Article(id=1151881496953500112, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1151881493552394994, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250303002, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1740931200000, receivedDateStr=2025-03-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752559549797, onlineDateStr=2025-07-15, pubDate=1748102400000, pubDateStr=2025-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752559549797, onlineIssueDateStr=2025-07-15, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752559549797, creator=13701087609, updateTime=1752559549797, updator=13701087609, issue=Issue{id=1151881493552394994, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='10', pageStart='1', pageEnd='324', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752559548986, creator=13701087609, updateTime=1756202008453, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1167159075906265916, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1151881493552394994, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1167159075906265917, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1151881493552394994, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=43, endPage=50, ext={EN=ArticleExt(id=1151923893410345663, articleId=1151881496953500112, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Characterization and analysis of volatile compounds in crude fat of Trachinotus ovatus by gas chromatography-ion mobility spectrometry combined with electronic-nose, columnId=1151923892194472566, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Research of Food Flavor, runingTitle=null, highlight=null, articleAbstract=

Objective To systematically analyze the characteristics of volatile compounds in the crude fat of Trachinotus ovatus by gas chromatography-ion mobility spectrometry (GC-IMS) combined with electronic-nose. Methods GC-IMS was used to qualitatively and quantitatively analyze the volatile compounds in the crude fat of different parts (head, abdomen and viscera) of Trachinotus ovatus, focusing on the identification of differences in key flavor components such as alcohols, ketones, acids and aldehydes. Combined with electronic-nose technology, the overall flavor profile of crude fat in each part was characterized to further evaluate the contribution of major volatile compounds to flavor formation. Results The crude fat in different parts of Trachinotus ovatus belonged to high-quality lipids, but there were significant differences in the composition of volatile components. The fish head group was mainly composed of alcohols and ketones. The abdominal group was dominated by alcohols, alkanes and acids; the visceral group contained higher volatile acids. Conclusion This study reveals the differences in volatile compounds in different parts of Trachinotus ovatus, provides theoretical support for its flavor regulation, and also provides guidance for the high-value utilization of by-products such as viscera.

, correspAuthors=Xiao-Guo YING, 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=Yu-Xiang WANG, Ji-Xiang ZHANG, Chen-Yang ZHAO, Jia-Yu PAN, Fei-Fan WU, Jin-Ming YE, Xiao-Guo YING, Shang-Gui DENG, Lu-Kai MA), CN=ArticleExt(id=1151923915623379360, articleId=1151881496953500112, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=气相色谱-离子迁移谱法与电子鼻联用对金鲳鱼粗脂肪特征挥发性化合物表征及分析, columnId=1151923892316107385, journalTitle=食品安全质量检测学报, columnName=专题:食品风味研究, runingTitle=null, highlight=null, articleAbstract=

目的 结合气相色谱-离子迁移谱法(gas chromatography-ion mobility spectrometry, GC-IMS)与电子鼻联用技术, 系统分析金鲳鱼粗脂肪中的挥发性化合物特征。方法 采用GC-IMS对金鲳鱼不同部位(鱼头、腹部及内脏)粗脂肪中的挥发性化合物进行定性和定量分析, 重点识别醇、酮、酸和醛类等关键风味组分的差异。结合电子鼻技术对各部位粗脂肪的整体风味轮廓进行表征, 进一步评估主要挥发性化合物对风味形成的贡献。结果 金鲳鱼不同部位粗脂肪均属于优质脂质, 但在挥发性成分组成上存在显著差异, 鱼头组主要为醇和酮类化合物; 腹部组则以醇、烷烃和酸类物质为主; 内脏组含有较高的挥发性酸类物质。结论 本研究揭示了金鲳鱼不同部位挥发性化合物的差异, 为其风味调控提供了理论支持, 也为副产物如内脏的高值化利用提供了方向指引。

, correspAuthors=应晓国, authorNote=null, correspAuthorsNote=
* 应晓国(1989—), 男, 博士, 副教授, 主要研究方向为水产品冷链物流、水产品精深加工与贮藏。E-mail:
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#王钰翔和张吉祥为共同第一作者

王钰翔(2000—), 女, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

张吉祥(1997—), 男, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

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王钰翔(2000—), 女, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

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王钰翔(2000—), 女, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

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张吉祥(1997—), 男, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

