The Aroma, Taste Contributions, and Flavor Evaluation Based on GC-IMS, E-Nose, and E-Tongue in Soybean Pastes: A Comparative Study

The objective of this study was to assess and compare the characteristics of different soybean pastes by using intelligent sensory analysis. In this study, color, flavor, texture, and taste were regarded as four factors affecting the sensory quality of soybean pastes and the sensory quality of four different soybean pastes was evaluated using fuzzy mathematics. The sensory evaluation scores of samples L, Z, and W were very similar and significantly higher than that of sample Y. Gas chromatography-ion mobility spectrometry (GC-IMS) detected 111 volatile flavor compounds, with acids, alcohol, and ketones having a significantly higher relative content than other compounds, indicating their vital role in the flavor formation process of soybean pastes. Furthermore, partial least squares discriminant analysis (PLS-DA) model analysis identified 41 marker compounds that could differentiate the four types of soybean pastes. The overall odor and flavor profile were detected by the E-nose and E-tongue. These fundamental results lay the groundwork for future research on the similarities and differences between the flavor characteristics of different brands of soybean paste.

Authors

Institutions

Publication Details

Journal
Foods
Published
2025-03-27
DOI
https://doi.org/10.3390/foods14071178
Citations
6
Primary Topic
GABA and Rice Research
Type
article
Field-Weighted Citation Impact
10.50
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Aroma, Taste Contributions, and Flavor Evaluation Based on GC-IMS, E-Nose, and E-Tongue in Soybean Pastes: A Comparative Study

Lishui Chen, Jing Yan, Fazheng Ren, Heng Wang et al.
6 citations
Foods
GABA and Rice Research
10.50
article

The Aroma, Taste Contributions, and Flavor Evaluation Based on GC-IMS, E-Nose, and E-Tongue in Soybean Pastes: A Comparative Study

Lishui Chen, Jing Yan, Fazheng Ren, Heng Wang, Wanli Zhang, Zijie Dong, Zhenxia Cao, Bing Yang
article en
6 citations

Abstract

The objective of this study was to assess and compare the characteristics of different soybean pastes by using intelligent sensory analysis. In this study, color, flavor, texture, and taste were regarded as four factors affecting the sensory quality of soybean pastes and the sensory quality of four different soybean pastes was evaluated using fuzzy mathematics. The sensory evaluation scores of samples L, Z, and W were very similar and significantly higher than that of sample Y. Gas chromatography-ion mobility spectrometry (GC-IMS) detected 111 volatile flavor compounds, with acids, alcohol, and ketones having a significantly higher relative content than other compounds, indicating their vital role in the flavor formation process of soybean pastes. Furthermore, partial least squares discriminant analysis (PLS-DA) model analysis identified 41 marker compounds that could differentiate the four types of soybean pastes. The overall odor and flavor profile were detected by the E-nose and E-tongue. These fundamental results lay the groundwork for future research on the similarities and differences between the flavor characteristics of different brands of soybean paste.

FoodsVol. 14(7)
Luohe Medical College (CN), China Agricultural University (CN)
Openalex Percentile: Top 2%
GABA and Rice Research
10.50
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.

The Aroma, Taste Contributions, and Flavor Evaluation Based on GC-IMS, E-Nose, and E-Tongue in Soybean Pastes: A Comparative Study — Lishui Chen, Jing Yan, et al. · Foods (2025) | TGRS Research Map | TGRS