The objective of this project is to Increase the rate of improvement in lean meat yield as specified in the Commonwealth Agreement.
This project has a number of quantifiable targets that will demonstrate outcomes;
1) Adoption of new methods to predict lean meat yield (LMY) in up to 4 abattoirs;
2) Development of processor specific supply chains with a focus on LMY,
3) Economic analysis on increasing LMY through specified abattoirs.
Without this project the quality science delivered through the 'Range of new meat phenotypes' and 'Biology & Production Pathways' projects will have much less impact. If producers are not rewarded for adopting changes at the farm level in terms of the types of lambs produced then the improved selection methods will have a diminished adoption within the industry. This project provides the means for a pull through incentive that can drive change throughout the supply chain.
The global aim of the meat program is to increase the rate of improvement in lean meat yield as specified in the Commonwealth Agreement. The supply chain component of this program will endeavour to help achieve this by:
business case targeted at processors/retailers.
Lean meat yield algorithms will be generated at 4 processing plants around Australia, in the first two years starting with one in WA (see project 3.8.2) and one in NSW. The first processors (Hillside Meats and Jacksons) will use indicator cuts tracked through the kill floor to the boning room using RFID technology. This will involve bone-outs at participating plants to generate yield algorithms that match their market trimming specifications. Carcases from a subset of these animals will be CAT scanned and then boned out to the same specifications as employed at each plant. This data will be used to correlate all prediction algorithms generated across
Australia. There will be continued CAT scanning of established yield algorithms at participating plants to ensure robustness of prediction across the genetic extremes of the sheep population. These data sets will also help to underpin the models used for yield prediction within the information nucleus slaughters.
WA Meat Marketing Cooperative (WAMMCO) has generated a considerable data-base of VIAscan predictions on lean meat yield. Data for the last two years has been requested. Analyses of this data will be carried out both to establish current ranges of carcase yields across the population generally, and also within given carcase weight and fatness grids. Further analysis will be undertaken to assess the impact of other known factors on lean meat yield such as production region, seasonality effects, feedlot or pasture fed etc. This will require the establishment of Intellectual Property agreements with the cooperating plants to direct what information will be made publicly available versus that which will be retained by the processor. In an attempt to provide a range of different technologies that can improve yield prediction, the
suitability of ultrasound measurement of fat depth for lamb carcases will be assessed. A readymade ultrasound system which was purpose built for the pig industry will be utilised, and a report prepared once complete. Ultrasound measurements will be taken on a number of carcase sites on all lambs slaughtered within one kill group of the Information Nucleus Flock in WA. These animals will also be fully boned out thus lean meat yield will be determined on each carcase. The various combinations of the ultrasound measurements will then be tested as predictors of yield. This process will be repeated in NSW using a flock slaughtered at Jackson’s (Tamworth) and boned out at UNE. Additionally, 300 animals of unknown origin and randomly selected will have their GR tissue depth measured manually, and using the ultrasound methods
to enable direct comparison of ultrasound prediction of GR.
A new 2D X-ray system was installed at CRF abattoir in September 08. Images will be obtained from this system and analysed to determine whether lean meat yield predictive algorithms can be derived. Assuming the success of this process, attempts will then be made to develop an on-line yield measurement system underpinned by this predictive algorithm for use within the plant. Finally an economic analysis of yield prediction will be undertaken using an Industry consultant (Phil Green) in collaboration with MLA, and business models generated which incorporate an understanding of lean meat yield in the context of the various processor business models that comprise the Australian meat processing industry. Plant visits will be undertaken and economic analyses carried out at each of these.
This five pronged approach, initially undertaken with the processing sectors “early adopters”, will then provide a flow of information and a knowledge back which will help to create our “case” for yield prediction during our subsequent approach to the next tier of processors within the meat industry in the later years of the CRC.
The work program mainly focuses on adoption of research from other projects within the meat program and will use the expertise of the state agencies to liaise and build upon their relationships with key processors. In year 1 this will mean assisting Program 6 with processor meetings where by the fundamental features of their business will be understood in relation to lean meat yield and used to build the case for lean meat yield. At the same time the project will canvas processors regarding their willingness to undertake co-investment with the CRC in establishing supply chain officers and/or master’s positions. The positions would have a focus on lean meat yield and be used to facilitate adoption up and down stream of the processors; although up stream work with producers would clearly be a key target.