"}, bioImg=null, bioContent=

张吉祥(1997—), 男, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

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Journal of Chinese Institute of Food Science and Technology, 2022, 22(11): 343-354., articleTitle=GC-IMS-based fingerprint analysis of volatile compounds in Fuliji roast chicken, refAbstract=null), Reference(id=1167158792576836165, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=6, pageStart=431, pageEnd=440, url=null, language=null, rfNumber=[29], rfOrder=52, authorNames=姜鹏飞, 柳杨, 张浩, journalName=中国食品学报, refType=null, unstructuredReference=姜鹏飞, 柳杨, 张浩, 等. 气相色谱-离子迁移谱在水产领域的应用[J]. 中国食品学报, 2023, 23(6): 431-440., articleTitle=气相色谱-离子迁移谱在水产领域的应用, refAbstract=null), Reference(id=1167158792719442502, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=6, pageStart=431, pageEnd=440, url=null, language=null, rfNumber=[29], rfOrder=53, authorNames=JIANG PF, LIU Y, ZHANG H, journalName=Journal of Chinese Institute of Food Science and Technology, refType=null, unstructuredReference=JIANG PF, LIU Y, ZHANG H, et al. 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Science and Technology of Food Industry, 2021, 42(19): 106-117., articleTitle=Analysis of flavor characteristics of five aquatic raw materials based on electronic nose, HS-GC-IMS and HS-SPME-GC-MS, refAbstract=null), Reference(id=1167158792924963401, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=8, pageStart=486, pageEnd=501, url=null, language=null, rfNumber=[31], rfOrder=56, authorNames=李帅, 柴春祥, 刘建福, journalName=中国食品学报, refType=null, unstructuredReference=李帅, 柴春祥, 刘建福. 机器学习算法在食品气味表征中的应用[J]. 中国食品学报, 2024, 24(8): 486-501., articleTitle=机器学习算法在食品气味表征中的应用, refAbstract=null), Reference(id=1167158792992072266, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=8, pageStart=486, pageEnd=501, url=null, language=null, rfNumber=[31], rfOrder=57, authorNames=LI S, CHAI CX, LIU JF, journalName=Journal of Chinese Institute of Food Science and Technology, refType=null, unstructuredReference=LI S, CHAI CX, LIU JF. Application of machine learning algorithms in food odor characterization[J]. Journal of Chinese Institute of Food Science and Technology, 2024, 24(8): 486-501., articleTitle=Application of machine learning algorithms in food odor characterization, refAbstract=null)], funds=[Fund(id=1167158788806156811, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, awardId=32302135, language=CN, fundingSource=国家自然科学基金项目(32302135), fundOrder=null, country=null), Fund(id=1167158788864877068, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, awardId=32072291, language=CN, fundingSource=国家自然科学基金项目(32072291), fundOrder=null, country=null), Fund(id=1167158788923597325, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, awardId=2024CXTD16, language=CN, fundingSource=广东省现代农业产业共性关键技术研发创新团队建设项目(加工与保鲜共性关键技术)(2024CXTD16), fundOrder=null, country=null), Fund(id=1167158788999094798, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, awardId=2023C03006, language=CN, fundingSource=大宗水产品预制菜肴加工关键技术研发项目(2023C03006), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1167158785027088831, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, xref=null, ext=[AuthorCompanyExt(id=1167158785035477440, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, companyId=1167158785027088831, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. Key Laboratory of Health Risk Factors for Seafood of Zhejiang Province, Food and Pharmacy College, Zhejiang Ocean University, Zhoushan 316022, China), AuthorCompanyExt(id=1167158785043866049, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, companyId=1167158785027088831, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.浙江省海鲜健康危险因素重点实验室, 浙江海洋大学食品药学学院, 舟山 316022)]), AuthorCompany(id=1167158785119363522, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, xref=null, ext=[AuthorCompanyExt(id=1167158785123557827, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, companyId=1167158785119363522, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Marine Science and Technology College, Zhejiang Ocean University, Zhoushan 316022, China), AuthorCompanyExt(id=1167158785131946436, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, companyId=1167158785119363522, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.浙江海洋大学海洋科学与技术学院, 舟山 316022)]), AuthorCompany(id=1167158785203249605, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, xref=null, ext=[AuthorCompanyExt(id=1167158785211638214, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, companyId=1167158785203249605, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3. Key Laboratory of Green Processing and Intelligent Manufacturing of Lingnan Specialty Food, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology, College of Food Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China), AuthorCompanyExt(id=1167158785215832519, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, companyId=1167158785203249605, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.农村部岭南特色食品绿色加工与智能制造重点实验室, 广东省岭南特色食品科学与技术重点实验室, 仲恺农业工程学院轻工食品学院, 广州 510225)])], figs=[ArticleFig(id=1167158787984073214, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=EN, label=Fig.1, caption=Extraction rate (A), acid value (B) and POV (C) of crude fat from different parts of Trachinotus ovatus, figureFileSmall=tpaCLayx9pG65k/z0g5mxA==, figureFileBig=w9IesAIfOnKTNwkw6o6Haw==, tableContent=null), ArticleFig(id=1167158788030210559, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=CN, label=图1, caption=金鲳鱼不同部位粗脂肪提取率(A)、酸价(B)和POV (C)

