Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis)
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
DOI: | 10.1017/S0021859620000325 |
Texto Completo: | http://dx.doi.org/10.1017/S0021859620000325 http://hdl.handle.net/11449/201763 |
Resumo: | The determination of livestock growth patterns is important for meat or milk production systems, and nonlinear models are used to summarize and interpret the information. The aim of this study was to more accurately estimate growth curve parameters in buffalo cows by evaluating and selecting nonlinear mixed models that employ different types of residuals and include or not contemporary groups (CG) as a covariate. Weight records from 720 animals obtained over a period of 60 months were used. The growth curves were fit using nonlinear mixed-effects models. The Bertalanffy, Gompertz and Logistic models were evaluated. Modelling residuals using four structures (constant, combined, exponential and proportional) and the inclusion or not of CG in the models were also evaluated. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to select the model. In addition to estimating the parameters of the nonlinear growth models and their correlations, the instantaneous growth rate and inflection point were obtained. The Bertalanffy model with a combined residual structure and CG exhibited the lowest AIC and BIC values. Asymptotic weight (A) estimates ranged from 621.8 to 742.1 kg, and the maturity rate (k) ranged from 0.068 to 0.115 kg/month. The correlation between A and k ranged from -0.32 to -0.82 among the models evaluated. The selection criteria indicated that the Bertalanffy model was the most suitable for growth curve analysis in buffaloes. |
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Repositório Institucional da UNESP |
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Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis)Model comparisonrandom effectSAEM algorithmThe determination of livestock growth patterns is important for meat or milk production systems, and nonlinear models are used to summarize and interpret the information. The aim of this study was to more accurately estimate growth curve parameters in buffalo cows by evaluating and selecting nonlinear mixed models that employ different types of residuals and include or not contemporary groups (CG) as a covariate. Weight records from 720 animals obtained over a period of 60 months were used. The growth curves were fit using nonlinear mixed-effects models. The Bertalanffy, Gompertz and Logistic models were evaluated. Modelling residuals using four structures (constant, combined, exponential and proportional) and the inclusion or not of CG in the models were also evaluated. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to select the model. In addition to estimating the parameters of the nonlinear growth models and their correlations, the instantaneous growth rate and inflection point were obtained. The Bertalanffy model with a combined residual structure and CG exhibited the lowest AIC and BIC values. Asymptotic weight (A) estimates ranged from 621.8 to 742.1 kg, and the maturity rate (k) ranged from 0.068 to 0.115 kg/month. The correlation between A and k ranged from -0.32 to -0.82 among the models evaluated. The selection criteria indicated that the Bertalanffy model was the most suitable for growth curve analysis in buffaloes.Insituto Federal de Educação Ciência e Tecnologia Goiano IF Goiano - Campus Rio VerdeUniversidade Estadual Paulista UNESP Campus JaboticabalUniversidade Federal de Grande DouradosUniversidade Estadual Paulista UNESP Campus JaboticabalIF Goiano - Campus Rio VerdeUniversidade Estadual Paulista (Unesp)Universidade Federal de Grande DouradosAraujo Neto, F. R.Oliveira, D. P. [UNESP]Aspilcueta-Borquis, R. R.Vieira, D. A.Guimarães, K. C.Oliveira, H. N. [UNESP]Tonhati, H. [UNESP]2020-12-12T02:41:08Z2020-12-12T02:41:08Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1017/S0021859620000325Journal of Agricultural Science.1469-51460021-8596http://hdl.handle.net/11449/20176310.1017/S00218596200003252-s2.0-85084847812Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Agricultural Scienceinfo:eu-repo/semantics/openAccess2024-06-07T18:40:13Zoai:repositorio.unesp.br:11449/201763Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:45:29.687667Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) |
title |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) |
spellingShingle |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) Araujo Neto, F. R. Model comparison random effect SAEM algorithm Araujo Neto, F. R. Model comparison random effect SAEM algorithm |
title_short |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) |
title_full |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) |
title_fullStr |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) |
title_full_unstemmed |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) |
title_sort |
Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis) |
author |
Araujo Neto, F. R. |
author_facet |
Araujo Neto, F. R. Araujo Neto, F. R. Oliveira, D. P. [UNESP] Aspilcueta-Borquis, R. R. Vieira, D. A. Guimarães, K. C. Oliveira, H. N. [UNESP] Tonhati, H. [UNESP] Oliveira, D. P. [UNESP] Aspilcueta-Borquis, R. R. Vieira, D. A. Guimarães, K. C. Oliveira, H. N. [UNESP] Tonhati, H. [UNESP] |
author_role |
author |
author2 |
Oliveira, D. P. [UNESP] Aspilcueta-Borquis, R. R. Vieira, D. A. Guimarães, K. C. Oliveira, H. N. [UNESP] Tonhati, H. [UNESP] |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
IF Goiano - Campus Rio Verde Universidade Estadual Paulista (Unesp) Universidade Federal de Grande Dourados |
dc.contributor.author.fl_str_mv |
Araujo Neto, F. R. Oliveira, D. P. [UNESP] Aspilcueta-Borquis, R. R. Vieira, D. A. Guimarães, K. C. Oliveira, H. N. [UNESP] Tonhati, H. [UNESP] |
dc.subject.por.fl_str_mv |
Model comparison random effect SAEM algorithm |
topic |
Model comparison random effect SAEM algorithm |
description |
The determination of livestock growth patterns is important for meat or milk production systems, and nonlinear models are used to summarize and interpret the information. The aim of this study was to more accurately estimate growth curve parameters in buffalo cows by evaluating and selecting nonlinear mixed models that employ different types of residuals and include or not contemporary groups (CG) as a covariate. Weight records from 720 animals obtained over a period of 60 months were used. The growth curves were fit using nonlinear mixed-effects models. The Bertalanffy, Gompertz and Logistic models were evaluated. Modelling residuals using four structures (constant, combined, exponential and proportional) and the inclusion or not of CG in the models were also evaluated. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to select the model. In addition to estimating the parameters of the nonlinear growth models and their correlations, the instantaneous growth rate and inflection point were obtained. The Bertalanffy model with a combined residual structure and CG exhibited the lowest AIC and BIC values. Asymptotic weight (A) estimates ranged from 621.8 to 742.1 kg, and the maturity rate (k) ranged from 0.068 to 0.115 kg/month. The correlation between A and k ranged from -0.32 to -0.82 among the models evaluated. The selection criteria indicated that the Bertalanffy model was the most suitable for growth curve analysis in buffaloes. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-12T02:41:08Z 2020-12-12T02:41:08Z 2020-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1017/S0021859620000325 Journal of Agricultural Science. 1469-5146 0021-8596 http://hdl.handle.net/11449/201763 10.1017/S0021859620000325 2-s2.0-85084847812 |
url |
http://dx.doi.org/10.1017/S0021859620000325 http://hdl.handle.net/11449/201763 |
identifier_str_mv |
Journal of Agricultural Science. 1469-5146 0021-8596 10.1017/S0021859620000325 2-s2.0-85084847812 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Agricultural Science |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1822218539333844992 |
dc.identifier.doi.none.fl_str_mv |
10.1017/S0021859620000325 |