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Article(id=1215670312407057330, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1215670311140381365, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250417002, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1744819200000, receivedDateStr=2025-04-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767767988540, onlineDateStr=2026-01-07, pubDate=1753372800000, pubDateStr=2025-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767767988540, onlineIssueDateStr=2026-01-07, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767767988540, creator=13701087609, updateTime=1767767988540, 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='1753372800000', pubDateStr='2025-07-25', 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, articleTotal=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, downloadFileDto=null}, startPage=154, endPage=159, ext={EN=ArticleExt(id=1215670314835559358, articleId=1215670312407057330, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Determination of total mercury in food by direct mercury analysis, columnId=1151895321388347923, journalTitle=Journal of Food Safety & Quality, columnName=Food Analysis and Detection, runingTitle=null, highlight=null, articleAbstract=

Objective To establish and evaluate the application of direct mercury analysis for the determination of total mercury in food. Methods A direct mercury analysis method was developed based on catalytic pyrolysis-gold amalgamation atomic absorption spectroscopy. By stepwise optimization of pyrolysis temperatures (150 °C/550 °C for low-concentration ranges and 200 °C/650 °C for high-concentration ranges) and carrier gas flow rates (150-200 mL/min), plant-derived samples (e.g., rice, jujube), animal-derived samples (e.g., snakehead, fish meal), and 14 kinds of food samples were analyzed. The method’s detection limit, accuracy, stability and spike recovery were evaluated to assess its performance and matrix applicability. Results The method established dual linear calibration curves of 0-10 ng and 25-200 ng, with correlation coefficients of 0.9993 and 0.9998, respectively. The limit of detection and limit of quantitation were 0.0002 mg/kg and 0.0005 mg/kg, respectively. Spike recoveries ranged from 90% to 116%, the intra-day and inter-day repeatability relative standard deviation was less than or equal to 6.5% and less than or equal to 7.7%, respectively. The method was systematically validated for complex matrices, including plant-derived, animal-derived, and processed foods, with all results complying with the GB 2762-2022 National food safety standard-Limits of contaminants in foods. Conclusion The proposed method eliminates the need for chemical digestion in sample pretreatment, significantly shortens the analytical time, and prevents mercury volatilization losses. It overcomes the limitations of single-matrix analysis and achieves rapid total mercury detection in diverse complex food matrices, thereby providing an efficient and reliable technical solution for food safety risk monitoring and regulatory compliance.

, authors=null, authorsList=Xing DU, Shu-Gang GUO, Wen-Jun WANG, authorCompany=null, correspAuthors=Xing DU, 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, fund=null), CN=ArticleExt(id=1215670315116577732, articleId=1215670312407057330, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=直接进样测汞法检测食品中总汞含量, 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=

目的 建立直接进样测汞法在食品总汞检测中的应用方法并进行评价。方法 基于催化热解-金汞齐原子吸收原理, 开发直接进样测汞法, 通过分段优化热解温度(低浓度段150 ℃/550 ℃, 高浓度段200 ℃/650 ℃)及载气流速(150~200 mL/min), 对植物性样品(大米、红枣等), 动物源性样品(黑鱼、鱼粉等)及14种食品样品进行检测, 对本方法的检出限、准确性、稳定性及加标回收率进行分析, 评价其方法性能及基质适用性。结果 方法成功构建0~10 ng与25~200 ng双线性校准曲线, 相关系数分别为0.9993和0.9998; 检出限与定量限分别为0.0002 mg/kg和0.0005 mg/kg; 加标回收率为90%~116%, 日内与日间重复性相对标准偏差分别小于等于6.5%和小于等于7.7%。系统验证了方法在植物性样品、动物源性样品及加工食品等复杂基质中的适用性, 检测结果均符合GB 2762—2022《食品安全国家标准 食品中污染物限量》的要求。结论 本方法 无需化学消解即可完成样品前处理, 显著缩短检测周期, 且避免了汞的挥发损失; 突破了单一基质检测的局限性, 实现了多种复杂基质食品中总汞的快速检测, 为食品安全风险监测及监管提供了高效可靠的技术支撑。

