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Article(id=1234106385957442164, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1234106384963400440, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734192000000, receivedDateStr=2024-12-15, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772163491000, onlineDateStr=2026-02-27, pubDate=1750348800000, pubDateStr=2025-06-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772163491000, onlineIssueDateStr=2026-02-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772163491000, creator=13701087609, updateTime=1772163491000, updator=13701087609, issue=Issue{id=1234106384963400440, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='6', pageStart='2961', pageEnd='3552', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1772163490763, creator=13701087609, updateTime=1772163969484, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1234108392948682946, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1234106384963400440, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1234108392948682947, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1234106384963400440, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3420, endPage=3427, ext={EN=ArticleExt(id=1234106386326540923, articleId=1234106385957442164, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=The detection methods of natural steroidal estrogens in vegetables based on UE-SPE-HPLC/FLD, columnId=1234106386213294713, journalTitle=China Environmental Science, columnName=Agriculture and Country Emerging Contaminants, runingTitle=null, highlight=null, articleAbstract=

To systematically assess the environmental risks of natural steroidal estrogens in vegetables, there is an urgent need to establish an efficient, reliable, universal, and convenient extraction and detection system for these estrogens. This study demonstrated that the three natural steroidal estrogens showed a strong linear relationship, with a correlation coefficient greater than 0.9995. The detection limits for estradiol, 17β-estradiol, and estrone were found to be 0.36~3.23μg/kg, 0.76~3.67μg/kg, and 13.97~20.12μg/kg, respectively. The average recoveries for these substances ranged from 104.9% to 130.5%, while the relative standard deviations were between 4.9% and 18.7%. In root samples, the average recoveries were between 80.5% and 129.9%, with relative standard deviations ranging from 4.2% to 38.8%. This method detected natural estrogens in vegetable samples randomly collected in Nanjing city. The results indicated that natural estriol was detected in all vegetable samples, with a 100% detection rate in both the ground and root parts. The detection rate for 17β-estradiol was 75% in the ground part and 100% in the root. In contrast, the detection rate for estrone was 43.8% in the ground part and 18.8% in the root. Further studies are needed to assess the potential risks associated with estrone. Overall, The method exhibits high accuracy and precision, fulfilling the requirements for analysis and determination. Consequently, it provides scientific evidences for effectively assessing and control the environmental risks associated with natural steroidal estrogens in vegetables.

, correspAuthors=Wan-ting LING, 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=Yang CHEN, Jun-yue WANG, Jia-yi YAN, Zi-kang ZHANG, Wan-ting LING), CN=ArticleExt(id=1234106389677789857, articleId=1234106385957442164, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=基于UE-SPE-HPLC/FLD的蔬菜中天然甾体雌激素检测方法, columnId=1234106388545327751, journalTitle=中国环境科学, columnName=农业与农村新污染物, runingTitle=null, highlight=null, articleAbstract=

本研究通过超声提取(UE)-固相萃取(SPE)相结合，采用高效液相色谱仪/荧光检测(HPLC/FLD)技术，构建了一种蔬菜中天然甾体雌激素提取与检测方法. HPLC/FLD仪器分析结果表明，3种天然甾体雌激素在1.00~1000μg/L浓度范围内具有良好的线性关系，其相关系数均高于0.9995.蔬菜中雌三醇、17β-雌二醇和雌酮的方法检出限分别为0.36~3.23，0.76~3.67和13.97~20.12μg/kg，地上部样品中3种雌激素的平均回收率为104.9%~130.5%，相对标准偏差为4.9%~18.7%;根部样品中3种雌激素的平均回收率为80.5%~129.9%，相对标准偏差为4.2%~38.8%.采用该方法对市场上随机采集的蔬菜样品进行检测，结果表明，所有蔬菜样品中均检测到天然甾体雌激素，其中雌三醇地上部及根部检出率为100%，17β-雌二醇地上部检出率为75%、根部为100%，雌酮地上部检出率43.8%、根部为18.8%.本方法的准确性与精密度良好，能够满足蔬菜中雌激素分析测定要求，为蔬菜中天然甾体雌激素环境风险评估与管控提供了科学依据.

, correspAuthors=凌婉婷, authorNote=null, correspAuthorsNote=
* 责任作者，教授，
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陈泱(2001-)，女，江苏常州人，南京农业大学硕士研究生，主要从事土壤有机污染控制与修复研究..

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陈泱(2001-)，女，江苏常州人，南京农业大学硕士研究生，主要从事土壤有机污染控制与修复研究..

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陈泱(2001-)，女，江苏常州人，南京农业大学硕士研究生，主要从事土壤有机污染控制与修复研究..

