Cargando…

Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content

A study was conducted with the goal of developing an algorithm for use in sensors to monitor available soil N. For this purpose, three different soils were selected. The soils were studied for electrical conductivity (EC) at four different moisture levels and four levels of N. The selection of moist...

Descripción completa

Detalles Bibliográficos
Autores principales: Mirzakhaninafchi, Hasan, Mani, Indra, Hasan, Murtaza, Nafchi, Ali Mirzakhani, Parray, Roaf Ahmad, Kumar, Dinesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502749/
https://www.ncbi.nlm.nih.gov/pubmed/36146077
http://dx.doi.org/10.3390/s22186728
_version_ 1784795782308691968
author Mirzakhaninafchi, Hasan
Mani, Indra
Hasan, Murtaza
Nafchi, Ali Mirzakhani
Parray, Roaf Ahmad
Kumar, Dinesh
author_facet Mirzakhaninafchi, Hasan
Mani, Indra
Hasan, Murtaza
Nafchi, Ali Mirzakhani
Parray, Roaf Ahmad
Kumar, Dinesh
author_sort Mirzakhaninafchi, Hasan
collection PubMed
description A study was conducted with the goal of developing an algorithm for use in sensors to monitor available soil N. For this purpose, three different soils were selected. The soils were studied for electrical conductivity (EC) at four different moisture levels and four levels of N. The selection of moisture levels was based on optimum moisture levels between tillage moisture and field capacity. The results revealed a significant relationship between electrical conductivity and moisture level of the soil as well as between electrical conductivity and soil N content. Based on these relations, a polynomial model was developed between the EC of each selected soil sample and moisture content as well as N levels. The regression model for moisture content-based EC determination had coefficients of determination of 0.985, 0.988, and 0.981 for clay loam, sandy loam, and sandy loam soils, respectively. Similarly, the regression model for N content-based EC determination had coefficients of determination of 0.9832, 0.9, and 0.99 for clay loam, sandy loam, and sandy loam soils, respectively. An algorithm developed using a polynomial relationship between the EC of each selected soil sample at all moisture and N levels can be used to develop a sensor for site-specific N application.
format Online
Article
Text
id pubmed-9502749
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-95027492022-09-24 Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content Mirzakhaninafchi, Hasan Mani, Indra Hasan, Murtaza Nafchi, Ali Mirzakhani Parray, Roaf Ahmad Kumar, Dinesh Sensors (Basel) Article A study was conducted with the goal of developing an algorithm for use in sensors to monitor available soil N. For this purpose, three different soils were selected. The soils were studied for electrical conductivity (EC) at four different moisture levels and four levels of N. The selection of moisture levels was based on optimum moisture levels between tillage moisture and field capacity. The results revealed a significant relationship between electrical conductivity and moisture level of the soil as well as between electrical conductivity and soil N content. Based on these relations, a polynomial model was developed between the EC of each selected soil sample and moisture content as well as N levels. The regression model for moisture content-based EC determination had coefficients of determination of 0.985, 0.988, and 0.981 for clay loam, sandy loam, and sandy loam soils, respectively. Similarly, the regression model for N content-based EC determination had coefficients of determination of 0.9832, 0.9, and 0.99 for clay loam, sandy loam, and sandy loam soils, respectively. An algorithm developed using a polynomial relationship between the EC of each selected soil sample at all moisture and N levels can be used to develop a sensor for site-specific N application. MDPI 2022-09-06 /pmc/articles/PMC9502749/ /pubmed/36146077 http://dx.doi.org/10.3390/s22186728 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mirzakhaninafchi, Hasan
Mani, Indra
Hasan, Murtaza
Nafchi, Ali Mirzakhani
Parray, Roaf Ahmad
Kumar, Dinesh
Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content
title Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content
title_full Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content
title_fullStr Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content
title_full_unstemmed Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content
title_short Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content
title_sort development of prediction models for soil nitrogen management based on electrical conductivity and moisture content
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502749/
https://www.ncbi.nlm.nih.gov/pubmed/36146077
http://dx.doi.org/10.3390/s22186728
work_keys_str_mv AT mirzakhaninafchihasan developmentofpredictionmodelsforsoilnitrogenmanagementbasedonelectricalconductivityandmoisturecontent
AT maniindra developmentofpredictionmodelsforsoilnitrogenmanagementbasedonelectricalconductivityandmoisturecontent
AT hasanmurtaza developmentofpredictionmodelsforsoilnitrogenmanagementbasedonelectricalconductivityandmoisturecontent
AT nafchialimirzakhani developmentofpredictionmodelsforsoilnitrogenmanagementbasedonelectricalconductivityandmoisturecontent
AT parrayroafahmad developmentofpredictionmodelsforsoilnitrogenmanagementbasedonelectricalconductivityandmoisturecontent
AT kumardinesh developmentofpredictionmodelsforsoilnitrogenmanagementbasedonelectricalconductivityandmoisturecontent