Article(id=1216517516302667873, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250213003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1739376000000, receivedDateStr=2025-02-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767969977688, onlineDateStr=2026-01-09, pubDate=1755187200000, pubDateStr=2025-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767969977688, onlineIssueDateStr=2026-01-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767969977688, creator=13701087609, updateTime=1767969977688, updator=13701087609, issue=Issue{id=1216517514570417012, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='15', pageStart='1', pageEnd='322', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1767969977276, creator=13701087609, updateTime=1768211590858, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1217530915467743720, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1217530915467743721, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=278, endPage=286, ext={EN=ArticleExt(id=1216517516696932452, articleId=1216517516302667873, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Optimization of extraction conditions and content study of total polyphenols from Artemisia capillaris, columnId=1151895321388347923, journalTitle=Journal of Food Safety & Quality, columnName=Food Analysis and Detection, runingTitle=null, highlight=null, articleAbstract=

Objective To optimize the extraction process of total polyphenols in Artemisia capillaris and study the content of it in Henan Province. Methods A single factor optimization combined with response surface optimization was used to establish the optimal method for extracting total polyphenols from Artemisia capillaris, mainly examining the effects of solid-liquid ratio, ethanol volume fraction, extraction time and extraction temperature on the extraction of total polyphenols from Artemisia capillaris. The samples of Artemisia capillaris were taken from 18 cities in Henan Province, and the total polyphenol content in Artemisia capillaris was analyzed based on soil type and distribution area. Results The best values of 4 factors were as follows: Solid-liquid ratio 1:30 (m:V), ethanol concentration 50%, extraction time 72 min, extraction temperature 63 ℃, and the best extraction rate of total polyphenols was 1.85%. With the best values of 4 factors, the total polyphenols in Artemisia capillaris from 18 regions in Henan was determined and analyzed. The highest value appears in Anyang and the lowest value appears in Zhengzhou. According to the types of soil, the tide soil had the highest value of total polyphenols, which was 7.51 mg/g, and the paddy soil had the lowest value of total polyphenols, which was 6.15 mg/g. Conclusion The method optimized by this study is stable, reliable and economy. The model established can predict the extraction rate of total polyphenols well. The content of total polyphenols in Artemisia capillaris from different regions in Henan is discrepant. But the discrepancy is not significant according to the soil types.

, correspAuthors=Xiang-Li LI, 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, authorCompany=null, fund=null, authors=null, authorsList=Na LI, Bing-Yang ZHAO, Xi-Xi SUN, Bei-Bei LUO, Bi-Wei JIANG, Xiang-Li LI), CN=ArticleExt(id=1216517519079297147, articleId=1216517516302667873, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=茵陈总多酚的提取条件优化及其含量研究, columnId=1151895321958773274, journalTitle=食品安全质量检测学报, columnName=食品分析与检测, runingTitle=null, highlight=null, articleAbstract=

目的 优化茵陈中总多酚的提取方法, 并研究河南地区茵陈中总多酚的含量水平。方法 采用单因素优化结合响应面优化建立茵陈中总多酚提取的最优方法, 主要考察料液比、乙醇体积分数、提取时间、提取温度对茵陈中总多酚提取的影响。茵陈样品取自河南省18个地市, 结合土壤类型和分布地区对茵陈中总多酚含量进行分析。结果 筛选出茵陈中总多酚提取的最优条件为: 料液比1:30 (m:V)、乙醇体积分数50%、提取时间72 min、提取温度63 ℃, 此时茵陈中多酚的得率为1.85%。分析了河南18个地市的茵陈总多酚含量, 最高值出现在安阳, 最低值出现在郑州; 就土壤类型而言, 潮土土壤的茵陈中总多酚最高为7.51 mg/g, 而水稻土的茵陈中总多酚含量最低为6.15 mg/g。结论 所确立的提取方法稳定、可靠、经济, 所建立的模型能很好预测茵陈总多酚的得率, 河南地区茵陈的总多酚含量因地区不同而存在差异, 但不同的土壤类型未对其产生显著影响。

, correspAuthors=李向力, authorNote=null, correspAuthorsNote=
*李向力(1979—), 男, 硕士, 研究员, 主要研究方向为生物与食品安全。E-mail:
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李娜(1985—), 女, 硕士, 工程师, 主要研究方向为食品安全与检测。E-mail:

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李娜(1985—), 女, 硕士, 工程师, 主要研究方向为食品安全与检测。E-mail:

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Remote Sensing for Natural Resources, 2023, 35(3): 241-252., articleTitle=Spatio-temporal distribution and influencing factors of soil moisture content in Henan Province during 1948—2021, refAbstract=null), Reference(id=1217127913212789605, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, doi=null, pmid=null, pmcid=null, year=2024, volume=52, issue=19, pageStart=45, pageEnd=49, url=null, language=null, rfNumber=[29], rfOrder=56, authorNames=郭强, 蔡春楠, 谷志云, journalName=安徽农业科学, refType=null, unstructuredReference=郭强, 蔡春楠, 谷志云, 等. 河南省表层土壤全碳与有机碳地球化学背景值研究[J]. 安徽农业科学, 2024, 52(19): 45-49., articleTitle=河南省表层土壤全碳与有机碳地球化学背景值研究, refAbstract=null), Reference(id=1217127913321841515, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, doi=null, pmid=null, pmcid=null, year=2024, volume=52, issue=19, pageStart=45, pageEnd=49, url=null, language=null, rfNumber=[29], rfOrder=57, authorNames=GUO Q, CAI CN, GU ZY, journalName=Journal of Anhui Agricultural Sciences, refType=null, unstructuredReference=GUO Q, CAI CN, GU ZY, et al. Study on geochemical background values of total carbon and organic carbon in surface soil of Henan Province[J]. Journal of Anhui Agricultural Sciences, 2024, 52(19): 45-49., articleTitle=Study on geochemical background values of total carbon and organic carbon in surface soil of Henan Province, refAbstract=null), Reference(id=1217127913422504816, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, doi=null, pmid=null, pmcid=null, year=2024, volume=36, issue=4, pageStart=71, pageEnd=76, url=null, language=null, rfNumber=[30], rfOrder=58, authorNames=张楚磊, 田耀武, journalName=环境监测管理与技术, refType=null, unstructuredReference=张楚磊, 田耀武. 河南省土壤有机碳储量及影响因素[J]. 环境监测管理与技术, 2024, 36(4): 71-76., articleTitle=河南省土壤有机碳储量及影响因素, refAbstract=null), Reference(id=1217127913560916858, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, doi=null, pmid=null, pmcid=null, year=2024, volume=36, issue=4, pageStart=71, pageEnd=76, url=null, language=null, rfNumber=[30], rfOrder=59, authorNames=ZHANG CL, TIAN YW, journalName=The Administration and Technique of Environmental Monitoring, refType=null, unstructuredReference=ZHANG CL, TIAN YW. Soil organic carbon storage and its influencing factors in Henan[J]. The Administration and Technique of Environmental Monitoring, 2024, 36(4): 71-76., articleTitle=Soil organic carbon storage and its influencing factors in Henan, refAbstract=null)], funds=[Fund(id=1217127903490392329, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, awardId=230611035, language=CN, fundingSource=河南省科学院基本科研业务费项目(230611035), fundOrder=null, country=null), Fund(id=1217127903662358806, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, awardId=20230104, language=CN, fundingSource=河南省科学院创新团队项目(20230104), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1217127894908847041, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, xref=1, ext=[AuthorCompanyExt(id=1217127894917235650, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, companyId=1217127894908847041, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Henan Commerce Science Institute Co., Ltd., Zhengzhou 450002, China), AuthorCompanyExt(id=1217127894925624260, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, companyId=1217127894908847041, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 河南省商业科学研究所有限责任公司, 郑州 450002)]), AuthorCompany(id=1217127895026287559, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, xref=2, ext=[AuthorCompanyExt(id=1217127895034676169, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, companyId=1217127895026287559, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 School of Food Science and Technology, Henan University of Technology, Zhengzhou 450001, China), AuthorCompanyExt(id=1217127895043064777, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, companyId=1217127895026287559, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 河南工业大学粮油食品学院, 郑州 450001)])], figs=[ArticleFig(id=1217127899627438193, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Fig.1, caption=Effects of Folin phenol addition amount (A), 10% sodium carbonate addition amount (B) and reaction time (C) on the absorbance of solution (n=3), figureFileSmall=s9tFJgC+1X2aE10dzm06GA==, figureFileBig=w9Bv1ZeanpsPRRDNT9JPyw==, tableContent=null), ArticleFig(id=1217127899749073016, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=图1, caption=福林酚加入量(A)、10%碳酸钠加入量(B)和显色时间(C)对溶液吸光度的影响(n=3)

注: 不同小写字母表示具有显著性差异(P<0.05), 图2同。

, figureFileSmall=s9tFJgC+1X2aE10dzm06GA==, figureFileBig=w9Bv1ZeanpsPRRDNT9JPyw==, tableContent=null), ArticleFig(id=1217127899933622401, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Fig.2, caption=Effects of extraction temperature (A), solid-liquid ratio (B), ethanol volume fraction (C) and extraction time (D) on the extraction rate of total polyphenol from Artemisia capillaris (n=3), figureFileSmall=nQcfW/JE9utJ+d5vqMEXug==, figureFileBig=lPA7/T4Rgx/BRH9Z01zr3g==, tableContent=null), ArticleFig(id=1217127900046868615, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=图2, caption=提取温度(A)、料液比(B)、乙醇体积分数(C)和提取时间(D)对茵陈中多酚得率的影响(n=3), figureFileSmall=nQcfW/JE9utJ+d5vqMEXug==, figureFileBig=lPA7/T4Rgx/BRH9Z01zr3g==, tableContent=null), ArticleFig(id=1217127900139143307, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Fig.3, caption=Three dimensional surface and contour map of the interaction between time and extraction temperature, figureFileSmall=6kJfMQsosl5XOJ5kdzPr/g==, figureFileBig=L3OIzUXLLPQdgFoPbH76cA==, tableContent=null), ArticleFig(id=1217127900239806609, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=图3, caption=提取时间和提取温度交互作用的三维曲面图和等高线图, figureFileSmall=6kJfMQsosl5XOJ5kdzPr/g==, figureFileBig=L3OIzUXLLPQdgFoPbH76cA==, tableContent=null), ArticleFig(id=1217127900348858520, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Fig.4, caption=Three dimensional surface and contour map of the interaction between ethanol concentration and extraction temperature, figureFileSmall=kVVgmGKU+F22USdc8TMjJw==, figureFileBig=70pow0ZKmdVCGy2+whhqaA==, tableContent=null), ArticleFig(id=1217127900436938910, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=图4, caption=乙醇体积分数和提取温度交互作用的三维曲面图和等高线图, figureFileSmall=kVVgmGKU+F22USdc8TMjJw==, figureFileBig=70pow0ZKmdVCGy2+whhqaA==, tableContent=null), ArticleFig(id=1217127900562768038, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Fig.5, caption=Three dimensional surface and contour map of the interaction between material-solvent ratio and extraction temperature, figureFileSmall=WAISsV0RLf6hJhECp8XtWw==, figureFileBig=d4Ngui8ui/ShHQUMNgkmtw==, tableContent=null), ArticleFig(id=1217127900688597166, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=图5, caption=料液比和提取温度交互作用的三维曲面图和等高线图, figureFileSmall=WAISsV0RLf6hJhECp8XtWw==, figureFileBig=d4Ngui8ui/ShHQUMNgkmtw==, tableContent=null), ArticleFig(id=1217127900789260467, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Table 1, caption=

