Q&A: More accurate genomic proofs for AI dairy sires

News Q&A: Active Dairy Bull List
Q&A: More accurate genomic proofs for AI dairy sires

What is different about this year’s list?

The list contains a number of improvements compared to previous years.

Two-year old bulls are included for the first time, due to these bulls now having their first official evaluation for calving difficulty, based on calves born this spring.

Genomic proofs for AI sires are now more accurate, due to changes by ICBF and Teagasc in the genomic evaluation system.

These changes include a 15% increase in the size of the sire reference population on which the genomic prediction equations are based; almost 1m extra fertility records from the 2017 calving season; and updates to the genomic evaluation systems and software.

What is the impact of the 2017 changes on the Active Bull List?

The average EBI on the ICBF Active Bull list continues to improve, with the latest listing being €7 ahead of last year’s listing, up from €222 in spring 2016 (after accounting for the base correction in August, 2016), to €229 for the current listing.

Once again, the listing is dominated by young Genomically Selected (GS) bulls, with 68 of the total 75 bulls being these young GS bulls.

The listing is once again almost completely dominated by Irish bred bulls (74 out of the 75 bulls are Irish bred), reflecting the very significant investments that Irish-owned AI companies have made in the national breeding programme, since the introduction of genomics in 2009.

Are there changes in the proofs for bulls as a result of the genomic and data updates?

Yes, there are changes, with these young GS bulls on average reducing by some €39 in EBI value (equivalent to about two days in calving interval, and 1% for survival).

Some bulls drop more and others less than this average figure, depending primarily on how the sires of these young GS bulls are performing on farms.

The impact will be seen most in bulls that have a genomic “only” proof, or a genomic component to their fertility proof (blended proof).

These are generally the younger GS bulls, born in 2015 and 2016.

Whilst the average drop is €39, the average ranking of bulls hardly changes (with a correlation of 95% between the new evaluation and the last official evaluation), indicating that only a very small number of bulls are re-ranking significantly.

What about reliability?

The reliability of bulls will increase as a result of the improvements in genomic evaluation, with the latest analysis indicating an increase in average reliability from 60% in the spring 2016 listing, up to 63% for bulls in the spring 2017 listing.

Should I continue to use genomic bulls, or should I now be considering using daughter proven bulls?

On average, a group of genomic bulls will still be better than any daughter proven bull, when it comes to delivering production and fertility.

For example, the current average EBI for a team of the top five genomic bulls is still some €53 ahead of the best daughter proven bull available on the new list.

This is also apparent from the performance of the Teagasc Next Generation herd, at Moorepark, which were all selected as calves based on their genomic EBI.

Compared to animals with the national average genetic merit, elite animals have delivered more milk solids per lactation, and with much better fertility (98% in calf at the end of a 12-week breeding season during 2016), under the same management conditions.

So the message to farmers is they should still use the genomic bulls, but they should use them in teams, with at least five bulls used equally across the herd, to minimise the potential impact of any EBI changes to bulls (and their herd) in the future.

Are the ICBF beef Euro-Star evaluations similarly affected?

No. Changes in proofs are only related to the genomic evaluations for the dairy milk and dairy fertility traits.

Are we likely to see more changes to the proofs for GS sires in the future?

Improvements to genetic evaluations are on-going.

Reasons for proof changes include addition of new data, addition of new traits, changes to the economic values of traits over time, better prediction methods, and increased computing power.

The main aim of these changes is to improve the reliability of sires and ultimately to help farmers breed the most profitable cows.

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