Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R
Ano de defesa: | 2017 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , , , |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | eng |
Instituição de defesa: |
Universidade Federal de Santa Maria
Centro de Ciências Rurais |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciência do Solo
|
Departamento: |
Agronomia
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/11343 |
Resumo: | This thesis presents a study of Visible Near-infrared spectroscopy technique applied to predict soil properties. The purpose was to develop quantitative soil information due to the demand of digital soil mapping, environmental monitoring, agricultural production and for increasing spatial information on soil. Soil spectroscopy emerge as an alternative to revolutionize soil monitoring, allowing rapid, low-cost, non-destructive samples sampling, environmental-friendly, reproducible, and repeatable analysis. To improve the efficiency of soil prediction using spectral data, several spectral preprocessing techniques and multivariate models were exploited. A graphical user interface (GUI) in R, named Alrad Spectra, was developed to perform preprocessing, multivariate modeling and prediction using spectral data. Hereby, the objectives were: The objectives were: i) to predict soil properties to improve soil information using spectral data, ii) to compare the performance of spectral preprocessing and multivariate calibration methods in the prediction of soil organic carbon, iii) to obtain reliable soil organic carbon prediction, and iv) to develop a graphical user interface that performs spectral preprocessing and prediction of the soil property using spectroscopic data. A total of 595 soil samples were collected in central region of Santa Catarina State, Brazil. Soil spectral reflectance was obtained using a FieldSpec 3 spectroradiometer with a spectral range of 350–2500 nm with 1 nm of spectral resolution. The outcomes of the thesis have demonstrated the great performance of predicting soil properties using Vis-NIR spectroscopy. Apparently, soil properties that are directly related to the chromophores such as organic carbon presented superior prediction statistics than particle size. Spectral preprocessing applied in the soil spectra contribute to the development of high-level prediction model. Comparing different spectral preprocessing techniques for soil organic carbon (SOC) prediction revealed that the scatter–corrective preprocessing techniques presented superior prediction results compared to spectral derivatives. In scatter–correction technique, continuum removal is the most suitable preprocessing to be used for SOC prediction. In the calibration modeling, excepting for random forest, all of methods presented robust prediction, with emphasis on the support vector machine method. The systematic methodology applied in this study can improve the reliability of SOC estimation by examining how techniques of spectral preprocessing and multivariate methods affect the prediction performance using spectral analysis. The development of easy-to-use graphical user interface may benefit a large number of users, who will take advantage of this useful chemometrics analysis. Alrad Spectra is the first GUI of its kind and the expectation is that this tool can expand the application of the spectroscopy technique. |
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2017-08-10T13:53:38Z2017-08-10T13:53:38Z2017-02-06http://repositorio.ufsm.br/handle/1/11343This thesis presents a study of Visible Near-infrared spectroscopy technique applied to predict soil properties. The purpose was to develop quantitative soil information due to the demand of digital soil mapping, environmental monitoring, agricultural production and for increasing spatial information on soil. Soil spectroscopy emerge as an alternative to revolutionize soil monitoring, allowing rapid, low-cost, non-destructive samples sampling, environmental-friendly, reproducible, and repeatable analysis. To improve the efficiency of soil prediction using spectral data, several spectral preprocessing techniques and multivariate models were exploited. A graphical user interface (GUI) in R, named Alrad Spectra, was developed to perform preprocessing, multivariate modeling and prediction using spectral data. Hereby, the objectives were: The objectives were: i) to predict soil properties to improve soil information using spectral data, ii) to compare the performance of spectral preprocessing and multivariate calibration methods in the prediction of soil organic carbon, iii) to obtain reliable soil organic carbon prediction, and iv) to develop a graphical user interface that performs spectral preprocessing and prediction of