Article(id=1151881495498076611, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1151881493552394994, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20241013001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728748800000, receivedDateStr=2024-10-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752559549450, onlineDateStr=2025-07-15, pubDate=1748102400000, pubDateStr=2025-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752559549450, onlineIssueDateStr=2025-07-15, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752559549450, creator=13701087609, updateTime=1752559549450, updator=13701087609, issue=Issue{id=1151881493552394994, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='10', pageStart='1', pageEnd='324', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752559548986, creator=13701087609, updateTime=1756202008453, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1167159075906265916, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1151881493552394994, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1167159075906265917, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1151881493552394994, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=72, endPage=81, ext={EN=ArticleExt(id=1151923894417453732, articleId=1151881495498076611, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Research progress on detection methods and pollution levels of perfluoroalkyl and polyfluoroalkyl substances in animal-derived foods, columnId=1151923892655846010, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Food Safety Risk Assessment and Risk Monitoring, runingTitle=null, highlight=null, articleAbstract=

Perfluoroalkyl and polyfluoroalkyl substances (PFASs), characterized by their environmental persistence, bioaccumulation potential, hydrophobic and oleophobic properties, and chemical stability, have been extensively applied in industrial production and daily life. However, the widespread presence of these compounds poses significant threats to both ecological systems and human health. Dietary intake, particularly through animal-derived foods (e.g., fish, shellfish, poultry, and their processed products), represents a primary pathway of human exposure to PFASs. To effectively assess their health risks and formulate relevant regulatory policies, it is crucial to establish rapid, efficient, and sensitive detection methods for monitoring PFAS contamination levels in animal-derived foods. This review systematically summarized sample preparation techniques for PFAS analysis in animal-derived foods and highlights advancements in chromatographic and chromatographic-mass spectrometric methods for detection. Furthermore, it provided an overview of current research on PFAS contamination levels across various food matrices, offering critical insights for environmental pollution assessment, food safety regulation, and optimization of analytical technologies.

, correspAuthors=Jia-Yong HU, Xin LIU, 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=Run LI, Jing-Lei ZHAO, Jia-Yong HU, Xin LIU), CN=ArticleExt(id=1151923896296501961, articleId=1151881495498076611, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=动物源性食品中全氟及多氟化合物的检测方法及污染水平研究进展, columnId=1151923892995109553, journalTitle=食品安全质量检测学报, columnName=专题:食品安全风险评估与风险监测, runingTitle=null, highlight=null, articleAbstract=

全氟及多氟化合物(perfluoroalkyl and polyfluoroalkyl substances, PFASs)因其环境持久性、生物累积性、疏水疏油性及化学稳定性, 被广泛应用于工业生产和日常生活。然而, 这些化合物的广泛存在对生态环境和人类健康构成了严重威胁, 尤其是通过动物源性食品(如鱼类、贝类、家禽及其加工产品等)的膳食摄入, 是人类暴露于PFASs的主要途径之一。为有效评估其健康风险并制定相关监管政策, 建立快速、高效、灵敏的检测方法以监测动物源性食品中的PFASs污染水平至关重要。本文系统综述了动物源性食品中PFASs的样品前处理方法, 并重点探讨了色谱技术及色谱-质谱联用技术在检测中的应用进展。进一步总结了不同基质的动物源性食品中PFASs污染水平的研究现状, 为环境污染评估、食品安全监管及检测技术的优化提供了重要参考。

, correspAuthors=胡家勇, 柳鑫, authorNote=null, correspAuthorsNote=
* 胡家勇(1989—), 男, 工程师, 主要研究方向为食品安全检测。E-mail:
柳鑫(1987—), 男, 教授, 主要研究方向为食品安全风险评估。E-mail:
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李润(2002—), 女, 硕士研究生, 主要研究方向为食品加工与安全。E-mail:

