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Article(id=1217781122306593149, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1217779717386715826, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250217004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1739721600000, receivedDateStr=2025-02-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1768271244837, onlineDateStr=2026-01-13, pubDate=1750780800000, pubDateStr=2025-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1768271244837, onlineIssueDateStr=2026-01-13, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1768271244837, creator=13701087609, updateTime=1768271244837, updator=13701087609, issue=Issue{id=1217779717386715826, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='12', pageStart='1', pageEnd='320', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1768270909877, creator=13701087609, updateTime=1768299620707, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1217900139386163208, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1217779717386715826, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1217900139386163209, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1217779717386715826, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=192, endPage=197, ext={EN=ArticleExt(id=1217781122726023565, articleId=1217781122306593149, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Determination of 26 kinds of elements content in liquor by matrix matching-inductively coupled plasma mass spectrometry, columnId=1151895321388347923, journalTitle=Journal of Food Safety & Quality, columnName=Food Analysis and Detection, runingTitle=null, highlight=null, articleAbstract=

Objective To establish a method for rapid determination of 26 kinds of elements in liquor by inductively coupled plasma mass spectrometry (ICP-MS) adopting matrix matching. Methods Combining with kinetic energy discrimination (KED) and internal standard correction mode, the determination method of Cd, Sn, Ba, Pb, Li, B, Mg, Al, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Rb, Sr, Mo, Sb, Na, Se and Hg in liquor had been established though direct dilution injection, and compared with the standard test method. Results The results showed that the correlation coefficient of standard curve was 0.9990-0.9999, the limit of determination was 0.1-300.0 μg/L, the standard recovery rates were 94.5%-104.4%, the relative standard deviations (RSDs) were 0.1%-1.2%. The standard recovery rate was obviously better than that without matrix matching method. The performance parameters of the method met the requirements of GB 5009.295—2023 National food safety standards-General rules for verification of chemical analysis methods. Compared with the standard test method, it could effectively reduce the pre-treatment steps, shorten the pre-treatment time, and save consumables. The results of the 2 kinds of methods showed no significant difference. Conclusion The method is simple, fast, accurate, stable and reliable, and is suitable for the bulk detection of multielement in liquor. The method provides technical support for ensuring liquor quality and safety.

, correspAuthors=Yu QIAN, 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=Wei-Bing DONG, Yu QIAN), CN=ArticleExt(id=1217781123187397038, articleId=1217781122306593149, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=基体匹配-电感耦合等离子体质谱法测定白酒中26种元素含量, 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 利用基体匹配, 建立电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)快速测定白酒中26种元素的方法。方法 结合动能歧视(kinetic energy discrimination, KED)模式, 采用内标法测定白酒中Cd、Sn、Ba、Pb、Li、B、Mg、Al、K、Ca、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Rb、Sr、Mo、Sb、Na、Se和Hg等26种元素含量, 并且与标准检验方法进行比较。结果 该方法相关系数为0.9990~0.9999, 检出限为0.1~300.0 μg/L, 加标回收率为94.5%~104.4%, 相对标准偏差(relative standard deviations, RSDs)为0.1%~1.2%。加标回收率明显优于未进行基体匹配测定方法, 方法性能参数均符合GB 5009.295—2023《食品安全国家标准 化学分析方法验证通则》要求。与标准检验方法比较, 能有效减少前处理步骤、缩短前处理时间、节约耗材, 二者测定结果无显著差异。结论 该方法简便易行、快捷准确、稳定可靠, 适用于批量白酒中多元素检测, 为保障白酒质量安全提供技术支持。

, correspAuthors=钱宇, authorNote=null, correspAuthorsNote=
*钱宇(1988—), 男, 博士, 讲师, 主要研究方向为分析化学, 白酒风味组学。E-mail:
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董维兵(1979—), 男, 硕士, 副主任技师, 主要研究方向为食品检验。E-mail:

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董维兵(1979—), 男, 硕士, 副主任技师, 主要研究方向为食品检验。E-mail:

