Article(id=1215670316362286071, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250425001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1745510400000, receivedDateStr=2025-04-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767767989483, onlineDateStr=2026-01-07, pubDate=1753372800000, pubDateStr=2025-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767767989483, onlineIssueDateStr=2026-01-07, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767767989483, creator=13701087609, updateTime=1767767989483, 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=128, endPage=138, ext={EN=ArticleExt(id=1215670317947731981, articleId=1215670316362286071, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Progress in the application of supramolecular solvent-microextraction technology in detection of food and environmental pollutants, columnId=1151895321388347923, journalTitle=Journal of Food Safety & Quality, columnName=Food Analysis and Detection, runingTitle=null, highlight=null, articleAbstract=

With the increasing attention to food safety and environmental quality, efficient and accurate pollutant detection technology is crucial. Supramolecular solvent microextraction technology, as an emerging sample pretreatment method, has demonstrated unique advantages in the field of food and environmental pollutant detection due to its high efficiency, good selectivity and environmental friendliness. This technology is based on the selective recognition and enrichment ability of specific pollutants by supramolecular solvents (such as nano/micro scale solvents formed by host molecules such as cyclodextrin and crown ether), and achieves rapid separation and concentration of target substances in samples through microextraction operations. As a new type of green solvent, supramolecular solvents have high extraction efficiency, wide polarity range, customizable structure, and both extraction and purification effects, making them widely used in the field of extraction and separation. This review introduced the properties of supramolecular solvents and types of supramolecular solvent microextraction, with a focus on the detailed application of this technology in the detection of food and environmental pollutants, and provided prospects for the work in this field, in order to provide reference for the promotion and application of supramolecular solvent-microextraction technology.

, correspAuthors=Yao-Hai ZHANG, 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=Guo-Shun QIN, Dan WU, Xin-Qi LONG, Yue HE, Yong-Liang CUI, Jing LI, Yao-Hai ZHANG), CN=ArticleExt(id=1215670319881306293, articleId=1215670316362286071, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=超分子溶剂-微萃取技术在食品及环境污染物检测中的应用进展, columnId=1151895321958773274, journalTitle=食品安全质量检测学报, columnName=食品分析与检测, runingTitle=null, highlight=null, articleAbstract=

随着人们对食品安全与环境质量关注度的不断提升, 高效精准的污染物检测技术至关重要。超分子溶剂-微萃取技术作为一种新兴的样品前处理手段, 凭借其高效、选择性好、环境友好等优势, 在食品及环境污染物检测领域展现出独特优势。该技术基于超分子溶剂(如环糊精、冠醚等主体分子形成的纳米/微米级溶剂)对特定污染物的选择性识别与富集能力, 通过微萃取操作实现样品中目标物的快速分离与浓缩。作为一种新型绿色溶剂, 超分子溶剂萃取效率高, 极性范围宽, 结构可设计, 兼具萃取和净化的效果, 在萃取分离领域应用广泛。本综述就超分子溶剂性质、超分子溶剂微萃取类型进行介绍, 重点对该技术在食品及环境污染物检测中的应用进行了较详细的综述, 并对该领域的工作进行了展望, 以期为超分子溶剂-微萃取技术的推广应用提供参考。

, correspAuthors=张耀海, authorNote=null, correspAuthorsNote=
*张耀海(1977—), 男, 博士, 副研究员, 主要研究方向为农产品监测和产地溯源。E-mail:
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覃国顺(2001—), 男, 硕士, 主要研究方向为食品科学与工程。E-mail:

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覃国顺(2001—), 男, 硕士, 主要研究方向为食品科学与工程。E-mail:

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覃国顺(2001—), 男, 硕士, 主要研究方向为食品科学与工程。E-mail:

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Global Food Industry, 2024, 2: 84-87., articleTitle=Determination of estrogen in milk by supramolecular hollow fiber membrane liquid microextraction with high performance liquid chromatography, refAbstract=null)], funds=[Fund(id=1215670328517378897, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, awardId=CARS-26, language=CN, fundingSource=农业农村部现代农业(柑橘)产业技术体系建设专项(CARS-26), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1215670320149741784, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, xref=1, ext=[AuthorCompanyExt(id=1215670320158130392, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, companyId=1215670320149741784, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Southwest University, Citrus Research Institute, Chinese Academy of Agricultural Sciences, Chongqing 400712, China), AuthorCompanyExt(id=1215670320162324698, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, companyId=1215670320149741784, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 西南大学, 中国农业科学院柑桔研究所, 重庆 400712)]), AuthorCompany(id=1215670320254599396, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, xref=2, ext=[AuthorCompanyExt(id=1215670320258793701, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, companyId=1215670320254599396, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 Key Laboratory of Quality and Safety Control of Citrus Fruits, Ministry of Agriculture and Rural Affairs, Chongqing 400712, China), AuthorCompanyExt(id=1215670320262988005, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, companyId=1215670320254599396, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 农业农村部柑橘类果品质量安全控制重点实验室, 重庆 400712)]), AuthorCompany(id=1215670320376234223, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, xref=3, ext=[AuthorCompanyExt(id=1215670320405594356, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, companyId=1215670320376234223, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 National Citrus Engineering Technology Research Center, Chongqing 400712, China), AuthorCompanyExt(id=1215670320413982967, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, companyId=1215670320376234223, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 国家柑桔工程技术研究中心, 重庆 400712)])], figs=[ArticleFig(id=1215670325652669118, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=EN, label=Fig.1, caption=Trend of the number of published papers and citation frequency of SSME technology in recent years, figureFileSmall=R7idNrLi34Ie9DB1syeMqQ==, figureFileBig=Rqi/aaHUQxtjpLNNqv5opg==, tableContent=null), ArticleFig(id=1215670326864822979, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=CN, label=图1, caption=近年来SSME技术的发文数量和被引频率趋势

注: 图中的数据来自Web of Science。

, figureFileSmall=R7idNrLi34Ie9DB1syeMqQ==, figureFileBig=Rqi/aaHUQxtjpLNNqv5opg==, tableContent=null), ArticleFig(id=1215670327137452764, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=EN, label=Fig.2, caption=General procedure of SUPRASs synthesis, figureFileSmall=WziLvxWev1xlBMzTrlzrCg==, figureFileBig=BdpM0r72bQNqf1Ip4TeijA==, tableContent=null), ArticleFig(id=1215670327250698983, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=CN, label=图2, caption=SUPRASs合成的一般程序

注: Colloidal suspension of amphiphiles: 两亲性物质胶体悬浮液; vesica: 囊泡; Aqueous micelle: 水相胶束; Reverse micelle: 反向胶束; Change in environmental conditions pH, T, salt, electrolyte, etc.: 环境条件改变(pH、温度、盐浓度、电解质浓度等); Coacervate droplets: 凝聚液滴; Droplet clusters: 液滴聚集体; Bulk solution: 本体溶液; Phase separation: 相分离; Coacervation: 凝聚作用。

, figureFileSmall=WziLvxWev1xlBMzTrlzrCg==, figureFileBig=BdpM0r72bQNqf1Ip4TeijA==, tableContent=null), ArticleFig(id=1215670327380722421, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=EN, label=Table 1, caption=