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Critical Reviews in Food Science and Nutrition, 2011, 51(7): 605-625., articleTitle=Perfluorinated compounds in food: A global perspective, refAbstract=null), Reference(id=1167158457586168388, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, doi=null, pmid=null, pmcid=null, year=2017, volume=605-606, issue=null, pageStart=38, pageEnd=47, url=null, language=null, rfNumber=[72], rfOrder=71, authorNames=BABUT M, LABADIE P, SIMONNET-LAPRADE C, journalName=Science of the Total Environment, refType=null, unstructuredReference=BABUT M, LABADIE P, SIMONNET-LAPRADE C, et al. Per- and poly-fluoroalkyl compounds in freshwater fish from the Rhône River: Influence of fish size, diet, prey contamination and biotransformation[J]. Science of the Total Environment, 2017, 605-606: 38-47., articleTitle=Per- and poly-fluoroalkyl compounds in freshwater fish from the Rhône River: Influence of fish size, diet, prey contamination and biotransformation, refAbstract=null), Reference(id=1167158457703608901, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, doi=null, pmid=null, pmcid=null, year=2013, volume=61, issue=38, pageStart=9052, pageEnd=9062, url=null, language=null, rfNumber=[73], rfOrder=72, authorNames=STILL M, SCHLUMMER M, GRUBER L, journalName=Journal of Agricultural and Food Chemistry, refType=null, unstructuredReference=STILL M, SCHLUMMER M, GRUBER L, et al. Impact of industrial production and packaging processes on the concentration of per- and polyfluorinated compounds in milk and dairy products[J]. Journal of Agricultural and Food Chemistry, 2013, 61(38): 9052-9062., articleTitle=Impact of industrial production and packaging processes on the concentration of per- and polyfluorinated compounds in milk and dairy products, refAbstract=null), Reference(id=1167158457770717766, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, doi=null, pmid=null, pmcid=null, year=2024, volume=1730, issue=null, pageStart=465041, pageEnd=null, url=null, language=null, rfNumber=[74], rfOrder=73, authorNames=AßHOFF N, BERNSMANN T, ESSELEN M, journalName=Journal of Chromatography A, refType=null, unstructuredReference=AßHOFF N, BERNSMANN T, ESSELEN M, et al. A sensitive method for the determination of per-and polyfluoroalkyl substances in food and food contact material using high-performance liquid chromatography coupled with tandem mass spectrometry[J]. 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Food Additives & Contaminants: Part A, 2013, 30(11): 1918-1932., articleTitle=Occurrence of perfluoroalkyl substances (PFASs) in various food items of animal origin collected in four European countries, refAbstract=null), Reference(id=1167158457993015880, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, doi=null, pmid=null, pmcid=null, year=2020, volume=740, issue=null, pageStart=140116, pageEnd=null, url=null, language=null, rfNumber=[76], rfOrder=75, authorNames=KOTTHOFF M, FLIEDNER A, RÜDEL H, journalName=Science of the Total Environment, refType=null, unstructuredReference=KOTTHOFF M, FLIEDNER A, RÜDEL H, et al. Per- and polyfluoroalkyl substances in the German environment-Levels and patterns in different matrices[J]. Science of the Total Environment, 2020, 740: 140116., articleTitle=Per- and polyfluoroalkyl substances in the German environment-Levels and patterns in different matrices, refAbstract=null), Reference(id=1167158458068513353, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, doi=null, pmid=null, pmcid=null, year=2022, volume=204, issue=null, pageStart=112033, pageEnd=null, url=null, language=null, rfNumber=[77], rfOrder=76, authorNames=MELAKE BA, BERVOETS L, NKUBA B, journalName=Environmental Research, refType=null, unstructuredReference=MELAKE BA, BERVOETS L, NKUBA B, et al. Distribution of perfluoroalkyl substances (PFASs) in water, sediment, and fish tissue, and the potential human health risks due to fish consumption in Lake Hawassa, Ethiopia[J]. Environmental Research, 2022, 204: 112033., articleTitle=Distribution of perfluoroalkyl substances (PFASs) in water, sediment, and fish tissue, and the potential human health risks due to fish consumption in Lake Hawassa, Ethiopia, refAbstract=null), Reference(id=1167158458232091210, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, doi=null, pmid=null, pmcid=null, year=2021, volume=8, issue=12, pageStart=1085, pageEnd=1090, url=null, language=null, rfNumber=[78], rfOrder=77, authorNames=BANGMA JT, REINER J, FRY RC, journalName=Environmental Science & Technology Letters, refType=null, unstructuredReference=BANGMA JT, REINER J, FRY RC, et al. Identification of an analytical method interference for perfluorobutanoic acid in biological samples[J]. Environmental Science & Technology Letters, 2021, 8(12): 1085-1090., articleTitle=Identification of an analytical method interference for perfluorobutanoic acid in biological samples, refAbstract=null), Reference(id=1167158458336948811, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, doi=null, pmid=null, pmcid=null, year=2023, volume=171, issue=null, pageStart=107640, pageEnd=null, url=null, language=null, rfNumber=[1], rfOrder=78, authorNames=HERZKE D, NIKIFOROV V, YEUNG L W, journalName=Environment International, refType=null, unstructuredReference=HERZKE D, NIKIFOROV V, YEUNG L W, et al. Targeted PFAS analyses and extractable organofluorine-Enhancing our understanding of the presence of unknown PFAS in Norwegian wildlife[J]. Environment International, 2023, 171: 107640., articleTitle=Targeted PFAS analyses and extractable organofluorine-Enhancing our understanding of the presence of unknown PFAS in Norwegian wildlife, refAbstract=null)], funds=[Fund(id=1167158448790712827, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, awardId=KF-202301, language=CN, fundingSource=国家市场监管重点实验室(动物源性食品中重点化学危害物检测技术)开放课题项目(KF-202301), fundOrder=null, country=null), Fund(id=1167158448853627388, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, awardId=2022YFF1102500, language=CN, fundingSource=国家重点研发计划项目(2022YFF1102500), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1167158445020033491, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, xref=null, ext=[AuthorCompanyExt(id=1167158445024227796, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, companyId=1167158445020033491, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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School of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China), AuthorCompanyExt(id=1167158445133279704, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, companyId=1167158445120696790, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.武汉轻工大学食品科学与工程学院, 武汉 430023)])], figs=[ArticleFig(id=1167158448136401399, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, language=EN, label=Table 1, caption=

Sample preparation methods for PFASs detection in animal-derived foods

, figureFileSmall=null, figureFileBig=null, tableContent=
样品类型 目标化合物 提取 提纯方法 参考文献
鱼、肉、肝脏 PFOS、PFOSA、PFOA / SPE (Oasis WAX) [26]
鸡蛋 PFOS、PFOA、PFNA、PFHxS 甲醇/氢氧化钾 SPE (Oasis WAX, ENVI Carb) [34]
PFOS, PFBA, PFAS 甲醇/乙腈 QuEChERS [33]
牛奶、乳制品和鸡蛋 PFOS和PFOA、PFBA、PFHxA、PFOSA 碱性消化 TFC [35]
海鲜 PFOA、PFTrDA、PFOS和PFPeA 离子对萃取 液液萃取 [31]
油脂 PFOA、PFBA / QuEChERS (d-SPE) [37]
禽蛋 PFOS、PFOA 乙腈 SPE [36]
鱼类肌肉组织 PFSA、PFCA ASE SPE [38]
动物组织 8-2 FTOH / 小型化固相萃取 [39]
肉类(牛、鱼和猪肌肉)、牛肝、鸡蛋和牛奶 PFNA、PFDA、PFOS和PFUnA 乙腈 QuEChERS (d-SPE) [40]
牛奶 PFOA、PFOS MIP-PR-DFE / [41]
猪肉 PFOA、PFNA、PFDA MIP-PR QuEChERS (d-SPE) [42]
牛奶 PFASs / QuEChERS [43]
PFOSs 乙腈 SPE (Oasis WAX) [44]
鸡蛋 PFOSs / / [45]
), ArticleFig(id=1167158448291590648, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, language=CN, label=表1, caption=

