Article(id=1153986590490747688, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986579971429187, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20240928001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1727452800000, receivedDateStr=2024-09-28, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1753061443207, onlineDateStr=2025-07-21, pubDate=1740412800000, pubDateStr=2025-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753061443207, onlineIssueDateStr=2025-07-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753061443207, creator=13701087609, updateTime=1753061443207, updator=13701087609, issue=Issue{id=1153986579971429187, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='4', 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=0, createTime=1753061440699, creator=13701087609, updateTime=1758783495950, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1177986619249406427, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986579971429187, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1177986619249406428, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986579971429187, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=126, endPage=136, ext={EN=ArticleExt(id=1153986591367357249, articleId=1153986590490747688, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Identification of honey adulteration based on electronic nose and gas chromatography-mass spectrometry, columnId=1153986583259767470, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Food Quality Analysis and Evaluation, runingTitle=null, highlight=null, articleAbstract=

Objective To explore of odor differences and volatile differences between rape honey-adulterated and syrup-adulterated samples and real honey. Methods Different proportions of 5%, 10%, 20% and 30% syrup-adulterated and rape honey-adulterated samples were constructed, and the electronic nose technique and headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to analyze the odors and volatiles of the adulterated and authentic honey samples. Results The electronic nose (E-nose) combined with the principal component analysis (PCA) and sparse partial least squares discriminant analysis (sPLS-DA) could distinguish different botanical honey of linden honey, jujube honey acacia honey, and could distinguish syrup-adulterated samples from real honey, but could not distinguish rape honey-adulterated samples from acacia honey. The GC-MS results showed that 62 kinds of volatile compounds were identified in acacia honey, linden honey and jujube honey, with the highest content of alcohols in acacia honey, aldehydes in jujube honey, terpenes in linden honey. The content of volatile compounds in combination with sPLS-DA could distinguish 100% acacia honey, 100% linden honey from 5%-30% syrup-adulterated samples and 5%-30% rape honey-adulterated samples. Conclusion The odor analysis and volatiles analysis based on E-nose and GC-MS combined with chemometrics analysis can be used to identify syrup-adulterated and rape honey-adulterated samples. The results of the study provide a reference for honey traceability and adulteration identification studies.

, correspAuthors=Xin-Ying ZHAO, 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=Ya-Qin WEN, Shuai LUO, Wei-Na TIAN, Guo-Wei YANG, Xin-Ying ZHAO), CN=ArticleExt(id=1153986628616970368, articleId=1153986590490747688, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=电子鼻技术与气相色谱-质谱法鉴别蜂蜜掺假, columnId=1153986583435928240, journalTitle=食品安全质量检测学报, columnName=本期专题:食品品质分析与评价, runingTitle=null, highlight=null, articleAbstract=

目的 探究油菜蜜掺假样品和糖浆掺假样品与真实蜂蜜气味差异和挥发性物质差异。方法 构建5%、10%、20%、30%不同比例糖浆掺假和蜜源掺假样品, 采用电子鼻技术和顶空固相微萃取结合气相色谱-质谱技术(solid-phase microextraction and gas chromatography-mass spectrometry, HS-SPME-GC-MS)分析掺假样品和真实蜂蜜样品的气味和挥发性物质。结果 电子鼻(electronic nose, E-nose)结合主成分分析((principal component analysis, PCA)和稀疏偏最小二乘法判别分析(sparse partial least squares-discriminant analysis, sPLS-DA)可以区分椴树蜜、枣花蜜、洋槐蜜不同蜜源蜂蜜, 能区分糖浆掺假样品与真实蜂蜜, 但不能区分洋槐蜜与油菜蜜掺假样品。GC-MS结果表明, 洋槐蜜、椴树蜜和枣花蜜中共鉴定出62种挥发性化合物, 洋槐蜜中醇类物质含量最高, 枣花蜜中醛类物质含量最高, 椴树蜜中萜烯类物质含量最高, 挥发性物质含量结合sPLS-DA可以区分100%洋槐蜜、100%椴树蜜和5%~30%糖浆掺假、5%~30%油菜蜜掺假样品。结论 基于E-nose气味分析和GC-MS挥发性物质分析结合化学计量学分析可以进行糖浆掺假和油菜蜜掺假蜂蜜样品鉴别, 研究结果为蜂蜜溯源和掺假鉴别研究提供参考。

, correspAuthors=赵新颖, authorNote=null, correspAuthorsNote=
* 赵新颖(1981—), 女, 教授, 主要研究方向为分离纯化与分析测试技术。E-mail:
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问亚琴(1989—), 女, 博士, 副教授, 主要研究方向为食品风味分析。E-mail:

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问亚琴(1989—), 女, 博士, 副教授, 主要研究方向为食品风味分析。E-mail:

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Qinghuangdao: Yanshan University, 2023., articleTitle=null, refAbstract=null), Reference(id=1178002286556102948, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, doi=null, pmid=null, pmcid=null, year=2015, volume=31, issue=增刊1, pageStart=325, pageEnd=331, url=null, language=null, rfNumber=[27], rfOrder=38, authorNames=裴高璞, 史波林, 高海燕, journalName=农业工程学报, refType=null, unstructuredReference=裴高璞, 史波林, 高海燕, 等. 典型掺假蜂蜜的电子鼻信息变化特征及判别能力[J]. 农业工程学报, 2015, 31(增刊1): 325-331., articleTitle=典型掺假蜂蜜的电子鼻信息变化特征及判别能力, refAbstract=null), Reference(id=1178002286614823205, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, doi=null, pmid=null, pmcid=null, year=2015, volume=null, issue=1, pageStart=325, pageEnd=331, url=null, language=null, rfNumber=[27], rfOrder=39, authorNames=PEI GP, SHI BL, GAO HY, journalName=(Supp, refType=null, unstructuredReference=PEI GP, SHI BL, GAO HY, et al. 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Research progress of electronicnose on identification of food adulteration[J]. Food & Machinery, 2023, 39(04): 211-216, 240., articleTitle=Research progress of electronicnose on identification of food adulteration, refAbstract=null), Reference(id=1178002286967144746, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, doi=null, pmid=null, pmcid=null, year=2011, volume=126, issue=null, pageStart=1288, pageEnd=1298, url=null, language=null, rfNumber=[30], rfOrder=44, authorNames=PLUTOWSKA B, CHMIEL T, DYMERSKI T, journalName=Food Chemistry, refType=null, unstructuredReference=PLUTOWSKA B, CHMIEL T, DYMERSKI T, et al. A headspace solid-phase microextraction method development and its application in the determination of volatiles in honeys by gas chromatography[J]. Food Chemistry, 2011, 126: 1288-1298., articleTitle=A headspace solid-phase microextraction method development and its application in the determination of volatiles in honeys by gas chromatography, refAbstract=null)], funds=[Fund(id=1178002283586535675, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, awardId=BPHR202203242, language=CN, fundingSource=北京市属高等学校优秀青年人才培育计划项目(BPHR202203242), fundOrder=null, country=null), Fund(id=1178002283662033148, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, awardId=KM201910858003, language=CN, fundingSource=北京市教育委员会科学研究计划项目(KM201910858003), fundOrder=null, country=null), Fund(id=1178002283750113533, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, awardId=BYESS2022135, language=CN, fundingSource=北京市科学技术协会青年人才托举工程项目(BYESS2022135), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1178002280151400645, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, xref=null, ext=[AuthorCompanyExt(id=1178002280159789254, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, companyId=1178002280151400645, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Beijing Polytechnic, College of Biotechnology, Beijing 100176, China), AuthorCompanyExt(id=1178002280172372167, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, companyId=1178002280151400645, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=北京电子科技职业学院生物工程学院, 北京 100176)])], figs=[ArticleFig(id=1178002282286301419, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Fig.1, caption=Plot of E-nose test of different honey samples, figureFileSmall=FJyLmYV5u9PBZYsrqcWgyw==, figureFileBig=0g3GXkU3bFST3JCy/bQr4A==, tableContent=null), ArticleFig(id=1178002282361798892, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=图1, caption=不同蜂蜜样品电子鼻测试图谱

