The Cattle Council of Australia is calling for a united front between Meat & Livestock Australia (MLA) and the Australian Meat Processing Corporation (AMPC) to co-operatively invest and accelerate the roll out of Dual Energy X-ray Absorptiometry (DEXA) objective carcass measurement technology across the Australian red meat processing sector.
The call for a collaborative approach to a whole-of-industry roll out of the technology to provide impartial and science-driven analysis of carcases comes on the back of findings of an AMPC-commissioned Ernst & Young (EY) report into the technology, Cattle Council of Australia President Howard Smith said.
“The Cattle Council of Australia looks forward to working with our value chain partners in the processing sector to develop greater transparency within industry and share the benefit of OCM technologies,” Mr Smith said.
The EY report reflected findings in the recently released year-long report by Greenleaf, Miracle Dog Consulting and S. Williams Consulting – jointly commissioned by MLA and AMPC – that showed that the potential benefits of the technology relating to measuring lean meat yield were shared between producers and processors.
“We have also seen objective measurement technology recommended by the ACCC, the Meat Industry Strategic Plan (MISP 2020) and MLA’s Strategic Plan 2016-2020,” Mr Smith said.
Mr Smith highlighted the need to fast track the roll out of the technology in order to realise the full financial benefits for the industry.
“We know that DEXA technology has been trialled and that DEXA hardware has been commercially used for both sheep and cattle processors for the past two years,” Mr Smith said.
“The adoption of DEXA’s technology across industry will provide numerous market advantages and will change the way we do business for the better.
“As well as paving the way for scientific measurement of saleable meat yield, there is the potential for future value based marketing and industry-wide productivity gains through processing automation, genetic improvement and data-based on-farm decision making.”