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

## TL;DR

This study uses machine learning and chemical analysis to predict sensory scores and identify key aroma compounds in fermented chopped pepper.

## Contribution

The study introduces a novel combination of electronic nose and random forest models for predicting sensory scores in fermented foods.

## Key findings

- Random forest outperformed other models in predicting sensory scores of fermented chopped pepper.
- GC × GC-O-Q-TOF-MS identified 97 volatile compounds, 34 of which had high odor activity values.
- 12 key aroma compounds were confirmed through recombination and omission experiments.

## 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.

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•Four machine learning models predicted sensory scores of fermented chopped peppers.•GC × GC-Q-TOF-MS identified 97 volatiles in FCP-1, with 34 having OAV > 1.•Esters, aldehydes, pyrazine, etc., were the main volatile compounds in FCP-1.•12 key aroma compounds were identified through recombination and omission tests.

Four machine learning models predicted sensory scores of fermented chopped peppers.

GC × GC-Q-TOF-MS identified 97 volatiles in FCP-1, with 34 having OAV > 1.

Esters, aldehydes, pyrazine, etc., were the main volatile compounds in FCP-1.

12 key aroma compounds were identified through recombination and omission tests.