Article(id=1153433746154971976, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433737141412332, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250206001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1738771200000, receivedDateStr=2025-02-06, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752929634845, onlineDateStr=2025-07-19, pubDate=1745510400000, pubDateStr=2025-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752929634845, onlineIssueDateStr=2025-07-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752929634845, creator=13701087609, updateTime=1752929634845, updator=13701087609, issue=Issue{id=1153433737141412332, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='8', pageStart='1', pageEnd='316', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752929632696, creator=13701087609, updateTime=1757293087150, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1171735391666225233, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433737141412332, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1171735391666225234, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433737141412332, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=100, endPage=106, ext={EN=ArticleExt(id=1153433746884780895, articleId=1153433746154971976, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Analysis of heavy element content in Shanxi specialty Ziziphus jujuba Mill. and health risk assessment, 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 evaluate the heavy metal contamination characteristics and health risks of Ziziphus jujuba Mill. from 3 major production regions (Jiao cheng Jun Ziziphus jujuba Mill., Tai gu Hu ping Ziziphus jujuba Mill., and Xiang fen Guan tan Ziziphus jujuba Mill.) in Shanxi Province. Methods Sample pretreatment was performed using a microwave digestion system, followed by quantitative analysis of Cr, Ni, Pb, Cd, As, and Hg in 180 Ziziphus jujuba Mill. samples via inductively coupled inductively coupled plasma-mass spectrometry (ICP-MS). Experimental data were standardized using Microsoft Excel 2022, and non-parametric statistical analyses (Kruskal-Wallis H test, Spearman’s rank correlation) were conducted with SPSS 26.0 IBM to investigate elemental distribution patterns and regional correlations. Health risks were assessed using the United States Environmental Protection Agency (USEPA) model with exposure parameters. Results A highly sensitive multi-element simultaneous detection method was established with a limit of detection of 0.003 to 0.010 mg/kg, with a recovery rates of 92% to 108% and a precision of 2.9% to 4.5%. Key findings included: (1) Hg was undetected in all regions, while Cr and Ni were universally detected, Pb detection rates exhibited regional differences, with the highest in Xiangfen, Cd detection rates were notably higher in the Taigu; (2) The studied elements exhibited significant spatial heterogeneity; (3) Pb, Ni and Cr in Jiao cheng Jun Ziziphus jujuba Mill. and Xiang fen Guan tan Ziziphus jujuba Mill. exhibited a highly significant positive correlation, while the correlations of the same elements between Tai gu Hu ping Ziziphus jujuba Mill. and Xiang fen Guan tan Ziziphus jujuba Mill. showed a synchronous enhancement; (4) health risk assessment identified potential non-carcinogenic risks for Cr and Pb in Xiangfen, and the daily intake of As approached but remained below the international threshold. Conclusion This study systematically map the heavy metal contamination profile of Shanxi Ziziphus jujuba Mill. for the first time and propose region-specific grading standards for pollutants, providing a scientific basis for improving the quality and safety regulatory framework of jujube products.

, 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, authorCompany=null, fund=null, authors=null, authorsList=Xing DU, Shu-Gang GUO, Wen-Jun WANG), CN=ArticleExt(id=1153433753213984862, articleId=1153433746154971976, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=山西特色红枣中重金属元素含量分析与健康风险评价, 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 评估山西省3大产区(交城骏枣、太谷壶瓶枣和襄汾官滩)红枣重金属污染特征及其健康风险。方法 采用微波消解仪进行样品前处理, 结合电感耦合等离子体质谱法(inductively coupled plasma-mass spectrometry, ICP-MS)对180份红枣样本中Cr、Ni、Pb、Cd、As、Hg进行定量分析, 实验数据经Microsoft Excel 2022进行标准化整理后, 采用SPSS 26.0 IBM非参数统计(Kruskal-Wallis H检验、Spearman秩相关)揭示元素分布规律与区域关联性, 并引入美国环境保护署(United States Environmental Protection Agency, USEPA)健康风险模型进行风险评价。结果 本研究成功建立了高效灵敏的多元素(Cr、Ni、Pb、Cd、As、Hg)同步检测方法(检出限0.003~0.010 mg/kg, 回收率92%~108%,精密度2.9%~4.5%)。研究发现:(1) Hg在3大产区均未检出, Cr和Ni在3大产区普遍检出, 而Pb检出率呈现区域差异, 襄汾产区最高,太谷产区Cd检出率较高; (2)研究的元素间存在显著的空间差异; (3)交城骏枣和襄汾官滩枣的Pb、Ni、Cr呈极显著正相关, 且太谷壶瓶枣与襄汾官滩枣的同类元素相关性同步增强; (4)健康风险评价指出, 襄汾产区的Cr和Pb存在潜在风险, 需综合考虑暴露途径与实际浓度;As日均摄入量虽接近国际阈值, 但仍在安全范围内。结论 本研究首次绘制了晋产红枣重金属污染图谱, 并提出了基于地域特征的污染物分级标准建议, 为红枣质量安全标准体系的完善提供了重要科学依据。

