Validation of genomic predictions in German Holsteins for all traits

Authors

  • S Rensing
  • Z Liu

Keywords:

Holsteins, genomic predictions, validation

Abstract

Genomic enhanced breeding values (gEBV) for Holsteins are official in Germany since August 2010. Independent gEBV in April 2010 of 1,374 German A.I. bulls derived from the validation for the ICAR/Interbull test for the German Holstein genomic evaluation system were compared with their official daughter based gEBV from August 2011. Traits were the milk production index RZM, total conformation index RZE, relative breeding value somatic cell score RZS, combined longevity RZN and daughter fertility index RZR. For all traits differences between means for gEBV without and with daughter information were very small indicating no bias. The same was observed for the top-100 bulls for RZM whereas the top bulls for the other traits seemed to be slightly overestimated by 0.1 (RZE) to 0.2 (RZN) genetic standard deviations (sg). Standard deviation of difference (SD) ranged from below 0.5 for RZS and RZR to 0.68 sg for RZM. There were indications that gEBV without daughters predict later highly reliable daughter based gEBV better than the first daughter based proofs.

Downloads

Issue

No. 44 (2011): Proceedings of the 2011 Interbull meeting

Section

Articles

License

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

 

    1. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

 

    1. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).