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Food and Fermentation Industries, 2020, 46(3): 257-263., articleTitle=Principal component analysis and cluster analysis of inorganic elements in Baijiu using inductively coupled plasma tandem mass spectrometry, refAbstract=null), Reference(id=1217833934726025772, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, doi=null, pmid=null, pmcid=null, year=2020, volume=11, issue=15, pageStart=5232, pageEnd=5237, url=null, language=null, rfNumber=[27], rfOrder=46, authorNames=王志洪, 廖唯棱, 马立超, journalName=食品安全质量检测学报, refType=null, unstructuredReference=王志洪, 廖唯棱, 马立超. 电感耦合等离子体质谱法同时测定白酒中18种金属元素[J]. 食品安全质量检测学报, 2020, 11(15): 5232-5237., articleTitle=电感耦合等离子体质谱法同时测定白酒中18种金属元素, refAbstract=null), Reference(id=1217833934818300466, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, doi=null, pmid=null, pmcid=null, year=2020, volume=11, issue=15, pageStart=5232, pageEnd=5237, url=null, language=null, rfNumber=[27], rfOrder=47, authorNames=WANG ZH, LIAO WL, MA LC, journalName=Journal of Food Safety & Quality, refType=null, unstructuredReference=WANG ZH, LIAO WL, MA LC. Simultaneous determination of 18 kinds of mental elements in Chinese baijiu by inductively coupled plasma mass spectrometry[J]. Journal of Food Safety & Quality, 2020, 11(15): 5232-5237., articleTitle=Simultaneous determination of 18 kinds of mental elements in Chinese baijiu by inductively coupled plasma mass spectrometry, refAbstract=null), Reference(id=1217833936122729018, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, doi=null, pmid=null, pmcid=null, year=2021, volume=null, issue=134, pageStart=116068, pageEnd=null, url=null, language=null, rfNumber=[28], rfOrder=48, authorNames=RAPOSO F, BARCELÓ D, journalName=TrAC: Trends in Analytical Chemistry, refType=null, unstructuredReference=RAPOSO F, BARCELÓ D. Challenges and strategies of matrix effects using chromatography-mass spectrometry: An overview from research versus regulatory viewpoints[J]. TrAC: Trends in Analytical Chemistry, 2021(134): 116068., articleTitle=Challenges and strategies of matrix effects using chromatography-mass spectrometry: An overview from research versus regulatory viewpoints, refAbstract=null), Reference(id=1217833936252752448, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, doi=null, pmid=null, pmcid=null, year=1987, volume=41, issue=5, pageStart=801, pageEnd=806, url=null, language=null, rfNumber=[29], rfOrder=49, authorNames=THOMPSON JJ, journalName=Applied Spectroscopy, refType=null, unstructuredReference=THOMPSON JJ. A study of internal standardization in inductively coupled plasma-mass spectrometry[J]. Applied Spectroscopy, 1987, 41(5): 801-806., articleTitle=A study of internal standardization in inductively coupled plasma-mass spectrometry, refAbstract=null), Reference(id=1217833936428913224, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, doi=null, pmid=null, pmcid=null, year=2020, volume=11, issue=4, pageStart=1197, pageEnd=1201, url=null, language=null, rfNumber=[30], rfOrder=50, authorNames=陈璐, 邓立刚, 丁敏, journalName=食品安全质量检测学报, refType=null, unstructuredReference=陈璐, 邓立刚, 丁敏, 等. 电感耦合等离子体质谱法测定白酒中铅的前处理方法[J]. 食品安全质量检测学报, 2020, 11(4): 1197-1201., articleTitle=电感耦合等离子体质谱法测定白酒中铅的前处理方法, refAbstract=null), Reference(id=1217833936630239820, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, doi=null, pmid=null, pmcid=null, year=2020, volume=11, issue=4, pageStart=1197, pageEnd=1201, url=null, language=null, rfNumber=[30], rfOrder=51, authorNames=CHEN L, DENG LG, DING M, journalName=Journal of Food Safety & Quality, refType=null, unstructuredReference=CHEN L, DENG LG, DING M, et al. 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Journal of Food Safety & Quality, 2020, 11(4): 1197-1201., articleTitle=Pretreatment method for determination of lead in liquor by inductively coupled plasma mass spectrometry, refAbstract=null)], funds=[Fund(id=1217833927423742039, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, awardId=2019YJ0698, language=CN, fundingSource=四川省自然科学基金项目(2019YJ0698), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1217833921102926574, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, xref=1, ext=[AuthorCompanyExt(id=1217833921111315183, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, companyId=1217833921102926574, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Xindu District Center for Disease Control and Prevention, Chengdu 610500, China), AuthorCompanyExt(id=1217833921115509489, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, companyId=1217833921102926574, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 成都市新都区疾病预防控制中心, 成都 610500)]), AuthorCompany(id=1217833921220367098, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, xref=2, ext=[AuthorCompanyExt(id=1217833921228755707, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, companyId=1217833921220367098, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 School of Chemical Engineering, Sichuan University of Science & Engineering, Zigong 643000, China), AuthorCompanyExt(id=1217833921237144317, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, companyId=1217833921220367098, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 四川轻化工大学化学工程学院, 自贡 643000)])], figs=[ArticleFig(id=1217833924605170636, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=EN, label=Table 1, caption=

Mass concentration of standard series solution

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 分析元素 标准溶液质量浓度
S0 S1 S2 S3 S4 S5 S6
标准系列一 Na*、K*、Ca*、Mg*、Fe* 0 0.5 1.0 5.0 10.0 20.0 50.0
标准系列二 Li、B、Al、Mn、Cu、Zn、Sr、Ba、Sn、Rb 0 5.0 10.0 50.0 100.0 200.0 500.0
V、Cr、Co、Ni、As、Se、Mo、Cd、Sb、Pb 0 0.5 1.0 5.0 10.0 20.0 50.0
标准系列三 Hg 0 0.1 0.2 0.5 1.0 1.5 2.0
), ArticleFig(id=1217833924718416856, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=CN, label=表1, caption=