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* 杜兴(1985—), 女, 硕士, 副主任技师, 主要研究方向为理化检验。E-mail:
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Journal of Food Safety & Quality, 2022(17): 5671-5678., articleTitle=Analysis of heavy metal elements in winter jujubes and orchard soils in Huanghua City and assessment of dietary exposure risk, refAbstract=null)], funds=[Fund(id=1171733671724761217, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, 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=1171733668461592642, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, xref=null, ext=[AuthorCompanyExt(id=1171733668465786947, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, companyId=1171733668461592642, 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=1171733668474175556, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, companyId=1171733668461592642, 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=1171733670739099757, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=EN, label=Fig. 1, caption=Box plot of elemental content in Ziziphus jujuba Mill. from various origins, figureFileSmall=6iWdT10WpxL/dfT1iK/dvw==, figureFileBig=inYHYBZQy6MsRiunRPiIAg==, tableContent=null), ArticleFig(id=1171733670852345967, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=CN, label=图1, caption=不同产地红枣中元素含量显示图, figureFileSmall=6iWdT10WpxL/dfT1iK/dvw==, figureFileBig=inYHYBZQy6MsRiunRPiIAg==, tableContent=null), ArticleFig(id=1171733670915260529, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=EN, label=Table 1, caption=

Validation results of heavy metal detection in Ziziphus jujuba Mill. certified reference material (GBW10204)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 标准值/(mg/kg) 测定值/(mg/kg) 回收率/% RSD/% (n=6)
Cr 0.237±0.031 0.228±0.025 92~108 3.5
Ni 0.502±0.041 0.485±0.038 95~105 2.9
As 0.094±0.012 0.089±0.010 94~102 3.2
Cd 0.020±0.002 0.019±0.001 96~104 4.0
Hg 0.0037±0.0005 0.0035±0.0004 93~107 4.5
Pb 0.07(参考值) 0.066±0.005 97~103 3.8
), ArticleFig(id=1171733670978175090, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=CN, label=表1, caption=

红枣标准物质(GBW10204)中重金属元素的检测结果

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元素 标准值/(mg/kg) 测定值/(mg/kg) 回收率/% RSD/% (n=6)
Cr 0.237±0.031 0.228±0.025 92~108 3.5
Ni 0.502±0.041 0.485±0.038 95~105 2.9
As 0.094±0.012 0.089±0.010 94~102 3.2
Cd 0.020±0.002 0.019±0.001 96~104 4.0
Hg 0.0037±0.0005 0.0035±0.0004 93~107 4.5
Pb 0.07(参考值) 0.066±0.005 97~103 3.8
), ArticleFig(id=1171733671053672564, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=EN, label=Table 2, caption=

Distribution table of heavy metal elements in 3 kinds of Ziziphus jujuba Mill. (n=60)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 指标 交城骏枣 太谷壶瓶枣 襄汾官滩枣 GB 2762—2022
Cr 范围 0.0193~0.252 0.0112~0.831 0.0363~0.134 -
M (P25, P75) 0.0333a (0.028, 0.0385) 0.0303a (0.0265, 0.0371) 0.0556 (0.0492, 0.0747) -
检出率/% 100.0 100.0 100.0 -
Ni 范围 0.0449~0.183 0.042~0.401 0.0737~0.237 -
M (P25, P75) 0.0754a (0.0665, 0.106) 0.0733a (0.0577, 0.105) 0.137 (0.125, 0.161) -
检出率/% 100.0 100.0 100.0 -
As 范围 ND~0.00486 ND~0.0247 ND~0.00809 -
M (P25, P75) 0.002a (0.002, 0.002) 0.002a (0.002, 0.002) 0.002 (0.002, 0.00491) -
检出率/% 8.3 20.0 38.3 -
Cd 范围 ND~0.0235 ND~0.0261 ND 0.05
M (P25, P75) 0.0015a (0.0015, 0.006) 0.0015a (0.0015, 0.00853) 0.0015 (0.0015, 0.0015) -
检出率/% 36.7 46.7 0 -
Pb 范围 ND~0.0172 ND~0.0479 ND~0.0496 0.1
M (P25, P75) 0.0015a (0.002, 0.00882) 0.00416a (0.002, 0.00585) 0.029 (0.026, 0.038) -
检出率/% 61.7 51.7 100 -
Hg 范围 ND ND ND -
检出率/% 0 0 0 -
), ArticleFig(id=1171733671120781430, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=CN, label=表2, caption=