Application of SSME in the analysis of agricultural and veterinary residues

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
4种有机磷(乙硫磷、磷胺、二嗪磷、毒死蜱) 大米、蔬菜 癸酸/THF VA-SSMEb HPLC-UV 102~178 0.05~0.205 µg/kg 83.6~105 [10]
二嗪磷、甲霜灵 果汁、水样 1-十二烷醇/甲苯 AA-DMSPEc GC-FID 500 0.6~0.8 µg/L 85.0~96.6 [11]
3种有机磷(杀螟硫磷、
伏杀硫磷、毒死蜱)
茶饮 二-(2-乙基己基)磷酸/THF SSMEa HPLC-UV 15~19 6~10 mg/L 77~98 [12]
4种全氟化合物、
5种含氟农药
水样 十一烷醇/THF VA-LLMEb UPLC-Q-Orbitrap HRMS 24.7~28.2 0.125~0.150 µg/L 82.9~105.9 [13]
氯酚 水样 六氟异丙醇/辛醇 VA-LLMEb HPLC-UV 72~147 0.38~0.57 ng/mL 96.0~107.9 [14]
氯菊酯 水果、蔬菜 1-己醇/THF VA-SSMEb LC-MS/MS - 0.2~0.3 µg/kg 93~107 [15]
啶酰菌胺、氟啶脲、氯氰
菊酯和联苯菊酯
牛奶 壬醇/六氟异丙醇 LPMEa HPLC-UV - 0.5~1.7 µg/L 80.8~111.0 [16]
5种菊酯(氟氰戊菊酯、甲氰菊酯、苄呋菊酯、氯菊酯、氟氯氰菊酯) 烟草样品 十六烷基三丁基鏻四
氟硼酸钠/柠檬
酸钠
TRSUPRAS-
DLLMEa
HPLC-DAD - 0.25~0.50 µg/L 91.6~100.2 [17]
多菌灵、氟虫腈、啶氧菌酯 水样 1-癸醇/THF LPMEa HPLC-DAD 21.43-71.36 0.23~0.45 µg/L 93.5~110.0 [18]
甲萘威 果蔬、水样 庚醇/THF VA-LLMEb UPLC-MS/MS 15 0.03 mg/L 90~102 [19]
草甘膦 黄瓜、西红柿 烷基多葡萄糖苷/
1-庚酸
LPMEa HPLC-MS/MS - 15 µg/kg 94~106 [20]
4种三嗪除草剂(扑灭津、扑草净、特丁通、杀草净) 茶叶 [BMIM]PF6/THF DLLMEa HPLC-DAD - 1.7~2.1 µg/kg 80.0~119.9 [21]
4种苯脲除草剂(灭草隆、氯甲苯酮、异丙隆、
绿谷隆)
水样、果汁、
牛奶
三丁基(辛基)溴化膦/六氟磷酸铵 DLLMEa HPLC-DAD 37.1~72.8 0.13~0.19 µg/L 97.4~109.4 [22]
百草枯、敌草快 蔬菜 十二烷基硫酸钠/四丁基溴化铵 VA-LPMEb IP-RPHPLC-UV 22~26 1.5~2.8 g/L 95.0~106.7 [23]
5种三唑类(腈菌唑、三唑酮、戊唑醇、己唑醇、丁硫克百威) 水样、果汁、
豆奶
1-十二烷醇/1-十一
烷醇
IS-CAEb HPLC-UV 73~318 0.3~1.0 µg/L 77~117 [24]
4种三唑类(腈菌唑、三唑酮、戊唑醇、己唑醇) 水、蜂蜜、
豆浆
1-十二烷醇/十二烷基溴化磷三丁酯 PGS-SSMEb HPLC-UV 14~51 10~30 µg/L 60~114 [25]
6种三唑类(腈菌唑、氟硅唑、戊唑醇、己唑醇、联苯三唑醇、烯唑醇) 饮料、水样 六氟异丙醇/十一醇 LPMEa HPLC-UV - 1.0~5.0 µg/L 63.4~112.1 [26]
13种硝基咪唑类 鱼血 1-辛醇/THF VA-DLLMEb UPLC-MS/MS - 0.05~0.2 μg/L 88.4~105 [27]
8种苯并咪唑类 牛奶 己醇/THF VA-LLMEb LC-MS/MS - 0.03~0.14 μg/L 74~112 [28]
啶虫脒、嘧菌酯、联苯菊酯、多菌灵、毒死蜱、吡虫啉
和戊唑醇
水样、谷物粉 1-癸醇/THF VA-SSMEb HPLC-DAD - 3 μg/L 80~112 [29]
5种苯并咪唑类(噻苯达唑、阿苯达唑砜、奥芬达唑、
阿苯达唑和芬达唑)
土壤 正癸醇/THF SSMEa HPLC-UV - 12.1~39.9 µg/kg 56.6~86.1 [30]
萘普生、酮洛芬 水样 甲基三辛基氯化铵/1-辛醇 VA-SS-DLLMEb HPLC-DAD 41~46 0.17~0.24 μg/L 93.6~101.4 [31]
), ArticleFig(id=1215670327531717378, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=CN, label=表1, caption=

SSME在农兽残留检测中的应用

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
4种有机磷(乙硫磷、磷胺、二嗪磷、毒死蜱) 大米、蔬菜 癸酸/THF VA-SSMEb HPLC-UV 102~178 0.05~0.205 µg/kg 83.6~105 [10]
二嗪磷、甲霜灵 果汁、水样 1-十二烷醇/甲苯 AA-DMSPEc GC-FID 500 0.6~0.8 µg/L 85.0~96.6 [11]
3种有机磷(杀螟硫磷、
伏杀硫磷、毒死蜱)
茶饮 二-(2-乙基己基)磷酸/THF SSMEa HPLC-UV 15~19 6~10 mg/L 77~98 [12]
4种全氟化合物、
5种含氟农药
水样 十一烷醇/THF VA-LLMEb UPLC-Q-Orbitrap HRMS 24.7~28.2 0.125~0.150 µg/L 82.9~105.9 [13]
氯酚 水样 六氟异丙醇/辛醇 VA-LLMEb HPLC-UV 72~147 0.38~0.57 ng/mL 96.0~107.9 [14]
氯菊酯 水果、蔬菜 1-己醇/THF VA-SSMEb LC-MS/MS - 0.2~0.3 µg/kg 93~107 [15]
啶酰菌胺、氟啶脲、氯氰
菊酯和联苯菊酯
牛奶 壬醇/六氟异丙醇 LPMEa HPLC-UV - 0.5~1.7 µg/L 80.8~111.0 [16]
5种菊酯(氟氰戊菊酯、甲氰菊酯、苄呋菊酯、氯菊酯、氟氯氰菊酯) 烟草样品 十六烷基三丁基鏻四
氟硼酸钠/柠檬
酸钠
TRSUPRAS-
DLLMEa
HPLC-DAD - 0.25~0.50 µg/L 91.6~100.2 [17]
多菌灵、氟虫腈、啶氧菌酯 水样 1-癸醇/THF LPMEa HPLC-DAD 21.43-71.36 0.23~0.45 µg/L 93.5~110.0 [18]
甲萘威 果蔬、水样 庚醇/THF VA-LLMEb UPLC-MS/MS 15 0.03 mg/L 90~102 [19]
草甘膦 黄瓜、西红柿 烷基多葡萄糖苷/
1-庚酸
LPMEa HPLC-MS/MS - 15 µg/kg 94~106 [20]
4种三嗪除草剂(扑灭津、扑草净、特丁通、杀草净) 茶叶 [BMIM]PF6/THF DLLMEa HPLC-DAD - 1.7~2.1 µg/kg 80.0~119.9 [21]
4种苯脲除草剂(灭草隆、氯甲苯酮、异丙隆、
绿谷隆)
水样、果汁、
牛奶
三丁基(辛基)溴化膦/六氟磷酸铵 DLLMEa HPLC-DAD 37.1~72.8 0.13~0.19 µg/L 97.4~109.4 [22]
百草枯、敌草快 蔬菜 十二烷基硫酸钠/四丁基溴化铵 VA-LPMEb IP-RPHPLC-UV 22~26 1.5~2.8 g/L 95.0~106.7 [23]
5种三唑类(腈菌唑、三唑酮、戊唑醇、己唑醇、丁硫克百威) 水样、果汁、
豆奶
1-十二烷醇/1-十一
烷醇
IS-CAEb HPLC-UV 73~318 0.3~1.0 µg/L 77~117 [24]
4种三唑类(腈菌唑、三唑酮、戊唑醇、己唑醇) 水、蜂蜜、
豆浆
1-十二烷醇/十二烷基溴化磷三丁酯 PGS-SSMEb HPLC-UV 14~51 10~30 µg/L 60~114 [25]
6种三唑类(腈菌唑、氟硅唑、戊唑醇、己唑醇、联苯三唑醇、烯唑醇) 饮料、水样 六氟异丙醇/十一醇 LPMEa HPLC-UV - 1.0~5.0 µg/L 63.4~112.1 [26]
13种硝基咪唑类 鱼血 1-辛醇/THF VA-DLLMEb UPLC-MS/MS - 0.05~0.2 μg/L 88.4~105 [27]
8种苯并咪唑类 牛奶 己醇/THF VA-LLMEb LC-MS/MS - 0.03~0.14 μg/L 74~112 [28]
啶虫脒、嘧菌酯、联苯菊酯、多菌灵、毒死蜱、吡虫啉
和戊唑醇
水样、谷物粉 1-癸醇/THF VA-SSMEb HPLC-DAD - 3 μg/L 80~112 [29]
5种苯并咪唑类(噻苯达唑、阿苯达唑砜、奥芬达唑、
阿苯达唑和芬达唑)
土壤 正癸醇/THF SSMEa HPLC-UV - 12.1~39.9 µg/kg 56.6~86.1 [30]
萘普生、酮洛芬 水样 甲基三辛基氯化铵/1-辛醇 VA-SS-DLLMEb HPLC-DAD 41~46 0.17~0.24 μg/L 93.6~101.4 [31]
), ArticleFig(id=1215670327678518032, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=EN, label=Table 2, caption=

