Article(id=1297134052440568794, tenantId=1146029695717560320, journalId=1296801528146919473, issueId=1297134028650468001, articleNumber=null, orderNo=null, doi=10.12377/1671-4393.26.03.12, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1787190457686, onlineDateStr=2026-08-20, pubDate=1774368000000, pubDateStr=2026-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1787190457686, onlineIssueDateStr=2026-08-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1787190457686, creator=13701087609, updateTime=1787190457686, updator=13701087609, issue=Issue{id=1297134028650468001, tenantId=1146029695717560320, journalId=1296801528146919473, year='2026', volume='', issue='3', pageStart='2', pageEnd='157', issueExtLink='null', onlineDate='null', pubDate='1774368000000', pubDateStr='2026-03-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1787190452015, creator='13701087609', updateTime=1787192267815, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1297141644734787890, tenantId=1146029695717560320, journalId=1296801528146919473, issueId=1297134028650468001, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1297141644734787891, tenantId=1146029695717560320, journalId=1296801528146919473, issueId=1297134028650468001, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=80, endPage=87, ext={EN=ArticleExt(id=1297134054114096091, articleId=1297134052440568794, tenantId=1146029695717560320, journalId=1296801528146919473, language=EN, title=Optimization and Comparative Study of Iodine Content Detection Method in Milk Based on Gas Chromatograph, columnId=1297134031947194991, journalTitle=China Dairy, columnName=QUALITY CONTROL, runingTitle=null, highlight=null, articleAbstract=
[Objective]

This study focused on the optimization of the sample pretreatment process for the determination of iodine content in food by gas chromatography stipulated in "GB 5009.267—2020 Food Safety National Standard Determination of Iodine in Food", aiming to reduce the detection cost, shorten the detection time, and improve the detection efficiency and accuracy.

[Method]

Replace the separatory funnel with a centrifuge tube to reduce the sample weighing, increase the number of vortexing and centrifugation, and optimize the amount of butanone added to explore the optimal detection method.

[Result]

The optimized gas chromatography method demonstrated excellent performance in terms of recovery rate, precision, repeatability and detection limit when compared with the gas chromatography method specified in the national standard.

[Conclusion]

By overcoming the cumbersome problem of pretreatment, the optimized gas chromatography method was possible to accurately and quickly determine the iodine content in milk, and it was suitable for the large-scale detection of iodine content in milk.

, authors=Yawei HUANG, Xiaofeng HOU, Wenyan CAO*, Meina WANG, Xiao ZHANG, Jianjun MA, Jing ZHAI, authorsList=Yawei HUANG, Xiaofeng HOU, Wenyan CAO, Meina WANG, Xiao ZHANG, Jianjun MA, Jing ZHAI, authorCompany=null, correspAuthors=Wenyan CAO, 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=1297134054382531548, articleId=1297134052440568794, tenantId=1146029695717560320, journalId=1296801528146919473, language=CN, title=基于气相色谱法的牛奶碘含量检测方法优化与比较研究, columnId=1297134032135938673, journalTitle=中国乳业, columnName=质量安全, runingTitle=null, highlight=null, articleAbstract=
[目的]

本研究聚焦于《GB 5009.267—2020食品安全国家标准食品中碘的测定》中气相色谱法测定碘含量的前处理优化,以降低检测成本和缩短检测时间,提高检测效率及准确性。

[方法]

采用离心管取代分液漏斗,降低称样量,增加漩涡、离心、优化丁酮加入量等探索最优检测方法。

[结果]

优化后气相色谱法与国标中气相色谱法相比,回收率、精密度、重复性及检出限均表现出良好水平。

[结论]

优化后气相色谱法克服了前处理繁琐的缺陷,能够简便、快速且精准测定牛奶碘含量,适用于大批量牛奶碘含量检测。

, authors=黄雅薇, 侯晓锋, 曹文燕*, 王美娜, 张宵, 马建军, 翟婧, authorsList=黄雅薇, 侯晓锋, 曹文燕, 王美娜, 张宵, 马建军, 翟婧, authorCompany=null, correspAuthors=曹文燕, authorNote=

黄雅薇(1984-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测

侯晓锋(1987-),男,河北张家口人,本科,研究方向为食品质量与安全、食品检测和追溯系统

王美娜(1984-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测

张宵(1988-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测

马建军(1984-),男,内蒙古呼和浩特人,本科,研究方向为行政管理。

翟婧(1993-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测。

, correspAuthorsNote=

*

曹文燕(1987-),女,山东济南人,本科,高级工程师,研究方向为食品质量与安全、食品检测和追溯系统。
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基于气相色谱法的牛奶碘含量检测方法优化与比较研究
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黄雅薇 , 侯晓锋 , 曹文燕 * , 王美娜 , 张宵 , 马建军 , 翟婧
中国乳业 | 质量安全 2026,(3): 80-87
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中国乳业 |质量安全 2026 , (3) : 80 -87
基于气相色谱法的牛奶碘含量检测方法优化与比较研究
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马建军(1984-),男,内蒙古呼和浩特人,本科,研究方向为行政管理。

