In addition, those farming in hotter climates also have an interest in a specific breeding tool to provide the best return on investment for their genetics.
These were some of the early findings from DataGene’s National Breeding Objective Review, a two-year project designed to ensure the industry continues to deliver the herd improvement resources dairy farmers want and need to breed their future herds.
This insight into dairy farmers’ breeding objectives comes as DataGene’s latest Australian Breeding Values release reveals a rise of about 75 per cent in the number of Holstein bulls in the Good Bulls Guide with a Balanced Performance Index of more than 500.
DataGene CEO Matt Shaffer said dairy farmers now had more and better bulls available that were proven to perform well under Australian conditions.
The most recent ABVs are an efficient way to understand how each sire performs and would work on farm.
“It’s easier than ever to compare bulls and find genetics to suit individual breeding objectives, so it’s not surprising that 90 per cent of farmer and herd improvement industry representatives told the National Breeding Objective Review they use DataGene tools,” Matt said.
“The most popular tool for survey respondents was the BPI, but they also used DataGene’s Health Weighted Index, Australian Selection Index and other ABVS to inform breeding decisions.
“Although there was interest in seasonal/pasture index and possibly a hot regions index, we also received the strong message to ‘keep it simple’ and avoid unnecessary complexity to the many decisions dairy farmers make in their businesses,” he said.
Other findings from the review indicated there wasn’t strong demand for a Jersey breed-specific index as current indices met Jersey respondents’ needs.
In parallel, Ever.Ag consultancy has completed an analysis of trends and forecasts of milk pricing and input costs.
Findings from this first stage of the review is informing the analysis and modelling by independent genetics consultancy AbacusBio working in consultation with DataGene.
Currently in progress, the results from the modelling and analysis will inform an options paper which will be discussed with industry next year.
DataGene’s review is on schedule for any changes to be implemented in December 2025.
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