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 | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
27/11/2017 |
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Data da última atualização: |
11/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SANTANA, F. B. de; SOUZA, A. M. de; POPPI, R. J. |
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Afiliação: |
FELIPE BACHION DE SANTANA, UNICAMP; ANDRE MARCELO DE SOUZA, CNPS; RONEI JESUS POPPI, UNICAMP. |
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Título: |
Visible and near infrared spectroscopy coupled to random forest to quantify some soil quality parameters. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, v. 191, p. 454-462, Feb. 2018. |
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DOI: |
https://doi.org/10.1016/j.saa.2017.10.052 |
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Idioma: |
Inglês |
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Conteúdo: |
This study evaluates the use of visible and near infrared spectroscopy (Vis-NIRS) combined with multivariate regression based on random forest to quantify some quality soil parameters. The parameters analyzed were soil cation exchange capacity (CEC), sum of exchange bases (SB), organic matter (OM), clay and sand present in the soils of several regions of Brazil. Current methods for evaluating these parameters are laborious, timely and require various wet analytical methods that are not adequate for use in precision agriculture, where faster and automatic responses are required. The random forest regression models were statistically better than PLS regression models for CEC, OM, clay and sand, demonstrating resistance to overfitting, attenuating the effect of outlier samples and indicating the most important variables for the model. The methodology demonstrates the potential of the Vis-NIR as an alternative for determination of CEC, SB, OM, sand and clay, making possible to develop a fast and automatic analytical procedure. |
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Palavras-Chave: |
Espectroscopia; Quimiometria. |
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Thesagro: |
Análise do Solo. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
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008 2018 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.saa.2017.10.052$2DOI
100 1 $aSANTANA, F. B. de
245 $aVisible and near infrared spectroscopy coupled to random forest to quantify some soil quality parameters.$h[electronic resource]
260 $c2018
520 $aThis study evaluates the use of visible and near infrared spectroscopy (Vis-NIRS) combined with multivariate regression based on random forest to quantify some quality soil parameters. The parameters analyzed were soil cation exchange capacity (CEC), sum of exchange bases (SB), organic matter (OM), clay and sand present in the soils of several regions of Brazil. Current methods for evaluating these parameters are laborious, timely and require various wet analytical methods that are not adequate for use in precision agriculture, where faster and automatic responses are required. The random forest regression models were statistically better than PLS regression models for CEC, OM, clay and sand, demonstrating resistance to overfitting, attenuating the effect of outlier samples and indicating the most important variables for the model. The methodology demonstrates the potential of the Vis-NIR as an alternative for determination of CEC, SB, OM, sand and clay, making possible to develop a fast and automatic analytical procedure.
650 $aAnálise do Solo
653 $aEspectroscopia
653 $aQuimiometria
700 1 $aSOUZA, A. M. de
700 1 $aPOPPI, R. J.
773 $tSpectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy$gv. 191, p. 454-462, Feb. 2018.
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