Lipidomics combined with random forest machine learning algorithms to reveal freshness markers for duck eggs during storage in different rearing systems

文献类型： 外文期刊

第一作者： Chen, Mengying

作者： Chen, Mengying;Gong, Lan;Zhu, Lei;Fang, Xiaomin;Wei, Ruicheng;Wang, Ran;Chen, Mengying;Zhang, Can;You, Zhaorong

作者机构：

关键词： duck egg; 2 rearing system; untargeted lipidomic; random forest algorithm; marker compound

期刊名称：POULTRY SCIENCE （ 影响因子：4.2； 五年影响因子：4.5 ）

ISSN： 0032-5791

年卷期： 2024 年 103 卷 11 期

页码：

收录情况： SCI

摘要： The differences in lipids in duck eggs between the 2 rearing systems during storage have not been fully studied. Herein, we propose untargeted lipidomics combined with a random forest (RF) algorithm to identify potential marker lipids based on ultra-perfor(UPLPC-MS/MS). A total of 106 and 16 differential lipids (DL) were screened in egg yolk and white, respectively. In yolk, metabolic pathway analysis of DLs revealed that glycerophospholipid metabolism and ways in the traditional free-range system (TFS) during storage, glycosylphosphatidylinositol-anchored biosynthesis and glyceride metabolism were the key pathways in the floor-rearing system (FRS). In egg white, the key pathway in both systems is the biosynthesis of unsaturated fatty acids. Combined with RF algorithm, 12 marker lipids were screened during storage. Therefore, this study elucidates the changes in lipids in duck eggs during storage in 2 rearing systems and provides new ideas for screening marker lipids during storage. This approach is highly important for evaluating the quality of egg and egg products and provides guidance for duck egg production.

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