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Article(id=1320884231849492852, tenantId=1146029695717560320, journalId=1260987677001138203, issueId=1320883923090002610, articleNumber=null, orderNo=null, doi=10.13386/j.issn1002-0306.2025030296, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1742832000000, receivedDateStr=2025-03-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792852941715, onlineDateStr=2026-10-24, pubDate=1774972800000, pubDateStr=2026-04-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792852941715, onlineIssueDateStr=2026-10-24, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792852941715, creator=13701087609, updateTime=1792852941715, updator=13701087609, issue=Issue{id=1320883923090002610, tenantId=1146029695717560320, journalId=1260987677001138203, year='2026', volume='47', issue='7', pageStart='1', pageEnd='510', issueExtLink='null', onlineDate='null', pubDate='1774972800000', pubDateStr='2026-04-01', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792852868101, creator='13701087609', updateTime=1792852868101, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=304, endPage=315, ext={EN=ArticleExt(id=1320884232021459317, articleId=1320884231849492852, tenantId=1146029695717560320, journalId=1260987677001138203, language=EN, title=Analysis of VOCs Differences between Different Formulations of Five-spice Flavored Oils Based on GC-MS and GC-IMS, columnId=1261343843585241413, journalTitle=Science and Technology of Food Industry, columnName=Analysis and Determination, runingTitle=null, highlight=null, articleAbstract=

In order to explore the differences in volatile organic compounds (VOCs) among six different formulations of five-spice seasoning oils, electronic nose, headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), and gas chromatography-ion mobility spectrometry (GC-IMS) were used in this study. The electronic nose sensor had a strong response to alkanes, alcohols, ketones and aldehydes in VOCs, and PF6 had a strong flavor response. HS-SPME-GC-MS identified 118 VOCs in the six formulations, including olefins, esters, ketones, alcohols, alkanes, aldehydes, acids, phenols, ethers, and heterocyclic compounds. Anise-based PF1 had 31 VOCs, PF3 had 33, PF5 had 37, and PF6 had 46; Cinnamon-based PF2 had 47; Galangal-based PF4 had 32. Relative odor activity value (ROAV) analysis found 14 key VOCs, with anisaldehyde, artemisia ketone, and eucalyptol (responsible for anise and camphor-like aromas) being the major contributors. A total of 45 VOCs were identified by GC-IMS, through principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), 19 key VOCs differentiating the formulations were found, such as phenethyl alcohol, 2-methyl-2-propanol, ethyl hexanoate, oxylinalool, 1-octanol, and 1-penten-3-one. This study is helpful to provide a basis for the study of complex flavor system, and provide a reference for the development of spice products.

, authors=Jiacheng XU1, Wenjing LU2, Di CHEN2, Cen ZHANG2, Xuan CHEN2, Haitao CHEN3, Guangyin CHEN4, Xingquan LIU1, *, Chaogeng XIAO2, *, authorsList=Jiacheng XU, Wenjing LU, Di CHEN, Cen ZHANG, Xuan CHEN, Haitao CHEN, Guangyin CHEN, Xingquan LIU, Chaogeng XIAO, authorCompany=null, correspAuthors=Xingquan LIU, Chaogeng XIAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2026 Science and Technology of Food Industry. All rights reserved., 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=1320884235691475340, articleId=1320884231849492852, tenantId=1146029695717560320, journalId=1260987677001138203, language=CN, title=基于GC-MS和GC-IMS分析不同配方五香调味油的挥发性物质差异, columnId=1261343846139572559, journalTitle=食品工业科技, columnName=分析检测, runingTitle=null, highlight=null, articleAbstract=

为探究不同配方五香调味油风味物质差异，本研究采用电子鼻、顶空固相微萃取-气相色谱-质谱联用以及气相-离子迁移谱相结合的方法分析6种不同配方五香调味油挥发性物质的差异。结果表明：在6种调味油样品中，电子鼻传感器对挥发性物质中的烷烃类、醇类、酮类、醛类物质响应较强，其中PF6的风味响应强度较大。顶空固相微萃取-气相色谱-质谱联用（Headspace solid phase microextraction-gas chromatography-mass spectrometry，HS-SPME-GC-MS）共检测出118种挥发性有机化合物（Volatile organic compounds，VOCs），主要包含烯烃类、酯类、酮类、醇类、烷烃类、醛类、酸类、酚类、醚类以及杂环化合物等，其中以茴香料为主的配方1有31种，配方3有33种，配方5有37种，配方6有46种；以桂皮料为主的配方2有47种；以山奈料为主的配方4有32种。通过相对气味活度值（Relative odor activity value，ROAV）判定6种配方调味油的关键风味物质，共筛选出14种对调味油香气有较大贡献的化合物，其中以大茴香醛、草蒿脑、桉叶油醇为主，分别表现为茴香香气和樟脑香气。气相-离子迁移谱（Gas chromatography-ion mobility spectrometry，GC-IMS）共鉴定出45种挥发性物质，经主成分分析（Principal component analysis，PCA）和偏最小二乘回归分析（Partial least squares-discriminant analysis，PLS-DA）得出，配方间区分明显并且筛选出19种关键风味差异化合物，包括芳甲基苯甲醇、2-甲基-2-丙醇、乙酸己酯、氧化芳樟醇、1-辛醇、1-戊烯-3-酮等。本项研究有助于为复杂的风味体系研究提供基础，并为香辛料产品开发提供参考。

, authors=徐嘉成1, 卢文静2, 谌迪2, 张岑2, 陈轩2, 陈海涛3, 陈光银4, 刘兴泉1, *, 肖朝耿2, *, authorsList=徐嘉成, 卢文静, 谌迪, 张岑, 陈轩, 陈海涛, 陈光银, 刘兴泉, 肖朝耿, authorCompany=null, correspAuthors=刘兴泉, 肖朝耿, authorNote=

徐嘉成（2000−），男，硕士研究生，研究方向：食品加工与安全，E-mail：

, correspAuthorsNote=
刘兴泉（1973−），男，博士，教授，研究方向：食品加工与安全，E-mail：。
肖朝耿（1978−），男，硕士，研究员，研究方向：食品加工新技术，E-mail：
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徐嘉成（2000−），男，硕士研究生，研究方向：食品加工与安全，E-mail：

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徐嘉成（2000−），男，硕士研究生，研究方向：食品加工与安全，E-mail：

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注：图中序号代表的物质与表3中五香调味油VOCs序号代表的一致。

, figureFileSmall=ApqH8/Nu1gpeG/vmJB04EA==, figureFileBig=UIuVDSmw0eOXnWTe0eCjzg==, tableContent=null), ArticleFig(id=1320884244491125222, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320884231849492852, language=EN, label=Table 1, caption=

