Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-05T06:45:52.664Z Has data issue: false hasContentIssue false
  • English
  • Français

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]
Get access Rights & Permissions [Opens in a new window]

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
Check for updates
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agudelo-Gómez, D, Hurtado-Lugo, N and Cerón-Muñoz, MF (2009) Growth curves and genetic parameters in Colombian buffaloes (Bubalus Bubalis Artiodactyla, Bovidae). Revista Colombiana de Ciencias Pecuarias, 22, 178–188.Google Scholar
Akaike, H (1974) A new look at the statistical model identification. IEEE Trans Automat Contr, 19, 716–723.CrossRefGoogle Scholar
Andrade, VD and Garcia, SK (2005) Padrões raciais e registro de bubalinos. Revista Brasileira de Reprodução Animal, 29, 39–45.Google Scholar
Araújo, ROD, Marcondes, CR, Damé, MCF, Garnero, ADV, Gunski, RJ, Everling, DM and Rorato, PRN (2012) Classical nonlinear models to describe the growth curve for Murrah buffalo breed. Ciência Rural, 42, 520–525.CrossRefGoogle Scholar
Aspilcueta-Borquis, RR, Araújo Neto, FR, Baldi, F, Bignard, AB and Albuquerque, LG (2010) Genetic parameters for buffalo milk yield and milk quality traits using Bayesian inference. Journal of Dairy Science 93, 2195–2201.CrossRefGoogle ScholarPubMed
Behzadi, MRB, Aslaminejad, AA, Sharifi, AR and Simianer, H (2014) Comparison of mathematical models for describing the growth of Baluchi sheep. Journal of Agricultural Science and Technology, 16, 57–68.Google Scholar
Bergamasco, AF, Aquino, L and Muniz, J (2001) Ajuste de modelos não-lineares a dados de crescimento de fêmeas da raça holandesa. Ciência e Agrotecnologia, 25, 235–241.Google Scholar
Brotherstone, S, Coffey, MP and Banos, G (2007) Genetic parameters of growth in dairy cattle and associations between growth and health traits. Journal of Dairy Science, 90, 444–450.CrossRefGoogle ScholarPubMed
Coffey, MP, Hickey, J and Brotherstone, S (2006) Genetic aspects of growth of Holstein-Friesian dairy cows from birth to maturity. Journal of Dairy Science, 89, 322–329.CrossRefGoogle ScholarPubMed
Comets, E, Lavenu, A and Lavielle, M (2017) Parameter estimation in nonlinear mixed effect models using saemix, an R implementation of the SAEM algorithm. Journal of Statistical Software, 80, 1–41.CrossRefGoogle Scholar
Coyne, JM, Berry, DP, Mäntysaari, EA, Juga, J and McHugh, N (2015) Comparison of fixed effects and mixed model growth functions in modelling and predicting live weight in pigs. Livestock Science, 177, 8–14.CrossRefGoogle Scholar
Freitas, ARD (2005) Growth curves in animal production. Revista Brasileira de Zootecnia, 34, 786–795.CrossRefGoogle Scholar
Garnero, ADV, Marcondes, CR, Bezerra, LAF, Oliveira, HND and Lôbo, RB (2005) Genetic parameters of maturation rate and asymptotic weight of Nellore females. Arquivo Brasileiro de Medecina Veterinária e Zootecnia, 57, 652–662.CrossRefGoogle Scholar
Goldberg, V and Ravagnolo, O (2015) Description of the growth curve for Angus pasture-fed cows under extensive systems. Journal of Animal Science, 93, 4285–4290.CrossRefGoogle ScholarPubMed
Houssein-Zahed, NG (2017) Modelling growth curve in Moghani sheep: comparison of non-linear mixed growth models and estimation of genetic relationship between growth curve parameters. The Journal of Agricultural Science, 155, 1150–1159.Google Scholar
