Article(id=1215670313740846004, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250217006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1739721600000, receivedDateStr=2025-02-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767767988858, onlineDateStr=2026-01-07, pubDate=1753372800000, pubDateStr=2025-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767767988858, onlineIssueDateStr=2026-01-07, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767767988858, creator=13701087609, updateTime=1767767988858, updator=13701087609, issue=Issue{id=1215670311140381365, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='14', pageStart='1', pageEnd='326', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1767767988237, creator=13701087609, updateTime=1767970098618, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1216518023599538606, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1216518023599538607, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=47, endPage=56, ext={EN=ArticleExt(id=1215670314076390326, articleId=1215670313740846004, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Determination of 23 kinds of per-and polyfluoroalkyl substances in food by high efficiency reinforced fat removal bilayer column-ultra performance liquid chromatography-tandem mass spectrometry, columnId=1215670312151208635, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Food Safety Risk Monitoring and Assessment in Beijing, runingTitle=null, highlight=null, articleAbstract=

Objective To establish a method for simultaneous determination of 23 kinds of per-and polyfluoroalkyl substances (PFASs) in food by high efficiency reinforced fat removal bilayer column-ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Methods The sample was extracted and centrifuged, high efficiency reinforced fat removal bilayer column method was adopted for the purification, the sample solution was separated on an Shim-pack GISS Hp 3 μm C18 column using 2 mmol/L ammonium formate and methanol as mobile phase for gradient elution, detected by tandem mass spectrometry with multiple reactions monitoring (MRM), and quantified by internal standard method. Results The 23 kinds of target compounds of PFASs were well retained on the chromatographic column with good linearity in the range of 0.2-50.0 µg/L (r2>0.995). The limits of detection (LODs) and the limits of quantitation (LOQs) about perfluorobutanoic acid (PFBA) and perfluoropentanoic acid (PFPeA) were 0.06 μg/kg and 0.18 μg/kg respectively. LODs and LOQs about the remaining 21 kinds of perfluorinated compounds were 0.03 μg/kg and 0.09 μg/kg, respectively. The recoveries of the 23 kinds of target compounds of 2.0 μg/kg and 10.0 μg/kg spiked levels in the meat, fish and milk matrix ranged from 70.3%-120.0% with relative standard deviations of 1.56%-9.65%. Conclusion This method is easy, fast, accurate and sensitive, which is suitable for the determination of 23 kinds of PFASs in food.

, correspAuthors=Jie GAO, Sai FAN, 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=Li-Ping LI, Yuan GUO, Da-Jin YANG, Rong ZHAO, Ping LIU, Jie GAO, Sai FAN), CN=ArticleExt(id=1215670315057857475, articleId=1215670313740846004, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=高效增强除脂双层柱结合超高效液相色谱-串联质谱法快速测定食品中23种全氟及多氟烷基化合物含量, columnId=1215670313522746049, journalTitle=食品安全质量检测学报, columnName=专题:北京市食品安全风险监测与评估, runingTitle=null, highlight=null, articleAbstract=

目的 建立高效增强除脂双层柱结合超高效液相色谱-串联质谱法(ultra performance liquid chromatography-tandem mass spectrometry, UPLC-MS/MS)同时检测食品中23种全氟和多氟烷基化合物(per-and polyfluoroalkyl substances, PFASs)的分析方法。方法 试样经提取、离心后, 上清液经高效增强除脂双层柱的快速滤过式固相萃取柱净化后, Shim-pack GISS Hp 3 μm C18色谱柱分离, 以2 mmol/L甲酸铵水溶液和甲醇为流动相进行梯度洗脱, 质谱采用多反应监测模式(multiple response monitoring, MRM), 内标法定量。结果 23种目标化合物在色谱柱上有很好地保留, 在0.2~50.0 µg/L范围内具有良好线性(r20.995)。全氟丁烷羧酸(perfluorobutanoic acid, PFBA)和全氟戊烷羧酸(perfluoropentanoic acid, PFPeA)的检出限(limits of detection, LODs)为0.06 μg/kg、定量限(limits of quantitation, LOQs)为0.18 μg/kg; 剩余21种全氟和多氟烷基化合物的LODs为0.03 μg/kg、LOQs为0.09 μg/kg。在猪肉、鱼肉和液态乳类基质样品中添加2.0 μg/kg和10.0 μg/kg浓度水平的混合标准溶液做加标回收实验, 结果显示平均回收率为70.3%~120.0%, 相对标准偏差为1.56%~9.87%。结论 该方法简单、快速、结果准确、灵敏度高, 适合测定食品中23种PFASs。

, correspAuthors=高洁, 范赛, authorNote=null, correspAuthorsNote=
*高洁(1986—), 女, 硕士, 副研究员, 主要研究方向为食品卫生。E-mail: ;
范赛(1982—), 男, 博士, 研究员, 主要研究方向为食品安全与食品理化检验。E-mail:
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#李丽萍和郭垣为共同第一作者

李丽萍(1982—), 女, 硕士, 副主任技师, 主要研究方向为食品安全与食品理化检验。E-mail: ;

郭垣(1996—), 女, 博士, 助理研究员, 主要研究方向为食品卫生。E-mail:

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李丽萍(1982—), 女, 硕士, 副主任技师, 主要研究方向为食品安全与食品理化检验。E-mail: ;

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李丽萍(1982—), 女, 硕士, 副主任技师, 主要研究方向为食品安全与食品理化检验。E-mail: ;

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郭垣(1996—), 女, 博士, 助理研究员, 主要研究方向为食品卫生。E-mail:

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郭垣(1996—), 女, 博士, 助理研究员, 主要研究方向为食品卫生。E-mail:

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Physical and Chemical Examination -Chemisty, 2024, 60(1): 60-66., articleTitle=Filtration solid phase extraction column for determination of 15 per- and polyfluoroalkyl substances in egg using liquid chromatography-high resolution mass spectrometry, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1215686849000035117, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, xref=1, ext=[AuthorCompanyExt(id=1215686849012618030, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, companyId=1215686849000035117, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Beijing Center for Disease Prevention and Control, Beijing 100013, China), AuthorCompanyExt(id=1215686849021006639, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, companyId=1215686849000035117, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 北京市疾病预防控制中心, 北京 100013)]), AuthorCompany(id=1215686849134252848, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, xref=2, ext=[AuthorCompanyExt(id=1215686849142641457, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, companyId=1215686849134252848, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 China National Center for Food Safety Risk Assessment, Beijing 100022, China), AuthorCompanyExt(id=1215686849151030066, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, companyId=1215686849134252848, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 国家食品安全风险评估中心, 北京 100022)])], figs=[ArticleFig(id=1215686854037393499, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Fig.1, caption=MRM chromatograms of standard solutions of 23 kinds of PFASs (10.0 ng/mL), figureFileSmall=6FQiI41/tN7bTLvqr0TxHQ==, figureFileBig=iRa3pwS30YiYRUyGsPmhkg==, tableContent=null), ArticleFig(id=1215686854142251106, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=图1, caption=23种PFASs的标准溶液MRM色谱图(10.0 ng/mL), figureFileSmall=6FQiI41/tN7bTLvqr0TxHQ==, figureFileBig=iRa3pwS30YiYRUyGsPmhkg==, tableContent=null), ArticleFig(id=1215686854268080239, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Fig.2, caption=Comparison of elution capacity of methanol-water mobile phase system and acetonitrile-water mobile phase system for PFBA and its internal standards, figureFileSmall=fRBO128TSQd9rOfBgLNpNw==, figureFileBig=5WBTe2O77bNsjnoxbOAOWw==, tableContent=null), ArticleFig(id=1215686854356160635, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=图2, caption=甲醇-水流动相体系和乙腈-水流动相体系对PFBA及其内标的洗脱能力对比, figureFileSmall=fRBO128TSQd9rOfBgLNpNw==, figureFileBig=5WBTe2O77bNsjnoxbOAOWw==, tableContent=null), ArticleFig(id=1215686854452629638, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Fig.3, caption=Comparison of PFBA residues in different pretreatment solid phase extraction columns, figureFileSmall=Eq65OJmJ313URs4KcO9A/Q==, figureFileBig=g0UjUsopOToiSKNDDvGY8Q==, tableContent=null), ArticleFig(id=1215686854549098637, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=图3, caption=不同前处理固相萃取柱PFBA残留对比, figureFileSmall=Eq65OJmJ313URs4KcO9A/Q==, figureFileBig=g0UjUsopOToiSKNDDvGY8Q==, tableContent=null), ArticleFig(id=1215686854624596118, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Fig.4, caption=Comparison of the recoveries of partial PFASs in two resolubilized solvents, MeOH and MeOH/W, figureFileSmall=jhnzDShkxbIKfg4x67neCg==, figureFileBig=KBQgXRFngMQUm20HlUX4aA==, tableContent=null), ArticleFig(id=1215686854754619552, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=图4, caption=MeOH和MeOH/W两种复溶溶剂部分PFASs的回收率对比, figureFileSmall=jhnzDShkxbIKfg4x67neCg==, figureFileBig=KBQgXRFngMQUm20HlUX4aA==, tableContent=null), ArticleFig(id=1215686854842699944, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Table 1, caption=

Mass spectrometry parameters of 23 kinds of PFASs and quantitative internal standards

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 英文全称 英文简称 母离子
(m/z)
子离子
(m/z)
定量内标 锥孔电压
/V
碰撞能量
/V
全氟丁酸 perfluorobutanoic acid PFBA 213.0 169.0* 13C4-PFBA 20 8
全氟戊酸 perfluoropentanoic acid PFPeA 262.9 218.9* 13C5-PFPeA 24 8
全氟己酸 perfluorohexanoic acid PFHxA 312.9 268.9* 13C5-PFHxA 8 10
312.9 118.9 8 16
全氟庚酸 perfluoroheptanoic acid PFHpA 362.9 318.9* 13C4-PFHpA 22 10
362.9 168.9 22 14
全氟辛酸 perfluorooctanoic acid PFOA 412.9 368.9* 13C8-PFOA 18 10
412.9 168.9 18 18
全氟壬酸 perfluorononanoic acid PFNA 462.9 418.9* 13C9-PFNA 8 10
462.9 218.9 8 14
全氟癸酸 perfluorodecanoic acid PFDA 512.9 468.9* 13C6-PFDA 24 10
512.9 218.9 24 181
全氟十一酸 perfluoroundecanoic acid PFUdA 562.9 518.9* 13C7-PFUdA 10 10
562.9 268.9 10 18
全氟十二酸 perfluorododecanoic acid PFDoA 612.9 568.9* 13C2-PFDoA 30 12
612.9 168.9 30 22
全氟十三酸 perfluorotridecanoic acid PFTrDA 662.9 618.9* 13C2-PFTrDA 30 10
662.9 168.9 30 26
全氟十四酸 perfluorotetradecanoic acid PFTeDA 712.9 668.9* 13C2-PFTeDA 34 12
712.9 168.9 34 28
全氟十六酸 perfluorohexadecanoic acid PFHxDA 812.9 768.9* 13C2-PFTeDA 30 14
812.9 168.9 30 32
全氟十八酸 perfluorooctadecanoic acid PFODA 912.9 868.9* 13C2-PFTeDA 30 14
912.9 268.9 30 30
全氟丁烷磺酸 perfluorobutanesulfonic acid PFBS 298.9 79.9* 13C3-PFBS 76 26
298.9 98.8 76 24
全氟己烷磺酸 perfluorohexanesulfonic acid PFHxS 398.9 79.9* 13C3-PFHxS 20 36
398.9 98.8 20 30
全氟辛烷磺酸 perfluorooctane sulfonic acid PFOS 498.9 79.9* 13C8-PFOS 20 42
498.9 98.8 20 38
全氟癸烷磺酸 perfluorodecanesulfonic acid sodium PFDS 598.9 79.9* 13C7-PFUdA 20 52
598.9 98.9 20 42
6/2氯代多氟烷基醚磺酸 9-chlorohexadecafluoro-3-oxanonane-
1-sulfonic acid
F-53B(6/2) 530.9 82.9* 13C6-PFDA 58 34
530.9 351.0 58 28
8/2氯代多氟烷基醚磺酸 8: 2 chlorinated polyfluorinated ether sulfonic acid F-53B(8/2) 630.9 82.9* 13C2-PFDoA 36 28
630.9 451.1 36 26
全氟壬烷磺酸 perfluorononanesulfonic acid PFNS 548.5 79.8* 13C7-PFUdA 4 48
548.5 98.9 4 44
4,8-二氧杂-3H-全氟壬酸 4,8-dioxa-3h-perfluorononanoic acid DONA 376.7 84.9* 13C4-PFHpA 2 30
376.7 250.8 2 12
全氟戊烷磺酸 perfluoropentanesulfonic acid PFPeS 348.6 79.9* 13C5-PFHxA 20 28
348.6 98.8 20 28
全氟庚烷磺酸 perfluoroheptanesulfonic acid PFHpS 448.9 79.9* 13C8-PFOA 94 36
448.9 98.8 94 32
), ArticleFig(id=1215686855002083507, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=表1, caption=

