composition
JIANG Xiaoya, LI Ning, ZHANG Zezhao, GAO Le, TIAN Wei, NIU Liying
Affiliations
doi: 10.7501/j.issn.0253-2670.2026.10.024
文章导航
目的 建立一种结合百合外观性状(颜色、气味、味道)和内在的化学成分的检测方法,对百合药材进行整体质量的综合评价。方法 利用智能感官技术从视觉、嗅觉和味觉角度检测15批不同产地百合药材的颜色、气味和味道;同时建立HPLC指纹图谱和多指标含量测定,从化学成分角度比较药材之间专属成分(王百合苷C、王百合苷A、2-乙酰王百合苷A、王百合苷E)的含量差异。结合聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)、偏最小二乘法判别分析(partial least squares discriminant analysis,PLS-DA)等多元统计分析方法,对不同产地百合的颜色、气味、味道和指纹图谱进行分析,筛选差异性成分,并利用Pearson相关性分析揭示外观颜色、气味与味道和专属成分之间的相关性。结果 测色仪结果表明15批百合药材的颜色均偏亮白且较浅,且浙江和湖南百合颜色比江苏百合更加洁白。电子鼻结果分析显示,传感器W3S、W5C、W6S、W1S,即15批百合药材均含有较多的烷烃类化合物和芳香类成分,但浙江百合中还含有较多的氢化物。电子舌结果显示,除了酸味,其他的味道均有响应。智能感官结果说明不同产地的百合在颜色、气味和味道均存在差异。指纹图谱中共确定了15个共有峰;含量测定的结果显示不同产地间百合质量存在差异,其中峰13、峰6(王百合苷A)、峰11(王百合苷E)是不同产地百合间成分差异的主要标志性成分。相关性分析结果表明,黄蓝色度(b *)、总色值(E *ab)、传感器W1S、传感器W6S、甜味(Sweetness)、涩味(Astringency)、涩味回味(Aftertaste-A)与王百合苷C、王百合苷A、2-乙酰王百合苷A、王百合苷E之间存在相互关联。结论 智能感官技术关联化学成分研究对百合药材综合质量评价的方法可行,可用于对不同产地百合药材品质的评价,为百合的质量控制及应用提供参考。
百合药材
/
综合质量评价
/
辨状论质
/
智能感官技术
/
高效液相色谱法
/
多元统计分析
/
王百合苷C
/
王百合苷A
/
2-乙酰王百合苷A
/
王百合苷E
Objective To establish a detection method that combines the appearance characteristics (color, odor, taste) and internal chemical components of Baihe (Lilii Bulbus ) to conduct a comprehensive evaluation of the overall quality of lily medicinal materials. Methods Using intelligent sensory technology to detect the color, odor, and taste of 15 batches Lilii Bulbus from the perspectives of vision, smell, and taste. At the same time, HPLC fingerprint spectra and multi-index content determinations were established to compare the content differences of specific components (regaloside C, regaloside A, 2-acetate regaloside A and regaloside E) among medicinal materials from the perspective of chemical composition. Multivariate statistical analysis methods such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) were used to analyze the color, odor, taste, and fingerprint spectra of Lilii Bulbus from different origins, and screen for differential components. Pearson correlation analysis was used to reveal the correlation between appearance color, odor, taste, and exclusive ingredients. Results The results of the colorimeter showed that the colors of the 15 batches of Lilii Bulbus medicinal materials were all bright white and lighter, and Zhejiang and Hunan were whiter than those of Jiangsu. The electronic nose analysis results indicated that sensors W3S, W5C, W6S, and W1S, corresponding to 15 batches of Lilii Bulbus medicinal materials contained relatively high levels of alkanes and aromatic compounds. However, Zhejiang Lilii Bulbus also exhibited elevated hydrides. Electronic tongue results revealed that all taste indicators showed obvious responses except sourness. Intelligent sensory analysis demonstrated that Lilii Bulbus from different regions exhibited significant differences in color, odor and taste. A total of 15 common peaks were identified in the fingerprint spectra. Content determination results indicated obvious quality differences among Lilii Bulbus samples from different origins. Among them, Peak 13, peak 6 (regaloside A) and peak 11 (regaloside E) were the main marker components causing compositional differences of Lilii Bulbus from different producing areas. The correlation analysis results indicated that yellow blue chromaticity(b* ), total color value(E* ab ), W1S, W6S, sweetness, astringency, aftertaste-A in Lilii Bulbus were correlated with regaloside C, regaloside A, 2-acetate regaloside A and regaloside E. Conclusion The method of integrating intelligent sensory technology with chemical composition research for comprehensive quality evaluation of Lilii Bulbus medicinal materials is feasible. It can be used to evaluate the comprehensive quality of Lilii Bulbus from different origins, providing reference for the quality control and application of Lilii Bulbus .
Lilii Bulbus
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comprehensive quality evaluation
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quality evaluation through morphological identification
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intelligent sensory technology
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HPLC
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multivariate statistical analysis
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regaloside C
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regaloside A
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2-acetate regaloside A
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regaloside E
姜晓娅, 李宁, 张泽昭, 高乐, 田伟, 牛丽颖.
基于智能感官结合化学成分的不同产地百合药材综合质量评价.
中草药,
2026
, 57
(10)
: 3963
-3973
.
DOI: 10.7501/j.issn.0253-2670.2026.10.024
JIANG Xiaoya, LI Ning, ZHANG Zezhao, GAO Le, TIAN Wei, NIU Liying.
Comprehensive quality evaluation of Lilii Bulbus from different regions based on intelligent sensory combined with chemical composition[J].
Chinese Traditional and Herbal Drugs ,
2026
, 57
(10)
: 3963
-3973
.
DOI: 10.7501/j.issn.0253-2670.2026.10.024
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2026年第57卷第10期
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doi: 10.7501/j.issn.0253-2670.2026.10.024
接收时间:2025-11-02
首发时间:2026-09-09
https://castjournals.cast.org.cn/joweb/zcy/CN/10.7501/j.issn.0253-2670.2026.10.024
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2种不同金属材料的力学参数
科 Family 属数 Number of genus 种数 Number of species 占总种数比例 Percentage of total species (%) 属 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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