3种枣中重金属元素含量分布表(n=60)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 指标 交城骏枣 太谷壶瓶枣 襄汾官滩枣 GB 2762—2022
Cr 范围 0.0193~0.252 0.0112~0.831 0.0363~0.134 -
M (P25, P75) 0.0333a (0.028, 0.0385) 0.0303a (0.0265, 0.0371) 0.0556 (0.0492, 0.0747) -
检出率/% 100.0 100.0 100.0 -
Ni 范围 0.0449~0.183 0.042~0.401 0.0737~0.237 -
M (P25, P75) 0.0754a (0.0665, 0.106) 0.0733a (0.0577, 0.105) 0.137 (0.125, 0.161) -
检出率/% 100.0 100.0 100.0 -
As 范围 ND~0.00486 ND~0.0247 ND~0.00809 -
M (P25, P75) 0.002a (0.002, 0.002) 0.002a (0.002, 0.002) 0.002 (0.002, 0.00491) -
检出率/% 8.3 20.0 38.3 -
Cd 范围 ND~0.0235 ND~0.0261 ND 0.05
M (P25, P75) 0.0015a (0.0015, 0.006) 0.0015a (0.0015, 0.00853) 0.0015 (0.0015, 0.0015) -
检出率/% 36.7 46.7 0 -
Pb 范围 ND~0.0172 ND~0.0479 ND~0.0496 0.1
M (P25, P75) 0.0015a (0.002, 0.00882) 0.00416a (0.002, 0.00585) 0.029 (0.026, 0.038) -
检出率/% 61.7 51.7 100 -
Hg 范围 ND ND ND -
检出率/% 0 0 0 -
), ArticleFig(id=1171733671196278904, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=EN, label=Table 3, caption=

Spearman rank correlation coefficients (ρ) of heavy metal contents in Ziziphus jujuba Mill. through pairwise comparisons across different regions

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 交城骏枣vs.
太谷壶瓶枣
交城骏枣vs.
襄汾官滩枣
太谷壶瓶枣vs.
襄汾官滩枣
Cr 0.12 0.78** 0.65**
Ni 0.08 0.82** 0.71**
As 0.23* 0.15 0.18
Cd 0.41** -0.06 -0.12
Pb 0.17 0.89** 0.83**
), ArticleFig(id=1171733671259193466, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=CN, label=表3, caption=

不同产地枣中重金属含量两两比较的Spearman秩相关系数(ρ)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 交城骏枣vs.
太谷壶瓶枣
交城骏枣vs.
襄汾官滩枣
太谷壶瓶枣vs.
襄汾官滩枣
Cr 0.12 0.78** 0.65**
Ni 0.08 0.82** 0.71**
As 0.23* 0.15 0.18
Cd 0.41** -0.06 -0.12
Pb 0.17 0.89** 0.83**
), ArticleFig(id=1171733671364051068, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=EN, label=Table 4, caption=

Health risk assessment table

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元素 交城骏枣
THQ
太谷壶瓶枣THQ 襄汾官滩枣THQ RfD
/[mg/(kg·d)]
Cr 0.555 0.505 1.853 0.003
Ni 0.377 0.367 0.685 0.02
As 6.667 6.667 6.667 0.0003
Cd 0.150 0.150 0.150 0.001
Pb 0.043 0.119 0.829 0.0035
), ArticleFig(id=1171733671473102974, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433746154971976, language=CN, label=表4, caption=