Application of SSME in the detection of mycotoxins and food additives

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
赭曲霉毒素A;
黄曲霉毒素B1
葡萄酒、香料;
小麦
十四烷酸/THF SSMEa ELISA - - 75~96 [32]
赭曲霉毒素A 香料 癸酸/THF VA-LPMEb LC-FLD - 0.5 mg/L 81~101 [33]
亚硝酸盐 加工肉制品 癸酸/THF VA-LPMEb UV-Vis 200 0.035 ng/mL 95.0~102.5 [34]
对羟基苯甲酸酯(6) 水样、药物、护理品 六氟异丙醇/Brij-35 LPMEa HPLC-DAD 26~193 0.042~0.167 g/L 90.2~112.4 [35]
苏丹红Ⅲ 香料 1-癸醇/THF UA-LLMEb UV-Vis 33 0.79 µg/L 87~102 [36]
苏丹红Ⅰ 水样、辣椒 1-癸醇/THF UA-LPMEb UV-Vis - 1.74 µg/L 101~108 [37]
苏丹黑B 黑米、黑豆、辣椒 1-辛醇/THF VA-DLLMEb UV-Vis 55 9.01 µg/L 78.1~105.0 [38]
苏丹I-IV染料 红酒、饮料粉、辣椒酱、红辣椒 1-辛醇/THF UA-SUPRASb HPLC-UV - 0.48~0.63 ng/mL 90.6~102.5 [39]
苏丹I、Ⅲ、IV染料 饮料、水样 六氟丁醇/法尼醇 VA-DLLMEb HPLC - 0.8~3.1 ng/mL 93.9~122.1 [40]
苏丹I-IV染料 水、食品样品 1-癸醇/THF 表面活性剂介导SSMEa HPLC-DAD 10~17 0.23~0.51 µg/L 81.8~109.0 [41]
亮蓝FCF、靛蓝胭脂红、日落黄FCF、苏丹I-III 香料、棉花糖、水果味糖果、干果和巧克力糖衣丸 1-辛胺/百里香酚 VA-LPMEb HPLC-PDA - 0.07~0.2 mg/kg 70~127 [42]
罗丹明B 辣椒粉 1-戊醇 VA- DLLMEb UV-vis 16 0.008 mg/kg 95.0~115.2 [43]
罗丹明B、甲基紫和荧光黑T 食品、化妆品、水样 1-癸醇/四氢呋喃 VA-LLMEb UV-vis 15~20 0.480~0.511 μg/L 95~100 [44]
罗丹明B、柯
衣定
水样、饮料 六氟异丙醇/
芳樟醇
VA-LLMEb HPLC - 1.3~1.5 μg/L 84.4~109.1 [45]
阳离子染料 饮料、河水 香叶醇/六氟丁醇 VA-LLMEb HPLC-DAD - 1~1.5 ng/mL 93.1~104.3 [46]
沙林、梭曼、甲基磷酸二甲酯 水样 聚氧乙烯单叔辛苯基醚/异辛烷 亲水胶束型SSMEa GC-MS - 0.2~0.8 ng/mL 80.7~89.3 [47]
马兜铃酸 马兜铃 六氟异丙醇/
十一醇
VA-DLLMEb HPLC-DAD - 0.3~3.1 ng/mL 92.8~100.6 [48]
), ArticleFig(id=1215670327816930076, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=CN, label=表2, caption=

SSME在真菌毒素、食品添加剂检测中的应用

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
赭曲霉毒素A;
黄曲霉毒素B1
葡萄酒、香料;
小麦
十四烷酸/THF SSMEa ELISA - - 75~96 [32]
赭曲霉毒素A 香料 癸酸/THF VA-LPMEb LC-FLD - 0.5 mg/L 81~101 [33]
亚硝酸盐 加工肉制品 癸酸/THF VA-LPMEb UV-Vis 200 0.035 ng/mL 95.0~102.5 [34]
对羟基苯甲酸酯(6) 水样、药物、护理品 六氟异丙醇/Brij-35 LPMEa HPLC-DAD 26~193 0.042~0.167 g/L 90.2~112.4 [35]
苏丹红Ⅲ 香料 1-癸醇/THF UA-LLMEb UV-Vis 33 0.79 µg/L 87~102 [36]
苏丹红Ⅰ 水样、辣椒 1-癸醇/THF UA-LPMEb UV-Vis - 1.74 µg/L 101~108 [37]
苏丹黑B 黑米、黑豆、辣椒 1-辛醇/THF VA-DLLMEb UV-Vis 55 9.01 µg/L 78.1~105.0 [38]
苏丹I-IV染料 红酒、饮料粉、辣椒酱、红辣椒 1-辛醇/THF UA-SUPRASb HPLC-UV - 0.48~0.63 ng/mL 90.6~102.5 [39]
苏丹I、Ⅲ、IV染料 饮料、水样 六氟丁醇/法尼醇 VA-DLLMEb HPLC - 0.8~3.1 ng/mL 93.9~122.1 [40]
苏丹I-IV染料 水、食品样品 1-癸醇/THF 表面活性剂介导SSMEa HPLC-DAD 10~17 0.23~0.51 µg/L 81.8~109.0 [41]
亮蓝FCF、靛蓝胭脂红、日落黄FCF、苏丹I-III 香料、棉花糖、水果味糖果、干果和巧克力糖衣丸 1-辛胺/百里香酚 VA-LPMEb HPLC-PDA - 0.07~0.2 mg/kg 70~127 [42]
罗丹明B 辣椒粉 1-戊醇 VA- DLLMEb UV-vis 16 0.008 mg/kg 95.0~115.2 [43]
罗丹明B、甲基紫和荧光黑T 食品、化妆品、水样 1-癸醇/四氢呋喃 VA-LLMEb UV-vis 15~20 0.480~0.511 μg/L 95~100 [44]
罗丹明B、柯
衣定
水样、饮料 六氟异丙醇/
芳樟醇
VA-LLMEb HPLC - 1.3~1.5 μg/L 84.4~109.1 [45]
阳离子染料 饮料、河水 香叶醇/六氟丁醇 VA-LLMEb HPLC-DAD - 1~1.5 ng/mL 93.1~104.3 [46]
沙林、梭曼、甲基磷酸二甲酯 水样 聚氧乙烯单叔辛苯基醚/异辛烷 亲水胶束型SSMEa GC-MS - 0.2~0.8 ng/mL 80.7~89.3 [47]
马兜铃酸 马兜铃 六氟异丙醇/
十一醇
VA-DLLMEb HPLC-DAD - 0.3~3.1 ng/mL 92.8~100.6 [48]
), ArticleFig(id=1215670327934370598, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=EN, label=Table 3, caption=

