空气油炸海鲜中的脂质氧化对人体健康构成风险。然而,在不同的空气油炸(AF)温度下,促氧化剂环境对海鲜中脂质氧化的影响仍然未知。集成机器学习(ML)指导的REIMS和脂质组学方法被应用于探索血脂谱,脂质氧化,和不同AF温度(140、160、180和200°C)下鲑鱼的脂质代谢途径。主要的ML方法(神经网络,支持向量机,合奏学习,和天真的贝叶斯)。总的来说,鉴定出773种差异表达代谢物(DEM),包括甘油磷脂(GP),甘油酯(GL),和鞘脂。共分析了34个p值<0.05且预测值的变量重要性>1.0的DEM,属于亚油酸代谢,GL代谢,和GP代谢途径。相关网络分析显示,一些特征性DEM(磷脂酰胆碱,溶血磷脂酰胆碱,甘油三酯,脂肪酸,和磷脂酰乙醇胺)与脂质氧化高度相关。此外,挥发性化合物的变化,颜色值,纹理特征,并对硫代巴比妥酸活性物质值进行了分析,以证实其氧化特性。
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 °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 naïve 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.