Modeling of available soil phosphorus (ASP) using multi-objective group method of data handling

Keshavarzi, A; Omran, EE; Bateni, SM; Pradhan, B; Vasu, D; Bagherzadeh, A

Modeling of available soil phosphorus (ASP) using multi-objective group method of data handling

Keshavarzi, A Omran, EE Bateni, SM Pradhan, B

Vasu, D Bagherzadeh, A

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: Modeling Earth Systems and Environment, 2016, 2, (3), pp. 157
Issue Date:: 2016

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Field	Value	Language
dc.contributor.author	Keshavarzi, A
dc.contributor.author	Omran, EE
dc.contributor.author	Bateni, SM
dc.contributor.author	Pradhan, B https://orcid.org/0000-0001-9863-2054
dc.contributor.author	Vasu, D
dc.contributor.author	Bagherzadeh, A
dc.date.accessioned	2022-07-14T23:05:30Z
dc.date.available	2022-07-14T23:05:30Z
dc.date.issued	2016
dc.identifier.citation	Modeling Earth Systems and Environment, 2016, 2, (3), pp. 157
dc.identifier.issn	2363-6203
dc.identifier.issn	2363-6211
dc.identifier.uri	http://hdl.handle.net/10453/158930
dc.description.abstract	The accurate estimation of available soil phosphorus (ASP) is required for the effective management of environmental resources and improving agricultural productivity. Direct measurement of ASP at large scales is time-consuming and expensive. Therefore, many empirical models or pedotransfer functions (PTFs) have been developed to obtain ASP. This study introduces a new model that estimates ASP from easily measurable soil properties by using the multi-objective group method of data handling (mGMDH) approach. Organic carbon, clay content, calcium carbonate equivalent, pH and ASP were obtained from 100 soil samples, which were collected by the stratified random sampling strategy in Mashhad Plain, Khorasan-e-Razavi Province, Northeast Iran. The suggested model for the prediction of ASP generated satisfactory results in terms of the statistical performance criteria. The coefficient of determination (R2) and mean square error (MSE) values of the mGMDH model in training step were 0.606 and 4.9671 mg kg−1, respectively, whereas those were 0.504 and 5.6685 mg kg−1, in the testing step. It was concluded that only 50 % of variations of ASP could be described by selecting easy-to-measure soil variables and owing to the key role of phosphorus in soil fertility and precision agriculture, the other related factors such as terrain attributes and fertilizer management should also be considered as they influence the distribution of the soil phosphorus.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Modeling Earth Systems and Environment
dc.relation.isbasedon	10.1007/s40808-016-0216-5
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Modeling of available soil phosphorus (ASP) using multi-objective group method of data handling
dc.type	Journal Article
utslib.citation.volume	2
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-14T23:05:29Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	2
utslib.citation.issue	3

Abstract:

The accurate estimation of available soil phosphorus (ASP) is required for the effective management of environmental resources and improving agricultural productivity. Direct measurement of ASP at large scales is time-consuming and expensive. Therefore, many empirical models or pedotransfer functions (PTFs) have been developed to obtain ASP. This study introduces a new model that estimates ASP from easily measurable soil properties by using the multi-objective group method of data handling (mGMDH) approach. Organic carbon, clay content, calcium carbonate equivalent, pH and ASP were obtained from 100 soil samples, which were collected by the stratified random sampling strategy in Mashhad Plain, Khorasan-e-Razavi Province, Northeast Iran. The suggested model for the prediction of ASP generated satisfactory results in terms of the statistical performance criteria. The coefficient of determination (R2) and mean square error (MSE) values of the mGMDH model in training step were 0.606 and 4.9671 mg kg−1, respectively, whereas those were 0.504 and 5.6685 mg kg−1, in the testing step. It was concluded that only 50 % of variations of ASP could be described by selecting easy-to-measure soil variables and owing to the key role of phosphorus in soil fertility and precision agriculture, the other related factors such as terrain attributes and fertilizer management should also be considered as they influence the distribution of the soil phosphorus.

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http://hdl.handle.net/10453/158930