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Articles | Volume 59, issue 2
Articles | Volume 59, issue 2
https://doi.org/10.5194/aab-59-243-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/aab-59-243-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
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

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Latest update: 20 Mar 2023
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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.
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