Articles | Volume 66, issue 3
Original study
15 Sep 2023
Original study |  | 15 Sep 2023

Genetic-parameter estimation of milk yield in White Maritza sheep breed using different test day models

Petya Zhelyazkova, Doytcho Dimov, and Sreten Andonov

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Cited articles

Akaike, H.: Information Theory and an Extension of the Maximum Likelihood Principle, in: International Symposium on Information Theory, edited by: Petrov, B. N. and Csaki, F., 267–281, Springer, New York, NY, 1973. 
Ali, T. E. and Schaeffer, L. R.: Accounting for covariances among test day milk yields in dairy cows, Can. J. Anim. Sci., 67, 637–644,, 1987. 
Andonov, S., Ødegård, J., Boman, I. A., Svendsen, M., Holme, I. J., Adnøy, T., Vukovic, V., and Klemetsdal, G.: Validation of test-day models for genetic evaluation of dairy goats in Norway, J. Dairy Sci., 90, 4863–4871,, 2007. 
Andonov, S., Ødegård, J., Svendsen, M., Ådnøy, T., Vegara, M., and Klemetsdal, G.: Comparison of random regression and repeatability models to predict breeding values from test-day records of Norwegian goats, J. Dairy Sci., 96, 1834–1843,, 2013. 
Barillet, F. and Boichard, D.: Use of first lactation test day data for genetic evaluation of the Lacaune dairy sheep, in: Proc. 5th World Congress on Genetics Applied to Livestock Production, Guelph, Canada, 111–114, Department of Animal & Poultry Science, University of Guelph, ISBN 9780889553668, 1994. 
Short summary
The aims of this study were to estimate the genetic parameters of test day milk yield in the population of the White Maritza sheep breed and to choose the most appropriate linear models for genetic-parameter estimation of test day milk yield. Nine test day models were formulated and tested for the estimation of genetic parameters of milk yield. To compare the linear models described above, Akaike information criterion, Bayesian information criterion and log-likelihood were calculated.