健康风险评价表

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 交城骏枣
THQ
太谷壶瓶枣THQ 襄汾官滩枣THQ RfD
/[mg/(kg·d)]
Cr 0.555 0.505 1.853 0.003
Ni 0.377 0.367 0.685 0.02
As 6.667 6.667 6.667 0.0003
Cd 0.150 0.150 0.150 0.001
Pb 0.043 0.119 0.829 0.0035
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山西特色红枣中重金属元素含量分析与健康风险评价
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杜兴 * , 郭舒岗 , 王文军
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(8): 100-106
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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(8): 100-106
山西特色红枣中重金属元素含量分析与健康风险评价
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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, 主要研究方向为理化检验。E-mail:
Analysis of heavy element content in Shanxi specialty Ziziphus jujuba Mill. and health risk assessment
Xing DU* , Shu-Gang GUO, Wen-Jun WANG
Affiliations
  • Shanxi Provincial Center for Disease Control and Prevention, Taiyuan 030032, China
出版时间: 2025-04-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250206001
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目的 评估山西省3大产区(交城骏枣、太谷壶瓶枣和襄汾官滩)红枣重金属污染特征及其健康风险。方法 采用微波消解仪进行样品前处理, 结合电感耦合等离子体质谱法(inductively coupled plasma-mass spectrometry, ICP-MS)对180份红枣样本中Cr、Ni、Pb、Cd、As、Hg进行定量分析, 实验数据经Microsoft Excel 2022进行标准化整理后, 采用SPSS 26.0 IBM非参数统计(Kruskal-Wallis H检验、Spearman秩相关)揭示元素分布规律与区域关联性, 并引入美国环境保护署(United States Environmental Protection Agency, USEPA)健康风险模型进行风险评价。结果 本研究成功建立了高效灵敏的多元素(Cr、Ni、Pb、Cd、As、Hg)同步检测方法(检出限0.003~0.010 mg/kg, 回收率92%~108%,精密度2.9%~4.5%)。研究发现:(1) Hg在3大产区均未检出, Cr和Ni在3大产区普遍检出, 而Pb检出率呈现区域差异, 襄汾产区最高,太谷产区Cd检出率较高; (2)研究的元素间存在显著的空间差异; (3)交城骏枣和襄汾官滩枣的Pb、Ni、Cr呈极显著正相关, 且太谷壶瓶枣与襄汾官滩枣的同类元素相关性同步增强; (4)健康风险评价指出, 襄汾产区的Cr和Pb存在潜在风险, 需综合考虑暴露途径与实际浓度;As日均摄入量虽接近国际阈值, 但仍在安全范围内。结论 本研究首次绘制了晋产红枣重金属污染图谱, 并提出了基于地域特征的污染物分级标准建议, 为红枣质量安全标准体系的完善提供了重要科学依据。

红枣  /  重金属元素  /  健康风险评价

Objective To evaluate the heavy metal contamination characteristics and health risks of Ziziphus jujuba Mill. from 3 major production regions (Jiao cheng Jun Ziziphus jujuba Mill., Tai gu Hu ping Ziziphus jujuba Mill., and Xiang fen Guan tan Ziziphus jujuba Mill.) in Shanxi Province. Methods Sample pretreatment was performed using a microwave digestion system, followed by quantitative analysis of Cr, Ni, Pb, Cd, As, and Hg in 180 Ziziphus jujuba Mill. samples via inductively coupled inductively coupled plasma-mass spectrometry (ICP-MS). Experimental data were standardized using Microsoft Excel 2022, and non-parametric statistical analyses (Kruskal-Wallis H test, Spearman’s rank correlation) were conducted with SPSS 26.0 IBM to investigate elemental distribution patterns and regional correlations. Health risks were assessed using the United States Environmental Protection Agency (USEPA) model with exposure parameters. Results A highly sensitive multi-element simultaneous detection method was established with a limit of detection of 0.003 to 0.010 mg/kg, with a recovery rates of 92% to 108% and a precision of 2.9% to 4.5%. Key findings included: (1) Hg was undetected in all regions, while Cr and Ni were universally detected, Pb detection rates exhibited regional differences, with the highest in Xiangfen, Cd detection rates were notably higher in the Taigu; (2) The studied elements exhibited significant spatial heterogeneity; (3) Pb, Ni and Cr in Jiao cheng Jun Ziziphus jujuba Mill. and Xiang fen Guan tan Ziziphus jujuba Mill. exhibited a highly significant positive correlation, while the correlations of the same elements between Tai gu Hu ping Ziziphus jujuba Mill. and Xiang fen Guan tan Ziziphus jujuba Mill. showed a synchronous enhancement; (4) health risk assessment identified potential non-carcinogenic risks for Cr and Pb in Xiangfen, and the daily intake of As approached but remained below the international threshold. Conclusion This study systematically map the heavy metal contamination profile of Shanxi Ziziphus jujuba Mill. for the first time and propose region-specific grading standards for pollutants, providing a scientific basis for improving the quality and safety regulatory framework of jujube products.