23种PFASs及定量内标的质谱参数

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 英文全称 英文简称 母离子
(m/z)
子离子
(m/z)
定量内标 锥孔电压
/V
碰撞能量
/V
全氟丁酸 perfluorobutanoic acid PFBA 213.0 169.0* 13C4-PFBA 20 8
全氟戊酸 perfluoropentanoic acid PFPeA 262.9 218.9* 13C5-PFPeA 24 8
全氟己酸 perfluorohexanoic acid PFHxA 312.9 268.9* 13C5-PFHxA 8 10
312.9 118.9 8 16
全氟庚酸 perfluoroheptanoic acid PFHpA 362.9 318.9* 13C4-PFHpA 22 10
362.9 168.9 22 14
全氟辛酸 perfluorooctanoic acid PFOA 412.9 368.9* 13C8-PFOA 18 10
412.9 168.9 18 18
全氟壬酸 perfluorononanoic acid PFNA 462.9 418.9* 13C9-PFNA 8 10
462.9 218.9 8 14
全氟癸酸 perfluorodecanoic acid PFDA 512.9 468.9* 13C6-PFDA 24 10
512.9 218.9 24 181
全氟十一酸 perfluoroundecanoic acid PFUdA 562.9 518.9* 13C7-PFUdA 10 10
562.9 268.9 10 18
全氟十二酸 perfluorododecanoic acid PFDoA 612.9 568.9* 13C2-PFDoA 30 12
612.9 168.9 30 22
全氟十三酸 perfluorotridecanoic acid PFTrDA 662.9 618.9* 13C2-PFTrDA 30 10
662.9 168.9 30 26
全氟十四酸 perfluorotetradecanoic acid PFTeDA 712.9 668.9* 13C2-PFTeDA 34 12
712.9 168.9 34 28
全氟十六酸 perfluorohexadecanoic acid PFHxDA 812.9 768.9* 13C2-PFTeDA 30 14
812.9 168.9 30 32
全氟十八酸 perfluorooctadecanoic acid PFODA 912.9 868.9* 13C2-PFTeDA 30 14
912.9 268.9 30 30
全氟丁烷磺酸 perfluorobutanesulfonic acid PFBS 298.9 79.9* 13C3-PFBS 76 26
298.9 98.8 76 24
全氟己烷磺酸 perfluorohexanesulfonic acid PFHxS 398.9 79.9* 13C3-PFHxS 20 36
398.9 98.8 20 30
全氟辛烷磺酸 perfluorooctane sulfonic acid PFOS 498.9 79.9* 13C8-PFOS 20 42
498.9 98.8 20 38
全氟癸烷磺酸 perfluorodecanesulfonic acid sodium PFDS 598.9 79.9* 13C7-PFUdA 20 52
598.9 98.9 20 42
6/2氯代多氟烷基醚磺酸 9-chlorohexadecafluoro-3-oxanonane-
1-sulfonic acid
F-53B(6/2) 530.9 82.9* 13C6-PFDA 58 34
530.9 351.0 58 28
8/2氯代多氟烷基醚磺酸 8: 2 chlorinated polyfluorinated ether sulfonic acid F-53B(8/2) 630.9 82.9* 13C2-PFDoA 36 28
630.9 451.1 36 26
全氟壬烷磺酸 perfluorononanesulfonic acid PFNS 548.5 79.8* 13C7-PFUdA 4 48
548.5 98.9 4 44
4,8-二氧杂-3H-全氟壬酸 4,8-dioxa-3h-perfluorononanoic acid DONA 376.7 84.9* 13C4-PFHpA 2 30
376.7 250.8 2 12
全氟戊烷磺酸 perfluoropentanesulfonic acid PFPeS 348.6 79.9* 13C5-PFHxA 20 28
348.6 98.8 20 28
全氟庚烷磺酸 perfluoroheptanesulfonic acid PFHpS 448.9 79.9* 13C8-PFOA 94 36
448.9 98.8 94 32
), ArticleFig(id=1215686855127912635, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Table 2, caption=

Standard curves, correlation coefficients, LODs and LOQs of 23 kinds of PFASs

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 化合物 线性范围/(μg/L) 线性方程 相关系数(r2) LODs/(μg/kg) LOQs/(μg/kg)
1 PFBA 0.2~50.0 Y=1.51138×10−1X 0.995 0.06 0.18
2 PFPeA 0.2~50.0 Y=1.71257×10−1X 0.999 0.06 0.18
3 PFHxA 0.2~50.0 Y=1.71257×10−1X 0.999 0.03 0.09
4 PFHpA 0.2~50.0 Y=2.69281×10−1X+3.104×10−3 0.998 0.03 0.09
5 PFOA 0.2~50.0 Y=1.94797×10−1X+1.2460×10−2 0.999 0.03 0.09
6 PFNA 0.2~50.0 Y=1.94797×10−1X+1.2460×10−2 0.995 0.03 0.09
7 PFDA 0.2~50.0 Y=2.30514×10−1X+2.799×10−3 0.999 0.03 0.09
8 PFUdA 0.2~50.0 Y=1.80455×10−1X+9.08×10−4 0.998 0.03 0.09
9 PFDoA 0.2~50.0 Y=1.80054×10−1X+6.002×10−3 0.998 0.03 0.09
10 PFTrDA 0.2~50.0 Y=1.66319×10−1X+3.268×10−3 0.999 0.03 0.09
11 PFTeDA 0.2~50.0 Y=1.66319×10−1X+3.268×10−3 0.998 0.03 0.09
12 PFHxDA 0.2~50.0 Y=1.70122×10−1X+6.913×10−3 0.999 0.03 0.09
13 PFODA 0.2~50.0 Y=6.8935×10−2X+4.637×10−3 0.999 0.03 0.09
14 PFBS 0.2~50.0 Y=3.7836X 0.999 0.03 0.09
15 PFHxS 0.2~50.0 Y=6.8935×10−2X+4.637×10−3 0.999 0.03 0.09
16 PFOS 0.2~50.0 Y=2.48873×10−1X+3.489×10−3 0.995 0.03 0.09
17 PFDS 0.2~50.0 Y=1.40464×10−1X+7.849×10−3 0.999 0.03 0.09
18 F-53B(6/2) 0.2~50.0 Y=1.98794×10−1X+2.2031×10−2 0.995 0.03 0.09
19 F-53B(8/2) 0.2~50.0 Y=7.9656×10−2X+6.184×10−3 0.997 0.03 0.09
20 PFNS 0.2~50.0 Y=7.7446×10−2X+6.657×10−3 0.996 0.03 0.09
21 DONA 0.2~50.0 Y=2.1765×10−2X+1.951×10−3 0.998 0.03 0.09
22 PFPeS 0.2~50.0 Y=1.30911×10−1X+2.951×10−3 0.998 0.03 0.09
23 PFHpS 0.2~50.0 Y=1.02685×10−1X+5.239×10−3 0.997 0.03 0.09
), ArticleFig(id=1215686856390398146, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=表2, caption=