注: A. 枣花蜜; B. 天然成熟洋槐蜜; C. 椴树蜜; D. 洋槐蜜。

, figureFileSmall=FJyLmYV5u9PBZYsrqcWgyw==, figureFileBig=0g3GXkU3bFST3JCy/bQr4A==, tableContent=null), ArticleFig(id=1178002282428907757, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Fig.2, caption=Comparison of aroma difference in different kinds of honey samples based on E-nose, figureFileSmall=X6DWt+NjdwEsgY+A/UG4eg==, figureFileBig=7KrdY8KLFowEIH164q/YJg==, tableContent=null), ArticleFig(id=1178002282487628014, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=图2, caption=不同种类蜂蜜电子鼻气味差异比较

注: A. PCA得分图; B. sPLS-DA得分图。

, figureFileSmall=X6DWt+NjdwEsgY+A/UG4eg==, figureFileBig=7KrdY8KLFowEIH164q/YJg==, tableContent=null), ArticleFig(id=1178002282550542575, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Fig.3, caption=sPLS-DA analysis of different honeys and adulterated honeys based on E-nose, figureFileSmall=tKVH/IR0BgxBGLLaUAdzzQ==, figureFileBig=yxzaTaBAJIY0nkxxv/KIug==, tableContent=null), ArticleFig(id=1178002282630234352, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=图3, caption=基于电子鼻的不同蜂蜜与掺假蜂蜜sPLS-DA分析, figureFileSmall=tKVH/IR0BgxBGLLaUAdzzQ==, figureFileBig=yxzaTaBAJIY0nkxxv/KIug==, tableContent=null), ArticleFig(id=1178002282701537521, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Fig.4, caption=sPLS-DA analysis chart of natural mature acacia honey samples and adulterated honey samples, figureFileSmall=UrtH1kf260j88IhLUFCYpg==, figureFileBig=0IqeueofRthLTmFuw3TDXA==, tableContent=null), ArticleFig(id=1178002282760257778, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=图4, caption=天然成熟洋槐蜜与掺假蜂蜜sPLS-DA分析图

注: CSYH+YC. 不同比例油菜蜜掺假样品; CSYH+F45. 不同比例糖浆掺假样品。红蓝色图例指示的是相关挥发性成分在掺假蜂蜜和原蜂蜜样本中的含量分布情况, 下同。

, figureFileSmall=UrtH1kf260j88IhLUFCYpg==, figureFileBig=0IqeueofRthLTmFuw3TDXA==, tableContent=null), ArticleFig(id=1178002282844143859, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Fig.5, caption=sPLS-DA analysis chart of acacia honey samples and adulterated honey samples, figureFileSmall=9TAqGeyYpECilrHChn3SqA==, figureFileBig=bjRgdFMB1pJjlK/AC8X27A==, tableContent=null), ArticleFig(id=1178002282911252724, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=图5, caption=洋槐蜜与掺假蜂蜜sPLS-DA分析图

注: YH+YC. 不同比例油菜蜜掺假样品; YH+F45. 不同比例糖浆掺假样品。

, figureFileSmall=9TAqGeyYpECilrHChn3SqA==, figureFileBig=bjRgdFMB1pJjlK/AC8X27A==, tableContent=null), ArticleFig(id=1178002282969972981, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Fig.6, caption=sPLS-DA analysis chart of linden honey samples and adulterated honey samples, figureFileSmall=MYsOVlw8dsZKPOIVfJKT5w==, figureFileBig=i4rkScaDpmjGzTCuNTEDTw==, tableContent=null), ArticleFig(id=1178002283045470454, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=图6, caption=椴树蜜与掺假蜂蜜sPLS-DA分析图

注: DS+YC. 不同比例油菜蜜掺假样品; DS+F45. 不同比例糖浆掺假样品。

, figureFileSmall=MYsOVlw8dsZKPOIVfJKT5w==, figureFileBig=i4rkScaDpmjGzTCuNTEDTw==, tableContent=null), ArticleFig(id=1178002283104190711, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Table 1, caption=

Adulterated honey samples

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 实验设计 样品编码信息
洋槐蜜糖浆掺假样品
(YH+F45)
洋槐蜜+5%糖浆 YH5F45
洋槐蜜+10%糖浆 YH10F45
洋槐蜜+20%糖浆 YH20F45
洋槐蜜+30%糖浆 YH30F45
洋槐蜜掺油菜蜜样品
(YH+YC)
洋槐蜜+5%油菜蜜 YH5YC
洋槐蜜+10%油菜蜜 YH10YC
洋槐蜜+20%油菜蜜 YH20YC
洋槐蜜+30%油菜蜜 YH30YC
成熟洋槐蜜糖浆掺假样品
(CSYH+F45)
天然成熟洋槐蜜+5%糖浆 CSYH5F45
天然成熟洋槐蜜+10%糖浆 CSYH10F45
天然成熟洋槐蜜+20%糖浆 CSYH20F45
天然成熟洋槐蜜+30%糖浆 CSYH30F45
成熟洋槐蜜掺油菜蜜样品
(CSYH+YC)
天然成熟洋槐蜜+5%油菜蜜 CSYH5YC
天然成熟洋槐蜜+10%油菜蜜 CSYH10YC
天然成熟洋槐蜜+20%油菜蜜 CSYH20YC
天然成熟洋槐蜜+30%油菜蜜 CSYH30YC
椴树蜜掺油菜蜜样品
(DS+YC)
椴树蜜+5%油菜蜜 DS5YC
椴树蜜+10%油菜蜜 DS10YC
椴树蜜+20%油菜蜜 DS20YC
椴树蜜+30%油菜蜜 DS30YC
椴树蜜糖浆掺假样品
(DS+F45)
椴树蜜+5%糖浆 DS5F45
椴树蜜+10%糖浆 DS10F45
椴树蜜+20%糖浆 DS20F45
椴树蜜+30%糖浆 DS30F45
枣花蜜糖浆掺假样品
(ZH+F45)
枣花蜜+5%糖浆 ZH5F45
枣花蜜+10%糖浆 ZH10F45
枣花蜜+20%糖浆 ZH20F45
枣花蜜+30%糖浆 ZH30F45
枣花蜜掺油菜蜜样品
(ZH+YC)
枣花蜜+5%油菜蜜 ZH5YC
枣花蜜+10%油菜蜜 ZH10YC
枣花蜜+20%油菜蜜 ZH20YC
枣花蜜+30%油菜蜜 ZH30YC
), ArticleFig(id=1178002283192271096, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=表1, caption=

掺假蜂蜜样品

, figureFileSmall=null, figureFileBig=null, tableContent=
样品 实验设计 样品编码信息
洋槐蜜糖浆掺假样品
(YH+F45)
洋槐蜜+5%糖浆 YH5F45
洋槐蜜+10%糖浆 YH10F45
洋槐蜜+20%糖浆 YH20F45
洋槐蜜+30%糖浆 YH30F45
洋槐蜜掺油菜蜜样品
(YH+YC)
洋槐蜜+5%油菜蜜 YH5YC
洋槐蜜+10%油菜蜜 YH10YC
洋槐蜜+20%油菜蜜 YH20YC
洋槐蜜+30%油菜蜜 YH30YC
成熟洋槐蜜糖浆掺假样品
(CSYH+F45)
天然成熟洋槐蜜+5%糖浆 CSYH5F45
天然成熟洋槐蜜+10%糖浆 CSYH10F45
天然成熟洋槐蜜+20%糖浆 CSYH20F45
天然成熟洋槐蜜+30%糖浆 CSYH30F45
成熟洋槐蜜掺油菜蜜样品
(CSYH+YC)
天然成熟洋槐蜜+5%油菜蜜 CSYH5YC
天然成熟洋槐蜜+10%油菜蜜 CSYH10YC
天然成熟洋槐蜜+20%油菜蜜 CSYH20YC
天然成熟洋槐蜜+30%油菜蜜 CSYH30YC
椴树蜜掺油菜蜜样品
(DS+YC)
椴树蜜+5%油菜蜜 DS5YC
椴树蜜+10%油菜蜜 DS10YC
椴树蜜+20%油菜蜜 DS20YC
椴树蜜+30%油菜蜜 DS30YC
椴树蜜糖浆掺假样品
(DS+F45)
椴树蜜+5%糖浆 DS5F45
椴树蜜+10%糖浆 DS10F45
椴树蜜+20%糖浆 DS20F45
椴树蜜+30%糖浆 DS30F45
枣花蜜糖浆掺假样品
(ZH+F45)
枣花蜜+5%糖浆 ZH5F45
枣花蜜+10%糖浆 ZH10F45
枣花蜜+20%糖浆 ZH20F45
枣花蜜+30%糖浆 ZH30F45
枣花蜜掺油菜蜜样品
(ZH+YC)
枣花蜜+5%油菜蜜 ZH5YC
枣花蜜+10%油菜蜜 ZH10YC
枣花蜜+20%油菜蜜 ZH20YC
枣花蜜+30%油菜蜜 ZH30YC
), ArticleFig(id=1178002283288740089, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=EN, label=Table 2, caption=

