Assessment of elemental profiling combined with chemometrics for authenticating the geographical origins of Pacific white shrimp (Litopenaeus vannamei)

Abstract Pacific white shrimp (Litopenaeus vannamei) is an important aquaculture species worldwide, and there is a growing concern over misdescribed shrimp products, particularly over their geographical origins. Shrimp samples were collected from 12 locations in northern and southern China to develop traceability methods in identifying their geographic origins. In one of the sampling sites, shrimp were collected from five farms using the same water source but feeding with different brands of feed to investigate the effect of feed on the elemental compositions of shrimp. Totally 35 elements (Ce, Nd, Pr, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Th, Y, U, Li, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Rb, Sr, Ag, Cd, Cs, Ba, and Pb) were detected in both shrimp and feed. Only Cd and Tb in shrimp were positively correlated with those in the feed. Moreover, 24 elements (Li, Al, V, Fe, As, Rb, Sr, Cd, Pb, Ce, Nd, Pr, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Th, and Y) in shrimp were significantly different between northern and southern China. Elements As, Fe, Pb, Rb, Cs, and U, selected by stepwise discriminant analysis (SDA), were used to create a new dataset (SSDAs dataset) to compare with the entire dataset (ATEs dataset) in discrimination analyses. Classification tools, including linear discriminant analysis (LDA), k-nearest neighbor (KNN), and random forest (RF) were used to create a discrimination model to authenticate shrimp provenance based on the ATEs and SSDAs datasets. The highest discrimination rate was achieved with RF using the SSDAs dataset, which achieved an overall correct discrimination rate of 100%, a cross-validation rate of 98.78%, and a predictive discrimination rate of 100%. Therefore, elemental profiling combined with chemometrics is a promising method which can be used to identify shrimp provenance.