Australia

Genetic gain on big data, a new challenge for Australian cattle producers

Genetics

Irish model of the genetic database system is recommended in order to obtain bigger profits on livestock transaction.

Posted on Feb 26 ,11:00

Genetic gain on big data, a new challenge for Australian cattle producers

A Meat&Livestock Australia (MLA) Forum on Breeding an Genetics revealed that the cattle industry needs to adopt a new system of gathering genetic data from the producers in order to increase the value of the livestock. At this time, Ireland seems to have the most performant beef genetic gain system, according to the speakers present at this meeting.
"It is all about getting access to the right data and getting paid for that", said Rod Polkinghorne, one of the guest at MLA's forum.
Ireland has achieved an impressive rate of genetic gains in the last 20 years through a national system that offers rewards for the producers who records individual data of the animals on a national database.
That led to an increase in the value of the cattle but also helped at improving the productivity of beef and dairy sector by using the bulls with the best performing genetics. Irish Cattle Breeding Federation (ICBF) is in charge with establishing and maintaining the genetic database and by now every animal in the Irish herds is recorded on the database along with its individual ancestry and data on traits related to beef or milk profitability indices, reports Beef Central magazine.
The database gathered by ICBF contains 100 million records on more than 30 million animals and it's also the world's single largest livestock genomics program. Compared to that, Australia's system on genetic gains it has more flaws in identifying all the valuable progeny and set a higher price for those used in commercial herds. Speakers at the MLA livestock breeding and genetic forum stressed that Australia's beef industry need to change the way it collects, share and uses genetic data in order to deliver cattle producers bigger gains on their herds.

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