Article(id=1153433741264408587, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153433737141412332, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250108001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736265600000, receivedDateStr=2025-01-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752929633680, onlineDateStr=2025-07-19, pubDate=1745510400000, pubDateStr=2025-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752929633680, onlineIssueDateStr=2025-07-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752929633680, creator=13701087609, updateTime=1752929633680, 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=146, endPage=151, ext={EN=ArticleExt(id=1153433741750947857, articleId=1153433741264408587, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Optimization and applicability evaluation of mineral oils detection methods in edible oils based on GB/T 37514—2019, 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 optimize two kinds of detection methods in GB/T 37514—2019 Animal and vegetable fats and oils-Determination of mineral oils. Methods The saponification time was extended from 5 min to 10 min; a turbidimeter was introduced to measure the turbidity value of the saponified sample solution; a commercially available aluminum foil plate was used instead of the homemade alumina thin-layer plate; and 3 kinds of mineral oils were added to compare with the liquid paraffin in the standard. Results The turbidity values of some edible oils decreased to different degrees after prolonging the saponification time; the lowest limits of detection of diesel and liquid paraffin could reach 0.2% after replacing the aluminum foil plate; the limits of detection of different mineral oils by different methods were all different. Although the sensitivity of the optimized method was improved, it still did not fully meet the ideal standard for the detection of very small amounts of mineral oil residues in food safety regulation. Conclusion We call on the relevant departments to accelerate the improvement of the standardization system for the detection of mineral oil in food, and to promote the establishment of a more sensitive and scientific standard for the detection of mineral oil, so as to ensure the safety and quality of the edible oil market and to safeguard public health.

, correspAuthors=Xu-Gang WAN, 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=Yun YOU, Ya-Nan SUN, Jie LIU, Tao ZHANG, Ya-Wen GENG, Tao-Hong ZHOU, Jin LIN, Xu-Gang WAN), CN=ArticleExt(id=1153433771459203794, articleId=1153433741264408587, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=基于GB/T 37514—2019的食用油中矿物油检测方法优化及适用性评价, 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 优化GB/T 37514—2019《动植物油脂 矿物油的检测》中两种检测方法。方法 延长皂化时间由5 min至10 min; 引入浊度仪测皂化后的样液浊度值; 以市售铝箔板代替自制氧化铝薄层板; 新增3种矿物油与标准中的液体石蜡作对比。结果 延长皂化时间后部分食用油的浊度值有不同程度的减小; 更换铝箔板后, 柴油和液体石蜡的最低检出限可达到0.2%; 不同方法检测不同矿物油的检出限均有差别。尽管优化后方法的灵敏度有所提升, 但仍未完全达到食品安全监管中对于极微量矿物油残留检测的理想标准。结论 呼吁相关部门加快完善食品中矿物油检测标准体系建设, 推动建立更为灵敏、科学的矿物油检测标准, 以确保食用油市场的安全与质量, 保障公众健康。

, correspAuthors=万旭刚, authorNote=null, correspAuthorsNote=
* 万旭刚(1975—), 男, 高级工程师, 主要研究方向为食品检测。E-mail:
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游云(1999—), 女, 主要研究方向为食品检测。E-mail:

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China Journal of Cereals and Oils, 2011, 26(3): 100-104, 109., articleTitle=Characterization of mineral oil in edible fats and oils, refAbstract=null)], funds=[Fund(id=1171733932203623066, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, awardId=2017YFC1602005, language=CN, fundingSource=食品安全预警监测及风险管控技术集成、应用与示范研究项目(2017YFC1602005), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1171733927224984109, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, xref=null, ext=[AuthorCompanyExt(id=1171733927258538542, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, companyId=1171733927224984109, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Hubei Provincial Institute for Food Supervision and Test, Wuhan 430075, China), AuthorCompanyExt(id=1171733927271121455, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, companyId=1171733927224984109, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=湖北省食品质量安全监督检验研究院, 武汉 430075)])], figs=[ArticleFig(id=1171733930618176127, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=EN, label=Fig.1, caption=Nine kinds of edible oils after saponification, figureFileSmall=SuhKT755sthT9t6OJGbWjg==, figureFileBig=CbBqXOtZddQRYJFpSFH9XA==, tableContent=null), ArticleFig(id=1171733930689479297, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=CN, label=图1, caption=9种食用油皂化后情况

