P.PSH.1369 - Supply chain integration and processor testing of the MIJ-30 beef ribeye grading camera

Summary

The development of precise objective measurement (OM) methods is an industry strategic 2025 imperative to capture more accurate data to explore and support alternative pricing methods for producers. This project evaluated Meat Image Japan (MIJ) OM technologies which are key to the Australian Wagyu Sector through the enablement of accurate grading measures of high marble scores, deriving increased accuracy in value capture. Results from this project will contribute to industry guidelines for the adoption and integration of new OM technologies.

Objectives

The aim of this project was to delivery an early adoption evaluation of the MIJ handheld camera to measure ribeye grading characteristics in beef. This aim was sufficiently met through the achievement of the specific project objectives:
• Evaluation of the integration of the MIJ grading solution into AACo’s workflows and business data management systems, including feedback to producers.
• Evaluation of the device’s grading capabilities across multiple classes of animals and sites.
• Development of a framework and procedures for the integration of new OM technologies including data captured into existing business solutions.
• Development of generic guidelines for adoption and integration of new OM technologies.

Key findings

An initial device was commissioned at the pilot toll processor site and tested to be trial ready. During the testing phase, 2177 images were collected across several processing weeks. Data from the initial testing phase was reviewed and approved by the project steering group and the project progressed to larger scale device trials. Following the establishment of device operating protocols at processing site one, device trials commenced at the second toll processing site. The initial device utilised within this project was the MIJ-30 rib eye cold grading camera and once the MIJ Mobile device was fully developed and validated in the concurrent project [P.PSH.1377], it was deployed for use within this trial.

At the completion of the AUS-MEAT data collection, a total of 10,800 were collected, meeting the project requirements as per the trial plan. Images were collected on F1 (7398) and PB (1672) carcases at toll processor site one, and F1 carcases (n=1630) at toll processor site two. Cold carcase grading data from the MIJ technologies and plant graders were compared, and the correlation and mean marble scores were analysed. Although variable between processing sites and weeks, overall, a high correlation of 0.75 was recorded between MIJ and plant grader marble scores. Differences in mean marble scores were also highly variable, with plant graders ranging from 1.3 marble scores below the MIJ camera to one full marble score above.

At the commencement of the AUS-MEAT data collection, findings from this project were shared internally to company’s processing and marketing teams. It was identified that implementing objective measurement technologies could offer a more reliable method for identifying high marbling carcases (marble score 9+), thereby capturing additional revenue through premium carcases.

Benefits to industry

This project contributes to a series of case studies generated through concurrent early adoption projects of several OM technologies. General learnings from this project will be used to develop generic guidelines for the adoption and integration of new OM technologies. The results from this project provide immediate benefits to the brand owners using the know-how developed within this project and retained by the technology sector.

Future research

Recommendations for future improvements include:
• Better understanding on how to address observed week to week variability between MIJ and AUS-MEAT grading systems.
• Addressing the systematic bias that exists between plants and individual graders.
• Leverage the MLA network to understand how other processors are managing the transition to objective measurement.
• Enhancement of device usability and user feedback mechanisms.
• Develop process for extracting value from carcases with marble score higher than the current maximum of 9 under AUS-MEAT.