Distribution area and number of Artemisia capillaris samples

, figureFileSmall=null, figureFileBig=null, tableContent=
采样地区 采样数量
郑州市 11
许昌市 5
平顶山市 6
开封市 5
漯河市 8
焦作市 5
洛阳市 10
新乡市 11
济源市 7
商丘市 7
三门峡市 7
周口市 8
南阳市 5
信阳市 5
鹤壁市 5
安阳市 5
濮阳市 5
驻马店 6
), ArticleFig(id=1217127900910895290, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=表1, caption=

茵陈采样数量及分布地区

, figureFileSmall=null, figureFileBig=null, tableContent=
采样地区 采样数量
郑州市 11
许昌市 5
平顶山市 6
开封市 5
漯河市 8
焦作市 5
洛阳市 10
新乡市 11
济源市 7
商丘市 7
三门峡市 7
周口市 8
南阳市 5
信阳市 5
鹤壁市 5
安阳市 5
濮阳市 5
驻马店 6
), ArticleFig(id=1217127901061890239, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Table 2, caption=

Design table of Box-Behnken response surface

, figureFileSmall=null, figureFileBig=null, tableContent=
水平 因素
A(料液比)
(m:V)
B(乙醇
体积分数)/%
C(提取
时间)/min
D(提取
温度)/℃
-1 1:20 40 60 50
0 1:30 50 75 60
1 1:40 60 90 70
), ArticleFig(id=1217127902328570054, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=表2, caption=

Box-Behnken响应面设计方案

, figureFileSmall=null, figureFileBig=null, tableContent=
水平 因素
A(料液比)
(m:V)
B(乙醇
体积分数)/%
C(提取
时间)/min
D(提取
温度)/℃
-1 1:20 40 60 50
0 1:30 50 75 60
1 1:40 60 90 70
), ArticleFig(id=1217127902458593484, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Table 3, caption=

Design and results of response surface (n=3)

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 A B C D 多酚得率/%
1 -1 -1 0 0 1.78±0.014
2 1 -1 0 0 1.71±0.016
3 -1 1 0 0 1.68±0.023
4 1 1 0 0 1.67±0.025
5 0 0 -1 -1 1.55±0.018
6 0 0 1 -1 1.61±0.011
7 0 0 -1 1 1.62±0.021
8 0 0 1 1 1.79±0.017
9 -1 0 0 -1 1.60±0.015
10 1 0 0 -1 1.56±0.019
11 -1 0 0 1 1.72±0.023
12 1 0 0 1 1.68±0.025
13 0 -1 -1 0 1.63±0.022
14 0 1 -1 0 1.58±0.003
15 0 -1 1 0 1.76±0.028
16 0 1 1 0 1.69±0.031
17 -1 0 -1 0 1.67±0.015
18 1 0 -1 0 1.58±0.026
19 -1 0 1 0 1.76±0.019
20 1 0 1 0 1.77±0.036
21 0 -1 0 -1 1.66±0.017
22 0 1 0 -1 1.52±0.036
23 0 -1 0 1 1.72±0.018
24 0 1 0 1 1.73±0.054
25 0 0 0 0 1.82±0.041
26 0 0 0 0 1.81±0.035
27 0 0 0 0 1.83±0.042
28 0 0 0 0 1.84±0.039
29 0 0 0 0 1.85±0.028
), ArticleFig(id=1217127902576034000, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=表3, caption=

响应面实验设计及结果(n=3)

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 A B C D 多酚得率/%
1 -1 -1 0 0 1.78±0.014
2 1 -1 0 0 1.71±0.016
3 -1 1 0 0 1.68±0.023
4 1 1 0 0 1.67±0.025
5 0 0 -1 -1 1.55±0.018
6 0 0 1 -1 1.61±0.011
7 0 0 -1 1 1.62±0.021
8 0 0 1 1 1.79±0.017
9 -1 0 0 -1 1.60±0.015
10 1 0 0 -1 1.56±0.019
11 -1 0 0 1 1.72±0.023
12 1 0 0 1 1.68±0.025
13 0 -1 -1 0 1.63±0.022
14 0 1 -1 0 1.58±0.003
15 0 -1 1 0 1.76±0.028
16 0 1 1 0 1.69±0.031
17 -1 0 -1 0 1.67±0.015
18 1 0 -1 0 1.58±0.026
19 -1 0 1 0 1.76±0.019
20 1 0 1 0 1.77±0.036
21 0 -1 0 -1 1.66±0.017
22 0 1 0 -1 1.52±0.036
23 0 -1 0 1 1.72±0.018
24 0 1 0 1 1.73±0.054
25 0 0 0 0 1.82±0.041
26 0 0 0 0 1.81±0.035
27 0 0 0 0 1.83±0.042
28 0 0 0 0 1.84±0.039
29 0 0 0 0 1.85±0.028
), ArticleFig(id=1217127902706057434, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Table 4, caption=