Sensor corresponding response substance name

, figureFileSmall=null, figureFileBig=null, tableContent=
传感器名称主要响应物质
S1丙烷、烟雾等
S2含碳类物质
S3氢气
S4硫化物
S5含氮类物质
S6醛酮类
S7短链烷烃类、可燃性气体等
S8液化气
S9烷烃，醇类、酮类等
S10氢气、含氢气体类
S11烷烃，一氧化碳等
S12液化气，甲烷类
S13短链烷烃类
S14甲烷，燃气，烟雾等
S15含碳类物质、醇类、醛类等
S16硫化氢
S17氨气，胺类等
S18甲苯、丙酮、乙醇等
), ArticleFig(id=1320884244562428391, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320884231849492852, language=CN, label=表1, caption=

传感器对应响应物质名称

, figureFileSmall=null, figureFileBig=null, tableContent=
传感器名称主要响应物质
S1丙烷、烟雾等
S2含碳类物质
S3氢气
S4硫化物
S5含氮类物质
S6醛酮类
S7短链烷烃类、可燃性气体等
S8液化气
S9烷烃，醇类、酮类等
S10氢气、含氢气体类
S11烷烃，一氧化碳等
S12液化气，甲烷类
S13短链烷烃类
S14甲烷，燃气，烟雾等
S15含碳类物质、醇类、醛类等
S16硫化氢
S17氨气，胺类等
S18甲苯、丙酮、乙醇等
), ArticleFig(id=1320884244633731560, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320884231849492852, language=EN, label=Table 2, caption=

ROAVs of volatile compounds in flavored oils

, figureFileSmall=null, figureFileBig=null, tableContent=
序号CAS号名称风味阈值[5，30]PF1PF2PF3PF4PF5PF6香气特征
1470-82-6桉叶油醇0.0046−−−681.44001.678115.2317樟脑香
297-53-0丁香酚0.0060−2.8103−−−1.2776丁香香气
3123-11-5大茴香醛0.0001−2301.7329223.8011−715.29192643.1761八角、杏仁味
457194-69-1顺式肉桂醛0.05004.5787100.00005.9276100.00004.233739.6108肉桂香
5109-52-4正戊酸0.0016−−1.0575−0.3271−果香
62244-16-8右旋香芹酮0.0230−1.27540.5640−−1.8789葛缕子味
799-83-2水芹烯0.04000.66750.7618−−−5.1591胡椒味
84180-23-8茴香烯0.0150−353.5148−−100.00002.8108茴香香气
9123-35-3月桂烯0.00124.985521.8390−−−−脂香、辛辣味
103856-25-5α-蒎烯0.0140−−1.0150−−−松脂味
11555-10-2β-水芹烯0.03601.09496.8677−−−−柑橘香气
124192-77-2反式肉桂酸乙酯0.1650−−−2.20590.0285−甜香、脂香
13104-46-1茴香醚0.05701.8423−10.49372.2515−100.0000茴香香气
14140-67-0草蒿脑0.0060100.0000191.7772100.0000−20.0821234.2676大茴香香气
), ArticleFig(id=1320884244721811945, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320884231849492852, language=CN, label=表2, caption=

调味油中VOCs的相对气味活度值

, figureFileSmall=null, figureFileBig=null, tableContent=
序号CAS号名称风味阈值[5，30]PF1PF2PF3PF4PF5PF6香气特征
1470-82-6桉叶油醇0.0046−−−681.44001.678115.2317樟脑香
297-53-0丁香酚0.0060−2.8103−−−1.2776丁香香气
3123-11-5大茴香醛0.0001−2301.7329223.8011−715.29192643.1761八角、杏仁味
457194-69-1顺式肉桂醛0.05004.5787100.00005.9276100.00004.233739.6108肉桂香
5109-52-4正戊酸0.0016−−1.0575−0.3271−果香
62244-16-8右旋香芹酮0.0230−1.27540.5640−−1.8789葛缕子味
799-83-2水芹烯0.04000.66750.7618−−−5.1591胡椒味
84180-23-8茴香烯0.0150−353.5148−−100.00002.8108茴香香气
9123-35-3月桂烯0.00124.985521.8390−−−−脂香、辛辣味
103856-25-5α-蒎烯0.0140−−1.0150−−−松脂味
11555-10-2β-水芹烯0.03601.09496.8677−−−−柑橘香气
124192-77-2反式肉桂酸乙酯0.1650−−−2.20590.0285−甜香、脂香
13104-46-1茴香醚0.05701.8423−10.49372.2515−100.0000茴香香气
14140-67-0草蒿脑0.0060100.0000191.7772100.0000−20.0821234.2676大茴香香气
), ArticleFig(id=1320884244826669546, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320884231849492852, language=EN, label=Table 3, caption=

Qualitative analysis of volatile compounds in five spice seasoning oil by GC-IMS

, figureFileSmall=null, figureFileBig=null, tableContent=
序号挥发物种类中文名称分子质量保留指数保留时间（s）迁移时间（ms）
1酯类3-甲硫基丙酸乙酯148.21096.4545.3491.21338
2丙酸异丁酯130.2853.8260.3161.27095
3反式-2-丁烯酸乙酯114.1850.5258.2931.55711
4丁酸乙酯116.2815.7237.7271.20491
5乙酸己酯144.21009.3405.9011.37206
6乙酸丙酯102.1714.4184.3661.15843
7乙酸甲酯74.1516.7122.2231.19639
8烯烃类柠檬烯136.21028.8433.5281.21431
9α-萜品烯136.21020.5421.5081.21431
103-蒈烯136.21011.4408.6751.29873
11酮类2-辛酮128.2991382.3231.33984
121-辛烯-3-酮126.2977.7367.5291.26095
131-戊烯-3-酮84.1669.1165.9181.31312
143-羟基-4,5-二甲基-2（5H）-呋喃酮128.11109.4569.9821.21434
15酸类3-甲基戊酸116.2945.7334.2421.26206
163-甲基丁酸102.1888.8282.9891.22051
17丙酸74.1691.2173.7171.26331
18乙酸60.1589.1141.3291.05457
19醛类肉桂醛132.21255.9936.6461.23498
203-甲硫基丙醛104.2905.9297.1281.08127
21庚醛114.2905.5296.7281.33106
222-甲基丁醛86.1676.3168.361.1615
232-甲基-2-丙烯醛70.1569.9135.991.21553
24吡嗪类2-异丁基-3-甲氧基吡嗪166.21180.9726.311.31153
252-甲基吡嗪94.1835.5249.191.09146
26甲基吡嗪94.1797.5227.6121.4081
272-乙基-6-甲基吡嗪122.2990.6381.8611.2054
282,6-二甲基吡嗪108.1919.5309.2771.13207
29呋喃类2-甲基-3-甲硫基呋喃128.2950.8339.3281.09984
302-乙酰基呋喃110.1879.3276.6341.11157
31醚类4-甲基苯甲醚122.21004.6399.4291.11762
32酚类2-甲氧基-4-乙烯基苯酚150.21322.61174.3821.21448
332-甲氧基-4-乙烯基苯酚（二聚体）150.21322.61174.3821.75781
342,6-二甲基苯酚122.21106.6564.4751.12873
354-甲基苯酚108.11067.3494.1411.13034
36醇类（+）-α-松油醇154.31192.5755.4531.21545
37氧化芳樟醇170.31055.3474.2911.25308
382-己醇102.2817.5238.7381.28534
392-呋喃甲醇98.1832.6247.5041.35815
40β-苯乙醇122.21117.3585.281.29651
41芳樟醇154.31096.8545.9831.70206
42甲基苯甲醇122.21058.7479.8721.56206
432-辛醇130.21003.9398.5041.44428
441-辛醇130.21060.2482.3341.46483
452-甲基-2-丙醇74.1538127.5621.14672
46其他二烯丙基二硫化物146.31075.6508.2611.63017
), ArticleFig(id=1320884244910555627, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320884231849492852, language=CN, label=表3, caption=

