Relation between higher heating value and elemental and mineral biomass plant components

Detalhes bibliográficos
Autor(a) principal: Protásio, Thiago de Paula
Data de Publicação: 2011
Outros Autores: Bufalino, Lina, Tonoli, Gustavo Henrique Denzin, Couto, Allan Motta, Trugilho, Paulo Fernando, Guimarães Júnior, Mário
Tipo de documento: Artigo
Idioma: por
Título da fonte: Pesquisa Florestal Brasileira (Online)
Texto Completo: https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200
Resumo: The aims of this work were to evaluate the correlation, to adjust and select simple and multiple linear statistical models between elemental components (carbon, hydrogen and oxygen) and ash content with higher heating value for plant biomass; to use the principle components analysis for the creation of an energetic development index and to adjust a linear model between energetic development index and higher heating value. Eight types of biomass were used. Three linear and nine multiple statistical models were adjusted. The best models were selected based on the significance of coefficients, adjusted determination coefficient, estimative standard error, coefficient of variation, linearity of parameters, normality, presence of heterocedasticity and lack of error correlation. The variance inflation factor was determined for linear multiple models. High correlation between the variables studied was found. Models 1, 3 and 11 were considered most adequate. Practical use of model 2 is not possible. Principle components analysis was efficient in obtaining an energetic development index of lignocellulosic residues and it may be used for solving multicollinearity found between variables considered.doi: 10.4336/2011.pfb.31.66.113
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spelling Relation between higher heating value and elemental and mineral biomass plant componentsRelação entre o poder calorífico superior e os componentes elementares e minerais da biomassa vegetalModelagemRegressãoCorrelaçãoSeleçãoModelingRegressionCorrelationSelectionThe aims of this work were to evaluate the correlation, to adjust and select simple and multiple linear statistical models between elemental components (carbon, hydrogen and oxygen) and ash content with higher heating value for plant biomass; to use the principle components analysis for the creation of an energetic development index and to adjust a linear model between energetic development index and higher heating value. Eight types of biomass were used. Three linear and nine multiple statistical models were adjusted. The best models were selected based on the significance of coefficients, adjusted determination coefficient, estimative standard error, coefficient of variation, linearity of parameters, normality, presence of heterocedasticity and lack of error correlation. The variance inflation factor was determined for linear multiple models. High correlation between the variables studied was found. Models 1, 3 and 11 were considered most adequate. Practical use of model 2 is not possible. Principle components analysis was efficient in obtaining an energetic development index of lignocellulosic residues and it may be used for solving multicollinearity found between variables considered.doi: 10.4336/2011.pfb.31.66.113Os objetivos do trabalho foram avaliar a correlação, ajustar e selecionar modelos estatísticos lineares simples e múltiplos entre os componentes elementares (carbono, hidrogênio e oxigênio) e o teor de cinzas com o poder calorífico superior da biomassa vegetal; utilizar a análise de componentes principais para a criação de um índice de desempenho energético e ajustar um modelo linear entre o índice de desempenho energético e o poder calorífico superior. Utilizaram-se oito tipos de biomassa. Foram ajustadas equações referentes a três modelos estatísticos lineares simples e nove múltiplos. Os melhores modelos foram selecionados com base na significância dos seus coeficientes, no coeficiente de determinação ajustado, no erro padrão da estimativa, no coeficiente de variação, na linearidade dos parâmetros, na normalidade, na presença de heterocedasticidade e ausência de autocorrelação dos erros. Para os modelos lineares múltiplos, determinou-se o fator de inflação de variância. Encontrou-se alta correlação entre as variáveis. Os modelos 1, 3 e 11 foram considerados os mais adequados. A utilização prática do modelo 2 foi impossibilitada. A análise de componentes principais foi eficiente na obtenção de um índice de desempenho energético dos resíduos lignocelulósicos e pode ser utilizada para contornar a multicolinearidade encontrada entre as variáveis consideradas.doi: 10.4336/2011.pfb.31.66.113Embrapa Florestas2011-05-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/mswordhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200Pesquisa