You could fast-forward the rate of genetic gain in your dairy cattle with LIC Australia’s genomic sires. Over the past three decades LIC has invested substantially into genomic science and genome sequencing technology, which is generating increased productivity and health traits for dairy cows, better returns for dairy farmers and improved environmental efficiency.
Genomics - a generation game
New Zealand has nearly 5 million dairy cows, the vast majority of which graze outside all year round. Uniquely, a high rate (70-80%) of these cows are milk recorded. Our scientists and farmers use the rich dataset from these records to genetically improve the New Zealand dairy herd, and in-turn dairy cows in Australia and across the globe.
Improved milking efficiency, greater cow robustness, and better on-farm profitability are outcomes of genetic gain, which contributes approximately $400 million to the New Zealand dairy economy every year.
Genetic gain is the result of a mathematical equation:
Modern genomic technologies allow us to make even faster gains, and 2020 saw a step change in our animal evaluation model. Here is why:
The goal with genomic selection is to increase the rate of genetic improvement in dairy animals, mainly by narrowing the five-year gap in the generation interval that occurs when using daughter proofs. Genomic evaluation allows us to evaluate a bull’s genetic merit with more accuracy at a younger age.
LIC has invested heavily over the last three decades to improve the accuracy of its animal evaluation system, with improved data providing better predictions on breeding worth for our farmers. The result of this scientific research is LIC’s Single Step Animal Model (SSAM), which combines ancestry, phenotypic and genomic information all in one step to produce an LIC genomic BW (gBW).
The history of genomics at LIC
LIC incorporates genomic estimations in its animal evaluations, both for daughter proven and genomic bulls, providing benefits to farmers such as access to elite genomic sires and better breeding value estimations for slowly expressed traits such as longevity.