Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
dARK ID: | ark:/26339/001300000xd28 |
Texto Completo: | http://repositorio.ufsm.br/handle/1/28294 |
Resumo: | The chemical analysis of soil components is a tool that allows good practices for correctives and fertilizers recommendation and managing soil fertility. Traditional methods of analysis usually consume a high number of reagents and require a lot of time for sample preparation and extractions. An alternative has been spectroscopy in the visible and near infrared (Vis-NIR) region. However, this tool needs validation and calibration of models for reliable estimates for different soil parameters. The objective of this work was to evaluate the reliability of Vis-NIR spectroscopy to estimate the potential acidity of tropical soils compared with values obtained by traditional methods used in routine soil analysis laboratories. We used 240 soil samples from agricultural areas and analyzed in the UFSM routine laboratory, 60 samples of each clay class (class 1: clay content ≤ 20; class 2: 21-40; class 3: 41-60; class 4: >60), which are subdivided by organic matter (OM) content into 20 samples of low content class (low ≤ 2.5), 20 samples of the medium class (medium 2.6 - 5.0), 20 samples of the high OM content class (high >5.0). For the validation of the models, 51 unknown samples were used, which were not part of the initial sample bank. The determination of the potential acidity of the samples was made by estimating with the SMP index and by the calcium acetate method. Five spectra pretreatments were used: smoothed (SMO), Savitzky-Golay Derivate (SGD), Multiplicative Scatter Correction (MSC), Continuum Removal (CRR) and Standard normalization variate (SNV). Prediction models for the potential acidity content were developed from raw and pre-processed spectral data. The models tested were Cubist, Multiple Linear Regression (MLR) and Partial Least Squares Regression (PLSR). The evaluation of the precision of the calibration curves was performed using the coefficient of determination (R² ) and the deviations from the root mean square error (RMSE). Curve validation was performed with the model that presented the best calibration performance. Soil spectra showed features related to soil constituents, mainly in SNV, MSC, SGD and CRR techniques. The pre-processing that obtained the best performance in both the calibration and validation stages was the CRR, regardless of the model used. There was a wide variation in the accuracy of the same multivariate method when different preprocesses were applied. The Cubist model presented the best performance, both for validation of samples analyzed by calcium acetate (R²=0.86; r=0.93) and for the SMP index (R²=0.91; r=0.95). Both the calcium acetate method and the SMP index method showed good fit with the model (R²=0.55 and R²=0.53, respectively). Vis-NIR spectroscopy has the potential to estimate the potential acidity, however, other studies and tests are needed to better elucidate the technique until the use of curves in soil analysis laboratories. |
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Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIREstimation of potential acidity in soils using Vis-NIR spectroscopyPré-processamentoModelos matemáticosCalibraçãoValidaçãoPre-processingMathematical modelsCalibrationValidationCNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLOThe chemical analysis of soil components is a tool that allows good practices for correctives and fertilizers recommendation and managing soil fertility. Traditional methods of analysis usually consume a high number of reagents and require a lot of time for sample preparation and extractions. An alternative has been spectroscopy in the visible and near infrared (Vis-NIR) region. However, this tool needs validation and calibration of models for reliable estimates for different soil parameters. The objective of this work was to evaluate the reliability of Vis-NIR spectroscopy to estimate the potential acidity of tropical soils compared with values obtained by traditional methods used in routine soil analysis laboratories. We used 240 soil samples from agricultural areas and analyzed in the UFSM routine laboratory, 60 samples of each clay class (class 1: clay content ≤ 20; class 2: 21-40; class 3: 41-60; class 4: >60), which are subdivided by organic matter (OM) content into 20 samples of low content class (low ≤ 2.5), 20 samples of the medium class (medium 2.6 - 5.0), 20 samples of the high OM content class (high >5.0). For the validation of the models, 51 unknown samples were used, which were not part of the initial sample bank. The determination of the potential acidity of the samples was made by estimating with the SMP index and by the calcium acetate method. Five spectra pretreatments were used: smoothed (SMO), Savitzky-Golay Derivate (SGD), Multiplicative Scatter Correction (MSC), Continuum Removal (CRR) and Standard normalization variate (SNV). Prediction models for the potential acidity content were developed from raw and pre-processed spectral data. The models tested were Cubist, Multiple Linear Regression (MLR) and Partial