GC-IMS定性五香调味油的VOCs

, figureFileSmall=null, figureFileBig=null, tableContent=
序号挥发物种类中文名称分子质量保留指数保留时间（s）迁移时间（ms）
1酯类3-甲硫基丙酸乙酯148.21096.4545.3491.21338
2丙酸异丁酯130.2853.8260.3161.27095
3反式-2-丁烯酸乙酯114.1850.5258.2931.55711
4丁酸乙酯116.2815.7237.7271.20491
5乙酸己酯144.21009.3405.9011.37206
6乙酸丙酯102.1714.4184.3661.15843
7乙酸甲酯74.1516.7122.2231.19639
8烯烃类柠檬烯136.21028.8433.5281.21431
9α-萜品烯136.21020.5421.5081.21431
103-蒈烯136.21011.4408.6751.29873
11酮类2-辛酮128.2991382.3231.33984
121-辛烯-3-酮126.2977.7367.5291.26095
131-戊烯-3-酮84.1669.1165.9181.31312
143-羟基-4,5-二甲基-2（5H）-呋喃酮128.11109.4569.9821.21434
15酸类3-甲基戊酸116.2945.7334.2421.26206
163-甲基丁酸102.1888.8282.9891.22051
17丙酸74.1691.2173.7171.26331
18乙酸60.1589.1141.3291.05457
19醛类肉桂醛132.21255.9936.6461.23498
203-甲硫基丙醛104.2905.9297.1281.08127
21庚醛114.2905.5296.7281.33106
222-甲基丁醛86.1676.3168.361.1615
232-甲基-2-丙烯醛70.1569.9135.991.21553
24吡嗪类2-异丁基-3-甲氧基吡嗪166.21180.9726.311.31153
252-甲基吡嗪94.1835.5249.191.09146
26甲基吡嗪94.1797.5227.6121.4081
272-乙基-6-甲基吡嗪122.2990.6381.8611.2054
282,6-二甲基吡嗪108.1919.5309.2771.13207
29呋喃类2-甲基-3-甲硫基呋喃128.2950.8339.3281.09984
302-乙酰基呋喃110.1879.3276.6341.11157
31醚类4-甲基苯甲醚122.21004.6399.4291.11762
32酚类2-甲氧基-4-乙烯基苯酚150.21322.61174.3821.21448
332-甲氧基-4-乙烯基苯酚（二聚体）150.21322.61174.3821.75781
342,6-二甲基苯酚122.21106.6564.4751.12873
354-甲基苯酚108.11067.3494.1411.13034
36醇类（+）-α-松油醇154.31192.5755.4531.21545
37氧化芳樟醇170.31055.3474.2911.25308
382-己醇102.2817.5238.7381.28534
392-呋喃甲醇98.1832.6247.5041.35815
40β-苯乙醇122.21117.3585.281.29651
41芳樟醇154.31096.8545.9831.70206
42甲基苯甲醇122.21058.7479.8721.56206
432-辛醇130.21003.9398.5041.44428
441-辛醇130.21060.2482.3341.46483
452-甲基-2-丙醇74.1538127.5621.14672
46其他二烯丙基二硫化物146.31075.6508.2611.63017
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基于GC-MS和GC-IMS分析不同配方五香调味油的挥发性物质差异
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徐嘉成 1 , 卢文静 2 , 谌迪 2 , 张岑 2 , 陈轩 2 , 陈海涛 3 , 陈光银 4 , 刘兴泉 1, * , 肖朝耿 2, *
食品工业科技 | 分析检测 2026,47(7): 304-315
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食品工业科技 |分析检测 2026 , 47 (7) : 304 -315
基于GC-MS和GC-IMS分析不同配方五香调味油的挥发性物质差异
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徐嘉成（2000−），男，硕士研究生，研究方向：食品加工与安全，E-mail：

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徐嘉成1 , 卢文静2, 谌迪2, 张岑2, 陈轩2, 陈海涛3, 陈光银4, 刘兴泉1, * , 肖朝耿2, *
作者信息
  • 1浙江农林大学食品与健康学院，浙江杭州 311300
  • 2浙江省农业科学院食品科学研究所，浙江杭州 310021
  • 3北京工商大学轻工科学技术学院，北京市食品风味化学重点实验室，北京 100048
  • 4浙江顶味食品有限公司，浙江温州 325200
通讯作者:
刘兴泉（1973−），男，博士，教授，研究方向：食品加工与安全，E-mail：。
肖朝耿（1978−），男，硕士，研究员，研究方向：食品加工新技术，E-mail：
作者简介:

徐嘉成（2000−），男，硕士研究生，研究方向：食品加工与安全，E-mail：

Analysis of VOCs Differences between Different Formulations of Five-spice Flavored Oils Based on GC-MS and GC-IMS
Jiacheng XU1 , Wenjing LU2, Di CHEN2, Cen ZHANG2, Xuan CHEN2, Haitao CHEN3, Guangyin CHEN4, Xingquan LIU1, * , Chaogeng XIAO2, *
Affiliations
  • 1College of Food and Health, Zhejiang A & F University, Hangzhou 311300, China
  • 2Food Science Institute, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
  • 3Beijing Key Laboratory of Flavor Chemistry, School of Light Industry, Beijing Technology and Business University, Beijing 100048, China
  • 4Zhejiang Dingwei Food Co., Ltd., Wenzhou 325200, China
出版时间: 2026-04-01 doi: 10.13386/j.issn1002-0306.2025030296
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为探究不同配方五香调味油风味物质差异，本研究采用电子鼻、顶空固相微萃取-气相色谱-质谱联用以及气相-离子迁移谱相结合的方法分析6种不同配方五香调味油挥发性物质的差异。结果表明：在6种调味油样品中，电子鼻传感器对挥发性物质中的烷烃类、醇类、酮类、醛类物质响应较强，其中PF6的风味响应强度较大。顶空固相微萃取-气相色谱-质谱联用（Headspace solid phase microextraction-gas chromatography-mass spectrometry，HS-SPME-GC-MS）共检测出118种挥发性有机化合物（Volatile organic compounds，VOCs），主要包含烯烃类、酯类、酮类、醇类、烷烃类、醛类、酸类、酚类、醚类以及杂环化合物等，其中以茴香料为主的配方1有31种，配方3有33种，配方5有37种，配方6有46种；以桂皮料为主的配方2有47种；以山奈料为主的配方4有32种。通过相对气味活度值（Relative odor activity value，ROAV）判定6种配方调味油的关键风味物质，共筛选出14种对调味油香气有较大贡献的化合物，其中以大茴香醛、草蒿脑、桉叶油醇为主，分别表现为茴香香气和樟脑香气。气相-离子迁移谱（Gas chromatography-ion mobility spectrometry，GC-IMS）共鉴定出45种挥发性物质，经主成分分析（Principal component analysis，PCA）和偏最小二乘回归分析（Partial least squares-discriminant analysis，PLS-DA）得出，配方间区分明显并且筛选出19种关键风味差异化合物，包括芳甲基苯甲醇、2-甲基-2-丙醇、乙酸己酯、氧化芳樟醇、1-辛醇、1-戊烯-3-酮等。本项研究有助于为复杂的风味体系研究提供基础，并为香辛料产品开发提供参考。

五香调味油  /  电子鼻  /  顶空固相微萃取-气相色谱-质谱联用（HS-SPME-GC-MS）  /  气相-离子迁移谱（GC-IMS）  /  风味物质

In order to explore the differences in volatile organic compounds (VOCs) among six different formulations of five-spice seasoning oils, electronic nose, headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), and gas chromatography-ion mobility spectrometry (GC-IMS) were used in this study. The electronic nose sensor had a strong response to alkanes, alcohols, ketones and aldehydes in VOCs, and PF6 had a strong flavor response. HS-SPME-GC-MS identified 118 VOCs in the six formulations, including olefins, esters, ketones, alcohols, alkanes, aldehydes, acids, phenols, ethers, and heterocyclic compounds. Anise-based PF1 had 31 VOCs, PF3 had 33, PF5 had 37, and PF6 had 46; Cinnamon-based PF2 had 47; Galangal-based PF4 had 32. Relative odor activity value (ROAV) analysis found 14 key VOCs, with anisaldehyde, artemisia ketone, and eucalyptol (responsible for anise and camphor-like aromas) being the major contributors. A total of 45 VOCs were identified by GC-IMS, through principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), 19 key VOCs differentiating the formulations were found, such as phenethyl alcohol, 2-methyl-2-propanol, ethyl hexanoate, oxylinalool, 1-octanol, and 1-penten-3-one. This study is helpful to provide a basis for the study of complex flavor system, and provide a reference for the development of spice products.

