Article(id=1153433696221778398, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433686872679135, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20241205001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1733328000000, receivedDateStr=2024-12-05, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752929622941, onlineDateStr=2025-07-19, pubDate=1744646400000, pubDateStr=2025-04-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752929622941, onlineIssueDateStr=2025-07-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752929622941, creator=13701087609, updateTime=1752929622941, updator=13701087609, issue=Issue{id=1153433686872679135, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='7', pageStart='1', pageEnd='322', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752929620712, creator=13701087609, updateTime=1757656380159, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1173259152974561742, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433686872679135, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1173259152978756047, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433686872679135, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=71, endPage=77, ext={EN=ArticleExt(id=1153433697035473393, articleId=1153433696221778398, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Determination of nitrofuran metabolites in aquatic products by chitosan purification-ultra performance liquid chromatography-quadrupole linear ion trap-mass spectrometry, columnId=1151895322692776479, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Analysis and Monitoring of Toxic and Harmful Substances in Food, runingTitle=null, highlight=null, articleAbstract=

Objective To develop a rapid method for the determination of nitrofuran metabolites in aquatic products based on chitosan purification combined with ultra performance liquid chromatography and triple quadrupole/composite linear ion trap mass spectrometer. Methods The samples were hydrolyzed by hydrochloric acid, derived by 2-nitrobenzaldehyde, extracted by ethyl acetate, rapidly purified by chitosan, and then concentrated and redissolved. Rapid separation was achieved by ultra performance liquid chromatography, measured by triple quadrupole/composite linear ion trap mass spectrometer, and quantified by internal standard method to achieve the rapid and accurate determination of nitrofuran metabolites residues in aquatic products. Results The 4 kinds of nitrofuran metabolites had a good linear relationship in the concentration range of 0.5-10.0 μg/L, the correlation coefficients were all more than 0.998, and the limit of quantification was 0.5 μg/kg. Taking carp, Scophthalmus maximus and Litopenaeus vannamei as samples, the average recovery of 4 kinds of nitrofuran metabolites at 3 different addition levels was 96.5%-116.5%, the intra-day relative standard deviation was 2.2%-9.3%, and the intra-day relative standard deviation was 2.7%-9.7%. Conclusion The method is economical, simple, efficient, sensitive and reproducible, and can be used as a routine method for the determination of 4 kinds of nitrofuran metabolites in aquatic products.

, correspAuthors=Rong-Yue ZHANG, Jin-Cheng LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Wen-Di HUO, Yu-Peng WEN, Rong-Yue ZHANG, Jin-Cheng LI), CN=ArticleExt(id=1153433720850731198, articleId=1153433696221778398, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=壳聚糖净化-超高效液相色谱-三重四极杆/复合线性离子阱质谱法测定水产品中硝基呋喃类代谢物残留研究, columnId=1151895322898297380, journalTitle=食品安全质量检测学报, columnName=本期专题:食品中有毒有害物质分析与监测, runingTitle=null, highlight=null, articleAbstract=

目的 建立一种基于壳聚糖净化结合超高效液相色谱-三重四极杆/复合线性离子阱质谱法, 测定水产品中硝基呋喃类代谢物残留的快速检测方法。方法 样品经盐酸水解、2-硝基苯甲醛衍生、乙酸乙酯提取、壳聚糖净化、氮吹浓缩复溶后, 借助超高效液相色谱仪实现快速分离, 三重四极杆/复合线性离子阱质谱仪进行测定, 内标法定量分析, 实现快速、准确地测定水产品中硝基呋喃类代谢物残留量。结果 4种硝基呋喃类代谢物在0.5~10.0 μg/L质量浓度范围内线性关系良好, 相关系数均大于0.998, 定量限为0.5 μg/kg; 以鲤鱼、大菱鲆以及南美白对虾为样品, 在3个不同添加水平下4种硝基呋喃类代谢物的平均回收率为96.5%~116.5%, 日内相对标准偏差为2.2%~9.3%, 日间相对标准偏差为2.7%~9.7%。结论 该方法经济、简便、高效, 灵敏度高, 重复性好, 可作为水产品中4种硝基呋喃类代谢物残留的常规检测方法。