the soil property using spectroscopic data. A total of 595 soil samples were collected in central region of Santa Catarina State, Brazil. Soil spectral reflectance was obtained using a FieldSpec 3 spectroradiometer with a spectral range of 350–2500 nm with 1 nm of spectral resolution. The outcomes of the thesis have demonstrated the great performance of predicting soil properties using Vis-NIR spectroscopy. Apparently, soil properties that are directly related to the chromophores such as organic carbon presented superior prediction statistics than particle size. Spectral preprocessing applied in the soil spectra contribute to the development of high-level prediction model. Comparing different spectral preprocessing techniques for soil organic carbon (SOC) prediction revealed that the scatter–corrective preprocessing techniques presented superior prediction results compared to spectral derivatives. In scatter–correction technique, continuum removal is the most suitable preprocessing to be used for SOC prediction. In the calibration modeling, excepting for random forest, all of methods presented robust prediction, with emphasis on the support vector machine method. The systematic methodology applied in this study can improve the reliability of SOC estimation by examining how techniques of spectral preprocessing and multivariate methods affect the prediction performance using spectral analysis. The development of easy-to-use graphical user interface may benefit a large number of users, who will take advantage of this useful chemometrics analysis. Alrad Spectra is the first GUI of its kind and the expectation is that this tool can expand the application of the spectroscopy technique.Esta tese apresenta um estudo da técnica de espectroscopia do visível ao infravermelho próximo aplicado à predição de propriedades do solo. O proposito foi de desenvolver informações quantitativas sobre o solo, devido à demanda do mapeamento digital de solos, monitoramento ambiental, produção agrícola e aumento das informações espaciais do solo. A espectroscopia surge como uma alternativa para revolucionar a monitorização do solo, permitindo uma amostragem rápida, de baixo custo, não destrutiva, ambientalmente amigável, reprodutível e repetitiva. Para melhorar a eficiência da predição do solo usando dados espectrais, várias técnicas de pré-processamento espectral e modelos multivariados foram explorados. Uma interface gráfica de usuário (GUI) no R, denominada Alrad Spectra, foi desenvolvida para realizar pré-processamento, modelagem multivariada e predição usando dados espectrais. Os objetivos foram: i) predizer as propriedades do solo para melhorar a informação do solo usando dados espectrais, ii) comparar os desempenhos dos pré-processamentos espectrais e métodos de calibração multivariada na predição do carbono orgânico do solo, iii) obter predições confiáveis do carbono orgânico do solo, e iv) desenvolver uma interface gráfica de usuário que realize o pré-processamento espectral e a predição do atributo solo usando dados espectroscópicos. Um total de 595 amostras de solo foram coletadas na região central do estado de Santa Catarina, Brasil. A reflectância espectral do solo foi obtida utilizando um espectrorradiômetro FieldSpec 3 com uma alcance espectral de 350-2500 nm com 1 nm de resolução espectral. Os resultados da tese demonstraram o grande desempenho da predição de propriedades do solo usando espectroscopia do vísivel ao infravermelho próximo. As propriedades do solo que estão diretamente relacionadas aos cromóforos, como o carbono orgânico, apresentaram predições superiores comparados com o tamanho de partículas. O pré-processamento espectral aplicado nos espectros do solo contribui para o desenvolvimento de um modelo de predição de alto nível. Comparando diferentes técnicas de pré-processamento espectral para a predição de carbono orgânico revelou que as técnicas de pré-processamento de correção de dispersão apresentaram resultados de predição superiores em comparação com as técnicas de derivação espectrais. Na técnica de correção de dispersão, a remoção do contínuo é o pré-processamento mais adequado a ser usado para a predição de carbono. Na modelagem de calibração, com exceção da floresta aleatória, todos os métodos apresentaram uma elevada predição, sendo destaque o método máquina de vetores de suporte. A metodologia sistemática aplicada neste estudo pode melhorar a confiabilidade da estimativa do carbono orgânico ao examinar como as técnicas de pré-processamento espectral e métodos multivariados afetam a performance da predição usando a análise espectral. O desenvolvimento da GUI de fácil utilização pode beneficiar um grande número de usuários, os quais podem tirar proveito desta análise quimiométrica. Alrad Spectra é a primeira GUI desse tipo e a expectativa é que esta ferramenta possa expandir a aplicação da técnica de espectroscopia.