Article(id=1304388067415057319, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388049975137100, articleNumber=null, orderNo=null, doi=10.7501/j.issn.0253-2670.2026.11.005, 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=1788919949630, onlineDateStr=2026-09-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1788919949630, onlineIssueDateStr=2026-09-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1788919949630, creator=13701087609, updateTime=1788919949630, updator=13701087609, issue=Issue{id=1304388049975137100, tenantId=1146029695717560320, journalId=1302319053441957962, year='2026', volume='57', issue='11', pageStart='4089', pageEnd='4508', issueExtLink='null', onlineDate='null', pubDate='1781193600000', pubDateStr='2026-06-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1788919945471, creator='13701087609', updateTime=1788923432386, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1304402675202805770, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388049975137100, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1304402675207000075, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304388049975137100, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4124, endPage=4134, ext={EN=ArticleExt(id=1304388069298299819, articleId=1304388067415057319, tenantId=1146029695717560320, journalId=1302319053441957962, language=EN, title=Optimization of volatile oil extraction and inclusion process from classical formula Dihuang Yinzi based on QbD and AHP-entropy weight method, columnId=null, journalTitle=Chinese Traditional and Herbal Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=Objective To optimize the extraction and β-cyclodextrin (β-CD) inclusion process for the volatile oil from the classical formula Dihuang Yinzi (地黄饮子) based on the quality by design (QbD) concept and the analytic hierarchy process-entropy weight (AHP-entropy) method. Methods Failure mode and effects analysis (FMEA) was employed for risk identification in the volatile oil extraction process. Heating time, material-to-liquid ratio, and soaking time were determined as the critical process parameters (CPPs), while cinnamaldehyde content, β-asarone content, and volatile oil extraction yield were defined as the critical quality attributes (CQAs). On the basis of single-factor tests, the Box-Behnken design-response surface methodology (BBD-RSM) was used for process optimization. The AHP-entropy weight method was applied to calculate a comprehensive score for the CQAs, which was then used to establish and validate an optimized design space. The inclusion process of volatile oil was investigated using the saturated aqueous solution method. The inclusion conditions were comprehensively optimized through orthogonal experimental design combined with the AHP-entropy weight method for multi-index evaluation. Finally, the optimal inclusion process parameters were determined and validated. Results The optimized volatile oil extraction process was as follows: soaking for 30 to 45 min, adding 9- to 10-fold volume of water, and extracting for 3.0 to 3.5 h. The optimal inclusion process parameters were: inclusion time of 2.0 h, β-cyclodextrin to volatile oil ratio of 10:1, and inclusion temperature of 30 ℃. Conclusion