five-spice seasoning oils  /  E-nose  /  headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS)  /  gas chromatography-ion mobility spectrometry (GC-IMS)  /  flavor substances
徐嘉成, 卢文静, 谌迪, 张岑, 陈轩, 陈海涛, 陈光银, 刘兴泉, 肖朝耿. 基于GC-MS和GC-IMS分析不同配方五香调味油的挥发性物质差异. 食品工业科技, 2026 , 47 (7) : 304 -315 . DOI: 10.13386/j.issn1002-0306.2025030296
Jiacheng XU, Wenjing LU, Di CHEN, Cen ZHANG, Xuan CHEN, Haitao CHEN, Guangyin CHEN, Xingquan LIU, Chaogeng XIAO. Analysis of VOCs Differences between Different Formulations of Five-spice Flavored Oils Based on GC-MS and GC-IMS[J]. Science and Technology of Food Industry, 2026 , 47 (7) : 304 -315 . DOI: 10.13386/j.issn1002-0306.2025030296
正文
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调味油是一种通过将各种香料浸泡在油中制成的调味品，能够为食物增添丰富的风味和香气。通常，制作调味油时会选择中性味道的植物油，如大豆油、菜籽油或葵花籽油，以便更好地吸收和传递香料的风味，Tian等[1]在对制备的葱香油进行风味物质检测时发现，以菜籽油作为载体油脂制得的葱香油中挥发性物质种类数最多，倪瑞洁[2]在制备花椒调味油时发现，与大豆油、花生油、葵花仁油相比，一级压榨菜籽油作为载体油脂制备的花椒调味油，色泽鲜亮且风味最为协调，且菜籽油是制作调味油最为常用的载体油脂。调味油为一种即食调味品，可直接淋在菜肴上，增添浓郁香气和风味。在烹饪过程中，其也可以作为基础油使用，用于煎炒、烤制或炖煮各种食材，从而提升菜肴整体的风味层次。此外，调味油还可以用作腌制液，将食材在烹饪前进行短时间腌制，使其在烹饪过程中更加入味。从健康角度上，通过调味油摄入的香料也能提供多种健康益处，如抗炎、抗菌和促进消化等[3]。五香是一种具有悠久历史和丰富风味的中式复合香辛料，广泛用于中国及其他东亚国家的烹饪中。五香粉的独特之处在于它融合了多种主要香料的香气和味道，形成了一个多层次、复杂的风味体系，其中花椒具有麻辣感和青香，能在口腔中产生独特的麻感，八角和桂皮提供了甜香和辛辣的口感，丁香则增添了强烈的香气和辛辣感，然而五香并不局限于固定的香料品类和数量，也可添加陈皮、山奈、砂仁等香料，不同的配方提供了不同的风味。将五香作为香料原料与油脂共同加工即可制得五香调味油。
五香调味油和花椒调味油都属于调味油的范畴，两者都具有相似的加工工艺和研究手段，而花椒调味油目前应用较为广泛。陈丽兰等[4]采用气相色谱-质谱联用（Gas chromatography-mass spectrometry，GC-MS）等技术，鉴定出14种不同花椒油中芳樟醇、乙酸芳樟酯、苯乙酸甲酯、γ-松油烯、水芹烯等为关键风味物质。高夏洁等[5]以不同产地的红花椒为对象分析不同产区花椒油的关键风味物质，分析得到关键香气物质为芳樟烯、桉叶油醇、月桂烯、柠檬烯等。刘玉兰等[6]通过研究发现，商品花椒调味油与新鲜压榨花椒籽油相比，在反映花椒油特征的挥发性风味成分含量方面和感官评价方面均具有高度相似性和一致性。总体而言，目前对花椒调味油的风味特性研究较为成熟，但针对五香调味油的风味研究仍有欠缺，徐立荣等[7]曾以电子鼻为检测手段，研究油料比值、浸提温度、浸提时间和保温时间等因素对五香调味油风味的影响，但未对具体风味成分进行深入研究。
本研究通过电子鼻、顶空固相微萃取-气相色谱-质谱联用（Headspace solid phase microextraction-gas chromatography-mass spectrometry，HS-SPME-GC-MS）及气相-离子迁移谱（Gas chromatography-ion mobility spectrometry，GC-IMS）相结合的方式对6种配方五香调味油风味物质进行分析。通过电子鼻初步分析五香调味油风味差异，然后对气质联用检测到的挥发性物质进行层次聚类分析（Hierarchical cluster analysis，HCA）并结合相对气味活度值（Relative odor activity value，ROAV）筛选各配方的关键香气物质，最后进行GC-IMS检测定性调味油中的挥发性物质并运用偏最小二乘回归分析（Partial least squares-discriminant analysis，PLS-DA）确定对风味轮廓有重要影响的关键风味差异化合物。本研究旨在深入探究复合香辛料调味油的具体风味成分及来源，为复杂的风味体系研究提供基础。
1　材料与方法
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1.1　材料与仪器
本实验所用低芥酸菜籽油　山东鲁花集团有限公司出品，置于常温避光处储存；常用香辛料八角、白胡椒、陈皮、丁香、豆蔻、甘草、干姜、桂皮、花椒、砂仁、山奈、五加皮、小茴香等　购于菜佳宜公司，置于低温干燥处储存。
C-Nose电子鼻　上海保圣实业发展有限公司；5191-5874顶空固相微萃取纤维（DVB/C-WR/PDMS/10）、6890N-G5795B GC-MS联用仪、DB-WAX（30 m×0.25 mm，0.25 μm）毛细管色谱柱　美国Agilent公司；FlavourSpec®GC-IMS联用仪、MXT-5非极性色谱柱　德国G.A.S公司。
1.2　实验方法
1.2.1　不同配方五香调味油的制备
香辛料的配方参考高延等[8]的方法及根据地域口味不同稍作修改，以丁香10 g，甘草30 g，桂皮10 g，花椒10 g，小茴香40 g为PF1；八角20 g，陈皮6 g，干姜5 g，桂皮43 g，花椒18 g，小茴香8 g为PF2；八角10 g，丁香5 g，甘草30 g，桂皮10 g，五加皮10 g，小茴香35 g为PF3；丁香22 g，豆蔻11 g，桂皮12 g，砂仁11 g，山奈44 g为PF4；八角55 g，白胡椒3 g，甘草5 g，干姜15 g，桂皮8 g，砂仁4 g，山奈10 g为PF5；八角30 g，桂皮15 g，花椒30 g，五加皮10 g，小茴香15 g为PF6形成6种不同的复合香辛料配方，经过干燥后打粉，直至可过40目筛后备用。调味油制备参照Sun等[9]的方法稍作修改，每个配方取30 g香辛料，加入150 g菜籽油在130 ℃下进行加热浸提，保温10 min后取出过滤，冷却至室温后以4000 r/min条件离心并在4 ℃下储存待测。
1.2.2　电子鼻（E-Nose）检测
