Document Type : Original Article
Authors
1
Department of Animal Production, Faculty of Agriculture, Mansoura University, Egypt.
2
Department of Animal Wealth Development, Faculty of Veterinary Medicine, Suez Canal University, Ismailia, Egypt.
3
Department of Animal Wealth Development, Faculty of Veterinary Medicine, Zagazig University, Zagazig, Egypt.
Abstract
The objective of this study was to compare four different statistical models for genetic evaluation of some
traits of Holstein-Friesian dairy cattle raised in Egypt. Data were collected from Alexandria Copenhagen Company; a
commercial dairy herd located in Egypt on Cairo-Alexandria desert road, and represented 2846 first three lactation
records pooled from cows having 60 sires and 428 dams. The studied traits were; days open (DO), 305-days milk yield
(305-DMY), fat yield (FY) and protein yield (PY). Models were discriminated according to random effects fitted in
each model. The random effects were; direct additive genetic effects of animals, maternal additive genetic effects,
permanent environmental effects, together with the covariance between direct and maternal genetic effects, and
residuals. Comparisons of statistical models were based on (AG) Log Likelihood values and estimates of genetic
parameters of traits. Co-variance components and genetic parameters were estimated with VCE-6 software package.
Heritabilities obtained from all models were ranged from (0.07 to 0.10), (0.24 to 0.32), (0.25 to 0.42) and (0.24 to 0.33)
for DO, 305-DMY, FY and PY, respectively. Also, for all traits, the best-fitted model was characterized by the highest
Log Likelihood value, the highest maternal heritability and the existence of direct-maternal genetic covariance.
Estimated breeding values (EBVs) showed high variations with positive spearman’s rank correlations (≥ 0.83) among
models. This study showed that the inclusion of maternal effects with direct-maternal genetic covariances in the
statistical models for genetic evaluations would improve the current herd genetically.
Keywords
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