ArticleVeterinary and animal science2025
Modeling growth performance of heterogeneous rabbits in a pastured system using nonlinear, spline and random regression models.
Article in Veterinary and animal science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Accurate modeling of growth trajectories is critical for decision-making in rabbit production, particularly under low-input systems. However, limited studies have evaluated the comparative performance of growth models for rabbits reared in such systems. This study evaluated the growth performance of heterogeneous rabbits using three modeling approaches. Weekly body weight records of 343 rabbits from birth to 20 weeks of age across four parities were analyzed. Four classical nonlinear models (Gompertz, Logistic, von Bertalanffy, and Richards) were fitted using the NLIN procedure of SAS®. Further, the REG procedure of SAS® was used to fit four linear spline models (SP3 to SP6) while four random regression models with varying variance-covariance structures (Compound Symmetry, Unstructured, Autoregressive, and Toeplitz) were also fitted to the growth data using the MIXED procedure of SAS®. There were significant effects of parity (
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