Application of SSME in the detection of heavy metals and other elements

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
Sb3+ 水样 十一醇/THF VA-LLMEb UV-Vis 15 0.19 g/L 94~101 [49]
Cr6+、总铬 蔬菜、饮料、水样 1-癸醇/四丁基氢氧化铵 UA-DLLMEb FAAS 134 0.03 µg/L 94.0~105.5 [50]
总铅 食品 1-辛醇/THF LLMEa FAAS 126 0.15 µg/L 91~104 [51]
Cu2+ 食品、水样 1-辛醇/THF DMSPEc GFAAS 280 0.2 ng/mL 92~96 [52]
Cu2+ 食品、水样 正丁醇/THF LLMEa FAAS 60 1.4 g/L >95 [53]
Cu 茴香茶 1-癸醇/THF SA-LPMEb FAAS - 1.91 µg/kg 80.2~111.8 [54]
U6+ 土壤、水样 十一烷醇/ THF LLMEa UV-Vis 17 0.31 g/L 96~105 [55]
Th4+ 土壤、水样 1-癸醇/THF LLMEa UV-Vis 40 0.40 µg/L 95~102 [56]
Hg 食品、水样 1-癸醇/THF VA-LLMEb UV-Vis 100 0.30 µg/L 95.71~99.65 [57]
Hg 水、食品样品 1-癸胺/百里香酚 VA-LLMEb UV-Vis 114 0.6 µg/L 93.2~96.7 [58]
Hg2+ 蔬菜、水样 1-十一烷醇/四丁基氢
氧化铵
UA-HLLMEb UV-vis 82 0.33 µg/L 96.4 [59]
Al3+ 食品、水样 十一醇/THF UA-LPMEb UV-vis 50 1.2 µg/L 95~100 [60]
Al 水、头发样品 1-癸醇/THF SSMEa UV-Vis 50 0.056 mg/L 92~110 [61]
Ni 蒲公英茶 1-癸醇/THF LPMEa FAAS - 25.86~497.64 µg/kg 86.0~131.8 [62]
As、Se 杏仁、核桃、开心果粉、
水样
十一酸/四丁基氢氧化铵 AA-SFODMEb HG-AAS 103 0.07~0.09 µg/L - [63]
As(III)砷 水样、土壤 癸酸/THF UA-DLLMEb GFAAS 60 0.2 ng/mL 91~105 [64]
), ArticleFig(id=1215670328056005424, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=CN, label=表3, caption=

SSME在重金属等元素检测中的应用

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
Sb3+ 水样 十一醇/THF VA-LLMEb UV-Vis 15 0.19 g/L 94~101 [49]
Cr6+、总铬 蔬菜、饮料、水样 1-癸醇/四丁基氢氧化铵 UA-DLLMEb FAAS 134 0.03 µg/L 94.0~105.5 [50]
总铅 食品 1-辛醇/THF LLMEa FAAS 126 0.15 µg/L 91~104 [51]
Cu2+ 食品、水样 1-辛醇/THF DMSPEc GFAAS 280 0.2 ng/mL 92~96 [52]
Cu2+ 食品、水样 正丁醇/THF LLMEa FAAS 60 1.4 g/L >95 [53]
Cu 茴香茶 1-癸醇/THF SA-LPMEb FAAS - 1.91 µg/kg 80.2~111.8 [54]
U6+ 土壤、水样 十一烷醇/ THF LLMEa UV-Vis 17 0.31 g/L 96~105 [55]
Th4+ 土壤、水样 1-癸醇/THF LLMEa UV-Vis 40 0.40 µg/L 95~102 [56]
Hg 食品、水样 1-癸醇/THF VA-LLMEb UV-Vis 100 0.30 µg/L 95.71~99.65 [57]
Hg 水、食品样品 1-癸胺/百里香酚 VA-LLMEb UV-Vis 114 0.6 µg/L 93.2~96.7 [58]
Hg2+ 蔬菜、水样 1-十一烷醇/四丁基氢
氧化铵
UA-HLLMEb UV-vis 82 0.33 µg/L 96.4 [59]
Al3+ 食品、水样 十一醇/THF UA-LPMEb UV-vis 50 1.2 µg/L 95~100 [60]
Al 水、头发样品 1-癸醇/THF SSMEa UV-Vis 50 0.056 mg/L 92~110 [61]
Ni 蒲公英茶 1-癸醇/THF LPMEa FAAS - 25.86~497.64 µg/kg 86.0~131.8 [62]
As、Se 杏仁、核桃、开心果粉、
水样
十一酸/四丁基氢氧化铵 AA-SFODMEb HG-AAS 103 0.07~0.09 µg/L - [63]
As(III)砷 水样、土壤 癸酸/THF UA-DLLMEb GFAAS 60 0.2 ng/mL 91~105 [64]
), ArticleFig(id=1215670328223777597, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=EN, label=Table 4, caption=

