Bayesian threshold analysis of litter size in sheep


  • Amin Mortazavi University of Tabriz
  • Sadegh Alijani University of Tabriz
  • Mostafa Ghaderi-Zefrehei Yasouj University
  • Farjad Rafeie University of Guilan
  • Ali Jafari Yasouj University
  • Hamed Amirpour-Najafabadi Lincoln University



Bayesian, bivariate analysis, genetic improvement, genetic parameters, heritability, litter size, maternal genetic, sheep, threshold models, univariate analysis


Background: Litter size at birth (LSB) is one of the most important economic traits in sheep and could be used in genetic improvement schemes for meat production. LSB is inherently a categorical trait and should be analysed with threshold models. Objective: Bayesian threshold models were used to analyze sheep LSB to estimate genetic parameters. Methods: Data was based on 7,901 LSB records from 14,968 dams and 682 sires collected from 1986 to 2012 at Makouie Sheep Breeding Station in Iran. Means of posterior distributions (MPDs) of LSB's genetic parameters were estimated, and the best-fitted models were selected using the deviance information criterion. Results: In the repeated measurement analysis, the estimated direct and maternal heritabilities, and permanent environmental effect (±SE), according to the best-fitted model (model 5), were 0.01 (0.010), 0.02 (0.014), and 0.01 (0.011), respectively. In the univariate analysis, the best estimates of direct and maternal heritabilities were 0.12 (0.064) and 0.08 (0.045), respectively. An increasing trend for direct and maternal heritabilities was observed in parity 2 (0.15 (0.082) and 0.25 (0.083), respectively). In the bivariate analysis, the best estimates of direct and maternal heritabilities for LSB were 0.03 (0.027) and 0.22 (0.041), respectively. The direct and maternal genetic correlations among parities were 0.25 (0.054) and 0.12 (0.021), respectively. Conclusions: The results showed a considerable influence of environmental factors on LSB in each parity of sheep; also, statistically different genetic parameters (p<0.05) were obtained from one parity to another, indicating the different and large influences of genetic and environmental factors for each parity.

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Author Biographies

Amin Mortazavi, University of Tabriz

Department of Animal Science, University of Tabriz, Tabriz, Iran

Sadegh Alijani, University of Tabriz

Department of Animal Science, University of Tabriz, Tabriz, Iran

Mostafa Ghaderi-Zefrehei, Yasouj University

Department of Animal Science, Yasouj University, Yasouj, Iran

Farjad Rafeie, University of Guilan

Department of Agricultural Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

Ali Jafari, Yasouj University

Department of Animal Science, Yasouj University, Yasouj, Iran

Hamed Amirpour-Najafabadi, Lincoln University

Faculty of Agriculture and Life Sciences, Lincoln University, Lincoln 7647, New Zealand


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How to Cite

Mortazavi, A., Alijani, S., Ghaderi-Zefrehei, M., Rafeie, F., Jafari, A., & Amirpour-Najafabadi, H. (2022). Bayesian threshold analysis of litter size in sheep. Revista Colombiana De Ciencias Pecuarias, 35(3), 125–140.



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