, authors=null, authorsList=杜兴, 郭舒岗, 王文军, authorCompany=null, correspAuthors=杜兴, authorNote=null, correspAuthorsNote=
*杜兴(1985—), 女, 硕士, 副主任技师, 主要研究方向为卫生检验。E-mail:
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Method 7473: Mercury in solids and solutions by thermal decomposition, amalgamation, and atomic absorption spectrophotometry [Z]. 2007., articleTitle=null, refAbstract=null), Reference(id=1215686863759790620, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, doi=null, pmid=null, pmcid=null, year=2024, volume=15, issue=14, pageStart=59, pageEnd=66, url=null, language=null, rfNumber=[30], rfOrder=52, authorNames=陈晓敏, 陈韵, 梁智安, journalName=食品安全质量检测学报, refType=null, unstructuredReference=陈晓敏, 陈韵, 梁智安, 等. 基于电感耦合等离子体质谱法对广州市售水产品中6种重金属的含量测定与污染评价[J]. 食品安全质量检测学报, 2024, 15(14): 59-66., articleTitle=基于电感耦合等离子体质谱法对广州市售水产品中6种重金属的含量测定与污染评价, refAbstract=null), Reference(id=1215686863818510881, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, doi=null, pmid=null, pmcid=null, year=2024, volume=15, issue=14, pageStart=59, pageEnd=66, url=null, language=null, rfNumber=[30], rfOrder=53, authorNames=CHEN XM, CHEN Y, LIANG ZAN, journalName=Journal of Food Safety & Quality, refType=null, unstructuredReference=CHEN XM, CHEN Y, LIANG ZAN, et al. Determination and pollution assessment of six heavy metals in commercially available aquatic products in Guangzhou City based on ICP-MS[J]. Journal of Food Safety & Quality, 2024, 15(14): 59-66., articleTitle=Determination and pollution assessment of six heavy metals in commercially available aquatic products in Guangzhou City based on ICP-MS, refAbstract=null)], funds=[Fund(id=1215686855123718330, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, awardId=2021121, language=CN, fundingSource=山西省卫生健康委科研课题项目(2021121), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1215686851860550540, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, xref=null, ext=[AuthorCompanyExt(id=1215686851873133454, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, companyId=1215686851860550540, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Shanxi Provincial Center for Disease Control and Prevention, Taiyuan 030032, China), AuthorCompanyExt(id=1215686851881522064, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, companyId=1215686851860550540, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=山西省疾病预防控制中心, 太原 030032)])], figs=[ArticleFig(id=1215686854029004890, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=EN, label=Table 1, caption=

Intra-day and inter-day stability results

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 日内测定均值/(mg/kg) 日内RSDs/% 日间测定均值/(mg/kg) 日间RSDs/%
大米 0.0018 4.1 0.0019 5.7
红枣 0.0021 4.0 0.0023 4.6
红茶 0.0016 6.5 0.0018 7.7
蘑菇粉 0.5700 0.8 0.5800 1.8
黑鱼(鲜) 0.0094 2.9 0.0094 3.1
鱼粉 0.2800 2.5 0.2900 3.7
), ArticleFig(id=1215686854171611241, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=CN, label=表1, caption=

日内与日间稳定性结果

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 日内测定均值/(mg/kg) 日内RSDs/% 日间测定均值/(mg/kg) 日间RSDs/%
大米 0.0018 4.1 0.0019 5.7
红枣 0.0021 4.0 0.0023 4.6
红茶 0.0016 6.5 0.0018 7.7
蘑菇粉 0.5700 0.8 0.5800 1.8
黑鱼(鲜) 0.0094 2.9 0.0094 3.1
鱼粉 0.2800 2.5 0.2900 3.7
), ArticleFig(id=1215686854297440374, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=EN, label=Table 2, caption=

Spike recovery results of different matrices (n=3, mg/kg)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 基质特性 本底值/(mg/kg) 加标水平/(mg/kg) 回收率
/%
矿泉水 水 <0.0002 0.0002 95
0.0005 96
0.0010 97
圆白菜 高水分 <0.0002 0.0018 96
0.0056 116
0.0120 111
大米 高纤维 0.0017 0.0011 108
0.01000 93
0.01800 111
鱼粉 均质粉末 0.058 0.00095 105
0.054 103
0.520 104
猪肝 高脂肪 0.072 0.005 96
0.020 105
0.100 95
全脂奶粉 高脂肪 <0.0002 0.001 90
0.005 94
0.010 95
), ArticleFig(id=1215686854385520769, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=CN, label=表2, caption=

