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B-spline polynomials models for analyzing growth patterns of Guzerat young bulls in field performance tests |
Ricardo Costa Sousa1 
, Fernando dos Santos Magaço2
, Daiane Cristina Becker Scalez3
, José Elivalto Guimarães Campelo4
, Clélia Soares de Assis5
, Idalmo Garcia Pereira5,*
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1Guzerat Agriculture and Livestock Selection LTDA, Rua Benjamin Constant, 366, Curvelo, MG 35790249, Brazil
2Department of Agriculture and Livestock, Faculty of Agricultural Science, Zambezi University, Ulónguè 2306, Mozambique
3Department of Animal Science, Faculty of Agricultural and Veterinary Sciences (FCAV), Jaboticabal, Universidade Estadual Paulista Júlio de Mesquita Filho – Unesp, SP 14884900, Brazil
4Department of Animal Science, Federal University of Piauí – UFPI, Teresina, Piauí 64049550, Brazil
5Department of Animal Science, Veterinary School, Federal University of Minas Gerais – UFMG, Belo Horizonte – MG, Brazil
6Department of Animal Science, Veterinary School, Federal University of Minas Gerais – UFMG, Belo Horizonte, MG 31270901, Brazil |
Correspondence:
Idalmo Garcia Pereira, Tel: +55-3134092186, Email: idalmo.garcia@gmail.com
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Received: 29 July 2023 • Revised: 6 October 2023 • Accepted: 15 November 2023 |
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| Abstract |
Objective
The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls.
Methods
A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied.
Results
Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture.
Conclusion
Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance. |
| Keywords:
Allometry; B-Spline; Legendre; Random Regression; Zebu |
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