注: 不同小写字母表示显著性差异(P<0.05)。

, figureFileSmall=tpaCLayx9pG65k/z0g5mxA==, figureFileBig=w9IesAIfOnKTNwkw6o6Haw==, tableContent=null), ArticleFig(id=1167158788080542208, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=EN, label=Fig.2, caption=GC-IMS spectra of volatile organic compounds in crude fat of different parts of Trachinotus ovatus (comparison of differences), figureFileSmall=EuiyC8EU+MbY2LJDTpcQSg==, figureFileBig=M4yGUIv1+K55GRB5yL0D/g==, tableContent=null), ArticleFig(id=1167158788143456769, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=CN, label=图2, caption=金鲳鱼不同部位粗脂肪中的挥发性有机物的GC-IMS谱图(差异对比), figureFileSmall=EuiyC8EU+MbY2LJDTpcQSg==, figureFileBig=M4yGUIv1+K55GRB5yL0D/g==, tableContent=null), ArticleFig(id=1167158788210565634, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=EN, label=Fig.3, caption=Content of volatile organic compounds in crude fat of different parts of Trachinotus ovatus, figureFileSmall=SAKzBIywj+rtxAnKsc60TA==, figureFileBig=e0AeADqfxjKfDvE3lAB9zg==, tableContent=null), ArticleFig(id=1167158788269285892, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=CN, label=图3, caption=金鲳鱼不同部位粗脂肪中挥发性有机物的含量图, figureFileSmall=SAKzBIywj+rtxAnKsc60TA==, figureFileBig=e0AeADqfxjKfDvE3lAB9zg==, tableContent=null), ArticleFig(id=1167158788332200453, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=EN, label=Fig.4, caption=Gallery Plot (fingerprinting) of volatile organic compounds in crude fat of different parts of Trachinotus ovatus, figureFileSmall=oEucgOXWMFbMJ3ySqmakDQ==, figureFileBig=4/Xj25e6IHrDxMGR5Ft5ig==, tableContent=null), ArticleFig(id=1167158788390920710, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=CN, label=图4, caption=金鲳鱼不同部位粗脂肪中挥发性有机物的Gallery Plot图(指纹图谱), figureFileSmall=oEucgOXWMFbMJ3ySqmakDQ==, figureFileBig=4/Xj25e6IHrDxMGR5Ft5ig==, tableContent=null), ArticleFig(id=1167158788445446663, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=EN, label=Fig.5, caption=Electronic-nose radargram and PCA diagram of crude fat in different parts of Trachinotus ovatus, figureFileSmall=NN1iqJqJcV4d+R+oqjUNeQ==, figureFileBig=/e+5Vm8t5/S0DHLeYHwq4Q==, tableContent=null), ArticleFig(id=1167158788508361224, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=CN, label=图5, caption=金鲳鱼不同部位粗脂肪电子鼻雷达图和PCA图, figureFileSmall=NN1iqJqJcV4d+R+oqjUNeQ==, figureFileBig=/e+5Vm8t5/S0DHLeYHwq4Q==, tableContent=null), ArticleFig(id=1167158788562887177, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=EN, label=Table 1, caption=

Analysis of physical and chemical indicators of Trachinotus ovatus

, figureFileSmall=null, figureFileBig=null, tableContent=
理化项目 含量
2-MIB <0.044 μg/kg
土臭素 <0.044 μg/kg
灰分 0.66 g/100 g
蛋白 15.2 g/100 g
), ArticleFig(id=1167158788625801738, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1151881496953500112, language=CN, label=表1, caption=

金鲳鱼理化指标分析

, figureFileSmall=null, figureFileBig=null, tableContent=
理化项目 含量
2-MIB <0.044 μg/kg
土臭素 <0.044 μg/kg
灰分 0.66 g/100 g
蛋白 15.2 g/100 g
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气相色谱-离子迁移谱法与电子鼻联用对金鲳鱼粗脂肪特征挥发性化合物表征及分析
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王钰翔 1, # , 张吉祥 1, # , 赵晨阳 1 , 潘佳宇 1 , 吴非凡 1 , 叶锦明 2 , 应晓国 1, * , 邓尚贵 1 , 马路凯 3
食品安全质量检测学报 | 专题:食品风味研究 2025,16(10): 43-50
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食品安全质量检测学报 | 专题:食品风味研究 2025, 16(10): 43-50
气相色谱-离子迁移谱法与电子鼻联用对金鲳鱼粗脂肪特征挥发性化合物表征及分析
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王钰翔1, # , 张吉祥1, # , 赵晨阳1, 潘佳宇1, 吴非凡1, 叶锦明2, 应晓国1, * , 邓尚贵1, 马路凯3
作者信息
  • 1.浙江省海鲜健康危险因素重点实验室, 浙江海洋大学食品药学学院, 舟山 316022
  • 2.浙江海洋大学海洋科学与技术学院, 舟山 316022
  • 3.农村部岭南特色食品绿色加工与智能制造重点实验室, 广东省岭南特色食品科学与技术重点实验室, 仲恺农业工程学院轻工食品学院, 广州 510225
  • 王钰翔(2000—), 女, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