Content of volatile compounds in different kinds of honey samples

, figureFileSmall=null, figureFileBig=null, tableContent=
保留时间/min 化合物(英文) 化合物(中文) 分类 枣花蜜/(ng/g) 椴树蜜/(ng/g) 成熟洋槐蜜/(ng/g) 加工洋槐蜜/(ng/g)
12.60 1-octen-3-ol 1-辛烯-3-醇 3.10±0.08a 2.68±0.06b 2.50±0.01c 2.64±0.04b
14.77 2-ethyl-1-hexanol 2-乙基-1-己醇 44.01±8.41c 42.54±0.10c 58.86±0.24a 50.59±1.08b
15.09 benzyl alcohol 苯甲醇 104.47±5.56b 116.98±4.53a 97.12±4.84b 105.11±4.66b
18.73 phenethyl alcohol 苯乙醇 118.85±4.92d 1015.91±29.06a 381.89±6.97b 230.30±4.80c
21.44 1-nonanol 壬醇 4.27±0.12b 4.64±0.07a 3.40±0.02c 3.25±0.01d
40.05 cedrol 雪松醇 7.25±0.03b 7.35±0.02a 7.22±0.01b 7.23±0.00b
总含量(占比/%) 281.94 (18.0) 1190.09 (15.0) 551.00 (48.8) 399.11 (45.0)
3.65 3-methyl-1-butanal 3-甲基-1-丁醛 3.91±0.49a 0.41±0.01b 0.24±0.05b 0.29±0.02b
3.75 2-methyl-1-butanal 2-甲基-1-丁醛 0.76±0.10a 0.30±0.03d 0.40±0.02c 0.49±0.08b
4.15 pentanal 戊醛 0.62±0.10a 0.35±0.10b 0.36±0.07b 0.41±0.00b
7.04 furfural 糠醛 2.68±0.16d 5.88±0.53b 8.11±1.09a 4.92±0.53c
9.43 heptanal 庚醛 2.92±0.20a 1.54±0.03b 1.50±0.09b 1.60±0.06b
11.90 benzaldehyde 苯甲醛 9.79±0.88a 8.59±0.19b 4.44±0.06c 4.71±0.29c
13.66 octanal 辛醛 2.56±0.09a 1.56±0.00b 1.63±0.01b 1.58±0.03b
15.52 phenylacetaldehyde 苯乙醛 477.3±51.63a 123.3±5.20b 19.06±0.17c 23.26±0.72c
15.58 2-hydroxybenzaldehyde 2-羟基苯甲醛 10.71±1.76a 2.49±0.12c 3.03±0.08c 8.18±0.26b
18.36 nonanal 壬醛 12.55±1.37a 2.09±0.01d 5.40±0.17b 3.61±0.17c
23.10 decanal 癸醛 5.21±0.17a 3.52±0.01d 4.11±0.03b 3.70±0.07c
28.15 (E,E)-2,4-decadienal (E,E)-2,4癸二烯醛 3.08±0.00b 3.20±0.10a 3.09±0.02b 3.06±0.03b
总含量(占比/%) 532.10 (34.0) 153.21 (1.9) 51.36(4.6) 55.80 (6.3)
3.11 acetic acid 乙酸 16.61±2.91b 37.16±0.78a 8.96±0.02c 9.33±0.87c
12.41 hexanoic acid 己酸 10.79±0.86b 11.92±0.39a 5.33±0.02c 5.60±0.31c
22.44 methyl salicylate 甲基水杨酸 1.37±0.01a 1.23±0.00b 1.19±0.01c 1.20±0.00c
25.80 nonanoic acid 壬酸 439.54±66.11a 365.85±11.48b 215.99±2.10c 155.11±5.56d
总含量(占比/%) 468.31 (29.9) 416.15 (5.3) 231.47 (20.5) 171.24 (19.3)
3.25 ethyl acetate 乙酸醋酸酯 47.28±1.17b 53.92±1.15a 26.10±0.70c 24.17±1.09d
29.32 α-terpineol acetate 萜品醇乙酸酯 22.46±1.17a 25.05±9.51a nd 19.15±1.17a
总含量(占比/%) 69.74 (4.5) 78.97 (1.0) 45.26 (4.0) 43.33 (4.9)
3.08 2,3-butanedione 2, 3-丁二酮 6.54±0.11a 5.76±0.04c 6.54±0.11a 6.13±0.05b
4.80 methyl isobutyl ketone 甲基异丁酮 3.07±0.00a 2.69±0.27a 2.71±0.24a 2.69±0.27a
25.06 carvotanacetone 香芹艾菊酮 nd 10.19±0.23 nd nd
总含量(占比/%) 9.61 (0.6) 18.63 (0.2) 9.25 (0.8) 8.82 (1.0)
10.70 α-pinene α-蒎烯 萜烯 0.83±0.19a nd nd nd
11.38 camphene 莰烯 萜烯 nd 1.00±0.01a nd nd
13.04 β-myrcene 月桂烯 萜烯 0.48±0.12a 0.17±0b 0.14±0.01b 0.13±0.06b
13.81 α-phellandrene α-水芹烯 萜烯 nd 0.46±0.03a nd nd
14.29 α-terpinene α-萜品烯 萜烯 4.97±0.13b 5.84±0.24a 4.11±0.02c nd
14.66 p-cymene β-伞花烃 萜烯 8.70±0.08b 11.44±0.10a 8.34±0.02c 8.24±0.01d
14.89 D-limonene 柠檬烯 萜烯 1.89±0a 1.35±0.02c 1.73±0.03b 1.34±0.03c
16.18 γ-terpinene γ-萜品烯 萜烯 5.92±0.40b 8.1±0.02a 4.12±0.01c nd
16.84 cis-linalool oxide (furanoid) 顺式里那醇氧化物 萜烯 12.29±0.94d 51.11±1.44a 18.77±0.47b 15.59±0.47c
17.44 terpinolene 异松油烯 萜烯 4.69±0.00c 5.20±0.08a 4.83±0.08b 4.37±0.08d
17.55 trans-linalool oxide (furanoid) 反式里那醇氧化物 萜烯 9.14±0.44b 18.95±0.47a 8.01±0.12c 7.11±0.10d
17.66 p-cymenene 脱氢对伞花烃 萜烯 8.24±0.02b 22.41±0.53a 8.71±0.03bc 8.39±0.01c
18.17 β-linalool 里那醇 萜烯 11.67±0.23a 11.53±0.16a 11.14±0.26b 8.84±0.19c
18.29 hotrienol 脱氢芳樟醇 萜烯 9.69±0.29c 55.64±1.75a 15.1±2.48b 10.24±1.40c
18.60 cis-rose oxide 顺式玫瑰醚 萜烯 4.47±0.04b 70.29±2.09a 4.67±0.02b 4.47±0.01b
19.36 trans-rose oxide 反式玫瑰醚 萜烯 nd 31.31±0.84a 4.5±0.01b nd
20.52 nerol oxide 橙花醚 萜烯 0.34±0.00c 0.9±0.01a 0.5±0.10b 0.38±0.06c
21.59 endo-borneol 龙脑 萜烯 8.63±0.10b 17.94±0.53a 7.28±0.02c 7.26±0.01c
21.97 terpinen-4-ol 萜品-4-醇 萜烯 6.82±0.15b 12.17±0.3a 4.54±0.10c 4.40±0.01c
22.64 α-terpineol 萜品醇 萜烯 5.45±0.14d 8.89±0.19a 8.44±0.25b 7.29±0.15c
22.80 safranal 藏红花醛 萜烯 1.36±0.05b 4.58±0.06a 1.03±0.10c 1.00±0.07c
24.00 citronellol 香茅醇 萜烯 4.86±0.31b 7.02±0.32a 4.14±0.51b 5.38±2.25b
24.75 cumaldehyde 枯茗醛 萜烯 nd 2.62±0.13a 0.97±0.02b 0.95±0.01b
26.40 thymol 百里酚 萜烯 nd 159.76±2.84a 59.8±0.17b 59.78±0.14b
27.70 citronellic acid 香茅酸 萜烯 nd 984.9±22.11a nd nd
29.74 geranic acid 香叶酸 萜烯 nd 4506.45±173.99a 16.29±4.73b nd
32.34 α-cedrene α-雪松烯 萜烯 nd 0.84±0.00a 0.73±0.00b 0.72±0.00b
32.50 caryophyllene 石竹烯 萜烯 1.57±0.12a 0.71±0.07b nd nd
总含量(占比/%) 116.43 (7.4) 6001.60 (75.9) 207.17 (18.4) 177.38 (20.0)
12.83 6-methyl-5-heptene-
2-one
6-甲基-5-庚-2-酮 C13降异戊二烯类 0.67±0.19b 1.00±0.11a 0.27±0.00c 0.30±0.04c
30.75 (E)-β-damascenone 大马士酮 C13降异戊二烯类 21.18±1.16a 18.16±0.28b 9.08±0.00c 8.74±0.03c
33.58 (E)-geranylacetone 香叶基丙酮 C13降异戊二烯类 2.58±0.35a 2.11±0.03b 1.85±0.02c 1.77±0.07c
34.80 (E)-β-ionone β-紫罗兰酮 C13降异戊二烯类 2.12±0.28a 1.61±0.03b 1.61±0.03b 1.58±0.00b
总含量(占比/%) 26.55 (1.7) 22.87 (0.3) 15.38 (1.4) 14.94 (1.7)
9.67 acetylfuran 乙酰呋喃 呋喃 1.73±0.16c 2.15±0.02a 1.92±0.02b 1.58±0.06d
总含量(占比/%) 1.73 (0.1) 2.15 (0) 1.92 (0) 1.58 (0)
5.41 toluene 甲苯 3.67±0.41a 1.65±0.06b 1.24±0.12c 1.29±0.05c
35.92 2,4-di-t-butylphenol 2,4-二叔丁基酚 56.75±6.57a 17.61±0.42b 14.00±0.31b 12.68±0.28b
总含量(占比/%) 60.42 (3.9) 19.25 (0.2) 15.24 (1.4) 13.97 (1.6)
), ArticleFig(id=1178002283401986298, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986590490747688, language=CN, label=表2, caption=

