Article(id=1304414859014202284, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304414858296971266, articleNumber=null, orderNo=null, doi=10.7501/j.issn.0253-2670.2026.06.007, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1761840000000, receivedDateStr=2025-10-31, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1788926337244, onlineDateStr=2026-09-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1788926337244, onlineIssueDateStr=2026-09-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1788926337244, creator=13701087609, updateTime=1788926337244, updator=13701087609, issue=Issue{id=1304414858296971266, tenantId=1146029695717560320, journalId=1302319053441957962, year='2026', volume='57', issue='6', pageStart='2009', pageEnd='2444', issueExtLink='null', onlineDate='null', pubDate='1774627200000', pubDateStr='2026-03-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1788926337074, creator='13701087609', updateTime=1788926665348, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1304416235240841997, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304414858296971266, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1304416235240841998, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304414858296971266, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2075, endPage=2085, ext={EN=ArticleExt(id=1304414860863890351, articleId=1304414859014202284, tenantId=1146029695717560320, journalId=1302319053441957962, language=EN, title=Quality evaluation of Zhishi Xiebai Guizhi Decoction benchmark samples based on multidimensional fusion of physical, chemical and taste information, columnId=null, journalTitle=Chinese Traditional and Herbal Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=Objective To establish the physical, chemical, and taste fingerprints of 15 batches of the classic traditional Chinese medicine formula Zhishi Xiebai Guizhi Decoction (ZXGD, 枳实薤白桂枝汤) benchmark samples, as well as a method for determining the content of three index components. Methods Fifteen batches of ZXGD benchmark samples were prepared. A physical fingerprint was constructed using six physical parameters: solid content rate, conductivity, refractive index, surface tension, density, and pH value. Similarity evaluation, principal component analysis (PCA), and cluster analysis were employed for analytical evaluation of this physical fingerprint. HPLC was used to establish the chemical fingerprint of ZXGD, followed by similarity evaluation of the chemical fingerprint. Additionally, the contents of three index components (cinnamic acid, cinnamaldehyde, and synephrine) were determined via HPLC. Electronic tongue technology was applied to analyze the taste of ZXGD, construct a taste radar chart, and generate a heatmap to analyze the correlation between taste, chemical component contents, and physical properties. Results The similarity between the physical fingerprint of each of the 15 batches of benchmark samples and the control fingerprint was greater than 0.9. Results of hierarchical cluster analysis showed that the 15 batches of samples were clustered into two groups: one group included samples S1, S6, S11, S12, and S15, while the remaining benchmark samples formed the other group. Cluster analysis based on the contents of the three index components showed results consistent with those of the physical fingerprint analysis. The heatmap revealed