动物源性食品中PFASs检测样品前处理方法

, figureFileSmall=null, figureFileBig=null, tableContent=
样品类型 目标化合物 提取 提纯方法 参考文献
鱼、肉、肝脏 PFOS、PFOSA、PFOA / SPE (Oasis WAX) [26]
鸡蛋 PFOS、PFOA、PFNA、PFHxS 甲醇/氢氧化钾 SPE (Oasis WAX, ENVI Carb) [34]
PFOS, PFBA, PFAS 甲醇/乙腈 QuEChERS [33]
牛奶、乳制品和鸡蛋 PFOS和PFOA、PFBA、PFHxA、PFOSA 碱性消化 TFC [35]
海鲜 PFOA、PFTrDA、PFOS和PFPeA 离子对萃取 液液萃取 [31]
油脂 PFOA、PFBA / QuEChERS (d-SPE) [37]
禽蛋 PFOS、PFOA 乙腈 SPE [36]
鱼类肌肉组织 PFSA、PFCA ASE SPE [38]
动物组织 8-2 FTOH / 小型化固相萃取 [39]
肉类(牛、鱼和猪肌肉)、牛肝、鸡蛋和牛奶 PFNA、PFDA、PFOS和PFUnA 乙腈 QuEChERS (d-SPE) [40]
牛奶 PFOA、PFOS MIP-PR-DFE / [41]
猪肉 PFOA、PFNA、PFDA MIP-PR QuEChERS (d-SPE) [42]
牛奶 PFASs / QuEChERS [43]
PFOSs 乙腈 SPE (Oasis WAX) [44]
鸡蛋 PFOSs / / [45]
), ArticleFig(id=1167158448425808377, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, language=EN, label=Table 2, caption=

Analytical instrumentation methods for PFASs detection in animal-derived foods

, figureFileSmall=null, figureFileBig=null, tableContent=
仪器分析方法 目标化合物回收率/% 定量限/(μg/kg) 检出限/(ng/g) 参考文献
LC-MS/MS / 0.001 / [26]
LC-MS/MS / 0.005~0.163 / [34]
LC-Q-TO F / / / [33]
LC-QqQ-MS 50~120 0.005~0.650 0.017~2.000 [35]
LC-MS/MS 80~120 0.04~0.18 0.01~0.06 [31]
LC-MS/MS 72~104 0.002~0.075 / [37]
LC-MS/MS 84~102 / / [36]
LC-ESI-MS/MS / 0.05~3.79 0.02~1.25 [50]
LC-MS/MS 78.0~90.3 0.10~1.5 / [39]
LC-MS/MS 80~120 / 0.05 [40]
LC-MS/MS 94.7~109 / / [41]
LC-MS/MS 89.3~116.3 / 0.011~0.08 [42]
LC-MS/MS 71.7~116 0.01~0.26 0.004~0.079 [43]
UPLC-MS/MS / / / [44]
LC-MS/MS / <0.5 / [45]
), ArticleFig(id=1167158448547443194, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881495498076611, language=CN, label=表2, caption=

动物源性食品中PFASs分析仪器检测方法

, figureFileSmall=null, figureFileBig=null, tableContent=
仪器分析方法 目标化合物回收率/% 定量限/(μg/kg) 检出限/(ng/g) 参考文献
LC-MS/MS / 0.001 / [26]
LC-MS/MS / 0.005~0.163 / [34]
LC-Q-TO F / / / [33]
LC-QqQ-MS 50~120 0.005~0.650 0.017~2.000 [35]
LC-MS/MS 80~120 0.04~0.18 0.01~0.06 [31]
LC-MS/MS 72~104 0.002~0.075 / [37]
LC-MS/MS 84~102 / / [36]
LC-ESI-MS/MS / 0.05~3.79 0.02~1.25 [50]
LC-MS/MS 78.0~90.3 0.10~1.5 / [39]
LC-MS/MS 80~120 / 0.05 [40]
LC-MS/MS 94.7~109 / / [41]
LC-MS/MS 89.3~116.3 / 0.011~0.08 [42]
LC-MS/MS 71.7~116 0.01~0.26 0.004~0.079 [43]
UPLC-MS/MS / / / [44]
LC-MS/MS / <0.5 / [45]
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动物源性食品中全氟及多氟化合物的检测方法及污染水平研究进展
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李润 1, 2 , 赵菁蕾 2 , 胡家勇 1, * , 柳鑫 1, 2, *
食品安全质量检测学报 | 专题:食品安全风险评估与风险监测 2025,16(10): 72-81
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食品安全质量检测学报 | 专题:食品安全风险评估与风险监测 2025, 16(10): 72-81
动物源性食品中全氟及多氟化合物的检测方法及污染水平研究进展
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李润1, 2 , 赵菁蕾2, 胡家勇1, * , 柳鑫1, 2, *
作者信息
  • 1.国家市场监管重点实验室(动物源性食品中重点化学危害物检测技术), 武汉 430075
  • 2.武汉轻工大学食品科学与工程学院, 武汉 430023
  • 李润(2002—), 女, 硕士研究生, 主要研究方向为食品加工与安全。E-mail:

通讯作者:

* 胡家勇(1989—), 男, 工程师, 主要研究方向为食品安全检测。E-mail:
柳鑫(1987—), 男, 教授, 主要研究方向为食品安全风险评估。E-mail:
Research progress on detection methods and pollution levels of perfluoroalkyl and polyfluoroalkyl substances in animal-derived foods
Run LI1, 2 , Jing-Lei ZHAO2, Jia-Yong HU1, * , Xin LIU1, 2, *
Affiliations
  • 1. Technology Innovation Center of Detection Technology of Focus Chemical Hazards in Animal-derived Food, State Admnistration for Market Regulation, Wuhan 430075, China
  • 2. School of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
出版时间: 2025-05-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20241013001
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全氟及多氟化合物(perfluoroalkyl and polyfluoroalkyl substances, PFASs)因其环境持久性、生物累积性、疏水疏油性及化学稳定性, 被广泛应用于工业生产和日常生活。然而, 这些化合物的广泛存在对生态环境和人类健康构成了严重威胁, 尤其是通过动物源性食品(如鱼类、贝类、家禽及其加工产品等)的膳食摄入, 是人类暴露于PFASs的主要途径之一。为有效评估其健康风险并制定相关监管政策, 建立快速、高效、灵敏的检测方法以监测动物源性食品中的PFASs污染水平至关重要。本文系统综述了动物源性食品中PFASs的样品前处理方法, 并重点探讨了色谱技术及色谱-质谱联用技术在检测中的应用进展。进一步总结了不同基质的动物源性食品中PFASs污染水平的研究现状, 为环境污染评估、食品安全监管及检测技术的优化提供了重要参考。