23种PFASs的标准曲线、相关系数、LODs和LOQs

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 化合物 线性范围/(μg/L) 线性方程 相关系数(r2) LODs/(μg/kg) LOQs/(μg/kg)
1 PFBA 0.2~50.0 Y=1.51138×10−1X 0.995 0.06 0.18
2 PFPeA 0.2~50.0 Y=1.71257×10−1X 0.999 0.06 0.18
3 PFHxA 0.2~50.0 Y=1.71257×10−1X 0.999 0.03 0.09
4 PFHpA 0.2~50.0 Y=2.69281×10−1X+3.104×10−3 0.998 0.03 0.09
5 PFOA 0.2~50.0 Y=1.94797×10−1X+1.2460×10−2 0.999 0.03 0.09
6 PFNA 0.2~50.0 Y=1.94797×10−1X+1.2460×10−2 0.995 0.03 0.09
7 PFDA 0.2~50.0 Y=2.30514×10−1X+2.799×10−3 0.999 0.03 0.09
8 PFUdA 0.2~50.0 Y=1.80455×10−1X+9.08×10−4 0.998 0.03 0.09
9 PFDoA 0.2~50.0 Y=1.80054×10−1X+6.002×10−3 0.998 0.03 0.09
10 PFTrDA 0.2~50.0 Y=1.66319×10−1X+3.268×10−3 0.999 0.03 0.09
11 PFTeDA 0.2~50.0 Y=1.66319×10−1X+3.268×10−3 0.998 0.03 0.09
12 PFHxDA 0.2~50.0 Y=1.70122×10−1X+6.913×10−3 0.999 0.03 0.09
13 PFODA 0.2~50.0 Y=6.8935×10−2X+4.637×10−3 0.999 0.03 0.09
14 PFBS 0.2~50.0 Y=3.7836X 0.999 0.03 0.09
15 PFHxS 0.2~50.0 Y=6.8935×10−2X+4.637×10−3 0.999 0.03 0.09
16 PFOS 0.2~50.0 Y=2.48873×10−1X+3.489×10−3 0.995 0.03 0.09
17 PFDS 0.2~50.0 Y=1.40464×10−1X+7.849×10−3 0.999 0.03 0.09
18 F-53B(6/2) 0.2~50.0 Y=1.98794×10−1X+2.2031×10−2 0.995 0.03 0.09
19 F-53B(8/2) 0.2~50.0 Y=7.9656×10−2X+6.184×10−3 0.997 0.03 0.09
20 PFNS 0.2~50.0 Y=7.7446×10−2X+6.657×10−3 0.996 0.03 0.09
21 DONA 0.2~50.0 Y=2.1765×10−2X+1.951×10−3 0.998 0.03 0.09
22 PFPeS 0.2~50.0 Y=1.30911×10−1X+2.951×10−3 0.998 0.03 0.09
23 PFHpS 0.2~50.0 Y=1.02685×10−1X+5.239×10−3 0.997 0.03 0.09
), ArticleFig(id=1215686856512032971, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Table 3, caption=

Recoveries of 23 kinds of PFASs (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
目标物 添加浓度
/(μg/kg)
液态乳
平均回收率/% RSDs/% 平均回收率/% RSDs/% 平均回收率/% RSDs/%
PFBA 2.0 84.4 9.65 119.0 7.63 105.0 8.65
10.0 99.6 7.34 105.0 8.67 84.6 9.07
PFPeA 2.0 107.0 8.77 103.0 7.44 88.3 8.74
10.0 84.0 7.96 98.7 7.01 89.5 7.45
PFHxA 2.0 85.2 8.02 95.6 4.55 97.6 3.20
10.0 80.1 7.98 104.0 6.34 113.0 5.73
PFHpA 2.0 88.1 5.89 103.0 4.54 89.0 2.43
10.0 85.7 6.88 88.7 6.78 87.1 5.61
PFOA 2.0 105.0 3.78 107.0 3.65 98.2 3.84
10.0 88.9 6.09 96.2 7.85 104.0 4.55
PFNA 2.0 97.4 7.34 107.0 6.56 75.0 8.35
10.0 82.3 6.71 112.0 3.86 85.2 7.44
PFDA 2.0 105.0 1.56 114.0 6.12 95.3 6.52
10.0 98.5 5.62 104.0 5.78 102.0 6.23
PFUdA 2.0 112.0 4.45 102.0 6.34 112.0 7.35
10.0 109.0 7.83 113.0 4.02 105.0 3.78
PFDoA 2.0 99.6 5.98 112.0 3.56 108.0 7.61
10.0 86.7 7.98 98.7 4.76 89.1 5.34
PFTrDA 2.0 104.0 8.50 114.0 9.02 113.0 8.79
10.0 104.0 4.64 118.0 9.87 98.1 6.35
PFTeDA 2.0 110.0 6.38 112.0 4.21 115.0 7.50
10.0 108.0 5.94 117.0 6.56 120.0 9.43
PFHxDA 2.0 108.0 4.12 70.8 5.68 77.6 6.88
10.0 105.0 7.42 75.9 5.89 106.0 3.69
PFODA 2.0 80.4 4.43 71.3 8.68 78.8 5.64
10.0 85.4 5.12 80.4 7.41 81.6 6.33
PFBS 2.0 88.3 3.98 112.0 4.15 86.4 6.00
10.0 70.3 8.76 105.0 6.32 82.2 2.43
PFHxS 2.0 84.5 4.32 89.6 7.65 90.2 8.78
10.0 86.6 4.87 96.7 5.65 86.3 7.53
PFOS 2.0 89.8 7.54 105.0 6.76 97.3 8.34
10.0 82.7 2.43 113.0 7.98 101.0 3.56
PFDS 2.0 81.7 5.65 78.7 7.66 86.4 4.34
10.0 80.1 7.87 75.8 3.56 88.5 7.55
F-53B(6/2) 2.0 108.0 6.12 81.4 5.73 95.7 3.76
10.0 110.0 4.86 88.3 2.12 79.6 7.97
F-53B(8/2) 2.0 86.4 2.76 116.0 3.67 104.0 5.45
10.0 77.6 6.78 107.0 5.45 88.7 3.78
PFNS 2.0 75.3 4.35 77.6 3.56 83.9 6.87
10.0 77.2 4.66 76.7 7.78 89.3 3.25
DONA 2.0 93.6 5.87 109.0 3.54 98.3 4.78
10.0 84.5 6.45 105.0 8.44 102.0 3.76
PFPeS 2.0 87.8 3.42 100.0 6.32 87.6 5.23
10.0 70.6 5.32 112.0 3.78 85.5 8.76
PFHpS 2.0 73.4 4.56 77.3 6.54 78.3 3.23
10.0 74.2 6.87 76.2 5.46 94.6 3.98
), ArticleFig(id=1215686856667222228, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=表3, caption=