that cinnamaldehyde and synephrine were strongly correlated with bitterness, bitter aftertaste, saltiness, and alkaline bitter aftertaste (P < 0.05); pH value was significantly associated with sourness and richness; while synephrine exhibited correlation with electrical conductivity, refractive index, and pH value. Conclusion There is a correlation among the physical, chemical and taste attributes of ZXGD benchmark samples. The established “physical-chemical-sensory” multi-dimensional evaluation model can more comprehensively reflect the overall quality, providing a scientific basis for the quality control of ZXGD benchmark samples and the development of compound preparations., authors=LI Xiaomei, WANG Xuesong, TAO Zhen, YAO Xue, XU Xiaolong, YIN Hongmei, WANG Zhenzhong, authorsList=LI Xiaomei, WANG Xuesong, TAO Zhen, YAO Xue, XU Xiaolong, YIN Hongmei, WANG 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=1304414859207140269, articleId=1304414859014202284, tenantId=1146029695717560320, journalId=1302319053441957962, language=CN, title=基于物理-化学-味觉多维信息融合的枳实薤白桂枝汤基准样品质量评价, columnId=1304140189132149234, journalTitle=中草药, columnName=药剂与工艺, runingTitle=null, highlight=null, articleAbstract=目的 建立15批经典名方枳实薤白桂枝汤（Zhishi Xiebai Guizhi Decoction，ZXGD）基准样品的物理、化学、味觉指纹图谱及3种指标成分的含量测定方法。方法 制备15批ZXGD基准样品，以固含量、电导率、折光率、表面张力、密度及pH值6个物理参数构建物理指纹图谱，使用相似度评价、主成分分析和聚类分析对其进行分析评价；采用HPLC法建立ZXGD基准样品的化学指纹图谱，并进行相似度评价，对肉桂酸、桂皮醛和辛弗林3种指标成分进行含量测定；采用电子舌技术对ZXGD基准样品的味觉进行分析，构建味觉雷达图，并绘制热图分析味觉与化学指标成分含量、物理属性的相关性。结果 15批ZXGD基准样品的物理指纹图谱与对照图谱相似度均大于0.9；物理属性的聚类结果显示，15批ZXGD基准样品聚为2类，S1、S6、S11、S12、S15聚为一类，其余基准样品聚为一类；3个指标成分含量的聚类结果与物理指纹图谱一致；热图分析显示，桂皮醛、辛弗林与苦味、苦味回味、咸味、碱性苦味回味相关性较强（P ＜0.05）；pH值与酸味、丰富性显著相关；辛弗林与电导率、折光率、pH值有相关性。结论 ZXGD基准样品的物理、化学与味觉属性间具有相关性，建立的“物理-化学-味觉”多维评价模式能更全面地反映整体质量，为ZXGD基准样品的质量控制和复方制剂开发提供科学依据。, authors=李小美1,2 , 王雪松3,4 , 陶振3,4 , 姚雪2,3,4 , 徐小龙5 , 殷洪梅2,3,4 , 王振中1,2,4 , authorsList=李小美, 王雪松, 陶振, 姚雪, 徐小龙, 殷洪梅, 王振中, authorCompany=1 中药制药过程控制与智能制造技术全国重点实验室(江苏康缘药业股份有限公司/南京中医药大学), 江苏 南京 211112;
中草药
|药剂与工艺
2026
, 57
(6) :
2075
-2085
基于物理-化学-味觉多维信息融合的枳实薤白桂枝汤基准样品质量评价
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李小美1,2 , 王雪松3,4 , 陶振3,4 , 姚雪2,3,4 , 徐小龙5 , 殷洪梅2,3,4 , 王振中1,2,4
作者信息
1 中药制药过程控制与智能制造技术全国重点实验室(江苏康缘药业股份有限公司/南京中医药大学), 江苏 南京 211112;
作者简介:
李小美: 李小美(2001-),女,硕士研究生,研究方向为药物制剂与产品研发。E-mail:leegrant2001@163.com
Quality evaluation of Zhishi Xiebai Guizhi Decoction benchmark samples based on multidimensional fusion of physical, chemical and taste information
LI Xiaomei, WANG Xuesong, TAO Zhen, YAO Xue, XU Xiaolong, YIN Hongmei, WANG Zhenzhong
Affiliations
doi: 10.7501/j.issn.0253-2670.2026.06.007
文章导航
目的 建立15批经典名方枳实薤白桂枝汤（Zhishi Xiebai Guizhi Decoction，ZXGD）基准样品的物理、化学、味觉指纹图谱及3种指标成分的含量测定方法。方法 制备15批ZXGD基准样品，以固含量、电导率、折光率、表面张力、密度及pH值6个物理参数构建物理指纹图谱，使用相似度评价、主成分分析和聚类分析对其进行分析评价；采用HPLC法建立ZXGD基准样品的化学指纹图谱，并进行相似度评价，对肉桂酸、桂皮醛和辛弗林3种指标成分进行含量测定；采用电子舌技术对ZXGD基准样品的味觉进行分析，构建味觉雷达图，并绘制热图分析味觉与化学指标成分含量、物理属性的相关性。结果 15批ZXGD基准样品的物理指纹图谱与对照图谱相似度均大于0.9；物理属性的聚类结果显示，15批ZXGD基准样品聚为2类，S1、S6、S11、S12、S15聚为一类，其余基准样品聚为一类；3个指标成分含量的聚类结果与物理指纹图谱一致；热图分析显示，桂皮醛、辛弗林与苦味、苦味回味、咸味、碱性苦味回味相关性较强（P ＜0.05）；pH值与酸味、丰富性显著相关；辛弗林与电导率、折光率、pH值有相关性。结论 ZXGD基准样品的物理、化学与味觉属性间具有相关性，建立的“物理-化学-味觉”多维评价模式能更全面地反映整体质量，为ZXGD基准样品的质量控制和复方制剂开发提供科学依据。
枳实薤白桂枝汤
/
物理指纹图谱
/
化学指纹图谱
/
电子舌
/
质量控制
/
多维信息融合
/
基准样品
/
肉桂酸
/
桂皮醛
/
辛弗林