不同基质样品的加标回收率测定结果(n=3, mg/kg)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 基质特性 本底值/(mg/kg) 加标水平/(mg/kg) 回收率
/%
矿泉水 水 <0.0002 0.0002 95
0.0005 96
0.0010 97
圆白菜 高水分 <0.0002 0.0018 96
0.0056 116
0.0120 111
大米 高纤维 0.0017 0.0011 108
0.01000 93
0.01800 111
鱼粉 均质粉末 0.058 0.00095 105
0.054 103
0.520 104
猪肝 高脂肪 0.072 0.005 96
0.020 105
0.100 95
全脂奶粉 高脂肪 <0.0002 0.001 90
0.005 94
0.010 95
), ArticleFig(id=1215686854507155593, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=EN, label=Table 3, caption=

Determination results of certified reference materials in different matrices (n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 认定值/(mg/kg) 平均值/(mg/kg) RSDs/% 标准物质编号
菠菜 0.567±0.096 0.5700 1.7 P51815B
茶叶 0.008±0.001 0.0086 1.3 GBW10016a GSB-7a
大米 0.0041±0.0008 0.0047 3.5 GBW(E)100349
黄豆 0.0015 0.0015 3.8 GBW10013(GSB-4)
奶粉 0.0022 0.0022 4.4 GBW10017a(GSB-8a)
三文鱼冻干粉 0.039±0.002 0.0390 1.5 GBW10210
猪肝 0.045±0.008 0.0460 4.5 GBW10051(GSB-29)
), ArticleFig(id=1215686854620401814, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=CN, label=表3, caption=

不同基质标准物质测定结果(n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 认定值/(mg/kg) 平均值/(mg/kg) RSDs/% 标准物质编号
菠菜 0.567±0.096 0.5700 1.7 P51815B
茶叶 0.008±0.001 0.0086 1.3 GBW10016a GSB-7a
大米 0.0041±0.0008 0.0047 3.5 GBW(E)100349
黄豆 0.0015 0.0015 3.8 GBW10013(GSB-4)
奶粉 0.0022 0.0022 4.4 GBW10017a(GSB-8a)
三文鱼冻干粉 0.039±0.002 0.0390 1.5 GBW10210
猪肝 0.045±0.008 0.0460 4.5 GBW10051(GSB-29)
), ArticleFig(id=1215686854750425247, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=EN, label=Table 4, caption=

Mercury content in different food samples (n=3, mg/kg)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 平均值 样品 平均值
矿泉水 <0.0002 奶粉 <0.0002
牛奶 <0.0002 黄豆 0.00071
鸡蛋 <0.0002 猪肉 <0.0002
黄桃罐头 <0.0002 鲜蘑菇 0.00068
白菜 <0.0002 食用盐 <0.0002
大米 0.0017 鱼肉 0.0095
小麦粉 <0.0002 茶叶 0.0086
), ArticleFig(id=1215686854846894247, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1215670312407057330, language=CN, label=表4, caption=

不同食品样品中汞的含量(n=3, mg/kg)

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 平均值 样品 平均值
矿泉水 <0.0002 奶粉 <0.0002
牛奶 <0.0002 黄豆 0.00071
鸡蛋 <0.0002 猪肉 <0.0002
黄桃罐头 <0.0002 鲜蘑菇 0.00068
白菜 <0.0002 食用盐 <0.0002
大米 0.0017 鱼肉 0.0095
小麦粉 <0.0002 茶叶 0.0086
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直接进样测汞法检测食品中总汞含量
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杜兴 * , 郭舒岗 , 王文军
食品安全质量检测学报 | 食品分析与检测 2025,16(14): 154-159
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食品安全质量检测学报 |食品分析与检测 2025 , 16 (14) : 154 -159
直接进样测汞法检测食品中总汞含量
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杜兴* , 郭舒岗, 王文军
作者信息
  • 山西省疾病预防控制中心, 太原 030032
通讯作者:
*杜兴(1985—), 女, 硕士, 副主任技师, 主要研究方向为卫生检验。E-mail:
Determination of total mercury in food by direct mercury analysis
Xing DU* , Shu-Gang GUO, Wen-Jun WANG
Affiliations
  • Shanxi Provincial Center for Disease Control and Prevention, Taiyuan 030032, China
出版时间: 2025-07-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250417002
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摘要
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目的 建立直接进样测汞法在食品总汞检测中的应用方法并进行评价。方法 基于催化热解-金汞齐原子吸收原理, 开发直接进样测汞法, 通过分段优化热解温度(低浓度段150 ℃/550 ℃, 高浓度段200 ℃/650 ℃)及载气流速(150~200 mL/min), 对植物性样品(大米、红枣等), 动物源性样品(黑鱼、鱼粉等)及14种食品样品进行检测, 对本方法的检出限、准确性、稳定性及加标回收率进行分析, 评价其方法性能及基质适用性。结果 方法成功构建0~10 ng与25~200 ng双线性校准曲线, 相关系数分别为0.9993和0.9998; 检出限与定量限分别为0.0002 mg/kg和0.0005 mg/kg; 加标回收率为90%~116%, 日内与日间重复性相对标准偏差分别小于等于6.5%和小于等于7.7%。系统验证了方法在植物性样品、动物源性样品及加工食品等复杂基质中的适用性, 检测结果均符合GB 2762—2022《食品安全国家标准 食品中污染物限量》的要求。结论 本方法 无需化学消解即可完成样品前处理, 显著缩短检测周期, 且避免了汞的挥发损失; 突破了单一基质检测的局限性, 实现了多种复杂基质食品中总汞的快速检测, 为食品安全风险监测及监管提供了高效可靠的技术支撑。

