Abstract Phospholipid fatty acid (PLFA) profiles were studied for their potential to discriminate between freshwater-cultured and seawater-cultured salmonids. The effects of culture season and fish size on the PLFAs compositions in salmonids were investigated to assess their effects on the discrimination results. Totally 19 PLFAs of salmonids were determined via gas chromatography (GC). Among them, 12 PLFAs were significantly different between freshwater-cultured and seawater-cultured salmonids. But only four PLFAs in salmonids cultured in different seasons and two PLFAs in fish with different size were significantly different. The PLFAs, including 18:1n9, 24:1n9, 20:5n3, 20:3n6, ∑MUFA, and ∑n6PUFA, were selected via stepwise discriminant analysis (SDA) for further multivariate statistics analysis. Principal component analysis (PCA) and canonical discriminant analysis (CDA) visualized the differences of the PLFAs profiles in fish cultured in freshwater and seawater. The linear discrimination analysis (LDA) and random forest (RF) were used to create a discrimination model that can authenticate salmonids farmed in freshwater and seawater. An overall correct classification rate of 95.89%, a cross-validation rate of 93.15%, and a predictive classification rate of 100% were achieved by the LDA. The RF achieved an overall correct classification rate of 95.89%, a cross-validation rate of 95.89%, and a predictive classification rate of 100%. These results indicate that PLFAs profiles can be used to effectively distinguish samples cultured in freshwater and seawater while less affected by season and fish size. Therefore, PLFAs analysis is a promising method for the accurate identification of salmonids cultured in freshwater and seawater.

中文翻译：

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评估用于区分淡水和海水养殖的鲑鱼的磷脂脂肪酸谱

摘要 研究了磷脂脂肪酸 (PLFA) 谱以区分淡水养殖鲑鱼和海水养殖鲑鱼的潜力。研究了养殖季节和鱼体大小对鲑鱼 PLFAs 组成的影响，以评估它们对区分结果的影响。通过气相色谱法 (GC) 共测定了鲑鱼的 19 种 PLFA。其中，淡水养殖和海水养殖的鲑鱼有 12 种 PLFAs 存在显着差异。但不同季节养殖的鲑鱼中只有四种PLFAs和不同大小的鱼中两种PLFAs有显着差异。通过逐步判别分析 (SDA) 选择 PLFA，包括 18:1n9、24:1n9、20:5n3、20:3n6、∑MUFA 和 ∑n6PUFA，用于进一步的多变量统计分析。主成分分析 (PCA) 和典型判别分析 (CDA) 可视化了淡水和海水养殖鱼类中 PLFA 谱的差异。线性判别分析 (LDA) 和随机森林 (RF) 用于创建判别模型，该模型可以验证淡水和海水养殖的鲑鱼。LDA 的总体正确分类率为 95.89%，交叉验证率为 93.15%，预测分类率为 100%。RF 实现了 95.89% 的整体正确分类率、95.89% 的交叉验证率和 100% 的预测分类率。这些结果表明，PLFAs 剖面可用于有效区分淡水和海水养殖的样品，同时受季节和鱼类大小的影响较小。所以，