不同植物源蜂蜜挥发性成分含量

, figureFileSmall=null, figureFileBig=null, tableContent=
保留时间/min 化合物(英文) 化合物(中文) 分类 枣花蜜/(ng/g) 椴树蜜/(ng/g) 成熟洋槐蜜/(ng/g) 加工洋槐蜜/(ng/g)
12.60 1-octen-3-ol 1-辛烯-3-醇 3.10±0.08a 2.68±0.06b 2.50±0.01c 2.64±0.04b
14.77 2-ethyl-1-hexanol 2-乙基-1-己醇 44.01±8.41c 42.54±0.10c 58.86±0.24a 50.59±1.08b
15.09 benzyl alcohol 苯甲醇 104.47±5.56b 116.98±4.53a 97.12±4.84b 105.11±4.66b
18.73 phenethyl alcohol 苯乙醇 118.85±4.92d 1015.91±29.06a 381.89±6.97b 230.30±4.80c
21.44 1-nonanol 壬醇 4.27±0.12b 4.64±0.07a 3.40±0.02c 3.25±0.01d
40.05 cedrol 雪松醇 7.25±0.03b 7.35±0.02a 7.22±0.01b 7.23±0.00b
总含量(占比/%) 281.94 (18.0) 1190.09 (15.0) 551.00 (48.8) 399.11 (45.0)
3.65 3-methyl-1-butanal 3-甲基-1-丁醛 3.91±0.49a 0.41±0.01b 0.24±0.05b 0.29±0.02b
3.75 2-methyl-1-butanal 2-甲基-1-丁醛 0.76±0.10a 0.30±0.03d 0.40±0.02c 0.49±0.08b
4.15 pentanal 戊醛 0.62±0.10a 0.35±0.10b 0.36±0.07b 0.41±0.00b
7.04 furfural 糠醛 2.68±0.16d 5.88±0.53b 8.11±1.09a 4.92±0.53c
9.43 heptanal 庚醛 2.92±0.20a 1.54±0.03b 1.50±0.09b 1.60±0.06b
11.90 benzaldehyde 苯甲醛 9.79±0.88a 8.59±0.19b 4.44±0.06c 4.71±0.29c
13.66 octanal 辛醛 2.56±0.09a 1.56±0.00b 1.63±0.01b 1.58±0.03b
15.52 phenylacetaldehyde 苯乙醛 477.3±51.63a 123.3±5.20b 19.06±0.17c 23.26±0.72c
15.58 2-hydroxybenzaldehyde 2-羟基苯甲醛 10.71±1.76a 2.49±0.12c 3.03±0.08c 8.18±0.26b
18.36 nonanal 壬醛 12.55±1.37a 2.09±0.01d 5.40±0.17b 3.61±0.17c
23.10 decanal 癸醛 5.21±0.17a 3.52±0.01d 4.11±0.03b 3.70±0.07c
28.15 (E,E)-2,4-decadienal (E,E)-2,4癸二烯醛 3.08±0.00b 3.20±0.10a 3.09±0.02b 3.06±0.03b
总含量(占比/%) 532.10 (34.0) 153.21 (1.9) 51.36(4.6) 55.80 (6.3)
3.11 acetic acid 乙酸 16.61±2.91b 37.16±0.78a 8.96±0.02c 9.33±0.87c
12.41 hexanoic acid 己酸 10.79±0.86b 11.92±0.39a 5.33±0.02c 5.60±0.31c
22.44 methyl salicylate 甲基水杨酸 1.37±0.01a 1.23±0.00b 1.19±0.01c 1.20±0.00c
25.80 nonanoic acid 壬酸 439.54±66.11a 365.85±11.48b 215.99±2.10c 155.11±5.56d
总含量(占比/%) 468.31 (29.9) 416.15 (5.3) 231.47 (20.5) 171.24 (19.3)
3.25 ethyl acetate 乙酸醋酸酯 47.28±1.17b 53.92±1.15a 26.10±0.70c 24.17±1.09d
29.32 α-terpineol acetate 萜品醇乙酸酯 22.46±1.17a 25.05±9.51a nd 19.15±1.17a
总含量(占比/%) 69.74 (4.5) 78.97 (1.0) 45.26 (4.0) 43.33 (4.9)
3.08 2,3-butanedione 2, 3-丁二酮 6.54±0.11a 5.76±0.04c 6.54±0.11a 6.13±0.05b
4.80 methyl isobutyl ketone 甲基异丁酮 3.07±0.00a 2.69±0.27a 2.71±0.24a 2.69±0.27a
25.06 carvotanacetone 香芹艾菊酮 nd 10.19±0.23 nd nd
总含量(占比/%) 9.61 (0.6) 18.63 (0.2) 9.25 (0.8) 8.82 (1.0)
10.70 α-pinene α-蒎烯 萜烯 0.83±0.19a nd nd nd
11.38 camphene 莰烯 萜烯 nd 1.00±0.01a nd nd
13.04 β-myrcene 月桂烯 萜烯 0.48±0.12a 0.17±0b 0.14±0.01b 0.13±0.06b
13.81 α-phellandrene α-水芹烯 萜烯 nd 0.46±0.03a nd nd
14.29 α-terpinene α-萜品烯 萜烯 4.97±0.13b 5.84±0.24a 4.11±0.02c nd
14.66 p-cymene β-伞花烃 萜烯 8.70±0.08b 11.44±0.10a 8.34±0.02c 8.24±0.01d
14.89 D-limonene 柠檬烯 萜烯 1.89±0a 1.35±0.02c 1.73±0.03b 1.34±0.03c
16.18 γ-terpinene γ-萜品烯 萜烯 5.92±0.40b 8.1±0.02a 4.12±0.01c nd
16.84 cis-linalool oxide (furanoid) 顺式里那醇氧化物 萜烯 12.29±0.94d 51.11±1.44a 18.77±0.47b 15.59±0.47c
17.44 terpinolene 异松油烯 萜烯 4.69±0.00c 5.20±0.08a 4.83±0.08b 4.37±0.08d
17.55 trans-linalool oxide (furanoid) 反式里那醇氧化物 萜烯 9.14±0.44b 18.95±0.47a 8.01±0.12c 7.11±0.10d
17.66 p-cymenene 脱氢对伞花烃 萜烯 8.24±0.02b 22.41±0.53a 8.71±0.03bc 8.39±0.01c
18.17 β-linalool 里那醇 萜烯 11.67±0.23a 11.53±0.16a 11.14±0.26b 8.84±0.19c
18.29 hotrienol 脱氢芳樟醇 萜烯 9.69±0.29c 55.64±1.75a 15.1±2.48b 10.24±1.40c
18.60 cis-rose oxide 顺式玫瑰醚 萜烯 4.47±0.04b 70.29±2.09a 4.67±0.02b 4.47±0.01b
19.36 trans-rose oxide 反式玫瑰醚 萜烯 nd 31.31±0.84a 4.5±0.01b nd
20.52 nerol oxide 橙花醚 萜烯 0.34±0.00c 0.9±0.01a 0.5±0.10b 0.38±0.06c
21.59 endo-borneol 龙脑 萜烯 8.63±0.10b 17.94±0.53a 7.28±0.02c 7.26±0.01c
21.97 terpinen-4-ol 萜品-4-醇 萜烯 6.82±0.15b 12.17±0.3a 4.54±0.10c 4.40±0.01c
22.64 α-terpineol 萜品醇 萜烯 5.45±0.14d 8.89±0.19a 8.44±0.25b 7.29±0.15c
22.80 safranal 藏红花醛 萜烯 1.36±0.05b 4.58±0.06a 1.03±0.10c 1.00±0.07c
24.00 citronellol 香茅醇 萜烯 4.86±0.31b 7.02±0.32a 4.14±0.51b 5.38±2.25b
24.75 cumaldehyde 枯茗醛 萜烯 nd 2.62±0.13a 0.97±0.02b 0.95±0.01b
26.40 thymol 百里酚 萜烯 nd 159.76±2.84a 59.8±0.17b 59.78±0.14b
27.70 citronellic acid 香茅酸 萜烯 nd 984.9±22.11a nd nd
29.74 geranic acid 香叶酸 萜烯 nd 4506.45±173.99a 16.29±4.73b nd
32.34 α-cedrene α-雪松烯 萜烯 nd 0.84±0.00a 0.73±0.00b 0.72±0.00b
32.50 caryophyllene 石竹烯 萜烯 1.57±0.12a 0.71±0.07b nd nd
总含量(占比/%) 116.43 (7.4) 6001.60 (75.9) 207.17 (18.4) 177.38 (20.0)
12.83 6-methyl-5-heptene-
2-one
6-甲基-5-庚-2-酮 C13降异戊二烯类 0.67±0.19b 1.00±0.11a 0.27±0.00c 0.30±0.04c
30.75 (E)-β-damascenone 大马士酮 C13降异戊二烯类 21.18±1.16a 18.16±0.28b 9.08±0.00c 8.74±0.03c
33.58 (E)-geranylacetone 香叶基丙酮 C13降异戊二烯类 2.58±0.35a 2.11±0.03b 1.85±0.02c 1.77±0.07c
34.80 (E)-β-ionone β-紫罗兰酮 C13降异戊二烯类 2.12±0.28a 1.61±0.03b 1.61±0.03b 1.58±0.00b
总含量(占比/%) 26.55 (1.7) 22.87 (0.3) 15.38 (1.4) 14.94 (1.7)
9.67 acetylfuran 乙酰呋喃 呋喃 1.73±0.16c 2.15±0.02a 1.92±0.02b 1.58±0.06d
总含量(占比/%) 1.73 (0.1) 2.15 (0) 1.92 (0) 1.58 (0)
5.41 toluene 甲苯 3.67±0.41a 1.65±0.06b 1.24±0.12c 1.29±0.05c
35.92 2,4-di-t-butylphenol 2,4-二叔丁基酚 56.75±6.57a 17.61±0.42b 14.00±0.31b 12.68±0.28b
总含量(占比/%) 60.42 (3.9) 19.25 (0.2) 15.24 (1.4) 13.97 (1.6)
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电子鼻技术与气相色谱-质谱法鉴别蜂蜜掺假
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问亚琴 , 罗帅 , 田维娜 , 杨国伟 , 赵新颖 *
食品安全质量检测学报 | 本期专题:食品品质分析与评价 2025,16(4): 126-136
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食品安全质量检测学报 | 本期专题:食品品质分析与评价 2025, 16(4): 126-136
电子鼻技术与气相色谱-质谱法鉴别蜂蜜掺假
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问亚琴 , 罗帅, 田维娜, 杨国伟, 赵新颖*
作者信息
  • 北京电子科技职业学院生物工程学院, 北京 100176
  • 问亚琴(1989—), 女, 博士, 副教授, 主要研究方向为食品风味分析。E-mail:

通讯作者:

* 赵新颖(1981—), 女, 教授, 主要研究方向为分离纯化与分析测试技术。E-mail:
Identification of honey adulteration based on electronic nose and gas chromatography-mass spectrometry
Ya-Qin WEN , Shuai LUO, Wei-Na TIAN, Guo-Wei YANG, Xin-Ying ZHAO*
Affiliations
  • Beijing Polytechnic, College of Biotechnology, Beijing 100176, China
出版时间: 2025-02-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20240928001
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目的 探究油菜蜜掺假样品和糖浆掺假样品与真实蜂蜜气味差异和挥发性物质差异。方法 构建5%、10%、20%、30%不同比例糖浆掺假和蜜源掺假样品, 采用电子鼻技术和顶空固相微萃取结合气相色谱-质谱技术(solid-phase microextraction and gas chromatography-mass spectrometry, HS-SPME-GC-MS)分析掺假样品和真实蜂蜜样品的气味和挥发性物质。结果 电子鼻(electronic nose, E-nose)结合主成分分析((principal component analysis, PCA)和稀疏偏最小二乘法判别分析(sparse partial least squares-discriminant analysis, sPLS-DA)可以区分椴树蜜、枣花蜜、洋槐蜜不同蜜源蜂蜜, 能区分糖浆掺假样品与真实蜂蜜, 但不能区分洋槐蜜与油菜蜜掺假样品。GC-MS结果表明, 洋槐蜜、椴树蜜和枣花蜜中共鉴定出62种挥发性化合物, 洋槐蜜中醇类物质含量最高, 枣花蜜中醛类物质含量最高, 椴树蜜中萜烯类物质含量最高, 挥发性物质含量结合sPLS-DA可以区分100%洋槐蜜、100%椴树蜜和5%~30%糖浆掺假、5%~30%油菜蜜掺假样品。结论 基于E-nose气味分析和GC-MS挥发性物质分析结合化学计量学分析可以进行糖浆掺假和油菜蜜掺假蜂蜜样品鉴别, 研究结果为蜂蜜溯源和掺假鉴别研究提供参考。

