Elemental imaging and classifying rice grains by using laser ablation inductively coupled plasma mass spectrometry and linear discriminant analysis

Abstract

This study aims to investigate elemental imaging in a longitudinal section of single rice grain using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and to classify rice according to their origins and types of 16 samples using LA-ICP-MS with linear discriminant analysis (LDA). The distributions of 8 essential elements (Ca, Cu, Fe, K, Mg, Mn, P and Zn) in a single rice grain were visualized as elemental images. Investigation of the elemental imaging of rice grain showed that essential elements were presented in large amounts in embryo and elevated level in endosperm. The elemental distributions of rice grain were not uniform. In addition, the concentration of 20 elements distributed in core endosperm was evaluated and used as chemical indicator to discriminate the origin and type of rice samples. The LDA can successfully differentiate rice samples according to their regions of origin (Northeast or South regions of Thailand) and types. Satisfied classifications are obtained with overall correct classification and cross-validation of 93.8% and 91.1% for origin classification and 100% and 97.9% for type classification.