Modeling the electrical conductivity relationship between saturated paste extract and 1:2.5 dilution in different soil textural classes

Modeling the electrical conductivity relationship between saturated paste extract and 1:2.5 dilution in different soil textural classes

Regression models were developed to estimate the electrical conductivity of saturated paste extract (ECe) from the electrical conductivity of soil-water ratio (EC1:2.5) for different soil textural classes. ECe is a crucial parameter used to indicate the presence, type, and distribution of salinity i...

Full description

Saved in:
Bibliographic Details
Main Authors: Moh’d M. Omar, Mawazo J. Shitindi, Boniface H. J. Massawe, Ole Pedersen, Joel L. Meliyo, Kadeghe G. Fue
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Soil Science
Subjects:
soil health
soil salinity
ECe prediction models
salinity management
regression model
agricultural productivity
Online Access:https://www.frontiersin.org/articles/10.3389/fsoil.2024.1421661/full
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Regression models were developed to estimate the electrical conductivity of saturated paste extract (ECe) from the electrical conductivity of soil-water ratio (EC1:2.5) for different soil textural classes. ECe is a crucial parameter used to indicate the presence, type, and distribution of salinity in soils. However, determining ECe is demanding, time-consuming, requires considerable skill to accurately identify the correct soil saturation point, and is not routinely performed by soil testing laboratories. Many laboratories, instead, commonly measure the electrical conductivity of soil-water extracts at various dilutions, such as EC1:1, EC1:2.5, or EC1:5. In this study, 706 soil samples were collected from depths of 0 - 30 cm across three rice irrigation schemes to determine EC1:2.5, with 50% analyzed for ECe. ECe values were grouped based on soil textural classes. The results showed a strong linear relationship between EC1:2.5 and ECe values, with a high coefficient of determination (R² > 0.95). The Root Mean Square Error values were low (1.4 < RMSE), and the Mean Absolute Error values were similarly low (0.85 < MAE). Therefore, the regression models developed provide a practical means of estimating ECe for various soil textural classes, thereby enhancing soil salinity assessment and management strategies.
ISSN:2673-8619

Similar Items