Genetic variance components of the growth curve for Isfahan indigenous chicken

Mostafa Ghaderi-Zefrehei, Farjad Rafeie, Sonia Zakizadeh, Mahdi Elahi Torshizi, Sunday O Peters, Jacqueline Smith

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.

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.

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 (R2 ), mean square error (MSE) and akaike information criterion.

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.

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.

Original languageEnglish
Article numbere1388
Pages (from-to)1-10
Number of pages10
JournalVeterinary Medicine and Science
Issue number2
Early online date20 Feb 2024
Publication statusPublished - Mar 2024

Keywords / Materials (for Non-textual outputs)

  • Animals
  • Chickens/genetics
  • Body Weight/genetics
  • Reproduction
  • Phenotype
  • Iran


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