注: A~I分别对应菜籽油、稻米油、亚麻籽油、玉米油、山茶油、花生芝麻油、大豆油、调和油1、调和油2, 图25同。

, figureFileSmall=SuhKT755sthT9t6OJGbWjg==, figureFileBig=CbBqXOtZddQRYJFpSFH9XA==, tableContent=null), ArticleFig(id=1171733930823697027, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=EN, label=Fig.2, caption=Changes in turbidity values of 9 kinds of edible oils after saponification for different times, figureFileSmall=6uRiOKeyHmVAF9LK/CY6HQ==, figureFileBig=nTpKLQ5F1KsAFdaEPSasrA==, tableContent=null), ArticleFig(id=1171733930886611589, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=CN, label=图2, caption=9种食用油皂化不同时间后浊度值变化, figureFileSmall=6uRiOKeyHmVAF9LK/CY6HQ==, figureFileBig=nTpKLQ5F1KsAFdaEPSasrA==, tableContent=null), ArticleFig(id=1171733931075355271, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=EN, label=Fig.3, caption=After saponification of 4 kinds of mineral oils with different concentrations of spiked standards, figureFileSmall=4tlgct8QiZpAkSz+m5Nb7Q==, figureFileBig=7g1YOHH5pSRhbZbvG1ingQ==, tableContent=null), ArticleFig(id=1171733931180212873, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=CN, label=图3, caption=不同浓度4种矿物油加标皂化后情况, figureFileSmall=4tlgct8QiZpAkSz+m5Nb7Q==, figureFileBig=7g1YOHH5pSRhbZbvG1ingQ==, tableContent=null), ArticleFig(id=1171733931272487563, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=EN, label=Fig.4, caption=Changes in turbidity values after spiked saponification of 4 kinds of mineral oils of different concentrations, figureFileSmall=1XMTqc+1+q6avKGLeHXKRA==, figureFileBig=ukm5ZtPIt+RRf7E7e6fa1A==, tableContent=null), ArticleFig(id=1171733931398316685, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=CN, label=图4, caption=不同浓度的4种矿物油加标皂化后浊度值变化, figureFileSmall=1XMTqc+1+q6avKGLeHXKRA==, figureFileBig=ukm5ZtPIt+RRf7E7e6fa1A==, tableContent=null), ArticleFig(id=1171733931570283152, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=EN, label=Fig.5, caption=Thin layer spectral bands of edible oils, figureFileSmall=tF0FJP1c2eXeFMSQKHMcxQ==, figureFileBig=WbQCPI6KwqTvsGpE13fIkg==, tableContent=null), ArticleFig(id=1171733931771609746, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=CN, label=图5, caption=食用油薄层谱带

注: a. 氧化铝薄层板点样谱带; b. 含荧光指示剂的铝箔板点样展开谱带。

, figureFileSmall=tF0FJP1c2eXeFMSQKHMcxQ==, figureFileBig=WbQCPI6KwqTvsGpE13fIkg==, tableContent=null), ArticleFig(id=1171733931985519253, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=EN, label=Fig.6, caption=Thin layer spectral bands of mineral oil spiking, figureFileSmall=qgKFjers23uD3vXh4X4TUw==, figureFileBig=s0CxoHkgmZS/Y1r7pbkyIw==, tableContent=null), ArticleFig(id=1171733932056822423, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153433741264408587, language=CN, label=图6, caption=矿物油加标薄层谱带

注: a. 氧化铝薄层板点样谱带, b~d. 含荧光指示剂的铝箔板点样展开谱带; a、b. 从左往右谱带依次为油脂、油脂+1%液体石蜡、煤油、柴油、润滑油、液体石蜡标准溶液; c. 从左往右依次为0.2%、0.3%、0.5%煤油加标标准溶液, 0.2%、0.3%、0.5%柴油加标标准溶液; d. 从左往右依次为0.2%、0.3%、0.5%润滑油加标标准溶液, 0.2%、0.3%、0.5%液体石蜡加标标准溶液。

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基于GB/T 37514—2019的食用油中矿物油检测方法优化及适用性评价
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游云 , 孙亚南 , 刘杰 , 张涛 , 耿雅雯 , 周陶鸿 , 林津 , 万旭刚 *
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): 146-151
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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): 146-151
基于GB/T 37514—2019的食用油中矿物油检测方法优化及适用性评价
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游云 , 孙亚南, 刘杰, 张涛, 耿雅雯, 周陶鸿, 林津, 万旭刚*
作者信息
  • 湖北省食品质量安全监督检验研究院, 武汉 430075
  • 游云(1999—), 女, 主要研究方向为食品检测。E-mail:

通讯作者:

* 万旭刚(1975—), 男, 高级工程师, 主要研究方向为食品检测。E-mail:
Optimization and applicability evaluation of mineral oils detection methods in edible oils based on GB/T 37514—2019
Yun YOU , Ya-Nan SUN, Jie LIU, Tao ZHANG, Ya-Wen GENG, Tao-Hong ZHOU, Jin LIN, Xu-Gang WAN*
Affiliations
  • Hubei Provincial Institute for Food Supervision and Test, Wuhan 430075, China
出版时间: 2025-04-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250108001
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目的 优化GB/T 37514—2019《动植物油脂 矿物油的检测》中两种检测方法。方法 延长皂化时间由5 min至10 min; 引入浊度仪测皂化后的样液浊度值; 以市售铝箔板代替自制氧化铝薄层板; 新增3种矿物油与标准中的液体石蜡作对比。结果 延长皂化时间后部分食用油的浊度值有不同程度的减小; 更换铝箔板后, 柴油和液体石蜡的最低检出限可达到0.2%; 不同方法检测不同矿物油的检出限均有差别。尽管优化后方法的灵敏度有所提升, 但仍未完全达到食品安全监管中对于极微量矿物油残留检测的理想标准。结论 呼吁相关部门加快完善食品中矿物油检测标准体系建设, 推动建立更为灵敏、科学的矿物油检测标准, 以确保食用油市场的安全与质量, 保障公众健康。

皂化法  /  薄层色谱  /  矿物油残留  /  浊度仪

Objective To optimize two kinds of detection methods in GB/T 37514—2019 Animal and vegetable fats and oils-Determination of mineral oils. Methods The saponification time was extended from 5 min to 10 min; a turbidimeter was introduced to measure the turbidity value of the saponified sample solution; a commercially available aluminum foil plate was used instead of the homemade alumina thin-layer plate; and 3 kinds of mineral oils were added to compare with the liquid paraffin in the standard. Results The turbidity values of some edible oils decreased to different degrees after prolonging the saponification time; the lowest limits of detection of diesel and liquid paraffin could reach 0.2% after replacing the aluminum foil plate; the limits of detection of different mineral oils by different methods were all different. Although the sensitivity of the optimized method was improved, it still did not fully meet the ideal standard for the detection of very small amounts of mineral oil residues in food safety regulation. Conclusion We call on the relevant departments to accelerate the improvement of the standardization system for the detection of mineral oil in food, and to promote the establishment of a more sensitive and scientific standard for the detection of mineral oil, so as to ensure the safety and quality of the edible oil market and to safeguard public health.