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Journal of Chromatography A，2018，1533:49-56., articleTitle=Determination of household and industrial chemicals，personal care products and hormones in leafy and root vegetables by liquid chromatography-tandem mass spectrometry, refAbstract=null)], funds=[Fund(id=1234106398557130925, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, awardId=42177016; 42261144738, language=CN, fundingSource=国家自然科学基金资助项目(42177016; 42261144738), fundOrder=null, country=null), Fund(id=1234106398771040456, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, awardId=BE2022849, language=CN, fundingSource=江苏省重点研发计划项目(BE2022849), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1234106389933642410, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, xref=null, ext=[AuthorCompanyExt(id=1234106389942031019, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, companyId=1234106389933642410, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Organic Contaminant Control and Soil Remediation, Nanjing Agricultural University, Nanjing 210095, China), AuthorCompanyExt(id=1234106389954613932, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, companyId=1234106389933642410, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=南京农业大学，土壤有机污染控制与修复研究所，江苏 南京 210095)])], figs=[ArticleFig(id=1234106394543182744, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Fig.1, caption=Effects of extractant volume on recovery rate, figureFileSmall=qpl5WWNFsIfGAjq4AsO1cA==, figureFileBig=VNqbXAfSC+ht2R+NvuRyZA==, tableContent=null), ArticleFig(id=1234106394643846051, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=图1, caption=提取剂体积对回收率的影响

同色柱形不同小写字母表示显著差异，下同

, figureFileSmall=qpl5WWNFsIfGAjq4AsO1cA==, figureFileBig=VNqbXAfSC+ht2R+NvuRyZA==, tableContent=null), ArticleFig(id=1234106394912281529, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Fig.2, caption=Effects of extraction times on the recovery rate of three natural SEs in the shoot and the root, figureFileSmall=b6AJRnTIC+Gm3J4yATgEQg==, figureFileBig=yTtf06eb1Si0guNwYx1HPA==, tableContent=null), ArticleFig(id=1234106395063276485, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=图2, caption=提取次数对地上部和根部内3种天然甾体雌激素提取效率的影响, figureFileSmall=b6AJRnTIC+Gm3J4yATgEQg==, figureFileBig=yTtf06eb1Si0guNwYx1HPA==, tableContent=null), ArticleFig(id=1234106395193299922, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Fig.3, caption=Effects of SPE columns on the recovery rate of three natural SEs in the shoot and the root, figureFileSmall=gDXVRRr2XUndnwHY0W+EiQ==, figureFileBig=kxOhHtoflO7tNtSSo5/yMQ==, tableContent=null), ArticleFig(id=1234106395344294879, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=图3, caption=固相萃取柱对地上部和根部内3种天然甾体雌激素提取效率的影响, figureFileSmall=gDXVRRr2XUndnwHY0W+EiQ==, figureFileBig=kxOhHtoflO7tNtSSo5/yMQ==, tableContent=null), ArticleFig(id=1234106395486901230, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Table 1, caption=

Effect of extractants on extraction efficiency(%, mean±SD)

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类植物组分提取剂类型
甲醇[18]乙腈[11]乙酸乙酯[15]乙腈：水(1:1)[11]正己烷：丙酮(1:1)[21]甲醇：二氯甲烷(7:3)
雌三醇地上部5.9±1.0d19.3±11.8c0d106.6±12.9a57.5±10.1b4.7±2.7d
根部77.9±66.4ab123.3±55.9a35.1±17.7b129.1±16.7ab44.1±40.3ab92.7±49.0ab
雌二醇地上部2.1±0.4b30.8±5.2b0.5±0.8b111.9±18.7a2.7±1.6b76.8±44.3a
根部1.7±1.5b13.1±6.4b4.6±3.9b105.8±14.1a0b0b
雌酮地上部152.1±67.4b31.4±18.1bc94.3±60.3bc104.9±14.8bc323.3±143.0a0c
根部109.2±30.2ab21.5±15.1b87.9±24.2ab80.5±31.8ab266.8±214.8a0b
), ArticleFig(id=1234106396954906632, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=表1, caption=

提取剂类型对提取效率的影响(%, mean±SD)

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类植物组分提取剂类型
甲醇[18]乙腈[11]乙酸乙酯[15]乙腈：水(1:1)[11]正己烷：丙酮(1:1)[21]甲醇：二氯甲烷(7:3)
雌三醇地上部5.9±1.0d19.3±11.8c0d106.6±12.9a57.5±10.1b4.7±2.7d
根部77.9±66.4ab123.3±55.9a35.1±17.7b129.1±16.7ab44.1±40.3ab92.7±49.0ab
雌二醇地上部2.1±0.4b30.8±5.2b0.5±0.8b111.9±18.7a2.7±1.6b76.8±44.3a
根部1.7±1.5b13.1±6.4b4.6±3.9b105.8±14.1a0b0b
雌酮地上部152.1±67.4b31.4±18.1bc94.3±60.3bc104.9±14.8bc323.3±143.0a0c
根部109.2±30.2ab21.5±15.1b87.9±24.2ab80.5±31.8ab266.8±214.8a0b
), ArticleFig(id=1234106397110095894, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Table 2, caption=

Working curves of three types of natural steroidal estrogen

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类线性方程相关系数线性范围(μg/L)保留时间相对标准偏差(%)
雌三醇H=407.99C+6433.40.99975.00~1000.000.07
雌二醇H=202.75C+3590.90.99965.00~1000.000.08
雌酮H=5.5333C+198.700.999830.00~1000.000.10
), ArticleFig(id=1234106397240119331, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=表2, caption=

