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Simple hierarchical and general nonlinear growth modeling in sheep

Ghaderi-Zefrehei, M
Rafeie, F
Bahreini Behzadi, MR
Nazari, S
Muhaghegh-Dolatabady, M
Samadian, F
Maxwell, Thomas
Amirpour Najafabadi, H
Journal Article
Fields of Research
ANZSRC::070202 Animal Growth and Development , ANZSRC::07 Agricultural and Veterinary Sciences , ANZSRC::070105 Agricultural Systems Analysis and Modelling , ANZSRC::3003 Animal production , ANZSRC::3009 Veterinary sciences
Differential equations and advanced statistical models have been used to predict growth phenomena. In the present study, general nonlinear growth functions such as von Bertalanffy, Gompertz, logistic, and Brody, along with hierarchical modeling were applied to investigate the phenotypic growth pattern of Iranian Lori-Bakhtiari sheep. Growth data from 1410 Lori- Bakhtiari lambs were used in the present study. The results showed that the Brody function outperformed the other three nonlinear growth functions. In addition, including hierarchical growth modeling results allowed the adoption of many random effect structures, suggesting that hierarchical growth modeling has a useful role in growth data modeling. This method provides an estimation of growth parameters based on individual animals, improving individual growth selection. The results suggest this approach for growth modeling. Combining the strength of individual growth modeling with general growth modeling, e.g., von Bertalanffy, Gompertz, logistic, and Brody would be deeply appealing in the future. In this regard, dealing with sheep growth phenomenon using pure mathematical models, i.e. grey system theory models that could be new powerful prediction tools for breeders and experts, has not been done yet. However, running the analysis on large datasets will require significantly higher computational power than is ordinarily available.