Abstract

The geographical traceability of food products is seen as a distinctive feature of the future of food which is increasingly becoming a concern for consumers. In this research, differences in the lipid composition of Coix seed samples from four major Chinese origins were investigated using non-targeted lipidomics. By multivariate statistical analysis, unsupervised PCA and OPLS-DA based differentiation between the four origins of Coix seed samples could be achieved. The OPLS-DA VIP > 1 screened 72 lipids out of 1211 lipids as potential markers to distinguish Coix seeds from different origins. In addition, the potential markers (SPH(d16:0), Cer(d18:2/20:0 + O) and PC(8:0e/8:0) were combined with statistical analysis algorithms to construct a discriminant function for rapid differentiation of Coix seed samples from different origins and a specific function for different origins with 100% discrimination accuracy. In general, a rapid and accurate method combining multivariate chemometrics and algorithms was developed based on untargeted lipidomics to determine the geographical origin of Coix seed samples, which can also be applied to other agricultural products.

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