Analysis of variance of Box-Behnken response surface

, figureFileSmall=null, figureFileBig=null, tableContent=
来源 平方和 自由度 均方 F P 显著性
模型 0.2426 14 0.0173 50.87 <0.0001 显著
A(料液比) 0.0049 1 0.0049 14.48 0.0019 显著
B(乙醇体积分数) 0.0117 1 0.0117 34.31 <0.0001 显著
C(提取时间) 0.0448 1 0.0448 131.67 <0.0001 显著
D(提取温度) 0.0479 1 0.0479 140.54 <0.0001 显著
AB 0.0010 1 0.0010 2.85 0.1135 不显著
AC 0.0022 1 0.0022 6.47 0.0234 显著
AD 0 1 0 0.05 0.8215 不显著
BC 0.0002 1 0.0002 0.47 0.5024 不显著
BD 0.0059 1 0.0059 17.28 0.0010 显著
CD 0.0033 1 0.0033 9.61 0.0078 显著
A² 0.0226 1 0.0226 66.26 <0.0001 显著
B² 0.0287 1 0.0287 84.17 <0.0001 显著
C² 0.0450 1 0.0450 132.03 <0.0001 显著
D² 0.0827 1 0.0827 242.72 <0.0001 显著
残差 0.0048 14 0.0003
失拟项 0.0039 10 0.0004 1.74 0.3121 不显著
纯误差 0.0009 4 0.0002
总和 0.2473 28
R2 0.9807 Radj2 0.9614
), ArticleFig(id=1217127902785749214, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=表4, caption=

Box-Behnken响应面试验方差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
来源 平方和 自由度 均方 F P 显著性
模型 0.2426 14 0.0173 50.87 <0.0001 显著
A(料液比) 0.0049 1 0.0049 14.48 0.0019 显著
B(乙醇体积分数) 0.0117 1 0.0117 34.31 <0.0001 显著
C(提取时间) 0.0448 1 0.0448 131.67 <0.0001 显著
D(提取温度) 0.0479 1 0.0479 140.54 <0.0001 显著
AB 0.0010 1 0.0010 2.85 0.1135 不显著
AC 0.0022 1 0.0022 6.47 0.0234 显著
AD 0 1 0 0.05 0.8215 不显著
BC 0.0002 1 0.0002 0.47 0.5024 不显著
BD 0.0059 1 0.0059 17.28 0.0010 显著
CD 0.0033 1 0.0033 9.61 0.0078 显著
A² 0.0226 1 0.0226 66.26 <0.0001 显著
B² 0.0287 1 0.0287 84.17 <0.0001 显著
C² 0.0450 1 0.0450 132.03 <0.0001 显著
D² 0.0827 1 0.0827 242.72 <0.0001 显著
残差 0.0048 14 0.0003
失拟项 0.0039 10 0.0004 1.74 0.3121 不显著
纯误差 0.0009 4 0.0002
总和 0.2473 28
R2 0.9807 Radj2 0.9614
), ArticleFig(id=1217127902932549864, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=EN, label=Table 5, caption=

Content of total polyphenol of Artemisia capillaris in Henan area (mg/g, n=3)

, figureFileSmall=null, figureFileBig=null, tableContent=
土壤类型 样品地区 总多酚含量 平均值
潮土 商丘 6.84±0.06 7.51
开封 5.66±0.08
周口 11.00±0.03
新乡 5.95±0.04
濮阳 10.70±0.08
鹤壁 7.19±0.03
焦作市 5.23±0.02
褐土 三门峡 8.43±0.03 7.11
许昌 6.06±0.13
济源 5.28±0.01
安阳 11.20±0.03
郑州 4.60±0.03
砂姜黑土 南阳 7.63±0.24 7.46
漯河 6.81±0.18
驻马店 7.93±0.13
黄褐土 平顶山市 7.10±0.18 6.38
洛阳 5.65±0.17
水稻土 信阳 6.15±0.11 6.15
), ArticleFig(id=1217127903200985329, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517516302667873, language=CN, label=表5, caption=

河南地区茵陈中总多酚含量(mg/g, n=3)