三种天然甾体雌激素的工作曲线

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类线性方程相关系数线性范围(μg/L)保留时间相对标准偏差(%)
雌三醇H=407.99C+6433.40.99975.00~1000.000.07
雌二醇H=202.75C+3590.90.99965.00~1000.000.08
雌酮H=5.5333C+198.700.999830.00~1000.000.10
), ArticleFig(id=1234106397349171249, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Table 3, caption=

Detection limits of three types of natural steroidal estrogen

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类3倍噪音值法液相色谱仪检定规程
3倍标准偏差值回归方程(5/30~500ug/L)检出限(μg/L)信号值(30μg/L)噪音值检出限(μg/L)
雌三醇1364.82H=422.79C+2509.83.231544893.880.36
雌二醇786.90H=214.16C+1019.93.67742293.880.76
雌酮80.61H=5.7745C+138.1913.9728093.8820.12
), ArticleFig(id=1234106397487583297, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=表3, caption=

三种天然甾体雌激素的液相检出限

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类3倍噪音值法液相色谱仪检定规程
3倍标准偏差值回归方程(5/30~500ug/L)检出限(μg/L)信号值(30μg/L)噪音值检出限(μg/L)
雌三醇1364.82H=422.79C+2509.83.231544893.880.36
雌二醇786.90H=214.16C+1019.93.67742293.880.76
雌酮80.61H=5.7745C+138.1913.9728093.8820.12
), ArticleFig(id=1234106397621801042, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Table 4, caption=

Recoveries and RSD of the method (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类加标后浓度(μg/kg)回收率(%)相对标准偏差(%)
地上部根部地上部根部
雌三醇50121.5129.94.927.6
500130.5119.68.425.0
1000106.6129.112.916.7
雌二醇50111.692.511.58.2
500119.888.98.74.2
1000111.9105.818.714.1
雌酮50110.7112.715.238.8
500121.290.818.425.5
1000104.980.514.831.8
), ArticleFig(id=1234106397739241568, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=表4, caption=

方法的加标回收及相对标准偏差(n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
雌激素种类加标后浓度(μg/kg)回收率(%)相对标准偏差(%)
地上部根部地上部根部
雌三醇50121.5129.94.927.6
500130.5119.68.425.0
1000106.6129.112.916.7
雌二醇50111.692.511.58.2
500119.888.98.74.2
1000111.9105.818.714.1
雌酮50110.7112.715.238.8
500121.290.818.425.5
1000104.980.514.831.8
), ArticleFig(id=1234106397869265001, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Table 5, caption=

Comparison of the proposed method with other methods

, figureFileSmall=null, figureFileBig=null, tableContent=
实际样品目标雌激素数量检测方法仪器分析时间(min)检出限(μg/kg)回收率(%)来源
蔬菜3HPLC/FLD201.1~27.080.5~130.5本研究
蔬菜3HPLC-ESI-MS/MS200.04~0.869.0~127.0[25]
蔬菜5LC-MS/MS12~21.50.04~0.670.0~130.0[26]
蔬菜5GC-MS/MS14.70.1~0.855.0~137.0[27]
蔬菜3LC-MS/MS270.025~12.581.0~125.0[28]
), ArticleFig(id=1234106397995094134, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=表5, caption=

本文方法与其他方法的比较

, figureFileSmall=null, figureFileBig=null, tableContent=
实际样品目标雌激素数量检测方法仪器分析时间(min)检出限(μg/kg)回收率(%)来源
蔬菜3HPLC/FLD201.1~27.080.5~130.5本研究
蔬菜3HPLC-ESI-MS/MS200.04~0.869.0~127.0[25]
蔬菜5LC-MS/MS12~21.50.04~0.670.0~130.0[26]
蔬菜5GC-MS/MS14.70.1~0.855.0~137.0[27]
蔬菜3LC-MS/MS270.025~12.581.0~125.0[28]
), ArticleFig(id=1234106398229975176, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=EN, label=Table 6, caption=

Contents of three types of natural steroidal estrogen in vegetable samples(μg/kg dw, mean±SD)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品雌三醇雌二醇雌酮
上海青地上部(n=9)1353.4±90.0160.2±13.2n.d.
油麦菜地上部(n=4)16.2±6.1n.d.28.6±1.6
生菜地上部(n=3)248.8±2.78.8±1.2267.7±13.0
地上部检出率(n=16)100%75%43.8%
上海青根部(n=9)3499.0±93.7314.0±68.5n.d.
油麦菜根部(n=4)140.3±9.4131.3±5.9n.d.
白萝卜根部(n=3)701.6±56.113.0±3.9454.5±93.1
根部检出率(n=16)100%100%18.8%
), ArticleFig(id=1234106398364192920, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106385957442164, language=CN, label=表6, caption=

