Comparison of different models in genetic analysis of dystocia

Abstract

Summary The aim of this study was to compare threshold sire model (TS), threshold sire-maternal grandsire model (TS-MGS) and linear sirematernal grandsire model (L) for genetic analysis of dystocia. Threshold models were based on Bayesian approach. In the study, a total of 19439 dystocia records from Holsteins in USA were used. The eff ects of calving year-season, sex of calf, parity of dam, sire of calf and herd eff ects were included in all models and also maternal grandsire eff ect of calf was included in only sire-maternal grandsire models. Variance-covariance estimates were greater in threshold models than in linear model. Estimates of heritability (±SE) of dystocia based on direct genetic eff ects (h 2 D) and maternal genetic eff ects (h 2 M) were 0.18±0.004 and 0.14±0.004 from TS-MGS and 0.12±0.003 and 0.09±0.003 from L, respectively. Heritability estimates based on direct genetic eff ects from TS was 0.20±0.009. Genetic correlation between direct and maternal genetic eff ect were -0.087±0.006 from the TS-MGS and -0.253±0.010 from L. It was concluded that the threshold models were better than the linear model in the analysis of dystocia. The higher heritability estimates on the underlying scale from threshold models should allow greater genetic improvement than those using linear model estimations.