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESengUniversidade Federal de Santa MariaCentro de Ciências RuraisPrograma de Pós-Graduação em Ciência do SoloUFSMBrasilAgronomiaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAlrad SpectraTécnica de espectroscopiaEspectros de soloAnálise quimiométricaGUI de fácil utilizaçãoSpectroscopy techniqueSoil spectraChemometrics analysisUser-friendly GUICNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLOEspectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em RSoil Vis-NIR spectroscopy: predictive potential and the development of a graphical user interface in Rinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisDalmolin, Ricardo Simão Dinizhttp://lattes.cnpq.br/3735884911693854Caten, Alexandre tenhttp://lattes.cnpq.br/4065267714747712Franco, ândrea Machado Pereirahttp://lattes.cnpq.br/8354735635774999Araújo, Suzana Romeirohttp://lattes.cnpq.br/7289473902924417Vasques, Gustavo de Mattoshttp://lattes.cnpq.br/1838153897546051http://lattes.cnpq.br/1495863324270099Dotto, André Carnieletto5001001000056006000845916a-ab9b-4bc9-a3d6-f1d2b58563e3fd87d1a1-707a-43e4-9f82-128caa9bebd4ee2bf0ba-5dd6-4f31-a961-fc7a1618096a07f86a83-d953-4d2b-8673-29603052ac5cedae6440-1b67-4a37-953a-5dd806aa01e280fa8080-a924-4b63-9fac-fca7ca37a8f0reponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8804http://repositorio.ufsm.br/bitstream/1/11343/2/license_rdfc1efe8e24d7281448e873be30ea326ffMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/11343/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD53ORIGINALDotto, Andre Carnieletto.pdfDotto, Andre Carnieletto.pdfTese de Doutoradoapplication/pdf2992405http://repositorio.ufsm.br/bitstream/1/11343/1/Dotto%2c%20Andre%20Carnieletto.pdf8e22e058d1e576540ca2ad6a3adc7c84MD51TEXTDotto, Andre Carnieletto.pdf.txtDotto, Andre Carnieletto.pdf.txtExtracted texttext/plain236987http://repositorio.ufsm.br/bitstream/1/11343/4/Dotto%2c%20Andre%20Carnieletto.pdf.txt11ffd0c705b91618829b6d0e211ca2c8MD54THUMBNAILDotto, Andre Carnieletto.pdf.jpgDotto, Andre Carnieletto.pdf.jpgIM Thumbnailimage/jpeg4403http://repositorio.ufsm.br/bitstream/1/11343/5/Dotto%2c%20Andre%20Carnieletto.pdf.jpgb9164e527151daf080610b8b1ca65b47MD551/113432017-08-21 21:40:12.757oai:repositorio.ufsm.br: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 Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2017-08-22T00:40:12Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R |
dc.title.alternative.eng.fl_str_mv |
Soil Vis-NIR spectroscopy: predictive potential and the development of a graphical user interface in R |
title |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R |
spellingShingle |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R Dotto, André Carnieletto Alrad Spectra Técnica de espectroscopia Espectros de solo Análise quimiométrica GUI de fácil utilização Spectroscopy technique Soil spectra Chemometrics analysis User-friendly GUI CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
title_short |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R |
title_full |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R |
title_fullStr |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R |
title_full_unstemmed |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R |
title_sort |
Espectroscopia do solo no Vis-IR: potencial predictivo e desenvolvimento de uma interface gráfica de usuário em R |
author |
Dotto, André Carnieletto |
author_facet |
Dotto, André Carnieletto |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Dalmolin, Ricardo Simão Diniz |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/3735884911693854 |
dc.contributor.referee1.fl_str_mv |
Caten, Alexandre ten |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/4065267714747712 |
dc.contributor.referee2.fl_str_mv |
Franco, ândrea Machado Pereira |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/8354735635774999 |
dc.contributor.referee3.fl_str_mv |
Araújo, Suzana Romeiro |
dc.contributor.referee3Lattes.fl_str_mv |
http://lattes.cnpq.br/7289473902924417 |
dc.contributor.referee4.fl_str_mv |
Vasques, Gustavo de Mattos |
dc.contributor.referee4Lattes.fl_str_mv |
http://lattes.cnpq.br/1838153897546051 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/1495863324270099 |
dc.contributor.author.fl_str_mv |
Dotto, André Carnieletto |
contributor_str_mv |
Dalmolin, Ricardo Simão Diniz Caten, Alexandre ten Franco, ândrea Machado Pereira Araújo, Suzana Romeiro Vasques, Gustavo de Mattos |
dc.subject.por.fl_str_mv |
Alrad Spectra Técnica de espectroscopia Espectros de solo Análise quimiométrica GUI de fácil utilização |
topic |