蔬菜样品中三种天然甾体雌激素的检出结果(μg/kg dw, mean±SD)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品雌三醇雌二醇雌酮
上海青地上部(n=9)1353.4±90.0160.2±13.2n.d.
油麦菜地上部(n=4)16.2±6.1n.d.28.6±1.6
生菜地上部(n=3)248.8±2.78.8±1.2267.7±13.0
地上部检出率(n=16)100%75%43.8%
上海青根部(n=9)3499.0±93.7314.0±68.5n.d.
油麦菜根部(n=4)140.3±9.4131.3±5.9n.d.
白萝卜根部(n=3)701.6±56.113.0±3.9454.5±93.1
根部检出率(n=16)100%100%18.8%
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基于UE-SPE-HPLC/FLD的蔬菜中天然甾体雌激素检测方法
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陈泱 , 王俊跃 , 闫佳艺 , 张紫康 , 凌婉婷 *
中国环境科学 | 农业与农村新污染物 2025,45(6): 3420-3427
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中国环境科学 | 农业与农村新污染物 2025, 45(6): 3420-3427
基于UE-SPE-HPLC/FLD的蔬菜中天然甾体雌激素检测方法
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陈泱 , 王俊跃, 闫佳艺, 张紫康, 凌婉婷*
作者信息
  • 南京农业大学，土壤有机污染控制与修复研究所，江苏 南京 210095

    • 陈泱(2001-)，女，江苏常州人，南京农业大学硕士研究生，主要从事土壤有机污染控制与修复研究..

通讯作者:

* 责任作者，教授，
The detection methods of natural steroidal estrogens in vegetables based on UE-SPE-HPLC/FLD
Yang CHEN , Jun-yue WANG, Jia-yi YAN, Zi-kang ZHANG, Wan-ting LING*
Affiliations
  • Institute of Organic Contaminant Control and Soil Remediation, Nanjing Agricultural University, Nanjing 210095, China
出版时间: 2025-06-20
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摘要
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本研究通过超声提取(UE)-固相萃取(SPE)相结合，采用高效液相色谱仪/荧光检测(HPLC/FLD)技术，构建了一种蔬菜中天然甾体雌激素提取与检测方法. HPLC/FLD仪器分析结果表明，3种天然甾体雌激素在1.00~1000μg/L浓度范围内具有良好的线性关系，其相关系数均高于0.9995.蔬菜中雌三醇、17β-雌二醇和雌酮的方法检出限分别为0.36~3.23，0.76~3.67和13.97~20.12μg/kg，地上部样品中3种雌激素的平均回收率为104.9%~130.5%，相对标准偏差为4.9%~18.7%;根部样品中3种雌激素的平均回收率为80.5%~129.9%，相对标准偏差为4.2%~38.8%.采用该方法对市场上随机采集的蔬菜样品进行检测，结果表明，所有蔬菜样品中均检测到天然甾体雌激素，其中雌三醇地上部及根部检出率为100%，17β-雌二醇地上部检出率为75%、根部为100%，雌酮地上部检出率43.8%、根部为18.8%.本方法的准确性与精密度良好，能够满足蔬菜中雌激素分析测定要求，为蔬菜中天然甾体雌激素环境风险评估与管控提供了科学依据.

蔬菜  /  天然甾体雌激素  /  超声提取  /  固相萃取  /  高效液相色谱

To systematically assess the environmental risks of natural steroidal estrogens in vegetables, there is an urgent need to establish an efficient, reliable, universal, and convenient extraction and detection system for these estrogens. This study demonstrated that the three natural steroidal estrogens showed a strong linear relationship, with a correlation coefficient greater than 0.9995. The detection limits for estradiol, 17β-estradiol, and estrone were found to be 0.36~3.23μg/kg, 0.76~3.67μg/kg, and 13.97~20.12μg/kg, respectively. The average recoveries for these substances ranged from 104.9% to 130.5%, while the relative standard deviations were between 4.9% and 18.7%. In root samples, the average recoveries were between 80.5% and 129.9%, with relative standard deviations ranging from 4.2% to 38.8%. This method detected natural estrogens in vegetable samples randomly collected in Nanjing city. The results indicated that natural estriol was detected in all vegetable samples, with a 100% detection rate in both the ground and root parts. The detection rate for 17β-estradiol was 75% in the ground part and 100% in the root. In contrast, the detection rate for estrone was 43.8% in the ground part and 18.8% in the root. Further studies are needed to assess the potential risks associated with estrone. Overall, The method exhibits high accuracy and precision, fulfilling the requirements for analysis and determination. Consequently, it provides scientific evidences for effectively assessing and control the environmental risks associated with natural steroidal estrogens in vegetables.