The volatile oil extraction and inclusion processes optimized based on the QbD concept and the AHP-entropy weight method can reliably ensure a stable extraction yield and consistent content of key active components. The resulting inclusion complex exhibits excellent quality. This study provides reliable data support and a solid process foundation for the industrial production and development of related Chinese medicinal preparations, while also offering a feasible pathway for the modern dosage form development of classical formulas., authors=WANG Xulong, JING Caifang, XIN Yanli, LIU Yan, LI Qinqing, HE Wenbin, ZHANG Junlong, authorsList=WANG Xulong, JING Caifang, XIN Yanli, LIU Yan, LI Qinqing, HE Wenbin, ZHANG Junlong, 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=1304388069218608042, articleId=1304388067415057319, tenantId=1146029695717560320, journalId=1302319053441957962, language=CN, title=基于质量源于设计理念和层级分析法-熵权法优化经典名方地黄饮子挥发油提取与包合工艺, columnId=1304140189132149234, journalTitle=中草药, columnName=药剂与工艺, runingTitle=null, highlight=null, articleAbstract=目的 基于质量源于设计（quality by design，QbD）理念和层级分析法（analytical hierarchy process，AHP）-熵权法优化经典名方地黄饮子挥发油的提取与β-环糊精（β-cyclodextrin，β-CD）包合工艺。方法 运用失效模式与效应分析对挥发油提取过程进行风险辨识，确定加热时间、料液比及浸泡时间为关键工艺参数（critical process parameters，CPPs），以桂皮醛含量、β-细辛醚含量及挥发油提取率为关键质量属性（critical quality attributes，CQAs）。在单因素试验基础上，采用Box-Behnken设计-响应面法（Box-Behnken design-response surface methodology，BBD-RSM）进行工艺优化，结合AHP-熵权法计算各CQAs的综合评分，建立优化设计空间并完成验证。采用饱和水溶液法研究挥发油包合工艺，通过正交法结合AHP-熵权法对包合条件进行多指标综合优化，最终确定最佳包合工艺参数并进行验证。结果 优化所得挥发油的最佳提取工艺为浸泡30～45 min，加水量为9～10倍，提取3.0～3.5 h。挥发油的最佳包合工艺为包合时间2.0 h、β-CD与挥发油比例10∶1、包合温度30 ℃。结论 基于QbD理念与AHP-熵权法优化的挥发油提取与包合工艺，可稳定保障挥发油提取率及关键有效成分含量，且所获包合物质量优良，为相关中药制剂的工业化生产与研发提供了可靠的数据支撑与工艺基础，同时为经典名方的现代制剂开发提供了可行路径。, authors=王旭龙1,2 , 景彩芳1,2 , 辛彦利1,2 , 刘艳1,2 , 李钦青1,2 , 贺文彬1,2 , 张俊龙1,2 , authorsList=王旭龙, 景彩芳, 辛彦利, 刘艳, 李钦青, 贺文彬, 张俊龙, authorCompany=1 山西中医药大学中药与食品工程学院, 山西 晋中 030619;
中草药
|药剂与工艺
2026
, 57
(11) :
4124
-4134
基于质量源于设计理念和层级分析法-熵权法优化经典名方地黄饮子挥发油提取与包合工艺
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王旭龙1,2 , 景彩芳1,2 , 辛彦利1,2 , 刘艳1,2 , 李钦青1,2 , 贺文彬1,2 , 张俊龙1,2
作者信息
1 山西中医药大学中药与食品工程学院, 山西 晋中 030619;
通讯作者:
李钦青
作者简介:
王旭龙: 王旭龙（1996—），男，硕士研究生，研究方向为中药制剂技术研究与质量评价。E-mail:1251909112@qq.com
Optimization of volatile oil extraction and inclusion process from classical formula Dihuang Yinzi based on QbD and AHP-entropy weight method
WANG Xulong, JING Caifang, XIN Yanli, LIU Yan, LI Qinqing, HE Wenbin, ZHANG Junlong
Affiliations
doi: 10.7501/j.issn.0253-2670.2026.11.005
文章导航
目的 基于质量源于设计（quality by design，QbD）理念和层级分析法（analytical hierarchy process，AHP）-熵权法优化经典名方地黄饮子挥发油的提取与β-环糊精（β-cyclodextrin，β-CD）包合工艺。方法 运用失效模式与效应分析对挥发油提取过程进行风险辨识，确定加热时间、料液比及浸泡时间为关键工艺参数（critical process parameters，CPPs），以桂皮醛含量、β-细辛醚含量及挥发油提取率为关键质量属性（critical quality attributes，CQAs）。在单因素试验基础上，采用Box-Behnken设计-响应面法（Box-Behnken design-response surface methodology，BBD-RSM）进行工艺优化，结合AHP-熵权法计算各CQAs的综合评分，建立优化设计空间并完成验证。采用饱和水溶液法研究挥发油包合工艺，通过正交法结合AHP-熵权法对包合条件进行多指标综合优化，最终确定最佳包合工艺参数并进行验证。结果 优化所得挥发油的最佳提取工艺为浸泡30～45 min，加水量为9～10倍，提取3.0～3.5 h。挥发油的最佳包合工艺为包合时间2.0 h、β-CD与挥发油比例10∶1、包合温度30 ℃。结论 基于QbD理念与AHP-熵权法优化的挥发油提取与包合工艺，可稳定保障挥发油提取率及关键有效成分含量，且所获包合物质量优良，为相关中药制剂的工业化生产与研发提供了可靠的数据支撑与工艺基础，同时为经典名方的现代制剂开发提供了可行路径。
质量源于设计
/
AHP-熵权法
/
地黄饮子
/
挥发油
/
包合
/
桂皮醛