saponification  /  thin layer chromatography  /  mineral oil residues  /  turbidimeter
游云, 孙亚南, 刘杰, 张涛, 耿雅雯, 周陶鸿, 林津, 万旭刚. 基于GB/T 37514—2019的食用油中矿物油检测方法优化及适用性评价. 食品安全质量检测学报, 2025 , 16 (8) : 146 -151 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250108001
Yun YOU, Ya-Nan SUN, Jie LIU, Tao ZHANG, Ya-Wen GENG, Tao-Hong ZHOU, Jin LIN, Xu-Gang WAN. Optimization and applicability evaluation of mineral oils detection methods in edible oils based on GB/T 37514—2019[J]. Journal of Food Safety & Quality, 2025 , 16 (8) : 146 -151 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250108001
食用油作为人体三大营养素之一, 其质量与安全问题一直是公众关注的焦点[1]。矿物油作为潜在污染物, 可能在油料的收割、晾晒、运输和加工过程中接触到发动机油、润滑油等, 或在油脂精炼过程中因导热油泄漏而引入污染。此外, 储存环境和塑料包装材料中的润滑剂迁移等因素也可能导致矿物油的污染, 进而对人体健康构成威胁[2-7]。近期“油罐车混装”事件更是加剧了公众对食品安全的担忧。
矿物油是由石油原油、煤、天然气等通过物理分离、化学转化或生物质液化所合成的C10~C50烃类化合物的总称, 主要包括直链烃、支链烃和烷基取代的环状饱和烷烃(mineral oil saturated hydrocarbons, MOSH)以及烷基取代的芳香烃(mineral oil aromatic hydrocarbons, MOAH)[8]。日常接触的矿物油包括煤油、汽油、柴油、石蜡、润滑油、液压油和发动机油等[9-10]。研究表明, 矿物油不易被肠胃吸收, 长期摄入过量可能导致脂溶性维生素吸收障碍及消化系统功能紊乱[11]。此外, 部分MOAH被认为具有基因毒性及更强的致癌性[12]。2017年10月27日, 世界卫生组织国际癌症研究机构将未经处理或轻度处理的矿物油列入一类致癌物名单。因此, 准确检测植物油中的矿物油残留具有重要学术和实践意义。
研究者们不断探索食用油脂中矿物油的测定方法, 包括皂化法、荧光法、薄层色谱法、气相色谱法、液相色谱-质谱法、红外光谱法和感官分析法[13-17]。其中, 皂化法和薄层色谱法作为国家标准方法, 被广泛用于检测食用油脂中的矿物油含量, 其他方法则存在适用范围局限和检测成本高等问题, 并未纳入国家标准, 不作为实验室日常检测的手段。GB/T 5009.37—2003《食用植物油卫生标准的分析方法》和GB/T 37514—2019《动植物油脂 矿物油的检测》主要用于食用油中矿物油掺假鉴定, 提供了矿物油的定性检测。然而, 由于油脂基质复杂, 干扰严重, 这两项标准方法的灵敏度无法满足实际检测需求。在油罐车混装事件发生后, 优化现有标准检测方法, 提高矿物油检测的灵敏度和准确性, 成为保障食用油安全的迫切任务。
本研究旨在优化GB/T 37514—2019中的皂化法和薄层色谱法, 皂化法是延长皂化时间提升油脂分离效果, 测量浊度值间接反映矿物油的存在及其含量, 增强结果准确性; 薄层色谱法是换用分离度更优的薄层板提升检测灵敏度。此外还增加了3种矿物油与标准规定的液体石蜡作对比, 进一步拓展检测样本的多样性, 以期为矿物油检测提供更广泛、可靠的数据支撑, 为优化检测方法提供新的思路。
食用油、煤油、柴油、润滑油由市场购买且食用油等级均为一级。
氢氧化钾、氢氧化钠、正己烷、无水乙醇、无水乙醚、液体石蜡、2’,7’-二氯荧光素(分析纯, 国药集团化学试剂有限公司); 实验用水均为三级水。
me403电子天平(精度0.001 g, 瑞士METTLER TOLEDO公司); ZF7-C三用紫外分析仪(上海康华生化仪器制造有限公司); WGZ-3散射光浊度仪(上海昕瑞仪器仪表有限公司); eme30250/ceb多位电加热套(深圳欣鼎盛电子有限公司); 薄层层析铝箔板(MERCK Silica gel 60 F254 20 cm×20 cm含荧光指示剂, 德国默克公司)。实验用玻璃器具使用前均用正己烷润洗。
选取市面上常见的9种食用油, 分别为菜籽油、稻米油、亚麻籽油、玉米油、山茶油、花生芝麻油、大豆油、调和油1(大豆、花生、菜籽)与调和油2(菜籽、玉米、花生), 对应编号A~I。按照GB/T 37514—2019第一法步骤进行检测后立即摇匀观察颜色并拍照。
