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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Bayesian Multi-Model Comparison and Nonlinear Mixed Modelling of Growth Trajectories in Denizli Chickens
Harun Raşit Manav1, Doğan Narinç2, Ali Aygun3
1Aselya Agriculture Corporation, Antalya 07500, Turkey.
Animals : an Open Access Journal From MDPI
|June 12, 2026
Summary
The Gompertz function best models Denizli chicken growth. Production systems and sex significantly impact chicken growth trajectories, offering insights for poultry management.
Area of Science:
- Poultry Science
- Animal Growth Modeling
- Bayesian Statistics
Background:
- Understanding poultry growth dynamics is crucial for optimizing production systems.
- Denizli chickens are an important indigenous and dual-purpose breed.
- Accurate growth modeling aids in informed breeding and management decisions.
Purpose of the Study:
- To model Denizli chicken growth trajectories under different production systems.
- To identify the most appropriate nonlinear growth function using a Bayesian framework.
- To evaluate the influence of sex and production system on growth dynamics.
Main Methods:
- Weekly monitoring of 156 Denizli chickens from hatch to 26 weeks.
- Evaluation of eight nonlinear growth models using Bayesian criteria (LOO, WAIC).
- Application of Bayesian nonlinear mixed modelling to assess sex and production system effects.
Main Results:
- The Gompertz function demonstrated superior predictive performance for chicken growth.
- Males had higher asymptotic weights; females exhibited faster early growth.
- Conventional floor systems promoted prolonged growth, while enriched systems increased variability.
Conclusions:
- Production system and sex significantly influence Denizli chicken growth scale and timing.
- Bayesian nonlinear mixed modelling provides biologically meaningful insights.
- Findings support improved breeding, housing, and management strategies for Denizli chickens.
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