, correspAuthors=张荣月, 李晋成, authorNote=null, correspAuthorsNote=
* 张荣月(1979—), 男, 教授, 主要研究方向为大孔层析介质制备及应用。E-mail:
李晋成(1983—), 男, 研究员, 主要研究方向为水产品质量安全检测技术。E-mail:
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霍文迪(2000—), 男, 研究生, 主要研究方向为水产品质量安全监测。E-mail:

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Food Hydrocolloids, 2017, 69(8): 382-392., articleTitle=Influence of dietary fibers on lipid digestion: comparison of single-stage and multiple-stage gastrointestinal models, refAbstract=null)], funds=[Fund(id=1173278549537599628, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, awardId=2025XT04, language=CN, fundingSource=中央级公益性科研院所基本科研业务费项目(2025XT04), fundOrder=null, country=null), Fund(id=1173278549600514190, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, awardId=CARS-48, language=CN, fundingSource=国家现代农业产业技术体系项目(CARS-48), fundOrder=null, country=null), Fund(id=1173278549663428752, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, awardId=2020TD75, language=CN, fundingSource=中国水产科学研究院科技创新项目(2020TD75), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1173278545808863271, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, xref=null, ext=[AuthorCompanyExt(id=1173278545817251880, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, companyId=1173278545808863271, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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Gradient elution procedure

, figureFileSmall=null, figureFileBig=null, tableContent=
时间/min 流速/(mL/min) A/% B/%
0 0.35 90.0 10.0
6.00 0.35 10.0 90.0
9.00 0.35 10.0 90.0
9.10 0.35 90.0 10.0
11.00 0.35 90.0 10.0
), ArticleFig(id=1173278548623241340, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, language=CN, label=表1, caption=

梯度洗脱程序

, figureFileSmall=null, figureFileBig=null, tableContent=
时间/min 流速/(mL/min) A/% B/%
0 0.35 90.0 10.0
6.00 0.35 10.0 90.0
9.00 0.35 10.0 90.0
9.10 0.35 90.0 10.0
11.00 0.35 90.0 10.0
), ArticleFig(id=1173278548707127422, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, language=EN, label=Table 2, caption=

Mass spectrometry detection parameters of 4 kinds of nitrofuran metabolites and their internal standards in multiple reaction monitoring mode

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 保留时间
/min
准分子
离子(m/z)
碎片离子
(m/z)
碰撞气能量
/eV
SEM 2.6 209.2 166.2*, 192.1 14, 16
AOZ 2.5 236.1 133.9*, 103.9 17, 31
AHD 2.3 249.2 134.1*, 104.1 17, 27
AMOZ 3.3 335.2 291.1*, 262.2 17, 23
SEM-13C-15N2 - 212.1 168.0 14
AOZ-D4 - 240.1 134.0 17
AHD-13C3 - 252.0 134.0 17
AMOZ-D5 - 340.4 296.2 17
), ArticleFig(id=1173278548795207808, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, language=CN, label=表2, caption=

4种硝基呋喃类代谢物及其内标物在多反应监测模式下的质谱检测参数

, figureFileSmall=null, figureFileBig=null, tableContent=
分析物 保留时间
/min
准分子
离子(m/z)
碎片离子
(m/z)
碰撞气能量
/eV
SEM 2.6 209.2 166.2*, 192.1 14, 16
AOZ 2.5 236.1 133.9*, 103.9 17, 31
AHD 2.3 249.2 134.1*, 104.1 17, 27
AMOZ 3.3 335.2 291.1*, 262.2 17, 23
SEM-13C-15N2 - 212.1 168.0 14
AOZ-D4 - 240.1 134.0 17
AHD-13C3 - 252.0 134.0 17
AMOZ-D5 - 340.4 296.2 17
), ArticleFig(id=1173278548912648322, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, language=EN, label=Table 3, caption=

Linear regression equation and limit of quantitation of 4 kinds of nitrofuran metabolites

