Choosing a future bull will soon be like an online dating experience, thanks to clever genetic research.
The NSW Department of Primary Industries (DPI) are building a framework for choosing the right bulls for select country and using a blend of detailed estimated breeding values to benefit cross-breeding in cattle production.
One project jointly funded by NSW DPI and MLA's donor company, is called DeSireBull, best described by the DPI technical officer driving this project, Laura Penrose, as a bit like Tinder for bulls but more like E Harmony, given the complexity of its algorithms.
Ms Penrose, based at Armidale, is currently working on an honours project taking raw data and testing new EBV subgroups via simulated breeding programs that span virtual decades.
The result will give information to the buyer with more confidence.
The trouble with technology is that while it might advance at a rapid pace, we as humans don't.
When a buyer at a bull sale is faced with nearly two dozen different EBVs the overwhelming flood of information has the same effect on the consumer as on a hungry bloke ordering take-away food.
There's too much choice so he tends to focus on a few favourites. In the case of the bull buyer the statistically popular traits involve mature cow weight and eye muscle area.
However, choosing just those two traits is a bit contradictory with EBVs targeting growth also reducing the efficacy of fat cover and fertility.
Ms Penrose and her team are on track to create a clever phone application that lets anyone dial in or out of known genetic correlations.
When somebody bidding on a bull is able to trust this application, Ms Penrose said quality of progeny will reap rewards at sale, while better lines of weaners will enhance Australia's position as a top exporter of quality beef.
As with everything there is give and take, and dialing up, or down, on genetic selection is a balancing act that takes some skill.
"We refine the criteria using EBV subgroups," she said. "And this helps you to choose a bull that suits a target market."
From 20 EBVs there becomes four potential groups - birth and calving, growth, carcase and fertility - with the top animals starting at one and the lowest at 100, just like the familiar breed percentage band figures in the bull catalogue.
There could be subgroups, which instead highlight bulls best suited to jobs like backgrounding and the feedlot market, with choices based on 200, 400 and 600-day weights and efficiency.
There would also be a processing sub-group, highlighting retail beef yield and eye muscle area.
From this point those EBVs can be manipulated using an index slider which correlates subgroups, so that when you slide the bar towards more growth, you will see that a correlating loss of carcase fat cover and IMF is the trade-off.
To assist making a decision in real terms, economic values or "weights" are combined with EBV subgroup data to show, in dollar terms, where your choices lie.
"This is a scientific assessment," Ms Penrose said, who is currently writing lines of code on her computer in a language called R. "It is not a subjective one."
To test whether the algorithm is working Ms Penrose enters raw data and weights from actual animals and creates her own estimated breeding values for those individuals, before "breeding" with them, and their progeny, for the next 20 years.
The actual rendering of that predicted outcome amazingly takes just minutes.
Of course, there are corrugations to smooth-out along the way. For instance - can the highly heritable trait for mature cow weight be grouped with growth? Should it be paired with predicted birth weight and which one is best?
The DeSireBull program is expected to wrap up by the end of December and a pilot application should be made available in the new year.