选取煤油、柴油、润滑油和液体石蜡4种矿物油, 从上述9种食用油中选出一个作为阴性对照组, 制成0%、0.3%、0.5%、1.0%系列浓度的矿物油加标样品。同样按照GB/T 37514—2019第一法步骤进行检测。
优化方法: 将皂化时间从标准规定的5 min延长至10 min; 使用浊度仪测量样液皂化后的浊度, 替代标准中规定的肉眼观察。
油脂标准溶液: 称0.2 g一级植物油加入4 mL正己烷溶解。
煤油、柴油、润滑油、液体石蜡标准溶液: 分别称0.2 g加入4 mL正己烷溶解。
0%、0.2%、0.3%、0.5%系列浓度的矿物油加标样品用正己烷溶解成质量浓度为200 mg/mL的溶液。
按照GB/T 37514—2019第二法步骤操作, 点样量20 μL, 待展开剂展开到距离薄层板上边缘约0.5 cm时取出, 充分晾干后均匀喷洒显色剂, 之后放在紫外分析仪365 nm波长下观察对比色谱带。
优化方法: 使用含荧光指示剂的铝箔板替代标准中规定的氧化铝薄层板。
采用Origin 2021进行绘图, 所有实验数据均为3次重复实验的平均值。
图1所示, 仅凭肉眼观测和拍照记录只能辨识稻米油(B)和山茶油(E)存在浑浊现象。进一步的浊度值测定(图2)显示亚麻籽油(C)和玉米油(D)也有一定浊度, 其中B、C和E浊度值较高。但这一结果并不能直接说明上述食用油掺有矿物油或被矿物油污染, 因为这几种油中含有植物性甾醇、脂溶性维生素等对人体有益的成分, 在精炼过程中需要尽量保留, 这些成分在皂化反应中不会参与反应, 且不溶于水, 可能导致水相混浊或形成透明油珠析出[18]。山茶油主要是油酸等单不饱和脂肪酸, 稻米油含有丰富的不饱和脂肪酸(包括油酸、亚油酸等), 这种脂肪酸组成的差异可能会影响皂化反应的进程和产物的性质[19]。此外, 食用油中还可能含有极少量的脂肪醇、蜡等来自油料作物本身的成分, 这些成分在精炼工艺中也难以完全去除, 同样不会发生皂化反应, 可能导致水相混浊[20]。在延长皂化时间至10 min后, B、C和E的浊度值均有不同程度的减小, 可能是时间的延长使皂化反应进行的更完全[21]
根据2.1不同食用油皂化情况选择菜籽油(A)作为阴性对照组进行加标实验。如图3所示, 润滑油在菜籽油中的加入量超过0.3%时, 观察到样液明显浑浊, 而添加不同浓度柴油、煤油和液体石蜡的菜籽油样皂化后样液仍保持澄清, 肉眼难以区分。
图4所示, 经浊度测量, 发现液体石蜡在添加量为1.0%时有浊度值但处于较小数值范围, 而柴油和煤油尽管添加量增加至2.0%样液仍表现澄清且浊度值极低。这可能是由于尽管矿物油具有较高的沸点, 但在加热皂化反应过程中, 它们能够与食用油中的挥发性成分形成共沸体系, 加之煤油、柴油以及液体石蜡均具有一定挥发性, 这些特性使得它们在皂化过程中能够随之挥发, 导致皂化后的体系并未观察到混浊[22]。而液体石蜡相对柴油和煤油更稳定, 化学结构更单一, 可能在皂化体系中与其他物质相互作用的方式不同, 因而能呈现浊度值随浓度上升趋势。润滑油在成分构成上与柴油、煤油和液体石蜡存在显著差异, 主要由基础油及添加剂复合而成, 其分子结构较为复杂, 含有长链的烃类、酯类等多种成分。润滑油中的高分子量化合物及颗粒物质往往会在皂化反应中生成大量浑浊物质[23], 这是导致浊度值显著升高的一个重要原因。另一方面由于润滑油成分的复杂性, 乳化性能较差, 容易出现油滴聚集而导致浑浊, 而柴油、煤油和液体石蜡在皂化后的体系中乳化性能相对较好, 或者能够以较小的颗粒分散在体系中。这些现象表明, GB/T 37514—2019中的皂化法在评估食用油质量时存在一定的误判风险。
在GB/T 37514—2019中, 除了皂化法外, 还采用了薄层色谱法检测矿物油。薄层色谱技术基于化学物质的极性差异特性, 借助展开剂使化学物质在薄层板上进行层析分离, 并利用显色剂达成显色效果, 从而达到分离与鉴定目标[24]
结合图5实验现象来看, 当采用氧化铝薄层板时[图5(a)], 展开剂蔓延至白色虚线所处位置时, 其向上展开的进程受阻, 但从已呈现出的有限谱带中仍可观察到, B、D、E、I 4种油样存在与甘三酯谱带有所区别的谱带分离情况。图5(b)中, 采用铝箔板进行点样操作后, 展开过程顺利, 成功分离出甘三酯和蜡质的谱带, 其中B、D、I油样的蜡质谱带表现明显。蜡质主要是长链脂肪酸与长链醇缩合形成的酯类化合物, 且具有不溶于水的特性[25], 结合2.1实验结果进一步佐证了对于天然含有蜡质成分的食用油样品, 用皂化法进行检测时, 极有可能出现假阳性结果, 从而影响检测结果的准确性。
