Estimation of variance components and genetic parameters of body weight traits in crossbreds of Japanese quail with considering non-additive genetic effects

Document Type : Research Paper

Authors

1 MSc of animal breeding, Department of Animal Science, Agriculture Faculty, University of Zabol, Zabol, Iran

2 Assistant Professor of University of Zabol

3 Academic staff at Research Center of Specific Livestock, University of Zabol, Zabol

4 Department of Animal Science, university of zabol

5 department of animal science, university of zabol

Abstract

Growth traits in broiler chicken are important economic traits in breeding programs. A major part of the growth performance in birds is the result of the gens combination, which use of these combined effects requires the optimal design for mating system to use the general and specific genes' combining ability. The aim of this study was to estimate variance components and genetic parameters for body weight traits in a crossbred population of four Japanese quail strains from of partial diallel cross design using an animal model includes direct additive and non-additive genetic effects. The estimation of variance components for body weight traits, including hatch weight and weights at 5, 10, 15, 20, 25, 30, 35, 40 and 45 days-old were performed using a single-trait animal model via Gibbs sampling. Gibbs chains with 1,500,000 iterations were generated, with an initial discard of 150,000 samples and a sampling interval of 100 iterations. The estimated heritability of the above mentioned traits were 0.655, 0.276, 0.201, 0.022, 0.053, 0.04, 0.129, 0.087, 0.417 and 0.046, respectively. The contribution of direct additive genetic variance was lower in early weighting traits and the additive variance contribution was incremented with an increase in the bird's age. Adding non-additive genetic effects, including dominance and epistasis in the model, reduced the error variance and increased the accuracy of additive genetic variance estimates.

Keywords

References

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Animal Sciences Journal
Volume 32, Issue 123
September 2019
Pages 285-300

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