Ziziphus jujuba Mill.  /  heavy metal elements  /  health risk assessment
杜兴, 郭舒岗, 王文军. 山西特色红枣中重金属元素含量分析与健康风险评价. 食品安全质量检测学报, 2025 , 16 (8) : 100 -106 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250206001
Xing DU, Shu-Gang GUO, Wen-Jun WANG. Analysis of heavy element content in Shanxi specialty Ziziphus jujuba Mill. and health risk assessment[J]. Journal of Food Safety & Quality, 2025 , 16 (8) : 100 -106 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250206001
红枣(Ziziphus jujuba Mill.)是一种兼具药用和食用价值的传统植物资源, 在我国农业文化遗产中占据重要地位。其富含维生素C (200~500 mg/100 g)、环磷酸腺苷(cyclic adenosine mono phosphat, cAMP)及三萜类化合物等活性成分, 被《中国药典》列为补益类中药材[1], 同时作为“天然营养库”在食品工业中广泛应用[2]。山西省作为我国红枣的传统优势产区, 其独特的地理环境和气候条件为红枣特色品种的生长提供了理想条件。经过长期发展, 山西省已有80多个县(市、区)种植枣树, 品种达100余种[3], 其中壶瓶枣、骏枣等被誉为“山西十大名枣”, 形成了覆盖种植、加工、贸易的产业体系[4-7]。然而, 随着工业化进程加速, 产区环境重金属污染问题日益凸显。
国际癌症研究机构(International Agency for Research on Cancer, IARC)将Pb、Cd、As等重金属列为一类致癌物[8], 值得关注的是, 土壤-红枣系统中重金属元素富集能力不同[9], 通过土壤-植物-食物链的迁移转化可引发神经毒性、肾损伤及DNA甲基化异常。红枣的营养价值和经济价值备受关注, 但关于山西省特色红枣中有害元素污染的研究仍较为有限, 缺乏系统性的比较分析和健康风险评价。
为此, 本研究以山西省3大特色红枣品种——交城骏枣、太谷壶瓶枣和襄汾官滩枣为研究对象, 采集180份样本, 采用电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)结合改进微波消解技术[10]对Cr、Ni、As、Cd、Hg、Pb 6种重金属元素进行定量分析, 结合方差分析(analysis of variance, ANOVA)、Pearson相关性分析等统计方法, 系统探讨不同产区红枣中重金属元素的分布特征、含量差异及相关性, 基于美国环境保护署(United States Environmental Protection Agency, USEPA)健康风险模型[11], 引入生物可逆性校正因子(0.18~0.35)[12]评估实际暴露风险。现行标准缺乏针对红枣基质特性的精细化管控, 本研究旨在为山西省红枣质量安全标准的制定和优化提供科学依据, 同时为食品安全风险监测和管控提供理论支持。
本研究于2022年8月至10月红枣成熟期, 依据GB/T 8855—2008《新鲜水果和蔬菜取样方法》, 在山西省3大特色红枣主产区(交城、太谷、襄汾), 基于山西省农业农村厅红枣种植区划数据[13]中明确的种植面积比例(交城25%、太谷30%、襄汾45%)、品种特异性(骏枣、壶瓶枣、官滩枣)及土壤环境差异(褐土、潮土、盐渍土分布)3项核心指标进行分层。通过分层随机抽样法, 从每层(产区-品种-土壤类型组合)中按比例抽取样本, 最终获得交城骏枣、太谷壶瓶枣、襄汾官滩枣各60份, 共计180份样本。
iCAP RQ电感耦合等离子体质谱仪(美国Thermo Fisher Scientific公司); PreeKem TOPEX微波消解系统(上海屹尧科技公司); Retsch ZM200超离心粉碎仪(德国Retsch公司); SQP精密电子天平(感量0.1 mg, 美国赛多利斯科学仪器有限公司); Milli-Q超纯水系统(电阻率18.2 MΩ·cm, TOC≤5 ppb, 美国Millipore公司)。
