This press release came from NZAEL
(New Zealand Animal Evaluations Ltd) in April:
“The NZAEL has decided to suspend genomic data from BW
estimates [Breeding Worth= their
equivalent to $Net Merit] until it is
better able to provide comparability between estimates of merit of young sires”
quoting Bill Montgomerie, head of NZAEL’s dairy evaluation team. Sire proving of the first genomic bulls
proved that their real BW was not what had been estimated by genomics. Genomic bull data has now been removed
from calculations of the national (NZ) breeding index.
The Kiwi’s had the first operating
Genomic estimation system, and the Oceanic AI systems were using this data for
young sire selection six years ahead of its release in Europe and North
America. However, on their first try,
it was found that the average overestimation at “elite” levels was 25-30%
depending on breed. They were the ones
who recommended to USDA to use a larger number of SNPs to gain on the
accuracy—yet the above announcement suggests even that solution is not working
for them.
The US and Canadian AI systems are
deeply immersed in Genomic theory as the preferred way to select the next
generations of young sires for AI. Yet
experiences from NZ, and to a lesser extent Europe, are still suggesting
dairymen need to be cautious in their selection of young sires on G index rank
alone.
Progeny proven sires at high levels
of Rel%-- and basing selection on more than just a ranking index—remains the
“gold standard” for herd improvement. Population genetics’ methods remain more adept
at predicting the behavior of populations than of individual animals.
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