蜂蜜掺假  /  植物源鉴别  /  挥发性物质  /  电子鼻  /  气相色谱-质谱法

Objective To explore of odor differences and volatile differences between rape honey-adulterated and syrup-adulterated samples and real honey. Methods Different proportions of 5%, 10%, 20% and 30% syrup-adulterated and rape honey-adulterated samples were constructed, and the electronic nose technique and headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to analyze the odors and volatiles of the adulterated and authentic honey samples. Results The electronic nose (E-nose) combined with the principal component analysis (PCA) and sparse partial least squares discriminant analysis (sPLS-DA) could distinguish different botanical honey of linden honey, jujube honey acacia honey, and could distinguish syrup-adulterated samples from real honey, but could not distinguish rape honey-adulterated samples from acacia honey. The GC-MS results showed that 62 kinds of volatile compounds were identified in acacia honey, linden honey and jujube honey, with the highest content of alcohols in acacia honey, aldehydes in jujube honey, terpenes in linden honey. The content of volatile compounds in combination with sPLS-DA could distinguish 100% acacia honey, 100% linden honey from 5%-30% syrup-adulterated samples and 5%-30% rape honey-adulterated samples. Conclusion The odor analysis and volatiles analysis based on E-nose and GC-MS combined with chemometrics analysis can be used to identify syrup-adulterated and rape honey-adulterated samples. The results of the study provide a reference for honey traceability and adulteration identification studies.

