2018: 150th Anniversary of the Foundation of Agricultural University in Debrecen

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Upgrading breeding value estimation in beef cattle

Published September 5, 2018
Authors
Ferenc Szabó
Széchenyi István University Faculty of Agricultural and Food Sciences Mosonmagyaróvár, Hungary
, Márton Szűcs
Hungarian Limousine and Blonde d’Aqiutaine Breeders Association, Budapest, Hungary
, Károly Tempfli
Széchenyi István University Faculty of Agricultural and Food Sciences Mosonmagyaróvár, Hungary
, Berry Donagh
Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermony, Co., Cork, Ireland
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Keywords
SNP information genomic evaluation beef cattle
How to Cite
Selected stlye: APA
Szabó, F., Szűcs, M., Tempfli, K., & Donagh, B. (2018). Upgrading breeding value estimation in beef cattle. Acta Agraria Debreceniensis, (150), 451–458. https://doi.org/10.34101/actaagrar/150/1740
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This work is licensed under a Creative Commons Attribution 4.0 International License.

This paper gives a summary of the possibility for applying genomic information for breeding value estimation in beef cattle breeding. This process is called genomic prediction and is now widely used in dairy cattle globally as well as in some beef and sheep populations. The advantage of genomic prediction is a more accurate estimate of the genetic merit of an individual at a young age thereby facilitating greater annual genetic gain, predominantly through shorter generation intervals. Genomic predictions are more advantageous for sex-linked (e.g., milk yield), low heritability (e.g., fertility) and difficult-to-measure (e.g., feed intake) traits. The larger the reference population, on average, the more accurate the genomic predictions; additionally, the closer genetically the reference population is to the candidate population, the greater the accuracy of genomic predictions. Research is continuing on strategies to generate accurate genomic predictions using a reference population consisting of multiple breeds (and crossbred). Retrospective analysis of real-life data where genomic predictions have been operation for several years clearly shows a benefit of this technology.

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