vegetables  /  natural steroidal estrogen  /  ultrasonic extraction  /  solid phase extraction  /  high-performance liquid chromatography
陈泱, 王俊跃, 闫佳艺, 张紫康, 凌婉婷. 基于UE-SPE-HPLC/FLD的蔬菜中天然甾体雌激素检测方法. 中国环境科学, 2025 , 45 (6) : 3420 -3427 .
Yang CHEN, Jun-yue WANG, Jia-yi YAN, Zi-kang ZHANG, Wan-ting LING. The detection methods of natural steroidal estrogens in vegetables based on UE-SPE-HPLC/FLD[J]. China Environmental Science, 2025 , 45 (6) : 3420 -3427 .
正文
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雌激素作为一种生物活性激素常应用于医疗、饲养及加工等生产过程，具有在极低浓度(<1ng/L)下就可扰乱生物内分泌系统正常功能的风险[1]，过量雌激素通过生物排泄及工业生产等行为进入环境.环境雌激素为具有环境内分泌干扰作用的新污染物，包括天然甾体雌激素和人工合成雌激素，其中天然甾体雌激素包括雌酮、雌二醇和雌三醇，由人类和动物的肾上腺皮质、睾丸、卵巢和胎盘释放，在结构上有甾体母核且具有较强的内分泌干扰效应，通过模拟、干扰或对抗机体内生荷尔蒙原有的正常合成、运输和释放，使生物无法维持自身平衡和调节，导致生物雌性化、繁殖力下降、免疫力降低、女性多种妇科疾病发生[2–5].在世界范围内，天然甾体雌激素在水土环境中的浓度迅速增加[6]，其污染范围广、对人体健康和生态系统的危害极大[7-8]，近年来引起了人们的极大关注.用处理过的废水或受污染的地表水进行农业灌溉以及有机肥的施用会导致环境中的天然甾体雌激素迁移到新鲜农产品的可食用部分，成为进入人体的潜在风险.目前蔬菜中已有天然甾体雌激素检出[9-10]，人们对雌激素进入人类食物链表现关注，进一步推进了关于植物如何吸收和代谢天然甾体雌激素的研究，其中如何高效且方便检出蔬菜中雌激素的方法成为了首要解决的问题.
目前，植物中天然甾体雌激素定量检测的主要方法有高效气相色谱法(GC)、高效液相色谱法(HPLC)、高效气相色谱-质谱联用法(GC-MS)及高效液相色谱-质谱联用(LC-MS)法等[11–13].近年来，质谱检测技术因其与GC或HPLC的结合使用而受到越来越多的关注，这种联用技术不仅显著提高了检测的灵敏度，还极大地增强了定性分析的能力[14]，适用于植物中雌激素含量的检测，但质谱检测成本高、操作复杂且其数据分析对操作人员专业要求较高.使用高效气相色谱法需要在上样前对样品进行衍生化处理[11].在仅用高效液相法检测过程中常会采用荧光检测器来提高检测的灵敏度[15]，同时会遇到雌激素化合物荧光效应不够强的情况，因此出现了结合荧光衍生剂以加强雌激素化合物的荧光效应的方法[12].
植物组织成分复杂，含有大量有机酸等有机物，这对有效分离雌激素和定性、定量方面提出更高的要求;同时由于植物样品中雌激素含量通常极低，常处于ng/kg和µg/kg级别[11]，对有效的富集及高灵敏的检测有较高需求，开发一种快速而有效的预处理方法对于成功检测雌激素至关重要.固相萃取(SPE)是目前富集天然甾体雌激素使用最为广泛的净化富集方法[14]，但尚未有系统性的高效提取-检测方法应用于蔬菜检测.
相关研究发现生菜中17β-雌二醇含量高于严重影响公众健康的毒性水平[11].目前粮农组织/世卫组织食品添加剂联合专家委员会仅对17 β-雌二醇每日摄入量提出建议[16]，但已有研究表明人体和植物中雌酮、雌三醇和雌二醇三者会发生相互转化[17-19].因此，本研究不仅关注雌二醇含量，还同时关注雌酮和雌三醇的潜在风险.本研究旨在优化UE-SPE-HPLC/FLD技术，通过比较不同的提取剂、提取剂体积、提取次数、固相萃取柱的种类和高效液相色谱方法，建立了一套高效、精确、泛用性好且兼具便捷性的蔬菜中天然甾体雌激素的提取与检测系统方法.本研究方法可用于分析市售有机肥种植蔬菜中雌激素的含量，能够为雌激素风险评估体系提供更准确的科学依据，并为保障食品安全和公众健康提供技术支持.
1　材料与方法
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1.1　材料
雌三醇标准品(E3,98%)、17β-雌二醇(17 β-E2,98%)、雌酮(E1,98%)均购自上海阿拉丁生化科技股份有限公司.甲醇、乙腈为色谱纯级别.C18固相萃取柱购自北京迈瑞达科技有限公司.GCB固相萃取柱购自北京迈瑞达科技有限公司.HLB固相萃取柱购自北京化玻站生物分析技术有限公司.PSA固相萃取柱购自北京迈瑞达科技有限公司.
1.2　样品采集
2024年选取南京市进行采样，分别在菜市场和超市随机购买蔬菜样品，并收集实验室温室盆栽种植的施用有机肥的油麦菜样品，样品采集后尽快运回实验室，洗净后分离地上部和根部冷冻干燥处理.冻干后的植物样品进一步剪碎后避光、4℃密封保存待用.