标准系列溶液质量浓度

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 分析元素 标准溶液质量浓度
S0 S1 S2 S3 S4 S5 S6
标准系列一 Na*、K*、Ca*、Mg*、Fe* 0 0.5 1.0 5.0 10.0 20.0 50.0
标准系列二 Li、B、Al、Mn、Cu、Zn、Sr、Ba、Sn、Rb 0 5.0 10.0 50.0 100.0 200.0 500.0
V、Cr、Co、Ni、As、Se、Mo、Cd、Sb、Pb 0 0.5 1.0 5.0 10.0 20.0 50.0
标准系列三 Hg 0 0.1 0.2 0.5 1.0 1.5 2.0
), ArticleFig(id=1217833924856828898, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=EN, label=Table 2, caption=

Conditions of ICP-MS

, figureFileSmall=null, figureFileBig=null, tableContent=
参数名称 参数值 参数名称 参数值
射频功率/W 1300 等离子体气流速/(L/min) 18
辅助器流速/(L/min) 1.2 样品提升速度/(r/min) 20
雾化器 同心雾化器 雾化器流量/(L/min) 0.87
采样锥/截取锥 镍锥 采集模式 跳峰
重复次数 3 氦气流速/(mL/min) 3.5
), ArticleFig(id=1217833924991046634, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=CN, label=表2, caption=

ICP-MS仪器条件

, figureFileSmall=null, figureFileBig=null, tableContent=
参数名称 参数值 参数名称 参数值
射频功率/W 1300 等离子体气流速/(L/min) 18
辅助器流速/(L/min) 1.2 样品提升速度/(r/min) 20
雾化器 同心雾化器 雾化器流量/(L/min) 0.87
采样锥/截取锥 镍锥 采集模式 跳峰
重复次数 3 氦气流速/(mL/min) 3.5
), ArticleFig(id=1217833925116875767, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=EN, label=Table 3, caption=

Comparison of recovery rates of 26 kinds of elements by water and alcohol standards (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 加标回收率 元素 加标回收率
水标 醇标 水标 醇标
Na 92.8 95.9 Sn 85.4 99.5
K 93.2 98.8 Rb 95.2 99.5
Ca 92.2 97.9 V 104.9 101.3
Mg 81.9 99.8 Cr 98.6 100.4
Fe 101.4 101.0 Co 110.4 104.4
Li 86.2 100.6 Ni 115.6 103.4
B 162.7 102.6 As 399.6 100.1
Al 90.5 94.6 Se 324.1 99.5
Mn 110.4 101.2 Mo 100.4 101.4
Cu 94.9 97.9 Cd 87.0 102.2
Zn 112.1 97.3 Sb 136.9 100.4
Sr 86.1 99.0 Pb 82.3 102.1
Ba 90.3 101.1 Hg 89.8 94.5
), ArticleFig(id=1217833925204956161, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=CN, label=表3, caption=

26种元素水标和醇标测定加标回收率比较(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 加标回收率 元素 加标回收率
水标 醇标 水标 醇标
Na 92.8 95.9 Sn 85.4 99.5
K 93.2 98.8 Rb 95.2 99.5
Ca 92.2 97.9 V 104.9 101.3
Mg 81.9 99.8 Cr 98.6 100.4
Fe 101.4 101.0 Co 110.4 104.4
Li 86.2 100.6 Ni 115.6 103.4
B 162.7 102.6 As 399.6 100.1
Al 90.5 94.6 Se 324.1 99.5
Mn 110.4 101.2 Mo 100.4 101.4
Cu 94.9 97.9 Cd 87.0 102.2
Zn 112.1 97.3 Sb 136.9 100.4
Sr 86.1 99.0 Pb 82.3 102.1
Ba 90.3 101.1 Hg 89.8 94.5
), ArticleFig(id=1217833925402087438, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=EN, label=Table 4, caption=

Internal standard, correlation coefficient, limits of detection, limits of quantitative and RSDs of 26 kinds of elements

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 内标选择 相关
系数		 检出限
/(μg/L)		 定量限
/(μg/L)		 RSDs/%
Na 45Sc 0.9991 50.0 170.0 0.7
K 45Sc 0.9995 80.0 270.0 0.7
Ca 45Sc 0.9997 300.0 1000.0 0.6
Mg 45Sc 0.9996 50.0 170.0 0.7
Fe 45Sc 0.9996 50.0 170.0 0.1
Li 45Sc 0.9998 0.6 2.0 1.2
B 45Sc 0.9992 10.0 33.0 0.7
Al 45Sc 0.9995 20.0 67.0 0.4
Mn 45Sc 0.9992 0.5 1.7 1.0
Cu 72Ge 0.9995 0.4 1.4 0.6
Zn 72Ge 0.9994 30.0 100.0 0.6
Sr 103Rh 0.9999 0.8 2.7 0.2
Ba 103Rh 0.9996 0.8 2.7 0.3
Sn 103Rh 0.9998 0.3 1.0 0.5
Rb 103Rh 0.9999 0.3 1.0 0.2
V 45Sc 0.9996 0.1 0.3 0.1
Cr 45Sc 0.9996 0.6 2.0 0.1
Co 72Ge 0.9997 0.1 0.3 0.6
Ni 72Ge 0.9997 1.0 3.4 0.4
As 72Ge 0.9998 0.2 0.7 1.1
Se 72Ge 0.9997 3.0 10.0 0.3
Mo 103Rh 0.9997 0.2 0.7 0.3
Cd 103Rh 0.9997 0.1 0.3 0.4
Sb 103Rh 0.9997 0.2 0.7 0.8
Pb 209Bi 0.9996 0.2 0.7 0.5
Hg 209Bi 0.9990 0.3 1.0 0.1
), ArticleFig(id=1217833925565665305, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=CN, label=表4, caption=

