Mathematical models to describe the growth curves of white-egg layers

Detalhes bibliográficos
Autor(a) principal: Oliveira, Cleber Franklin Santos de
Data de Publicação: 2018
Outros Autores: Tavares, João Marcos Novais, Corrêa, Gerusa da Silva Salles, Vieira, Bruno Serpa, Barbosa, Silvana Alves Pedrozo Vitalino, Corrêa, André Brito, Lima, Cristina Amorim Ribeiro de
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/30565
Resumo: The aim of this study was to compare mathematical models describing growth curves of white-egg layers at different population densities. To fit the models, 4,000 growing white-egg layers were utilized. The experimental design was completely randomized, with population densities of 71, 68, 65, 62, and 59 birds per cage in the starter phase and 19, 17, 15, 13, and 11 birds per cage in the grower phase, with 10 replicates each. Birds were weighed weekly to determine the average body weight and the weight gain. Gompertz and Logistic models were utilized to estimate their growth. The data analysis was carried out using the PROC NLMIXED procedure of the SAS® statistical computer software to estimate the parameters of the equation because mixed models were employed. The mean squared error, the coefficient of determination, and Akaike’s information criterion were used to evaluate the quality of fit of the models. The studied models converged for the description of the growth of the birds at the different densities studied, showing that they were appropriate for estimating the growth of white-egg layers housed at different population densities. The Gompertz model showed a better fit than the Logistic model.
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spelling Mathematical models to describe the growth curves of white-egg layersModelos matemáticos para descrever curvas de crescimento de poedeiras levesGompertzPerformancePoultry.AviculturaDesempenhoGompertz.The aim of this study was to compare mathematical models describing growth curves of white-egg layers at different population densities. To fit the models, 4,000 growing white-egg layers were utilized. The experimental design was completely randomized, with population densities of 71, 68, 65, 62, and 59 birds per cage in the starter phase and 19, 17, 15, 13, and 11 birds per cage in the grower phase, with 10 replicates each. Birds were weighed weekly to determine the average body weight and the weight gain. Gompertz and Logistic models were utilized to estimate their growth. The data analysis was carried out using the PROC NLMIXED procedure of the SAS® statistical computer software to estimate the parameters of the equation because mixed models were employed. The mean squared error, the coefficient of determination, and Akaike’s information criterion were used to evaluate the quality of fit of the models. The studied models converged for the description of the growth of the birds at the different densities studied, showing that they were appropriate for estimating the growth of white-egg layers housed at different population densities. The Gompertz model showed a better fit than the Logistic model.Esta pesquisa teve por objetivo comparar modelos matemáticos para descrever curva de crescimento de poedeiras leves em diferentes densidades populacional, por meio de equações de modelos de crescimento. Para o ajuste dos modelos foram utilizadas 4000 poedeiras leves em crescimento. O delineamento utilizado foi o inteiramente casualizado nas densidades populacional de 71, 68, 65, 62 e 59 aves por gaiola na fase de cria e de 19, 17, 15, 13 e 11 aves por gaiola na fase de recria, com dez repetições cada. Semanalmente, as aves foram pesadas para determinação do peso corporal médio e o ganho de peso. Para estimar o crescimento das aves foram utilizados os modelos de Gompertz e Logistic. A análise dos dados foi realizada pelo procedimento PROC NLMIXED do programa computacional estatístico SAS®, para estimar os parâmetros da equação por se tratar de modelos mistos. O quadrático médio do erro, o coeficiente de determinação e o critério de informação de Akaike foram utilizados na avaliação da qualidade do ajuste dos modelos. Os modelos estudados atingiram a convergência para a descrição do crescimento das aves nas diferentes densidades estudadas, adequados para estimar o crescimento corporal das aves com alto grau de confiabilidade. Os modelos estimaram o crescimento de poedeiras leves, alojadas em diferentes densidades populacional, em que o modelo de Gompertz apresentou melhores ajustes em comparação ao Logistic.UEL2018-05-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPesquisa Empírica de Campoapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/3056510.5433/1679-0359.2018v39n3p1327Semina: Ciências Agrárias; Vol. 39 No. 3 (2018); 1327-1334Semina: Ciências Agrárias; v. 39 n. 3 (2018); 1327-13341679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELenghttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/30565/23526Copyright (c) 2018 Semina: Ciências Agráriashttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessOliveira, Cleber Franklin Santos deTavares, João Marcos NovaisCorrêa, Gerusa da Silva SallesVieira, Bruno SerpaBarbosa, Silvana Alves Pedrozo VitalinoCorrêa, André BritoLima, Cristina Amorim Ribeiro de2022-10-20T21:02:53Zoai:ojs.pkp.sfu.ca:article/30565Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2022-10-20T21:02:53Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false
dc.title.none.fl_str_mv Mathematical models to describe the growth curves of white-egg layers
Modelos matemáticos para descrever curvas de crescimento de poedeiras leves
title Mathematical models to describe the growth curves of white-egg layers
spellingShingle Mathematical models to describe the growth curves of white-egg layers
Oliveira, Cleber Franklin Santos de
Gompertz
Performance
Poultry.
