Document Type : Research Paper
Ph.D. Candidate, Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran
Assistant Professor; Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran
Professor; Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran
The objective of the present study was to perform genetic evaluation of dystocia, using linear (observed and adjusted) and threshold models in Holstein cattle. Data and pedigree information of 8 dairy herds were obtained from Vahdat Industrial Agriculturists & Dairymen Cooperative, Isfahan, Iran. Final data included 133876 calving records during 2005 to 2018. The fixed effects of the model were included, herd, year-season of calving, calf gender and age at first calving. The random effects of the model were included sire, maternal grandsire, permanent environment of dam and residual effects. Furthermore, 305-day milk yield was considered as a covariate in the final equation. Quality control and data validation were conducted in SAS and Microsoft Excel. Genetic evaluations and prediction of breeding values for dystocia was computed, using different statistical models by DMU program. Direct heritability for dystocia for heifers and other cows based on linear model were 0.10 and 0.07 and based on threshold model were 0.13 and 0.10, respectively. Estimated heritability was higher in threshold model compare to the linear model. The results of this study showed that beyond the environmental improvement, genetic selection might be an option for decreasing dystocia. Estimated heritability for heifers and other cows by the linear model were adjusted on the underlying scale to 0.19 and 0.14, respectively. Estimated correlations between direct and maternal genetic effects were negative and ranged from -0.56 to -0.74, indicating the genetic antagonism between direct and maternal effects. The Spearman rank correlations for breeding values predicted from the linear and threshold models were significant and different from 1, indicating that ranking of animals are not unique in linear and threshold models. Based on the Akaike Information Criterion (AIC), threshold model was better and more accurate than linear model for genetic analysis of dystocia in Holstein cows.