总汞检测  /  直接测汞法  /  复杂基质  /  食品安全

Objective To establish and evaluate the application of direct mercury analysis for the determination of total mercury in food. Methods A direct mercury analysis method was developed based on catalytic pyrolysis-gold amalgamation atomic absorption spectroscopy. By stepwise optimization of pyrolysis temperatures (150 °C/550 °C for low-concentration ranges and 200 °C/650 °C for high-concentration ranges) and carrier gas flow rates (150-200 mL/min), plant-derived samples (e.g., rice, jujube), animal-derived samples (e.g., snakehead, fish meal), and 14 kinds of food samples were analyzed. The method’s detection limit, accuracy, stability and spike recovery were evaluated to assess its performance and matrix applicability. Results The method established dual linear calibration curves of 0-10 ng and 25-200 ng, with correlation coefficients of 0.9993 and 0.9998, respectively. The limit of detection and limit of quantitation were 0.0002 mg/kg and 0.0005 mg/kg, respectively. Spike recoveries ranged from 90% to 116%, the intra-day and inter-day repeatability relative standard deviation was less than or equal to 6.5% and less than or equal to 7.7%, respectively. The method was systematically validated for complex matrices, including plant-derived, animal-derived, and processed foods, with all results complying with the GB 2762-2022 National food safety standard-Limits of contaminants in foods. Conclusion The proposed method eliminates the need for chemical digestion in sample pretreatment, significantly shortens the analytical time, and prevents mercury volatilization losses. It overcomes the limitations of single-matrix analysis and achieves rapid total mercury detection in diverse complex food matrices, thereby providing an efficient and reliable technical solution for food safety risk monitoring and regulatory compliance.

