Estimation of soil sodium adsorption ratio without soluble sodium Na+ on sandy clay loam soil, Khartoum, Sudan

Paper Details

Research Paper 01/04/2016
Views (224) Download (5)

Estimation of soil sodium adsorption ratio without soluble sodium Na+ on sandy clay loam soil, Khartoum, Sudan

Mohammed M. A. Elbashier, Albashir A. S. Ali, Mohammed M. M. Osman, Ayman M. Elameen
Int. J. Agron. Agri. Res.8( 4), 120-124, April 2016.
Certificate: IJAAR 2016 [Generate Certificate]


Prediction of sodium adsorption ratio using available soil properties and simple empirical models have become particularly urgent to reduce the time and cost of some complex soil properties. The aim of this study is to estimate the sodium adsorption ratio (SAR) from soil electrical conductivity (EC), soluble calcium (Ca++) and magnesium (Mg++) to this end, a new equation was modified from soil SAR equation (MSAR). For this purpose, 30 soil samples were collected from the field of experiment, Jabal Awliya, south of Khartoum state, Sudan. Sodium adsorption ratio (SAR) was estimated as a function of soil EC, soluble Ca++ and Mg++ in order to compare the predicted results with measured SAR using laboratory tests. The results show that on saline soil samples, the standard error of mean (SEM) of predicted SAR obtained by MSAR was (0.8029) and the p-value was (0.6433). On non-saline soil samples, the standard error of mean (SEM) of predicted SAR acquired by MSAR was (0.4203) and the p-value was (0.2197). The statistical results indicated that MSAR has a high performance in predicting soil SAR and it can be recommended for both saline soil and non-saline soil samples.


Elbashier MM, Ebrahim MH, Musa AA, Ali AA, Mohammed MA. 2016. Efficiency of Two Models for Prediction of Exchangeable Sodium Percentage from Sodium Adsorption Ratio on Saline and Non Saline Soil. Universal Journal of Agricultural Research 4 (1), 32-36.

Graaff R, Patterson RA. 2001. Explaining the Mysteries of Salinity, Sodicity, SAR and ESP in On-site Practice in Proceedings of On-site ‘01 Conference: Advancing On-site Wastewater Systems, Lanfax Laboratories, Armidale 361- 368.

Kalkhajeh YK, Arshad RR, Amerikhah H, Sami M. 2012. Comparison of multiple linear regressions and artificial intelligence-based modeling techniques for prediction the soil cation exchange capacity of Aridisols and Entisols in a semiarid region. Australian Journal of Agricultural Engineering 3, 39-46.

Keshavarzi A, Sarmadian F. 2012. Mapping of Spatial Distribution of Soil Salinity and Alkalinity in a Semi-arid Region, Annals of Warsaw University of Life Sciences, Land Reclamation 44, 3-14.

Moasheri SA, Foroughifar H. 2013. Estimation of the values of soil absorption ratio using integrated geostatistical and artificial neural network methods. International Journal of Agriculture and Crop Sciences 5, 2423-2433.

Plant Science Department, South Dakota State University, Agricultural Experiment Station. 2006. Soil Testing and Plant Analysis 76-78.

Rashidi M, Seilsepour M. 2008. Sodium Adsorption Ratio Pedotransfer Function for Calcareous Soils of Varamin Region, International Journal of Agriculture & Biology 10, 715-718.

Richards LA. 1954. Diagnosis and Improvement of Saline and Alkali Soils, Determination of the properties of saline and alkali soils United States Department of Agriculture, Washington DC 26, 72.

Robbins CW. 1993. Coefficients for Estimating SAR from Soil pH and EC Data and Calculating pH from SAR and EC Values in Salinity Models. Arid Soil Research and Rehabilitation 7, 29-38.

Robert F, Ulery A. 2011. An Introduction to Soil Salinity and Sodium Issues in New Mexico, las cruces, circular 656, 1-6.

Sudduth KA,  Drummond ST, Kitchen NR. 2001. Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture. Computers and Electronics in Agriculture 31, 239-264.

Valente DS, Queiroz DM, Pinto FD, Santos NT, Santos FL. 2012. The relationship between apparent soil electrical conductivity and soil properties. Revista Ciencia Agronomica 43(4), 683-690.