Investigating the viability of using MEXA for objective measurement of IMF and WBSF in Australian new and old seasons lambs

Summary

There is a strong call from lamb producers to transition the Meat Standards Australia (MSA) grading system from mob-based to an individual carcase grading system, as is well-established for beef.

Through extensive research and consumer testing, intramuscular fat percentage and shear force have been identified as key drivers of eating quality in lamb.

Multi-energy X-ray Absorptiometry (MEXA) technology that can measure these two traits at abattoir chain speed would enable the roll-out of an individual carcase MSA grading system for lamb.

Objectives

The main objective of this project was to conduct an initial evaluation of the potential for MEXA to measure shear force and intramuscular fat percentage in the lamb loin to inform further investment.

Key findings

• The results of this project highlighted the potential for MEXA to differentiate tissue components and predict the percentage of intramuscular fat and shear force of lamb meat with precision and accuracy.
• The consistency of the predictions for the scanned carcase samples provide a level of confidence that the predictions for the eating quality of lamb are repeatable and therefore applicable to the industry.
• Further data are required to validate the precision and accuracy of prediction models developed in this project.

Benefits to industry

The outcomes of this project indicate the potential of MEXA to measure key traits required for industry to implement cuts-based MSA grading of lamb carcases.

MLA action

Further research and development into MEXA technology has been initiated under the Advanced Livestock Measurement Technologies programme.

MLA has also engaged a commercial partner for collaboration on two variations of MEXA that warrant further investigation.

Future research

In future work, it is recommended to calibrate MEXA across a larger dataset consisting of more diverse animals, across varying environmental conditions, across different time periods (hours/days/weeks), and across different MEXA devices.