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Changing Australia's trading language has enhanced the implementation of objective carcase measurement technologies
G E Gardner1, H B Calnan1, S L Connaughton1
1Advanced Livestock Measurement Technologies (ALMTech), Food Futures Institute, Murdoch University, Western Australia 6150, Australia.
Abstract:
In 2016 an Australian project, the Advanced Livestock Measurement Technologies project (ALMTech), was initiated to accelerate the development and implementation of technologies that measure lean meat yield and eating quality. This led to the commercial testing, and implementation of a range of new technologies in the lamb, beef, and pork industries. For measuring lean meat yield %, these technologies included dual energy X-ray absorptiometry, hand-held microwave systems, and 3-D imaging systems. For measuring beef rib-eye traits and intramuscular fat %, both pre- and post-chilling technologies were developed. Post-chilling, a range of camera systems and near infrared spectrophotometers were developed. While pre-chilling, technologies included insertable needle probes, nuclear magnetic resonance, and X-ray systems. Initially these technologies were trained to predict the pre-existing traits already traded upon within industry. However, this approach was limiting because the technologies could measure attributes that were either non-existent in the trading language, were superior as calibrating standards, or more accurately reflected value than the pre-existing trait. Therefore, we introduced IMF% into the trading language for both beef and sheep meat, and carcase lean%, fat%, and bone% for sheep meat. These new technologies and the traits that they predict have delivered multiple benefits. Technology provider-companies are instilled with the confidence to commercialise due to the provision of achievable accreditation standards. Processors have the confidence to invest in these technologies and establish payment grids based upon their measurements. And lastly, it has enhanced data flow into genetic databases, industry data systems (MSA), and as feedback to producers.
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