    张吉祥(1997—), 男, 硕士研究生, 主要研究方向为食品加工与贮藏。E-mail:

通讯作者:

* 应晓国(1989—), 男, 博士, 副教授, 主要研究方向为水产品冷链物流、水产品精深加工与贮藏。E-mail:
Characterization and analysis of volatile compounds in crude fat of Trachinotus ovatus by gas chromatography-ion mobility spectrometry combined with electronic-nose
Yu-Xiang WANG1 , Ji-Xiang ZHANG1 , Chen-Yang ZHAO1, Jia-Yu PAN1, Fei-Fan WU1, Jin-Ming YE2, Xiao-Guo YING1, * , Shang-Gui DENG1, Lu-Kai MA3
Affiliations
  • 1. Key Laboratory of Health Risk Factors for Seafood of Zhejiang Province, Food and Pharmacy College, Zhejiang Ocean University, Zhoushan 316022, China
  • 2. Marine Science and Technology College, Zhejiang Ocean University, Zhoushan 316022, China
  • 3. Key Laboratory of Green Processing and Intelligent Manufacturing of Lingnan Specialty Food, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology, College of Food Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
出版时间: 2025-05-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250303002
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目的 结合气相色谱-离子迁移谱法(gas chromatography-ion mobility spectrometry, GC-IMS)与电子鼻联用技术, 系统分析金鲳鱼粗脂肪中的挥发性化合物特征。方法 采用GC-IMS对金鲳鱼不同部位(鱼头、腹部及内脏)粗脂肪中的挥发性化合物进行定性和定量分析, 重点识别醇、酮、酸和醛类等关键风味组分的差异。结合电子鼻技术对各部位粗脂肪的整体风味轮廓进行表征, 进一步评估主要挥发性化合物对风味形成的贡献。结果 金鲳鱼不同部位粗脂肪均属于优质脂质, 但在挥发性成分组成上存在显著差异, 鱼头组主要为醇和酮类化合物; 腹部组则以醇、烷烃和酸类物质为主; 内脏组含有较高的挥发性酸类物质。结论 本研究揭示了金鲳鱼不同部位挥发性化合物的差异, 为其风味调控提供了理论支持, 也为副产物如内脏的高值化利用提供了方向指引。

金鲳鱼  /  气相色谱-离子迁移谱法  /  电子鼻  /  挥发性化合物

Objective To systematically analyze the characteristics of volatile compounds in the crude fat of Trachinotus ovatus by gas chromatography-ion mobility spectrometry (GC-IMS) combined with electronic-nose. Methods GC-IMS was used to qualitatively and quantitatively analyze the volatile compounds in the crude fat of different parts (head, abdomen and viscera) of Trachinotus ovatus, focusing on the identification of differences in key flavor components such as alcohols, ketones, acids and aldehydes. Combined with electronic-nose technology, the overall flavor profile of crude fat in each part was characterized to further evaluate the contribution of major volatile compounds to flavor formation. Results The crude fat in different parts of Trachinotus ovatus belonged to high-quality lipids, but there were significant differences in the composition of volatile components. The fish head group was mainly composed of alcohols and ketones. The abdominal group was dominated by alcohols, alkanes and acids; the visceral group contained higher volatile acids. Conclusion This study reveals the differences in volatile compounds in different parts of Trachinotus ovatus, provides theoretical support for its flavor regulation, and also provides guidance for the high-value utilization of by-products such as viscera.

