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P.PSH.1364 - MEQ Sheep Probe early adoption of hot carcase IMF measurement

Red meat traits are graded using manual and primarily visual subjective methods.

Project start date: 25 March 2022
Project end date: 30 September 2023
Publication date: 15 May 2024
Project status: Completed
Livestock species: Sheep, Lamb
Relevant regions: National
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Summary

The purpose of this project is to deliver a system that can deliver individual hot carcase IMF% values to a processor than can be used to support branding and marketing.
The questions being addressed are:
• Is the MEQ system capable of providing this data?
• Can the on-floor systems be integrated with the technology?
• Can carcases be sorted based on IMF% range?
• What can be done with the data to support the creation of a premium brand and market?

This is designed to display to the broader processing industry that lamb IMF% is not only an important attribute to capture but can be collected at high chain speeds on individual hot carcases. The results of this project will be used to justify broader adoption of objective technology and create awareness for premium IMF% brands and markets.

Objectives

The overall objective of the project is to deliver an early adoption and evaluation of the MEQ lamb probe to measure hot lamb carcase marble to improve accuracy and consistency compared to current visual grading methods. This project’s primary objective is to ensure consistent grading results to provide the most accurate supply chain feedback. This will drive producer engagement with brand specifications and improve genetic gain.

The specific objectives of the project were:
• Test and trial integration of developing equipment and integration of software into feedback systems including MSA grading outputs.
• Evaluate the integration of the MEQ lamb probe into Frews’ workflows and business data management systems, including feedback to producers.
• Evaluate device grading capabilities across multiple classes of animals.
• Develop protocols on how to integrate new OM technologies including data captured into existing business systems.
• Develop generic guidelines for adoption and integration of new OM technologies.

Key findings

The MEQ solution commissioned, including the supporting software, on plant at the pilot site (Frewstal, Stawell) and was validated to be trial ready. The critical design components were identified and included in the MEQ solution were:

• carcase identification linking capability
• MEQ technical support and training of Frew Foods operators
• IT capability
• resourcing and dedicated Frew Foods operators
• dedicated operators required preferably several trained dedicated operators that cycle across shifts (i.e. 2h at a time).

The Probe is now in use commercially across all Frews lambs in order to collect a data set that represents the quality of the population for brand creation and marketing. The grading terminal successfully displays the MEQ IMF% value on the screen as the carcase is graded, which then allows for carcase sortation as the body enters the chillers.

While an initial MSA review and preliminary analysis of Frews' MEQ data was conducted by MSA, further validation of Frews'lamb data is required in order to understand the value proposition of sheepmeats cut model to the business.

Benefits to industry

With Frews developing accurate IMF measurement capability of individual carcases, this will position them to be early adopters also of the cuts-based MSA sheepmeat model, yield LMY% using DEXA and animal health disease reporting, thereby providing feedback to their livestock suppliers. The potential solution will integrate an optimise plant data business management system couple with RFID hook tracking capability from legging through to the boning room. Adopting technology like this will provide greater consistency to brand owners which encourages greater investment as they know it will be rewarded in optimal product categorisation.

There have been significant benefits to the industry displayed in this project. These include but are not limited to:
• successful integration with on-site software that displays an ability to be used widely
• display of an ability to capture a high population of individual hot carcase IMF% at a high chain speed
• proven capability of rolling out large scale user training and maintenance of the MEQ system.

MLA action

Based on the results of the project, it is recommended that future research and development focuses on how to support processing businesses build an awareness in the market for how to promote high quality lamb and how different IMF% level impact consumer experience.

Future research

Based on the results of the project, it is recommended that future research and development focuses on how to support processing businesses build an awareness in the market for how to promote high quality lamb and how different IMF% level impact consumer experience. Once the value proposition has been built out for processors, it becomes much easier to introduce quality grading to the industry as a whole. Further validation of Frews lamb data is required in order to understand the value proposition of sheepmeats cut model to the business.

More information

Project manager: Dean Gutzke
Contact email: reports@mla.com.au
Primary researcher: Frews