使用电子鼻对6种五香调味油风味特征进行分析，电子鼻系统配备18个传感器，每个传感器响应不同的挥发性物质成分，具体如表1所示。将10 mL调味油样品放置到40 mL顶空样品瓶中，密封后静置60 min，用空气作为载气对传感器阵列进行清洗，使信号响应归零。每组准备三个样品进行三次平行实验，取59~60 s的数据的平均值作进一步分析。
1.2.3　顶空固相微萃取-气质联用（HS-SPME-GC-MS）检测
参照Ni等[10]的方法稍作修改，将6种调味油样品各取2 mL于20 mL顶空样品瓶中，用聚四氟乙烯瓶盖封隔，避光保存。预先将涂有DVB/C-WR/PDMS/10的萃取纤维头插入GC-MS进样口（250 ℃）进行老化。在80 ℃的恒温水浴中振荡样品，样品平衡时间为15 min，萃取时间为30 min。然后将萃取后的纤维头取出后立即插入GC-MS进样口中，于250 ℃解吸5 min。采用DB-WAX色谱柱（均为30 m×0.25 mm，0.25 μm）分离挥发性化合物，进样口温度250 ℃；进样方式为1:1分流模式；载气为氦气（99.99%）；流速1.5 mL/min；升温程序：初温60 ℃，以5 ℃/min升温至70 ℃，保持10 min，以3 ℃/min升温至95 ℃，保持7 min，以3 ℃/min升温至120 ℃，保持6 min，再以3 ℃/min升温至140 ℃，保持6 min，最后以10 ℃/min升温至210 ℃，保持3 min。质谱条件：电子电离（EI）模式；电子能量70 eV；离子源温度230 ℃；传输线温度250 ℃；质量扫描范围m/z 30~450；溶剂延迟1 min。通过比对质谱图，利用NIST 17标准谱库检索，根据匹配保留时间和质谱碎片以实现化合物的鉴定，并采用峰面积归一化法计算各挥发性成分的相对百分含量。
通过计算 ROAV，确定香气物质对样品风味的贡献。
$ \mathrm{ROAV}_{ \mathrm{A}} \mathrm{=(C}_{ \mathrm{A}} \mathrm{/T}_{ \mathrm{A}} \mathrm{)\times (T}_{ \mathrm{stan}} \mathrm{/C}_{ \mathrm{stan}} \mathrm{)\times 100} $
式中：CA表示化合物A的相对百分含量；TA表示化合物A的香气阈值；Tstan及Cstan分别是对样品风味贡献最大的化合物的香气阈值和相对百分含量。
1.2.4　气相-离子迁移谱（GC-IMS）检测
参照Zheng等[11]的方法稍作修改，顶空进样条件：准确称取1.5 g五香调味油，装入20 mL顶空进样瓶中密封。70 ℃条件下孵育20 min，孵化转速500 r/min；进样针温度85 ℃；进样体积500 μL。
GC条件：MXT-5非极性色谱柱（15 m×0.53 mm，1 μm） ；柱温60 ℃；分析时间30 min；载气：N2（纯度≥99.999%）；载气流速：0~2 min，2 mL/min；2~10 min，2~10 mL/min；10~20 min，10~100 mL/min；20~30 min，100~150 mL/min。
IMS条件：漂移管长度5 cm；管内线性电压400 V/cm；漂移气：N2（纯度≥99.999%）；流速150 mL/min；IMS温度45 ℃。每组准备三个样品进行三次平行实验。
数据分析：基于NIST2020 RI DB-5数据库，对样本的挥发性有机物进行定性分析。
1.3　数据处理
柱形图、雷达图采用Origin 2021软件绘图。PCA采用基迪奥生物信息云平台绘图。采用Tbtools v2.21绘图进行挥发性风味物质的层次聚类分析。GC-IMS指纹图谱和挥发性化合物定性通过内置的Gallery Plot插件和GC×IMS Library Search实现。采用SIMCA 14.0软件进行PLS-DA分析和绘图。
2　结果与分析
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2.1　电子鼻对五香调味油的风味分析
使用PCA可直观地根据不同调味油样品之间的距离来判断样品之间的相似性或差异性，结果如图1所示，前两个主成分PC1和PC2对总方差的贡献率分别为75.4%和15.5%，累积贡献率达到90.9%，表明主成分分析能反映出不同配方五香调味油的原始风味信息。不同配方香辛料调味油样品的空间分布不同，PF4和PF5的调味油分布在PC1的负侧，PF1的调味油分布在PC2的正侧，PF2与PF3则在原点周围，这3类样品之间距离相近，表明样品间差异较小；配方6位于PC1的正侧，距离其他样品较远，说明与其他样品风味有明显差异。
根据18个传感器对样品的平均响应值建立传感器信号雷达强度图，以便比较6种配方五香调味油样品的风味轮廓。不同传感器对应不同的响应物质，结果如图1所示，在传感器2、9、15上对五香调味油的风味轮廓感知更敏感，说明调味油风味物质中含有较多的烷烃类、醇类、酮类、醛类物质，各配方在传感器13上的响应值较小，说明调味油中含有较少的短链烷烃。从整体响应程度看，不同配方调味油的香气轮廓大体一致，PF6的风味响应强度较大，PF4的风味响应强度较小。电子鼻的检测可以在一些传感器上较好地区分样品，但要表征代表调味油香气的具体物质则需要进一步检测分析。
2.2　HS-SPME-GC-MS 对五香调味油风味成分的分析
2.2.1　调味油样品风味物质种类及含量比较
采用HS-SPME-GC-MS对6种配方调味油的VOCs进行检测分析，共检测出118种VOCs，包括烯烃类25种，酯类19种，酮类16种，醇类13种，烷烃类9种，醛类8种，酸类7种，吡啶类4种，酚类4种，醚类3种，吡嗪类3种，其他7种。如图2所示，6种配方五香调味油的VOCs种类和含量存在较大差别，这与配方中添加不同的香辛料和不同的配比有直接关系。从化合物数量上看，调味油PF2的VOCs数量最为丰富，多达47种，其次是调味油PF6，为46种，最少的是PF1，仅为31种，这可能与所添加的香辛料风味本身寡淡有关。6种配方调味油的VOCs组成种类大致相同，以醚类、醛类、烯烃类和酯类为主，这与电子鼻的检测结果相似。从化合物相对含量上看，其中醚类化合物在调味油配方1、3、6中占比最高，分别为43.25%、43.85%、46.38%，烯烃类化合物在调味油配方2、5中占比最高，分别为31.42%、54.94%，这与添加香辛料导致香辛料中风味物质进入油脂有较大关联，香辛料的VOCs主要以醚类、烯烃类为主。一些含氮化合物如吡嗪类化合物是由糖类和蛋白质通过美拉德反应产生[12]，碳水化合物、蛋白质和脂肪间通过糖类热降解产生呋喃类物质，这在制备葱油中也有报道[13]。
通过Upset图可看出各配方的共有物质和特有物质，如图3所示，橙色柱状表示调味油VOCs的总数量，黑色的圆点表示含有的VOCs，点和点之间的连线表示共有的VOCs，绿色柱状则分别表示共有挥发性成分的数量，当仅有一个点无连线时，说明这是该配方的特有物质。从图中可看出，6种调味油所含VOCs共性物质较低，其中PF2所含特有化合物有14种，PF2与PF6共有物质最多，为8种，6种配方共有化合物为2种，分别为顺式肉桂醛和乙酸。
2.2.2　五香调味油风味物质的层次聚类热图分析