, figureFileSmall=null, figureFileBig=null, tableContent=
土壤类型 样品地区 总多酚含量 平均值
潮土 商丘 6.84±0.06 7.51
开封 5.66±0.08
周口 11.00±0.03
新乡 5.95±0.04
濮阳 10.70±0.08
鹤壁 7.19±0.03
焦作市 5.23±0.02
褐土 三门峡 8.43±0.03 7.11
许昌 6.06±0.13
济源 5.28±0.01
安阳 11.20±0.03
郑州 4.60±0.03
砂姜黑土 南阳 7.63±0.24 7.46
漯河 6.81±0.18
驻马店 7.93±0.13
黄褐土 平顶山市 7.10±0.18 6.38
洛阳 5.65±0.17
水稻土 信阳 6.15±0.11 6.15
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茵陈总多酚的提取条件优化及其含量研究
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李娜 1 , 赵冰洋 2 , 孙茜茜 1 , 罗蓓蓓 1 , 蒋碧伟 1 , 李向力 1, *
食品安全质量检测学报 | 食品分析与检测 2025,16(15): 278-286
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食品安全质量检测学报 | 食品分析与检测 2025, 16(15): 278-286
茵陈总多酚的提取条件优化及其含量研究
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李娜1 , 赵冰洋2, 孙茜茜1, 罗蓓蓓1, 蒋碧伟1, 李向力1, *
作者信息
  • 1 河南省商业科学研究所有限责任公司, 郑州 450002
  • 2 河南工业大学粮油食品学院, 郑州 450001
  • 李娜(1985—), 女, 硕士, 工程师, 主要研究方向为食品安全与检测。E-mail:

通讯作者:

*李向力(1979—), 男, 硕士, 研究员, 主要研究方向为生物与食品安全。E-mail:
Optimization of extraction conditions and content study of total polyphenols from Artemisia capillaris
Na LI1 , Bing-Yang ZHAO2, Xi-Xi SUN1, Bei-Bei LUO1, Bi-Wei JIANG1, Xiang-Li LI1, *
Affiliations
  • 1 Henan Commerce Science Institute Co., Ltd., Zhengzhou 450002, China
  • 2 School of Food Science and Technology, Henan University of Technology, Zhengzhou 450001, China
出版时间: 2025-08-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250213003
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目的 优化茵陈中总多酚的提取方法, 并研究河南地区茵陈中总多酚的含量水平。方法 采用单因素优化结合响应面优化建立茵陈中总多酚提取的最优方法, 主要考察料液比、乙醇体积分数、提取时间、提取温度对茵陈中总多酚提取的影响。茵陈样品取自河南省18个地市, 结合土壤类型和分布地区对茵陈中总多酚含量进行分析。结果 筛选出茵陈中总多酚提取的最优条件为: 料液比1:30 (m:V)、乙醇体积分数50%、提取时间72 min、提取温度63 ℃, 此时茵陈中多酚的得率为1.85%。分析了河南18个地市的茵陈总多酚含量, 最高值出现在安阳, 最低值出现在郑州; 就土壤类型而言, 潮土土壤的茵陈中总多酚最高为7.51 mg/g, 而水稻土的茵陈中总多酚含量最低为6.15 mg/g。结论 所确立的提取方法稳定、可靠、经济, 所建立的模型能很好预测茵陈总多酚的得率, 河南地区茵陈的总多酚含量因地区不同而存在差异, 但不同的土壤类型未对其产生显著影响。

茵陈  /  总多酚提取  /  河南  /  响应面优化

Objective To optimize the extraction process of total polyphenols in Artemisia capillaris and study the content of it in Henan Province. Methods A single factor optimization combined with response surface optimization was used to establish the optimal method for extracting total polyphenols from Artemisia capillaris, mainly examining the effects of solid-liquid ratio, ethanol volume fraction, extraction time and extraction temperature on the extraction of total polyphenols from Artemisia capillaris. The samples of Artemisia capillaris were taken from 18 cities in Henan Province, and the total polyphenol content in Artemisia capillaris was analyzed based on soil type and distribution area. Results The best values of 4 factors were as follows: Solid-liquid ratio 1:30 (m:V), ethanol concentration 50%, extraction time 72 min, extraction temperature 63 ℃, and the best extraction rate of total polyphenols was 1.85%. With the best values of 4 factors, the total polyphenols in Artemisia capillaris from 18 regions in Henan was determined and analyzed. The highest value appears in Anyang and the lowest value appears in Zhengzhou. According to the types of soil, the tide soil had the highest value of total polyphenols, which was 7.51 mg/g, and the paddy soil had the lowest value of total polyphenols, which was 6.15 mg/g. Conclusion The method optimized by this study is stable, reliable and economy. The model established can predict the extraction rate of total polyphenols well. The content of total polyphenols in Artemisia capillaris from different regions in Henan is discrepant. But the discrepancy is not significant according to the soil types.