动物源性食品  /  全氟及多氟化合物  /  检测方法  /  污染水平

Perfluoroalkyl and polyfluoroalkyl substances (PFASs), characterized by their environmental persistence, bioaccumulation potential, hydrophobic and oleophobic properties, and chemical stability, have been extensively applied in industrial production and daily life. However, the widespread presence of these compounds poses significant threats to both ecological systems and human health. Dietary intake, particularly through animal-derived foods (e.g., fish, shellfish, poultry, and their processed products), represents a primary pathway of human exposure to PFASs. To effectively assess their health risks and formulate relevant regulatory policies, it is crucial to establish rapid, efficient, and sensitive detection methods for monitoring PFAS contamination levels in animal-derived foods. This review systematically summarized sample preparation techniques for PFAS analysis in animal-derived foods and highlights advancements in chromatographic and chromatographic-mass spectrometric methods for detection. Furthermore, it provided an overview of current research on PFAS contamination levels across various food matrices, offering critical insights for environmental pollution assessment, food safety regulation, and optimization of analytical technologies.

animal-derived foods  /  perfluoroalkyl and polyfluoroalkyl substances  /  detection methods  /  contamination levels
李润, 赵菁蕾, 胡家勇, 柳鑫. 动物源性食品中全氟及多氟化合物的检测方法及污染水平研究进展. 食品安全质量检测学报, 2025 , 16 (10) : 72 -81 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241013001
Run LI, Jing-Lei ZHAO, Jia-Yong HU, Xin LIU. Research progress on detection methods and pollution levels of perfluoroalkyl and polyfluoroalkyl substances in animal-derived foods[J]. Journal of Food Safety & Quality, 2025 , 16 (10) : 72 -81 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241013001
全氟及多氟化合物(perfluoroalkyl and polyfluoroalkyl substances, PFASs)是一类结构多样的人造氟化化学物质[1], 广泛存在于环境中, 且具有显著的全球迁移性[2]。这些物质由于其难以完全生物降解的特性[3], 已成为环境毒物, 并通过多种途径对人类和生态系统健康构成威胁[4]。其中, 研究最为广泛且具有代表性的 PFASs, 包括全氟烷基羧酸类(perfluoroalkyl carboxylic acids, PFCAs)和全氟烷基磺酸类(perfluoroalkyl sulfonic acids, PFSAs), 主要化合物包括: 全氟辛烷磺酸(perfluorooctane sulfonate, PFOS)、全氟辛烷羧酸(perfluorooctane carboxylic acid, PFOA)、全氟壬酸(perfluorononanoic acid, PFNA)、全氟己烷磺酸(perfluorohexanesulfonic acid, PFHxS)等[5]。这些全氟烷基物质的分子结构包含了具有极强化学稳定性的全氟烷基链(-CnF2n+1)与官能团(如羧酸或磺酸), 使其具备了极强的持久性。与此同时, 部分多氟烷基物质则包含至少一个全氟烷基段、一个非氟化碳段以及一个官能团, 通常被称为“前体物质”, 因为它们在环境中会降解为末端的PFCAs或PFSAs[6]
根据碳链长度, PFASs可进一步分为短链和长链物质, 短链PFAS(如C<7的PFCAs和C<6的PFSAs)与长链PFAS(如C≥7的PFCAs和C≥6的PFSAs)在环境中表现出不同的行为特征[7]。近年来, 短链PFAS在工业应用中逐渐替代了长链PFAS, 以减少对环境和健康的危害。然而, 研究表明, 短链PFAS尽管在毒性上低于长链PFAS, 但其在水中的溶解性较高, 且在地下水和土壤污染情况下具有更强的迁移性[8]。此外, PFAS的衰变和脱氟速率受到头部基团和氟烷基链长度的显著影响[9]。由于其碳氟键的稳定性, PFASs在化学、热稳定性、表面活性和疏水疏油性方面表现优异, 广泛应用于表面活性剂、涂料、黏合剂、乳化剂、润滑剂等产品中[10-11]。随着这些化合物的废弃和降解, 垃圾填埋场、污水处理厂以及污水污泥等成为其潜在间接来源, 许多前体物质最终转化为PFCAs或PFSAs并释放到环境中[12-13]