total mercury detection  /  direct mercury analyzer  /  complex matrices  /  food safety
杜兴, 郭舒岗, 王文军. 直接进样测汞法检测食品中总汞含量. 食品安全质量检测学报, 2025 , 16 (14) : 154 -159 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250417002
Xing DU, Shu-Gang GUO, Wen-Jun WANG. Determination of total mercury in food by direct mercury analysis[J]. Journal of Food Safety & Quality, 2025 , 16 (14) : 154 -159 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250417002
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0 引言
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汞是一种具有毒性和致癌性的重金属污染物, 已于2017年被世界卫生国际癌症研究机构列入癌症清单[1]。其广泛以金属汞(Hg⁰)、无机汞(Hg²⁺)和有机汞(如甲基汞)等形式存在, 可通过生物链进入人体, 并在器官中累积, 具有持久性、生物累积性和多器官毒性, 严重威胁生态系统和人类健康[2-5]。汞中毒可导致神经系统损伤(语言障碍、听力障碍、感觉障碍等, 甚至瘫痪)及致畸、致癌、致突变的效应, 高浓度暴露可致死[6]。世界卫生组织将其列为重点管控的重金属[7-9]。鉴于食用含汞食品是人类主要暴露途径,对食品中总汞的精准检测与动态监控至关重要。
目前, 食品总汞检测主要依赖于原子荧光光谱法(atomic fluorescence spectrometry, AFS)[10-16]、电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)[17-22]及冷原子吸收光谱法(cold vapor atomic absorption spectrometry, CVAAS)[23-24]等传统技术。AFS虽灵敏度高[检出限(limit of detection, LOD)=0.0003 mg/kg], 但存在汞蒸气泄漏风险; ICP-MS虽可检测超痕量汞(LOD=0.0005 mg/kg), 但需复杂前处理且仪器成本高昂; CVAAS操作简便, 但易受挥发性有机物干扰且检出限较高。这些技术的局限性推动了检测方法的革新。
直接进样测汞法(direct mercury analysis, DMA)基于催化热解-金齐化-冷原子吸收原理可直接测定固体及液体样品中的总汞, 无需消解前处理, 具有检出限低, 避免试剂污染及汞挥发损失等优势, 显著减少前处理时间和污染风险[25], 为食品汞污染快速筛查提供了高效、环保的解决方案。然而, 现有研究多聚焦单一食品基质[26-28], 其在复杂多样基质中的适用性尚缺乏系统验证。本研究通过优化仪器参数, 建立双线性检测范围, 系统评价直接进样测汞法在多种食品基质中的准确性、精密度及稳定性, 旨在为食品安全监管提供技术支持。
1 材料与方法
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1.1 材料与试剂
大米、红枣、红茶、蘑菇粉、黑鱼(鲜)、鱼粉、圆白菜、矿泉水、牛奶、鸡蛋、黄桃罐头、白菜、大米、奶粉、黄豆、猪肉、鲜蘑菇、食用盐样品为实验室留存; 国家标准物质样品有菠菜(P51815B)、茶叶(GBW10016a GSB-7a)、大米[GBW(E)100349]、黄豆[GBW10013(GSB-4)]、奶粉GBW10017a(GSB-8a)、三文鱼冻干粉(GBW10210)、猪肝GBW10051(GSB-29)、汞标准溶液[GBW(E)83186](中国坛墨质检科技股份有限公司); 高纯氧气(纯度99.999%, 太原市泰能气体有限公司); 硝酸(优级纯, 国药集团化学试剂有限公司)。
1.2 仪器与设备
DMA-80全自动直接测汞仪(意大利MILESTONE公司); SQP电子天平(感量为0.1 mg, 德国赛多利斯公司); Milli-Q超纯水系统(美国Millipore公司); LX1811马弗炉(天津莱玻特瑞公司)。
1.3 实验方法
1.3.1 样品前处理
