Fast nutritional characterization of different pigmented rice grains using a combination of NMR and decision tree analysis

Abstract

Different rice cultivars contain various metabolites which are closely related with their nutritional and functional effects. In the current study, NMR and chemometrics methods – decision tree analysis (DTA) were applied to explore the chemical characteristics in different rice cultivars. The pigmented rice were completely discriminated from each other, and the key metabolites that mostly contributed to the rice discrimination were explored, including sugars compounds (sucrose, fructose and glucose) and non-sugar compounds (γ-amino butyric acid (GABA), asparagine, citric acid and malic acid) with DTA approach and 1HNMR metabolite fingerprints. The purple rice has the highest concentrations of sucrose, citric acid and asparagine (p < 0.05), but lowest fructose (p < 0.05); red rice has the lowest GABA concentration comparing with the other three groups (p < 0.05). This study implies that DTA method is a powerful tool to discriminate different pigmented rice varieties. Furthermore, it also reveals the crucial nutrients based on 1H-NMR metabolic profiling.

Keywords

• pigmented rice
• 1h-nmr
• decision tree
• metabolomics
• principal components analysis