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 线性范围/(μg/L) 回归方程 相关系数
(r)
定量限/(μg/kg)
SEM 0.5~10.0 Y=0.29683X+0.01936 0.99964 0.5
AOZ 0.5~10.0 Y=0.23747X+0.00523 0.99875 0.5
AHD 0.5~10.0 Y=0.32279X-0.00140 0.99977 0.5
AMOZ 0.5~10.0 Y=0.38553X+0.01646 0.99937 0.5
), ArticleFig(id=1173278549021700228, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, language=CN, label=表3, caption=

4种硝基呋喃类代谢物的线性回归方程和定量限

, figureFileSmall=null, figureFileBig=null, tableContent=
化合物 线性范围/(μg/L) 回归方程 相关系数
(r)
定量限/(μg/kg)
SEM 0.5~10.0 Y=0.29683X+0.01936 0.99964 0.5
AOZ 0.5~10.0 Y=0.23747X+0.00523 0.99875 0.5
AHD 0.5~10.0 Y=0.32279X-0.00140 0.99977 0.5
AMOZ 0.5~10.0 Y=0.38553X+0.01646 0.99937 0.5
), ArticleFig(id=1173278549197860999, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, language=EN, label=Table 4, caption=

Recoveries and RSDs of 4 kinds of nitrofuran metabolites in aquatic products (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
水产样品 化合物 添加水平/(μg/kg) 平均回收率
/%
日间RSDs/% 日内RSDs/%
鲤鱼 AOZ 0.5 115.9 7.7 9.3
2.0 116.3 9.5 8.7
10.0 116.5 3.8 4.5
AMOZ 0.5 100.5 3.2 2.7
2.0 102.6 3.2 2.5
10.0 99.3 3.5 3.6
AHD 0.5 104.1 4.8 6.4
2.0 104.4 5.2 2.2
10.0 102.0 4.2 4.5
SEM 0.5 105.9 9.7 9.1
2.0 102.6 5.1 5.9
10.0 98.6 5.3 9.1
南美白对虾 AOZ 0.5 99.3 6.4 8.0
2.0 106.4 8.1 5.0
10.0 104.3 7.7 5.5
南美白对虾 AMOZ 0.5 96.5 9.4 8.5
2.0 97.2 2.8 2.7
10.0 98.0 3.9 2.6
AHD 0.5 103.8 6.0 5.9
2.0 107.9 3.7 4.9
10.0 105.6 3.6 2.6
SEM 0.5 99.5 7.4 6.1
2.0 103.7 4.3 5.4
10.0 99.9 2.7 2.5
大菱鲆 AOZ 0.5 102.3 7.2 6.3
2.0 105.4 5.9 7.4
10.0 104.9 5.7 4.6
AMOZ 0.5 101.2 3.7 4.3
2.0 100.4 4.7 5.8
10.0 98.7 4.0 2.8
AHD 0.5 104.8 5.8 6.4
2.0 100.6 4.6 5.2
10.0 102.6 4.2 4.6
SEM 0.5 101.3 6.3 5.8
2.0 100.5 4.4 4.5
10.0 98.6 3.6 3.3
), ArticleFig(id=1173278549332078728, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433696221778398, language=CN, label=表4, caption=