Trachinotus ovatus  /  gas chromatography-ion mobility spectrometry  /  electronic-nose  /  volatile compounds
王钰翔, 张吉祥, 赵晨阳, 潘佳宇, 吴非凡, 叶锦明, 应晓国, 邓尚贵, 马路凯. 气相色谱-离子迁移谱法与电子鼻联用对金鲳鱼粗脂肪特征挥发性化合物表征及分析. 食品安全质量检测学报, 2025 , 16 (10) : 43 -50 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250303002
Yu-Xiang WANG, Ji-Xiang ZHANG, Chen-Yang ZHAO, Jia-Yu PAN, Fei-Fan WU, Jin-Ming YE, Xiao-Guo YING, Shang-Gui DENG, Lu-Kai MA. Characterization and analysis of volatile compounds in crude fat of Trachinotus ovatus by gas chromatography-ion mobility spectrometry combined with electronic-nose[J]. Journal of Food Safety & Quality, 2025 , 16 (10) : 43 -50 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250303002
金鲳鱼学名卵形鲳鲹(Trachinotus ovatus), 属硬骨鱼纲鲈形目鯵科鲳鲹属, 其肉质鲜嫩、味道鲜美、无肌间刺、营养价值高, 是南海地区名贵海产经济鱼类之一[1]。作为重要的海水养殖鱼类, 金鲳鱼丰富的营养成分和独特的风味使其成为市场上备受欢迎的水产品[2]
随着水产加工业的快速发展和资源可持续利用理念的普及, 深入研究金鲳鱼副产物中脂质与风味物质的特性, 并探索其高值化利用路径, 已成为水产科学领域的热点[3]。金鲳鱼加工过程中会产生大量鱼头、内脏等副产物, 约占金鲳鱼总重的20%~50%, 这些副产物的利用仍处于初级阶段, 多用于鱼粉生产或直接废弃[4]。但它们与食用部分一样营养丰富, 具有一定的分离开发潜力, 如鱼头中含有丰富的多不饱和脂肪酸, 内脏中富含脂肪酶[5]。目前, 对于金鲳鱼脂质成分的全面解析仍存在不足, 尤其是对副产物中的脂质特性研究较为匮乏, 这制约了对其营养价值的深层次挖掘和综合利用的开发。
本研究通过提取金鲳鱼鱼头、腹部和内脏3部分的粗脂肪样品, 并应用气相色谱-离子迁移谱法(gas chromatography-ion mobility spectrometry, GC-IMS)对其挥发性化合物进行定性与定量分析。GC-IMS融合了GC的高效分离性能与IMS的高灵敏度特性, 显著提升了挥发性成分检测的灵敏度和分辨率[6]。通过该方法, 定性分析了3部分粗脂肪中主要的挥发性化合物, 揭示了不同部位粗脂肪中挥发性化合物的浓度差异, 为风味特征的评估提供了数据支持。同时, 本研究还采用了电子鼻技术对3部分粗脂肪样品的整体风味特征进行评价, 通过模拟人类嗅觉系统[7], 对金鲳鱼不同部位的气味特征进行综合分析。通过与GC-IMS分析结果的对比, 进一步揭示了不同部位粗脂肪在挥发性化合物组成上的差异以及这些化合物如何共同作用形成特定的风味, 为风味的形成机制提供了新的见解[8]。研究结果不仅为金鲳鱼风味的优化和改良提供了理论支持, 还为其他水产品的风味改善和质量控制提供了参考。未来, 基于粗脂肪挥发性化合物的精准分析, 有望为水产品加工和存储过程中脂质挥发性化合物的全面解析提升提供新的思路与技术手段。
金鲳鱼[重量(520±60.86) g, 长(29±3.25) cm]购自舟山国际水产城水产品贸易区(2024年11月, 中国)。整条金鲳鱼在低温环境下运送至实验室, 并被分割为鱼头、腹部和内脏3部分, 以备后续实验使用。
石油醚(沸程30~60 ℃)、无水硫代硫酸钠、冰醋酸、酚酞指示剂、乙醚、碘化钾、氢氧化钾、三氯甲烷、异辛烷、硫代巴比妥酸、乙醇、三氯乙酸、正己烷、氯化钠、乙酸镁、浓盐酸(分析纯, 国药集团化学试剂有限公司)。
FOSS自动索氏提取器(丹麦FOSS分析有限公司); Agilent7890A-5977C单四极杆气质联用仪(加装免放空换柱装置)、VF-624 ms色谱柱(30 m×0.25 mm, 1.4 μm)、PAL/PAL3自动进样器系统、微量进样针(美国Agilent公司); FlavourSpec®风味分析仪(德国G. A. S公司); PEN-3电子鼻系统(德国AIRSENSE公司); QUINTIX35-1CN十万分之一电子天平(南京莱步科技实业有限公司)。
