With the support of the Meat & Livestock Australia donor company, CQ University is addressing the challenge of increasing the uptake of objective genetic performance recording in extensive beef production systems. The participation in performance-recording programs is in part limited by the challenge of collecting accurate, BREEDPLAN compliant, performance data.

This challenge is particularly critical for more difficult to record data such as birth dates and weights and these are the very traits that have the potential to have the greatest positive impact on production.

DataMuster is a fast, simple and accurate tool for automatically monitoring and managing the performance of your herd, right down to the individual animal. DataMuster combines cutting edge technology with walk over weigh systems to automatically gather phenotypic data such as animal live-weight, pregnancy status and parentage, as well as improve the understanding of animal behavior, all with a view to improve on-farm profitability and production.

Which is why DataMuster is seeking producers to assist this research project in achieving these goals.

We are looking for:

• Seedstock producers, who are either already BREEDPLAN participants OR are recording (in any format) genetic performing traits that could be submitted to BREEDPLAN
  
• Tagging/recording calves once dropped (not critical however preferable to be able to validate DataMuster’s trait analysis algorithms)

If you fit the above criteria and would like to participate in the DataMuster journey, please contact Hannah Jasperson on h.jasperson@cqu.edu.au or 0427 716 721 to discuss further. Once we get a group of potential participants we will arrange a webinar/zoom session to go through the project in finer detail.

If you could share this through your channels for further reach that would be greatly appreciated. Or, if you have a newsletter that we could put a snippet in, please let me know and I would be happy to get a PDF version through to you.

It is also important to note, if producers are interested in automating their livestock data but don’t fit the above criteria we would still love to hear from them!

Kind Regards,