26种元素内标、相关系数、检出限、定量限和RSDs

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 内标选择 相关
系数		 检出限
/(μg/L)		 定量限
/(μg/L)		 RSDs/%
Na 45Sc 0.9991 50.0 170.0 0.7
K 45Sc 0.9995 80.0 270.0 0.7
Ca 45Sc 0.9997 300.0 1000.0 0.6
Mg 45Sc 0.9996 50.0 170.0 0.7
Fe 45Sc 0.9996 50.0 170.0 0.1
Li 45Sc 0.9998 0.6 2.0 1.2
B 45Sc 0.9992 10.0 33.0 0.7
Al 45Sc 0.9995 20.0 67.0 0.4
Mn 45Sc 0.9992 0.5 1.7 1.0
Cu 72Ge 0.9995 0.4 1.4 0.6
Zn 72Ge 0.9994 30.0 100.0 0.6
Sr 103Rh 0.9999 0.8 2.7 0.2
Ba 103Rh 0.9996 0.8 2.7 0.3
Sn 103Rh 0.9998 0.3 1.0 0.5
Rb 103Rh 0.9999 0.3 1.0 0.2
V 45Sc 0.9996 0.1 0.3 0.1
Cr 45Sc 0.9996 0.6 2.0 0.1
Co 72Ge 0.9997 0.1 0.3 0.6
Ni 72Ge 0.9997 1.0 3.4 0.4
As 72Ge 0.9998 0.2 0.7 1.1
Se 72Ge 0.9997 3.0 10.0 0.3
Mo 103Rh 0.9997 0.2 0.7 0.3
Cd 103Rh 0.9997 0.1 0.3 0.4
Sb 103Rh 0.9997 0.2 0.7 0.8
Pb 209Bi 0.9996 0.2 0.7 0.5
Hg 209Bi 0.9990 0.3 1.0 0.1
), ArticleFig(id=1217833925712465953, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=EN, label=Table 5, caption=

Comparison of the results of determination of 26 kinds of elements in samples by 2 kinds of methods

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 45%vol酒样 50%vol酒样 55%vol酒样 63%vol酒样
基体匹配 标准方法 基体匹配 标准方法 基体匹配 标准方法 基体匹配 标准方法
Na* 2.9 3.0 4.8 5.0 23.6 23.8 2.8 2.7
K* 1.4 1.4 1.3 1.3 1.4 1.4 3.3 3.4
Ca* 4.8 4.9 7.5 7.5 28.8 28.7 6.2 6.3
Mg* 0.9 0.9 3.6 3.7 4.8 4.9 1.0 1.0
Fe* 0.1 ND 0.2 ND 0.5 0.5 0.7 0.7
Li 4.4 ND 5.4 ND 21.0 20.5 34.2 33.6
B 14.2 ND 23.7 ND 39.4 ND 36.3 ND
Al 143.0 ND 175.0 ND 687.0 698.0 1270.0 1293.0
Mn 8.3 8.3 69.5 68.3 61.0 61.5 62.8 61.2
Cu 10.2 10.7 37.2 38.4 8.1 8.2 20.5 19.6
Zn ND ND 101.0 ND ND ND 39.5 ND
Sr 35.2 35.9 42.9 43.6 298.0 306.0 44.8 44.1
Ba 2.3 ND 8.6 8.5 1.4 ND 0.8 ND
Sn 8.7 8.8 7.9 8.1 2.2 ND 6.6 6.7
Rb 1.6 ND 1.8 ND 4.7 4.7 8.6 8.7
V 0.4 ND 1.3 1.3 1.6 1.5 1.8 1.8
Cr 1.1 ND 4.5 ND 17.1 16.5 23.8 22.9
Co ND ND 0.7 ND 0.6 ND 0.9 0.9
Ni ND ND 13.0 12.6 14.8 14.3 18.6 18.1
As 0.2 ND 2.2 2.2 0.5 ND 2.0 2.0
Se ND ND ND ND ND ND ND ND
Mo 0.4 ND 1.1 ND 1.2 ND 1.6 ND
Cd ND ND 1.2 1.2 0.1 ND 1.0 1.0
Sb 1.2 ND 1.2 ND 0.9 ND 0.7 ND
Pb 1.9 ND 15.2 14.6 1.5 ND 8.1 8.0
Hg ND ND ND ND ND ND ND ND
), ArticleFig(id=1217833925813129259, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=CN, label=表5, caption=

