Determination of chemical elements in rice from Singapore markets: Distribution, estimated intake and differentiation of rice varieties

•Rice purchased from Singapore markets were poor in Co, Cu, Mn, Se and Zn.•Concentrations of i-As close to the maximum levels established for foodstuffs were observed.•As, Mn and Zn were preferably in the outer part of rice grain, while Co and Cu in the center.•Concentrations of Cd, Pb and Se were well-distributed along the grains.•The elemental profile can be used to discriminate different rice samples. Concentrations of As, Cd, Co, Cu, Mn, Pb, Se and Zn were determined in polished and husked rice samples purchased from Singapore markets to estimate nutritional risk by their estimated weekly intakes (EWIs). The elemental distribution in rice grain was studied using scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS), and a principal component analysis was performed to investigate the relationships between the variables (total element concentration) in a multidimensional space. Except for Cd and Se, the median concentration of analytes for husked grains was higher than in polished grains. Rice samples with As concentration higher than 198 μg kg−1 were submitted to speciation analysis, and inorganic-As found in grains ranged from 41 to 87 % of the total As. Calculated EWIs for essential elements were lower than the Recommended Dietary Allowance, while the EWIs for non-essential elements were below the Provisional Tolerable Weekly Intake. Nevertheless, our results demonstrate that the presence of toxic elements in rice, especially As, must be carefully monitored. It was found a significantly low concentration levels of essential elements in most of the samples analyzed, highlighting the relevance of biofortification strategies to mitigate hidden hunger. Furthermore, the mineral profile obtained from the samples allowed discrimination of rice samples according to farming practice, grain processing and country of origin using principal component analysis and discriminant function analysis.