The effect of the seasons on geographical traceability of salmonid based on multi-element analysis

Salmonid samples collected from two sites in different aquaculture areas (Yantai and Liujiaxia, China) in four seasons were subjected to multi-element analysis. The amounts of 18 elements in fish were measured by inductively coupled plasma atomic emission spectrometry (ICP-AES). The results showed that concentrations of elements in fish from Yantai were stable with seasonal alternation. However, the element concentrations and compositions of fish obtained from Liujiaxia were vulnerable to seasonal change. Principal component analysis (PCA) and canonical discriminant analysis (CDA) were used to visualize the regional and seasonal distribution of samples, and it was determined that CDA was more distinct than PCA. To determine if seasonal effects would influence the discrimination of the geographical origin of salmonid, multivariate statistics including linear discriminant analysis (LDA), k-nearest neighbor (KNN), and partial least squares discriminant analysis (PLS-DA) were used to discriminate fish samples from the two different areas. The results showed that all discrimination techniques could effectively distinguish samples while remaining unaffected by seasonal effects.