两种薄层板对比结果可能的原因一方面是氧化铝的表面活性位点分布及亲疏水性可能不利于展开剂在其表面均匀、快速地扩散, 使得展开进程容易受阻, 而铝箔板经过特殊处理或本身材质相对均匀光滑, 能与展开剂形成更良好的相互作用, 保障展开剂顺利携带样品迁移; 另一方面自制氧化铝薄层板在制作过程中的条件把控若存在细微偏差, 都可能影响其性能稳定性, 造成展开困难, 而市售铝箔板通常采用标准化、精细化的制备工艺, 质量稳定可靠, 更易于保证实验中的展开效果[26]
选择A样制备油脂标准样品, 图6(a)所示, 当展开剂蔓延至白色虚线所处位置时依旧无法继续向上展开, 因此后续实验均用铝箔板进行。铝箔板可以很好地分离油脂, 从图6(b)可以明显看到甘三酯和矿物油谱带的区分, 在图6(c)及(d)所示的不同矿物油浓度谱带中, 观察到煤油的检出限为0.5%, 润滑油为0.3%, 而柴油和液体石蜡在0.2%的含量时即可呈现显著矿物油谱带。这可能是因为矿物油的化学构成、挥发性以及不同矿物油与展开剂的相互作用程度不同都会影响它们在薄层板上的迁移速度和分离效果, 进而影响检出限[27-29]。杨会芳等[30]研究对比了皂化法、薄层色谱法及棒状薄层色谱-氢火焰离子化检测器法检测食用油脂中的矿物油, 结果表明薄层色谱法可对食用油脂中的矿物油进行定性检测, 最低检出限可达到0.2%, 与本研究结论一致。
综上所述, 通过实验明确了GB 37514—2019标准下的皂化法和氧化铝薄层色谱法在检测植物油中矿物油残留方面存在假阳性和检出限较高的问题及优化后的局限性。第一法检测发现有两种食用油出现浑浊情况, 但这无法确定这些食用油就是被矿物油污染, 通过延长皂化时间, 部分食用油的浊度有不同程度的减小, 但并不显著; 矿物油中仅有润滑油的检出限达到0.3%, 煤油、柴油、液体石蜡均在1.0%以上; 引入浊度仪监测虽然在一定程度上提高了检测灵敏度, 但受限于方法本身的局限性, 难以保证检测结果和检出限的准确性。第二法通过改变薄层板可以将柴油和液体石蜡的检出限提升至0.2%, 但仍难满足对微量残留的检测需求。此外两种方法均呈现出矿物油种类不同则检出限不同的现象, 因此以液体石蜡作为唯一标准溶液的科学性亦有待商榷。基于上述发现, 建议在完善矿物油检测标准体系时, 首先需建立覆盖柴油、润滑油、煤油等典型污染物的多组分参考物质库, 并通过毒理学研究确定不同矿物油的风险阈值以制定分级检测限标准。检测方法应强制要求加标回收率和重复性验证作为核心质控指标, 根据GB/T 27404—2008《实验室质量控制规范 食品理化检测》加标回收率建议控制范围为95%~105%, 标准偏差≤5%。同时需系统研究矿物油在油脂精炼、储运及包装迁移过程中的形态转化规律。对于浊度法计加入过程的改进, 可进一步探索其与色谱法的联用策略, 通过建立基于矿物油特征响应的浊度校准曲线来提升特异性。监管部门还应推动生产环节原料筛查、加工设备润滑油管控以及食品级包装材料认证等全过程防控体系的建设, 从根本上减少矿物油污染风险。
  • 食品安全预警监测及风险管控技术集成、应用与示范研究项目(2017YFC1602005)
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250108001
  • 接收时间:2025-01-08
  • 首发时间:2025-07-19
  • 出版时间:2025-04-25
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  • 收稿日期:2025-01-08
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食品安全预警监测及风险管控技术集成、应用与示范研究项目(2017YFC1602005)
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    湖北省食品质量安全监督检验研究院, 武汉 430075

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* 万旭刚(1975—), 男, 高级工程师, 主要研究方向为食品检测。E-mail:
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2种不同金属材料的力学参数

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genus
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Percentage of
total species (%)

Genus
种数
Number of
species
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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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