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Genetic variance components of the growth curve for Isfahan indigenous chicken.
- Source :
-
Veterinary medicine and science [Vet Med Sci] 2024 Mar; Vol. 10 (2), pp. e1388. - Publication Year :
- 2024
-
Abstract
- Background: Being able to model a growth curve using three or four non-linear functional parameters could help explain the growth phenomenon in a precise way and would allow the comparison of an animal's development rate, optimize management and feeding strategies and guide animal production strategies.<br />Objective: The goal of this study was to estimate the genetic parameters of growth traits of Isfahan indigenous chicken in Iran and to determine the best non-linear model describing the growth curve.<br />Methods: The prediction of additive genetic parameters was performed using the REML method by WOMBAT. Direct heritability of the studied traits and genetic correlations between them were obtained. The Logistic, Gompertz, von Bertalanffy, Brody, Negative exponential, Weibull, Janoschek and Bridges models were compared based on the coefficient of determination (R <superscript>2</superscript> ), mean square error (MSE) and akaike information criterion.<br />Results: The Gompertz model was identified as the best model for describing the growth curve for Isfahan native chicken. The heritability of maturity weights (A), initial weight (B) and maturity rate (K) parameters were 0.223 ± 0.002, 0.016 ± 0.005 and 0.087 ± 0.001, respectively.<br />Conclusion: This study shows that Isfahan indigenous chicken has the genetic potential for improving growth and reproduction based on their desirable heritabilities and correlations using appropriate models.<br /> (© 2024 The Authors. Veterinary Medicine and Science published by John Wiley & Sons Ltd.)
- Subjects :
- Animals
Body Weight genetics
Phenotype
Iran
Chickens genetics
Reproduction
Subjects
Details
- Language :
- English
- ISSN :
- 2053-1095
- Volume :
- 10
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Veterinary medicine and science
- Publication Type :
- Academic Journal
- Accession number :
- 38379342
- Full Text :
- https://doi.org/10.1002/vms3.1388