液体样品: 矿泉水、牛奶直接摇匀后取样, 取液体样品0.1~0.5 g(视汞浓度调整)直接进样; 半固体/膏状样品: 黄桃罐头果肉、酸奶(若含固体成分), 使用研钵研磨至无可见颗粒。取均质后样品0.1~0.3 g, 直接进样; 鲜样(高水分动植物组织): 黑鱼(鲜)、猪肉、圆白菜、白菜、鲜蘑菇、鸡蛋(全蛋匀浆), 可直接取样品的可食部分匀浆后称取0.5~1.0 g的样品进样; 干样(低水分固体): 大米、红枣、红茶、蘑菇粉、鱼粉、奶粉、黄豆、食用盐, 使用高速粉碎机研磨至粉末(过80目筛), 粉末样品混合均匀后称量 0.05~0.10 g直接进样。所有样品需混合均匀, 避免局部汞分布差异; 每批次实验同步测定空白样品; 高油脂样品(如鱼粉)进样后需增加仪器清洁程序, 防止残留。根据样品类型, 准确称取0.05~0.50 g(精确至0.0001 g)置于镍舟中, 避免手动接触以减少污染。
1.3.2 标准曲线绘制
采用逐级稀释法配制汞标准系列: 低质量浓度段(0、2、5、10 ng/mL)和高质量浓度段(25、50、100、200 ng/mL), 以0.5 g/L重铬酸钾和3%硝酸溶液为稀释剂, 避免汞吸附损失[29]。
1.3.3 仪器参数优化
通过单因素实验确定最佳热解条件: 低浓度段(0~10 ng): 干燥温度150 ℃ (40 s)、分解温度550 ℃ (180 s), 载气流速150 mL/min, 延长汞蒸气停留时间以提升灵敏度; 高浓度段(25~200 ng): 干燥温度200 ℃ (30 s)、分解温度650 ℃ (150 s), 载气流速200 mL/min, 加速汞释放并防止信号饱和。
样品舟的净化: 将样品舟中残留的样品灰烬处理干净后,可使用马弗炉高温灼烧(600~800 ℃) 20 min以上, 去除汞残留。
1.3.4 热解与催化分解
食品置于石英样品舟中, 送入高温炉在氧气流中热解, 有机物被完全氧化分解, 汞蒸气的预富集: 汞蒸气通过金汞齐捕集阱, 选择性吸附汞原子, 热释放与检测: 捕集阱快速加热, 释放纯化后的汞蒸气, 汞蒸气进入检测池采用冷蒸气原子吸收法测定汞特征吸收信号。
1.3.5 方法验证
线性范围: 采用最小二乘法拟合标准曲线; 灵敏度: 以3倍信噪比(S/N=3)计算LOD, 10倍信噪比(S/N=10)计算定量限(limit of quantitation, LOQ); 准确度与精密度: 通过加标回收实验(低、中、高3个水平)和重复性实验(日内n=6, 日间n=6)评估; 基质效应: 选取14类食品(涵盖谷物、水产品、加工食品等)进行检测, 对比不同基质的回收率与相对标准偏差(relative standard deviation, RSD)。
1.4 数据处理
每组实验重复进行3次, 采用Excel 2022 (Microsoft)对检测数据进行分析, 计算方法的检出限、稳定性、精密度、加标回收率等实验结果。
2 结果与分析
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2.1 标准曲线构建与线性分析
低浓度段(0~10 ng)回归方程为A=0.0051+0.0437×Hg (r=0.9993); 高浓度段(25~200 ng)为A=0.0032+0.0008×Hg (r=0.9998)。双线性设计有效覆盖食品中痕量(0.0002 mg/kg)至中高浓度汞(0.2 mg/kg)的检测需求。双线性范围覆盖食品常见汞含量, 对空白样品进行21次重复性实验, 当取样量为0.1 g时, LOD与LOQ分别达0.0002 mg/kg和0.0005 mg/kg, 优于传统ICP-MS法(LOD=0.001 mg/kg)[30]。
2.2 方法稳定性验证
本研究通过日内(n=6)和日间(n=6)重复性实验, 评估了直接进样测汞法在不同食品基质中的稳定性, 结果如表1所示。以下从基质特性、汞含量与稳定性关联性、方法适用性3方面进行讨论。
2.2.1 基质特性对稳定性的影响
植物性食品(大米、红枣、红茶): 低汞含量与高RSD: 大米(日内RSD=4.1%, 日间RSD=5.7%)和红茶(日间RSD=7.7%)的稳定性较低, 可能因植物纤维包裹汞导致分布不均, 且低含量(0.0016~0.0023 mg/kg)下微小波动易被放大。红枣的特殊性: 红枣(日内RSD=4.0%)稳定性优于其他植物样品, 可能与其糖分和果胶成分固定汞有关。加工粉末(蘑菇粉): 最优稳定性: 蘑菇粉的日内RSD=0.8%, 日间RSD=1.8%, 显著优于其他样品。其干燥均质特性降低了基质复杂性, 高汞含量(0.57 mg/kg)也提升了信号稳定性。动物源性样品(黑鱼、鱼粉): 中等稳定性: 黑鱼(日内RSD=2.9%)和鱼粉(日间RSD=3.7%)的均匀蛋白质基质减少了汞分布差异, 但鱼粉加工过程中可能的脂肪残留导致日间波动略高。
2.2.2 汞含量与稳定性的关联性
高汞样品(蘑菇粉、鱼粉): 汞含量>0.1 mg/kg时, RSD普遍<4%, 符合GB/T 27404—2008 实验室质量控制规范 食品理化检测对高含量样品的要求(RSD≤5%)。低汞样品(大米、红茶): 汞含量<0.005 mg/kg时, RSD升高至5%~8%, 需通过增加平行测定次数(如n=9)或优化前处理(如延长均质时间)提升重复性。