Florestal Brasileira; v. 31 n. 66 (2011): abr./jun.; 113Pesquisa Florestal Brasileira; Vol. 31 No. 66 (2011): abr./jun.; 1131983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200/211https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200/970Protásio, Thiago de PaulaBufalino, LinaTonoli, Gustavo Henrique DenzinCouto, Allan MottaTrugilho, Paulo FernandoGuimarães Júnior, Márioinfo:eu-repo/semantics/openAccess2017-04-28T13:06:42Zoai:pfb.cnpf.embrapa.br/pfb:article/200Revistahttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/PUBhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/oaipfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br1983-26051809-3647opendoar:2017-04-28T13:06:42Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Relation between higher heating value and elemental and mineral biomass plant components
Relação entre o poder calorífico superior e os componentes elementares e minerais da biomassa vegetal
title Relation between higher heating value and elemental and mineral biomass plant components
spellingShingle Relation between higher heating value and elemental and mineral biomass plant components
Protásio, Thiago de Paula
Modelagem
Regressão
Correlação
Seleção
Modeling
Regression
Correlation
Selection
title_short Relation between higher heating value and elemental and mineral biomass plant components
title_full Relation between higher heating value and elemental and mineral biomass plant components
title_fullStr Relation between higher heating value and elemental and mineral biomass plant components
title_full_unstemmed Relation between higher heating value and elemental and mineral biomass plant components
title_sort Relation between higher heating value and elemental and mineral biomass plant components
author Protásio, Thiago de Paula
author_facet Protásio, Thiago de Paula
Bufalino, Lina
Tonoli, Gustavo Henrique Denzin
Couto, Allan Motta
Trugilho, Paulo Fernando
Guimarães Júnior, Mário
author_role author
author2 Bufalino, Lina
Tonoli, Gustavo Henrique Denzin
Couto, Allan Motta
Trugilho, Paulo Fernando
Guimarães Júnior, Mário
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Protásio, Thiago de Paula
Bufalino, Lina
Tonoli, Gustavo Henrique Denzin
Couto, Allan Motta
Trugilho, Paulo Fernando
Guimarães Júnior, Mário
dc.subject.por.fl_str_mv Modelagem
Regressão
Correlação
Seleção
Modeling
Regression
Correlation
Selection
topic Modelagem
Regressão
Correlação
Seleção
Modeling
Regression
Correlation
Selection
description The aims of this work were to evaluate the correlation, to adjust and select simple and multiple linear statistical models between elemental components (carbon, hydrogen and oxygen) and ash content with higher heating value for plant biomass; to use the principle components analysis for the creation of an energetic development index and to adjust a linear model between energetic development index and higher heating value. Eight types of biomass were used. Three linear and nine multiple statistical models were adjusted. The best models were selected based on the significance of coefficients, adjusted determination coefficient, estimative standard error, coefficient of variation, linearity of parameters, normality, presence of heterocedasticity and lack of error correlation. The variance inflation factor was determined for linear multiple models. High correlation between the variables studied was found. Models 1, 3 and 11 were considered most adequate. Practical use of model 2 is not possible. Principle components analysis was efficient in obtaining an energetic development index of lignocellulosic residues and it may be used for solving multicollinearity found between variables considered.doi: 10.4336/2011.pfb.31.66.113
publishDate 2011
dc.date.none.fl_str_mv 2011-05-23
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://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200
url https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200/211
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/200/970
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/msword
dc.publisher.none.fl_str_mv Embrapa Florestas
publisher.none.fl_str_mv Embrapa Florestas
dc.source.none.fl_str_mv Pesquisa Florestal Brasileira; v. 31 n. 66 (2011): abr./jun.; 113
Pesquisa Florestal Brasileira; Vol. 31 No. 66 (2011): abr./jun.; 113
1983-2605
1809-3647
reponame:Pesquisa Florestal Brasileira (Online)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Pesquisa Florestal Brasileira (Online)
collection Pesquisa Florestal Brasileira (Online)
repository.name.fl_str_mv Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv pfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br
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