Application of SSME in emerging contaminants detection

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
4种磺胺类(磺胺嘧啶、磺胺二甲氧嘧啶、5-甲氧基磺胺嘧啶、磺胺二甲嘧啶) 沉积物 六氟丁醇/香茅醇 VA-DMEb HPLC-DAD - 30~60 ng/g 99.5~104.2 [66]
抗生素(7) 水样 无盐月桂酸/十二烷基三甲基氢氧化铵 MNP-LLMEc HPLC-UV 12~118 0.10~0.76 ng/mL 92.0~111.3 [67]
四环素类(5) 牛奶、鸡蛋、蜂蜜 双十二烷基二甲基溴化铵/十二烷基三甲基溴化铵 LPMEa HPLC 48~198 0.7~3.4 µg/L 61.4~130.3 [68]
3种氟喹诺酮类(环丙沙星、达那沙星、恩诺沙星) 水样 癸酸/三辛基甲基氯化铵 VA-LLMEb HPLC-PDA 153~241 0.06~0.14 μg/L 99~101 [69]
苯并芘 食品 正辛醇/四丁基溴化铵 UA-SSMEb HPLC-FLD - 0.11 μg/kg 89.86~100.01 [70]
多环芳烃(13) 茶叶 己酸/己酸钠 DLLMEa HPLC-FLD 38~46 0.02~0.04 μg/L 85~105 [71]
多环芳烃(7) 土壤 辛酸/THF VA-LPMEb HPLC-FLD - 0.07~0.4 μg/kg 89~117 [72]
多环芳烃(15) 苹果皮 癸酸/THF SFE-SSMEc HPLC-FLD 138~196 0.34~1.27 μg/kg 60~78 [73]
氯代多环芳烃、
多环芳烃
土壤 四氢呋喃/1-辛醇 SSMEa HPLC-FLD - 0.07~2.30 μg/kg 76.5~105.3 [74]
全氟烷基酸、
全氟烷基酸前体
螃蟹、虾、鱼 1-庚醇/THF DLLMEa UPLC-MS/MS - 0.03~0.15 ng/g 81.1~120.0 [75]
邻苯二甲酸酯(8) 食品接触
材料
正辛醇/THF VA-DLLMEb UPLC-MS/MS - 0.1~1.0 µg/L 84.8~117.5 [76]
邻苯二甲酸酯(4) 婴儿食品 癸基葡萄糖苷/正庚醇 LPMEa HPLC-UV - 10 µg/kg 85~93 [77]
邻苯二甲酸盐(4) 水样 十四烷基三甲基溴化铵/六氟异丙醇 DLLMEa RP-HPLC 75 0.3~0.6 µg/L 93.1~104.4 [78]
双酚A、双酚S 热敏纸 1-癸醇/乙醇 SFME段塞流微萃取 ASAP-MS/MS - - - [79]
雌激素 牛奶样品 正辛醇/1-丁基-3-甲基咪唑鎓四氟硼酸盐 SS-VA-HF-LPMEb HPLC-DAD 330 0.10~0.22 ng/mL - [80]
雌激素 牛奶样品 正辛醇/1-丁基-3-甲基咪唑鎓四氟硼酸盐 SS-HF-LPMEb HPLC 334 0.10~0.22 ng/mL 88.30~93.93 [81]
), ArticleFig(id=1215670328341218117, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670316362286071, language=CN, label=表4, caption=

SSME在新污染物检测中的应用

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 样品 SUPRAS 前处理方法 仪器方法 富集倍数 检出限 回收率/% 参考
文献
4种磺胺类(磺胺嘧啶、磺胺二甲氧嘧啶、5-甲氧基磺胺嘧啶、磺胺二甲嘧啶) 沉积物 六氟丁醇/香茅醇 VA-DMEb HPLC-DAD - 30~60 ng/g 99.5~104.2 [66]
抗生素(7) 水样 无盐月桂酸/十二烷基三甲基氢氧化铵 MNP-LLMEc HPLC-UV 12~118 0.10~0.76 ng/mL 92.0~111.3 [67]
四环素类(5) 牛奶、鸡蛋、蜂蜜 双十二烷基二甲基溴化铵/十二烷基三甲基溴化铵 LPMEa HPLC 48~198 0.7~3.4 µg/L 61.4~130.3 [68]
3种氟喹诺酮类(环丙沙星、达那沙星、恩诺沙星) 水样 癸酸/三辛基甲基氯化铵 VA-LLMEb HPLC-PDA 153~241 0.06~0.14 μg/L 99~101 [69]
苯并芘 食品 正辛醇/四丁基溴化铵 UA-SSMEb HPLC-FLD - 0.11 μg/kg 89.86~100.01 [70]
多环芳烃(13) 茶叶 己酸/己酸钠 DLLMEa HPLC-FLD 38~46 0.02~0.04 μg/L 85~105 [71]
多环芳烃(7) 土壤 辛酸/THF VA-LPMEb HPLC-FLD - 0.07~0.4 μg/kg 89~117 [72]
多环芳烃(15) 苹果皮 癸酸/THF SFE-SSMEc HPLC-FLD 138~196 0.34~1.27 μg/kg 60~78 [73]
氯代多环芳烃、
多环芳烃
土壤 四氢呋喃/1-辛醇 SSMEa HPLC-FLD - 0.07~2.30 μg/kg 76.5~105.3 [74]
全氟烷基酸、
全氟烷基酸前体
螃蟹、虾、鱼 1-庚醇/THF DLLMEa UPLC-MS/MS - 0.03~0.15 ng/g 81.1~120.0 [75]
邻苯二甲酸酯(8) 食品接触
材料
正辛醇/THF VA-DLLMEb UPLC-MS/MS - 0.1~1.0 µg/L 84.8~117.5 [76]
邻苯二甲酸酯(4) 婴儿食品 癸基葡萄糖苷/正庚醇 LPMEa HPLC-UV - 10 µg/kg 85~93 [77]
邻苯二甲酸盐(4) 水样 十四烷基三甲基溴化铵/六氟异丙醇 DLLMEa RP-HPLC 75 0.3~0.6 µg/L 93.1~104.4 [78]
双酚A、双酚S 热敏纸 1-癸醇/乙醇 SFME段塞流微萃取 ASAP-MS/MS - - - [79]
雌激素 牛奶样品 正辛醇/1-丁基-3-甲基咪唑鎓四氟硼酸盐 SS-VA-HF-LPMEb HPLC-DAD 330 0.10~0.22 ng/mL - [80]
雌激素 牛奶样品 正辛醇/1-丁基-3-甲基咪唑鎓四氟硼酸盐 SS-HF-LPMEb HPLC 334 0.10~0.22 ng/mL 88.30~93.93 [81]
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超分子溶剂-微萃取技术在食品及环境污染物检测中的应用进展
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覃国顺 1, 2, 3 , 吴丹 1, 2, 3 , 龙欣琦 1, 2, 3 , 何悦 1, 2, 3 , 崔永亮 1, 2, 3 , 李晶 1, 2, 3 , 张耀海 1, 2, 3, *
食品安全质量检测学报 | 食品分析与检测 2025,16(14): 128-138
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食品安全质量检测学报 | 食品分析与检测 2025, 16(14): 128-138
超分子溶剂-微萃取技术在食品及环境污染物检测中的应用进展
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覃国顺1, 2, 3 , 吴丹1, 2, 3, 龙欣琦1, 2, 3, 何悦1, 2, 3, 崔永亮1, 2, 3, 李晶1, 2, 3, 张耀海1, 2, 3, *
作者信息
  • 1 西南大学, 中国农业科学院柑桔研究所, 重庆 400712
  • 2 农业农村部柑橘类果品质量安全控制重点实验室, 重庆 400712
  • 3 国家柑桔工程技术研究中心, 重庆 400712
  • 覃国顺(2001—), 男, 硕士, 主要研究方向为食品科学与工程。E-mail:

通讯作者:

*张耀海(1977—), 男, 博士, 副研究员, 主要研究方向为农产品监测和产地溯源。E-mail:
Progress in the application of supramolecular solvent-microextraction technology in detection of food and environmental pollutants
Guo-Shun QIN1, 2, 3 , Dan WU1, 2, 3, Xin-Qi LONG1, 2, 3, Yue HE1, 2, 3, Yong-Liang CUI1, 2, 3, Jing LI1, 2, 3, Yao-Hai ZHANG1, 2, 3, *
Affiliations
  • 1 Southwest University, Citrus Research Institute, Chinese Academy of Agricultural Sciences, Chongqing 400712, China
  • 2 Key Laboratory of Quality and Safety Control of Citrus Fruits, Ministry of Agriculture and Rural Affairs, Chongqing 400712, China
  • 3 National Citrus Engineering Technology Research Center, Chongqing 400712, China
出版时间: 2025-07-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250425001
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随着人们对食品安全与环境质量关注度的不断提升, 高效精准的污染物检测技术至关重要。超分子溶剂-微萃取技术作为一种新兴的样品前处理手段, 凭借其高效、选择性好、环境友好等优势, 在食品及环境污染物检测领域展现出独特优势。该技术基于超分子溶剂(如环糊精、冠醚等主体分子形成的纳米/微米级溶剂)对特定污染物的选择性识别与富集能力, 通过微萃取操作实现样品中目标物的快速分离与浓缩。作为一种新型绿色溶剂, 超分子溶剂萃取效率高, 极性范围宽, 结构可设计, 兼具萃取和净化的效果, 在萃取分离领域应用广泛。本综述就超分子溶剂性质、超分子溶剂微萃取类型进行介绍, 重点对该技术在食品及环境污染物检测中的应用进行了较详细的综述, 并对该领域的工作进行了展望, 以期为超分子溶剂-微萃取技术的推广应用提供参考。

超分子溶剂  /  微萃取  /  环境污染物  /  绿色化学

With the increasing attention to food safety and environmental quality, efficient and accurate pollutant detection technology is crucial. Supramolecular solvent microextraction technology, as an emerging sample pretreatment method, has demonstrated unique advantages in the field of food and environmental pollutant detection due to its high efficiency, good selectivity and environmental friendliness. This technology is based on the selective recognition and enrichment ability of specific pollutants by supramolecular solvents (such as nano/micro scale solvents formed by host molecules such as cyclodextrin and crown ether), and achieves rapid separation and concentration of target substances in samples through microextraction operations. As a new type of green solvent, supramolecular solvents have high extraction efficiency, wide polarity range, customizable structure, and both extraction and purification effects, making them widely used in the field of extraction and separation. This review introduced the properties of supramolecular solvents and types of supramolecular solvent microextraction, with a focus on the detailed application of this technology in the detection of food and environmental pollutants, and provided prospects for the work in this field, in order to provide reference for the promotion and application of supramolecular solvent-microextraction technology.

