Linear Regression Models to Estimate Exchangeable Sodium Percentage and Bulk Density of Salt Affected Soils in Sahl El-Hossinia, El-Sharkia Governorate, Egypt

Abstract

ABSTRACTThe objective of this study was to develop a Linear Regression Model for the prediction of soil bulk density based on organic matter content (OM) and textural fractions (% sand, silt and clay) as well as the soil exchangeable sodium percentage (ESP) based on soil sodium adsorption ratio (SAR) in some salt affected soils of Sahl El-Hossinia, El-Sharkia Governorate, Egypt. For this purpose, 160 samples were randomly taken from top of the surface soil (0–30 cm) from different locations and samples were subjected to various analyzes. XLSTAT Version 2016.02.27444 software was used to build and test conceptual and empirical models. The statistical results of the study indicated that to predict soil bulk density (BD) based on organic matter content and textural fractions the Multiple linear regression model BD = 1.817–0.730 × OM – 0.002 × Clay – 0.001 × Silt with R2 = 0.794. On the other hand, to predict soil ESP based on SAR the linear regression model ESP = 5.577 + 0.851 × SAR with R2 = 0.773. A Linear Regression Model for prediction of BD and ESP of Sahl El-Hossinia, El-Sharkia Governorate, Egypt, can be used with high prediction.