1.3　标准溶液配制
准确称取3种天然甾体雌激素(E3、17β-E2和E1)标准品(100.00±0.01) mg置于100mL棕色容量瓶中，以甲醇为溶剂配置浓度1.00g/L的母液，-20℃保存.分别取E3、17β-E2和E1母液100μL置于100mL棕色容量瓶中，甲醇定容，得到E3、17β-E2和E1浓度均为1.0mg/L的混合标准储备液，-20℃保存.
1.4　色谱条件
色谱柱：Inertsil ODS-SP-C18 (150mm × 4.6mm,5μm);流动相为乙腈：水(体积比为40:60)，流速0.8mL/min，进样量20μL，柱温40℃;采用荧光检测器：激发/发射波长为280/310nm，每个样品20min.
1.5　样品前处理
1.5.1　超声提取
本研究的超声提取方法参考了付银杰等[15]对畜禽粪便中雌激素超声提取条件的优化研究成果，以及Adeel等[11]对生菜中雌激素的提取方法.综合考虑提取效率与实验条件的可行性，本研究选择以30min作为超声提取时间，以此为基础进一步优化提取剂等条件以实现对目标雌激素的最佳提取效果.
冷冻干燥的蔬菜样品分为地上部分和根部，称取地上部分(0.50 ± 0.01) g，根部(0.05 ± 0.001) g，置于40mL顶空瓶中.加入10μL的3种天然甾体雌激素混合标准溶液，涡旋混合均匀后避光放置12h.提取时加入10mL提取剂，涡旋30s后超声提取30min，振荡30min，并以10000r/min离心10min[11]，上清液过0.22μm有机相滤膜后转入另一顶空瓶，重复提取1次，合并2次提取液，40℃恒温水浴并氮吹至1mL，后加入1mL乙腈溶解、超纯水稀释至40mL容量瓶中待用.空白组：称取地上部分(0.50 ± 0.01) g，根部(0.05± 0.001) g，置于40mL玻璃顶空瓶中.加入10 μL的甲醇溶液，涡旋混合均匀后避光放置24h，其他操作同上.实验中每个处理组均设置了3个平行样本，以确保数据的重复性和可靠性.
1.5.2　固相萃取
C18固相萃取[15]：需分别采用5mL甲醇和5mL超纯水活化固相萃取柱，然后将提取后的样品溶液以5~8mL/min流速过固相萃取柱，用5mL超纯水淋洗柱体清除杂质并继续抽吸至无液体滴下，最后用15mL体积比为1:1的乙酸乙酯和甲醇混合液洗脱，洗脱液收集至小试管中.小试管置于40℃恒温水浴并氮吹至干，加入2mL甲醇重新溶解并涡旋，过0.22μm有机相滤膜后，收集于棕色液相小瓶，-20℃保存，用于高效液相色谱分析.
HLB+GCB固相萃取[11]：Oasis HLB固相萃取柱先采用5mL乙酸乙酯活化，再加入5mL甲醇浸泡柱体5min，然后以1~3mL/min的速率通过10mL超纯水.将提取后的样品溶液以5~8mL/min流速过固相萃取柱，用10mL10%甲醇水溶液淋洗柱体清除杂质并继续抽吸至无液体滴下，最后用15mL体积比为1：1的乙酸乙酯和甲醇混合液洗脱，洗脱液收集至小试管中.小试管置于40℃恒温水浴并氮吹至干.为了去除色素的干扰，将上一步的样品再通过GCB固相萃取柱净化.GCB固相萃取柱先采用10mL正己烷：丙酮(1：1，体积分数，下同)活化，然后以1~3mL/min的速率通过5mL超纯水.上一步的样品加入2mL甲醇重新溶解并用超纯水定容至10mL，以5~8mL/min流速过固相萃取柱，用5mL超纯水淋洗柱体清除杂质并继续抽吸至无液体滴下，最后用15mL体积比为1：1的乙酸乙酯和甲醇混合液洗脱，洗脱液收集至小试管中.小试管置于40℃恒温水浴并氮吹至干，加入2mL甲醇重新溶解并涡旋，过0.22μm有机相滤膜后，收集于棕色液相小瓶，-20℃保存，用于高效液相色谱分析.
PSA[20]+GCB固相萃取：PSA固相萃取柱先采用5mL乙酸乙酯活化，再加入10mL正己烷：丙酮体积比(1：1)浸泡柱体5min，然后以1~3mL/min的速率通过10mL超纯水.将提取后的样品溶液以5~8mL/min流速过固相萃取柱，用10mL水溶液淋洗柱体清除杂质并继续抽吸至无液体滴下，最后用15mL体积比为1：1的乙酸乙酯和甲醇混合液洗脱，洗脱液收集至小试管中.小试管置于40℃恒温水浴并氮吹至干.为了去除色素的干扰，将上一步的样品再通过GCB固相萃取柱净化.GCB固相萃取柱的操作同上.
1.6　回收率计算
鉴于采用有机肥种植的蔬菜含有雌激素，因此在计算回收率时需要扣除雌激素的本底浓度，因此得到以下回收率公式：
式中：Cx为加标检测浓度，mg/L;C0为样品检测浓度，mg/L;Cs为标准溶液浓度，mg/L;Vs为加入标准溶液体积，mL;V为样品定容体积，mL.
1.7　数据处理与统计分析
相关图形使用Origin 2024绘制，使用Excel 365处理回收率、相对标准偏差等实验数据，使用IBM SPSS Statistics 22对所有数据进行统计分析.
符合正态分布的连续变量用均数±标准差(SD)表示.单因素方差分析(连续变量)被用于对于多组数据比较.在所有比较中，显著性水平为0.05被认为具有统计学意义.本次统计分析采用字母标记法来展示不同组别之间的显著性差异.
2　结果与分析
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2.1　植物样品前处理方法