根据《斯德哥尔摩公约》, 部分PFASs已被列入受控清单, 并逐步限制其生产和使用。2016年, 美国环境保护署(United States Environmental Protection Agency, EPA)为PFOS和PFOA设定了终生健康建议水平为0.07 μg/L, 并正在制定其他PFAS类别的建议标准[14]
PFASs通过多种途径进入食物链, 尤其是在动物源性食品中, 其中主要来源为受污染的动物生长环境和饲料添加剂[15]。此外, PFAS与脂肪酸结合蛋白的相互作用是决定其在生物体内蓄积的重要因素[16]。研究表明, 鱼类和海鲜是PFASs进入人类饮食的主要途径之一, 尤其是当地捕捞的淡水鱼类, 常常成为人类接触PFAS的主要来源[17-18]。PFOS和PFOA作为研究中最常见的两种全氟化合物, 已在多种动物组织中广泛分布, 并在人类血清中具有较长的半衰期, 分别可达约5年和3年[19-20]。根据现有调查, 瑞典、西班牙和加拿大的研究结果发现, PFOS的含量在部分鱼类中高达23 mg/kg, 且在牛肉、海鱼和碎牛肉等动物性食品中也存在一定浓度[21-22]。PFASs在动物源性食品中的含量通常呈现亲脂性特征, 尤其在血液、肝脏和肾脏中的浓度高于肌肉[23]
PFASs的污染已经成为全球关注的环境问题, 许多研究表明, 这些化合物不仅存在于沉积物、空气、水、植物、食品包装材料和土壤等环境介质中[24-25], 而且通过饮食途径进入人体后, 会在肝脏、免疫系统、甲状腺激素等器官中积累, 可能对健康产生长期负面影响[26-28]。此外, PFASs也被认为是潜在的致癌物[29]。在食品领域, PFAS的检测方法通常包括样品提取、净化和液相色谱-串联质谱法(liquid chromatography-tandem mass spectrometry, LC-MS/MS)分析。三重四极杆质谱(triple-quadrupole mass spectrometry, QqQ-MS/MS)是目前应用最广泛的分析技术。然而, 生物基质中的内源性化合物, 特别是与分析物共洗脱的干扰物, 可能对分析结果产生影响[30]。因此, 为了提高分析灵敏度和准确性, 亟需开发更高效、精确的检测方法, 以克服基质效应对PFASs检测的干扰。
本文综述了动物源性食品中PFASs的检测方法、污染水平以及其潜在的健康风险, 重点讨论了样品前处理技术和色谱-质谱联用技术的应用进展。鉴于PFASs在环境中的持久性和生物累积性, 它们对人类健康构成长期威胁, 因此开发高效且灵敏的检测方法对监测动物源性食品中的PFAS污染具有重要意义。此项研究为评估PFASs在食品中的分布、迁移及其健康风险提供了科学依据, 也为制定相关食品安全标准和政策提供了理论支持。
通过检索X-MOL、PubMed等数据库, 筛选与动物源性食品中 PFASs检测和污染相关的文献, 关键词包括“动物源性食品”“PFASs”“鱼”“鸡”“PFOA”等, 并手动筛选出符合条件的文献进行整理。研究表明, 当前关注的主要PFASs包括PFOA和PFOS等。常用的萃取方法包括甲醇/氢氧化钾提取和甲醇/乙腈直接提取等, 提纯方法主要采用固相萃取和分散固相萃取等技术。PFASs的检测方法主要为LC-MS/MS和气相色谱-串联质谱法(gas chromatography-tandem mass spectrometry, GC-MS/MS)。
样品前处理是对样品中待测物质进行提取、净化和浓缩等一系列步骤, 旨在去除样品中的杂质, 提高目标化合物的富集程度, 并减少基质效应对检测结果的干扰。在动物源性食品中, PFASs通常以痕量存在, 因此前处理步骤在检测过程中尤为关键。选择合适的提取方法不仅能够提高检测的灵敏度, 还能增强检测的准确性和可靠性。例如, 通过优化液-液萃取或固相萃取等技术, 可以更高效地从复杂的食品基质中分离出PFASs, 从而提高最终分析结果的精确度。
离子对萃取法, 又称离子缔合萃取, 是一种利用阳离子和阴离子通过较强的静电力相结合形成的疏水性离子缔合物进行萃取的方法。在这一过程中, 被萃取物质通常是疏水性的离子缔合物, 即阳离子和阴离子通过静电力结合在一起的化合物。该方法通常以四丁基硫酸氢铵作为离子对试剂, 以叔丁基甲基醚作为萃取剂, 除此之外可能用到的试剂还有离子对试剂(强酸或强碱)、阳离子交换树脂或阴离子交换树脂、有机溶剂、缓冲液及其他辅助试剂。其中阳离子交换树脂或阴离子交换树脂主要用于固定相, 通过静电吸引力将带相反电荷的目标化合物吸附在柱上。JEONG等[31]为了测量韩国海鲜中PFOA、PFOS及其他PFASs的含量, 利用离子配对法结合高效液相色谱-串联质谱法(high performance liquid chromatography-tandem mass spectrometry, HPLC-MS/MS)调查了302个海鲜样本中19种不同类型的全氟化合物(perfluorinated compounds, PFCs)的含量, 在不同的天数内进行3次验证, 以确定日间的准确性和精密度, 发现准确率为80%~120%, 其中PFOA、全氟十三酸(perfluorotridecanoicacid, PFTrDA)、PFOS和全氟戊酸(perfluoro-n-pentanoic, PFPeA)水平最高, 分别出现在干海鲜、罐头和盐腌33种海鲜、加工鱼粮和调味紫菜中。但是对于全氟丁酸(perfluorobutyric acid, PFBA)来说, 使用离子对方法提取比用弱阴离子固相萃取柱(weak anion exchange-solid phase extraction, SPE-WAX)提取的回收率低近30%[32]
