SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000600202 |
Resumo: | ABSTRACT Phosphorus concentration is one of the main attributes determined in laboratory analyses of soil samples collected in the field. The objective is to develop a soil phosphorus test using a low-cost spectrophotometer and a machine learning technique. For reflectance measurements, a low-cost system consisting of a Sparkfun AS7625x spectrophotometer and an Arduino Uno is used. Ion exchange resins under standard saturated solutions and modified conditions are used to extract phosphorus ions from the soil samples. Reflectance and phosphorus concentrations determined by the reference method are used in the training and testing of a machine learning. A modification procedure of the ion-exchange resin saturation solution allows the establishment of a strong correlation between the reflectance in 18 spectral bands and P concentration of the soil samples. The obtained model uses five reflectance of the modified resins at wavelengths of 410, 460, 560, 705, and 645 nm to predict the phosphorus concentration. This model presents an R2t accuracy of 0.97 in the training stage with an R2v of 0.96, RMSEv of 9.05, and ratio of prediction to deviation) of 3.81 in the test step. |
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Engenharia Agrícola |
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SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNINGprecision agricultureproximal spectroscopy sensorsembedded systemsion exchange resinsmachine learning by multiple linear regressionABSTRACT Phosphorus concentration is one of the main attributes determined in laboratory analyses of soil samples collected in the field. The objective is to develop a soil phosphorus test using a low-cost spectrophotometer and a machine learning technique. For reflectance measurements, a low-cost system consisting of a Sparkfun AS7625x spectrophotometer and an Arduino Uno is used. Ion exchange resins under standard saturated solutions and modified conditions are used to extract phosphorus ions from the soil samples. Reflectance and phosphorus concentrations determined by the reference method are used in the training and testing of a machine learning. A modification procedure of the ion-exchange resin saturation solution allows the establishment of a strong correlation between the reflectance in 18 spectral bands and P concentration of the soil samples. The obtained model uses five reflectance of the modified resins at wavelengths of 410, 460, 560, 705, and 645 nm to predict the phosphorus concentration. This model presents an R2t accuracy of 0.97 in the training stage with an R2v of 0.96, RMSEv of 9.05, and ratio of prediction to deviation) of 3.81 in the test step.Associação Brasileira de Engenharia Agrícola2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000600202Engenharia Agrícola v.42 n.6 2022reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v42n6e20210228/2022info:eu-repo/semantics/openAccessMayrink,Grégory O.Queiroz,Daniel M. deCoelho,Andre L. de F.Valente,Domingos S. M.eng2022-11-23T00:00:00Zoai:scielo:S0100-69162022000600202Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2022-11-23T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING |
title |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING |
spellingShingle |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING Mayrink,Grégory O. precision agriculture proximal spectroscopy sensors embedded systems ion exchange resins machine learning by multiple linear regression |
title_short |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING |
title_full |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING |
title_fullStr |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING |
title_full_unstemmed |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING |
title_sort |
SOIL PHOSPHORUS TEST USING A LOW-COST SPECTROPHOTOMETER AND MACHINE LEARNING |
author |
Mayrink,Grégory O. |
author_facet |
Mayrink,Grégory O. Queiroz,Daniel M. de Coelho,Andre L. de F. Valente,Domingos S. M. |
author_role |
author |
author2 |
Queiroz,Daniel M. de Coelho,Andre L. de F. Valente,Domingos S. M. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Mayrink,Grégory O. Queiroz,Daniel M. de Coelho,Andre L. de F. Valente,Domingos S. M. |
dc.subject.por.fl_str_mv |
precision agriculture proximal spectroscopy sensors embedded systems ion exchange resins machine learning by multiple linear regression |
topic |
precision agriculture proximal spectroscopy sensors embedded systems ion exchange resins machine learning by multiple linear regression |
description |
ABSTRACT Phosphorus concentration is one of the main attributes determined in laboratory analyses of soil samples collected in the field. The objective is to develop a soil phosphorus test using a low-cost spectrophotometer and a machine learning technique. For reflectance measurements, a low-cost system consisting of a Sparkfun AS7625x spectrophotometer and an Arduino Uno is used. Ion exchange resins under standard saturated solutions and modified conditions are used to extract phosphorus ions from the soil samples. Reflectance and phosphorus concentrations determined by the reference method are used in the training and testing of a machine learning. A modification procedure of the ion-exchange resin saturation solution allows the establishment of a strong correlation between the reflectance in 18 spectral bands and P concentration of the soil samples. The obtained model uses five reflectance of the modified resins at wavelengths of 410, 460, 560, 705, and 645 nm to predict the phosphorus concentration. This model presents an R2t accuracy of 0.97 in the training stage with an R2v of 0.96, RMSEv of 9.05, and ratio of prediction to deviation) of 3.81 in the test step. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000600202 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162022000600202 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-eng.agric.v42n6e20210228/2022 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
dc.source.none.fl_str_mv |
Engenharia Agrícola v.42 n.6 2022 reponame:Engenharia Agrícola instname:Associação Brasileira de Engenharia Agrícola (SBEA) instacron:SBEA |
instname_str |
Associação Brasileira de Engenharia Agrícola (SBEA) |
instacron_str |
SBEA |
institution |
SBEA |
reponame_str |
Engenharia Agrícola |
collection |
Engenharia Agrícola |
repository.name.fl_str_mv |
Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA) |
repository.mail.fl_str_mv |
revistasbea@sbea.org.br||sbea@sbea.org.br |
_version_ |
1752126275402596352 |