23种PFASs的加标回收率(n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
目标物 添加浓度
/(μg/kg)
液态乳
平均回收率/% RSDs/% 平均回收率/% RSDs/% 平均回收率/% RSDs/%
PFBA 2.0 84.4 9.65 119.0 7.63 105.0 8.65
10.0 99.6 7.34 105.0 8.67 84.6 9.07
PFPeA 2.0 107.0 8.77 103.0 7.44 88.3 8.74
10.0 84.0 7.96 98.7 7.01 89.5 7.45
PFHxA 2.0 85.2 8.02 95.6 4.55 97.6 3.20
10.0 80.1 7.98 104.0 6.34 113.0 5.73
PFHpA 2.0 88.1 5.89 103.0 4.54 89.0 2.43
10.0 85.7 6.88 88.7 6.78 87.1 5.61
PFOA 2.0 105.0 3.78 107.0 3.65 98.2 3.84
10.0 88.9 6.09 96.2 7.85 104.0 4.55
PFNA 2.0 97.4 7.34 107.0 6.56 75.0 8.35
10.0 82.3 6.71 112.0 3.86 85.2 7.44
PFDA 2.0 105.0 1.56 114.0 6.12 95.3 6.52
10.0 98.5 5.62 104.0 5.78 102.0 6.23
PFUdA 2.0 112.0 4.45 102.0 6.34 112.0 7.35
10.0 109.0 7.83 113.0 4.02 105.0 3.78
PFDoA 2.0 99.6 5.98 112.0 3.56 108.0 7.61
10.0 86.7 7.98 98.7 4.76 89.1 5.34
PFTrDA 2.0 104.0 8.50 114.0 9.02 113.0 8.79
10.0 104.0 4.64 118.0 9.87 98.1 6.35
PFTeDA 2.0 110.0 6.38 112.0 4.21 115.0 7.50
10.0 108.0 5.94 117.0 6.56 120.0 9.43
PFHxDA 2.0 108.0 4.12 70.8 5.68 77.6 6.88
10.0 105.0 7.42 75.9 5.89 106.0 3.69
PFODA 2.0 80.4 4.43 71.3 8.68 78.8 5.64
10.0 85.4 5.12 80.4 7.41 81.6 6.33
PFBS 2.0 88.3 3.98 112.0 4.15 86.4 6.00
10.0 70.3 8.76 105.0 6.32 82.2 2.43
PFHxS 2.0 84.5 4.32 89.6 7.65 90.2 8.78
10.0 86.6 4.87 96.7 5.65 86.3 7.53
PFOS 2.0 89.8 7.54 105.0 6.76 97.3 8.34
10.0 82.7 2.43 113.0 7.98 101.0 3.56
PFDS 2.0 81.7 5.65 78.7 7.66 86.4 4.34
10.0 80.1 7.87 75.8 3.56 88.5 7.55
F-53B(6/2) 2.0 108.0 6.12 81.4 5.73 95.7 3.76
10.0 110.0 4.86 88.3 2.12 79.6 7.97
F-53B(8/2) 2.0 86.4 2.76 116.0 3.67 104.0 5.45
10.0 77.6 6.78 107.0 5.45 88.7 3.78
PFNS 2.0 75.3 4.35 77.6 3.56 83.9 6.87
10.0 77.2 4.66 76.7 7.78 89.3 3.25
DONA 2.0 93.6 5.87 109.0 3.54 98.3 4.78
10.0 84.5 6.45 105.0 8.44 102.0 3.76
PFPeS 2.0 87.8 3.42 100.0 6.32 87.6 5.23
10.0 70.6 5.32 112.0 3.78 85.5 8.76
PFHpS 2.0 73.4 4.56 77.3 6.54 78.3 3.23
10.0 74.2 6.87 76.2 5.46 94.6 3.98
), ArticleFig(id=1215686856793051355, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=EN, label=Table 4, caption=

Determination results of the quality control sample fish meal (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 平均值 RSDs/% 参考值/(μg/kg)
PFOA 4.44 8.18 4.62
PFNA 5.67 5.95 6.00
PFOS 3.88 6.71 4.11
PFDA 5.73 6.92 6.04
PFUdA 5.30 3.80 5.45
PFDoA 5.49 6.30 5.61
), ArticleFig(id=1215686856931463399, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670313740846004, language=CN, label=表4, caption=

质控样鱼粉的测定结果(n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 平均值 RSDs/% 参考值/(μg/kg)
PFOA 4.44 8.18 4.62
PFNA 5.67 5.95 6.00
PFOS 3.88 6.71 4.11
PFDA 5.73 6.92 6.04
PFUdA 5.30 3.80 5.45
PFDoA 5.49 6.30 5.61
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高效增强除脂双层柱结合超高效液相色谱-串联质谱法快速测定食品中23种全氟及多氟烷基化合物含量
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李丽萍 1, # , 郭垣 2, # , 杨大进 2 , 赵榕 1 , 刘平 1 , 高洁 2, * , 范赛 1, *
食品安全质量检测学报 | 专题:北京市食品安全风险监测与评估 2025,16(14): 47-56
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食品安全质量检测学报 | 专题:北京市食品安全风险监测与评估 2025, 16(14): 47-56
高效增强除脂双层柱结合超高效液相色谱-串联质谱法快速测定食品中23种全氟及多氟烷基化合物含量
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李丽萍1, # , 郭垣2, # , 杨大进2, 赵榕1, 刘平1, 高洁2, * , 范赛1, *
作者信息
  • 1 北京市疾病预防控制中心, 北京 100013
  • 2 国家食品安全风险评估中心, 北京 100022
  • 李丽萍(1982—), 女, 硕士, 副主任技师, 主要研究方向为食品安全与食品理化检验。E-mail: ;

    郭垣(1996—), 女, 博士, 助理研究员, 主要研究方向为食品卫生。E-mail:

通讯作者:

*高洁(1986—), 女, 硕士, 副研究员, 主要研究方向为食品卫生。E-mail: ;
范赛(1982—), 男, 博士, 研究员, 主要研究方向为食品安全与食品理化检验。E-mail:
Determination of 23 kinds of per-and polyfluoroalkyl substances in food by high efficiency reinforced fat removal bilayer column-ultra performance liquid chromatography-tandem mass spectrometry
Li-Ping LI1, # , Yuan GUO2, # , Da-Jin YANG2, Rong ZHAO1, Ping LIU1, Jie GAO2, * , Sai FAN1, *
Affiliations
  • 1 Beijing Center for Disease Prevention and Control, Beijing 100013, China
  • 2 China National Center for Food Safety Risk Assessment, Beijing 100022, China
出版时间: 2025-07-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250217006
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目的 建立高效增强除脂双层柱结合超高效液相色谱-串联质谱法(ultra performance liquid chromatography-tandem mass spectrometry, UPLC-MS/MS)同时检测食品中23种全氟和多氟烷基化合物(per-and polyfluoroalkyl substances, PFASs)的分析方法。方法 试样经提取、离心后, 上清液经高效增强除脂双层柱的快速滤过式固相萃取柱净化后, Shim-pack GISS Hp 3 μm C18色谱柱分离, 以2 mmol/L甲酸铵水溶液和甲醇为流动相进行梯度洗脱, 质谱采用多反应监测模式(multiple response monitoring, MRM), 内标法定量。结果 23种目标化合物在色谱柱上有很好地保留, 在0.2~50.0 µg/L范围内具有良好线性(r20.995)。全氟丁烷羧酸(perfluorobutanoic acid, PFBA)和全氟戊烷羧酸(perfluoropentanoic acid, PFPeA)的检出限(limits of detection, LODs)为0.06 μg/kg、定量限(limits of quantitation, LOQs)为0.18 μg/kg; 剩余21种全氟和多氟烷基化合物的LODs为0.03 μg/kg、LOQs为0.09 μg/kg。在猪肉、鱼肉和液态乳类基质样品中添加2.0 μg/kg和10.0 μg/kg浓度水平的混合标准溶液做加标回收实验, 结果显示平均回收率为70.3%~120.0%, 相对标准偏差为1.56%~9.87%。结论 该方法简单、快速、结果准确、灵敏度高, 适合测定食品中23种PFASs。

全氟和多氟烷基化合物  /  高效增强除脂双层柱  /  超高效液相色谱-串联质谱法

Objective To establish a method for simultaneous determination of 23 kinds of per-and polyfluoroalkyl substances (PFASs) in food by high efficiency reinforced fat removal bilayer column-ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Methods The sample was extracted and centrifuged, high efficiency reinforced fat removal bilayer column method was adopted for the purification, the sample solution was separated on an Shim-pack GISS Hp 3 μm C18 column using 2 mmol/L ammonium formate and methanol as mobile phase for gradient elution, detected by tandem mass spectrometry with multiple reactions monitoring (MRM), and quantified by internal standard method. Results The 23 kinds of target compounds of PFASs were well retained on the chromatographic column with good linearity in the range of 0.2-50.0 µg/L (r2>0.995). The limits of detection (LODs) and the limits of quantitation (LOQs) about perfluorobutanoic acid (PFBA) and perfluoropentanoic acid (PFPeA) were 0.06 μg/kg and 0.18 μg/kg respectively. LODs and LOQs about the remaining 21 kinds of perfluorinated compounds were 0.03 μg/kg and 0.09 μg/kg, respectively. The recoveries of the 23 kinds of target compounds of 2.0 μg/kg and 10.0 μg/kg spiked levels in the meat, fish and milk matrix ranged from 70.3%-120.0% with relative standard deviations of 1.56%-9.65%. Conclusion This method is easy, fast, accurate and sensitive, which is suitable for the determination of 23 kinds of PFASs in food.