Kass, RE and Raftery, AE (1995) Bayes Factors. Journal of the American Statistical Association, 90, 773–795.CrossRefGoogle Scholar
Kuhn, E and Lavielle, M (2005) Maximum likelihood estimation in nonlinear mixed effects models. Computational Statistics & Data Analysis, 49, 1020–1038.CrossRefGoogle Scholar
Laird, AK (1965) Dynamics of relative growth. Growth, 29, 249–263.Google ScholarPubMed
Lopes, FB, Silva, MC, Marques, EG and McManus, CM (2012) Analysis of longitudinal data of beef cattle raised on pasture from northern Brazil using nonlinear models. Tropical Animal Health and Production, 44, 1945–1951.CrossRefGoogle ScholarPubMed
Lopes, FB, Magnabosco, CDU, Souza, FM, Assis, AS and Brunes, LC (2016) Análises de dados longitudinais em bovinos Nelore Mocho por meio de modelos não lineares. Archivos de Zootecnia, 65, 123–129.CrossRefGoogle Scholar
Malhado, CHM, Ramos, AA, Carneiro, PLS, Souza, JC, Wechsler, FS, Eler, JP, Azevêdo, DMMR and Sereno, JRB (2008) Nonlinear models to describe the growth of the buffaloes of Murrah breed. Archivos de Zootecnia, 57, 497–503.Google Scholar
Malhado, CHM, Gonçalves Rezende, MP, Malhado, ACM, Azevedo, DMMR, Souza, JC and Carneiro, PLS (2017) Comparison of nonlinear models to describe the growth curves of Jaffarabaddi, Mediterranean and Murrah buffaloes. Journal of Agricultural Science and Technology, 19, 1485–1494.Google Scholar
Marai, IFM and Haeeb, AAM (2010) Buffalo's biological functions as affected by heat stress – A review. Livestock Science, 127, 89–109.CrossRefGoogle Scholar
Marinho, KNDS, Freitas, ARD, Falcão, AJDS and Dias, FEF (2013) Nonlinear models for fitting growth curves of Nellore cows reared in the Amazon biome. Revista Brasileira de Zootecnia, 42, 645–650.CrossRefGoogle Scholar
Moreira, RP, Mercadante, ME, Pedrosa, VB, Cyrillo, JNDSG and Henrique, W (2016) Growth curves on females of the Caracu breed. Semina: Ciências Agrárias, 37, 2749–2758.Google Scholar
Morrow, RE, McLaren, JB and Butts, WT (1978) Effect of age on estimates of bovine growth-curve parameters. Journal of Animal Science, 47, 352–357.CrossRefGoogle Scholar
Nelder, JA (1961). The fitting of a generalization of the logistic curve. Biometrics, 17, 89–110.CrossRefGoogle Scholar
Oliveira, HN, Lôbo, RB and Pereira, CS (2000) Comparação de modelos não-lineares para descrever o crescimento de fêmeas da raça Guzerá. Pesquisa Agropecuária Brasileira, 35, 1843–1851.CrossRefGoogle Scholar
Perera, BMAO (2011) Reproductive cycles of buffalo. Animal Reproduction Science, 124, 194–199.CrossRefGoogle ScholarPubMed
R Core Team (2018) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Available at https://www.R-project.org/.Google Scholar
Schwarz, G (1978) Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.CrossRefGoogle Scholar
Teleken, JT, Galvão, AC and Robazza, WS (2017) Comparing non-linear mathematical models to describe growth of different animals. Acta Scientiarum. Animal Sciences, 39, 73–81.CrossRefGoogle Scholar
Torre, GL, Candotti, JJ, Reverter, A, Bellido, MM, Vasco, P, Garcia, LJ and Brinks, JS (1992) Effects of growth curve parameters on cow efficiency. Journal of Animal Science, 70, 2668–2672.CrossRefGoogle Scholar
Van De Stroet, DL, Díaz, JC, Stalder, KJ, Heinrichs, AJ and Dechow, CD (2016) Association of calf growth traits with production characteristics in dairy cattle. Journal of Dairy Science, 99, 8347–8355.CrossRefGoogle ScholarPubMed
Von Bertalanffy, L (1957) Quantitative laws in metabolism and growth. The Quarterly Review of Biology, 32, 217–231.CrossRefGoogle Scholar