水产品中4种硝基呋喃类代谢物的回收率和RSDs (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
水产样品 化合物 添加水平/(μg/kg) 平均回收率
/%
日间RSDs/% 日内RSDs/%
鲤鱼 AOZ 0.5 115.9 7.7 9.3
2.0 116.3 9.5 8.7
10.0 116.5 3.8 4.5
AMOZ 0.5 100.5 3.2 2.7
2.0 102.6 3.2 2.5
10.0 99.3 3.5 3.6
AHD 0.5 104.1 4.8 6.4
2.0 104.4 5.2 2.2
10.0 102.0 4.2 4.5
SEM 0.5 105.9 9.7 9.1
2.0 102.6 5.1 5.9
10.0 98.6 5.3 9.1
南美白对虾 AOZ 0.5 99.3 6.4 8.0
2.0 106.4 8.1 5.0
10.0 104.3 7.7 5.5
南美白对虾 AMOZ 0.5 96.5 9.4 8.5
2.0 97.2 2.8 2.7
10.0 98.0 3.9 2.6
AHD 0.5 103.8 6.0 5.9
2.0 107.9 3.7 4.9
10.0 105.6 3.6 2.6
SEM 0.5 99.5 7.4 6.1
2.0 103.7 4.3 5.4
10.0 99.9 2.7 2.5
大菱鲆 AOZ 0.5 102.3 7.2 6.3
2.0 105.4 5.9 7.4
10.0 104.9 5.7 4.6
AMOZ 0.5 101.2 3.7 4.3
2.0 100.4 4.7 5.8
10.0 98.7 4.0 2.8
AHD 0.5 104.8 5.8 6.4
2.0 100.6 4.6 5.2
10.0 102.6 4.2 4.6
SEM 0.5 101.3 6.3 5.8
2.0 100.5 4.4 4.5
10.0 98.6 3.6 3.3
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壳聚糖净化-超高效液相色谱-三重四极杆/复合线性离子阱质谱法测定水产品中硝基呋喃类代谢物残留研究
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霍文迪 1, 2, 3 , 文宇鹏 2, 3, 4 , 张荣月 1, * , 李晋成 2, 3, *
食品安全质量检测学报 | 本期专题:食品中有毒有害物质分析与监测 2025,16(7): 71-77
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食品安全质量检测学报 | 本期专题:食品中有毒有害物质分析与监测 2025, 16(7): 71-77
壳聚糖净化-超高效液相色谱-三重四极杆/复合线性离子阱质谱法测定水产品中硝基呋喃类代谢物残留研究
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霍文迪1, 2, 3 , 文宇鹏2, 3, 4, 张荣月1, * , 李晋成2, 3, *
作者信息
  • 1.北京石油化工学院新材料与化工学院, 北京 102617
  • 2.中国水产科学研究院, 北京 100141
  • 3.农业农村部水产品质量安全控制重点实验室, 北京 100141
  • 4.上海海洋大学水产与生命学院, 上海 201306
  • 霍文迪(2000—), 男, 研究生, 主要研究方向为水产品质量安全监测。E-mail:

通讯作者:

* 张荣月(1979—), 男, 教授, 主要研究方向为大孔层析介质制备及应用。E-mail:
李晋成(1983—), 男, 研究员, 主要研究方向为水产品质量安全检测技术。E-mail:
Determination of nitrofuran metabolites in aquatic products by chitosan purification-ultra performance liquid chromatography-quadrupole linear ion trap-mass spectrometry
Wen-Di HUO1, 2, 3 , Yu-Peng WEN2, 3, 4, Rong-Yue ZHANG1, * , Jin-Cheng LI2, 3, *
Affiliations
  • 1. School of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
  • 2. Chinese Academy of Fishery Sciences, Beijing 100141, China
  • 3. Key Laboratory of Control of Quality and Safety for Aquatic Products, Ministry of Agriculture, Beijing 100141, China
  • 4. College of Fisheries and Life Science, Shanghai Ocean University, Shanghai 201306, China
出版时间: 2025-04-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20241205001
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目的 建立一种基于壳聚糖净化结合超高效液相色谱-三重四极杆/复合线性离子阱质谱法, 测定水产品中硝基呋喃类代谢物残留的快速检测方法。方法 样品经盐酸水解、2-硝基苯甲醛衍生、乙酸乙酯提取、壳聚糖净化、氮吹浓缩复溶后, 借助超高效液相色谱仪实现快速分离, 三重四极杆/复合线性离子阱质谱仪进行测定, 内标法定量分析, 实现快速、准确地测定水产品中硝基呋喃类代谢物残留量。结果 4种硝基呋喃类代谢物在0.5~10.0 μg/L质量浓度范围内线性关系良好, 相关系数均大于0.998, 定量限为0.5 μg/kg; 以鲤鱼、大菱鲆以及南美白对虾为样品, 在3个不同添加水平下4种硝基呋喃类代谢物的平均回收率为96.5%~116.5%, 日内相对标准偏差为2.2%~9.3%, 日间相对标准偏差为2.7%~9.7%。结论 该方法经济、简便、高效, 灵敏度高, 重复性好, 可作为水产品中4种硝基呋喃类代谢物残留的常规检测方法。

