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
作者： Song, Gongshuai 1 ; Zeng, Mingwei 1 ; Chen, Shengjun 2 ; Lyu, Zhangfan 4 ; Jiang, Nengliang 1 ; Wang, Danli 1 ; Yuan, Tinglan 1 ; Li, Ling 1 ; Mei, Guangming 5 ; Shen, Qing 3 ; Gong, Jinyan 1 ;
作者机构： 1.Zhejiang Univ Sci & Technol, Sch Biol & Chem Engn, Zhejiang Prov Key Lab Biol & Chem Proc Technol Far, Hangzhou 310023, Peoples R China
2.Chinese Acad Fishery Sci, South China Sea Fisheries Res Inst, Key Lab Aquat Prod Proc, Minist Agr & Rural Affairs, Guangzhou 510300, Peoples R China
3.Zhejiang Gongshang Univ, Inst Seafood, Collaborat Innovat Ctr Seafood Deep Proc, Zhejiang Prov Joint Key Lab Aquat Prod Proc, Hangzhou 310012, Zhejiang, Peoples R China
4.McGill Univ, Sch Human Nutr, Montreal, PQ H9X 3V9, Canada
5.Zhejiang Marine Fisheries Res Inst, Zhoushan 316021, Peoples R China
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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