Inbreeding depression for growth traits in small ruminants: A meta-analysis

Document Type : Research Paper

Authors

1 Former M.Sc. Student, Department of Animal Science, Faculty of Agriculture, University of ‎Kurdistan, Sanandaj, Iran

2 Assistant Professor, Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, ‎Iran

3 Ph.D. Candidate, Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran

Abstract

Because of undesirable effects on economic traits and performance of animals, the inbreeding has always been a challenge in animal breeding. Control of inbreeding at an appropriate level for improving the response to selection is very important. Reported values for inbreeding depression rates varied across populations of small ruminants. The present study aimed to investigate the effect of inbreeding on growth traits, including birth weight (BW), weaning weight (WW), sixth month weight (6MW), ninth month weight (9MW) and yearly weight (YW) in small ruminants. A meta-analysis was performed in order to obtain a more precise estimation of inbreeding depression. Meta-analysis is an analytical technique designed to summarize the results of multiple studies. Comprehensive Meta-Analysis software was used to analyze data. Cochran’s Qtest and I-squared (I2)statistic were used to quantify heterogeneity of studies and select the appropriate analysis model. A sensitivity analysis was applied by removing one study at a time to detect stability of overall results. Publication bias among studies was determined using the Egger’s regression test. The results of this meta-analysis showed that the inbreeding depression per one percent increase in inbreeding for BW, WW, 6MW, 9MW and YW were -0.004, -0.054, -0.035 -0.13 and -0.067 kg, respectively. In addition, inbreeding effects were significant for BW and WW (p <0.05).

Keywords

References

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Iranian Journal of animal Science
Volume 51, Issue 3
December 2020
Pages 231-241

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History

  • Receive Date: 10 December 2019
  • Revise Date: 17 October 2020
  • Accept Date: 24 October 2020

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