Avicultura
Desempenho
Gompertz.
title_short Mathematical models to describe the growth curves of white-egg layers
title_full Mathematical models to describe the growth curves of white-egg layers
title_fullStr Mathematical models to describe the growth curves of white-egg layers
title_full_unstemmed Mathematical models to describe the growth curves of white-egg layers
title_sort Mathematical models to describe the growth curves of white-egg layers
author Oliveira, Cleber Franklin Santos de
author_facet Oliveira, Cleber Franklin Santos de
Tavares, João Marcos Novais
Corrêa, Gerusa da Silva Salles
Vieira, Bruno Serpa
Barbosa, Silvana Alves Pedrozo Vitalino
Corrêa, André Brito
Lima, Cristina Amorim Ribeiro de
author_role author
author2 Tavares, João Marcos Novais
Corrêa, Gerusa da Silva Salles
Vieira, Bruno Serpa
Barbosa, Silvana Alves Pedrozo Vitalino
Corrêa, André Brito
Lima, Cristina Amorim Ribeiro de
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Oliveira, Cleber Franklin Santos de
Tavares, João Marcos Novais
Corrêa, Gerusa da Silva Salles
Vieira, Bruno Serpa
Barbosa, Silvana Alves Pedrozo Vitalino
Corrêa, André Brito
Lima, Cristina Amorim Ribeiro de
dc.subject.por.fl_str_mv Gompertz
Performance
Poultry.
Avicultura
Desempenho
Gompertz.
topic Gompertz
Performance
Poultry.
Avicultura
Desempenho
Gompertz.
description The aim of this study was to compare mathematical models describing growth curves of white-egg layers at different population densities. To fit the models, 4,000 growing white-egg layers were utilized. The experimental design was completely randomized, with population densities of 71, 68, 65, 62, and 59 birds per cage in the starter phase and 19, 17, 15, 13, and 11 birds per cage in the grower phase, with 10 replicates each. Birds were weighed weekly to determine the average body weight and the weight gain. Gompertz and Logistic models were utilized to estimate their growth. The data analysis was carried out using the PROC NLMIXED procedure of the SAS® statistical computer software to estimate the parameters of the equation because mixed models were employed. The mean squared error, the coefficient of determination, and Akaike’s information criterion were used to evaluate the quality of fit of the models. The studied models converged for the description of the growth of the birds at the different densities studied, showing that they were appropriate for estimating the growth of white-egg layers housed at different population densities. The Gompertz model showed a better fit than the Logistic model.
publishDate 2018
dc.date.none.fl_str_mv 2018-05-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Pesquisa Empírica de Campo
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/30565
10.5433/1679-0359.2018v39n3p1327
url https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/30565
identifier_str_mv 10.5433/1679-0359.2018v39n3p1327
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/30565/23526
dc.rights.driver.fl_str_mv Copyright (c) 2018 Semina: Ciências Agrárias
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2018 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. 39 No. 3 (2018); 1327-1334
Semina: Ciências Agrárias; v. 39 n. 3 (2018); 1327-1334
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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