Proposal for a new non-linear model to describe growth curves
Autor(a) principal: | |
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Data de Publicação: | 2024 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Bioscience journal (Online) |
Texto Completo: | https://seer.ufu.br/index.php/biosciencejournal/article/view/68936 |
Resumo: | This study was developed with longitudinal data measurements of Norfolk rabbits from birth to 119 days of age to estimate the average growth curve, with the primary objective of proposing a non-linear model. It also selected the most appropriate sigmoidal model to describe the growth of Norfolk rabbits. The adjustments provided by the logistic, von Bertalanffy, Gompertz, Brody, Richards, and proposed models were compared. The parameters were estimated using the “nls” function of the “stats” package in R software, the least-squares method, and the Gauss-Newton convergence algorithm. The goodness-of-fit comparison was based on the following criteria: adjusted coefficient of determination (), mean square error (MSE), mean absolute deviation (MAD), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Cluster analysis helped select and classify the non-linear growth models, considering the other goodness-of-fit criteria results. The proposed non-linear, von Bertalanffy, Gompertz, and Richards models described the growth curve of Norfolk rabbits satisfactorily, providing parameters with practical interpretations. The goodness-of-fit criteria showed that the proposed and von Bertalanffy models best represented the growth of rabbits. |
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Proposal for a new non-linear model to describe growth curvesAnimal growthBiological parametersCluster analysisGrowth curvesLongitudinal data. Agricultural SciencesThis study was developed with longitudinal data measurements of Norfolk rabbits from birth to 119 days of age to estimate the average growth curve, with the primary objective of proposing a non-linear model. It also selected the most appropriate sigmoidal model to describe the growth of Norfolk rabbits. The adjustments provided by the logistic, von Bertalanffy, Gompertz, Brody, Richards, and proposed models were compared. The parameters were estimated using the “nls” function of the “stats” package in R software, the least-squares method, and the Gauss-Newton convergence algorithm. The goodness-of-fit comparison was based on the following criteria: adjusted coefficient of determination (), mean square error (MSE), mean absolute deviation (MAD), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Cluster analysis helped select and classify the non-linear growth models, considering the other goodness-of-fit criteria results. The proposed non-linear, von Bertalanffy, Gompertz, and Richards models described the growth curve of Norfolk rabbits satisfactorily, providing parameters with practical interpretations. The goodness-of-fit criteria showed that the proposed and von Bertalanffy models best represented the growth of rabbits.Universidade Federal de Uberlândia2024-02-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/biosciencejournal/article/view/6893610.14393/BJ-v40n0a2024-68936Bioscience Journal ; Vol. 40 (2024): Continuous Publication; e40011Bioscience Journal ; v. 40 (2024): Continuous Publication; e400111981-3163reponame:Bioscience journal (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/biosciencejournal/article/view/68936/37987Brazil; Contemporary Copyright (c) 2024 André Luiz Pinto dos Santos, Tiago Alessandro Espínola Ferreira, Cícero Carlos Ramos de Brito, Frank Gomes-Silva, Guilherme Rocha Moreirahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSantos, André Luiz Pinto dosFerreira, Tiago Alessandro EspínolaBrito, Cícero Carlos Ramos deGomes-Silva, FrankMoreira, Guilherme Rocha2024-04-03T20:47:42Zoai:ojs.www.seer.ufu.br:article/68936Revistahttps://seer.ufu.br/index.php/biosciencejournalPUBhttps://seer.ufu.br/index.php/biosciencejournal/oaibiosciencej@ufu.br||1981-31631516-3725opendoar:2024-04-03T20:47:42Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)false |
dc.title.none.fl_str_mv |
Proposal for a new non-linear model to describe growth curves |
title |
Proposal for a new non-linear model to describe growth curves |
spellingShingle |
Proposal for a new non-linear model to describe growth curves Santos, André Luiz Pinto dos Animal growth Biological parameters Cluster analysis Growth curves Longitudinal data. Agricultural Sciences |
title_short |
Proposal for a new non-linear model to describe growth curves |
title_full |
Proposal for a new non-linear model to describe growth curves |
title_fullStr |
Proposal for a new non-linear model to describe growth curves |
title_full_unstemmed |
Proposal for a new non-linear model to describe growth curves |
title_sort |
Proposal for a new non-linear model to describe growth curves |
author |
Santos, André Luiz Pinto dos |
author_facet |
Santos, André Luiz Pinto dos Ferreira, Tiago Alessandro Espínola Brito, Cícero Carlos Ramos de Gomes-Silva, Frank Moreira, Guilherme Rocha |
author_role |
author |
author2 |
Ferreira, Tiago Alessandro Espínola Brito, Cícero Carlos Ramos de Gomes-Silva, Frank Moreira, Guilherme Rocha |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Santos, André Luiz Pinto dos Ferreira, Tiago Alessandro Espínola Brito, Cícero Carlos Ramos de Gomes-Silva, Frank Moreira, Guilherme Rocha |
dc.subject.por.fl_str_mv |
Animal growth Biological parameters Cluster analysis Growth curves Longitudinal data. Agricultural Sciences |
topic |
Animal growth Biological parameters Cluster analysis Growth curves Longitudinal data. Agricultural Sciences |
description |
This study was developed with longitudinal data measurements of Norfolk rabbits from birth to 119 days of age to estimate the average growth curve, with the primary objective of proposing a non-linear model. It also selected the most appropriate sigmoidal model to describe the growth of Norfolk rabbits. The adjustments provided by the logistic, von Bertalanffy, Gompertz, Brody, Richards, and proposed models were compared. The parameters were estimated using the “nls” function of the “stats” package in R software, the least-squares method, and the Gauss-Newton convergence algorithm. The goodness-of-fit comparison was based on the following criteria: adjusted coefficient of determination (), mean square error (MSE), mean absolute deviation (MAD), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Cluster analysis helped select and classify the non-linear growth models, considering the other goodness-of-fit criteria results. The proposed non-linear, von Bertalanffy, Gompertz, and Richards models described the growth curve of Norfolk rabbits satisfactorily, providing parameters with practical interpretations. The goodness-of-fit criteria showed that the proposed and von Bertalanffy models best represented the growth of rabbits. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-02-15 |
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://seer.ufu.br/index.php/biosciencejournal/article/view/68936 10.14393/BJ-v40n0a2024-68936 |
url |
https://seer.ufu.br/index.php/biosciencejournal/article/view/68936 |
identifier_str_mv |
10.14393/BJ-v40n0a2024-68936 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://seer.ufu.br/index.php/biosciencejournal/article/view/68936/37987 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
Brazil; Contemporary |
dc.publisher.none.fl_str_mv |
Universidade Federal de Uberlândia |
publisher.none.fl_str_mv |
Universidade Federal de Uberlândia |
dc.source.none.fl_str_mv |
Bioscience Journal ; Vol. 40 (2024): Continuous Publication; e40011 Bioscience Journal ; v. 40 (2024): Continuous Publication; e40011 1981-3163 reponame:Bioscience journal (Online) instname:Universidade Federal de Uberlândia (UFU) instacron:UFU |
instname_str |
Universidade Federal de Uberlândia (UFU) |
instacron_str |
UFU |
institution |
UFU |
reponame_str |
Bioscience journal (Online) |
collection |
Bioscience journal (Online) |
repository.name.fl_str_mv |
Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU) |
repository.mail.fl_str_mv |
biosciencej@ufu.br|| |
_version_ |
1797069065837084672 |