Identification of characteristic volatiles of Zhenjiang aromatic vinegar using HS-SPME-GC/MS coupled with multivariate analysis

IF 2.1 3区 农林科学 Q3 CHEMISTRY, APPLIED
Zhihua Li, Wenbing Fang, Siwen Wang, Jiyong Shi, Xiaobo Zou, Xiaowei Huang
{"title":"Identification of characteristic volatiles of Zhenjiang aromatic vinegar using HS-SPME-GC/MS coupled with multivariate analysis","authors":"Zhihua Li,&nbsp;Wenbing Fang,&nbsp;Siwen Wang,&nbsp;Jiyong Shi,&nbsp;Xiaobo Zou,&nbsp;Xiaowei Huang","doi":"10.1002/ffj.3796","DOIUrl":null,"url":null,"abstract":"<p>This study employed headspace solid phase micro-extraction gas chromatography mass spectrometry (HS-SPME-GC–MS) coupled with multivariate statistical analysis to identify volatile markers in various levels of Zhenjiang Aromatic Vinegar (ZAV). A full range of 40 volatile organic compounds (VOCs) were identified and categorized into acids, alcohols, esters, aldehydes, ketones, heterocyclic compounds and others. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) demonstrated a clear clustering effect among different levels of ZAV, indicating distinct volatile characteristics at the relative content level. Furthermore, using Orthogonal partial least squares discrimination analysis (OPLS-DA), 20 significant volatile organic compounds (VOCs) were identified as markers for distinguishing between the various levels of ZAV. To differentiate among the levels of ZAV, two volatile compounds, acetic acid and n-hexanol, were identified as characteristic volatile compounds using a combination of Venn diagram, analysis of variance (ANOVA) and boxplot analysis. The results showed notable variations in VOCs among ZAV samples of different grades. Acetic acid and n-hexanol can serve as reliable markers for grade distinction, providing valuable technical and theoretical support for the production and quality control of ZAV.</p>","PeriodicalId":170,"journal":{"name":"Flavour and Fragrance Journal","volume":"39 5","pages":"271-281"},"PeriodicalIF":2.1000,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Flavour and Fragrance Journal","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ffj.3796","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

This study employed headspace solid phase micro-extraction gas chromatography mass spectrometry (HS-SPME-GC–MS) coupled with multivariate statistical analysis to identify volatile markers in various levels of Zhenjiang Aromatic Vinegar (ZAV). A full range of 40 volatile organic compounds (VOCs) were identified and categorized into acids, alcohols, esters, aldehydes, ketones, heterocyclic compounds and others. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) demonstrated a clear clustering effect among different levels of ZAV, indicating distinct volatile characteristics at the relative content level. Furthermore, using Orthogonal partial least squares discrimination analysis (OPLS-DA), 20 significant volatile organic compounds (VOCs) were identified as markers for distinguishing between the various levels of ZAV. To differentiate among the levels of ZAV, two volatile compounds, acetic acid and n-hexanol, were identified as characteristic volatile compounds using a combination of Venn diagram, analysis of variance (ANOVA) and boxplot analysis. The results showed notable variations in VOCs among ZAV samples of different grades. Acetic acid and n-hexanol can serve as reliable markers for grade distinction, providing valuable technical and theoretical support for the production and quality control of ZAV.

Abstract Image

利用 HS-SPME-GC/MS 结合多元分析鉴定镇江香醋的特征挥发物
本研究采用顶空固相微萃取气相色谱质谱法(HS-SPME-GC-MS),结合多元统计分析,对镇江香醋(ZAV)中不同含量的挥发性标记物进行了鉴定。共鉴定出 40 种挥发性有机化合物(VOC),并将其分为酸类、醇类、酯类、醛类、酮类、杂环化合物等。主成分分析(PCA)和层次聚类分析(HCA)显示,不同级别的 ZAV 之间存在明显的聚类效应,表明在相对含量水平上存在不同的挥发性特征。此外,利用正交偏最小二乘判别分析(OPLS-DA),确定了 20 种重要的挥发性有机化合物(VOC),作为区分不同水平 ZAV 的标记。为了区分不同水平的 ZAV,结合使用 Venn 图、方差分析 (ANOVA) 和方框图分析,确定了醋酸和正己醇这两种挥发性化合物为特征挥发性化合物。结果表明,不同等级的 ZAV 样品在挥发性有机化合物方面存在显著差异。乙酸和正己醇可作为区分等级的可靠标记,为 ZAV 的生产和质量控制提供了宝贵的技术和理论支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Flavour and Fragrance Journal
Flavour and Fragrance Journal 工程技术-食品科技
CiteScore
6.00
自引率
3.80%
发文量
40
审稿时长
1 months
期刊介绍: Flavour and Fragrance Journal publishes original research articles, reviews and special reports on all aspects of flavour and fragrance. Its high scientific standards and international character is ensured by a strict refereeing system and an editorial team representing the multidisciplinary expertise of our field of research. Because analysis is the matter of many submissions and supports the data used in many other domains, a special attention is placed on the quality of analytical techniques. All natural or synthetic products eliciting or influencing a sensory stimulus related to gustation or olfaction are eligible for publication in the Journal. Eligible as well are the techniques related to their preparation, characterization and safety. This notably involves analytical and sensory analysis, physical chemistry, modeling, microbiology – antimicrobial properties, biology, chemosensory perception and legislation. The overall aim is to produce a journal of the highest quality which provides a scientific forum for academia as well as for industry on all aspects of flavors, fragrances and related materials, and which is valued by readers and contributors alike.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信