壳聚糖  /  水产品  /  硝基呋喃类代谢物  /  超高效液相色谱-三重四极杆/复合线性离子阱质谱法

Objective To develop a rapid method for the determination of nitrofuran metabolites in aquatic products based on chitosan purification combined with ultra performance liquid chromatography and triple quadrupole/composite linear ion trap mass spectrometer. Methods The samples were hydrolyzed by hydrochloric acid, derived by 2-nitrobenzaldehyde, extracted by ethyl acetate, rapidly purified by chitosan, and then concentrated and redissolved. Rapid separation was achieved by ultra performance liquid chromatography, measured by triple quadrupole/composite linear ion trap mass spectrometer, and quantified by internal standard method to achieve the rapid and accurate determination of nitrofuran metabolites residues in aquatic products. Results The 4 kinds of nitrofuran metabolites had a good linear relationship in the concentration range of 0.5-10.0 μg/L, the correlation coefficients were all more than 0.998, and the limit of quantification was 0.5 μg/kg. Taking carp, Scophthalmus maximus and Litopenaeus vannamei as samples, the average recovery of 4 kinds of nitrofuran metabolites at 3 different addition levels was 96.5%-116.5%, the intra-day relative standard deviation was 2.2%-9.3%, and the intra-day relative standard deviation was 2.7%-9.7%. Conclusion The method is economical, simple, efficient, sensitive and reproducible, and can be used as a routine method for the determination of 4 kinds of nitrofuran metabolites in aquatic products.