参考周鑫盛[9]的实验方法测定2-甲基异莰醇(2-methylisoborneol, 2-MIB)和土臭素, 称取2.0 g烘烤后的氯化钠于20 mL顶空样品瓶中, 再加入10.0 mL样品, 旋紧瓶盖, 摇匀, 待氯化钠充分溶解后放置于自动进样器系统的样品盘, 按照所建方法进行测定。孵化盒温度设置为50 ℃, 转速为450 r/min。水样于50 ℃孵化5 min后萃取25 min, 最后在250 ℃进样口解吸5 min。萃取纤维在首次使用时需要在270 ℃老化30 min。灰分参照GB 5009.4—2016《食品安全国家标准 食品中灰分的测定》的高温灼烧法进行测定; 粗蛋白参照GB 5009.5—2016《食品安全国家标准 食品中蛋白质的测定》的凯氏定氮法进行测定。
粗脂肪提取参考李邰宇等[10]的方法, 使用新鲜的金鲳鱼鱼头、腹部和内脏作为原料。以石油醚作为萃取溶剂, 液料比为1:5 (g/mL)。样品在提取纸管中称重后, 将其放入烘干至恒重的提取器中, 两端放置脱脂棉花, 在温度为65 ℃下于索氏提取器中回流提取1 h。取下接收瓶, 回收石油醚, 待接收瓶冷却至室温后, 记录质量。用式(1)计算金鲳鱼粗脂肪的提取率。
$W=\frac{{{m}_{1}}-{{m}_{2}}}{{{m}_{0}}}\times 100%$
式中: W为金鲳鱼油的提取率, %; m1为金鲳鱼粗脂肪加提取杯的质量, g; m2为提取杯的质量, g; m0为金鲳鱼粗脂肪的称样质量, g。
测定酸值(acid value, AV)可作为油的变质程度的指标。参考ZHANG等[11]和ZHAO等[12]的方法, 并稍作修改。将从金鲳鱼腹肉中提取的5.00 g鱼油溶解在石油醚和乙醇中(1:1, V:V)。随后, 用0.10 mol/L氢氧化钾标准滴定剂测定样品溶液中的游离脂肪酸含量。终点是以酚酞的颜色变化作为指标来确定的。用滴定结束时消耗的标准滴定溶液的体积来计算油样的酸价。
${{X}_{\text{AV}}}=\frac{\left( V-{{V}_{0}} \right)\times c\times 56.1}{{{m}_{3}}}$
式中: XAV为酸价, mg/g; V为试剂测定所消耗的标准溶液的体积, mL; V0为相应的空白测定所消耗的标准滴定溶液的体积, mL; c为标准滴定溶液的摩尔浓度, moL/L; 56.1为氢氧化钾的摩尔质量, g/moL; m3为粗脂肪样品的称样量, g。
过氧化值(peroxide value, POV)的测定参考ZHAO等[13]的测定方法, 并进行了某些修改。将制备的5.00 g鱼油溶解在乙酸和异辛烷(3:2, V:V)中。过氧化物与碘化钾反应生成碘, 用0.01 mol/L硫代硫酸钠的标准溶液滴定沉淀后的碘。
${{X}_{\text{POV}}}=\frac{\left( {{V}_{1}}-{{V}_{2}} \right)\times {{c}_{\text{1}}}\times 0.1269}{{{m}_{4}}}\times 100$
式中: XPOV为POV, g/100 g; V1为试样消耗的硫代硫酸钠标准滴定溶液体积, mL; V2为空白实验消耗的硫代硫酸钠标准滴定溶液体积, mL; c1为硫代硫酸钠标准滴定溶液的浓度, moL/L; 0.1269为与1.00 mL硫代硫酸钠标准滴定溶液相当的碘的质量, g/mmoL; m4为粗脂肪样品的称样量, g; 100为折算为100 g的试样的换算系数。为更好的分析金鲳鱼粗脂肪POV, 在g/100 g的基础上将单位换算为mg/100 g。
参考文献[14-15]方法并作出适当修改, 量取1.0 mL粗脂肪, 置于20 mL顶空瓶中, 使用FlavourSpec®风味分析仪进行分析。自动顶空进样单元: 进样体积1.0 mL, 孵育时间10 min, 孵育温度60 ℃, 进样针温度85 ℃, 孵化转速500 r/min; GC-IMS单元: 分析时间30 min, 色谱柱类型为VF-624 ms色谱柱(30 m×0.25 mm, 1.4 μm), 柱温60 ℃, 载气N2, IMS温度45 ℃。