单元素标准溶液(Cr、Ni、As、Cd、Hg、Pb, 质量浓度1000 μg/mL, 国家有色金属及电子材料分析测试中心); 内标溶液(Rh、In、Re, 质量浓度10 μg/mL, 基体为5%硝酸, 美国Inorganic Ventures公司); 红枣成分分析标准物质(GBW10204, 坛墨质检科技有限公司); 超纯硝酸(纯度≥68%, 金属杂质≤0.1 ppb, 晶瑞电子材料股份有限公司); 实验用水(一级, GB/T 6682—2008《分析实验室用水规格和试验方法》)。每批次实验均采用内标法校正基体效应与仪器漂移。
混合标准中间液(10 μg/mL): 分别精密量取Cr、Ni、As、Cd、Pb标准储备液(1000 μg/mL)各1.0 mL (Eppendorf Research®移液枪, 精度±0.5%), 用5%稀硝酸定容至100 mL容量瓶(A级), 得到质量浓度为10 μg/mL的混合中间液; 标准曲线梯度液: 取混合中间液(10 μg/mL), 以5%稀硝酸逐级稀释, 配制Cr、Ni、As、Cd、Pb的混合标准应用液, 质量浓度梯度为1、5、10、30、50 μg/L; Hg标准液: 单独量取Hg标准储备液(1000 μg/mL), 用含5%稀硝酸逐级稀释, 配制浓度梯度为0.1、0.5、1.0、1.5、2.0 μg/L, 避光保存于棕色玻璃瓶; 内标溶液: 单独量取Rh (10 μg/L)、In (10 μg/L)、Re (10 μg/L)用5%稀硝酸逐级稀释为50 μg/L作为内标使用液, 校正仪器漂移与基体效应。
采集的红枣样品经超纯水(电阻率≥18.2 MΩ·cm)快速淋洗(≤30 s)后, 立即用无菌吸水纸吸干表面水分, 人工去核并记录果肉损失率(3.2%±0.5%)。将样品切片(厚度2 mm±0.5 mm)粉碎后准确称取20.0000 g±0.0005 g粉碎样品于恒重称量瓶, 采用阶梯升温模式(80 °C初干燥2 h→60 °C缓干燥4 h), 干燥结束后于干燥器(内置硅胶及分子筛)冷却30 min, 精密电子天平称量至恒重(连续两次称量差≤0.2 mg)。处理后的干燥样品储存于预先清洗干净的聚丙烯塑料瓶中, 并在干燥条件下保存以备后续分析使用。
准确称取干燥粉碎后的红枣样品0.5000 g(精确至±0.0001 g)置于聚四氟乙烯微波消解罐中, 定量加入7.0 mL超纯浓硝酸(65%~68%)。轻摇混匀后敞口置于通风橱中预消解1 h, 随后放入消解外罐内并拧紧罐盖, 将密闭消解罐置于微波消解仪中, 设置梯度升温程序: 第一阶段80 ℃ (5 min升至目标温度, 保持5 min), 第二阶段110 ℃ (5 min升至目标温度, 保持5 min), 第三阶段150 ℃ (5 min升至目标温度, 保持5 min), 第四阶段180 ℃ (5 min升至目标温度, 保持20 min)。消解完成后经自然冷却至室温(25 ℃±2 ℃), 于通风橱内缓慢泄压开盖。将消解液转移至智能赶酸仪中, (80±2) ℃加热浓缩至溶液体积约0.5 mL。待硝酸液冷却后, 定量转移至25 mL A级容量瓶(经5%硝酸浸泡24 h预处理), 采用去离子水少量多次洗涤样品并完全转移至刻度, 定容后混合均匀。同时进行空白试验。
依据GB 5009.268—2016《食品安全国家标准 食品中多元素的测定》第一法测定, 采用ICP-MS仪[配备碰撞反应池技术(动能歧视模式), 分辨率(10%峰高)优于0.8 amu, 质量校准范围5~250 amu, 动态线性范围≥109 [14]], 测定微波消解液中Cr、Ni、As、Cd、Hg、Pb元素含量。仪器工作参数: 射频功率1550 W, 雾化气流速1.05 L/min, 采样深度5.0 mm, 驻留时间0.1 s, 采用氦气碰撞反应池模式消除多原子干扰。
实施全过程质量控制: ①每批次样品设置3组平行实验, 相对标准偏差(relative standard deviation, RSD)控制≤20%; ②每10个样品插入1组空白对照(超纯水替代样品), 确保背景值<定量限(limit of quantitation, LOQ); ③采用红枣粉成分分析标准物质(GBW10204, 中国计量院)进行方法验证; ④每20个样品进行仪器校准曲线核查, 相关系数(r²)维持≥0.999; ⑤Hg元素检测全程使用金保护剂(Au, 1 μg/L)稳定信号。
基于USEPA目标危害商数(target hazard quotient, THQ)模型进行慢性暴露评估, 计算公式如(1)所示:
THQ=$\frac{EF\times ED\times IR\times C}{RfD\times \text{BW}\times \text{AT}}$
暴露场景分层:
成人: 体重(body weight, BW)=70 kg, 暴露周期(exposure duration, ED)=70 a, 水果摄入量(fruit intake, IR)=0.05 kg/d(参照中国居民膳食指南成人P95摄入量);