chitosan  /  aquatic products  /  nitrofuran metabolites  /  ultra performance liquid chromatography- quadrupole linear ion trap-mass spectrometry
霍文迪, 文宇鹏, 张荣月, 李晋成. 壳聚糖净化-超高效液相色谱-三重四极杆/复合线性离子阱质谱法测定水产品中硝基呋喃类代谢物残留研究. 食品安全质量检测学报, 2025 , 16 (7) : 71 -77 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241205001
Wen-Di HUO, Yu-Peng WEN, Rong-Yue ZHANG, Jin-Cheng LI. Determination of nitrofuran metabolites in aquatic products by chitosan purification-ultra performance liquid chromatography-quadrupole linear ion trap-mass spectrometry[J]. Journal of Food Safety & Quality, 2025 , 16 (7) : 71 -77 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241205001
硝基呋喃类药物作为一种能够对抗大部分细菌的抗生素, 其主要包括呋喃西林、呋喃它酮、呋喃妥因和呋喃唑酮4种化合物[1-3]。已有研究表明, 硝基呋喃类化合物毒副作用明显, 可能造成致癌、致畸、致突变等严重后果[4-6]。因此, 其残留问题引起了国内外的广泛重视。我国农业农村部公告第250号[7]明确规定硝基呋喃类化合物禁止在食品动物中使用。
呋喃西林、呋喃它酮、呋喃妥因和呋喃唑酮4种硝基呋喃类药物有着在鱼肉、虾肉等水产基质内快速代谢的特性, 它们所对应的最终代谢后目标物分别为氨基脲(semicarbazide, SEM)、3-氨基-2-恶唑烷基酮(3-amino-2-oxazolidone, AOZ)、1-氨基-2-内酰脲(1-aminohydantoin, AHD)和5-甲基吗啉-3-氨基-2-噁唑烷基酮(5-morpholinomethyl-3-amino-2-oxazolidone, AMOZ), 这些产物容易与蛋白相结合且最终产物结构稳定。故常通过检测其相应的4种代谢产物来反映4种硝基呋喃类化合物残留水平[8-9]。目前, 硝基呋喃类代谢药物残留的检测方法有免疫层析法[10-12]、酶联免疫法[13-14]和高效液相色谱法[15]等。与超高效液相色谱-串联质谱法相比, 免疫层析法受抗原的稳定性及灵敏度的影响, 易受杂质干扰; 酶联免疫法的操作过程中易受温度干扰; 高效液相色谱法则存在灵敏度较低的问题。
水产品基质中成分相对复杂, 杂质蛋白以及脂质成分较为丰富, 因此需要选用合适的样品前处理方法对最终所得复溶上机液净化处理, 以此来保障硝基呋喃类代谢物残留测定的准确性及稳定性, 如正己烷去脂法[16-17]、固相萃取法[18]、基质分散固相萃取[19]和Oasis PRiME HLB净化法[5]等。然而, 传统的固相萃取净化方法的操作步骤烦琐, 耗时长[20]。GB 31656.13—2021《食品安全国家标准 水产品中硝基呋喃类代谢物多残留的测定 液相色谱-串联质谱法》需要采用14000 r/min超高速离心10 min的方式对最终的复溶后上机液进行净化操作。而在各领域的实际应用中, 壳聚糖作为渔业副产物的一类天然聚合物[21], 其自身具有无毒[22]、绿色环保、可降解[23-24]且低成本[25]的优势, 此外, 壳聚糖其表面富含众多的羟基、氨基等官能团[26], 赋予了它对多种油脂类杂质[27-30]优异的吸附效果, 同时在农药残留检测中, 壳聚糖由于除脂能力, 能够极大程度降低脂类杂质对于最终仪器检测的干扰。该材料将可以选择性吸附并去除提取液中的脂肪、磷脂类等干扰物, 从而达到净化提取液的目的。与固相萃取、14000 r/min超高速离心等传统样品前处理方法相比, 使用壳聚糖来进行净化处理可以免除活化、淋洗以及洗脱等一系列步骤, 仅需一步离心便可以完成提取液的净化处理, 具有处理方法高效、操作便捷的优势。
本研究基于壳聚糖快速净化方法, 结合超高效液相色谱-三重四极杆/复合线性离子阱质谱仪(ultra performance liquid chromatography-quadrupole linear ion trap-mass spectrometry, UPLC-QTRAP-MS/MS)建立了鲤鱼中4种硝基呋喃类代谢物的准确定量检测方法, 以期为水产基质中硝基呋喃类代谢的检测提供新思路。