2.1.1　提取剂类型
雌激素在弱极性或中等极性有机溶剂中有较高的溶解性.已知的有机溶剂极性比较为：乙腈>甲醇>乙酸乙酯>二氯甲烷>正己烷[15].提取剂的选择参考了目前植物总雌激素提取检测方法中涉及到的提取剂如表1.在提取过程中，绿叶蔬菜中的酚类色素和有机酸等杂质同时被提取出来，对后续检测产生了显著干扰.当采用甲醇作为提取剂时，提取液颜色较深，其中所含杂质会影响目标物的定量分析;采用甲醇：二氯甲烷(7:3，体积分数，下同)提取时，后续检测中雌二醇与雌酮无法实现有效分离;采用乙腈提取时，检测结果整体偏低.此外，还普遍存在同一种提取剂对3种天然甾体雌激素提取效果差异显著的现象.如采用正己烷：丙酮(1:1)提取时，雌二醇回收率极低，而雌酮则出现超量检出.同时，同一种提取剂在植物地上部和根部的提取效果也存在差异.从统计学角度分析，在所选共6种提取剂中，乙腈：水(1:1)对蔬菜地上部中的雌三醇及蔬菜中雌二醇提取效果有显著优势，在其他方面则保持较好提取水平且地上部和根部回收效果差异较小，具有良好的通用性.因此，本实验选择乙腈：水(1:1)作为提取剂.
乙腈：水(1:1)作为提取剂时回收率大都超过100%，考虑到植物体中含有大量木质素、纤维素、果酸、叶绿素、生物碱和植物激素等有机物质[22]，其中部分有机物与目标提取物同时被提出.由于目标提取物含量相对较低，杂质对液相色谱检测结果产生了显著的干扰，影响了检测的准确性和灵敏度.因此后续仍需优化提取条件，以实现样品深度净化，从而降低杂质对检测结果的干扰，提高检测的可靠性与准确性.
2.1.2　提取剂体积
提取剂体积偏少则无法将蔬菜中的3种天然甾体雌激素完全提出，由于蔬菜中含有大量有机酸及酚类色素物质，用量过多则易产生较多杂质干扰液相检测结果.为了追求较好的提取效率且同时能尽可能减少杂质的干扰，试验考察了乙腈：水(1:1)体积分别为10、20、30和40mL时对3种物质的提取回收率.由图1可知，提取体积在10mL和20mL时，整体回收效率均表现出相对稳定性.然而10mL提取体积下，根部的雌酮和雌二醇提取效果欠佳，20mL提取体积在地上部和根部的提取效果都表现良好，3种天然甾体雌激素的提取回收率在80.50%~129.10%.当提取剂体积分别增加至30mL和40mL时，观察到地上部雌酮回收率显著降低，而雌三醇回收率异常升高;或根部雌酮回收率异常升高，雌三醇回收率显著降低的现象.推测其原因可能是提取剂体积的增加导致地上部和根部的杂质大量析出，进而对液相色谱检测中的出峰产生干扰.因此，综合考虑回收率和杂质干扰的影响，本研究最终确定20mL为提取剂的最佳体积.
2.1.3　提取次数
试验选择体积20mL作为提取剂体积，考察了提取1次20mL、2次各10mL和4次各5mL分别提取蔬菜地上部和根部样品中3种天然甾体雌激素.地上部的提取结果显示(图2)，雌二醇的提取效果最为稳定，雌三醇和雌酮在单次提取时效果较差，且随着提取次数的增加，误差呈增大趋势.从实验操作复杂程度和误差控制的角度分析，提取四次的操作最为复杂，并且引入的误差最大.相比之下，提取两次的效果较为稳定，且误差处于可接受范围内.因此，本研究确定提取两次作为最佳提取次数.
2.1.4　固相萃取柱填料类型
C18固相萃取柱可以为疏水化合物提供反相键合作用[23].HLB固相萃取柱对各类极性，非极性化合物具有较均衡的吸附作用，PSA固相萃取柱可以有效去除食品中影响农残检测的脂肪酸(包括油酸、棕榈酸、亚麻酸等)有机酸、一些极性色素以及糖类等干扰物，GCB则对平面分子有很强的吸附能力，例如可以去除蔬菜水果中的叶绿素、叶黄素、胡萝卜素等.由于目标提取物三种天然甾体雌激素均具有中度疏水性(lgKow:2.6~3.94)[24,6]，同时考虑到蔬菜中糖类有机酸等干扰物较多，选用GCB分别结合C18、HLB和PSA实验其优化效果.
结果表明(图3)，样品经过GCB柱处理后能够有效去除杂质，实现对目标提取物的纯化.然而，采用HLB +GCB和C18 + GCB固相萃取方法时，由于均为两次过柱操作，目标提取物在两次过柱过程中发生了显著损耗，导致回收率较低.相比之下，PSA + GCB固相萃取方法表现出较好的回收率和稳定性，无论是在植物地上部还是根部，均展现出显著优势.然而，本研究中使用的PSA与GCB填料结合柱在抽滤样品时，相较于单一填料的固相萃取柱，需要更大的压力且更容易发生堵塞.此外，PSA + GCB键合柱的成本较高，限制了其广泛应用.综合考虑经济性和实验操作的可行性，本研究最终选择C18柱作为固相萃取柱，以实现目标提取物的有效纯化.
2.2　标准曲线及检出限
由表2可知，3种天然甾体雌激素在浓度范围内具有良好的线性关系，相关系数均大于0.9995.分别用3倍噪音值法和液相色谱仪检定规程来计算3种天然甾体雌激素所对应的方法的检出限.如表3所示，可以得到雌三醇、雌二醇和雌酮的检出限分别为0.36~3.23、0.76~3.67和13.97~20.12μg/kg，保留时间的相对标准偏差均小0.1%.
2.3　加标回收率及相对标准偏差