honey adulteration  /  identification of botanical origin  /  volatile compounds  /  electronic nose  /  gas chromatography-mass spectrometry
问亚琴, 罗帅, 田维娜, 杨国伟, 赵新颖. 电子鼻技术与气相色谱-质谱法鉴别蜂蜜掺假. 食品安全质量检测学报, 2025 , 16 (4) : 126 -136 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20240928001
Ya-Qin WEN, Shuai LUO, Wei-Na TIAN, Guo-Wei YANG, Xin-Ying ZHAO. Identification of honey adulteration based on electronic nose and gas chromatography-mass spectrometry[J]. Journal of Food Safety & Quality, 2025 , 16 (4) : 126 -136 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20240928001
蜂蜜作为一种传统的食品, 具有悠久的食用历史。现代科学研究证明蜂蜜具有显著的抗氧化和抗菌活性等生理活性作用, 有益于人体健康[1-2]。蜂蜜深受消费者的喜爱, 而实际生产的蜂蜜产量远远满足不了市场的需求, 在利益的驱动下, 蜂蜜掺杂使假的现象时有发生[3-4], 常见的蜂蜜掺假方式有2种, 糖浆掺假, 掺入果脯糖浆等廉价糖浆冒充天然蜂蜜[5]; 蜜源掺假, 便宜单花蜜掺入优质单花蜜获取暴利, 如将售价较低的油菜蜜掺入价格较高的洋槐蜜、枣花蜜和椴树蜜等[6]。蜂蜜掺假极大损害了蜂农、消费者和正规蜂蜜生产企业的利益, 严重影响了蜂蜜产品的市场秩序和我国蜂蜜的出口贸易[7]
对掺假蜂蜜的鉴别研究一直是蜂产业研究的热点和难点。由于蜂蜜成分复杂、内部组分含量变化范围大等特征使得掺假造假容易, 也使得蜂蜜品质检测技术遇到了很大的挑战。近年来, 随着仪器分析的发展, 有学者使用不同仪器检测技术研究蜂蜜掺假鉴别[8-9], 主要包括红外光谱法[10]、荧光分光光度法[11]、拉曼光谱法[12], 气相色谱法[13-14]、液相色谱法[15]、薄层色谱法[5], 核磁共振法[16]、稳定同位素比值质谱法[17], 电子鼻[18-19]、电子舌[20]、电泳法[21]、DNA技术[22]等。这些方法各有优缺点和局限性, 近年来, 研究者焦点又集中在利用蜂蜜中固有化合物开发鉴别其真实性的方法, 如蜂蜜中的植物次级代谢产物, 包括挥发性物质[3]
蜂蜜含有多种挥发性物质, 目前已鉴定出的化合物有600多种[23]。不同产地、植物源的蜂蜜都具有自己独特的挥发性成分轮廓, 这个轮廓能够较为全面地揭示蜂蜜成分的复杂性和相关性, 反映蜂蜜样品的信息差异, 国内外已有很多利用挥发性成分进行蜂蜜品种鉴别和真实性鉴别的研究[24-25], 如龙门等[6]利用气相色谱-离子迁移谱法区分不同比例油菜蜜混合洋槐蜜。梁冬爽[26]对椴树蜜、油菜蜜、枣花蜜、荆条蜜、薰衣草蜜和洋槐蜜的挥发性成分进行了分析, 发现不同蜜源植物的蜂蜜挥发性成分存在差异, 应用化学计量学方法对6种蜂蜜可以准确分类。以上研究说明挥发性成分的分析是鉴别蜂蜜来源、品种掺假的有效途径。龙门等[6]研究表明感官分析方法辨别油菜蜜掺入洋槐蜜的混合比例为50%以上, 那么对于低比例(<50%)掺假样品, 基于挥发性物质进行鉴别的研究效果还较少。电子鼻是一种模拟嗅觉的电子系统, 可识别简单或复杂的气体成分, 广泛应用于蜂蜜[27-28]、牛奶等其他食品的掺假检测[29]。电子鼻气味分析无需对样品进行处理, 检测速度快, 操作简便。但是, 电子鼻不能对样品中的挥发性成分进行定性或定量, 在蜂蜜挥发性成分的研究中, 电子鼻常结合其他的方法来共同对蜂蜜样品进行测定分析。气相色谱-质谱(gas chromatography-mass spectrometry, GC-MS)技术是常用的挥发性物质分析方法, GC-MS技术既能够高效分离挥发性成分, 又能对其进行专属定性定量, 已广泛应用于蜂蜜中挥发性成分的检测及鉴定。本研究拟采用电子鼻技术以及GC-MS技术, 研究真实蜂蜜样品和构建的不同比例糖浆掺假和油菜蜜掺假样品气味和挥发性成分差异, 结合化学统计学方法对掺假蜂蜜进行鉴别, 为蜂蜜来源鉴定及掺假鉴别提供理论依据和数据支撑。
蜂蜜样品椴树蜜(DS)采自辽宁省抚顺市、枣花蜜(ZH)采自陕西延安市、成熟洋槐蜜(CSYH)采自山西沁水、加工洋槐蜜来自陕西(九蜂堂蜂产品有限公司), 所有蜂蜜样品由蜂场直接采集, 在蜜源植物盛花期进行采集, 椴树蜜在2017年7月采集, 枣花蜜在2017年6月采集, 洋槐蜜在2017年4—5月份采集, 保证了样品的真实性。
香气标准品(纯度>97%, 美国Sigma公司、北京百灵威科技有限公司), 用甲醇配制30种香气物质的标准储备液, 于4 ℃条件下保存, 保存期为6个月; 氯化钠、葡萄糖、果糖、氢氧化钠(分析纯, 北京化学试剂公司); 甲醇(色谱纯, 美国Sigma公司)。
PEN3电子鼻系统(德国AIRSENSE公司); 7890B GC-5977B MS气相色谱与质谱联用仪、J&W HP-DB-5石英毛细柱(30 m×0.25 mm, 0.25 µm)(美国安捷伦公司); CTC CombiPAL自动进样装置(瑞士茨温根公司); Milli-Q超纯水装置(美国Millipore公司); DVB/CAR/PDMS SPME萃取头(美国Supelco公司)。
糖浆掺假蜂蜜样品构建: 选择目前市场上常见的糖浆(F45)为掺假物质, 按照5%、10%、20%、30%的比例混入不同品种蜜, 混合均匀, 室温条件(20 ℃)储存1年, 取样测定。蜜源掺假蜂蜜样品构建: 根据市场上常见的掺假方式, 将油菜蜜(YC)按照5%、10%、20%、30%的比例混入洋槐蜜、椴树蜜和枣花蜜, 混合均匀, 然后在室温条件(20 ℃)储存1年, 取样测定。掺假蜂蜜样品具体信息及编号如表1所示。
分别称取2 g样品至100 mL烧杯中, 双层保鲜膜封口, 室温下静置30 min后上机测试。采用直接顶空吸气法, 直接将进样针头插入含样品的顶空瓶中, 进行电子鼻测定。测定条件: 采样时间为1 s/组; 传感器自清洗时间为80 s; 传感器归零时间为5 s; 样品准备时间为5 s; 进样流量为400 mL/min; 分析采样时间为80 s。每个样品重复测定3次。
(1)蜂蜜香气成分提取