壳聚糖(CAS: 9012-76-4, 黏度: 100~200 mPa·s, 阿拉丁生化科技股份有限公司); SEM、AOZ、AHD和AMOZ 4种硝基呋喃类代谢物标准品(批号: S155597)、SEM-13C-15N2、AOZ-D4、AHD-13C3和AMOZ-D5 4种硝基呋喃类代谢物同位素内标标准品(批号: S178961)(天津阿尔塔科技有限公司); 2-硝基苯甲醛(德国CNW科技公司); 乙酸乙酯和甲醇(色谱纯, 美国J.T.Baker公司); 盐酸(分析纯, 上海信裕生物科技有限公司); 二甲基亚砜、乙酸铵(色谱纯)、磷酸氢二钾(分析纯)(阿拉丁生化科技股份有限公司); 蒸馏水(广州屈臣氏食品饮料有限公司)。
QTRAP 5500 HPLC-QTRAP-MS/MS(美国AB SCIEX公司); H-2050 R台式高速离心机(湖南湘仪实验室仪器开发有限公司); SB-5200 DTN超声波水浴机(宁波新芝生物科技股份有限公司); MVM-2500多管涡旋混匀仪(上海泰坦科技股份有限公司); AB265-S双量程分析天平(0.01/0.1 mg)、MS 3 Basic旋涡混匀器(德国IKA公司); ZHWY-110 X 30水浴恒温振荡器(上海智城分析仪器制造有限公司); N-EVAPTM112氮吹仪(美国Organomation Aossociates公司); Hypersil GOLD色谱柱(50 mm×2.1 mm, 1.7 µm)(美国沃特世公司)。
本研究用于方法建立与验证的鲤鱼采购于北京市水产市场, 通过冷藏运输转移至实验室; 去除鱼皮鱼骨, 保留可食用部位, 经均质机捣碎为鱼糜状, 于-20 ℃下冷冻保存, 备用。
取适量硝基呋喃混合标准液采用甲醇稀释, 配制系列混合标准中间液(100.0、10.0、1.0 μg/mL)和混合内标标准中间液(100.0、10.0、1.0 μg/mL), -20 ℃遮光保存备用。于临近使用前, 用水进行逐级稀释, 分别制备得到混合标准工作液(100.0、10.0 ng/mL)和混合内标标准工作液(50.0 ng/mL)。
液相色谱柱为Hypersil GOLD色谱柱(50 mm×2.1 mm, 1.7 µm); 进样量: 10.0 μL; 柱温箱设定温度: 40℃; 流动相由A相和B相两相组成, 其中A相: 醋酸铵水溶液(2 mmol/L), B相: 甲醇; 梯度洗脱, 洗脱程序详见表1
采用电喷雾离子源在正离子模式下电离分析物, 检测模式为多反应监测模式。离子源具体设置参数: 离子源温度: 650.0 ℃; 离子化电压: 5.5 kV; 气帘气: 30.0 psi; 雾化气: 60.0 psi; 辅助气: 55.0 psi。4种硝基呋喃类代谢物在多反应监测模式下的质谱参数详见表2
(1)水解和衍生化
取一支50 mL离心管, 准确称量并加入2.0 g样品, 加入0.05 mL混合内标工作溶液(100 μg/L), 涡旋混合均匀。随后分别加入5.0 mL盐酸(0.2 mol/L)和0.15 mL 2-硝基苯甲醛溶液(0.05 mol/L), 涡旋混合至分散均匀。最后将离心管放于恒温水浴振荡器(水温37 ℃)内且避光振荡反应16 h (衍生化反应方程式见图1)。
(2)提取和净化过程
取出离心管冷却至室温, 加入1.0 mol/L磷酸氢二钾15 mL调整pH至7.0~7.5, 随后加入8 mL乙酸乙酯涡旋振荡1 min, 6000 r/min离心5 min, 取上清液加入至15 mL离心管, 再加入1.2 g无水硫酸钠以及80 mg壳聚糖涡旋1 min, 随后8000 r/min离心10 min并将全部液体转移至10 mL离心管, 40 ℃下氮吹至干, 加入1 mL 5%甲醇水溶液进行复溶, 过0.22 μm滤膜上机检测。
采用甲醇稀释混合标准工作溶液以分别得到10.0 ng/mL以及100.0 ng/mL混合标准工作溶液, 配制得到质量浓度为0.5、1.0、2.0、5.0和10.0 ng/mL的系列标准溶液, 除不加实际样品和不进行净化处理外, 其余实验步骤按1.2.4进行前处理操作, 按1.2.3条件进行检测, 采用内标法制做标准曲线。
采用SCIEX的Analyst® Software软件对数据进行采集, MultiQuant 3.0.3软件进行定量分析。所有数据均由Word Processing System Excel计算, 由OriginPro 2022软件作图。
硝基呋喃类代谢物经水解、衍生、提取、浓缩等一系列前处理后的复溶液中仍含有干扰物质, 影响定量检测结果。本研究以鲤鱼样品为实验对象, 采用壳聚糖对乙酸乙酯提取液进行除杂净化处理。本研究以加标浓度为10 μg/kg的鲤鱼肌肉为实验对象, 采用壳聚糖对乙酸乙酯提取液进行除杂净化处理。本研究先后对比了1 g无水硫酸钠组合不同质量壳聚糖(0、10、20、50、60、80、100 mg)净化效果。由图2可知, 随着壳聚糖用量的增加目标化合物的响应强度也随之增长, 使用80 mg壳聚糖净化乙酸乙酯提取液时目标化合物的峰响应强度综合水平较优。当壳聚糖的量低于80 mg时, 硝基呋喃类代谢物的仪器信号可能为受到基质效应的抑制, 导致仪器响应低; 当壳聚糖的量高于80 mg时, 硝基呋喃类代谢物被壳聚糖吸附的效应显著, 从而导致硝基呋喃类代谢物的仪器响应降低。因此, 本研究采用80 mg壳聚糖对乙酸乙酯提取液进行除杂净化处理。