两种方法测定酒样中26种元素结果比较

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 45%vol酒样 50%vol酒样 55%vol酒样 63%vol酒样
基体匹配 标准方法 基体匹配 标准方法 基体匹配 标准方法 基体匹配 标准方法
Na* 2.9 3.0 4.8 5.0 23.6 23.8 2.8 2.7
K* 1.4 1.4 1.3 1.3 1.4 1.4 3.3 3.4
Ca* 4.8 4.9 7.5 7.5 28.8 28.7 6.2 6.3
Mg* 0.9 0.9 3.6 3.7 4.8 4.9 1.0 1.0
Fe* 0.1 ND 0.2 ND 0.5 0.5 0.7 0.7
Li 4.4 ND 5.4 ND 21.0 20.5 34.2 33.6
B 14.2 ND 23.7 ND 39.4 ND 36.3 ND
Al 143.0 ND 175.0 ND 687.0 698.0 1270.0 1293.0
Mn 8.3 8.3 69.5 68.3 61.0 61.5 62.8 61.2
Cu 10.2 10.7 37.2 38.4 8.1 8.2 20.5 19.6
Zn ND ND 101.0 ND ND ND 39.5 ND
Sr 35.2 35.9 42.9 43.6 298.0 306.0 44.8 44.1
Ba 2.3 ND 8.6 8.5 1.4 ND 0.8 ND
Sn 8.7 8.8 7.9 8.1 2.2 ND 6.6 6.7
Rb 1.6 ND 1.8 ND 4.7 4.7 8.6 8.7
V 0.4 ND 1.3 1.3 1.6 1.5 1.8 1.8
Cr 1.1 ND 4.5 ND 17.1 16.5 23.8 22.9
Co ND ND 0.7 ND 0.6 ND 0.9 0.9
Ni ND ND 13.0 12.6 14.8 14.3 18.6 18.1
As 0.2 ND 2.2 2.2 0.5 ND 2.0 2.0
Se ND ND ND ND ND ND ND ND
Mo 0.4 ND 1.1 ND 1.2 ND 1.6 ND
Cd ND ND 1.2 1.2 0.1 ND 1.0 1.0
Sb 1.2 ND 1.2 ND 0.9 ND 0.7 ND
Pb 1.9 ND 15.2 14.6 1.5 ND 8.1 8.0
Hg ND ND ND ND ND ND ND ND
), ArticleFig(id=1217833927117557812, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=EN, label=Table 6, caption=

Determination resuts of 26 kinds of elements in wine samples

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 测定结果 元素 测定结果 元素 测定结果
Li 5~35 Mn 8~70 Sr 30~330
B 15~45 Fe* 0.06~0.80 Mo 0.4~1.8
Na* 3~40 Co ND~1 Cd ND~1.3
Mg* 0.5~5.0 Ni ND~24 Sn 2~9
Al 50~1300 Cu 8~43 Sb 0.7~1.3
K* 0.5~3.5 Zn ND~135 Ba 0.8~10.0
Ca* 5~32 As 0.2~3.0 Hg ND
V 0.5~2.0 Se ND Pb 1.3~18.0
Cr 1~25 Rb 1.5~10.0
), ArticleFig(id=1217833927226609726, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1217781122306593149, language=CN, label=表6, caption=

酒样中26种元素测定结果

, figureFileSmall=null, figureFileBig=null, tableContent=
元素 测定结果 元素 测定结果 元素 测定结果
Li 5~35 Mn 8~70 Sr 30~330
B 15~45 Fe* 0.06~0.80 Mo 0.4~1.8
Na* 3~40 Co ND~1 Cd ND~1.3
Mg* 0.5~5.0 Ni ND~24 Sn 2~9
Al 50~1300 Cu 8~43 Sb 0.7~1.3
K* 0.5~3.5 Zn ND~135 Ba 0.8~10.0
Ca* 5~32 As 0.2~3.0 Hg ND
V 0.5~2.0 Se ND Pb 1.3~18.0
Cr 1~25 Rb 1.5~10.0
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基体匹配-电感耦合等离子体质谱法测定白酒中26种元素含量
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董维兵 1 , 钱宇 2, *
食品安全质量检测学报 | 食品分析与检测 2025,16(12): 192-197
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食品安全质量检测学报 | 食品分析与检测 2025, 16(12): 192-197
基体匹配-电感耦合等离子体质谱法测定白酒中26种元素含量
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董维兵1 , 钱宇2, *
作者信息
  • 1 成都市新都区疾病预防控制中心, 成都 610500
  • 2 四川轻化工大学化学工程学院, 自贡 643000

    • 董维兵(1979—), 男, 硕士, 副主任技师, 主要研究方向为食品检验。E-mail:

通讯作者:

