The Details of Multi-elemental Analysis and 2D Image Mapping within Roots, Leaves, and Seeds from Oryza glaberrima: Application of the Micro-PIXE Technique

Abstract

The Oryza glaberrima Steud (OG) plant was domesticated 3,500 years ago in the inland delta of the upper Niger River in present-day Mali. From there, it spread across all of West Africa and adapted to very different environments from the desert region of Mali to the humid forests of Sierra Leone. Understanding metal accumulation at the organ level in roots, leaves and seeds in O. gla-berrima (OG) is crucial for improving physiological and metabolic aspects in growing Asian and African rice in salted areas. The micro-analytical imaging techniques are required to reveal its accumulation and distribution within plant tissues. The aim of the study is to investigate the metal accumulation at the organ level in roots, leaves, and seeds in African rice by performing 2D elemental image mapping and by determining their elemental composition. PIXE studies were performed to determine different elements in rice plants. The existing microbeam analytical technique at the iThemba LABS applied for the 2D image mapping of fresh rice tissues to perform a concentration of low atomic mass elements (such as Al, Si, P, S, Cl, Ca, Ti, Mn, Fe, Cu, Br, Zn and K) with detection limits of typically 1-10µg/g. Comparison of the distribution of the elements between leaves, root and seed samples using uptake and distribution of elements in particular environmental conditions with potential amount of salt in water was done. The results showed that there were significant correlations among most of the mineral element contents. Ca, Al, Si, Cl, K, S, and P contents were significantly correlated with most of the other mineral element contents, while Br, Cu, Zn, Ti, Mn, and Fe content showed significantly negative associations with the S, Cl and Ca contents of rice side leaves. The study also indicated metal exclusion as a salt tolerance strategy from leaves, root, and seed compartments using matrix correlation between samples and between elements on rice species. The study concluded that