Artemisia capillaris  /  extraction of total polyphenol  /  Henan  /  response surface optimization
李娜, 赵冰洋, 孙茜茜, 罗蓓蓓, 蒋碧伟, 李向力. 茵陈总多酚的提取条件优化及其含量研究. 食品安全质量检测学报, 2025 , 16 (15) : 278 -286 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250213003
Na LI, Bing-Yang ZHAO, Xi-Xi SUN, Bei-Bei LUO, Bi-Wei JIANG, Xiang-Li LI. Optimization of extraction conditions and content study of total polyphenols from Artemisia capillaris[J]. Journal of Food Safety & Quality, 2025 , 16 (15) : 278 -286 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250213003
茵陈(Artemisia capillaris)是菊科蒿属植物, 多生于山坡、河岸、砂砾地, 喜温暖湿润气候, 适应性较强[1]。茵陈植株具有浓烈的香气, 是一种食用历史悠久且具有良好药效的天然植物。400多年前, 李时珍发现“茵陈, 昔人多莳为蔬”[2], 此外, 茵陈还被制作成茶饮、糕点等。中国人还较早地认识到茵陈的药效, 例如成书于1800年前的《神农本草经》认为“久服轻身益气, 面白长年”, 茵陈有清热除湿, 保肝利胆的作用[3]; 现代医学进一步的研究认为, 茵陈具有抗氧化、抗炎、抗病毒、调节脂类代谢等功效[4]。目前对茵陈的研究主要集中在药效, 尤其是茵陈和其他中药配伍对于肝病的治疗, 而把茵陈作为食品进行研究的文献很少。
茵陈显著的食效和药效是由于其含有多种活性成分, 如有机酸、挥发油、萜类、多酚等[5-7]。其中多酚是植物生长过程中重要的次生代谢物, 普遍存在于水果、蔬菜等食物中。在结构上, 其多个氢原子被羟基所取代, 这些酚羟基能与人体内的自由基反应, 从而避避免自由基对人体的伤害, 因此多酚具有很强的抗氧化能力, 在预防和治疗心血管疾病、癌症、老年痴呆症等慢性疾病中发挥着重要作用[8-9]。对多酚的研究见于多种植物, 比如金樱子、罗望子、郁金香、花椒、罗汉果、余甘子、芦苇、粽叶等[10-14], 但对于茵陈中多酚的研究甚少。欧阳玉祝等[15]采用超声提取工艺对茵陈中总多酚进行提取, 总多酚得率最高为0.5%, 但李晓强等[16]的研究认为, 溶剂浸提法提取总多酚的效果要好于超声提取法。因此本研究采用溶剂浸提法提取茵陈中总多酚, 优化其中的关键实验参数, 对河南不同市区茵陈的总多酚含量进行测定, 同时结合不同的土壤类型对茵陈中总多酚含量进行分析, 以期为茵陈中总多酚的进一步研究提供基础, 为茵陈的更好利用提供技术支撑。
茵陈样品共121份, 来自河南18个地市, 具有采集科学、分布广泛的特点, 如表1所示。
乙醇、碳酸钠(分析纯, 天津市科密欧化学试剂有限公司); 没食子酸对照品(纯度大于98%, 美国Sigma-Aldrich贸易有限公司); 福林酚(分析纯, 上海源叶生物科技有限公司)。
HH-S6A型恒温水浴锅(北京科伟永兴仪器有限公司); UV-2700型紫外可见分光光度计[岛津企业管理(中国)有限公司]; GZX-9246MBE型电热鼓风干燥箱(上海博迅实业有限公司医疗设备厂); JYL-C012E榨汁搅拌机(九阳股份有限公司); AL104电子天平(精度0.0001 g, 梅特勒-托利多仪器上海有限公司)。
去除茵陈样品中的杂草、石块等异物, 用蒸馏水洗去灰尘, 低温烘干至恒重后进行粉碎, 密封保存, 备用。
依次考察福林酚加入量(mL)、质量分数为10%的碳酸钠加入量(mL)、显色时间(min)对一定浓度没食子酸标准溶液吸光度的影响, 并考察最优条件下标准曲线的相关系数。
取10 mg没食子酸标准品, 用纯净水溶解定容至100 mL, 制成0.1 mg/mL的没食子酸标准溶液。取2 mL标准溶液至25 mL容量瓶中, 加入1 mL 10%碳酸钠、不同体积(0.1、0.2、0.5、1.0 mL)的福林酚试剂, 定容至25 mL, 于暗处反应1 h, 在760 nm处测溶液的吸光度。每个处理做3个平行, 取平均值, 以确定最佳的福林酚试剂加入量(mL)。
取2 mL标准溶液至25 mL容量瓶中, 加入不同体积(0.5、1.0、2.0、4.0 mL)的10%碳酸钠、0.5 mL福林酚试剂, 定容至25 mL, 于暗处反应1 h, 在760 nm处测溶液的吸光度。每个处理做3个平行, 取平均值, 以确定最佳的10%碳酸钠加入量。
取2 mL标准溶液至25 mL容量瓶中, 加入1 mL 10%碳酸钠、0.5 mL福林酚试剂, 定容至25 mL, 在暗处放置不同的时间(10、20、30、60 min), 在760 nm处测溶液的吸光度, 每个处理做3个平行, 取平均值, 以确定最佳的显色时间。
标准曲线的制作, 分别取0.1 mg/mL的没食子酸标准溶液0、0.5、1.0、1.5、2.0、2.5 mL至25 mL容量瓶中, 加入1 mL 10%碳酸钠、0.5 mL福林酚试剂, 定容至25 mL, 在暗处放置30 min, 在760 nm处测溶液的吸光度, 得到标准曲线。
