Growth Modeling and Genetic Analysis in Poultry
Summary
Poultry production has undergone a revolution through the integration of sophisticated growth models and genetic analysis. Growth modelling employs mathematical and statistical functions to characterise age-related weight gain, enabling producers to predict performance, optimise feeding regimes and estimate maturity indices. Models such as Gompertz, Logistic and Richards capture the sigmoidal nature of avian growth, while mixed-effect frameworks accommodate individual variation and flock-level effects. In parallel, genetic analysis—ranging from traditional quantitative genetics to genomic selection—dissects the heritable components of growth rate, feed efficiency and body composition. Advances in high-density genotyping and whole-genome sequencing have accelerated the identification of quantitative trait loci and single-nucleotide polymorphisms associated with economically important traits. By combining pedigree-based and molecular information, breeders now achieve more accurate estimates of breeding values, accelerating gains in weight, carcass yield and disease resilience. Integrating environmental covariates with genomic predictors further refines performance forecasts under diverse production systems. Globally, these techniques support sustainable intensification, reduce the environmental footprint of poultry farming and enhance food security by delivering robust, efficient breeds that meet consumer and welfare expectations.
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Growth Modeling and Genetic Analysis in Poultry publication trend
The graph below shows the total number of articles in growth modeling and genetic analysis in poultry across all publications each year (not limited to Nature Index journals).
Technical terms
Growth curve model: A mathematical function that describes weight gain over time, commonly sigmoidal in form, used to estimate growth rate, inflection point and mature size.
Heritability: The proportion of phenotypic variance in a trait attributable to genetic differences among individuals, guiding selection intensity.
Quantitative trait locus (QTL): A genomic region containing one or more genes that contribute to variation in a quantitative trait, such as growth rate or feed efficiency.
Genomic selection: A breeding approach that uses genome-wide marker information to predict the genetic merit of individuals and accelerate genetic gain.
Mixed-effect model: A statistical framework that incorporates both fixed effects (e.g. treatment) and random effects (e.g. individual or pen) to account for hierarchical data structure.
References
- A Multistep Interval Prediction Method Combining Environmental Variables and Attention Mechanism for Egg Production Rate. Agriculture (2023).
- The Study of Growth and Performance in Local Chicken Breeds and Varieties: A Review of Methods and Scientific Transference. Animals (2021).
- Comparison of non-linear models to describe the growth in the Andalusian turkey breed. Italian Journal of Animal Science (2021).
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