per-and polyfluoroalkyl substances  /  high efficiency reinforced fat removal bilayer column  /  ultra performance liquid chromatography-tandem mass spectrometry
李丽萍, 郭垣, 杨大进, 赵榕, 刘平, 高洁, 范赛. 高效增强除脂双层柱结合超高效液相色谱-串联质谱法快速测定食品中23种全氟及多氟烷基化合物含量. 食品安全质量检测学报, 2025 , 16 (14) : 47 -56 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250217006
Li-Ping LI, Yuan GUO, Da-Jin YANG, Rong ZHAO, Ping LIU, Jie GAO, Sai FAN. Determination of 23 kinds of per-and polyfluoroalkyl substances in food by high efficiency reinforced fat removal bilayer column-ultra performance liquid chromatography-tandem mass spectrometry[J]. Journal of Food Safety & Quality, 2025 , 16 (14) : 47 -56 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250217006
全氟及多氟烷基化合物[1-4](per-and polyfluoroalkyl substances, PFASs)是一种人工合成的将碳链上与碳元素相连的氢元素部分或全都用氟元素取代所产生的一类物质, 通常由疏水性烷基链和亲水性官能团组成[5]。因其良好的化学稳定性、耐热性、疏水疏油性[1,6-7]及高表面活性等特性, 被广泛应用于纺织品[2]、皮革保护剂、纸张涂料、农药和消防泡沫[8-9]等人类生产和生活领域[10-11]。毒理学和流行病学研究表明PFASs具有潜在的神经毒性[5]、免疫毒性[12-13]、生殖毒性[14-16]和内分泌毒性[17]等, 并对多个器官产生直接或间接毒性作用[18]。由于碳氟键极强的稳定性[19], PFASs具有持久性[6,20-22]、生物积累性[3,23]等特点, 其潜在毒性以及长距离迁移性等特性[24]使得其污染已经逐渐成为全球性问题。环境介质中的PFASs进入到动物体内, 会发生生物蓄积作用并通过食物链[8,25]被逐级放大, 从而产生多种毒性效应, 可能导致器官衰竭或癌变[3,7,26-27]。全氟辛烷磺酸(perfluorooctane sulfonic acid, PFOS)及其盐类、全氟辛酸(perfluorooctanoic acid, PFOA)及其盐类和全氟己烷磺酸(perfluorohexane sulfonic acid, PFHxS)及其盐类及相关化合物已相继被被联合国环境规划署《关于持久性有机污染物的斯德哥尔摩公约》列为持久性有机污染物(persistent organic pollutants, POPs)管控清单, 我国在2023年也出台了相应的限制政策, 将上述物质列入《重点管控新污染物清单》[28-29]; 2023年11月, 国际癌症研究机构将PFOA归类为“对人类致癌”1类致癌物, PFOS归类为“可能对人类致癌”2B类致癌物[30]。人体主要通过呼吸吸入、皮肤接触、食物链循环和饮水暴露[17]4种途径接触PFASs, 其中食物链摄取是主要途径。人体内PFASs持续存在, 其消除半衰期从2年到8年不等[31]
我国现行检测标准GB 5009.253—2016《食品安全国家标准 动物源性食品中全氟辛烷磺酸(PFOS)和全氟辛酸(PFOA)的测定》中涵盖了PFOS和PFOA 2种典型PFASs。国内外食品中PFASs检测前处理技术有液液萃取、液固萃取、固相萃取、QuEChERS法等[14,16,26], 检测技术包括液相色谱-质谱技术(liquid chromatography-mass spectrometry, LC-MS)[26]、分子印迹传感器技术[3,9]和高分辨质谱法[6,14,32]等, 涉及的PFASs的种类从几种到几十种不等[21,32]。LC-MS因其特异性强、灵敏度高、线性范围宽等优势是PFASs检测的金标准[17,26]。食品中PFASs检测仍然面临挑战。首先, 传统的PFOA和PFOS虽然已限制使用, 但其多种替代物由于极性、溶解性和色谱保留行为等差异, 同时检测会出现溶剂效应和色谱不保留等现象; 其次, PFASs检测水平为痕量和超痕量, 食品基质因富含脂肪、蛋白质、磷脂等, 基质效应和背景干扰复杂, 提取、净化和富集困难, 目前主流净化方式包括复合吸附剂[33]、弱阴离子交换固相萃取柱[32]、通过式脂质吸附型固相萃取柱[34]等, 这些净化方式或存在操作复杂需活化和洗脱, 或存在只保留部分目标组分导致回收率差等问题; 再次, PFASs是一类环境污染物, 本底干扰大, 特别是低碳链的物质如全氟丁烷羧酸(perfluorobutanoic acid, PFBA)在检测仪器、耗材和提取溶剂中被大量检出。
本研究使用中等极性的乙腈提取目标化合物, 使用高效增强除脂双层柱进行净化, 将内标的使用范围扩大到14种, 建立了超高效液相色谱-串联质谱法同时测定食品中23种PFASs的分析方法, 为食品中PFASs的监测、膳食暴露和评估相关的疾病负担提供了有利的技术支撑。
ACQUITY UPLC H-Class超高效液相色谱仪、Xevo TQS三重四极杆质谱仪(美国Waters公司); XPE105十万分之一电子天平(瑞士Mettler Toledo公司); 3-18K高速冷冻离心机(德国Sigma公司); M8800H-C超声波清洗机(美国Bransonic公司); Shim-pack GISS Hp C18 (2.1 mm×150 mm, 3 μm)色谱柱(日本Shimadzu公司); Milli-Q超纯水仪(德国Merck公司); 高效增强除脂双层专用柱HLB-P/HMR-Lipid (200 mg/300 mg, 6 mL, 北京纳鸥公司)。
23种全氟和多氟烷基化合物混合标准品(5.0 µg/mL)、全氟十三酸内标(50 µg/mL)(德国Dr. Ehrenstorfer公司); 13种全氟和多氟烷基化合物混合内标(2.0 µg/mL, 加拿大Wellington公司); 乙腈、甲醇(色谱纯, 美国Thermo Fisher Scientific公司); 甲酸铵(色谱纯, 北京迪科马科技有限公司)。
食品样品采集于超市和农贸市场。散装样品每份样品采样量大于500 g; 预包装样品同一批号(或生产日期)的食品为1份样品, 每份样品的采样量大于500 g, 单个包装重量250 g以上的, 每份样品采集3~4个包装, 单个包装在250 g以下的, 每份样品采集5~8个包装。
混合标准中间液: 用甲醇将23种混合标准溶液配制成质量浓度为200 ng/mL全氟化合物的混合标准中间液, 4 ℃保存。
同位素内标中间液: 用甲醇将14种同位素混合内标溶液配制成质量浓度为200 ng/mL全氟和多氟烷基化合物的内标工作液, 4 ℃保存。
标准曲线: 用甲醇溶液将混合标准工作液逐级稀释为质量浓度0.2、1.0、5.0、10.0、50.0 ng/mL混合标准系列溶液, 标准曲线中全氟化合物的定量内标质量浓度为5.0 ng/mL。
固体样品: 取适量有代表性的可食部分试样, 切成小块, 组织捣碎机捣碎, 分成两份置于聚丙烯塑料离心管中, 作为试样和留样, 分别装入洁净容器中, 密封并标记, 于-18 ℃避光保存; 蛋类样品: 将蛋去壳后, 搅拌均匀, 分成两份置于聚丙烯塑料离心管中, 作为试样和留样, 分别装入洁净容器中, 密封并标记, 于-18 ℃保存备用。
固体样品(畜禽肉、水产品等)提取: 准确称取2 g(精确至0.001 g)试样置于50 mL具塞离心管中, 加入10 μL同位素内标使用液, 准确加入2.0 mL超纯水, 涡旋振荡3 min, 加入8.0 mL乙腈, 混匀超声振荡30 min, 10000 r/min离心10 min, 取全部上清液待净化。
液体样品(蛋类、液态乳等)提取: 准确称取5 g(精确至0.001 g)试样置于50 mL具塞离心管中, 加入25 μL同位素内标使用液, 加入20 mL乙腈, 混匀超声振荡30 min, 10000 r/min离心10 min, 取上清液10.0 mL待净化。
吸取上述上清液, 按通过式的方式过固相萃取柱, 收集全部流出液, 加1.5 g氯化钠混匀振荡分层, 10000 r/min离心10 min, 取上层乙腈层4.0 mL氮吹吹干, 0.2 mL甲醇复溶后供超高效液相色谱-串联质谱仪测定。
(1)超高效液相色谱条件
Shim-pack GISS Hp C18 (2.1 mm×150 mm, 3 μm), 流动相: 2.0 mmol/L甲酸铵水溶液(B1)-甲醇(A2), 流速: 0.4 mL/min, 进样体积: 2 μL, 柱温: 35 ℃。液相色谱梯度洗脱程序: 0~0.5 min, 80% B1; 0.5~9.0 min, 80%~5% B1; 9.0~12.0 min, 5% B1; 12.0~12.1 min, 80% B1