2.2.3 方法适用性评价
日内稳定性: 所有样品RSD≤6.5%, 满足常规检测需求(RSD≤10%)。
日间稳定性: 日间RSD≤7.7%, 其中均质样品(如蘑菇粉)RSD≤1.8%, 表明方法长期可靠性良好。
2.3 方法准确度验证
准确度是本研究评判方法是否可靠的重要一环, 只有保证方法的准确度才能验证方法的实用性和可靠性。本研究选取了6种不同的食品样品进行3水平加标回收的试验, 同时还采用标准物质进行验证性实验。
2.3.1 加标回收率
不同的食品样品中汞含量不同, 为系统评估方法准确性, 本研究选取矿泉水、圆白菜(高水分)、大米(高纤维)、鱼粉(均质粉末)、猪肝(动物内脏)、全脂奶粉(高脂肪)6类典型基质, 分别进行低、中、高3个水平的加标回收实验, 每个水平平行测定3次, 计算回收率, 回收率范围为90%~116%, 结果见表2。
GB 5009.295—2023《食品安全国家标准 化学分析方法验证通则》中规定了不同浓度对方法正确度的要求, 样品中被测组分含量不同, 其加标回收率的要求是不同的。当被测组分含量<1 μg/kg, 回收率范围50%~120%; 被测组分含量1~10 μg/kg, 回收率范围60%~120%; 被测组分含量10~100 μg/kg, 回收率范围70%~120%; 被测组分含量100~1000 mg/kg, 回收率范围80%~110%; 被测组分含量>1 g/kg, 回收率范围90%~105%。从表2结果可以看出, 矿泉水的3水平加标回收率在95%~97%; 圆白菜的3水平加标回收率在96%~116%之间, 大米的3水平加标回收率在93%~111%之间; 鱼粉的3水平加标回收率在103%~105%之间, 鱼粉(均质粉末): 所有加标水平回收率(103%~105%)接近理论最佳值(100%), 验证均匀基质对准确性的提升作用。
猪肝的3水平加标回收率在95%~105%之间, 表明脂肪(5%~7%)未显著干扰汞检测; 全脂奶粉的3水平加标回收率在90%~95%之间, 略低于低脂样品(如鱼粉), 可能与乳脂包裹汞颗粒导致部分损失有关, 可以增加梯度升温程序(200 ℃→500 ℃)以分解脂质提高回收率。不同基质的样品均满足不同含量水平的回收率要求, 表明结果准确性较好且结果稳定。
2.3.2 标准物质的测定
本研究采用直接进样测汞法对7种国家有证标准物质(菠菜、茶叶、大米、黄豆、奶粉、三文鱼冻干粉、猪肝)进行检测, 验证方法的准确性、精密度及基质适用性, 结果如表3所示。
(1)准确性验证
植物性样品: 菠菜: 测定平均值(0.57 mg/kg)与认定值(0.567 mg/kg)偏差仅0.53%, 表明高汞植物基质的检测准确性优异, 可能得益于优化的热解程序(650 ℃梯度升温)减少有机质干扰。茶叶: 测定值(0.0086 mg/kg)在认定值范围内(0.007~0.009 mg/kg), 偏差7.5%, 符合痕量汞检测要求。黄豆: 测定平均值(0.0015 mg/kg)与认定值完全一致, 但RSD=3.8%, 可能与低汞含量(0.0015 mg/kg)及纤维基质导致的分布不均有关。
动物源性样品: 三文鱼冻干粉: 测定平均值(0.039 mg/kg)与认定值(0.039 mg/kg)一致, RSD=1.5%, 验证了均匀基质(冻干粉末)对高重复性的贡献。猪肝: 测定值(0.046 mg/kg)在认定值范围内(0.037~0.053 mg/kg), 但RSD=4.5%, 可能因是脂肪残留或蛋白质结合态汞的释放差异引起。
加工食品(奶粉): 测定平均值(0.0022 mg/kg)与认定值一致, RSD=4.4%, 表明加工过程中脂肪或添加剂的干扰可控。
(2)精密度分析
高均匀性基质: 菠菜(RSD=1.7%)、茶叶(RSD=1.3)、三文鱼冻干粉(RSD=1.5%)因基质均一性高, 重复性最优; 复杂基质样品: 大米(RSD=3.5%)和黄豆(RSD=3.8%)的波动性较高, 与植物纤维包裹及低汞含量相关; 奶粉(RSD=4.4%)、猪肝(RSD=4.5%)的波动较其它基质标准物质高, 但仍低于5%, 符合GB/T 27404—2008《实验室质量控制规范 食品理化检测》对高精度检测的要求(RSD≤5%)。
动物源性样品: 猪肝(RSD=4.5%)因脂肪含量(约5%)和汞结合态差异, 重复性略低于其他动物样品, 需优化均质工艺。
(3)基质效应与干扰
植物基质(菠菜、茶叶、黄豆): 纤维和有机质可能包裹汞, 需通过提高分解温度(如650 ℃)或延长热解时间以提升释放效率。动物基质(猪肝、三文鱼): 蛋白质和脂肪的均匀分布降低了检测波动, 但脂肪残留需通过梯度升温程序(200 ℃→500 ℃)避免碳化干扰。加工食品(奶粉): 乳脂可能包裹汞颗粒, 建议添加硝酸镁(0.5 g/g样品)作为助灰化剂, 促进脂肪氧化。
