New bicompartmental model: an application for the production of gases using the in vitro technique

Detalhes bibliográficos
Autor(a) principal: Santos, Andre Luiz Pinto dos
Data de Publicação: 2023
Outros Autores: Ferreira, Tiago Alessandro Espínola, Brito, Cícero Carlos Ramos de, Gomes-Silva, Frank, Moreira, Guilherme Rocha, Leite, Leonardo Andrade, Reis, Ronaldo Braga, Pimentel, Patrícia Guimarães
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Semina. Ciências Agrárias (Online)
Texto Completo: https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/48220
Resumo: The purpose of this study was to propose a bicompartmental nonlinear model and to identify the bestperforming model between the proposed model and the bicompartmental logistic (BL) mode regarding the quality of fit to the curve of cumulative gas production (CGP) using corn silage, sunflower, and their mixtures. Gas production was measured 2, 3, 4, 6, 8, 9, 10, 12, 15, 19, 24, 30, 36, 48, 72, and 96 h after beginning the in vitro fermentation process. The generated data were used to generate the parameters of each model tested using the stats package of the R computational tool version 4.0.4. The mathematical models were subjected to the following selection criteria: the adjusted coefficient of determination (Raj. ), residual mean square (RMS), mean absolute deviation (MAD), and Akaike information criterion (AIC). It was demonstrated that the proposed model had better performance with a high Raj., and lower values of RMS, AIC, and MAD than the bicompartmental logistic model for the prediction of the parameters of cumulative gas production (CGP), per to present a superior fit in the set of criteria according to the methodology and conditions in which the present study was developed.
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spelling New bicompartmental model: an application for the production of gases using the in vitro technique.Novo modelo bicompartimental: uma aplicação para a produção de gases pela técnica in vitroCorn silageMathematical modelsProposed modelRuminal kineticsSunflower silage.Cinética ruminalModelos matemáticosModelo propostoSilagem de milhoSilagem de girassol.The purpose of this study was to propose a bicompartmental nonlinear model and to identify the bestperforming model between the proposed model and the bicompartmental logistic (BL) mode regarding the quality of fit to the curve of cumulative gas production (CGP) using corn silage, sunflower, and their mixtures. Gas production was measured 2, 3, 4, 6, 8, 9, 10, 12, 15, 19, 24, 30, 36, 48, 72, and 96 h after beginning the in vitro fermentation process. The generated data were used to generate the parameters of each model tested using the stats package of the R computational tool version 4.0.4. The mathematical models were subjected to the following selection criteria: the adjusted coefficient of determination (Raj. ), residual mean square (RMS), mean absolute deviation (MAD), and Akaike information criterion (AIC). It was demonstrated that the proposed model had better performance with a high Raj., and lower values of RMS, AIC, and MAD than the bicompartmental logistic model for the prediction of the parameters of cumulative gas production (CGP), per to present a superior fit in the set of criteria according to the methodology and conditions in which the present study was developed..No presente trabalho, com silagem de milho, girassol e suas misturas, objetivou-se propor um modelo não linear bicompartimental e identificar entre o modelo proposto e Logístico Bicompartimental (LB), aquele que apresenta maior qualidade de ajuste à curva de cinética de produção cumulativa de gases (PCG). A leitura da produção de gás foi realizada nos tempos 2, 3, 4, 6, 8, 9, 10, 12, 15, 19, 24, 30, 36, 48, 72 e 96 horas, após o início do processo de fermentação in vitro. Os dados gerados foram utilizados para geração dos parâmetros de cada modelo testado com auxílio do pacote stats da ferramenta computacional R versão 4.0.4. Os modelos matemáticos foram submetidos aos seguintes critérios de seleção o coeficiente de determinação ajustado (Raj. ), quadrado médio do resíduo (QMR), desvio médio absoluto (DMA) e o critério de informação de Akaike (AIC). Foi demonstrado que o modelo proposto teve melhor desempenho com altos Raj., e menores valores de QMR, AIC e DMA, por apresentar um ajustamento superior no conjunto dos critérios em comparação com o modelo logístico bicompartimental para a predição dos parâmetros de produção cumulativa de gases (PCG) de acordo com a metodologia e condições em que foi desenvolvido o presente estudo.  UEL2023-11-16info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/4822010.5433/1679-0359.2023v44n5p1733Semina: Ciências Agrárias; Vol. 44 No. 5 (2023); 1733-1744Semina: Ciências Agrárias; v. 44 n. 5 (2023); 1733-17441679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELenghttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/48220/49673Copyright (c) 2023 Semina: Ciências Agráriashttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessSantos, Andre Luiz Pinto dosFerreira, Tiago Alessandro EspínolaBrito, Cícero Carlos Ramos deGomes-Silva, FrankMoreira, Guilherme RochaLeite, Leonardo AndradeReis, Ronaldo BragaPimentel, Patrícia Guimarães2023-12-12T16:14:49Zoai:ojs.pkp.sfu.ca:article/48220Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2023-12-12T16:14:49Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false
dc.title.none.fl_str_mv New bicompartmental model: an application for the production of gases using the in vitro technique
.
