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不同中国鸡种挥发性有机成分的气相色谱-离子迁移谱及多变量分析

GC-IMS and multivariate analyses of volatile organic components in different Chinese breeds of chickens.

作者信息

Li Hongqiang, Zhao Xiangmin, Qin Shizhen, Li Jinlu, Tang Defu, Xi Bin

机构信息

College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.

Laboratory of Quality & Safety Risk Assessment for Livestock Products of Ministry of Agriculture, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.

出版信息

Heliyon. 2024 Apr 15;10(8):e29664. doi: 10.1016/j.heliyon.2024.e29664. eCollection 2024 Apr 30.

Abstract

This study examined the difference in volatile flavor characteristics among four different local breeds of chicken by headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with multivariate analysis. In total, 65 volatile organic compounds (VOCs) were identified (17 aldehydes, 12 alcohols, 7 ketones, 5 esters, 2 acids, and 22 unidentified, i.e., 26.15% aldehydes, 18.46% alcohols, 10.77% ketones, 7.69% esters, 3.08% acids, and 33.84% unidentified), of which 43 were annotated. The chicken meats from the four breeds exhibited good separation in topographic plots, VOC fingerprinting, and multivariate analysis. Meanwhile, 20 different volatile components, with variable importance in projection value > 1, were selected as potential markers to distinguish different breeds of chicken by partial least squares discriminant analysis (PLS-DA). These findings provide insights into the flavor traits of chicken meat. Also, HS-GC-IMS combined with multivariate analysis can be a convenient and powerful method for characterizing different meats.

摘要

本研究采用顶空气相色谱-离子迁移谱(HS-GC-IMS)结合多变量分析,研究了四种不同本地鸡品种挥发性风味特征的差异。共鉴定出65种挥发性有机化合物(VOCs)(17种醛类、12种醇类、7种酮类、5种酯类、2种酸类和22种未鉴定的,即醛类占26.15%、醇类占18.46%、酮类占10.77%、酯类占7.69%、酸类占3.08%、未鉴定的占33.84%),其中43种得到了注释。四个品种的鸡肉在地形图、VOC指纹图谱和多变量分析中表现出良好的分离。同时,通过偏最小二乘判别分析(PLS-DA),选择了20种投影变量重要性>1的不同挥发性成分作为区分不同鸡品种的潜在标志物。这些发现为鸡肉的风味特征提供了见解。此外,HS-GC-IMS结合多变量分析可以成为表征不同肉类的一种便捷而强大的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f4e/11035028/ffec07b41105/gr1.jpg

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