本研究先后对比了80 mg壳聚糖组合不同质量无水硫酸钠(200、500、700、1000、1200、1500 mg)净化效果(图3)。结果表明, 采用80 mg壳聚糖和1200 mg无水硫酸钠对复溶液进行净化处理, 4种目标物色谱峰的强度最高。因此, 本研究最终选择80 mg壳聚糖和1200 mg无水硫酸钠作为最佳净化填料组合。
在GB 31656.13—2021中, 采用14000 r/min高速离心10 min的方式对复溶液进行净化处理。本研究以鲤鱼样品为实验对象, 对比了经两种不同净化方式处理后净化液的色谱图(见图4)。结果表明, 采用壳聚糖一步式净化, 4种目标物色谱峰的强度均有明显提高; 在与国标法的实验流程对比时, 使用壳聚糖一步净化的方法实验步骤更为简便, 在最终上机检测前省去了额外的高速离心以分离杂质的操作, 整体实验流程更为安全便捷; 此外, 壳聚糖的加入可以吸附去除在乙酸乙酯提取液中的脂类杂质, 使得目标物峰响应值更强。综合考虑, 选择对样品进行壳聚糖净化处理。
按照1.2.5绘制标准曲线, 内标法定量。4种目标化合物的线性回归方程、相关系数和定量限见表3。4种硝基呋喃类代谢物在0.5~10.0 μg/L浓度范围内的线性关系良好, 相关系数(r)均大于0.998, 选择10倍信噪比下的加标浓度为定量限即0.5 µg/kg, 说明本方法具有较高的灵敏度。
分别选择鲤鱼、大菱鲆以及南美白对虾为空白样品, 按照1.2.4中样品制备方法, 选用未加标基质为空白样品, 根据GB 2704—2008的要求, 选择以1倍、4倍、20倍定量限对应3个不同浓度水平制备加标样品(0.5、2.0、10.0 μg/kg)进行实验, 以保证样品在检测时浓度在一定程度内的不同变化都可以通过所设计方法进行正确的测定, 确保实验结果在不同浓度范围下的真实可靠。选择相对标准偏差(relative standard deviations, RSDs)作为该方法重复性的衡量标准。每个加标浓度下的样品采用6个平行, 计算回收率及RSDs。结果如表4所示, 3个添加浓度水平下, 4种硝基呋喃类代谢物的平均回收率为96.5%~116.5%, 日内RSDs为2.2%~9.3%, 日间RSDs为2.7%~9.7%。表明本研究建立的检测方法正确度高且重复性良好, 可满足常见水产品中4种硝基呋喃类代谢物的检测需求。
本研究使用壳聚糖快速净化, 结合UPLC-QTRAP- MS/MS, 建立了水产品中4种硝基呋喃类代谢物残留准确测定方法。实验结果表明, 该方法无需传统的高速离心净化, 且由于使用了壳聚糖对乙酸乙酯提取液进行净化, 使得目标物峰响应强度也变得更高。可以同时快速、准确测定水产品中4种硝基呋喃类代谢物残留量。此方法完全可以满足GB 31656.13—2021对AOZ、AMOZ、AHD和SEM 4种硝基呋喃类代谢物的检测要求。
  • 中央级公益性科研院所基本科研业务费项目(2025XT04)
  • 国家现代农业产业技术体系项目(CARS-48)
  • 中国水产科学研究院科技创新项目(2020TD75)
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20241205001
  • 接收时间:2024-12-05
  • 首发时间:2025-07-19
  • 出版时间:2025-04-15
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  • 收稿日期:2024-12-05
基金
中央级公益性科研院所基本科研业务费项目(2025XT04)
国家现代农业产业技术体系项目(CARS-48)
中国水产科学研究院科技创新项目(2020TD75)
作者信息
    1.北京石油化工学院新材料与化工学院, 北京 102617
    2.中国水产科学研究院, 北京 100141
    3.农业农村部水产品质量安全控制重点实验室, 北京 100141
    4.上海海洋大学水产与生命学院, 上海 201306

通讯作者:

* 张荣月(1979—), 男, 教授, 主要研究方向为大孔层析介质制备及应用。E-mail:
李晋成(1983—), 男, 研究员, 主要研究方向为水产品质量安全检测技术。E-mail:
参考文献
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https://castjournals.cast.org.cn/joweb/spaq/CN/10.19812/j.cnki.jfsq11-5956/ts.20241205001
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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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