用甲醇/乙腈直接萃取可以达到更好的分离效果, 其通常与固定相结合使用。甲醇/乙腈直接萃取可以高效溶解多种有机物和无机物, 也适用于血清样本中的蛋白质沉淀, 能够有效移除大分子蛋白质。有研究对QuEChERS样品制备方法和甲醇/乙腈进行萃取的方法进行了比较总结, 前者会导致极性物质的损失, 而使用甲醇/乙腈进行提取时可以通过添加水和/或酸来优化提取过程[33]。MIKOLAJCZYK等[34]以甲醇/氢氧化钾作为提取剂, 通过LC-MS/MS测定了笼内、生态和自由放养生产的家禽蛋中受PFASs污染的程度, 主要包括PFOS、PFOA、PFNA、PFHxS水平, 其中有机鸡蛋是受污染最大的, 其次是自由放养和笼内禽蛋。
碱性消化是一种用于从污水、土壤、沉淀物或生物样品中提取PFASs的方法。在碱性消解和提取过程中, 常用的萃取液主要包括某些碱性溶液和有机溶剂的组合, 常见的碱性溶液有氢氧化钠和氢氧化钾, 有机溶剂有甲醇、乙腈, 通常有机溶剂会根据具体的实验需求与水混合, 其混合物可以在碱性环境中用于优化萃取过程。这种混合液可以调节萃取的极性, 也可以使目标化合物更易于溶解。PÉREZ等[35]测定了不同地理区域的283种食品(38种来自巴西, 38种来自沙特阿拉伯, 35种来自西班牙, 36种来自塞尔维亚)中21种PFAS的水平, 在前处理时首先采用碱性消化法提取牛奶、乳制品和固体基质, 在样品中加入10 mL的氢氧化钠溶液(20 mmol/L甲醇溶液), 进行转速消化再离心, 随后使用湍流色谱法(turbulent chromatography, TFC)进行纯化, 然后使用甲酸酸化至pH 4.5的超纯水将液体样品和提取物装入富集柱中。
除了以上几种处理方法外, 还出现了新的优化方法用于动物源性食品中PFASs的测定, 如蛋白质沉淀法。TAHZIZ等[36]尝试了几种净化和提取程序的组合, 包括碱性酶解、简单蛋白质沉淀、超声以及固相萃取(solid phase extraction, SPE), 最终选择了简单的蛋白质沉淀法对禽蛋的蛋黄样品中PFOS、PFOA进行萃取, 加标后, 用乙腈作为提取剂, 进行涡旋离心后, 将上清液转移到新的、干净的聚丙烯管中进行氮吹, 干燥后加入甲醇涡旋过滤后用LC-MS/MS进行测样, 该方法中PFOS、PFOA的平均回收率在84%到102%。
表1对动物源性食品中PFASs的不同萃取方法进行了总结, 虽然动物源性食品中PFASs的前处理方法有很多, 但各有优点和缺点。另外, 为了更有效地富集目标化合物, 降低基质效应带来的影响, 萃取方法优化和萃取后的净化步骤也十分重要。
靶向分析是一种预先设定特定化合物或化合物类别的检测方法, 目的是准确量化和确认已知物质的存在。在这种分析中, 研究者会提前确定要分析的目标化合物, 并使用特定的分析方法, 如液相色谱-质谱法(liquid chromatograph-mass spectrometry, LC-MS), 气相色谱-质谱法(gas chromatograph-mass spectromtry, GC-MS)等, 针对这些特定化合物进行定量和定性。
在动物源性食品中, 检测PFAS的污染水平是一个重要的研究领域。LC-MS作为一种常用的分析方法, 在PFAS的检测中发挥了重要作用。
LC是一种有效的分离技术, 适用于分离非挥发性、高极性或热不稳定的化合物。MS则用于对分离后的化合物进行定性和定量分析。LC与MS的联用能够提供更高的灵敏度和选择性, 使得在复杂基质中检测低浓度的PFAS成为可能。在PFAS的分析中, LC-MS/MS被广泛应用于食品、环境和生物样本的检测。特别是在动物源性食品中, LC-MS能够有效检测多种PFAS, 提供有关其污染水平的重要数据。CHEN等[39]开发了一种用于小型化固相萃取的吸附剂金属有机骨架(metal organic framework, MOF), 将其与LC-MS/MS结合, 测定动物源性食品中含氟调聚物及其代谢物。该方法的回收率在78.0%到90.3%之间, 相对标准偏差小于12.0%, 与其他传统方法相比, 具有简单、高效、经济等优点。通过不断优化检测方法和加强对PFAS污染的研究, 可以更好地保障食品安全, 保护公众健康。REN等[41]将设计出的提取方法与LC-MS/MS结合, 从牛奶中快速提取具有挥发性的PFOA和PFOS。LC-MS/MS在检测动物源性食品中的PFASs是最优选的技术, 但代价是仪器昂贵[46-47]
GC-MS是一种结合了GC和MS的分析技术, 被广泛应用于环境分析、食品安全、药物检测等领域, 该方法利用GC的高分离效能和MS的高灵敏度, 能够高效地对混合物中的组分进行定性和定量分析, 气相色谱通常用于测定挥发性和半挥发性化合物[48], 因此风味物质的检测, 如植物香气、白酒发酵、农药残留等多使用GC检测。有研究利用GC-MS/MS结合液-液萃取检测动物组织中的PFASs[49], 然而, 由于GC-MS/MS主要适用于挥发性样品, 对许多异构体的分辨能力有限, 且前处理和衍生化步骤烦琐, 相比之下, LC-MS/MS在快速和准确检测方面具有优势。所以目前LC-MS/MS检测PFASs更为流行。
非靶向分析不预设具体分析目标, 旨在探测样品中尽可能多的化合物, 包括未知和意外的化合物。这种方法通常依赖于高分辨率质谱, 可以在不知道具体化合物的情况下, 对样品进行广泛的化学分析。非靶向分析有助于发现新的污染物、代谢物或变化趋势, 对于环境监测、新型污染物的识别和暴露评估具有重要意义。表2对动物源性食品中PFASs的检测方法进行了总结。
人们对 PFASs的担忧主要来源于其极高的稳定性、生物蓄积性和毒性, 以及它们的广泛存在性。为了研究PFAS及其潜在转化产物在环境中的输入、归宿以及人类和野生动物暴露PFASs的途径, 需要采用先进的分析方法。研究者通常结合高分辨质谱(high resolution mass spectrum, HRMS)与色谱技术, 使用非目标筛选(non targeted screening, NTS)方法来应对PFAS数量众多、化学多样性、缺乏可靠标准和信息等分析挑战[50]。使用HRMS的非靶向分析能够检测和鉴定样品基质中未知和意外的目标化合物[51], 虽然已有研究将非靶向分析应用于地表水[52]、地下水[53]、饮用水、土壤、沉积物等环境样品中, 但是缺乏对动物源性食品或食品复杂基质中PFASs的非靶向筛选技术的研究, 比如, 传统的鱼类检测只针对少数PFASs, 但非靶向分析能够检测到受PFASs严重污染水域的鱼类。液相色谱通常伴随高分辨的质谱技术(如Orbitrap或TOF-MS)对复杂样品中的PFASs进行非靶向检测和识别。BOATMAN等[54]使用LC、离子迁移谱、MS评估了北卡罗来纳州中部娱乐和饮用水域鱼片中的PFAS, 以评估这些鱼片中常规靶向方法无法检测到的PFAS。基于LC-MS的非靶向分析已应用于代谢组学、石油组学和环境分析, 以发现与某些生物或非生物化学反应相关的未知化合物[55]。但是由于缺乏认证标准品, 在LC-MS/MS的目标分析中遗漏了未知PFAS的浓度, 因此, 需要使用HRMS和其他更好的技术对PFAS进行非靶向分析以克服这种低估问题, 该研究可为传统和新兴PFAS的科学研究和政策制定提供帮助[56]
