Estimation of soil phosphorus availability via visible and near-infrared spectroscopy
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
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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Scientia Agrícola (Online) |
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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 |
_version_ |
1800222794459381760 |