Exploring molecular mechanisms underlying changes in lipid fingerprinting of salmon (Salmo salar) during air frying integrating machine learning-guided REIMS and lipidomics analysis

文献类型： 外文期刊

第一作者： Song, Gongshuai

作者： Song, Gongshuai;Zeng, Mingwei;Jiang, Nengliang;Wang, Danli;Yuan, Tinglan;Li, Ling;Gong, Jinyan;Song, Gongshuai;Chen, Shengjun;Song, Gongshuai;Shen, Qing;Lyu, Zhangfan;Mei, Guangming

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关键词： Salmon; Air frying; Lipids oxidation; Lipidomics; Machine learning

期刊名称：FOOD CHEMISTRY （ 影响因子：8.5； 五年影响因子：8.2 ）

ISSN： 0308-8146

年卷期： 2024 年 460 卷

页码：

收录情况： SCI

摘要： Lipid oxidation in air-fried seafood poses a risk to human health. However, the effect of a prooxidant environment on lipid oxidation in seafood at different air frying (AF) temperatures remains unknown. An integrated machine learning (ML) - guided REIMS and lipidomics method was applied to explore lipid profiles, lipid oxidation, and lipid metabolic pathways of salmons under different AF temperatures (140, 160, 180, and 200 degrees C). A significant difference in the lipidomic fingerprinting of air-dried salmon at different temperatures was shown by the main ML methods (neural networks, support vector machines, ensemble learning, and na & iuml;ve bayes). In total, 773 differential expression metabolites (DEMs) were identified, including glycerophospholipids (GPs), glycerides (GLs), and sphingolipids. A total of 34 DEMs with p values <0.05 and variable importance of projection values >1.0 were analyzed, belonging to linoleic acid metabolism, GL metabolism, and GP metabolism pathways. Correlation network analysis revealed that some characteristic DEMs (phosphatidylcholine, lyso-phosphatidylcholine, triglycerides, fatty acids, and phosphatidylethanolamine) were highly correlated with lipid oxidation. In addition, variations of volatile compounds, color values, texture characteristics, and thiobarbituric acid-reactive substance values were analyzed to corroborate the oxidation characteristics.

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