非靶向筛选要求个性化的样品制备策略, 以从复杂的食品基质中提取多种化学成分, 理想情况下, 使用单一、广泛的样品制备方法可以提取多种化合物, 但由于样品的复杂性和分析物浓度差异, 这一过程常面临挑战[57]。适当的样品预处理是成功分析的先决条件, 特别是要有效提取有害化合物和掺杂物, 常用的提取方法包括固-液萃取、液-液萃取、固相微萃取(solid phase microextraction, SPME)、QuEChERS, 但这些方法存在分析时间长、操作复杂和选择性低等局限性。DAVID等[58]通过靶向分析和非靶向分析检测了英国西北部5个淡水样本中的数百种PFAS, 结果显示PFOA浓度最高达12100 ng/L, 非靶向筛查鉴定了89至1175种不同置信水平的PFAS, 其中33种为置信水平3, 10种为置信水平2, 此外, 还发现了一类新型不饱和全氟烷基醚羧酸(unsaturated-perfluoroalkyl ether carboxylic acids, U-PFECAs)。JACOB等[59]从美国3个工厂收集废水样本, 并采用高分辨率质谱结合目标和非目标分析方法, 非靶标分析揭示了41个同源序列的PFAS, 包括133个同源物, 并首次报道了其中6个非目标PFAS的结构, 半定量估计显示, 每个工厂废水样本中目标和非目标PFAS的总浓度差异显著, 最高达78700 ng/L。另外, 基于MOF的涂层材料在样品制备中表现出快速和灵敏的应用潜力[60], 例如, MOF-5涂层的搅拌棒可重复使用, 并且对多氯联苯的回收率超过80%。尽管基于MOF的样品制备方法显示出高灵敏度和选择性, 但MOF的水稳定性和结构缺陷问题仍需改进。QuEChERS方法在提取非极性和极性化合物时表现良好, 并可用于不同样品类型的分析, 但基质效应可能导致某些化合物的损失, 对蛋白质的去除可以帮助改善低分子量物质的分析, 而QuEChERS与分散固相萃取的结合在农药残留测定中得到广泛应用。另外共价有机框架(covalent organic framework, COF)因其低密度、大表面积、可调孔径和结构, 以及可定制的功能, 展现出相对于其他材料的独特优势, COF近期在微量食品污染物的吸附应用方面取得了显著进展[61]
PFAS对于动物源性食品的污染程度由于其种类、特性, 还有动物源性食品的类别和产地等而有所不同。SEO等[62]对多媒体环境中的PFASs进行调查, 得出的结果为全氟丁烷磺酸盐(perfluorobutanesulfonate, PFBS)主要在水体中被检测到, 而长链PFCAs和PFOSs则主要存在于灰尘、土壤、沉积物和污泥中。尽管PFBS和中性PFASs在空气中占据主导地位, 但PFCAs主要被检测到在植物和鱼类中。VANDER-SCHYFF等[63]对西印度洋海鸟蛋中PFAS进行首次研究, 分析了仙女燕鸥(Gygis alba)、烟灰燕鸥(Onychoprion fuscatus)和圣布兰登环礁普通燕鸥(Anous stolidus)蛋中的8种PFAS, 发现仙女燕鸥蛋中全氟十一烷酸(perfluoroundecanoic acid, PFUdA)的平均浓度最高(2.3 ng/g wm), 其次是PFOS (2.0 ng/g wm)和PFNA (0.93 ng/g wm)。另外, 有研究表明蛋黄中全氟烷酸(perfluoroalkyl acids, PFAAs)的浓度明显高于蛋清中的PFAA[64]。JOUANNEAU等[65]对斯瓦尔巴群岛繁殖的产卵黑腿小猫尾鹰的血浆和卵黄中不同PFAS化合物从母体转移到蛋的程度以及污染水平进行研究, 测量了其中传统的和新出现的PFAS, 包括Gen-X、3H-全氟-3-[(3-甲基氧-丙氧基)丙酸](3H-perfluoro-3-[(3-methoxy-propoxy)propanoic acid], ADONA)和6:2氯多氟辛烷醚磺酸盐(6:2 chloro-perfluorooctane ether sulfonate, F-53B), 结果表明在84%的蛋黄中发现了7:3氟调聚物羧酸(长链羧酸盐的前体)。LÖFSTRAND等[66]收集了大量来自冰岛、法罗群岛、瑞典和挪威等地的鸟蛋, 并对其内部的PFCs(包含了PFOS、PFOSA以及PFCAs)浓度进行了深入的分析。研究结果表明, 瑞典的鸟蛋中PFOS的浓度是最高的, 大约是挪威样本的5倍, 另外, PFOSA和PFCAs在不同的气候区域内的浓度分布与瑞典有所不同, 瑞典的样本中主要是PFOSA的存在, 而在其他地区, 其PFOS浓度则远远低于瑞典, 特别是冰岛和法罗群岛的样本。
虽然海鲜是人类饮食中PFAS的主要来源, 但是对于其污染水平的调查没有数据支持。ABAFE等[67]通过UPLC-MS/MS测量了4种养殖海洋贝类中15种PFAS的浓度, 首次在非洲养殖海洋贝类中检测到PFAS, 研究表明鲍鱼、贻贝、牡蛎和龙虾中∑11 PFAS浓度(以ng/g ww计)分别为0.12~0.49、4.83~6.43、0.64~0.66和0.22 ng/g ww, 另外在养殖贝类样品中, 短链PFAS占主导地位, 并且贻贝中PFOA比PFOS更为常见[68]。BARBO等[69]分析了2013到2015年在美国国家河流和溪流以及五大湖人类健康鱼片组织研究收集的样本数据, 发现PFOS是PFAS总量的最大贡献者, 平均占总量的74%。CAO等[70]开发了一种针对高脂质和蛋白质含量实验室鱼类饲料和宠物食品中PFAS的分析方法, 回收率为70%~130%, 在实验室鱼类饲料中检测到3类PFAS, 包括PFOS、PFCAs和PFSAs, 其中两种实验室鱼饲料的PFOS浓度大于1.3 ng/g, 3种实验室鱼类饲料的总PFAS含量超过1.0 ng/g, 而在宠物食品中仅检测到PFCAs和PFSAs。