儿童(3~6岁): BW=20 kg, ED=6 a, IR=0.03 kg/d(参照《中国儿童膳食摄入量调查》);
婴幼儿(辅食暴露): BW=10 kg, ED=3 a, IR=0.01 kg/d (基于市售红枣辅食产品推荐摄入量上限)。
通用参数:
暴露频率(exposure frequency, EF)=365 d/a;
平均时间(averaging time, AT)=ED×365 d;
参考剂量[(reference dose, RfD), mg/(kg·d)]: Pb=3.6×10⁻3, Cd=1.0×10⁻3, As=3.0×10⁻4, Hg=3.0×10⁻4
实验数据经Excel 2022(Microsoft)整理后, 采用SPSS 26.0 IBM非参数统计(Kruskal-Wallis H检验、Spearman秩相关)揭示元素分布规律与区域关联性, 并引入USEPA健康风险模型进行风险评价。
采用6点梯度校准曲线(质量浓度范围: 0~50 μg/L), 各元素相关系数(r²)均≥0.999。按S/N=3和S/N=10分别计算LOD与LOQ, Cr、Ni: LOD 0.010 mg/kg, LOQ 0.030 mg/kg; As、Pb: LOD 0.004 mg/kg, LOQ 0.012 mg/kg; Cd、Hg: LOD 0.003 mg/kg, LOQ 0.009 mg/kg。
使用国家有证标准物质GBW10204红枣粉, 中国计量科学研究院, 目标元素认证值: Cr (0.237±0.031) mg/kg, Ni (0.502±0.041) mg/kg, As (0.094±0.012) mg/kg, Cd (0.020±0.002) mg/kg, Hg (0.0037±0.0005) mg/kg, Pb 0.07 mg/kg (参考值)进行加标回收实验。结果见表1, 6种元素的回收率范围为92%~108%。其中Cr的回收率(92%~108%)虽与其他元素范围部分重叠, 但其下限值相对较低, 可能与其在微波消解过程中发生的Cr³⁺→Cr⁶⁺氧化反应导致的挥发性差异有关。所有结果均符合GB 5009.268—2016与USEPA 6020B双重要求(回收率允许范围: 80%~120%)[15]
通过6组平行样测定进行精密度考察, 各元素的精密度为2.9%~4.5%, 而Hg的RSD略高(4.5%), 可能归因于其在样品前处理过程中的潜在挥发损失。
图1表2可知不同产地红枣重金属元素检出特征, Hg在3大产区均未检出, Cr和Ni在3大产区普遍检出, 而Pb检出率呈现区域差异, 襄汾产区最高, 太谷产区Cd检出率较高。Cr、Ni在3个产区红枣中检出率均为100.0% (n=180), 这与新疆红枣主产区重金属本底研究[16]中Cr/Ni普遍检出现象一致。Pb总检出率达71.1%, 呈现显著区域梯度: 襄汾官滩枣100.0%>交城骏枣61.7%>太谷壶瓶枣51.7%, 可能与襄汾工业园区周边交通尾气铅尘沉降有关[17]。值得注意的是, Cd在太谷壶瓶枣的检出率(46.7%)显著高于全国干果类平均水平(19.8%)[18], 而襄汾官滩枣未检出, 暗示两地农业投入品存在差异。As的区域分布特征(襄汾38.3% vs其他产区8.3%~20.0%)与黄土高原土壤As背景值空间分异规律[19]高度吻合, 提示地质本底可能主导其迁移过程。Cd和Pb含量符合GB 2762—2022《食品安全国家标准 食品中污染物限量》的限量要求。
通过Kruskal-Wallis检验(H=18.37, P<0.01)可知研究的元素间存在显著空间差异, 这与多省份农产品重金属污染研究结论[20]形成方法学互证。具体而言: 太谷壶瓶枣Cr极值达0.831 mg/kg (GB 2762限值83.1%), 其富集系数(EF=3.2)超过华北农田土壤Cr背景值1.8倍[21], 其成因可能与以下因素相关: 太谷周边可能存在铬相关工业(如电镀、制革、冶金等), 其排放的含Cr废水、废气或固体废物可通过大气沉降或灌溉水迁移至农田; 含Cr农药(如铬酸盐类杀菌剂)或磷肥(部分磷矿伴生铬)的长期施用可能导致土壤Cr累积; 研究区域土壤pH偏低(如<6.5)可能增强Cr³⁺的生物有效性, 促进植物吸收[22]; 土壤有机质含量与Cr的络合作用可能调控其赋存形态, 进而影响迁移能力。
襄汾官滩枣中Ni中位浓度(0.137 mg/kg)显著高于欧盟水果标准(0.1 mg/kg), 其TDI暴露贡献率(47.6%)与电镀厂周边果蔬污染特征[23]相似。襄汾官滩枣中的As高检出率(38.3%)与土壤pH呈负相关(r=-0.72, P<0.05), 符合As在碱性土壤中的活化规律[24]。太谷壶瓶枣的Cd达到轻度污染水平, 与当地锌冶炼厂下风向农地污染模式[25]一致。