蜂蜜香气成分的萃取利用文献中的香气顶空固相微萃取方法[30], 略加修改。具体操作如下: 称取蜂蜜2.0 g于15 mL顶空固相微萃取专用样品瓶中, 加入2 mL蒸馏水和0.8 g NaCl和10 μL内标4-甲基-2-戊醇, 置于磁力加热搅拌台上加热, 于60 ℃下平衡30 min, 使用DVB/ CAR/PDMS萃取头萃取40 min。在GC进样口解析5 min。每个样品重复测定3次。
(2)色谱条件
色谱柱: J&W HP-DB-5石英毛细柱(30 m×0.25 mm, 0.25 µm); 升温程序: 50 ℃保持1 min, 以3 ℃/min升至220 ℃, 保持5 min; 载气(He)流速为1 mL/min, 进样口温度为260 ℃, 采用不分流模式。
(3)质谱条件
电子轰击离子源; 电子能量70 eV; 离子源温度230 ℃; 四极杆温度为150 ℃, 质谱接口温度280 ℃, 质量扫描范围m/z 30~350。
(4)香气物质定性定量分析
对于有标准品的香气物质, 依据本研究已建立的相同色谱条件下该化合物的保留指数和质谱信息进行定性分析。没有标样的香气物质, 利用文献报道中相似色谱条件下该化合物的保留指数以及NIST17标准谱库比对结果进行半定性分析; 对于文献中未报道相似色谱条件下化合物保留指数的香气物质, 则根据NIST17标准谱库比对结果进行半定性分析。
根据蜂蜜中糖含量和pH范围, 用pH 4.5的磷酸缓冲液配制含45 g/L果糖和35 g/L葡萄糖的水溶液作蜂蜜模式溶液。按照蜂蜜样品各类香气化合物的浓度水平, 分别称取不同量的已有香气化合物标样用甲醇溶解, 将各类香气标样溶液混合配制标准母液, 连续梯度稀释10个不同浓度, 建立蜂蜜香气物质标准曲线(香气化合物标样与内标化合物质的质谱选择离子扫描的峰面积比/该香气化合物标样的浓度)。对于已有标样的香气物质利用其相应的标准曲线来进行定量, 没有标样的香气物质利用化学结构相似, 碳原子数相近的标样香气物质的标准曲线进行半定量。
电子鼻数据聚类分析, 本研究提取10个传感器的特征值, 然后采用主成分分析((principal component analysis, PCA)和稀疏偏最小二乘法判别分析(sparse partial least squares-discriminant analysis, sPLS-DA)作为主要区别分析方法。统计分析在代谢组学网站进行(http://www.metaboanalyst.ca/), 所有分析是在数据进行标准化处理后进行。
从电子鼻原始信号图(图1)可以看出, 电子鼻对蜂蜜有明显的应答, 整个测试过程中传感器的响应明显。蜂蜜在密封过程中容易形成顶空浓度比较高的积累, 故测试开始的前10 s内所有传感器的响应均会很强(尤其是2、7、9号), 且达到峰值, 后响应值迅速降低, 最后逐渐趋于平稳; 整个测试过程中对蜂蜜响应较强烈的传感器主要是2号(小分子氮氧化物类气体敏感)、7号(无机硫类气体敏感)和9号(有机硫类气体敏感), 其次6号(甲烷等短链烷烃灵敏)、8号(醇醚醛酮类灵敏)传感器的响应值也较为明显, 其他传感器在整个测试过程中无明显变化, 响应值均在1左右。结果显示在采集时间为70 s时电子鼻传感器的信号响应值曲线趋于平缓, 为保证检测数据的准确性和稳定性, 后续气味差异分析基于70~72 s数据进行。
为了更好地分析洋槐蜜、椴树蜜和枣花蜜气味差异, 基于10个传感器采集数据进行PCA分析, 结果如图2所示, PCA中, 第一和第二主成分累积贡献率之和达到99%以上, 基本上涵盖了样本的大部分原始信息, 其中第一主成分的贡献率为89.0%, 第二主成分的贡献率为10.5%, 可见样品之间的差异主要表现在第一主成分上(图2A)。
sPLS-DA也是一种聚类分析的方法, 在sPLS-DA分析中会尽量缩小组内的差异, 扩大组间的差异。sPLS-DA分析结果表明两个主成分的贡献率同样达到95%以上, 缩小组内的差异后, 第一主成分可以将洋槐蜜和椴树蜜、枣花蜜区分开来(图2B)。这和其他研究者结果相似, 利用电子鼻结合聚类分析可以区分不同植物源蜂蜜[28]
从sPLS-DA分析结果可见(图3A), 100%枣花蜜(ZH)与不同比例糖浆掺假和油菜蜜掺假样品在气味上差异非常明显, 不同掺假比例样品的分析数据点分布于各自区域, 没有重叠, 说明电子鼻结合sPLS-DA分析能准确鉴别枣花蜜与掺假模型蜂蜜气味差异。
椴树蜜(DS)与不同比例油菜蜜掺假样品在气味上差异较大(图3B), 在图中被明显分为两类, 椴树蜜分布在sPLS-DA图右侧, 添加不同比例油菜蜜的4个样品在图中集中重叠分布在左侧, 表明电子鼻结合sPLS-DA分析能准确鉴别椴树蜜与添加不同比例油菜蜜的蜂蜜样品。
洋槐蜜选择了洋槐蜜(YH)和天然成熟洋槐蜜(CSYH)进行蜂蜜掺假鉴别研究。洋槐蜜掺假组sPLS-DA结果如图3C所示, 图中, 添加不同比例糖浆掺假样品与洋槐蜜在气味上差异非常明显, 被分成两类, 而油菜蜜掺假样品与100%洋槐蜜样品没有完全分离, 尤其是低比例油菜蜜掺假样品YH5YC和YH10YC与洋槐蜜三者图形重叠(图3C), 说明3个样品在气味上非常接近, 添加量少于10%的油菜蜜与常规洋槐蜜在气味上还是比较难区分。
天然成熟洋槐蜜掺假组sPLS-DA结果表明(图3D), 不同比例油菜蜜掺假样品与天然成熟洋槐蜜分布在图右侧, 低比例(<20%)糖浆掺假样品和油菜掺假样品的6个数据点在图中重叠在一起, 与天然成熟洋槐蜜不能完全区分, 而添加20%糖浆样品CSYH20F45和30%糖浆样品CSYH30F45分布在图左侧, 与天然成熟洋槐蜜可以完全区分。说明电子鼻结合sPLS-DA分析能准确鉴别天然成熟洋槐蜜与高比例糖浆掺假样品。
电子鼻主要对样品的整体风味进行分析检测, 能直观地反映蜂蜜与掺假蜂蜜整体气味的差异, 但不能对风味物质的具体种类和含量进行分析, 为进一步了解掺假蜂蜜与真实蜂蜜挥发性成分的差异, 提高基于气味差异的油菜蜜掺假样品的鉴别, 采用SPME-GC-MS分析了掺假蜂蜜样品的挥发性物质。
3种不同植物源蜂蜜的挥发性成分种类及含量存在较大差异(表2), 从3种蜂蜜样品中共检测出62种挥发性成分, 其中醇类化合物6种、醛类12种、酸类4种、酯类2种、酮类3种、萜烯类28种、C13降异戊二烯类4种, 呋喃1种, 苯类2种。3种蜂蜜中挥发性成分含量比例不同, 洋槐蜜中主要为醇类、酸类和萜烯类物质, 占比分别为48.8%、20.5%、18.4% (天然成熟洋槐蜜), 枣花蜜中主要为醛类、酸类和醇类, 分别占总挥发性成分的34.0%、29.9%和18.0%, 这与前人关于醛类物质是蜂蜜风味的重要来源相一致[18-19]。椴树蜜含有萜烯类物质较多, 占总挥发性成分的75.9%, 其次是醇类物质, 占总挥发性成分的15.0%。