采用乙醇水溶剂浸提法提取茵陈中总多酚。称取0.5 g茵陈样品于250 mL锥形瓶中, 加入一定量的乙醇溶液, 将其置于恒温水浴锅中, 设定提取温度, 准确计时, 提取完成后, 将提取液过滤至50 mL容量瓶中, 用乙醇溶液多次润洗锥形瓶, 多次过滤, 合并滤液, 定容至50 mL。从中取出0.5 mL滤液置于25 mL容量瓶中, 依次加入10%碳酸钠、福林酚试剂, 定容至25 mL, 摇匀, 在25 ℃避光放置, 用试剂空白作参比, 用1 cm比色皿于760 nm处测定溶液的吸光度, 结合标准曲线计算出溶液中多酚质量, 按照公式(1)计算多酚得率:
X/%=$\frac{{m}_{1}}{{m}_{2}}$×100%
式中: X为茵陈中总多酚得率, %; m1为提取液中总多酚质量, g; m2为茵陈样品质量, g。
设置乙醇体积分数50%、料液比1:30 (m:V)、时间1 h, 温度为50、60、70、80℃, 以总多酚得率为评价指标, 选取最佳的提取温度。
设置乙醇体积分数50%、时间1 h、温度60 ℃, 料液比为1:20、1:30、1:40、1:50 (m:V), 以总多酚得率为评价指标, 选取最佳的料液比。
设置料液比1:30 (m:V)、时间1 h、温度60 ℃, 乙醇体积分数30%、40%、50%、60%, 以总多酚得率为评价指标, 选取最佳的乙醇体积分数。
设置料液比1:30 (m:V)、温度60 ℃、乙醇体积分数50%, 提取时间45、60、75、90 min, 以总多酚得率为评价指标, 选取最佳的提取时间。
在单因素优化的基础上, 采用Box-Behnken响应面设计方法, 以料液比(A)、乙醇体积分数(B)、提取时间(C)、提取温度(D)为考察因素, 以总多酚得率为响应值, 开展四因素三水平实验, 设计方案见表2
用最优的提取和测定方法处理河南地区茵陈样品, 得到茵陈中总多酚含量。对于测定结果, 分别从不同地区、不同土壤类型的角度进行分析。
所有实验数据均重复3次, 用Origin 2018进行数据处理和制图, 用Design-Expert 12进行响应面设计及分析。
图1A可知, 对于一定浓度的没食子酸标准溶液, 随着福林酚加入量的增加, 溶液的吸光度先升高后降低。当加入0.5 mL福林酚时, 溶液的吸光度最大。这种变化趋势与杨春妹等[17]优化海藻多酚的测定时观察到的现象一致, 因此选择0.5 mL福林酚为实验加入量。
图1B可知, 随着不同体积10%碳酸钠的加入, 没食子酸标准溶液的吸光度先增大后减小, 当加入1.0 mL 10%碳酸钠时, 溶液的吸光度最大。这是因为福林酚试剂必须在弱碱性环境下才能与多酚类物质发生反应并稳定显色。如果碳酸钠试剂不够则显色不完全, 过量则显色体系不稳定。因此本研究选择加入1.0 mL 10%碳酸钠。朱霞等[18]在优化比色法测定核桃青皮中多酚时选择加入3 mL 12.5%碳酸钠试剂, 但其最大吸光度小于0.5, 而本研究最大吸光度大于0.6, 明显更优。
图1C所示, 30 min之前, 没食子酸标准溶液的吸光度随着时间延长而增加, 但30 min之后, 溶液的吸光度保持稳定。为了提高实验的效率, 选30 min为最佳的显色时间。
用最优条件测定一系列标准溶液的吸光度, 所生成的标准曲线相关系数为0.9993, 线性方程为: Y=-0.0174X+ 0.071, 具有良好的线性关系, 可以满足实验的需求。
单因素实验中提取温度对总多酚得率的影响如图2A所示。随着提取温度的升高, 总多酚得率先升高后降低, 在60 ℃时达到最大。这是因为, 温度升高会促进总多酚的溶解和扩散, 但过高的温度会使总多酚的稳定性发生变化而导致其含量下降。所以确定最佳的提取温度为60 ℃。张立攀等[19]在研究牡丹花中总多酚提取的时候发现, 50 ℃时可以得到最多的总多酚。这可能是牡丹花和茵陈样品的基质差别较大所导致的。
单因素实验中料液比对总多酚得率的影响如图2B所示。随着料液比的增加, 茵陈中总多酚得率呈现先升高再降低的趋势。这是因为乙醇溶剂的增加使茵陈样品的细胞渗透压增高, 从而有利于总多酚的溶出, 使其得率提高。当料液比为1:30 (m:V)时, 总多酚的得率最高。而进一步增加乙醇溶剂, 相当于稀释了多酚。从提高实验效率和降低实验成本考虑, 选择1:30 (m:V)为最佳的料液比。王玉启等[20]在优化圆齿野鸦椿果皮总多酚的提取时选择1:31 (m:V)的料液比, 与本研究的结果接近。
选择不同体积分数的乙醇溶液浸提茵陈总多酚, 总多酚得率变化如图2C所示。随着乙醇体积分数的升高, 总多酚得率先增加后减少, 当乙醇的体积分数为50%, 总多酚得率最高。这是因为乙醇体积分数不同则提取溶剂的极性不同, 而这会对活性成分的溶出有影响。当提取溶剂中水相较多时会抑制总多酚的溶出, 而当提取溶剂中乙醇较多时会增加其他脂溶性成分的溶出, 形成对总多酚溶出的竞争性抑制[21]。所以确定50%的乙醇为最佳提取溶剂。
提取时间对总多酚得率的影响如图2D所示。随着时间的增加, 总多酚得率不断提高, 在75 min时最高, 但是随着时间的进一步延长总多酚得率反而降低。这是因为更长的提取时间使得溶出的总多酚在空气中被氧化, 其结构发生变化[22], 从而使测定数值降低。所以选择75 min为最优的提取时间。
