Unraveling the chemosensory characteristics of strong-aroma type Baijiu from different regions using comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry and descriptive sensory analysis

芳香 风味 化学 感官分析 质谱法 偏最小二乘回归 气相色谱-质谱法 定量描述分析 气相色谱法 食品科学 色谱法 数学 统计
作者
Yingxia He,Zhipeng Liu,Michael C. Qian,Xiao‐Wei Yu,Yan Xu,Shuang Chen
出处
期刊:Food Chemistry [Elsevier BV]
卷期号:331: 127335-127335 被引量:167
标识
DOI:10.1016/j.foodchem.2020.127335
摘要

Comprehensive 2D gas chromatography–time-of-flight mass spectrometry was combined with descriptive sensory analysis to elucidate the specificity of strong-aroma type Baijiu (Chinese liquor) from different regions, based on regionally distinct flavor characterized by chemical and sensory profiles. Numerous potential aroma compounds (262) were identified, among which 58 aroma compounds were significantly different between the samples from Sichuan and Jianghuai regions. Relationships between these potential aroma compounds and sensory attributes were investigated by partial least squares regression and network analysis. The compounds that dominantly contributed to the important sensory attributes were identified. The high pyrazines, furanoids, and carbonyls amounts contributed to the high intensities of the cellar, toasted, and grain aroma profiles of the Sichuan region samples, while the high ester and alcohol levels contributed to the fruity and floral aroma profiles of the Jianghuai region samples. This approach may have practical application in flavor characterization of other alcoholic beverages.
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
刚刚
1秒前
2秒前
xiang应助肖肖采纳,获得20
3秒前
4秒前
慕青应助maowei采纳,获得10
4秒前
Unicorn发布了新的文献求助10
4秒前
共享精神应助回家放羊采纳,获得10
4秒前
4秒前
yi应助淡然白萱采纳,获得10
5秒前
5秒前
酷波er应助杯酒可醉风雨采纳,获得10
6秒前
6秒前
6秒前
6秒前
NINI给NINI的求助进行了留言
6秒前
丘丘完成签到,获得积分20
7秒前
诚心书南完成签到,获得积分10
7秒前
隐形曼青应助qwz采纳,获得20
7秒前
李健应助虚心的灵寒采纳,获得10
8秒前
Jakssa完成签到,获得积分10
8秒前
ShellyHan发布了新的文献求助200
9秒前
豆腐宣誓完成签到,获得积分10
9秒前
xuyujia完成签到,获得积分10
9秒前
Lucas应助chemchen采纳,获得10
9秒前
9秒前
Bonaventure完成签到,获得积分10
10秒前
10秒前
11秒前
chou1发布了新的文献求助10
11秒前
哈哈哈完成签到 ,获得积分20
11秒前
FashionBoy应助波子汽水采纳,获得10
11秒前
11秒前
任伟超发布了新的文献求助10
12秒前
Ava应助坚强的大凄采纳,获得10
13秒前
14秒前
所所应助Stella采纳,获得10
14秒前
14秒前
ShellyHan完成签到,获得积分10
14秒前
15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
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Synthesis of P-Chiral Phosphine Ligands and Their Applications in Asymmetric Catalysis 400
Management and the Arts 310
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7629705
求助须知:如何正确求助?哪些是违规求助? 9204069
关于积分的说明 19736982
捐赠科研通 7199182
什么是DOI,文献DOI怎么找? 3274314
关于科研通互助平台的介绍 2436445
邀请新用户注册赠送积分活动 2270480