Back to R&D main

Industry's response to the recommendations of the Beef Language Review White Paper

Project start date: 01 January 2014
Project end date: 01 April 2017
Publication date: 01 April 2017
Project status: Completed
Livestock species: Grassfed cattle, Grainfed cattle
Relevant regions: National
Download Report (0.3 MB)

Summary

To view the Australian Beef Language Review White Paper, click here.
To view industry's response to the recommendations of the Beef Language Review White Paper, click here.

The Australian cattle industry (CCA, ALFA and AMIC) requested that MLA commission a R&D project that provides a white paper to inform industry on how future developments in science and technology and our growing understanding of consumer and customer requirements can shape the Australian beef trading language.

The existing beef language predominantly describes visual appearance or source animal attributes; there is an argument that this may transition toward description of an end result directly reflecting consumer value in addition to traditional physical specification. The end result may be a single comprehensive beef language; a "family" of beef languages used by producers, processors, traders and retailers; or purely standardised data exchange formats.

In summary, the white paper should consider existing and potential new descriptors (objective and subjective) at each stage in the red meat pipeline, covering production, processing, wholesaling, retailing, consumption and future societal and government requirements. It should develop a range of options, test those against a diverse range of trading situations, and then propose a preferred option for industry consideration.

V.MLR.1501 and L.EQT.1613 – CMA: Beef Language White Paper Steering Committee Expenses.

The above Company Managed Activity (CMA) was set up in order to cover all Steering Committee accommodation and travel expenses associated with the Beef Language White Paper Review.

More information

Project manager: Sarah Strachan
Primary researcher: MLA