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. 2025 Jul 5:29:102743.
doi: 10.1016/j.fochx.2025.102743. eCollection 2025 Jul.

Sensory score prediction and key aroma compounds characterization in fermented chopped pepper

Yuan Liu  1 , Lingyan Zhao  1 , Chunya Yang  1 , Yeyou Qin  2 , Li Zhu  1 , Fangming Deng  1
Affiliations

Sensory score prediction and key aroma compounds characterization in fermented chopped pepper

Yuan Liu et al. Food Chem X. .

Abstract

Fermented chopped pepper (FCP) exhibits complex and variable aroma profiles, making it challenging to accurately predict its sensory scores and identify key aroma compounds. In this study, electronic nose (E-nose) combined with machine learning methods were applied for the prediction of FCPs sensory scores. The random forest (RF) demonstrated the highest predictive accuracy among support vector machine (SVM), multiple linear regression (MLR), and back propagation neural network (BPNN). E-nose combined with the trained RF was used to predict the sensory scores of FCPs from eight regions. Totally, 97 volatile compounds and 19 odor-active compounds were detected by GC × GC-O-Q-TOF-MS in the top-performing sample (FCP-1). Among these, 34 compounds exhibited odor activity values (OAV) greater than 1. Aroma recombination and omission experiments confirmed that linalool, phenethyl alcohol, methional, 3-isobutyl-2-methoxypyrazine, ethyl trans-4-decenoate, β-ionone, spiroxide, ethyl 2-methylbutyrate, α-terpineol, 4-ethylphenol, β-damascenone, and nerolidol were the key aroma compounds in FCP-1.

Keywords: 3-Isobutyl-2-methoxypyrazine (PubChem; 4-Ethylphenol (PubChem; CID: 18635); CID: 24020); CID: 31242); CID: 32594); CID: 5362583); CID: 6054); CID: 61953); CID: 638014); CID:17100); Ethyl 2-methylbutyrate (PubChem; Ethyl trans-4-decenoate (PubChem; Fermented chopped pepper; Key aroma compounds; Linalool (PubChem CID: 6549); Machine learning methods; Methional (PubChem; Odor activity values; Phenethyl alcohol (PubChem; Prediction; Spiroxide (PubChem; α-Terpineol (PubChem; β-Ionone (PubChem.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Unlabelled Image
Graphical abstract
Fig. 1
Fig. 1
Regression plots of predicted vs. measured sensory scores for training and test sets using RF (A), SVM (B), BPNN (C), and MLR (D) models.
Fig. 2
Fig. 2
Radar chart of e-nose sensor responses for 8 types of fermented chopped peppers (A), LDA analysis results (B), and Bar chart of predicted sensory scores in the eight types of ferment chopped peppers (C).
Fig. 3
Fig. 3
GC × GC-O-Q-TOF-MS analysis of representative topographic maps of volatile compounds (A), Venn graph of GC × GC-O-Q-TOF-MS and GC–MS volatile compounds (B) in FCP-1.
Fig. 4
Fig. 4
Radargram of Personnel sensory (A) or E-nose Sensory (B).
See this image and copyright information in PMC

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