supramolecular solvent  /  microextraction  /  environmental pollutant  /  green chemistry
覃国顺, 吴丹, 龙欣琦, 何悦, 崔永亮, 李晶, 张耀海. 超分子溶剂-微萃取技术在食品及环境污染物检测中的应用进展. 食品安全质量检测学报, 2025 , 16 (14) : 128 -138 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250425001
Guo-Shun QIN, Dan WU, Xin-Qi LONG, Yue HE, Yong-Liang CUI, Jing LI, Yao-Hai ZHANG. Progress in the application of supramolecular solvent-microextraction technology in detection of food and environmental pollutants[J]. Journal of Food Safety & Quality, 2025 , 16 (14) : 128 -138 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250425001
食品及环境污染物检测中, 样品分析过程主要包括样品采集、样品前处理、上机分析、数据处理及结果报告等步骤。而样品前处理是最烦琐、最耗时、最重要的步骤之一, 通过该步骤能够达到减少基质干扰、富集和浓缩目标分析物的目的[1-2]。目前主要的样品前处理技术为液相萃取和固相萃取, 均存在着耗时、不环保、成本高、操作复杂等缺点, 样品前处理方法正逐渐向着快速、绿色、简便、微型化、自动化方向发展。自1990年, ARTHUR等[3]在固相萃取的基础上提出固相微萃取(solid-phase microextraction, SPME)技术以来, 微萃取技术便得到了不断的发展和应用。作为两种主要的微萃取技术, SPME和液相微萃取(liquid phase microextraction, LPME)技术在食品和环境中的农药、真菌毒素、重金属等污染物的前处理中已有着广泛的应用。
2009年, BALLESTEROS-GÓMEZ等[4]首次引入了超分子溶剂(supramolecular solvents, SUPRASs)这一术语。SUPRASs是由两亲性分子自组装和凝聚形成, 与水不混溶, 具有纳米结构的胶束聚集体; 具有环境友好、原料廉价、制备简单、提取效率高等优点。SUPRASs与微萃取相结合, 能够充分发挥两者的优势, 形成了一种环境友好、快速简单、富集系数高的绿色新技术—超分子溶剂微萃取(supramolecular solvent microextraction, SSME)。2010年, COSTI等[5]首次将SUPRAS用于固体样品微萃取, 并测定鱼和贝类中恶喹酸和氟甲喹残留量, 此后SSME在各类污染物中的应用研究相继出现(图1)。本文简要介绍SUPRASs及SSME类型, 重点综述SSME在食品及环境污染物检测中的应用, 以期为SSME的研究提供一些参考。
SUPRASs的合成通常包括两个步骤(图2): 首先, 两亲性分子在超过临界聚集浓度后会自主形成纳米结构(主要是囊泡、水相胶束和反向胶束3种结构); 然后, 在外界条件(如pH、温度、溶剂、电解质)的诱导下, 生成的纳米结构三维聚集体会自组装形成更大的聚集体, 并絮凝从溶剂中分离, 即为SUPRASs。
SUPRASs最突出的特点包括: 制备简单、提取效率高、绿色环保等。(1)大量的可结合位点。溶剂中含有高浓度的两亲性分子, 由此有大量的可结合位点, 少量的SUPRASs便可以获得高提取效率, 低体积便可达到高浓缩系数(通常为100~500); (2)极性范围宽。两亲性分子具有亲水部分和疏水部分, 能够提供不同极性区, 可同时提取各种溶质; (3)表面积大。凝聚层液滴在SUPRASs中保持独立的个体(见图2), 提供了大的表面积, 在萃取过程中能快速传质; (4)制备简单。两亲性分子廉价易得, SUPRASs只需添加两亲性分子并提供絮凝条件就可制得; (5)绿色安全。与传统有机溶剂相比更加绿色环保, 不挥发、不可燃, 使用过程中安全性高。此外, SUPRASs还具有限制进入的特性, 能够限制蛋白质和多糖等大分子物质的进入[6]
SUPRASs的萃取性能受两亲性分子和絮凝条件的影响, 因此通过调整两亲性分子和絮凝条件可以制备具有特定功能的SUPRASs。ALGAR等[7]通过改变羧酸烃链的长度和浓度以及四氢呋喃的浓度, 优化了SUPRASs非极性结构域的甲烷三基-π氢键组成, 从而提高了对土壤中芳香化合物萃取效率。SÁNCHEZ-VALLEJO等[8]分别以正辛醇和1,2-辛二醇为原料合成了7种SUPRASs, 用于树莓多酚的萃取, 其研究表示合成的1,2-辛二醇海绵状结构的SUPRASs具有丰富的水互连通道, 对高极性多酚糖苷共轭物和低极性多酚有优异的提取性能。
目前, SUPRASs应用最广泛的类型为反相胶束结构, 其次是囊泡结构, 水相胶束结构最少。反相胶束结构SUPRASs中, 均采用链烷酸或烷醇作为两亲性分子, 四氢呋喃作为凝聚剂。因此, 合成SUPRASs的原料类型还有待发展。ACCIONI等[9]则用七氟丁酸作为两亲性分子制备SUPRASs, 并用于提取氨基酸和寡肽, 其研究结果表明制备的SUPRASs对含有非极性脂肪族、环状和芳香族侧链取代基(log D>-3.62)的氨基酸和寡肽具有很好的提取效果。
本文将SSME分为3种模式: 基本模式、外力辅助模式和联用模式。在这3种模式中, 基本模式是最简单的, 主要是将SUPRASs与微萃取相结合, 如单滴微萃取(single drop microextraction, SDME)、LPME和分散液液微萃取(dispersive liquid-liquid microextraction, DLLME)。但基本模式存在着提取效率低等问题, 为加快萃取速度, 研究人员陆续将涡旋辅助(vortex-assisted, VA)、超声波辅助(ultrasound-assisted, UA)、空气辅助(air assisted, AA)等外力辅助应用于SSME: 这些辅助模式主要是通过增加SUPRASs和待测物质的接触面积, 或者改变目标物在样品与萃取相间的分配系数, 从而提高萃取效率。除以上单一的萃取模式, 目前还发展了与其他技术联用的模式: 如基于超临界流体萃取(supercritical fluid extraction, SFE)、磁纳米粒(magnetic nanoparticles, MNPs)、分散微固相萃取(dispersive micro-solid phase extraction, DMSPE)的联用模式。以下针对SSME在食品和环境中各种污染物检测中的应用进行简要阐述。
近年来SSME在农兽药残留检测中的应用, 见表1。农兽药残留涵盖了有机磷、有机氯、菊酯类、氨基甲酸酯等杀虫剂, 三唑类杀菌剂, 三嗪类和苯脲类除草剂, 硝基咪唑类、苯并咪唑类兽药, 仪器大多为HPLC-UV/DAD。
COSTI等[5]最早将SSME结合LC-UV应用到鱼贝类固体样品中氟甲喹和恶喹酸兽药残留检测: 400 μL SUPRAS和200 mg切碎的样品混合后, 恒温到15 ℃, 离心后取SUPRAS提取物上机分析; 在最佳条件下, 定量限为5~22 μg/kg, 回收率为99%~102%。该方法验证了SUPRAS在固体样品微萃取中的适用性, 简单快速、结果可靠、低成本, 为SSME在兽药残留中的应用奠定了基础。LI等[14]用六氟异丙醇和辛醇制备了SUPRAS, 结合HPLC-UV测定水样中氯酚, 富集倍数为72~147, 回收率为96.0%~107.9%。此外, 其制备的SUPRAS能排除蛋白质、多糖及腐殖物质等大分子物质, 而对分子量很小的氯酚不排阻, 彰显了从复杂基质中萃取小分子而排除大分子的应用潜力。
最初的SSME技术仅用于水样、果汁等简单基质, 而后逐步应用于果蔬、土壤等复杂基质。GORJI等[10]以癸酸和THF制备SUPRAS, 结合HPLC-UV检测了大米和蔬菜中噻螨酮和4种有机磷农药残留, 富集因子为102~178, 检出限为0.05~0.20 μg/kg, 回收率为83.6%~105.0%; ANA等[15]以1-己醇和THF制备SUPRAS, 结合LC-MS/MS, 分析了水果、蔬菜中4种氯菊酯对映体, 检出限为0.2~0.3 μg/kg, 符合相关农药残留标准。
近年来SSME在真菌毒素和食品添加剂检测中的应用, 见表2
目前SSME技术在真菌毒素上的相关报道较少: GARCÍA-FONSECA等[32]用十四烷酸和THF制备成SUPRAS, 结合酶联免疫吸附, 测定小麦中黄曲霉毒素B1和葡萄酒、香料中赭曲霉毒素A, 回收率为84%~96%, 与免疫亲和柱前处理技术相比, 两者均有相似的检出限和线性范围, 但后者不适用于香料, 更消耗有机溶剂, 因此该方法彰显出更大的应用潜力; CABALLERO-CASERO等[33]利用SUPRAS限制进入的特性, 用癸酸和THF制备成SUPRAS, 结合HPLC-UV测定了5种香料中赭曲霉毒素A, 检出限为0.5 mg/L, 回收率为81%~101%, 该方法省去了免疫亲和柱净化, 节省了时间与成本, 也符合欧盟相关标准。
食品添加剂在现代的食品工业中使用广泛, 主要有防腐剂、着色剂、抗氧化剂等20余种。但超量、超范围等违规使用对人体健康会造成潜在危害, 因此开发相关的快速简便检测方法也十分重要。ALTUNAY等[34]利用癸酸和THF制备SUPRAS, 结合紫外分光光度计检测了加工肉制品中亚硝酸盐含量, 富集倍数高达200倍, 检测结果与标准方法无显著差异, 结果准确可靠, 并具有快速、成本低、绿色等优点。CHEN等[35]提出了一种基于六氟异丙醇/Brij-35的新型SUPRAS, 结合HPLC-DAD检测了水、药物和个人护理品中6种对羟基苯甲酸酯防腐剂, 检出限为0.042~0.167 g/L, 回收率为90.2%~112.4%。