Alrad Spectra Técnica de espectroscopia Espectros de solo Análise quimiométrica GUI de fácil utilização Spectroscopy technique Soil spectra Chemometrics analysis User-friendly GUI CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
dc.subject.eng.fl_str_mv |
Spectroscopy technique Soil spectra Chemometrics analysis User-friendly GUI |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::CIENCIA DO SOLO |
description |
This thesis presents a study of Visible Near-infrared spectroscopy technique applied to predict soil properties. The purpose was to develop quantitative soil information due to the demand of digital soil mapping, environmental monitoring, agricultural production and for increasing spatial information on soil. Soil spectroscopy emerge as an alternative to revolutionize soil monitoring, allowing rapid, low-cost, non-destructive samples sampling, environmental-friendly, reproducible, and repeatable analysis. To improve the efficiency of soil prediction using spectral data, several spectral preprocessing techniques and multivariate models were exploited. A graphical user interface (GUI) in R, named Alrad Spectra, was developed to perform preprocessing, multivariate modeling and prediction using spectral data. Hereby, the objectives were: The objectives were: i) to predict soil properties to improve soil information using spectral data, ii) to compare the performance of spectral preprocessing and multivariate calibration methods in the prediction of soil organic carbon, iii) to obtain reliable soil organic carbon prediction, and iv) to develop a graphical user interface that performs spectral preprocessing and prediction of the soil property using spectroscopic data. A total of 595 soil samples were collected in central region of Santa Catarina State, Brazil. Soil spectral reflectance was obtained using a FieldSpec 3 spectroradiometer with a spectral range of 350–2500 nm with 1 nm of spectral resolution. The outcomes of the thesis have demonstrated the great performance of predicting soil properties using Vis-NIR spectroscopy. Apparently, soil properties that are directly related to the chromophores such as organic carbon presented superior prediction statistics than particle size. Spectral preprocessing applied in the soil spectra contribute to the development of high-level prediction model. Comparing different spectral preprocessing techniques for soil organic carbon (SOC) prediction revealed that the scatter–corrective preprocessing techniques presented superior prediction results compared to spectral derivatives. In scatter–correction technique, continuum removal is the most suitable preprocessing to be used for SOC prediction. In the calibration modeling, excepting for random forest, all of methods presented robust prediction, with emphasis on the support vector machine method. The systematic methodology applied in this study can improve the reliability of SOC estimation by examining how techniques of spectral preprocessing and multivariate methods affect the prediction performance using spectral analysis. The development of easy-to-use graphical user interface may benefit a large number of users, who will take advantage of this useful chemometrics analysis. Alrad Spectra is the first GUI of its kind and the expectation is that this tool can expand the application of the spectroscopy technique. |
publishDate |
2017 |
dc.date.accessioned.fl_str_mv |
2017-08-10T13:53:38Z |
dc.date.available.fl_str_mv |
2017-08-10T13:53:38Z |
dc.date.issued.fl_str_mv |
2017-02-06 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/11343 |
url |
http://repositorio.ufsm.br/handle/1/11343 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.cnpq.fl_str_mv |
500100100005 |
dc.relation.confidence.fl_str_mv |
600 600 |
dc.relation.authority.fl_str_mv |
0845916a-ab9b-4bc9-a3d6-f1d2b58563e3 fd87d1a1-707a-43e4-9f82-128caa9bebd4 ee2bf0ba-5dd6-4f31-a961-fc7a1618096a 07f86a83-d953-4d2b-8673-29603052ac5c edae6440-1b67-4a37-953a-5dd806aa01e2 80fa8080-a924-4b63-9fac-fca7ca37a8f0 |
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.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Ciência do Solo |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Agronomia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Ciências Rurais |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações do 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 |
Biblioteca Digital de Teses e Dissertações do UFSM |
collection |
Biblioteca Digital de Teses e Dissertações do UFSM |
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Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM) |
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atendimento.sib@ufsm.br||tedebc@gmail.com |
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