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黄雅薇, 侯晓锋, 曹文燕*, 王美娜, 张宵, 马建军, 翟婧
作者信息
  • 保定蒙牛饮料有限公司,河北省乳品智能化检测技术重点实验室,河北 保定 072450
通讯作者:

*

曹文燕(1987-),女,山东济南人,本科,高级工程师,研究方向为食品质量与安全、食品检测和追溯系统。
作者简介:

黄雅薇(1984-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测

侯晓锋(1987-),男,河北张家口人,本科,研究方向为食品质量与安全、食品检测和追溯系统

王美娜(1984-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测

张宵(1988-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测

马建军(1984-),男,内蒙古呼和浩特人,本科,研究方向为行政管理。

翟婧(1993-),女,河北保定人,本科,中级工程师,研究方向为食品检验检测。

Optimization and Comparative Study of Iodine Content Detection Method in Milk Based on Gas Chromatograph
Yawei HUANG, Xiaofeng HOU, Wenyan CAO*, Meina WANG, Xiao ZHANG, Jianjun MA, Jing ZHAI
Affiliations
  • Baoding Mengniu Beverage Co., Ltd., Hebei Province Key Laboratory of Intelligent Testing Technology for Dairy Products, Baoding Hebei 072450
出版时间: 2026-03-25 doi: 10.12377/1671-4393.26.03.12
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[目的]

本研究聚焦于《GB 5009.267—2020食品安全国家标准食品中碘的测定》中气相色谱法测定碘含量的前处理优化,以降低检测成本和缩短检测时间,提高检测效率及准确性。

[方法]

采用离心管取代分液漏斗,降低称样量,增加漩涡、离心、优化丁酮加入量等探索最优检测方法。

[结果]

优化后气相色谱法与国标中气相色谱法相比,回收率、精密度、重复性及检出限均表现出良好水平。

[结论]

优化后气相色谱法克服了前处理繁琐的缺陷,能够简便、快速且精准测定牛奶碘含量,适用于大批量牛奶碘含量检测。

碘  /  牛奶  /  气相色谱法
[Objective]

This study focused on the optimization of the sample pretreatment process for the determination of iodine content in food by gas chromatography stipulated in "GB 5009.267—2020 Food Safety National Standard Determination of Iodine in Food", aiming to reduce the detection cost, shorten the detection time, and improve the detection efficiency and accuracy.

[Method]

Replace the separatory funnel with a centrifuge tube to reduce the sample weighing, increase the number of vortexing and centrifugation, and optimize the amount of butanone added to explore the optimal detection method.

[Result]

The optimized gas chromatography method demonstrated excellent performance in terms of recovery rate, precision, repeatability and detection limit when compared with the gas chromatography method specified in the national standard.

[Conclusion]

By overcoming the cumbersome problem of pretreatment, the optimized gas chromatography method was possible to accurately and quickly determine the iodine content in milk, and it was suitable for the large-scale detection of iodine content in milk.

iodine  /  milk  /  Gas Chromatography (GC)
黄雅薇, 侯晓锋, 曹文燕, 王美娜, 张宵, 马建军, 翟婧. 基于气相色谱法的牛奶碘含量检测方法优化与比较研究. 中国乳业, 2026 , (3) : 80 -87 . DOI: 10.12377/1671-4393.26.03.12
Yawei HUANG, Xiaofeng HOU, Wenyan CAO, Meina WANG, Xiao ZHANG, Jianjun MA, Jing ZHAI. Optimization and Comparative Study of Iodine Content Detection Method in Milk Based on Gas Chromatograph[J]. China Dairy, 2026 , (3) : 80 -87 . DOI: 10.12377/1671-4393.26.03.12
  • 河北省乳品智能化检测技术重点实验室项目(SZQ2020018)
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doi: 10.12377/1671-4393.26.03.12
  • 首发时间:2026-08-20
  • 出版时间:2026-03-25
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基金
河北省乳品智能化检测技术重点实验室项目(SZQ2020018)
作者信息
    保定蒙牛饮料有限公司,河北省乳品智能化检测技术重点实验室,河北 保定 072450

通讯作者:

*

曹文燕(1987-),女,山东济南人,本科,高级工程师,研究方向为食品质量与安全、食品检测和追溯系统。
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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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