参考文献[16-17]方法并进行一定修改, 将解冻且温度回升至室温后的金鲳鱼粗脂肪摇匀后, 称取0.5 g置于100 mL烧杯中, 双层保鲜膜封口, 静置30 min后上机测试。在样品分析过程中, 将进样针头直接插入含有样品的密封烧杯, 利用电子鼻进行检测。检测条件如下: 采样频率为每组1 s; 传感器自清洗时长为80 s; 传感器归零时长为5 s; 样品准备时长为5 s; 进样流量设定为400 mL/min; 分析采样时长为80 s。在对每个样品进行数据采集时, 通过观察各传感器响应信号的变化趋势、各时间点的信号数值以及星型雷达图, 确定样品在分析过程中主要挥发的特征气体。
使用OriginPro 9.1进行分析。GC-IMS数据的采用Reporter插件、LAV (Laboratory Analytical Viewer)、Dynamic主成分分析(principal component analysis, PCA)插件、Gallery Plot插件以及GC×IMS Library Search软件进行分析。为对实验结果进行统计分析, 根据3个独立实验的结果计算了平均值和标准误差。采用多范围检验评估均数的差异, 在P<0.05时认为差异有显著性意义。
金鲳鱼的理化性质, 如表1所示, 2-MIB与土臭素均为天然萜烯醇类化合物, 它们是由地表水中的蓝藻(蓝绿藻)及放线菌(一种细菌)产生的[18]。当2-MIB和土臭素的质量浓度分别达到5 ng/L和30 ng/L时, 人类的嗅觉系统能够感知到这两种化合物。鉴于食品中挥发性化合物的感官特性及其对消费者接受度的潜在影响, 对水产品中2-MIB和土臭素进行鉴定与定量分析, 已成为保障水产品质量不可或缺的重要环节[19]。通过表1得出金鲳鱼在检测过程中2-MIB和土臭素均低于检出限。煅烧后的无机物为0.66 g/100 g, 说明金鲳鱼在生产中达到了合理的鲜鱼标准; 金鲳鱼整理的粗蛋白为15.2 g/100 g, 属于优质高蛋白鱼类[20]
图1(A)所示。用索氏提取法提取鲜金鲳鱼的鱼头组粗脂肪提取率为13.15%±1.65%, 腹部组粗脂肪提取率为28.41%±1.02%, 内脏组粗脂肪提取率为10.77%±1.54%。金鲳鱼腹部是油脂的脂质来源, 同时鱼头和内脏也含有油脂的脂质, 此外, 金鲳鱼粗脂肪提取率有一定的波动, 这可能与储存时间、金鲳鱼本身的状态和实验过程中的操作有关。
酸价主要反映鱼油中游离脂肪酸的含量, 在一定程度上可以判断鱼油品质的劣变程度。通过图1(B)金鲳鱼的鱼头组粗脂肪酸价为(0.23±0.06) mg/g, 腹部组粗脂肪酸价为(0.22±0.03) mg/g, 内脏组粗脂肪酸价为(0.85±0.08) mg/g, 均达到SC/T 3502—2016《鱼油》中粗鱼油一级标准[21]。酸价测量结果反映了鱼油的氧化特性, 可作为评价新鲜鱼油的指标。
POV是衡量鱼油酸败程度的关键指标, 其主要反映氢过氧化物的含量[22]。如图1(C)所示, 金鲳鱼的鱼头组粗脂肪POV为(1.42±0.01) mg/100 g, 腹部组粗脂肪POV为(1.61±0.02) mg/100 g, 内脏组粗脂肪POV为(2.14±0.05) mg/100 g, 均符合优质鱼油评判标准[23]
采用GC-IMS获得金鲳鱼不同部位粗脂肪的二维俯视图, 分析挥发性有机物的保留时间、迁移时间和离子信号强度, 通过俯视图可以直观看出金鲳鱼不同部位鱼油产品中挥发性有机物的差异对比[24]。如图2所示, 金鲳鱼内脏组的反应离子峰左侧出现了一个显著的竖峰, 该峰为氨气的特征峰, 这表明内脏组织中富含在加热条件下能够产生氨气的物质。为了实现更精准的差异对比分析, 本研究以金鲳鱼鱼头组的谱图为基准, 采用谱图扣减法对其他样品的谱图进行处理, 从而凸显各组之间的差异特征[25]。如果二者挥发性有机物一致, 则扣减后的背景为白色, 而红色代表该物质的浓度高于参比, 蓝色代表该物质的浓度低于参比[26]。金鲳鱼不同部位的峰值强度主要集中在200~300 s和1.00~1.50 ms范围内, 腹部组在400~600 s和1.00~1.50 ms范围内挥发性化合物与鱼头组相似, 金鲳鱼内脏组在400~1000 s和1.00~1.50 ms范围内与金鲳鱼鱼头组和腹部组有较大差异, 说明金鲳鱼的内脏粗脂肪与其他两组粗脂肪存在较大差别。
采用GC-IMS获得金鲳鱼不同部位粗脂肪中的挥发性化合物的种类和含量。如图3所示, 对比了金鲳鱼鱼头组、腹部组和内脏组中6类挥发性化合物的相对含量, 可见在3个部位中含量最高的芳香化合物成分都是醇类物质。除此以外, 鱼头组还有较多的酮类物质, 但酸类物质较少; 腹部组含有较多杂环化合物和烷烃类物质, 酯类物质含量相对较少; 内脏组的醛类和酸类物质含量均高于其他两组。
