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Volatile Compounds Fingerprints for White Duck down and White Goose down Determined by Gas Chromatography-Ion Mobility Spectrometry

Volatile Compounds Fingerprints for White Duck down and White Goose down Determined by Gas Chromatography-Ion Mobility Spectrometry
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摘要 This work first describes a simple approach for the untargeted profiling of volatile compounds for distinguishing between white duck down (WDD) and white goose down (WGD) based on resolution-optimized GC-IMS combined with optimized chemometric techniques, namely PCA. The detection method for down samples was established by using GC-IMS. Meanwhile, the reason of unpleasant odors caused by WDD was explained on the basis of the characteristic volatile compounds identification. GC-IMS fingerprinting can be considered a revolutionary approach for a truly fully automatable, cost-efficient, and in particular highly sensitive method. A total of 22 compounds were successfully separated and identified through GC-IMS method, and the significant differences in volatile compounds were observed in three parts of WDD and WGD samples. The most characteristic volatile compounds of WGD belong to aldehydes, whereas carboxylic acids from WDD were detected generated by autoxidation reaction. Meanwhile, the main reason of unpleasant odor generation was possibly attributed to the high concentration of volatile carboxylic acids of WDD. Therefore, the constructed model presents a simple and efficient method of analysis and serves as a basis for down processing and quality control. This work first describes a simple approach for the untargeted profiling of volatile compounds for distinguishing between white duck down (WDD) and white goose down (WGD) based on resolution-optimized GC-IMS combined with optimized chemometric techniques, namely PCA. The detection method for down samples was established by using GC-IMS. Meanwhile, the reason of unpleasant odors caused by WDD was explained on the basis of the characteristic volatile compounds identification. GC-IMS fingerprinting can be considered a revolutionary approach for a truly fully automatable, cost-efficient, and in particular highly sensitive method. A total of 22 compounds were successfully separated and identified through GC-IMS method, and the significant differences in volatile compounds were observed in three parts of WDD and WGD samples. The most characteristic volatile compounds of WGD belong to aldehydes, whereas carboxylic acids from WDD were detected generated by autoxidation reaction. Meanwhile, the main reason of unpleasant odor generation was possibly attributed to the high concentration of volatile carboxylic acids of WDD. Therefore, the constructed model presents a simple and efficient method of analysis and serves as a basis for down processing and quality control.
作者 Fei Wang Qihui Zhang Yiwen Lin Wenjian Chen Hui Wang Kuntai Li Jihua Li Yuliang Chen Leiyu Wang Fei Wang;Qihui Zhang;Yiwen Lin;Wenjian Chen;Hui Wang;Kuntai Li;Jihua Li;Yuliang Chen;Leiyu Wang(Agricultural Products Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, China;College of Biological Sciences and Engineering, Jiangxi Agricultural University, Nanchang, China;Zhanjiang Zikang Fiderdown Production Company Ltd., Zhanjiang, China;School of Food Science & Technology, Guangdong Ocean University, Zhanjiang, China)
出处 《Agricultural Sciences》 CAS 2023年第3期432-445,共14页 农业科学(英文)
关键词 Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) Principal Components Analysis (PCA) DOWN Characteristic Volatiles Fingerprints Carboxylic Acids Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) Principal Components Analysis (PCA) Down Characteristic Volatiles Fingerprints Carboxylic Acids
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