Coupling electronic nose with GC–MS improves flavor recognition and grade differentiation of Zhenjiang aromatic vinegar

电子鼻 化学 糠醛 风味 醋酸 色谱法 气相色谱-质谱法 芳香 气相色谱法 质谱法 有机化学 食品科学 神经科学 催化作用 生物
作者
Li Wang,Xingyi Huang,Chengquan Wang,Joshua Harrington Aheto,Xianhui Chang,Shanshan Yu,Xiaorui Zhang,Yu Wang
出处
期刊:Journal of Food Process Engineering [Wiley]
卷期号:44 (10) 被引量:39
标识
DOI:10.1111/jfpe.13806
摘要

Abstract In this study, the flavor volatile profiles of five grades of Zhenjiang aromatic vinegar (ZAV) were compared using a gas chromatography‐mass spectrometer (GC–MS) and electronic nose (E‐nose). A total of 55 volatile compounds were identified, with 14 volatile compounds, including furfural, acetic acid, tetramethylpyrazine, phenethyl acetate, and phenylethyl alcohol, being identified as the key volatile compounds causing significant differences between different grades of ZAV samples. Principal component analysis (PCA) analysis of E‐nose data revealed that the W5S, W1W, W2W, W1S, and W2S sensors with high signal intensity to all ZAV samples correctly categorized the five grades of ZAV samples. The correlation analysis results suggested that the response signal intensities of W5S, W1W, and W2W had significant positive correlations with the abundances of acetic acid, isobutyric acid, ethyl phenylacetate, 3‐hydroxy‐2‐butanone, 2,3‐butanedione, 2‐acetylfuran, etc., adding to the evidence that W5S, W1W, and W2W sensors were sensitive to nitrogen oxides, sulfur compounds, pyrazines, and aromatic components. Based on the findings, it is possible to conclude that E‐nose, in conjunction with chemometric pattern recognition methods, can be used to differentiate between different grades of ZAV based on volatile compounds. Practical Applications Different grades of Zhenjiang aromatic vinegar (ZAV) were distinguished by physical and chemical detection of total acid, nonvolatile acid, amino acid nitrogen and other indicators. In order to simplify the detection work, this study was to establish a rapid and feasible method for achieving ZAV grades differentiation according to their flavor volatile compounds. PCA of E‐nose data showed that the five grades of ZAV samples were well classified by the W5S, W1W, W2W, W1S, and W2S sensors. The correlation analysis results suggested that the response signal intensities of W5S, W1W, and W2W had significant positive correlations with the abundances of acetic acid, isobutyric acid, ethyl phenylacetate, 3‐hydroxy‐2‐butanone, etc., which adds to the proof that W5S, W1W, and W2W sensors were sensitive to nitrogen oxides, sulfur compounds, pyrazines and aromatic components. Therefore, E‐nose can be used as a rapid and nondestructive testing tool for quality measurements of ZAV.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
皮卡狗发布了新的文献求助10
刚刚
小杜关注了科研通微信公众号
刚刚
YikY完成签到 ,获得积分10
1秒前
orixero的应助被淡定的竺采纳,获得10
2秒前
2秒前
2秒前
丘比特的应助被雪意采纳,获得10
2秒前
小二郎的应助被菜菜求带采纳,获得10
2秒前
xy发布了新的文献求助10
3秒前
4秒前
Orange的应助被asetttt采纳,获得10
4秒前
4秒前
WRJ发布了新的文献求助10
5秒前
传奇3的应助被leichen采纳,获得10
5秒前
小天发布了新的文献求助10
6秒前
快乐的鱼完成签到,获得积分10
6秒前
6秒前
7秒前
大个的应助被ww采纳,获得10
7秒前
科研通AI6.2的应助被喜悦桥采纳,获得10
8秒前
lulu完成签到,获得积分10
8秒前
Luckyhai完成签到,获得积分10
8秒前
HelloFM完成签到,获得积分10
8秒前
自觉的牛马完成签到,获得积分10
9秒前
9秒前
9秒前
10秒前
jin完成签到,获得积分10
10秒前
董文强发布了新的文献求助10
11秒前
qiao发布了新的文献求助10
12秒前
12秒前
12秒前
xzz发布了新的文献求助50
13秒前
阿拉完成签到,获得积分10
13秒前
13秒前
13秒前
13秒前
丸子吖发布了新的文献求助10
14秒前
14秒前
共享精神的应助被咕咕采纳,获得10
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Das Matthäusevangelium: Kapitel 1:1–17 1000
Les Mots du discours 600
OREDA手册2009年第5版 500
A Consideration on Use of Material Grades for Hull Structural Members Based on Fracture Toughness(Second Report) 500
AI Disclosure in Annual Reports: Evolution, Determinants, and Capital Market Participants’ Perceptions 500
5th World Conference on Detergents: Reinventing the Industry : Opportunities and Challenges 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8112940
求助须知:如何正确求助?哪些是违规求助? 9519702
关于积分的说明 21525724
捐赠科研通 7690856
什么是DOI,文献DOI怎么找? 3412685
关于科研通互助平台的介绍 2539213
邀请新用户注册赠送积分活动 2452570