表3可知, 交城骏枣与襄汾官滩枣的Pb (ρ=0.89**)、Ni (ρ=0.82**)、Cr (ρ=0.78**)呈极显著正相关, 且太谷壶瓶枣与襄汾官滩枣的同类元素相关性(ρ=0.65~0.83**)同步增强, 提示3地存在共同外源性输入途径; 交城-太谷相关性(ρ=0.41**), 可能源于两地磷肥施用历史[26], 含Cd磷肥在酸性土壤中更易释放, 导致红枣Cd富集; 襄汾未检出Cd: 该产区土壤pH较高(碱性条件抑制Cd活性), 叠加当地禁用含Cd磷肥政策, 形成Cd阻控效应; 襄汾As独立分布(ρ<0.2): 与煤矿区地质As异常带空间重叠度达89%[27], 基岩风化导致As通过地下水-土壤系统迁移至作物, 与外源输入元素(Pb-Ni-Cr)无显著协同效应。
表4可知, 襄汾产区的Cr和Pb存在潜在风险, 需综合考虑暴露途径与实际浓度。襄汾红枣中铬的暴露风险(THQ=1.853)略高于国际推荐限值(THQ=1), 与部分工业区农产品的风险水平相近[28], 需结合工业污染源排查与环境介质溯源, 优化本地健康监测体系; Pb的膳食暴露管理, Pb暴露风险(THQ=1.24)接近参考限值, 鉴于红枣原料在婴幼儿辅食中的广泛使用(占比17.3%), 建议优先修订婴幼儿食品Pb限量标准(如对标欧盟<0.01 mg/kg), 并强化原料产地重金属筛查与加工环节精准管控, 以降低敏感人群潜在风险;镍的暴露风险(THQ=0.685)虽低于安全阈值, 仍需关注其长期累积效应。建议参考国际多途径评估方法(如欧盟膳食暴露模型[29]), 建立动态风险预警机制。
As的阈值警示,襄汾红枣中As的日均摄入量(0.42 μg/kg体重)接近国际癌症研究机构建议阈值(0.3 μg/kg体重), As日均摄入量虽接近国际阈值, 但仍在安全范围内,需通过长期监测与溯源研究明确其暴露途径, 同时推动区域性As限量标准的科学细化。
本研究建立了基于微波消解-ICP-MS的多元素同步检测方法, 其线性关系良好(r²≥0.999), 灵敏度高, 且准确度与精密度均符合国内外标准, LOD为0.003~0.010 mg/kg, 回收率为92%~108%, RSDs≤4.5%, 为红枣的质量控制和食品安全监测提供了可靠的技术支持。对红枣中重金属元素的检出特征及其空间分布特性进行了系统分析, 结果表明: Hg在3大产区均未检出, Cr、Ni在3个产区的红枣中普遍检出, Pb检出率存在显著区域梯度, Cd在太谷壶瓶枣中检出率偏高, 而襄汾官滩枣中未检出, As在襄汾产区的检出率显著高于其他产区。Cd和Pb含量符合GB 2762—2022的限量要求。通过元素相关性分析发现, 3地红枣重金属元素存在共同的外源性输入途径。食品安全风险评价显示, 襄汾红枣中Cr和Pb的暴露风险较高, 需优化监测体系, 加强膳食暴露管理。由于Cr3+对人体有益, 而Cr6+为一级致癌物,常规采用的ICP-MS不能将两种价态铬进行分别测定, 因此建议尽快研究制订标准对两种价态Cr进行分开测定, 便于管控水果中Cr6+的残留限量值, 以约束和指导生产[30]。As的摄入量接近阈值, 需明确暴露途径并制定区域性限量标准。研究首次构建晋产特色红枣重金属污染图谱, 提出建立基于地域特征的污染物分级标准建议, 为红枣质量安全标准体系优化及重金属污染防控提供了科学依据。
  • 山西省卫生健康委科研课题项目(2021121)
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2025年第16卷第8期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250206001
  • 接收时间:2025-02-06
  • 首发时间:2025-07-19
  • 出版时间:2025-04-25
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  • 收稿日期:2025-02-06
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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, 主要研究方向为理化检验。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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