食物链中的生物聚积会使动物源性食品中的PFCs含量出现上升。例如, 在图库西海豚体内, PFOS的生物放大因子(biomagnification factors, BMFs)估计范围是从7.7到63, 相比之下, PFOS的BMFs仅在1.3到2.6之间。PFOSA在海豚的肝脏内所含的BMFs与PFOS相似, 其浓度范围在5.6至35之间, 差异相当显著[71]。BABUT等[72]在法国罗纳河的一个地点对水生植物、底栖无脊椎动物和3种鲤科鱼(Barbus barbusGobio gobioRutilus rutilus)进行了调查, 总共收集了47个个体。研究发现从水生植物到鱼类的背部肌肉中, 全氟化学品的浓度逐渐增加, 并且年轻个体的一些全氟化学品浓度明显高于大型个体, 例如PFOS、PFNA和全氟癸酸(perflyorodecanoic acid, PFDA), 而全氟十四烷酸(perfluorotetradecanoic acid, Pfteda)在大型个体中浓度更高。另外, 鱼中长链PFASs的浓度在烹饪后增加, 而短链PFASs的浓度下降, 饮食习惯(即δ13C和δ15N)是解释不同种类间差异的关键因素。
牛奶和乳制品中的全氟烷基酸(perfluoroalky acids, PFAAs)的含量低于纳克/克(ng/g)[73], 对于动物源性食品, 例如鸡蛋、肉类、鱼类, 其最低标准是1.6 ng/kg, 而定量限(limit of quantitation, LOQ)则是5.0 ng/kg[74]。HLOUSKOVA等[75]测定了15中动物源性食品中21中全氟烷基物质, 其中PFOS是样品中最广泛的检出物。另外, 在各种PFASs中, 单一化合物的浓度范围是: PFSAs(不包括PFOSs)的浓度范围为2.33~76.3 ng/kg, PFCAs的浓度范围为4.99~961 ng/kg, 全氟烷基丙烯酸酯聚合物(perfluoroalkyl acrylates, PFPAs)的浓度范围为10.6~95.4 ng/kg, 而全氟辛烷磺酰胺(perfluorooctane sulfonamide, FOSA)的浓度范围是1.61~519 ng/kg。通过比较样品中不同国家的PFASs的污染水平发现了差异, 且含量有所降低, 主要表现为比利时>>挪威、意大利>捷克共和国。
在萨勒河鲷鱼肝中观察到PFOS浓度是最高的(226 μg/kg)[76]。ZAFEIRAKI等[45]对希腊的不同物种鲨鱼和鳐鱼的各种组织(肌肉、鳃、肝脏、心脏和性腺)中的PFASs水平进行了检测, 长碳链PFASs最常检测到, 其中PFTrDA浓度最高, 顺序为: 性腺>心脏>肝脏>鳃>肌肉。MELAKE等[77]研究了埃塞俄比亚哈瓦萨湖水中、沉积物和鱼类组织中PFASs的分布情况, 以及可能由鱼类消费对人类健康带来的风险。水中和沉积物中主要检测到了PFOA, 鱼组织中以长链PFASs为主, 基于平均浓度和鱼类消费量, 然经常食用鱼类的人群(如渔民和湖边居民)可能会因PFASs污染而面临健康风险。
本文综述了PFASs在动物源性食品中的检测方法及其污染水平, 总结了样品前处理技术和检测技术的最新进展, 特别是LC-MS/MS和GC-MS/MS在动物源性食品中PFASs检测中的应用。研究发现, 这些污染物普遍存在于各类动物源性食品中, 对人类健康构成潜在威胁。本文提供了一种系统的方法来评估和比较不同检测技术的效能, 特别是对于那些可能因食品基质复杂性而影响检测准确性的场景。此外, 本文还对比了各种前处理和检测方法的优劣。
环境和生物样品中PFAS的研究依赖于高分辨率和低分辨率质谱技术[78]。由于社会上流传的PFAS种类繁多, 但有关其化学结构的信息很少, 并且缺乏真实的标准品[79], 所以无法测量PFASs的全部成分, 并且相对于短链PFAS的检测, 长链PFAS的检测进展并不大, 需要优化样品前处理过程和分析方法来准确快速的检测这些物质, 或者开发新的检测方法, 另外, 对于PFAS的处理也是十分紧要的, PFAS废物目前有3种方法可供选择: 填埋、废水处理和焚烧, 但是每种处理PFAS的方法都会将原始PFAS或其降解产物释放到环境中, 这意味着PFAS问题具有周期性。因此, 为了解决这一周期性问题, 未来研究应聚焦于开发更高效、环境友好的PFAS废物处理技术。例如, 探索先进的化学氧化过程和生物降解方法, 此外, 吸附技术, 特别是利用新型纳米材料或功能化高表面活性材料吸附并固定PFAS, 也显示出潜在的应用前景。
  • 国家市场监管重点实验室(动物源性食品中重点化学危害物检测技术)开放课题项目(KF-202301)
  • 国家重点研发计划项目(2022YFF1102500)
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2025年第16卷第10期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20241013001
  • 接收时间:2024-10-13
  • 首发时间:2025-07-15
  • 出版时间:2025-05-25
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  • 收稿日期:2024-10-13
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国家市场监管重点实验室(动物源性食品中重点化学危害物检测技术)开放课题项目(KF-202301)
国家重点研发计划项目(2022YFF1102500)
作者信息
    1.国家市场监管重点实验室(动物源性食品中重点化学危害物检测技术), 武汉 430075
    2.武汉轻工大学食品科学与工程学院, 武汉 430023

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* 胡家勇(1989—), 男, 工程师, 主要研究方向为食品安全检测。E-mail:
柳鑫(1987—), 男, 教授, 主要研究方向为食品安全风险评估。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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