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Autoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle

Published online by Cambridge University Press:  21 January 2020

Hugo T. Silva ,
Paulo S. Lopes ,
Claudio N. Costa ,
Fabyano F. Silva ,
Delvan A. Silva ,
Alessandra A. Silva ,
Gertrude Thompson  and
Júlio Carvalheira
Hugo T. Silva
Affiliation:
Department of Animal Science, Federal University of Viçosa, Viçosa36570-000, Brazil
Paulo S. Lopes
Affiliation:
Department of Animal Science, Federal University of Viçosa, Viçosa36570-000, Brazil
Claudio N. Costa
Affiliation:
Embrapa Dairy Cattle, Juiz de Fora36.038-330, Brazil
Fabyano F. Silva
Affiliation:
Department of Animal Science, Federal University of Viçosa, Viçosa36570-000, Brazil
Delvan A. Silva
Affiliation:
Department of Animal Science, Federal University of Viçosa, Viçosa36570-000, Brazil
Alessandra A. Silva
Affiliation:
Department of Animal Science, Federal University of Viçosa, Viçosa36570-000, Brazil
Gertrude Thompson
Affiliation:
Research Center in Biodiversity and Genetic Resources (CIBIO-InBio), University of Porto, Vairão4485-661, Portugal Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto4050-313, Portugal
Júlio Carvalheira*
Affiliation:
Research Center in Biodiversity and Genetic Resources (CIBIO-InBio), University of Porto, Vairão4485-661, Portugal Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto4050-313, Portugal
*
Author for correspondence: Júlio Carvalheira, Email: [email protected]
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Abstract

We investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two models. Overall, the proposed AR model was suitable for genetic evaluations of longitudinal reproductive traits in dairy cattle, outperforming the REP model.

Keywords

AutocorrelationHolstein cattlemodel evaluationreproduction performance
Type
Research Article
Information
Journal of Dairy Research , Volume 87 , Issue 1 , February 2020 , pp. 37 - 44
Copyright
Copyright © Hannah Dairy Research Foundation 2020

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