在单因素实验基础上, 以总多酚得率为响应值, 以料液比(A)、乙醇体积分数(B)、提取时间(C)、提取温度(D)为考察因素, 采用Design-Expert 12.0软件设计4因素3水平的Box-Behnken响应面实验, 实验设计与结果见表3, 方差分析见表4。在表4的方差分析中可以看到, 模型极显著(P<0.01), 失拟项不显著(P>0.05), 表明该方程可以很好地反映总多酚得率和4个实验因素之间的关系。R2=0.9807, 表明该拟合方程的相关性很强; R2Radj2的差值小于0.2, 在合理的范围之内。一次项系数ABCD和二次项ACBDCDA2B2C2D2具有显著性差异(P<0.01或P<0.05)。从F来看, F越大说明该因素对响应值的影响强度越大[23], 因此, 对茵陈总多酚得率的影响大小依次为D>C>B>A, 即提取温度>提取时间>乙醇体积分数>料液比。
利用Design Expert软件对上述结果进行多元回归拟合分析, 得到实验中4个单因素对茵陈中总多酚得率的拟合方程如下:
Y=1.83-0.0203A-0.0312B+0.0611C+0.0632D+0.0156AB+0.0235AC-0.0021AD-0.0064BC +0.0384BD+0.0286CD-0.0590A2-0.0665B2-0.0833C2-0.1129D2
通过响应面交互作用分析, 可以得到两两因素的作用情况。三维曲面图和等高线图可以直观地反映因素间的交互作用对响应值的影响程度。其三维曲面图和等高线图如图3~5所示。曲面坡度陡、等高线密集则表示两因素交互作用显著[24]图3~5的三维曲面图皆是凸形曲面, 存在最高点, 说明茵陈总多酚得率在因子设计范围内存在最大值。由图3~5的等高线图可知, CDBD均呈椭圆形, 说明提取时间和提取温度, 乙醇体积分数和提取温度的交互作用显著, 而AD呈近圆形, 说明料液比和提取温度的交互作用不显著[25]。这与方差分析结果一致。
通过Design-expert软件得到茵陈中多酚最优提取条件为: 料液比1:28.80 (m:V)、乙醇体积分数48.18%、提取时间72.25 min、提取温度63.01 ℃, 在此条件下, 总多酚含量为1.86%。考虑到实验操作可行性, 将其修正为料液比1:30 (m:V)、乙醇体积分数50%、提取时间72 min、提取温度63 ℃。按照优化后的实验参数对茵陈总多酚进行3次测定, 平均值为1.85%, 与理论值很接近, 表明该模型稳定可靠, 能很好预测茵陈总多酚的得率。
河南地区有多种土壤类型[26], 每种土壤类型的营养成分不同[27-30], 生长于其上的植物合成的营养成分也有差异。本研究所采集的茵陈属于野生样品, 因此茵陈总多酚含量除了与其生理生化特性有关, 也可能与其所根植的土壤类型有关。用最优实验参数测定茵陈样品总多酚含量, 结合采样地点以及河南地区土壤类型分布得到表5。从表5可以看到, 潮土土壤的茵陈总多酚含量最高为7.51 mg/g, 而水稻土的茵陈总多酚含量最低为6.15 mg/g。从地区看, 最高值出现在安阳, 最低值出现在郑州, 而这两个地区都属于褐土土壤。用SPSS 20对不同土壤类型中茵陈总多酚含量进行分析, 其差异并不显著(P>0.05)。
本研究通过单因素优化和响应面优化相结合的方法, 确定了茵陈总多酚提取的最优条件: 料液比1:30 (m:V)、乙醇体积分数50%、提取时间72 min、提取温度63 ℃, 该方法具有可靠、稳定、经济的特点, 与已有文献相比, 该方法显著提高了茵陈总多酚的得率, 可用于茵陈总多酚的提取。对河南不同地区茵陈样品的测定表明, 茵陈总多酚最高含量出现在安阳地区, 周口地区紧跟其后, 郑州地区的茵陈总多酚含量最低。分析了不同土壤类型对茵陈总多酚含量的影响, 方差分析表明差异并不显著。本研究从总多酚的提取和含量的角度对茵陈进行了研究, 将为茵陈的进一步开发利用提供技术支持。同时, 我国有丰富的茵陈资源, 茵陈含有多种生物活性物质, 对于产地自然环境对茵陈总多酚含量及生物活性的影响机制, 以及溶剂浸提法所得总多酚的具体组成成分及其生理功效还有待进一步研究。
  • 河南省科学院基本科研业务费项目(230611035)
  • 河南省科学院创新团队项目(20230104)
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2025年第16卷第15期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250213003
  • 接收时间:2025-02-13
  • 首发时间:2026-01-09
  • 出版时间:2025-08-15
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  • 收稿日期:2025-02-13
基金
河南省科学院基本科研业务费项目(230611035)
河南省科学院创新团队项目(20230104)
作者信息
    1 河南省商业科学研究所有限责任公司, 郑州 450002
    2 河南工业大学粮油食品学院, 郑州 450001

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*李向力(1979—), 男, 硕士, 研究员, 主要研究方向为生物与食品安全。E-mail:
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https://castjournals.cast.org.cn/joweb/spaq/CN/10.19812/j.cnki.jfsq11-5956/ts.20250213003
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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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