*钱宇(1988—), 男, 博士, 讲师, 主要研究方向为分析化学, 白酒风味组学。E-mail:
Determination of 26 kinds of elements content in liquor by matrix matching-inductively coupled plasma mass spectrometry
Wei-Bing DONG1 , Yu QIAN2, *
Affiliations
  • 1 Xindu District Center for Disease Control and Prevention, Chengdu 610500, China
  • 2 School of Chemical Engineering, Sichuan University of Science & Engineering, Zigong 643000, China
出版时间: 2025-06-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250217004
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摘要
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目的 利用基体匹配, 建立电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)快速测定白酒中26种元素的方法。方法 结合动能歧视(kinetic energy discrimination, KED)模式, 采用内标法测定白酒中Cd、Sn、Ba、Pb、Li、B、Mg、Al、K、Ca、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Rb、Sr、Mo、Sb、Na、Se和Hg等26种元素含量, 并且与标准检验方法进行比较。结果 该方法相关系数为0.9990~0.9999, 检出限为0.1~300.0 μg/L, 加标回收率为94.5%~104.4%, 相对标准偏差(relative standard deviations, RSDs)为0.1%~1.2%。加标回收率明显优于未进行基体匹配测定方法, 方法性能参数均符合GB 5009.295—2023《食品安全国家标准 化学分析方法验证通则》要求。与标准检验方法比较, 能有效减少前处理步骤、缩短前处理时间、节约耗材, 二者测定结果无显著差异。结论 该方法简便易行、快捷准确、稳定可靠, 适用于批量白酒中多元素检测, 为保障白酒质量安全提供技术支持。

基体匹配  /  白酒  /  多元素  /  电感耦合等离子体质谱法

Objective To establish a method for rapid determination of 26 kinds of elements in liquor by inductively coupled plasma mass spectrometry (ICP-MS) adopting matrix matching. Methods Combining with kinetic energy discrimination (KED) and internal standard correction mode, the determination method of Cd, Sn, Ba, Pb, Li, B, Mg, Al, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Rb, Sr, Mo, Sb, Na, Se and Hg in liquor had been established though direct dilution injection, and compared with the standard test method. Results The results showed that the correlation coefficient of standard curve was 0.9990-0.9999, the limit of determination was 0.1-300.0 μg/L, the standard recovery rates were 94.5%-104.4%, the relative standard deviations (RSDs) were 0.1%-1.2%. The standard recovery rate was obviously better than that without matrix matching method. The performance parameters of the method met the requirements of GB 5009.295—2023 National food safety standards-General rules for verification of chemical analysis methods. Compared with the standard test method, it could effectively reduce the pre-treatment steps, shorten the pre-treatment time, and save consumables. The results of the 2 kinds of methods showed no significant difference. Conclusion The method is simple, fast, accurate, stable and reliable, and is suitable for the bulk detection of multielement in liquor. The method provides technical support for ensuring liquor quality and safety.

