Estimation of soil phosphorus availability via visible and near-infrared spectroscopy

Detalhes bibliográficos
Autor(a) principal: Souza, Micael Felipe de
Data de Publicação: 2020
Outros Autores: Franco, Henrique Coutinho Junqueira, Amaral, Lucas Rios do
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/183018
Resumo: Spectroscopic techniques have great potential to evaluate soil properties. However, there are still questions regarding the applicability of spectroscopy to analyze soil phosphorous (P) availability, especially in tropical soils with low nutrient contents. Therefore, this study evaluated the possibility to estimate P availability in soil and its pools (labile, moderately labile and non-labile) via Vis-NIR spectroscopy based on intra-field calibration. We used soils from two different locations, a plot experiment that received application of phosphate fertilizers (Field-A) and a cultivated field where a grid soil sampling was performed (Field-B). We used the technique of diffuse reflectance in the visible and near-infrared (Vis-NIR) to obtain the spectra of soil samples. Predictive modeling for P availability and labile, moderately labile and non-labile pools of P in soil were obtained via partial least squares (PLS) regression; classification modeling was performed via Soft Independent Modeling of Class Analogy (SIMCA) on three P availability levels in order to overcome the limitation on quantifying P via Vis-NIR spectroscopy. We found that isolating P contents as the only variable (Field-A), Vis-NIR spectroscopy does not allow estimating P pools in the soil. In addition, quantification of P available in the soil via predictive modeling has limitations in tropical soils. On the other hand, estimating P content in soil through classes of availability is a feasible and promising alternative.
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spelling Estimation of soil phosphorus availability via visible and near-infrared spectroscopypredictive modelingclassification modelprecision agriculturefractionation of phosphorussoil fertilitySpectroscopic techniques have great potential to evaluate soil properties. However, there are still questions regarding the applicability of spectroscopy to analyze soil phosphorous (P) availability, especially in tropical soils with low nutrient contents. Therefore, this study evaluated the possibility to estimate P availability in soil and its pools (labile, moderately labile and non-labile) via Vis-NIR spectroscopy based on intra-field calibration. We used soils from two different locations, a plot experiment that received application of phosphate fertilizers (Field-A) and a cultivated field where a grid soil sampling was performed (Field-B). We used the technique of diffuse reflectance in the visible and near-infrared (Vis-NIR) to obtain the spectra of soil samples. Predictive modeling for P availability and labile, moderately labile and non-labile pools of P in soil were obtained via partial least squares (PLS) regression; classification modeling was performed via Soft Independent Modeling of Class Analogy (SIMCA) on three P availability levels in order to overcome the limitation on quantifying P via Vis-NIR spectroscopy. We found that isolating P contents as the only variable (Field-A), Vis-NIR spectroscopy does not allow estimating P pools in the soil. In addition, quantification of P available in the soil via predictive modeling has limitations in tropical soils. On the other hand, estimating P content in soil through classes of availability is a feasible and promising alternative.Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2020-12-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/18301810.1590/1678-992X-2018-0295Scientia Agricola; v. 77 n. 5 (2020); e20180295Scientia Agricola; Vol. 77 Núm. 5 (2020); e20180295Scientia Agricola; Vol. 77 No. 5 (2020); e201802951678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/183018/169778Copyright (c) 2020 Scientia Agricolahttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessSouza, Micael Felipe de Franco, Henrique Coutinho Junqueira Amaral, Lucas Rios do 2021-03-09T20:14:40Zoai:revistas.usp.br:article/183018Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2021-03-09T20:14:40Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
title Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
spellingShingle Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
Souza, Micael Felipe de
predictive modeling
classification model
precision agriculture
fractionation of phosphorus
soil fertility
title_short Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
title_full Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
title_fullStr Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
title_full_unstemmed Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
title_sort Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
author Souza, Micael Felipe de
author_facet Souza, Micael Felipe de
Franco, Henrique Coutinho Junqueira
Amaral, Lucas Rios do
author_role author
author2 Franco, Henrique Coutinho Junqueira
Amaral, Lucas Rios do
author2_role author
author
dc.contributor.author.fl_str_mv Souza, Micael Felipe de
Franco, Henrique Coutinho Junqueira
Amaral, Lucas Rios do
dc.subject.por.fl_str_mv predictive modeling
classification model
precision agriculture
fractionation of phosphorus
soil fertility
topic predictive modeling
classification model
precision agriculture
fractionation of phosphorus
soil fertility
description Spectroscopic techniques have great potential to evaluate soil properties. However, there are still questions regarding the applicability of spectroscopy to analyze soil phosphorous (P) availability, especially in tropical soils with low nutrient contents. Therefore, this study evaluated the possibility to estimate P availability in soil and its pools (labile, moderately labile and non-labile) via Vis-NIR spectroscopy based on intra-field calibration. We used soils from two different locations, a plot experiment that received application of phosphate fertilizers (Field-A) and a cultivated field where a grid soil sampling was performed (Field-B). We used the technique of diffuse reflectance in the visible and near-infrared (Vis-NIR) to obtain the spectra of soil samples. Predictive modeling for P availability and labile, moderately labile and non-labile pools of P in soil were obtained via partial least squares (PLS) regression; classification modeling was performed via Soft Independent Modeling of Class Analogy (SIMCA) on three P availability levels in order to overcome the limitation on quantifying P via Vis-NIR spectroscopy. We found that isolating P contents as the only variable (Field-A), Vis-NIR spectroscopy does not allow estimating P pools in the soil. In addition, quantification of P available in the soil via predictive modeling has limitations in tropical soils. On the other hand, estimating P content in soil through classes of availability is a feasible and promising alternative.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-09
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/183018
10.1590/1678-992X-2018-0295
url https://www.revistas.usp.br/sa/article/view/183018
identifier_str_mv 10.1590/1678-992X-2018-0295
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/183018/169778
dc.rights.driver.fl_str_mv Copyright (c) 2020 Scientia Agricola
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Scientia Agricola
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 77 n. 5 (2020); e20180295
Scientia Agricola; Vol. 77 Núm. 5 (2020); e20180295
Scientia Agricola; Vol. 77 No. 5 (2020); e20180295
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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