Mirkhani, R., Shabanpour, M., Saadat, S. (2006). Using Particle Size Distribution and Organic Carbon Percentage to Predict the Cation Exchange Capacity of Soils of Lorestan Province. , 19(2), 231-237. doi: 10.22092/ijsr.2006.127454
R. Mirkhani; M. Shabanpour; S. Saadat. "Using Particle Size Distribution and Organic Carbon Percentage to Predict the Cation Exchange Capacity of Soils of Lorestan Province". , 19, 2, 2006, 231-237. doi: 10.22092/ijsr.2006.127454
Mirkhani, R., Shabanpour, M., Saadat, S. (2006). 'Using Particle Size Distribution and Organic Carbon Percentage to Predict the Cation Exchange Capacity of Soils of Lorestan Province', , 19(2), pp. 231-237. doi: 10.22092/ijsr.2006.127454
Mirkhani, R., Shabanpour, M., Saadat, S. Using Particle Size Distribution and Organic Carbon Percentage to Predict the Cation Exchange Capacity of Soils of Lorestan Province. , 2006; 19(2): 231-237. doi: 10.22092/ijsr.2006.127454
Using Particle Size Distribution and Organic Carbon Percentage to Predict the Cation Exchange Capacity of Soils of Lorestan Province
3Ph.D Student, Tarbiat Modarres University and Member Scientific Staff Soil and Water Research Institute.
Abstract
Cation exchange capacity (CEC) has a major effect on soil chemical, physical and biological properties. CEC measurement, however, is time consuming and costly. Many attempts have been made to predict CEC indirectly from some easily available soil physical and chemical properties with reasonable accuracy. The objective of this study was to predict soil CEC by pedotransfer functions. Fifty soil samples were collected from Lorestan Province, of which fourty samples were used for model development and ten samples were used for validation. CEC, particle size distribution, calcium carbonate and organic carbon percentage of soil samples were measured with ammonium acetate, hydrometry, acid neutralization and Walkly Black methods, respectively. The optimum combination of independent variables for estimation of CEC was selected by using stepwise regression method. The regression equation CEC=-0.01+0.233(CLAY)+ 0.00187(SILT)2+7.69(O.C)0.5 was obtained using multiple linear regression method. The results showed that there was a significant correlation (R2adj=0.873) between measured and predicted values. Statistical analysis for the evaluation of PTF indicated that GMER=1.1 and GSDER =1.099. The results indicated that the presented function was valid.
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