工业染料等非食品添加剂在食品工业中的违法滥用时有发生, 科研人员对此进行了相关研究。SOYLAK等[36]建立了UA-SSME结合分光光度法测定香料中苏丹红Ⅲ的方法: 以1-癸醇和THF制备SUPRAS, 回收率为87%~102%, 该法在复杂基质中展现了较好的回收率、重现性和选择性。BOGDANOVA等[42]以1-辛胺为两亲物, 麝香草酚为凝聚剂, 结合HPLC-PDA分析了香料、糖果中6种合成染料(亮蓝、靛蓝胭脂红、日落黄、苏丹红Ⅰ、苏丹红Ⅱ、苏丹红Ⅲ), 检出限为0.07~0.2 mg/kg, 结果满足欧盟食品检测的要求。
目前SSME常与火焰原子吸收(flame atomic absorption spectrometry, FAAS)和石墨炉原子吸收(graphite furnace atomic absorption spectrometry, GFAAS)等联用检测重金属等元素, 表3列出了SSME在重金属等元素检测中的主要应用。如KHAN等[49]首次将十一醇和THF制备的SUPRAS结合紫外分光光度计用于检测水样中的Sb3+, 检出限为0.19 g/L, 回收率为94%~101%, 该方法适用于各种环境水样。
近年来, SSME技术逐渐应用于复杂基质中重金属等元素的分析检测。TUZEN等[50]建立了UA-SUPRAS- DLLME-FAAS方法对水、饮料及蔬菜中Cr6+和总铬进行了测定: 以1-癸醇和四丁基氢氧化铵制备的SUPRAS作为萃取剂, 偶氮红为络合剂, 检出限为0.03 μg/L, 富集倍数为134, 回收率为94.0%~105.5%; 同传统检测方法相比, 该方法富集倍数更高, 检出限更低。此外, ELIK[51]使用1-辛醇和THF制备成SUPRAS, 建立了一种基于液-液微萃取的新方法, 分析了蔬菜、烤肉制品等食品及水样中总铅, 该方法绿色高效, 适用于复杂基质样品中铬的测定。
KASHANAKI等[52]将SSME与DMSPE技术联用, 建立了一种食品样品中超痕量铜离子的萃取新方法: 首先将样品中铜离子提取到Al-Fu纳米薄片上, 并用THF进行解吸; 接着将THF解吸液与1-辛醇制备成SUPRAS; 最后用GFAAS对铜离子进行检测。在最佳条件下, 可获得高达280的富集倍数, 检出限为0.2 ng/mL。与其他方法相比, DMSPE-SSME方法可有效净化样品、高效富集铜离子, 具有优异的选择性和更高的灵敏度, 该法也可用于各种基质中其他离子的萃取和预浓缩。
抗生素、持久性有机污染物(persistent organic pollutants, POPs)、环境内分泌干扰物(endocrine disrupting chemicals, EDCs)和微塑料(microplastics)是目前4大类典型新污染物, 具有以下几个共性特征: (1)多数为目前正在生产和应用的产品, 尚未有效控制其生产和排放; (2)污染正在发生, 环境介质中的存量较高, 对其环境行为缺乏足够认知; (3)缺乏毒性与健康风险数据, 缺乏全面的科学评估[65]。新污染物的来源广泛、种类繁多, 其在环境中的存在与迁移转化规律复杂多变, 给环境监测、风险评估和污染治理带来了前所未有的挑战。四环素、磺胺类药物等抗生素, 多环芳烃、全氟烷基酸等POPs, 邻苯二甲酸酯、双酚A、双酚S等增塑剂及雌激素等EDCs, 均属于新污染物。SSME在这些新污染物检测中的应用, 见表4
YANG等[70]以正辛醇和四丁基溴化铵为原料制备SUPRAS, 结合LC-FLD, 用于食品中苯并芘的提取检测: 在优化条件下, 检出限为0.11 μg/kg, 回收率为89.86%~100.01%; 整个样品处理时间需30 min, 与GB 5009.27—2016《食品安全国家标准 食品中苯并(a)芘的测定》的传统处理方法相比, 该方法更简单快速, 可减少60%的处理时间。王春等[76]以正辛醇和THF制备SUPRAS, 结合UPLC-MS/MS对食品接触材料中8种邻苯二甲酸酯类增塑剂进行了检测, 检出限为0.1~1.0 μg/L, 回收率为84.8%~117.5%, 该方法简单快速、结果准确可靠。除了以上两类新污染物, SSME也同样适用于抗生素类污染物的检测: SELAHLE等[69]采用癸酸和三丙甲基氯化铵制备SUPRAS, 结合HPLC-PDA检测水样中3种氟喹诺酮类抗生素, 检出限为0.06~0.14 μg/L, 富集倍数为153~241, 回收率为99%~101%, 此方法操作简便、精密度高, 可有效从废水中提取抗生素。
在SSME过程中, 离心步骤可以使含有目标分析物的SUPRAS相沉积在离心管的底部或顶部, 但此过程往往耗时较长。相关研究表明将MNPs应用到SSME过程中, 可以避免离心分离, 从而提高效率。JIA等[67]首次将无盐月桂酸与十二烷基三甲基氢氧化铵制备成SUPRAS, 联用疏水性MNPs, 并结合HPLC-UV分析水中磺胺类和氟喹诺酮类抗生素, 检出限为0.10~0.76 ng/mL, 回收率为92.0%~111.3%, 提取时间仅需3 min。该研究将SSME联合疏水性MNPs, 简化了萃取过程, 缩短了萃取时间, 且与离心辅助的SSME进行比较, 该方法中所有分析物明显预浓缩, 富集系数远高于离心辅助的SSME。
GISSAWONG等[68]探究了混合阳离子表面活性剂制作的SUPRAS在LPME中的适用性, 采用双十二烷基二甲基溴化铵和十二烷基三甲基溴化铵制备SUPRAS, 结合HPLC, 用于鸡蛋、牛奶和蜂蜜中5种四环素类的分析检测, 检出限为0.7~3.4 μg/L, 回收率为61.4%~130.3%。该方法简单、快速、环保, 制备的SUPRAS可在室温下保存3周, 为SUPRAS的合成提供了方向。
最近, TIMOFEEVA等[71]开发了一种基于注射器的自动化SS-DLLME方法, 并成功地结合HPLC-UV测定茶叶中13种多环芳烃。该研究在流动系统的注射器中混合己酸、己酸钠与含水样品相, 自发相分离后得到含有目标分析物的超分子相。结果表明: SUPRAS可有效提取多环芳烃, 并在注射器中快速相分离, 无需离心; 自动微萃取过程持续4 min, 在最佳条件下检出限为0.02~0.04 μg/L; 该方法简单、快速、自动化, 具有较高的再现性和可重复性。
与传统有机溶剂相比, SUPRAS的优势在于提取效率高、制备简单、绿色环保, 可高效萃取环境样品和农产品等多种基质中的目标分析物, 且可以结合多种辅助手段及与其他技术联用, 适用于开发通用的样品前处理方式。与其他绿色萃取技术相比, SSME也展现出独特的优势:
与离子液体萃取相比, SSME的优势在于其不仅可实现更高效的预浓缩、且所采用SUPRAS组分(如天然表面活性剂、脂肪酸、醇)本身具有低毒性和较好的生物降解性。该技术在工艺实施过程中体现出低能耗、低成本、操作便捷等优点, 同时产生的废渣和需要的溶剂更少; 与超临界流体萃取相比, SSME的优势在于其不仅具有高选择性、且操作流程简捷, 无需高压设备支持成本低、多功能萃取能力强、快速预浓缩效率高、极性物质提取能力强、萃取过程温和, 避免热敏性成分降解; 废渣和溶剂量少, 后续分离简便。
尽管SSME具有各种优点和很强的实用性, 但它也存在一些局限性: (1)一般SUPRAS的黏度都较高, 在分析前需要稀释, 会降低分析物的检测灵敏度, 且稀释过程中使用的有机溶剂也会造成环境问题; (2)目前SUPRAS基本上是由链烷醇/酸和THF制备的, 组成成分有待发展, 且THF具有一定毒性, 世界卫生组织将THF归类为2 B类致癌物; (3)SSME过程中常需要通过离心的步骤促进相分离, 增加了时间; (4)在萃取完成后, SUPRAS相与检测仪器设备的兼容问题也是目前的一大难题, 如SUPRAS的低挥发性造成无法用气相色谱进行分析。因此, 为推广SSME技术的应用, 今后还应加强以下方面的研究: (1)针对目标分析物的性质, 研发黏度较小、更加绿色安全的新型超分子溶剂; (2)丰富两亲性分子的种类, 探索适合复杂基质微萃取的替代溶剂, 使用表面活性离子液体作为两亲性分子可作为一个方向; (3)在SSME过程中建议引入铁磁流体。采用外加磁场进行相分离, 则可以避免离心过程的耗时, 提高萃取效率; (4)开发自动化SSME技术, 加强与其他检测技术的联用。此外, SSME可与人工智能(artificial intelligence, AI)进行技术融合, 强化“AI+SSME+传感”三角架构, 实现溶剂设计-过程控制-数据分析闭环。SSME还与其他先进技术的结合: (1)分子印迹超分子溶剂。通过在超分子溶剂中嵌入特异性识别位点, 实现对激素、抗生素等痕量污染物的靶向捕获; (2)微流控芯片集成。将超分子溶剂微萃取单元嵌入微流控平台, 实现“样品进-结果出”的单细胞代谢分析。随着对超分子溶剂的进一步研究, 相信SSME未来在食品和环境污染物等检测上的应用将会更加绿色化、自动化、微型化。
  • 农业农村部现代农业(柑橘)产业技术体系建设专项(CARS-26)
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2025年第16卷第14期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250425001
  • 接收时间:2025-04-25
  • 首发时间:2026-01-07
  • 出版时间:2025-07-25
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  • 收稿日期:2025-04-25
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农业农村部现代农业(柑橘)产业技术体系建设专项(CARS-26)
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    1 西南大学, 中国农业科学院柑桔研究所, 重庆 400712
    2 农业农村部柑橘类果品质量安全控制重点实验室, 重庆 400712
    3 国家柑桔工程技术研究中心, 重庆 400712

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*张耀海(1977—), 男, 博士, 副研究员, 主要研究方向为农产品监测和产地溯源。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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