Britain International of Exact Sciences Journal (BIoEx Journal)
Vol 1 No 1 (2019): Britain International of Exact Sciences Journal, September

Application of Modern Methods: Modeling of Sedimentary Soil ESP Content

Sorush Niknamian (Board Member of Weston A Price Foundation, Washington DC, USA)



Article Info

Publish Date
20 Aug 2019

Abstract

Knowing the exchangeable sodium percentage (ESP) variations and its values in sodic or saline-sodic soils is essential in order to estimate the amount of soil amendments and better land management. ESP calculated from cation exchange capacity (CEC), and since CEC measurement is difficult and time-consuming, ESP computation is costly and subject to error. Thus, presenting a method to estimate ESP indirectly, by an easily available index is much more efficient and economical. In this study, 296 soil samples collected and analyzed from Sistan plain, southeastern Iran. Soil ESP were predicted by using artificial neural networks, comprising radial basis functions (RBFN) and multilayer perceptron (MLP) and adaptive neuro-fuzzy inference systems (ANFIS), and results compared with stepwise linear regression method. Results indicated that the linear regression models performed poorly in order to estimate ESP (R2 ≤ 0.58 and root mean square error (RMSE) ≥ 4.31). Applying fewer inputs (electrical conductivity (EC) and pH), ANFIS showed better results (R2=0.80, RMSE=2.34), while increasing inputs (clay and organic carbon) decreased the accuracy (R2=0.82, RMSE=4.20). Using more inputs, RBFN resulted in better performance in comparison with other methods (R2=0.83, RMSE=2.85). Sensitivity analysis using the connection weight method demonstrated that EC, pH, clay percentage and bulk density are the most important variables in order to explain ESP variability in the region, respectively. Generally, considering the evaluation criteria and the number of used variables of models, ANFIS (with EC and pH as inputs) is the most appropriate method for estimating ESP in Sistan plain.

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Journal Info

Abbrev

bioex

Publisher

Subject

Biochemistry, Genetics & Molecular Biology Chemistry Mathematics Medicine & Pharmacology Physics

Description

Britain International of Exact Sciences Journal is a peer-reviewed journal published in January, May and September by BIAR Publisher. BIoEx Journal welcomes research paper in mathematics, physics, chemistry, biology, engineering, medical sciences, argicultural sciences and other related fields which ...