/
β-细辛醚
Objective To optimize the extraction and β-cyclodextrin (β-CD) inclusion process for the volatile oil from the classical formula Dihuang Yinzi (地黄饮子) based on the quality by design (QbD) concept and the analytic hierarchy process-entropy weight (AHP-entropy) method. Methods Failure mode and effects analysis (FMEA) was employed for risk identification in the volatile oil extraction process. Heating time, material-to-liquid ratio, and soaking time were determined as the critical process parameters (CPPs), while cinnamaldehyde content, β-asarone content, and volatile oil extraction yield were defined as the critical quality attributes (CQAs). On the basis of single-factor tests, the Box-Behnken design-response surface methodology (BBD-RSM) was used for process optimization. The AHP-entropy weight method was applied to calculate a comprehensive score for the CQAs, which was then used to establish and validate an optimized design space. The inclusion process of volatile oil was investigated using the saturated aqueous solution method. The inclusion conditions were comprehensively optimized through orthogonal experimental design combined with the AHP-entropy weight method for multi-index evaluation. Finally, the optimal inclusion process parameters were determined and validated. Results The optimized volatile oil extraction process was as follows: soaking for 30 to 45 min, adding 9- to 10-fold volume of water, and extracting for 3.0 to 3.5 h. The optimal inclusion process parameters were: inclusion time of 2.0 h, β-cyclodextrin to volatile oil ratio of 10:1, and inclusion temperature of 30 ℃. Conclusion The volatile oil extraction and inclusion processes optimized based on the QbD concept and the AHP-entropy weight method can reliably ensure a stable extraction yield and consistent content of key active components. The resulting inclusion complex exhibits excellent quality. This study provides reliable data support and a solid process foundation for the industrial production and development of related Chinese medicinal preparations, while also offering a feasible pathway for the modern dosage form development of classical formulas.
quality by design (QbD)
/
AHP-entropy weight method
/
Dihuang Yinzi
/
volatile oil
/
inclusion
/
cinnamaldehyde
/
β-asarone
王旭龙, 景彩芳, 辛彦利, 刘艳, 李钦青, 贺文彬, 张俊龙.
基于质量源于设计理念和层级分析法-熵权法优化经典名方地黄饮子挥发油提取与包合工艺.
中草药,
2026
, 57
(11)
: 4124
-4134
.
DOI: 10.7501/j.issn.0253-2670.2026.11.005
WANG Xulong, JING Caifang, XIN Yanli, LIU Yan, LI Qinqing, HE Wenbin, ZHANG Junlong.
Optimization of volatile oil extraction and inclusion process from classical formula Dihuang Yinzi based on QbD and AHP-entropy weight method[J].
Chinese Traditional and Herbal Drugs ,
2026
, 57
(11)
: 4124
-4134
.
DOI: 10.7501/j.issn.0253-2670.2026.11.005
参考文献
引证文献
高喜梅, 贾萌, 赵晓莉, 等. 经典名方传统制法向现代生产工艺转化关键问题探索[J]. 南京中医药大学学报, 2019, 35(5): 601-605.
2026年第57卷第11期
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doi: 10.7501/j.issn.0253-2670.2026.11.005
接收时间：2025-12-24
首发时间：2026-09-09
https://castjournals.cast.org.cn/joweb/zcy/CN/10.7501/j.issn.0253-2670.2026.11.005
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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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