Discrimination of geographical origin of rice (Oryza sativa L.) by multielement analysis using inductively coupled plasma atomic emission spectroscopy and multivariate analysis

Abstract

This study aims to determine the authenticity of the geographical origin of rice using inductively coupled plasma atomic emission spectroscopy (ICP-AES) and chemometrics. The profiles of 25 elements in brown rice measured by ICP-AES were subjected to data-mining processes, including principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). PLS-DA clearly discriminated the geographical origin of rice samples grown in three countries. Eleven elements (Cu, Ag, Zn, Cr, Ca, Ba, Cd, Bi, K, Pb, and In) significantly contributed to the ability to discriminate the geographical origin of the rice. These results demonstrate the use of multielement profiling combined with chemometrics as a tool for discriminating food origins. This study extends our knowledge about the applications of both multielement profiling and chemometrics for the determination of food authenticity, and thus can be useful for controlling the geographical origin of rice by governmental administration and protecting consumers from improper domestic labeling.