2.4 实际样品检测与污染评估
本研究选取14种食品样品(覆盖GB 2762—2022中所有汞限量中的食品类别), 采用直接进样测汞法进行检测, 结果如表4所示。以下从检出情况、污染水平、基质适用性3方面分析:
2.4.1 检出情况与污染水平
检出样品: 黄豆(0.00071 mg/kg)、鲜蘑菇(0.00068 mg/kg)、大米(0.0017 mg/kg)、鱼肉(0.0095 mg/kg)、茶叶(0.0086 mg/kg)中汞均被检出, 但含量远低于国家标准限值(如谷物限值0.02 mg/kg, 水产品限值0.1 mg/kg); 未检出样品: 矿泉水、牛奶、鸡蛋等9类样品中汞含量均低于方法检出限(LOD=0.0002 mg/kg), 表明其污染风险极低; 污染源分析: 谷物与豆类: 大米和黄豆中汞可能源于土壤污染或灌溉水渗透, 但当前含量(分别为限值的8.5%和3.5%)表明污染水平可控, 与《中国粮食质量安全发展报告(2022)》中低风险结论一致; 水产品: 鱼肉汞含量(0.0095 mg/kg)接近限值的10%, 可能与水生生物富集作用相关, 但显著低于深海鱼类(如金枪鱼通常为0.1~0.3 mg/kg)。
2.4.2 方法灵敏度与基质适用性
灵敏度: 9类样品未检出(LOD=0.0002 mg/kg), 验证方法对痕量汞的检测能力优于传统微波消解-ICP-MS法(LOD=0.001 mg/kg); 基质兼容性: 高水分样品(牛奶、黄桃罐头): 直接进样避免水分干扰; 高纤维样品(茶叶): 检测值(0.0086 mg/kg)与标准物质(茶叶GBW10016a)结果趋势一致, 表明方法对复杂基质的适应性。
14 类食品中汞含量均低于GB 2762—2022限值的10%。水产品(鱼肉, 0.0095 mg/kg)和谷物(大米, 0.0017 mg/kg)的污染水平与文献报道一致[11], 未检出样品(如牛奶)汞含量低于LOD, 表明当前食品中汞的安全风险可控。
3 结论
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本研究基于催化热解-金汞齐原子吸收原理, 开发了一种高效、环保的直接测汞法(DMA-80), 系统验证了其在食品总汞检测中的方法学性能与应用价值。方法成功构建0~10 ng与25~200 ng双线性校准曲线, 标准曲线相关系数均大于0.999, 方法LOD与LOQ分别为0.0002 mg/kg和0.0005 mg/kg, 标准物质的检测结果在指定范围内, 加标回收率为90%~116%, 日内与日间稳定性RSD分别小于等于6.5%和小于等于7.7%, 充分说明本研究中的直接进样测汞法测定食品中汞元素的可行性。14类食品样品中汞的检测含量均低于GB 2762—2022限量要求的10%。与传统测汞方法相比, 本方法无需化学消解即可完成样品前处理, 显著缩短检测周期, 且避免了汞的挥发损失; 突破了单一基质检测的局限性, 实现了多种复杂基质食品中总汞的快速检测, 为食品安全风险监测及监管提供了高效可靠的技术支撑。
基金
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  • 山西省卫生健康委科研课题项目(2021121)
文献
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参考文献 引证文献
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2025年第16卷第14期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250417002
  • 接收时间：2025-04-17
  • 首发时间：2026-01-07
  • 出版时间：2025-07-25
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  • 收稿日期：2025-04-17
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山西省卫生健康委科研课题项目(2021121)
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    山西省疾病预防控制中心, 太原 030032

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*杜兴(1985—), 女, 硕士, 副主任技师, 主要研究方向为卫生检验。E-mail:
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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