Changing Australia's trading language has enhanced the implementation of objective carcase measurement technologies.
Accreditation standards
Carcase grading
Computed tomography
Intramuscular fat %
Lean meat yield %
Journal
Meat science
ISSN: 1873-4138
Titre abrégé: Meat Sci
Pays: England
ID NLM: 101160862
Informations de publication
Date de publication:
10 Aug 2024
10 Aug 2024
Historique:
received:
02
05
2024
revised:
04
08
2024
accepted:
05
08
2024
medline:
26
8
2024
pubmed:
26
8
2024
entrez:
24
8
2024
Statut:
aheadofprint
Résumé
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.
Identifiants
pubmed: 39181808
pii: S0309-1740(24)00202-X
doi: 10.1016/j.meatsci.2024.109625
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
109625Informations de copyright
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest None.