Article

Volatile compounds for discrimination between beef, pork, and their admixture using SPME-GC-MS and chemometrics analysis

Zubayed Ahamed1, Jin-Kyu Seo1, Jeong-Uk Eom1, Han-Sul Yang1,2,*
Author Information & Copyright
1Division of Applied Life Science (BK21Four), Gyeongsang National University, Jinju 52828, Korea
2Institute of Agriculture and Life Science Gyeongsang National University, Jinju 52828 Korea
*Corresponding Author: Han-Sul Yang. E-mail: hsyang@gnu.ac.kr.

© Copyright 2024 Korean Society for Food Science of Animal Resources. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Feb 19, 2024 ; Revised: Apr 04, 2024 ; Accepted: Apr 15, 2024

Published Online: Apr 19, 2024

Abstract

This study addresses the prevalent issue of meat species authentication and adulteration through a chemometrics-based approach, crucial for upholding public health and ensuring a fair marketplace. Volatile compounds were extracted and analyzed using headspace-solid-phase-microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Adulterated meat samples were effectively identified through principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Through variable importance in projection (VIP) scores and a Random Forest test, 11 key compounds, including nonanal, octanal, hexadecanal, benzaldehyde, 1-octanol, hexanoic acid, heptanoic acid, octanoic acid, and 2-acetylpyrrole for beef, and hexanal and 1-octen-3-ol for pork, were robustly identified as biomarkers. These compounds exhibited a discernible trend in adulterated samples based on adulteration ratios, evident in a heatmap. Notably, lipid degradation compounds strongly influenced meat discrimination. PCA and PLS-DA yielded significant sample separation, with the first two components capturing 80% and 72.1% of total variance, respectively. This technique could be a reliable method for detecting meat adulteration in cooked meat.

Keywords: SPME-GC-MS; Adulteration; PLS-DA; PCA; Cooked meat