采用GC-IMS获得挥发性化合物指纹图谱, 分析芳香化合物, 了解金鲳鱼不同部位的挥发性化合物的组成和变化。图4中每一行展示了一特定样品中所选取的全部信号峰, 而每一列则反映了同一种挥发性有机物在不同样品中的信号峰变化。通过图4可以清晰地观察到每种样品所包含的完整挥发性有机物信息, 以及不同样品之间挥发性有机物的差异性。图4中物质名称后的“M”和“D”分别表示该物质的单体和二聚体形式[27-28]在金鲳鱼3部分粗脂肪中共检测到49种挥发性化合物, 其中包括39种已知成分和10种未知成分。金鲳鱼鱼头组主要挥发性化合物为醇和酮类物质, 含量最高的醇类挥发性物质为乙醇, 含量最高的酮类物质为丙酮, 其次是醛类挥发性化合物。金鲳鱼腹部组主要挥发性化合物包括乙醇、1,4-二氧己环、丙酮和乙酸等物质, 金鲳鱼内脏组主要挥发性化合物为醇、酮、酸和醛类物质, 包括乙醇、丙酮、乙酸和戊醛等物质。对比金鲳鱼3个部位的挥发性化合物指纹图谱能看到鱼头组的醇类和烷烃类物质要高于其他两组, 腹部组含有的醛类物质要少于其他两组, 金鲳鱼内脏组在加热过程中有明显的氨气的峰说明金鲳鱼内脏组含有较高的易挥发性酸类化合物。
电子鼻由于其对食品风味的综合表征, 已广泛应用于食品工业的风味分析和质量控制[29]。根据图5(A)可以得到传感器W3S、W1S和W5C之间存在差异, 表明观察到的组间气味差异主要归因于烷烃类和烷烃芳香成分[30]。PCA图有助于观察个体样本之间的相似性, 样本之间的规律性和差异可以通过主成分(principal component, PC)因子的贡献来评估[31]。3组挥发性PCA分析图如图5(B)所示。PC1和PC2的方差贡献分别为84.27%和10.00%, 总方差贡献超过94%。图5(B)为金鲳鱼不同部位粗脂肪中挥发性有机物的PCA分析图, 样品之间距离近则代表差异小, 距离远则代表差异明显。3种鱼油差异均较大, 鱼头组与腹部组和内脏组在PCA图上存在部分重叠, 而腹部组和内脏组在PCA图上不存在重叠, 内脏组粗脂肪跟另两组粗脂肪样品差异更大, 结果与GC-IMS的检测结果相似。
本研究结合GC-IMS与电子鼻技术, 系统分析了金鲳鱼不同部位(鱼头、腹部和内脏)粗脂肪中的挥发性化合物, 揭示了各部位挥发性有机物的组成差异及可能的风味特征。GC-IMS分析检测到49种挥发性化合物, 其中39种已知成分, 10种未知成分。鱼头组主要为醇和酮类化合物, 以乙醇和丙酮为主; 腹部组则以醇、烷烃和酸类物质为主, 乙醇和丙酮含量较高; 内脏组则含有较多氨气和酸类物质, 显示出明显差异。电子鼻PCA图显示鱼头组与腹部组和内脏组的挥发性物质有部分重叠, 而腹部组和内脏组差异较大, 这些差异可能与各部位脂肪酸的组成和代谢特性密切相关, 与GC-IMS结果一致。本研究详细表征了金鲳鱼不同部位的挥发性化合物, 揭示了各部位在风味物质上的显著差异, 为金鲳鱼风味优化和质量控制提供了理论依据。
  • 国家自然科学基金项目(32302135)
  • 国家自然科学基金项目(32072291)
  • 广东省现代农业产业共性关键技术研发创新团队建设项目(加工与保鲜共性关键技术)(2024CXTD16)
  • 大宗水产品预制菜肴加工关键技术研发项目(2023C03006)
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2025年第16卷第10期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250303002
  • 接收时间:2025-03-03
  • 首发时间:2025-07-15
  • 出版时间:2025-05-25
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  • 收稿日期:2025-03-03
基金
国家自然科学基金项目(32302135)
国家自然科学基金项目(32072291)
广东省现代农业产业共性关键技术研发创新团队建设项目(加工与保鲜共性关键技术)(2024CXTD16)
大宗水产品预制菜肴加工关键技术研发项目(2023C03006)
作者信息
    1.浙江省海鲜健康危险因素重点实验室, 浙江海洋大学食品药学学院, 舟山 316022
    2.浙江海洋大学海洋科学与技术学院, 舟山 316022
    3.农村部岭南特色食品绿色加工与智能制造重点实验室, 广东省岭南特色食品科学与技术重点实验室, 仲恺农业工程学院轻工食品学院, 广州 510225

通讯作者:

* 应晓国(1989—), 男, 博士, 副教授, 主要研究方向为水产品冷链物流、水产品精深加工与贮藏。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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