1H-NMR metabolomic fingerprinting for differentiation of organic and conventional Italian brown and white rice

Conventional farming is the most common agricultural system in Italy, but the demand for organic alternatives is steadily increasing, given the environmental and health concerns of the consumers. Nuclear Magnetic Resonance (NMR) offers fast, non-destructive, and reproducible analysis for such purposes. In this work, the selected NMR metabolomics approach led to the development of supervised and unsupervised multivariate statistical models which classified Italian brown and white rice samples according to cultivation practice. Amino acids (aspartate, tryptophan, lysine, leucine), sugars (maltose, sucrose, glucose), and purines (adenosine, guanosine, oxypurinol) were the main metabolites proposed as markers for rice authentication. Quantification results showed that organic samples were higher in amino acids and nitrogen compounds and conventional brown rice being the only with high purine content.