Differential Non-Volatile Metabolomics in High- and Low-Alcohol Strong-Flavor Baijiu by Non-Targeted Approach

Alcohol level is a critical quality parameter in Chinese baijiu, significantly influencing its flavor profile, sensory characteristics, and overall quality, which in turn affect consumer preferences and the development of the liquor industry. Understanding the non-volatile compounds in strong-flavor baijiu (SFB) is essential for elucidating its taste and mouthfeel characteristics. This study aims to identify non-volatile compounds using a non-targeted metabolomics approach and investigate the differences between high- and low-alcohol SFB from the Jiangsu region. A total of 647 non-volatile compounds were quantified. The key differential metabolites were screened among different samples. In total, 110 key differential non-volatile compounds were identified and quantified, which displayed significant differences between high- and low-alcohol SFB samples and showed notable similarities in compound types. Furthermore, the variation in non-volatile profiles among samples of the same brand but different alcohol levels was investigated. The different brands and origins of SFB samples were identified using OPLS-DA. The results indicated that the key non-volatile metabolites in most of the high-alcohol samples were higher than those in low-alcohol samples. This study provides valuable insights into the impact of alcohol level on the non-volatile composition of SFB, offering a theoretical foundation for flavor characterization, quality control, and standardization in baijiu production.

Authors

Institutions

Publication Details

Journal
Foods
Published
2025-12-22
DOI
https://doi.org/10.3390/foods15010037
Primary Topic
Fermentation and Sensory Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Differential Non-Volatile Metabolomics in High- and Low-Alcohol Strong-Flavor Baijiu by Non-Targeted Approach

Yajiao Zhao, Dengyong Liu, Panpan Chen, Shui Jiang et al.
Foods
Fermentation and Sensory Analysis
article

Differential Non-Volatile Metabolomics in High- and Low-Alcohol Strong-Flavor Baijiu by Non-Targeted Approach

Yajiao Zhao, Dengyong Liu, Panpan Chen, Shui Jiang, Xu Feng, Ying Liu, Fan YuXia, Chenxi Qiu, Yufa Cao, Shi Liu
article en

Abstract

Alcohol level is a critical quality parameter in Chinese baijiu, significantly influencing its flavor profile, sensory characteristics, and overall quality, which in turn affect consumer preferences and the development of the liquor industry. Understanding the non-volatile compounds in strong-flavor baijiu (SFB) is essential for elucidating its taste and mouthfeel characteristics. This study aims to identify non-volatile compounds using a non-targeted metabolomics approach and investigate the differences between high- and low-alcohol SFB from the Jiangsu region. A total of 647 non-volatile compounds were quantified. The key differential metabolites were screened among different samples. In total, 110 key differential non-volatile compounds were identified and quantified, which displayed significant differences between high- and low-alcohol SFB samples and showed notable similarities in compound types. Furthermore, the variation in non-volatile profiles among samples of the same brand but different alcohol levels was investigated. The different brands and origins of SFB samples were identified using OPLS-DA. The results indicated that the key non-volatile metabolites in most of the high-alcohol samples were higher than those in low-alcohol samples. This study provides valuable insights into the impact of alcohol level on the non-volatile composition of SFB, offering a theoretical foundation for flavor characterization, quality control, and standardization in baijiu production.

FoodsVol. 15(1)
Shanghai Jiao Tong University (CN), Ningxia University (CN), Bohai University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 36%
Fermentation and Sensory Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.