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Characterization of aroma profiles of chinese four most famous traditional red-cooked chickens using GC–MS, GC-IMS, and E-nose

Research Authors
Xiangxiang Sun, Yumei Yu, Ahmed SM Saleh, Xinyu Yang, Jiale Ma, Ziwu Gao, Dequan Zhang, Wenhao Li, Zhenyu Wang
Research Abstract

The aroma profile of the four most popular types of red-cooked chickens in China was analyzed using a combination of gas chromatography-mass spectrometry (GC–MS), gas chromatography-ion mobility spectrometry (GC-IMS), and electronic nose (E-nose). Principal component analysis (PCA) demonstrated that the E-nose could successfully distinguish between the four types of red-cooked chickens. Additionally, a fingerprint was created using GC-IMS to examine the variations in volatile organic compounds (VOCs) distribution in the four chicken types. A total number of 84 and 62 VOCs were identified in the four types of red-cooked chickens using GC–MS and GC-IMS, respectively. Odor activity value (OAV) showed that 1-octen-3-ol, heptanal, hexanal, nonanal, octanal, eugenol, dimethyl trisulfide, anethole, anisaldehyde, estragole, and eucalyptol were the key volatile components in all samples. Furthermore, partial least squares-discriminant analysis (PLS-DA) demonstrated that (E, E)-2,4-decadienal, dimethyl trisulfide, octanal, eugenol, hexanal, (E)-2-nonenal, 1-octen-3-ol, butanal, ethyl acetate, ethyl acetate (D), nonanal, and heptanal could be used as markers to distinguish aroma of the four types of red-cooked chickens. Also, it is worth noting that levels of VOCs varied between chicken breast muscle and skin. The obtained results offer theoretical and technological support for flavor identification and control in red-cooked chickens to enhance their quality and encourage consumer consumption, which will be advantageous for the red-cooked chicken production chain. 

Research Date
Research Journal
Food Research International
Research Member
Research Publisher
Elsevier
Research Vol
173
Research Website
https://www.sciencedirect.com/science/article/abs/pii/S0963996923008803
Research Year
2023