# Unraveling the difference in aroma characteristics of tomato flesh with different colors using HS-SPME-GC–MS/MS and E-nose combined with multivariate data analysis

## TL;DR

This study identifies 154 volatile compounds in tomatoes of different colors and finds 16 key compounds that may explain flavor differences, using advanced analytical and machine learning techniques.

## Contribution

The study combines HS-SPME-GC–MS/MS, E-nose, and LightGBM to identify color-specific aroma compounds in tomatoes, revealing 16 VOCs linked to fruit color.

## Key findings

- 154 volatile organic compounds were identified in 16 tomato varieties with four different fruit colors.
- Twenty-six VOCs were found to significantly contribute to tomato aroma based on odor activity values.
- Multivariate analysis identified 16 VOCs strongly associated with fruit color, aiding flavor evaluation and improvement.

## Abstract

Aroma profiles of tomato flesh from 16 tomato varieties with 4 different fruit colors were characterized by headspace-solid phase microextraction coupled with gas chromatography-triple quadrupole mass spectrometry (HS-SPME-GC–MS/MS) and electronic nose (E-nose). A total of 154 volatile organic compounds (VOCs) were qualitatively and semi-quantitatively identified, including 29 aldehydes, 22 hydrocarbons, 21 alcohols, 32 unknown compounds, and others, with aldehydes being the most abundant. Twenty-six characteristic VOCs might be major contributors to tomato flavor by relative odor activity value analysis. The correlation between E-nose sensor responses and GC–MS/MS volatile profiles was also examined. The machine learning models were constructed to show potential for distinguishing the fruit colors of the tomato. Finally, 16 fruit color-indicating VOCs were selected via multivariate data analysis. The present study will contribute to flavor evaluation and provide a chemical basis for future tomato flavor improvement, to be accompanied by sensory validation.

•HS-SPME-GC–MS/MS identified 154 VOCs in the flesh of 16 tomato varieties.•Twenty-six characteristic volatiles contributed to various aroma notes.•E-nose and GC–MS/MS combined with LightGBM showed potential to classify fruit colors.•Multivariate data analysis uncovered 16 fruit color-indicative VOCs.

HS-SPME-GC–MS/MS identified 154 VOCs in the flesh of 16 tomato varieties.

Twenty-six characteristic volatiles contributed to various aroma notes.

E-nose and GC–MS/MS combined with LightGBM showed potential to classify fruit colors.

Multivariate data analysis uncovered 16 fruit color-indicative VOCs.