![Sample our Environment & Agriculture journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5934/TOC-Subject-Sample-2021-Environment-Agriculture.jpg"})
Abstract
Vertisols in the Sudan occur under different climatic zones, ranging from arid in the north to tropical monsoon in the south, with rainfall varying from 150 mm to 1000 mm per annum. In this study, the exchangeable sodium percentage (ESP) was estimated from the sodium adsorption ratio (SAR); values of SAR and ESP for all identified soil series of Vertisols in the Sudan were extracted from the available data. These data were used to examine the variability in SAR and ESP in these soils using coefficient of variation (CV) as an index and then to regress ESP on SAR for the three master horizons (A, AC, C) and pooled data for all horizon. Curvilinear, linear, quadratic, and cubic equations were used to examine the relation between ESP and SAR. The significance of the F ratio and correlation coefficient was tested for individual equation. The soil series were then sorted out into saline and nonsaline, sodic and nonsodic, and the ESP was regressed on SAR once again. The equations used for the regression were curvilinear and first‐, second‐, and third‐degree polynomial equations. Then analysis of variance (ANOVA) was used to screen any significant difference between the estimated values of ESP (using these equations and USDA salinity laboratory equation) on one hand and the actual (measured) values of ESP. The results revealed that ESP and SAR are highly variable irrespective of depth despite slight decrease with depth. Furthermore, ESP is more variable than SAR in horizons A and AC but less variable in horizon C. The regression equations indicated that ESP might be reasonably estimated from SAR. However, different equations were appropriate for different horizons. Moreover, the result indicated that in most of the cases the relation between ESP and SAR better fits quadratic equations. But for simplicity, linear equations for all horizons could be used to estimate ESP from SAR.