采用层次聚类分析6种配方五香调味油的VOCs变量并绘制热图。如图4所示，6种配方五香调味油含有的VOCs聚集为不同的类别，其中PF2、PF6为一类，其他配方为一类。此外，检出的VOCs中醛类、烯烃类、醇类物质含量相对较高，主要是因为香辛料在高温加热时大量的香味物质溶入油脂中，如顺式肉桂醛、草蒿脑、茴香醚、茴香烯等由香辛料提供的VOCs，这些物质是香辛料含有的典型挥发性物质，在纯菜籽油热处理样品中未检测到[2]。此外，在检出物质中也发现一些环状化合物的存在，这可能是由于油脂在高温下发生了非氧化热聚合反应和氧化热聚合反应生成环状化合物[14]。
从香辛料配方与检出的VOCs对应关系看：水芹烯在PF1、PF2、PF6中被检出，而其他配方中未检出，这可能与这三种配方中添加了花椒有关，一些萜类化合物如水芹烯已被确定为花椒油中的特征香气物质[9]，其具有胡椒风味[5]；γ-松油烯在PF2中被检出，而其他配方不含，这可能与其配方中添加了陈皮有关，陈霖虹等[15]在陈皮精油中检测出含量最高的萜烯类物质为γ-松油烯，其具有油香、木香风味；PF4未检出草蒿脑，而其他配方都含有该物质，因此，推测草蒿脑是茴香类香料的特有VOCs，蒲丹丹等[16]在分析小茴香香气活性成分中检测到大量4-烯丙基苯甲醚（草蒿脑），八角中也有测得，这与上述结果一致。PF1与PF4未添加八角（又称大茴香），且两种配方均未检测到大茴香醛，说明大茴香醛是八角特有的VOCs，可与添加了小茴香的调味油进行明显区分。由于五香风味的调味料中桂皮是重要的一味香料，因此在制作调味油中，所有配方都添加了桂皮，顺式肉桂醛在所有配方中均有检测到，其风味描述为具有肉桂香，且相对含量与添加比例相关，其中PF2的桂皮添加量最高，所检测到的顺式肉桂醛相对含量也最高，醛类是桂皮中主要的VOCs类别[17]，其中又以反式肉桂醛为主，由于在高温下易发生异构化，反式肉桂醛转化为顺式结构，两者香气极为相似。一些VOCs如小茴香酮，其在调味油中的检出与是否添加小茴香密切相关，然而，在部分配方（PF2和PF6）中，尽管添加了小茴香，却未检测到小茴香酮。原因可能是：一方面，小茴香本身所含的小茴香酮相对较少；另一方面，在制作过程中，热处理使得小茴香酮的挥发性增强，从而只有少量的小茴香酮能够保留在调味油中。因此，若想增加小茴香酮在调味油中的保留量，可以考虑适当提高小茴香的添加量。
从检出主要VOCs的特性看：从醇类看，PF4检测出桉叶油醇，含量达到10.80%，桉叶油醇具有樟脑气息。除PF1与PF3外，都检出了4-萜烯醇，其具有木香与辛香[18]，此外，α-松油醇与L-α-松油醇分别在PF2、PF5、PF6中被检出，两者同样提供了薄荷香气[19]，肉桂醇在PF2与PF6中检测到，尽管相对含量较低（小于1%），但由于其气味阈值较低，因此对整体风味贡献较大，呈现出香脂和花香的味道[20]。醛类是脂质的衍生物，一般阈值较低，具有脂肪香味[21]，顺式肉桂醛是6种配方调味油的共有物质，枯茗醛在PF3、PF5、PF6中被检出，枯茗醛天然存在于丁香、茴香与肉桂中，具有辛辣味、小茴香味[2]，此外，5-甲基糠醛在除PF1、PF6外的配方中均被检测到，具有甜香、辛香以及咖啡、焦糖的感官特征[22]。酸类物质的总体比例较低，对风味贡献不大。酮类物质主要来源于脂肪氧化和美拉德反应，在调味油中含量不高，且阈值较高，呈现的香气不够鲜明强烈，主要对其他风味起辅助作用，可与调味油中其他风味物质（如醇类、酯类）结合使整体风味更加有层次感且变得饱满[23]，其中香芹酮在PF1与PF3中存在，具有清香和薄荷香[20]。烯烃类物质主要来源于香辛料中，具有较高的气味阈值，对调味油风味起辅助、修饰作用。从各配方调味油整体看，烯烃类种类多但共有成分较少且百分含量普遍偏低，可能与配方本身共性低和烯烃类物质本身存在于香辛料的含量较低有关，但由于茴香在配方中添加较多，因此茴香烯例外。α-蒎烯主要呈清香气味[24]，主要存在于广西桂皮中，其他品类香辛料中也有存在，月桂烯具有清淡的脂香、果香香气[20]，在桂皮、肉豆蔻等香辛料均含有。酯类物质中的反式肉桂酸乙酯、乙酸芳樟酯具有果香和花香的特征，它们对总体气味有协同效应，但乙酸芳樟酯对感官的影响更大[25−26]。其他物质如2-甲基吡嗪、2-乙基吡嗪、2-乙酰基吡咯等具有坚果香或烘烤香，吡嗪类化合物产生原因与油料的加热处理有关，高油温导致发生美拉德反应，碳水化合物降解生成吡嗪的碳链，氨基酸提供了其中的氮原子[27]，2-乙酰基吡咯则是美拉德反应中脯氨酸与单糖反应的产物[28]，但这三种物质并不都存在于各个配方。
2.2.3　五香调味油风味物质的ROAV分析
简单观察相对含量无法判断各个香气成分对整体风味的贡献，许多VOCs本身并不具有香气，或者具有香气的VOCs虽然含量较高，但其气味阈值较高，因此其相对气味活度值较低，对样品整体呈香不能产生明显影响，有些VOCs虽然含量较低，但其气味阈值非常低，相对气味活度值较高，对样品整体香气贡献较大。将GC-MS获得的气味变量利用ROAV方法处理，可以快速判别香气成分对整体风味的贡献，进而筛选出关键风味化合物[29]。通常香气组分ROAV≥1，被认为其对样品香气有很大贡献，0.1≤ROAV<1的组分对样品总体风味具有重要修饰作用，ROAV<0.1的组分对样品香气几乎没有影响。
调味油中的风味物质ROAV如表2所示。已知风味阈值的香气化合物中筛选出14种ROAV≥1的关键香气化合物，按ROAV值的大小排序，在PF1中：草蒿脑>月桂烯>顺式肉桂醛>茴香醚>β-水芹烯，共5种，草蒿脑呈现的大茴香香气是PF1的主要香气类型；在PF2中：大茴香醛>茴香烯>草蒿脑>顺式肉桂醛>月桂烯>β-水芹烯>丁香酚>右旋香芹酮，共8种，其中大茴香醛的ROAV值远高于其他物质，可认为大茴香醛的八角、杏仁味是PF2的主要香气类型；在PF3中：大茴香醛>草蒿脑>茴香醚>顺式肉桂醛>正戊酸>α-蒎烯，共6种，八角、杏仁味是该配方的主要香气；在PF4中：桉叶油醇>顺式肉桂醛>茴香醚>反式肉桂酸乙酯，共4种，其中桉叶油醇的ROAV值最高，主要在该配方中呈现樟脑味；在PF5中：大茴香醛>茴香烯>草蒿脑>顺式肉桂醛>桉叶油醇，共5种，大茴香醛所具有的八角、杏仁味是该配方的主要气味；在PF6中：大茴香醛>草蒿脑>茴香醚>顺式肉桂醛>桉叶油醇>水芹烯>茴香烯>右旋香芹酮>丁香酚，共9种，该配方主要气味为八角、杏仁味。由此可见，除PF4表现为樟脑味，其余配方均表现为八角（茴香）的风味，原因是大茴香醛和草蒿脑的风味阈值低，而且相对含量高，导致ROAV值显著偏高，二者表现出的香气类型成为调味油的主导风味。由于杂环化合物2-甲基吡嗪、2-乙酰基吡咯的风味阈值较高，相对含量低，因此该物质对调味油的整体风味没有影响。
2.3　GC-IMS 对五香调味油风味成分的分析
2.3.1　VOCs指纹图谱分析
GC-IMS作为一种非靶向分析方法，根据保留时间和漂移时间识别VOCs[31]，并具有快速检测、结果直观的特点。GC-IMS获得的谱图如图5所示，其中水平坐标表示迁移时间，垂直坐标表示保留时间，红色垂直线表示归一化反应离子峰（RIP），RIP峰两侧的点代表VOCs，颜色变化代表挥发性成分浓度高低，较低浓度以蓝色显示，较高浓度以红色显示，由图可知，大部分VOCs在迁移时间为4.0~8.0 ms和保留时间200~800 s的范围内。以其中一个样品为对照可生成差异谱图，颜色加深则为VOCs浓度相对较高，反之则相对较低，在图6中可见PF6的VOCs点的颜色发生了明显的加深，说明其VOCs浓度较其他样品升高。在二维图谱上对VOCs点进行具体物质的定性，利用设备自带软件的内置插件生成气味指纹图谱，如图7所示，以便观察不同组间风味化合物的差异。每行代表样品中选择的所有信号峰，每列对应不同样品中同一VOCs的信号峰。不同的颜色表示不同的浓度，白点表示较低的含量，红点表示较高的含量[32]。通过定性，得到45种化合物，其中一种含有二聚体（2-甲氧基-4-乙烯基苯酚），二聚体是具有相近的保留时间和不同的迁移时间的化合物的另一种形式，具体化合物如表3所示。