Novo modelo bicompartimental: uma aplicação para a produção de gases pela técnica in vitro
title New bicompartmental model: an application for the production of gases using the in vitro technique
spellingShingle New bicompartmental model: an application for the production of gases using the in vitro technique
Santos, Andre Luiz Pinto dos
Corn silage
Mathematical models
Proposed model
Ruminal kinetics
Sunflower silage.
Cinética ruminal
Modelos matemáticos
Modelo proposto
Silagem de milho
Silagem de girassol.
title_short New bicompartmental model: an application for the production of gases using the in vitro technique
title_full New bicompartmental model: an application for the production of gases using the in vitro technique
title_fullStr New bicompartmental model: an application for the production of gases using the in vitro technique
title_full_unstemmed New bicompartmental model: an application for the production of gases using the in vitro technique
title_sort New bicompartmental model: an application for the production of gases using the in vitro technique
author Santos, Andre Luiz Pinto dos
author_facet Santos, Andre Luiz Pinto dos
Ferreira, Tiago Alessandro Espínola
Brito, Cícero Carlos Ramos de
Gomes-Silva, Frank
Moreira, Guilherme Rocha
Leite, Leonardo Andrade
Reis, Ronaldo Braga
Pimentel, Patrícia Guimarães
author_role author
author2 Ferreira, Tiago Alessandro Espínola
Brito, Cícero Carlos Ramos de
Gomes-Silva, Frank
Moreira, Guilherme Rocha
Leite, Leonardo Andrade
Reis, Ronaldo Braga
Pimentel, Patrícia Guimarães
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Santos, Andre Luiz Pinto dos
Ferreira, Tiago Alessandro Espínola
Brito, Cícero Carlos Ramos de
Gomes-Silva, Frank
Moreira, Guilherme Rocha
Leite, Leonardo Andrade
Reis, Ronaldo Braga
Pimentel, Patrícia Guimarães
dc.subject.por.fl_str_mv Corn silage
Mathematical models
Proposed model
Ruminal kinetics
Sunflower silage.
Cinética ruminal
Modelos matemáticos
Modelo proposto
Silagem de milho
Silagem de girassol.
topic Corn silage
Mathematical models
Proposed model
Ruminal kinetics
Sunflower silage.
Cinética ruminal
Modelos matemáticos
Modelo proposto
Silagem de milho
Silagem de girassol.
description The purpose of this study was to propose a bicompartmental nonlinear model and to identify the bestperforming model between the proposed model and the bicompartmental logistic (BL) mode regarding the quality of fit to the curve of cumulative gas production (CGP) using corn silage, sunflower, and their mixtures. Gas production was measured 2, 3, 4, 6, 8, 9, 10, 12, 15, 19, 24, 30, 36, 48, 72, and 96 h after beginning the in vitro fermentation process. The generated data were used to generate the parameters of each model tested using the stats package of the R computational tool version 4.0.4. The mathematical models were subjected to the following selection criteria: the adjusted coefficient of determination (Raj. ), residual mean square (RMS), mean absolute deviation (MAD), and Akaike information criterion (AIC). It was demonstrated that the proposed model had better performance with a high Raj., and lower values of RMS, AIC, and MAD than the bicompartmental logistic model for the prediction of the parameters of cumulative gas production (CGP), per to present a superior fit in the set of criteria according to the methodology and conditions in which the present study was developed.
publishDate 2023
dc.date.none.fl_str_mv 2023-11-16
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://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/48220
10.5433/1679-0359.2023v44n5p1733
url https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/48220
identifier_str_mv 10.5433/1679-0359.2023v44n5p1733
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/48220/49673
dc.rights.driver.fl_str_mv Copyright (c) 2023 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv UEL
publisher.none.fl_str_mv UEL
dc.source.none.fl_str_mv Semina: Ciências Agrárias; Vol. 44 No. 5 (2023); 1733-1744
Semina: Ciências Agrárias; v. 44 n. 5 (2023); 1733-1744
1679-0359
1676-546X
reponame:Semina. Ciências Agrárias (Online)
instname:Universidade Estadual de Londrina (UEL)
instacron:UEL
instname_str Universidade Estadual de Londrina (UEL)
instacron_str UEL
institution UEL
reponame_str Semina. Ciências Agrárias (Online)
collection Semina. Ciências Agrárias (Online)
repository.name.fl_str_mv Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)
repository.mail.fl_str_mv semina.agrarias@uel.br
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