Objective To establish the physical, chemical, and taste fingerprints of 15 batches of the classic traditional Chinese medicine formula Zhishi Xiebai Guizhi Decoction (ZXGD, 枳实薤白桂枝汤) benchmark samples, as well as a method for determining the content of three index components. Methods Fifteen batches of ZXGD benchmark samples were prepared. A physical fingerprint was constructed using six physical parameters: solid content rate, conductivity, refractive index, surface tension, density, and pH value. Similarity evaluation, principal component analysis (PCA), and cluster analysis were employed for analytical evaluation of this physical fingerprint. HPLC was used to establish the chemical fingerprint of ZXGD, followed by similarity evaluation of the chemical fingerprint. Additionally, the contents of three index components (cinnamic acid, cinnamaldehyde, and synephrine) were determined via HPLC. Electronic tongue technology was applied to analyze the taste of ZXGD, construct a taste radar chart, and generate a heatmap to analyze the correlation between taste, chemical component contents, and physical properties. Results The similarity between the physical fingerprint of each of the 15 batches of benchmark samples and the control fingerprint was greater than 0.9. Results of hierarchical cluster analysis showed that the 15 batches of samples were clustered into two groups: one group included samples S1, S6, S11, S12, and S15, while the remaining benchmark samples formed the other group. Cluster analysis based on the contents of the three index components showed results consistent with those of the physical fingerprint analysis. The heatmap revealed that cinnamaldehyde and synephrine were strongly correlated with bitterness, bitter aftertaste, saltiness, and alkaline bitter aftertaste (P < 0.05); pH value was significantly associated with sourness and richness; while synephrine exhibited correlation with electrical conductivity, refractive index, and pH value. Conclusion There is a correlation among the physical, chemical and taste attributes of ZXGD benchmark samples. The established “physical-chemical-sensory” multi-dimensional evaluation model can more comprehensively reflect the overall quality, providing a scientific basis for the quality control of ZXGD benchmark samples and the development of compound preparations.
Zhishi Xiebai Guizhi Decoction
/
physical fingerprint
/
chemical fingerprint
/
electronic tongue
/
quality control
/
multidimensional fusion
/
benchmark sample
/
cinnamic acid
/
cinnamaldehyde
/
synephrine
李小美, 王雪松, 陶振, 姚雪, 徐小龙, 殷洪梅, 王振中.
基于物理-化学-味觉多维信息融合的枳实薤白桂枝汤基准样品质量评价.
中草药,
2026
, 57
(6)
: 2075
-2085
.
DOI: 10.7501/j.issn.0253-2670.2026.06.007
LI Xiaomei, WANG Xuesong, TAO Zhen, YAO Xue, XU Xiaolong, YIN Hongmei, WANG Zhenzhong.
Quality evaluation of Zhishi Xiebai Guizhi Decoction benchmark samples based on multidimensional fusion of physical, chemical and taste information[J].
Chinese Traditional and Herbal Drugs ,
2026
, 57
(6)
: 2075
-2085
.
DOI: 10.7501/j.issn.0253-2670.2026.06.007
参考文献
引证文献
陈志强, 张意林, 陈仁寿. 经典名方枳实薤白桂枝汤的古今文献研究[J]. 中国中医基础医学杂志, 2023, 29(9): 1515-1522.
2026年第57卷第6期
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doi: 10.7501/j.issn.0253-2670.2026.06.007
接收时间：2025-10-31
首发时间：2026-09-09
https://castjournals.cast.org.cn/joweb/zcy/CN/10.7501/j.issn.0253-2670.2026.06.007
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2种不同金属材料的力学参数
科 属数 种数 占总种数比例 属 种数 占总种数比例 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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