# Analysis of volatile compounds in Aglaia odorata flower extracts with different possessing methods by HS-SPME-GC-MS and E-nose

## TL;DR

This study compares how different extraction methods affect the volatile compounds and aroma of Aglaia odorata flower extracts using advanced analytical techniques.

## Contribution

The study introduces a multidimensional analysis combining HS-SPME-GC-MS and E-nose to evaluate extraction method impacts on AOFE volatile profiles.

## Key findings

- UAE and MAE extracts showed similar volatile compound profiles but differed in concentration and aroma intensity.
- HRE produced fewer compounds and distinct green and spicy aroma characteristics compared to UAE and MAE.
- Eight key volatile markers were identified as contributors to the sweet and floral aroma of AOFEs.

## Abstract

To investigate the impact of different processing methods on the volatile components in Aglaia odorata flower extract (AOFEs).

Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and electronic nose (E-Nose) analysis were employed to characterize volatiles of extracts obtained by ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), and heated reflux extraction (HRE). Multidimensional assessment using aroma radar charts, orthogonal partial least squares-discriminant analysis (OPLS-DA), K-means clustering, and relative odor activity value (ROAV) revealed significant processing-dependent variations.

The results indicated that the fiber coated with DVB/CAR/PDMS had optimal extraction efficiency. A total of 46 compounds were identified, including eight alcohols, four aldehydes, one acid, 25 terpenes, seven ketones, and one heterocyclic compound. UAE and MAE had 36 and 38 compounds respectively, sharing similar compositional profiles but differing in concentrations, while HRE produced only 25 compounds Sensory evaluation and E-Nose results revealed differences in the aroma profiles of the extracts, with UAE and MAE extracts exhibiting intensified floral and sweet notes, whereas HRE displayed prominent green and spicy characteristics. K-means clustering categorized volatile evolution trends into four distinct subclasses. OPLS-DA identified 13 differential volatiles with variable importance in projection greater than 1, with ROAV analysis further selecting eight key markers, including (1R,7S)-germacra-4(15),5,10(14)-trien-1β-ol, α-humulene, copaene, β-cadinene, (E)-β-caryophylene, Γ-cadinene, humulene oxide II, and caryophyllene oxide. These compounds collectively contribute to the sweet and floral attributes of AOFEs. This study elucidated extraction-method-dependent volatile profiles and aroma characteristics, providing theoretical guidance for process optimization and quality enhancement in AOFEs production.

Aglaia odorata Lour. flower samples are processed into three extract types: HRE, MAE, and UAE, then analyzed by HS-SPME-GC-MS and electronic nose to assess volatile composition, aroma characteristics, and undergo sensory and multivariate statistical analysis, including pie charts of compound classes, radar plots, PCA, and heat maps of identified compounds.