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The research aims to model growth trajectories of Denizli chickens under varying production systems and to identify optimal nonlinear growth functions using a Bayesian approach.

May 29, 2026AnimalsOpen Access

Bayesian Multi-Model Comparison and Nonlinear Mixed Modelling of Growth Trajectories in Denizli Chickens

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The research aims to model growth trajectories of Denizli chickens under varying production systems and to identify optimal nonlinear growth functions using a Bayesian approach.
Monitored 156 Denizli chickens weekly from hatch to 26 weeks across three production systems: conventional cage, conventional floor, and enriched floor.
Evaluated eight nonlinear growth models using Bayesian criteria, including leave-one-out cross-validation (LOO) and WAIC.
Extended the Gompertz function model to a Bayesian nonlinear mixed modelling framework for sex and production system effects.
The Gompertz function showed superior predictive performance with the lowest LOOIC of 225.16.
Males had higher asymptotic weights than females, while females had faster early growth and earlier stabilization.
Conventional floor systems yielded the highest asymptotic growth potential, indicating prolonged growth phases.

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Implication

Randomized trial models growth trajectories in Denizli chickens, indicating how production systems and sex affect growth.

Cite This Study

Manav et al. (2026) studied this question.

synapsesocial.com/papers/6a192dbbfab5b468c441693c https://doi.org/10.3390/ani16111633

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Bayesian Multi-Model Comparison and Nonlinear Mixed Modelling of Growth Trajectories in Denizli Chickens

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Cite This Study

Bayesian Multi-Model Comparison and Nonlinear Mixed Modelling of Growth Trajectories in Denizli Chickens

Key Points

Discussion

Implication

Cite This Study

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