matrix matching  /  liquor  /  multielement  /  inductively coupled plasma mass spectrometry
董维兵, 钱宇. 基体匹配-电感耦合等离子体质谱法测定白酒中26种元素含量. 食品安全质量检测学报, 2025 , 16 (12) : 192 -197 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250217004
Wei-Bing DONG, Yu QIAN. Determination of 26 kinds of elements content in liquor by matrix matching-inductively coupled plasma mass spectrometry[J]. Journal of Food Safety & Quality, 2025 , 16 (12) : 192 -197 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250217004
正文
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0 引言
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白酒在生产和储存过程中, 与蒸酒器具、输酒管路及贮酒容器的接触, 蒸馏过程及勾调过程均易引入金属元素从而引起白酒质量安全隐患[1-2]。
白酒中元素离子的混入有利有弊, 研究表明铁锰离子因自身颜色易造成白酒呈色且影响感官品质[3]; 过量的钙、镁、钡、铁离子会影响白酒稳定性, 导致浑浊和沉淀[4-5]; 白酒中铅、砷、汞、镉等元素会引起氧化损伤、慢性炎症疾病、癌症以及过早衰老等健康问题, 是食品中必须检测的安全性指标[6]。然而, 适量的钾离子有利于提升口感, 使酒体老熟、增加酒体的醇甜感; 铜离子的催化作用可以加快白酒的陈化[7-8]。因此, 研究白酒中各元素的准确分析方法是有必要且具有重要现实意义。
目前白酒中元素的检验方法主要有GB 5009.12—2023《食品安全国家标准 食品中铅的测定》中石墨炉原子吸收光谱法和火焰原子吸收光谱法以及GB 5009.268—2016《食品安全国家标准 食品中多元素的测定》中电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)和电感耦合等离子体发射光谱法, 这些检验方法的试样前处理为加热除乙醇及加酸消解, 操作复杂, 并使用有毒有害化学试剂, 同时易造成二次污染[9-11]。
基体匹配-ICP-MS是通过匹配样品与标准溶液的基体成分来优化分析性能的技术, 可以减少基体干扰, 能有效降低甚至消除基体效应, 改善灵敏度与检出限, 增强方法适用性[12-14]。刘曙等[15]梳理总结了ICP-MS测定元素时基体效应产生机制、不同元素的基体效应消除及校正方法, 连旭东等[16]介绍了直接稀释法、基体匹配法及内标校正法等减少和补偿基质效应的方法。基体匹配法在测定医用注射液[17]、矿石[18]和合金[19]等样品中元素应用较多, 也被大量应用于激光剥蚀ICP-MS测定固体样品[20-22]。但基体匹配法在白酒分析中鲜有报告, 仅有少量关于葡萄酒的研究, AUGAGNEUR等[23]用10%的乙醇配制空白溶液和标准溶液进行基体匹配, 采用ICP-MS测定葡萄酒中稀土元素含量。
本研究利用基体匹配结合ICP-MS同时测定15个白酒样品中26种元素, 对样品前处理方法进行了讨论, 并进行了方法学验证, 为白酒生产过程中的质量控制及安全风险评估提供方法支持。
1 材料与方法
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1.1 材料与试剂
15份风险监测酒样采自本地区饭店及酒坊散装白酒, 酒精度为45%vol ~63%vol。
Na、K、Ca、Mg、Fe混合标准溶液(质量浓度1000 mg/L)、Li、B、Al、Mn、Cu、Zn、Sr、Ba、Sn、Rb混合标准溶液(质量浓度100 mg/L)、V、Cr、Co、Ni、As、Se、Mo、Cd、Sb、Pb混合标准溶液(质量浓度10 mg/L)(北京北方伟业计量技术研究院); Hg标准溶液(质量浓度10 mg/L)、Be、Ce、Fe、In、Li、Mg、Pb、U调谐液(质量浓度1 μg/L)(美国PerkinElmer公司); Au标准溶液(质量浓度1000 mg/L)(国家有色金属及电子材料分析测试中心); Sc、Ge、Rh、In、Re、Bi混合内标溶液(质量浓度10 mg/L)(中国计量科学研究院); 硝酸(电子级)、无水乙醇(色谱纯)(国药集团化学试剂有限公司)。
1.2 仪器与设备
350X电感耦合等离子体质谱仪(美国PerkinElmer公司); MAS6微波消解仪(美国CEM公司); EHD-24赶酸仪(北京东航科仪仪器有限公司); UPHW-11-90T优普系列超纯水器(18.24 MΩ•cm, 四川优普超纯科技有限公司)。
1.3 实验方法
1.3.1 标准溶液配制
以2%的硝酸溶液逐级稀释1.1中各元素标准溶液配制成混合标准系列溶液(以下称水标), 质量浓度如表1所示, 按照标准系列序号分别依次进样测定。乙醇标准系列溶液(以下称醇标)除需加入适量的乙醇使乙醇浓度至5%外, 配制方法与水标完全一致。
1.3.2 内标溶液配制
将1.1中Sc、Ge、Rh、In、Re、Bi混合内标溶液用2%硝酸稀释为100 μg/L。
1.3.3 样品前处理
微波消解法: 参照GB 5009.268—2016第一法中微波消解法, 准确移取液体试样2.00 mL于微波消解罐中, 在赶酸仪上80 ℃加热除去乙醇, 加入7 mL硝酸, 加盖放置1 h, 旋紧罐盖, 设置微波消解仪功率1600 W, 20 min温度升高至180 ℃保持20 min进行消解。冷却后取出, 缓慢打开罐盖排气, 将消解罐放在赶酸仪上, 于80 ℃加热至酸液挥发殆尽, 用纯水定容至25 mL, 混匀, 同时作加标回收和空白实验。
直接稀释法: 直接吸取白酒样品5 mL, 用2%的硝酸稀释定容至50 mL作10倍稀释, 混匀, 同时作加标回收和空白实验。
1.3.4 样品测定
以调谐液进样将仪器调至最佳工作状态, 用水标作微波消解法和直接稀释法前处理酒样的标准系列溶液, 氦气碰撞模式下在线加入内标溶液按照表2的工作参数导入ICP-MS进行测定; 醇标按照相同的方法对直接稀释法处理的酒样进行测定。在标准溶液和样品测定间隙用200 μg/L的Au溶液进行冲洗, 消除Hg的记忆效应, 工作站分析软件自动运算处理数据, 绘制标准曲线, 计算样品中各元素含量。