Least Squares Regression (PLSR). The evaluation of the precision of the calibration curves was performed using the coefficient of determination (R² ) and the deviations from the root mean square error (RMSE). Curve validation was performed with the model that presented the best calibration performance. Soil spectra showed features related to soil constituents, mainly in SNV, MSC, SGD and CRR techniques. The pre-processing that obtained the best performance in both the calibration and validation stages was the CRR, regardless of the model used. There was a wide variation in the accuracy of the same multivariate method when different preprocesses were applied. The Cubist model presented the best performance, both for validation of samples analyzed by calcium acetate (R²=0.86; r=0.93) and for the SMP index (R²=0.91; r=0.95). Both the calcium acetate method and the SMP index method showed good fit with the model (R²=0.55 and R²=0.53, respectively). Vis-NIR spectroscopy has the potential to estimate the potential acidity, however, other studies and tests are needed to better elucidate the technique until the use of curves in soil analysis laboratories.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESA análise química dos componentes do solo é uma ferramenta que permite boas práticas de recomendação de corretivos e fertilizantes e manejo da fertilidade do solo. Os métodos tradicionais de análise normalmente consomem uma elevada quantidade de reagentes e demandam de muito tempo para preparo das mostras e extrações. Uma alternativa têm sido a espectroscopia na região do visível e infravermelho próximo (Vis-NIR). Contudo, essa ferramenta necessita de validação e calibração de modelos para estimativas confiáveis para diferentes parâmetros do solo. O objetivo deste trabalho foi avaliar a confiabilidade da espectroscopia Vis-NIR para estimar a acidez potencial dos solos tropicais e subtropicais comparado com os valores obtidos pelos métodos tradicionais utilizados em laboratórios de rotina de análise de solo. Foram utilizadas 240 amostras de solos de áreas agrícolas e analisadas no laboratório de rotina da UFSM, 60 amostras de cada classe de argila (classe 1: teor de argila ≤ 20%; classe 2: 21-40%; classe 3: 41-60%; classe 4: >60%), sendo estas subdivididas conforme o teor de matéria orgânica (MO) em 20 amostras de classe baixo (≤ 2,5%), 20 amostras da classe médio (2,6-5,0%), e 20 amostras da classe alto (>5,0%). Para a validação dos modelos foram utilizadas 51 amostras desconhecidas, as quais não faziam parte do banco de amostras inicial. A determinação da acidez potencial das amostras se deu pela estimativa com o índice SMP e pelo método de acetato de cálcio. Foram utilizados cinco pré-tratamentos aos espectros: smoothed (SMO), Savitzky-Golay Derivate (SGD), Multiplicative Scatter Correction (MSC), Continuum Removal (CRR) e Standart normalization variate (SNV). Modelos de predição para o teor de acidez potencial foram desenvolvidos a partir dos dados espectrais brutos e pré-processados. Os modelos testados foram Cubist, Regressão linear múltipla (MLR) e regressão por mínimos quadrados parciais (PLSR). A avaliação da precisão das curvas de calibração foi realizada por meio do coeficiente de determinação (R² ) e os desvios da raiz quadrada média do erro (RMSE). A validação da curva foi realizada com o modelo que apresentou melhor desempenho na calibração. Os espectros do solo apresentaram feições relacionadas com os constituintes do solo, principalmente nas técnicas SNV, MSC, SGD e CRR. O pré-processamento que obteve o melhor desempenho tanto na etapa de calibração quanto de validação foi o CRR, independentemente do modelo utilizado. Houve uma ampla variação na acurácia do mesmo método multivariado, quando aplicados pré-processamentos diferentes. O modelo Cubist apresentou o melhor desempenho, tanto para validação de amostras analisadas pelo acetato de cálcio (R2=0,86; r=0,93) quanto para o índice SMP (R²=0,91; r=0,95). Ambos o método de acetato de cálcio e método do índice SMP apresentaram bom ajuste com o modelo (R²=0,55 e R²=0,53, respectivamente). A espectroscopia Vis-NIR possui potencial para estimar a acidez potencial, contudo, são necessários outros estudos e testes para melhor elucidação da técnica até a utilização de curvas em laboratórios de análises de solos.Universidade Federal de Santa MariaBrasilAgronomiaUFSMPrograma de Pós-Graduação em Ciência do SoloCentro de Ciências RuraisSilva, Leandro Souza dahttp://lattes.cnpq.br/2152888530643357Moura-Bueno, Jean MichelMallmann, Fábio Joel KochemTiecher, TalesKunz, Karine Mariele2023-03-20T18:38:21Z2023-03-20T18:38:21Z2022-09-30info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/28294ark:/26339/001300000xd28porAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2023-03-20T18:38:21Zoai:repositorio.ufsm.br:1/28294Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2023-03-20T18:38:21Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR Estimation of potential acidity in soils using Vis-NIR spectroscopy |
title |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR |
spellingShingle |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR Kunz, Karine Mariele Pré-processamento Modelos matemáticos Calibração Validação Pre-processing Mathematical models Calibration Validation CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
title_short |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR |
title_full |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR |
title_fullStr |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR |
title_full_unstemmed |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR |
title_sort |
Estimativa da acidez potencial em solos utilizando a espectroscopia Vis-NIR |
author |
Kunz, Karine Mariele |
author_facet |
Kunz, Karine Mariele |
author_role |
author |
dc.contributor.none.fl_str_mv |
Silva, Leandro Souza da http://lattes.cnpq.br/2152888530643357 Moura-Bueno, Jean Michel Mallmann, Fábio Joel Kochem Tiecher, Tales |
dc.contributor.author.fl_str_mv |
Kunz, Karine Mariele |
dc.subject.por.fl_str_mv |
Pré-processamento Modelos matemáticos Calibração Validação Pre-processing Mathematical models Calibration Validation CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
topic |
Pré-processamento Modelos matemáticos Calibração Validação Pre-processing Mathematical models Calibration Validation CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
description |
The chemical analysis of soil components is a tool that allows good practices for correctives and fertilizers recommendation and managing soil fertility. Traditional methods of analysis usually consume a high number of reagents and require a lot of time for sample preparation and extractions. An alternative has been spectroscopy in the visible and near infrared (Vis-NIR) region. However, this tool needs validation and calibration of models for reliable estimates for different soil parameters. The objective of this work was to evaluate the reliability of Vis-NIR spectroscopy to estimate the potential acidity of tropical soils compared with values obtained by traditional methods used in routine soil analysis laboratories. We used 240 soil samples from agricultural areas and analyzed in the UFSM routine laboratory, 60 samples of each clay class (class 1: clay content ≤ 20; class 2: 21-40; class 3: 41-60; class 4: >60), which are subdivided by organic matter (OM) content into 20 samples of low content class (low ≤ 2.5), 20 samples of the medium class (medium 2.6 - 5.0), 20 samples of the high OM content class (high >5.0). For the validation of the models, 51 unknown samples were used, which were not part of the initial sample bank. The determination of the potential acidity of the samples was made by estimating with the SMP index and by the calcium acetate method. Five spectra pretreatments were used: smoothed (SMO), Savitzky-Golay Derivate (SGD), Multiplicative Scatter Correction (MSC), Continuum Removal (CRR) and Standard normalization variate (SNV). Prediction models for the potential acidity content were developed from raw and pre-processed spectral data. The models tested were Cubist, Multiple Linear Regression (MLR) and Partial Least Squares Regression (PLSR). The evaluation of the precision of the calibration curves was performed using the coefficient of determination (R² ) and the deviations from the root mean square error (RMSE). Curve validation was performed with the model that presented the best calibration performance. Soil spectra showed features related to soil constituents, mainly in SNV, MSC, SGD and CRR techniques. The pre-processing that obtained the best performance in both the calibration and validation stages was the CRR, regardless of the model used. There was a wide variation in the accuracy of the same multivariate method when different preprocesses were applied. The Cubist model presented the best performance, both for validation of samples analyzed by calcium acetate (R²=0.86; r=0.93) and for the SMP index (R²=0.91; r=0.95). Both the calcium acetate method and the SMP index method showed good fit with the model (R²=0.55 and R²=0.53, respectively). Vis-NIR spectroscopy has the potential to estimate the potential acidity, however, other studies and tests are needed to better elucidate the technique until the use of curves in soil analysis laboratories. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-09-30 2023-03-20T18:38:21Z 2023-03-20T18:38:21Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/28294 |
dc.identifier.dark.fl_str_mv |
ark:/26339/001300000xd28 |
url |
http://repositorio.ufsm.br/handle/1/28294 |
identifier_str_mv |
ark:/26339/001300000xd28 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Agronomia UFSM Programa de Pós-Graduação em Ciência do Solo Centro de Ciências Rurais |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Agronomia UFSM Programa de Pós-Graduação em Ciência do Solo Centro de Ciências Rurais |
dc.source.none.fl_str_mv |
reponame:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Manancial - Repositório Digital da UFSM |
collection |
Manancial - Repositório Digital da UFSM |
repository.name.fl_str_mv |
Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
atendimento.sib@ufsm.br||tedebc@gmail.com |
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1815172412589735936 |