通过指纹图谱可看出，2-甲氧基-4-乙烯基苯酚在PF1和PF4中含量较低，该物质表现为焦香和丁香香味。肉桂醛在PF4中含量较低，具有肉桂香[33]。α-松油醇具有茴香和薄荷风味，该物质在PF3和PF4中含量较低。2-异丁基-3-甲氧基吡嗪在PF5中含量较低，其具有青椒和花香的特点。在PF3、PF4、PF5中，3-甲硫基丙醛、芳樟醇、二烯丙基二硫化物、α-萜品烯的含量相较其他配方显著偏低，其中3-甲硫基丙醛具有烤土豆香气，芳樟醇具有铃兰香气，二烯丙基二硫化物具有刺鼻蒜味。6种配方都含有的乙酸己酯和丁酸乙酯分别具有果味和甜味[34]，1-辛烯-3-酮则呈现出土壤、蘑菇和金属味[35]。
2.3.2　主成分分析（PCA）
PCA表明，PC1贡献率和PC2贡献率分别为44.1%和28.7%，前两个主成分的累积贡献率为72.8%，说明2个主成分能较好地体现原始数据所反映的信息。由图8可知，主成分分析能够对6种配方调味油进行较好的区分，其中PF1与PF3较为接近，这可能与两者配方相似度较高有关，即都加入了大量的小茴香。PF2与PF6也较为接近，这与GC-MS检测得到的VOCs聚类结果相似。PF4距离其他样品较远，可能与配方中未添加茴香类香料而加入了大量的山柰有关。由于GC-IMS作为一种补充分析手段，与GC-MS的检测原理有所不同，因此其鉴定得到的VOCs与GC-MS所鉴定得到的有较大区别，两者结合应用可以完善五香调味油的整体风味信息。
2.3.3　偏最小二乘判别分析（PLS-DA）
偏最小二乘判别分析是一种基于偏最小二乘回归算法的有监督的分析方法，可实现复杂数据的可视化、判别分析和预测[36]，以五香调味油的VOCs的峰体积和配方为变量使用7倍交叉验证和200次随机重分类对五香调味油VOCs进行置换检验、因子载荷分析和变量重要性投影（Variable importance in projection，VIP）计算。
如图9置换检验模型所示，模型中R2X=0.965，R2Y=0.995，Q2 =0.980，Q2的回归线截距为负值，说明该模型稳定性较好，无过拟合现象，且具有较好的预测能力。由图10因子载荷图可知，VOCs与样品点较为接近说明二者相关性较高，其中，2-异丁基-3-甲氧基吡嗪、丁酸乙酯与PF1相关性较高；3-甲基戊酸、1-辛醇、反式-2-丁烯酸乙酯、乙酸己酯与PF2相关性较高；2,6-二甲基苯酚、1-辛烯-3-酮与PF3相关性较高；乙酸与PF4相关性较高；3-甲硫基丙醛、2-甲基-3-甲硫基呋喃与PF5相关性较高；（+）-α-松油醇与PF6相关性较高。从样品间差异看，PF1、PF12、PF13与PF4、PF15、PF16分别处于横轴两侧，该结果与PCA结果一致。
VIP可用于筛选对6种五香调味油风味轮廓有重要影响的关键风味差异化合物[37]，如图11所示，19种VIP值≥1的VOCs在判别分类中具有重要贡献，按照VIP值高低依次为甲基苯甲醇、2-甲基-2-丙醇、乙酸己酯、氧化芳樟醇、1-辛醇、1-戊烯-3-酮、反式-2-丁烯酸乙酯、3-蒈烯、肉桂醛、2-辛酮、丁酸乙酯、2-异丁基-3-甲氧基吡嗪、2,6-二甲基苯酚、丙酸、2-甲基丁醛、3-甲基戊酸、2-甲基-3-甲硫基呋喃、丙酸异丁酯、2-甲基-2-丙烯醛，VIP值越大，则对五香调味油分类的贡献度越大。
相较GC-IMS方法，HS-SPME-GC-MS方法可检测到烷烃类物质，这可能与烷烃类物质的质子亲和力比水弱有关，而GC-IMS方法依靠化合物的质子亲和力，因此难以检测到烷烃类物质[38]。此外，由于IMS数据库完善度低且两者检测原理（如离子模式）不同[39]，使得到的VOCs存在较大差异且重合度低，HS-SPME-GC-MS方法检测得到的VOCs数量远远高于GC-IMS方法，仅1-戊烯-3-酮、乙酸、2-甲基吡嗪、2-乙酰基呋喃等物质同时被检出，但两种方法的结合可以更全面地定性五香调味油中的VOCs，一般来说，GC-IMS对分子量较小的醛类、酮类、酯类、醇类响应较好，如通过IMS检出了芳樟醇、氧化芳樟醇、庚醛等物质。
3　结论
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本研究采用电子鼻、HS-SPME-GC-MS、GC-IMS相结合的方法对不同配方五香调味油的风味物质进行探究，结果表明各配方的风味物质存在较大差异。在6种配方调味油样品中，通过气质联用共检测出118种VOCs，其中醚类、醛类、醇类、烯烃类物质总体比例较高；通过分析ROAV值确定了14种关键香气化合物，除配方4中具有樟脑味的桉叶油醇对调味油风味影响较大外，其余配方中含有较多的关键香气化合物如草蒿脑、大茴香醛为调味油贡献了较多的八角（茴香）风味。经GC-IMS检测定性得到45种VOCs，通过PLS-DA分析中的VIP值确定了19种关键风味差异化合物，同时发现该检测手段检出的VOCs数量较少，且与GC-MS方法检测得到的VOCs重合度低，但作为一种较新的检测方法，GC-IMS具有方便快捷的优势，无需复杂的手动过程，在风味成分研究中可与GC-MS结合使用形成互补优势。本研究比较了不同配方五香调味油的风味差异及风味特征，以期为香辛料调味油产品开发和风味分析提供参考。

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2026年第47卷第7期
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doi: 10.13386/j.issn1002-0306.2025030296
  • 接收时间：2025-03-25
  • 首发时间：2026-10-24
  • 出版时间：2026-04-01
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  • 收稿日期：2025-03-25
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    1浙江农林大学食品与健康学院，浙江杭州 311300
    2浙江省农业科学院食品科学研究所，浙江杭州 310021
    3北京工商大学轻工科学技术学院，北京市食品风味化学重点实验室，北京 100048
    4浙江顶味食品有限公司，浙江温州 325200

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刘兴泉（1973−），男，博士，教授，研究方向：食品加工与安全，E-mail：。
肖朝耿（1978−），男，硕士，研究员，研究方向：食品加工新技术，E-mail：
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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