1.4 数据处理
使用Excel 2019版对测定数据进行计算及统计, 每份样品重复测定6次, 计算加标回收率和相对标准偏差(relative standard deviation, RSD), 另计算测定结果与标准检验方法的相对偏差, 比较二者差异。
2 结果与分析
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2.1 酒样稀释倍数选择
直接进样高浓度有机溶剂会导致等离子不稳定甚至熄火, 同时会在炬管中心管和锥孔形成积碳, 造成信号不稳定或无信号[24-25], 在对白酒中元素测定时需要将乙醇浓度降低至5%以下。杨雯懿等[26]以5%的乙醇浓度进行基体匹配, ICP-MS/MS模式下测定白酒中14种元素, 方法的检出限低、准确度好、稳定性和精密度高。本研究选择用5%的乙醇浓度作基体匹配, 配制乙醇浓度为5%的标准系列溶液, 市售白酒酒精度以50%左右居多, 故白酒样品一律用2%的硝酸稀释10倍至酒精度约为5%, 从而与标准系列溶液基体匹配。此稀释浓度既能保证较高的灵敏度满足分析要求, 又不会损伤仪器。
2.2 基体匹配方法
白酒中因含乙醇等有机物, 在等离子体高温条件下会产生较多的碳基等, 具备KED氦气碰撞模式能有效降低ICP-MS测定中C、Ar、O、N、Cl、S等多原子干扰[27]。根据内标元素最好与待测元素的质量和电离能接近原则分别选择Sc、Ge、Rh、Bi作内标元素, 能有效降低基体干扰及仪器波动的影响[28-29]。使用水标和醇标分别测定直接稀释法处理的酒样, 选择其中一个样品作加标回收实验, 分别进行低、中、高3个梯度的加标实验, 每个加标样平行测定6次, 计算平均加标回收率, 实验结果见表3。
使用水标进行样品测定加标回收率为81.9%~399.6%, 26种元素回收率整体偏差较大, 其中B、As和Se回收率出现异常值, 分别达到162.7%、399.6%和324.1%, 但6次结果的RSD<0.5%, 具有较好的重现性, 出现以上异常现象可能是稀释处理的酒样仍含少量乙醇等有机物, 会影响分析稳定性[30], 对B元素, 基体效应可能改变其离子化效率, 高基体浓度增加多原子离子BH的形成, 导致质谱干扰, 且因其质量数较小, 更易受基体效应影响。同时乙醇基体可能增强了As和Se元素的激发。这些因素直接或间接导致了基体对B、As和Se的增强效应, 直接使用水标结合KED模式及内标校正并不能完全消除基体干扰从而导致结果偏离; 而使用醇标测定加标回收率为94.5%~104.4%, 效果优于使用水标的测定值。
2.3 方法验证
以1.3.1方法配制醇标, 酒样以2%的硝酸作10倍稀释, 以表2仪器条件进样测定, 按照GB 5009.295—2023《食品安全国家标准 化学分析方法验证通则》计算方法检出限、定量限、精密度和加标回收率, 空白样品基质连续测定20次计算标准偏差, 以3倍标准偏差计算检出限, 以10倍标准偏差计算定量限, 2.2中以醇标测定的加标样每个平行测定6次, 计算RSDs, 结果见表4。26种元素测定相关系数为0.9990~0.9999, 方法线性关系好。方法检出限为0.1~300.0 μg/L, RSD为0.1%~1.2%, 说明方法精密度高, 检出限低。
选择4份不同酒精度样品, 分别以GB 5009.268—2016第一法及基体匹配法测定其26种元素并作结果比较, 测定结果见表5。因稀释倍数更小, 本研究方法测定的元素检出限大部分比标准方法的更低, 采用标准检验方法测定, 有更多的元素低于其方法检出限。表5中, 以基体匹配法测定值与标准方法测定值之差除以标准方法测定值, 分别计算两种方法测定不同酒精度26种元素的相对偏差, 与标准方法相比Cu元素为最大负偏离-4.7%, V元素为最大正偏离6.7%, 两种方法测定结果基本一致, 样品中不同酒精度(45%~63%)对测定结果几乎没有影响。结合表4和表5可知, 基体匹配ICP-MS测定白酒中26种元素性能参数均符合GB 5009.295—2023要求。
2.4 样品测定结果分析
方法具有较高的灵敏度, 15份白酒中除Se和Hg的测定结果低于方法检出限, 其他各元素均有检出, 测定结果见表6, GB 2762—2022《食品安全国家标准 食品中污染物限量》中白酒限量(以Pb计)为0.5 mg/kg, 本次测定Pb含量最大值为0.018 mg/L, 经查50度白酒密度约为0.9 kg/L, 0.018 mg/L的Pb含量可换算为0.02 mg/kg, 远小于白酒限量标准。其他部分元素评价参考GB 5749—2022《生活饮用水卫生标准》, 有5份白酒中Al含量, 2份白酒中Fe含量超过生活饮用水卫生标准限值, 重金属元素均低于标准限值, 总体而言本地区散装白酒中26种元素测定结果较低, 有害元素残留的安全风险较小。
3 结论
收起
结合内标校正、KED模式和样品稀释采用基体匹配ICP-MS建立白酒中26种元素测定方法, 26种元素的检出限为0.1~300.0 μg/L, 加标回收率为94.5%~104.4%, 相关系数为0.9990~0.9999, RSD为0.1%~1.2%, 结果显示方法具有较高的灵敏度和准确度, 良好的方法线性和精密度。与标准检验方法比较结果一致, 结果偏差在-4.7%~6.7%, 但相比标准方法, 本研究方法能极大缩短前处理时间, 减少有毒有害溶剂使用, 可以有效避免前处理步骤过多带入的污染及元素损失, 能满足大批量酒样多元素测定, 为白酒的监督检测提供快速有效的技术支持。
基金
收起
  • 四川省自然科学基金项目(2019YJ0698)
文献
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2025年第16卷第12期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250217004
  • 接收时间：2025-02-17
  • 首发时间：2026-01-13
  • 出版时间：2025-06-25
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  • 收稿日期：2025-02-17
基金
四川省自然科学基金项目(2019YJ0698)
作者信息
    1 成都市新都区疾病预防控制中心, 成都 610500
    2 四川轻化工大学化学工程学院, 自贡 643000

通讯作者:

*钱宇(1988—), 男, 博士, 讲师, 主要研究方向为分析化学, 白酒风味组学。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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