醇类物质中, 苯乙醇、苯甲醇在3种蜂蜜中含量均较高, 苯乙醇在椴树蜜中含量显著高于其他两种蜂蜜, 这和其他研究者结果一致[6], 其次是2-乙基-1-己醇。醛类物质中苯乙醛在3种蜂蜜中含量最高, 这和其他研究者结果一致, 在椴树蜜、枣花蜜和洋槐蜜中也检测到较高含量的苯乙醛[24,26]。枣花蜜中壬醛、2-羟基苯甲醛和苯甲醛含量也较高, 天然成熟洋槐蜜中糠醛含量高于加工洋槐蜜, 这可能和天然成熟洋槐蜜在蜂巢中成熟时间较长有关, 糠醛是天然存在蜂蜜中的一种化合物, 可能是热加工过程或者长期储存过程中美拉德反应的产物。酸类中含量最高的是壬酸, 其次是乙酸和己酸。萜烯类在椴树蜜中种类和含量都最高, 香茅酸只在椴树蜜中检测到。另外, 里那醇、脱氢芳樟醇、顺/反式氧化里那醇氧化物、脱氢对伞花烃在3种蜂蜜中都检测到较高含量, 这和其他研究者结果相似, 里那醇衍生物是蜂蜜中常见的挥发性成分[26]
为了进一步探究掺假蜂蜜样品与100%蜂蜜样品之间挥发性成分差异, 分析了100%洋槐蜜、100%椴树蜜、及其掺假样品的挥发性成分并进行sPLS-DA分析, 结合变量重要性投影值(variable importance projection, VIP)及P<0.05筛选出潜在的差异化合物。
天然成熟洋槐蜜模型中, 100%天然成熟洋槐蜜样品分布在主成分得分散点图第四象限, 糖浆掺假样品、油菜蜜掺假样品各自聚集在一起, 分布在其他象限(图4A), 主成分1可以区分100%天然成熟洋槐蜜与不同比例糖浆掺假样品, 主成分1贡献率较大物质有壬醛、苯甲醛、脱氢芳樟醇、反式里那醇氧化物、苯乙醇(图4B); 主成分2可以区分100%天然成熟洋槐蜜与不同比例油菜蜜掺假样品, 主成分2贡献率较大物质有2-羟基苯甲醛、2-甲基-1-丁醛、乙酸醋酸酯、里那醇、3-甲基-1-丁醛(图4C)。
洋槐蜜模型中, 100%洋槐蜜样品、糖浆掺假样品、油菜蜜掺假样品各自聚集在一起, 分离效果较好, 第一主成分可以区分100%加工洋槐蜜与掺假样品, 第二主成分可以区分100%加工洋槐蜜与不同比例油菜掺假样品(图5A)。第一主成分贡献率较大物质有2-羟基苯甲醛、苯乙醛、己酸、糠醛(图5B), 第二主成分贡献率较大物质有3-甲基-1-丁醛、2-甲基-1-丁醛、脱氢芳樟醇、乙酸(图5C)。对比电子鼻对低比例油菜蜜掺假样品YH5YC和YH10YC与洋槐蜜区分效果较差, sPLS-DA结合挥发性物质分析, 可以提升区分效果。
椴树蜜模型中, 100%椴树蜜样品、糖浆掺假样品、油菜蜜掺假样品各自聚集在一起, 分布在不同象限, sPLS-DA可以完全区分3种类型样品(图6A), 第一主成分可以区分100%椴树蜜与不同比例油菜蜜掺假样品, 第一主成分贡献率较大物质有脱氢芳樟醇、藏红花醛、己酸,、苯甲醇(图6B); 第二主成分可以区分100%椴树蜜与不同比例糖浆掺假样品、油菜掺假样品, 贡献率较大物质有2-羟基苯甲醛、脱氢对伞花烃、顺式玫瑰醚、反式玫瑰醚、香茅酸(图6C)。
随着添加比例增加, 掺假样品与真蜂蜜样品距离也越远, 以上结果可见, 利用挥发性成分结合sPLS-DA可以将成熟洋槐蜜、加工洋槐蜜、椴树蜜与不同比例糖浆掺假蜂蜜样品和油菜掺假蜂蜜样品分开, 这与其他研究结果相一致[6], 说明基于挥发性物质进行蜂蜜品种鉴别和掺假鉴别具有一定的应用潜力。
蜂蜜掺假鉴别一直是蜂产业的研究难点。本研究构建了低比例糖浆掺假样品和低比例油菜蜜掺假样品, 采用电子鼻和HS-SPME-GC-MS分析了3种不同蜜源蜂蜜和掺假蜂蜜的气味差异和挥发性物质差异, 基于PCA、sPLS-DA方法的电子鼻检测能很好地区分枣花蜜、洋槐蜜和椴树蜜3种不同蜜源蜂蜜, 可以区分不同蜜源蜂蜜与糖浆掺假样品, 但是对洋槐蜜与不同比例油菜蜜掺假样品无法区分。HS-SPME-GC-MS从3种蜂蜜中共鉴定出62种挥发性化合物, 枣花蜜、洋槐蜜和椴树蜜挥发性物质组成和含量存在显著差异, 洋槐蜜中醇类物质含量最高, 枣花蜜中醛类物质含量最高, 椴树蜜中萜烯类物质含量最高, 基于挥发性物质含量结合sPLS-DA分析可以对100%洋槐蜜、100%椴树蜜和不同比例糖浆掺假和油菜蜜掺假蜂蜜样品进行区分。基于挥发性物质构建sPLS-DA模型对低比例油菜蜜(<50%)掺假样品区分效果要高于电子鼻气味模型。通过电子鼻和GC-MS结合统计学分析为蜂蜜挥发性物质组成和蜂蜜溯源、品质提供了理论依据和技术支撑。
蜜源掺假中最常用的就是蜜源相对丰富、价格较低的油菜蜜, 在本研究中, 构建了不同比例油菜蜜掺入洋槐蜜和椴树蜜样品, 基于电子鼻和HS-SPME-GC-MS构建鉴别模型表明, 基于挥发性物质进行油菜蜜掺入其他蜜源蜂蜜鉴别是一种可行的有效的方法。本研究中糖浆掺假模型中只用一种糖浆, 而在实际应用中掺假的物质可能不止一种, 在以后的研究中可以探索多种糖浆掺假物; 另外, 本研究中不同蜜源蜂蜜数量和构建的掺假样品数量有限, 未来研究中应加大不同地理来源、不同加工方式蜂蜜的采集, 扩大样品数量, 进一步提升鉴别模型的区分能力, 为蜂蜜蜜源鉴别和掺假鉴别提供新的思路和方法。
  • 北京市属高等学校优秀青年人才培育计划项目(BPHR202203242)
  • 北京市教育委员会科学研究计划项目(KM201910858003)
  • 北京市科学技术协会青年人才托举工程项目(BYESS2022135)
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2025年第16卷第4期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20240928001
  • 接收时间:2024-09-28
  • 首发时间:2025-07-21
  • 出版时间:2025-02-25
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  • 收稿日期:2024-09-28
基金
北京市属高等学校优秀青年人才培育计划项目(BPHR202203242)
北京市教育委员会科学研究计划项目(KM201910858003)
北京市科学技术协会青年人才托举工程项目(BYESS2022135)
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    北京电子科技职业学院生物工程学院, 北京 100176

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* 赵新颖(1981—), 女, 教授, 主要研究方向为分离纯化与分析测试技术。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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