Articles | Volume 59, issue 2
Original study
01 Jun 2016
Original study |  | 01 Jun 2016

Estimation of variance components of milk, fat, and protein yields of Tunisian Holstein dairy cattle using Bayesian and REML methods

Hafedh Ben Zaabza, Abderrahmen Ben Gara, Hedi Hammami, Mohamed Amine Ferchichi, and Boulbaba Rekik

Abstract. A multi-trait repeatability animal model under restricted maximum likelihood (REML) and Bayesian methods was used to estimate genetic parameters of milk, fat, and protein yields in Tunisian Holstein cows. The estimates of heritability for milk, fat, and protein yields from the REML procedure were 0.21 ± 0.05, 0.159 ± 0.04, and 0.158 ± 0.04, respectively. The corresponding results from the Bayesian procedure were 0.273 ± 0.02, 0.198 ± 0.01, and 0.187 ± 0.01. Heritability estimates tended to be larger via the Bayesian than those obtained by the REML method. Genetic and permanent environmental variances estimated by REML were smaller than those obtained by the Bayesian analysis. Inversely, REML estimates of the residual variances were larger than Bayesian estimates. Genetic and permanent correlation estimates were on the other hand comparable by both REML and Bayesian methods with permanent environmental being larger than genetic correlations. Results from this study confirm previous reports on genetic parameters for milk traits in Tunisian Holsteins and suggest that a multi-trait approach can be an alternative for implementing a routine genetic evaluation of the Tunisian dairy cattle population.

Short summary
A Bayesian and REML analyses were used on Tunisian dairy cattle data. Genetic parameters for 305-day milk, fat, and protein yields were estimated. Heritability estimates by using Bayesian method ranged from 0.187 to 0.273, and slightly higher than the corresponding REML. Large genetic correlations (> 0.88) among milk, fat, and protein yields were found for the two methods. This study suggests that results from both methods were reasonably similar to suggest both methods can be used.