Characterization of Qu-aroma of medium–high temperature Daqu from different production areas using sensory evaluation, E-nose, and GC–MS/O analysis

Qu-aroma is a critical quality indicator for medium-high temperature Daqu (MT-Daqu). Due to the differences in regional and environmental conditions, these differences are likely to cause variations in the Qu-aroma of MT-Daqu. Despite this, comprehensive research on the variations in Qu-aroma across different regions has been lacking. This study aims to address this gap to analyze the differences in Qu-aroma characteristics of MT-Daqu from seven distinct production areas. Sensory analysis identified seven broad aroma categories and 25 specific aromas characterizing the Qu-aroma of MT-Daqu samples. Chen aroma and roasted aroma were notably more prevalent in MT-Daqu samples from Sichuan compared to those from other regions (P < 0.05). In total, 123 volatile compounds were detected in MT-Daqu, with 42 classified as aroma-active compounds. Among these, 21 aroma-active compounds were identified as markers distinguishing Sichuan MT-Daqu from those produced in non-Sichuan regions, showing significant differences in their concentrations (P < 0.05). Additionally, six major aroma-active compounds were found to significantly contribute to the aroma differences between Sichuan and non-Sichuan MT-Daqu. This study delineates the distinct Qu-aroma characteristics of MT-Daqu from various SAB production areas. The insights gained from this research offer valuable guidance for optimizing flavor profiles in MT-Daqu production.

Authors

Institutions

Publication Details

Journal
Bioresources and Bioprocessing
Published
2025-04-25
DOI
https://doi.org/10.1186/s40643-025-00863-y
Citations
6
Primary Topic
Fermentation and Sensory Analysis
Type
article
Field-Weighted Citation Impact
6.97

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterization of Qu-aroma of medium–high temperature Daqu from different production areas using sensory evaluation, E-nose, and GC–MS/O analysis

Guangbin Ye, Dan Huang, Jia Zheng, Xing Li et al.
6 citations
Bioresources and Bioprocessing
Fermentation and Sensory Analysis
6.97
article

Characterization of Qu-aroma of medium–high temperature Daqu from different production areas using sensory evaluation, E-nose, and GC–MS/O analysis

Guangbin Ye, Dan Huang, Jia Zheng, Xing Li, Huibo Luo, Jie Deng
article en
6 citations

Abstract

Qu-aroma is a critical quality indicator for medium-high temperature Daqu (MT-Daqu). Due to the differences in regional and environmental conditions, these differences are likely to cause variations in the Qu-aroma of MT-Daqu. Despite this, comprehensive research on the variations in Qu-aroma across different regions has been lacking. This study aims to address this gap to analyze the differences in Qu-aroma characteristics of MT-Daqu from seven distinct production areas. Sensory analysis identified seven broad aroma categories and 25 specific aromas characterizing the Qu-aroma of MT-Daqu samples. Chen aroma and roasted aroma were notably more prevalent in MT-Daqu samples from Sichuan compared to those from other regions (P < 0.05). In total, 123 volatile compounds were detected in MT-Daqu, with 42 classified as aroma-active compounds. Among these, 21 aroma-active compounds were identified as markers distinguishing Sichuan MT-Daqu from those produced in non-Sichuan regions, showing significant differences in their concentrations (P < 0.05). Additionally, six major aroma-active compounds were found to significantly contribute to the aroma differences between Sichuan and non-Sichuan MT-Daqu. This study delineates the distinct Qu-aroma characteristics of MT-Daqu from various SAB production areas. The insights gained from this research offer valuable guidance for optimizing flavor profiles in MT-Daqu production.

Bioresources and BioprocessingVol. 12(1)
Beijing Technology and Business University (CN), Yibin University (CN), Second People’s Hospital of Yibin (CN), Sichuan University of Science and Engineering (CN)
Sichuan Province Science and Technology Support Program
Openalex Percentile: Top 3%
Fermentation and Sensory Analysis
6.97
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.