(2)质谱条件
离子源: 电喷雾电离(electrospray ionization, ESI), 负离子模式ESI(-); 毛细管电压: 2.0 kV; 碰撞气: 氩气; 脱溶剂气温度: 500 ℃; 脱溶剂气流量: 1000 L/h; 扫描模式: 多反应监测(multiple reaction monitoring, MRM)模式。
本研究采用Masslynx 4.1软件进行定性定量分析, 数据处理和绘图使用Microsoft Office 2021软件和Origin 2021软件。
将23种混合标准溶液和14种内标稀释成0.1 mg/L质量浓度的流动注射溶液, 注入质谱仪中, 分别在正离子和负离子模式下进行一级质谱扫描。结果表明, 23种化合物和14种内标在负离子模式下有质谱信号, 选择负离子模式, 确定化合物的分子离子峰, 将分子离子作为母离子, 再进一步进行二级质谱扫描, 选取丰度较强、干扰较小的两个子离子分别作为定性及定量离子, 并优化锥孔电压和碰撞能量, 23种全氟化合物质谱参数优化结果见表1, 对应表1的23种化合物的标准溶液MRM色谱图见图1
C4~C18不同碳链长度的全氟和多氟烷基化合物极性差异大, 本研究对比了甲醇-水流动相体系和乙腈-水流动相体系对全氟和多氟烷基化合物的洗脱能力图2, 发现在PFBA和PFPeA的检测中, 甲醇-水流动相体系比乙腈-水流动相体系具有显著性优势, 所以选择甲醇-水作为流动相体系。本研究发现选择甲醇-水流动相体系色谱柱压力相对乙腈-水流动相体系显著升高, 选择小颗粒度的色谱柱会出现柱压过载漏液的现象, 因此选择岛津Shim-pack GISS Hp C18 (2.1 mm×150 mm, 3 μm)色谱柱作为分析柱, 实验结果显示23种化合物都有较好的保留和较高的灵敏度。在流动相中加入甲酸铵能提高目标化合物的响应并改善峰型, 选择甲酸铵溶液的浓度2.0 mmol/L, 各组分响应值、峰型及分离度满足检测要求。
PFASs的提取方式有索氏萃取、加压液相萃取、液-液萃取、分散液-液微萃取和离子对萃取等[5]。由于PFASs结构的多样性, 不同的提取方式对于样品基质、PFASs类型等有较强的选择性。本研究选择中等极性沉淀蛋白效果好的乙腈溶液进行萃取, 具有操作方便, 稳定性好等特点, 可简化和标准化前处理步骤, 提高PFASs分析效率。本研究采用2.0 mL水充分分散固体样品基质后加入8 mL乙腈提取, 有效避免直接加入有机溶剂时脂肪含量高的样品基质结团而影响提取效率的情况。
PFASs可以在常见的基本实验室组件、移液头、试剂、溶剂和仪器组件中找到, PFBA是一个主要的干扰[21]。PFASs的净化常用混合型弱阴离子交换型、混合型强阴离子交换型、亲水亲脂平衡吸附型等固相萃取柱。这些固相萃取柱多需要活化、上样、清洗、洗脱等复杂的操作过程, 并存在部分目标化合物回收率低的情况。本研究比较了3款滤过式的净化柱PRiME HLB、HLB-P/HMR-Lipid和Captiva EMR-Lipid, 发现HLB-P/HMR-Lipid高效增强除脂双层专用柱不但净化效果优异, 且在低碳链全氟化合物如PFBA和PFPeA中的本底含量最低, 干扰最小。经检测, Captiva EMR-Lipid和PRiME HLB中PFBA含量分别为试剂空白值的37倍和23倍, 见图3。本研究首次选择使用HLB-P/HMR-Lipid高效增强除脂双层专用柱作为前处理净化柱, 23种PFASs回收率范围70.3%~119.0%。该固相萃取柱无需活化、洗脱等操作, 简化了样品前处理过程, 可实现重力自流, 快速有效。
为保证长碳链的PFASs溶解性, 比较MeOH和MeOH:W (4:6, V:V)两种复溶溶剂的在鱼肉基质加标量1.0 μg/kg的水平下部分代表性全氟化合物的回收率情况, 结果显示MeOH:W (4:6, V:V)作为复溶溶剂, PFODA和PFHxDA的回收率都小于50%, 见图4, 故选择甲醇为复溶溶剂。
进样时因与初始流动相溶剂不一致, 容易产生溶剂效应, 表现为峰展宽, 峰型不对称, 定量不准确。本研究采用初始流动相为80%的2.0 mmol/L甲酸铵水溶液-20%甲醇流动相体系, 使用2.0 μL的进样体积能显著降低溶剂效应, 同时满足灵敏度需求; 另外可使用溶剂效应消除器能将进样量提高至10.0 μL, 进一步提高检测方法的灵敏度。进样过程中洗针液的极性也会造成长碳链的PFASs如PFODA和PFHxDA残留, 可能污染样品, 定性和定量不准确。考虑到PFODA和PFHxDA极性特点将弱清洗针溶液换成高有机相比例, 从而减少残留。
按照各目标组分的质谱响应特性, 配制混合标准溶液系列, 在优化后的色谱和串联质谱条件下进行测定, 以各待测物的色谱峰面积对其在溶液中的含量进行线性拟合, 以信噪比为3 (S/N=3)计算检出限(limit of detection, LOD), 信噪比为10 (S/N=10)计算定量限(limit of quantitation, LOQ)。结果表明, 23种PFASs标准曲线的线性范围均为0.20~50.00 µg/L, 具有良好线性(r2>0.995), PFBA和PFPeA的LODs为0.06 μg/kg、LOQs为0.18 μg/kg; 剩余21种PFASs的LODs为0.03 μg/kg、LOQs为0.09 μg/kg, 满足食品中PFASs的定量检测要求。23种PFASs的标准曲线、相关系数、LODs和LOQs见表2
分别在猪肉、鱼肉和液态乳类基质样品中添加2.0 μg/kg和10.0 μg/kg浓度水平的混合标准溶液做加标回收实验, 每个浓度水平平行测定6次。结果显示平均回收率为70.3%~120.0%, 相对标准偏差(relative standard deviation, RSD)为1.56%~9.87%, 本方法测量结果的RSDs均小于10%, 满足方法精密度要求; 优化后的方法加标回收率满足前处理过程误差和损耗较小的要求, 表明该方法准确度良好, 结果详见表3。同时本方法使用含有PFOA、PFNA、PFOS、PFDA、PFuDA、PFdOA 6种全氟及多氟烷基化合物的国家二级标准参考物质鱼粉作为质控样评价方法的精密度和准确度, 每个样品重复测定6次。鱼粉平行测定6次后6种目标全氟及多氟烷基化合物的均值均在参考值范围内, RSDs为3.80%~8.18%, 结果均为满意, 详见表4。说明本方法的准确度与精密度良好, 能够满足食品中PFASs测定要求。
按照本研究方法对10份市售猪肉样品进行检测。结果显示: 检出的PFASs种类有PFOA、PFOS、PFTrDA共3种, 检出值范围0.042~0.210 μg/kg。
按照本研究方法对10份市售鱼类样品进行检测。结果显示: 检出的PFASs种类有PFBA、PFPeA、PFOA、PFOS、PFNA、PFDA、PFUdA、6/2F-53B、8/2F-53B共9种, 检出值范围0.034~0.610 μg/kg。
按照本研究方法对10份市售液态乳样品进行检测, PFASs均未检出。
本研究通过改进后的前处理技术及色谱-质谱技术, 建立了一种高效增强除脂双层柱结合超高效液相色谱-串联质谱法同时测定食品中23种PFASs的快速、准确、灵敏的分析方法。方法成功应用于实际食品样品中PFASs的多残留分析, 在12 min内即可完成目标物的检测分析, 检出水平处于0.03 μg/kg级别。该方法具有前处理简单分析速度快、消耗有机溶剂少较环保、灵敏高和准确性高等优点, 为食品中PFASs的快速定量分析提供了新的解决方案。
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2025年第16卷第14期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250217006
  • 接收时间:2025-02-17
  • 首发时间:2026-01-07
  • 出版时间:2025-07-25
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  • 收稿日期:2025-02-17
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    1 北京市疾病预防控制中心, 北京 100013
    2 国家食品安全风险评估中心, 北京 100022

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*高洁(1986—), 女, 硕士, 副研究员, 主要研究方向为食品卫生。E-mail: ;
范赛(1982—), 男, 博士, 研究员, 主要研究方向为食品安全与食品理化检验。E-mail:
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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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