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Selection of nonlinear mixed models for growth curves of dairy buffaloes (Bubalus bubalis)

Published online by Cambridge University Press:  07 May 2020

F. R. Araujo Neto Open the ORCID record for F. R. Araujo Neto [Opens in a new window] ,
D. P. Oliveira ,
R. R. Aspilcueta-Borquis ,
D. A. Vieira Open the ORCID record for D. A. Vieira [Opens in a new window] ,
K. C. Guimarães ,
H. N. Oliveira  and
H. Tonhati
F. R. Araujo Neto*
Affiliation:
Insituto Federal de Educação, Ciência e Tecnologia Goiano – IF Goiano – campus Rio Verde, 75901970Rio Verde, Goiás, Brazil
D. P. Oliveira
Affiliation:
Universidade Estadual Paulista – UNESP – campus Jaboticabal, Jaboticabal, 14884900São Paulo, Brazil
R. R. Aspilcueta-Borquis
Affiliation:
Universidade Federal de Grande Dourados, Dourados, 79825070Mato Grosso do Sul, Brazil
D. A. Vieira
Affiliation:
Insituto Federal de Educação, Ciência e Tecnologia Goiano – IF Goiano – campus Rio Verde, 75901970Rio Verde, Goiás, Brazil
K. C. Guimarães
Affiliation:
Insituto Federal de Educação, Ciência e Tecnologia Goiano – IF Goiano – campus Rio Verde, 75901970Rio Verde, Goiás, Brazil
H. N. Oliveira
Affiliation:
Universidade Estadual Paulista – UNESP – campus Jaboticabal, Jaboticabal, 14884900São Paulo, Brazil
H. Tonhati
Affiliation:
Universidade Estadual Paulista – UNESP – campus Jaboticabal, Jaboticabal, 14884900São Paulo, Brazil
*
Author for correspondence: F. R. Araujo Neto, E-mail: [email protected]
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Abstract

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.

Keywords

Model comparisonrandom effectSAEM algorithm
Type
Modelling Animal Systems Research Paper
Information
The Journal of Agricultural Science , Volume 158 , Issue 3 , April 2020 , pp. 218 - 224
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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