在蔬菜样品中加入不同浓度的3种天然甾体雌激素混合标准溶液，制备加标浓度为50,500和1000μg/kg的加标样品，并将两者混合均匀后放置12h，使目标物与蔬菜样品充分接触.加标样品经超声提取、固相萃取柱净化和HPLC/FLD分析，每个混合加标样平行测定4次，计算3种天然甾体雌激素的回收率和相对标准偏差值(RSD).每次样品提取物分析后，纯甲醇样品分析均未显示仪器残留，整个过程证明是稳定的.通过对其他浓度的回收率测试进一步验证了稳健性，由表4可知，上海青地上部样品中3种物质的平均回收率为104.9%~130.5%，相对标准偏差为4.9%~18.7%;根部样品中3种物质的平均回收率为80.5%~129.9%，相对标准偏差为4.2%~38.8%.表明所建立方法的准确性与精密度均良好，满足分析测定的要求.
2.4　方法比较
将本研究建立的方法与目前已发表的蔬菜中雌激素的检测方法进行对比，目前检测蔬菜中雌激素的方法主要采用气相色谱-串联质谱(GC-MS/MS)或液相色谱-串联质谱(LC-MS/MS)技术，具体结果见表5.液质联用对样品的纯度要求较高，需要进行更为复杂的前处理，在处理蔬菜类等复杂基质的样品时重复性可能不如高效液相色谱，且结果的准确性可能受到样品基质效应的影响.由于天然甾体雌激素的分子量大、饱和蒸汽压低，且分子中存在一些极性基团，可相互之间形成氢键，使得分子间结合更紧密，降低其挥发性.因此，使用气相色谱检测天然甾体雌激素时，需要在上样前进行衍生化处理，样品处理时间更长，并可能产生有毒残留物.气质联用和液质联用技术在仪器购置及运行成本方面均表现出较高的费用需求.本方法针对三种天然甾体雌激素的检测方法进行了优化，该方法在回收率方面表现出色，虽然检出限略高于基于质谱的检测方法，但在分离效率、分析速度和重复性方面均表现良好，且操作相对简便、成本较低，具有较高的实用性，能够满足日常检测的需求.
2.5　实际样品检测
按照粮农/世卫组织食品添加剂联合专家委员会对17β-雌二醇每日摄入量的评价[16],60kg的成人每日允许摄入17β-雌二醇的量为3μg，参考《中国居民膳食指南(2016)》建议成人每天应摄入300~500g蔬菜，即蔬菜中雌二醇含量小于60μg/kg dw为安全浓度.本次测量的样本中仅有机上海青可食用部分超过安全阈值，如表6所示，蔬菜样品均有天然甾体雌激素的检出，雌三醇地上部及根部检出率为100%;17β-雌二醇地上部检出率为75%，根部为100%;雌酮地上部检出率43.8%，根部为18.8%，其潜在风险仍需进一步研究.对实际样品的检测结果表明，本方法的检测效果良好，可用于开展蔬菜中3种天然甾体雌激素的检测.
3　结论
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3.1　采用超声提取-固相萃取-高效液相色谱联用的分析方法提取并检测蔬菜中天然甾体雌激素含量.对提取剂、提取剂体积、提取次数、固相萃取柱的种类进行优化，该方法对蔬菜地上部样品中3种物质的平均回收率为104.9%~130.5%，相对标准偏差为4.9%~18.7%;根部样品中3种物质的平均回收率为80.5%~129.9%，相对标准偏差为4.2%~38.8%.蔬菜中雌三醇、17β-雌二醇和雌酮的方法检出限分别为0.36~3.23，0.76~3.67和13.97~20.12μg/kg.
3.2　利用该方法对南京市内随机采样的蔬菜检测时发现，雌三醇地上部及根部检出率为100%;17β-雌二醇地上部检出率为75%，根部为100%;雌酮地上部检出率43.8%，根部为18.8%，其潜在风险仍需进一步研究.同时，检测结果表明，不同蔬菜对雌激素积累特征存在差异，本文方法可用于进一步明确不同种类蔬菜吸收和积累天然甾体雌激素的机制及风险.
基金
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  • 国家自然科学基金资助项目(42177016; 42261144738)
  • 江苏省重点研发计划项目(BE2022849)
文献
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2025年第45卷第6期
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  • 接收时间：2024-12-15
  • 首发时间：2026-02-27
  • 出版时间：2025-06-20
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  • 收稿日期：2024-12-15
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国家自然科学基金资助项目(42177016; 42261144738)
江苏省重点研发计划项目(BE2022849)
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    南京农业大学，土壤有机污染控制与修复研究所，江苏 南京 210095

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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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