Sensors for adaptation to the meat industry

Summary

This project details an evaluation of contrast agents for optical enhancement. Optical contrast marker agents are tags that mark a carcase to identify critical features or reference points, which can be analysed using a sensing system either for a “manual assist sensing task” or as an intermediate step in a process task automation where the task or sensing component requires development in situation to be successful.

Objectives

The objective of this project was to evaluate contrast agents for optical enhancement. Examples of agents that were considered take the form of:

• visual food grade dyes and marking inks
• active fluorescence
• alternative markers.

Key findings

• Two sheep and four beef plants were visited and the manual task data investigated and analysed. 
• Issues affecting what sensing is required to automate the task, for example boundary discrimination required, detection of an internal or external feature and application of the technology, was considered to evaluate these categories.
• The key technologies considered to be the most developed and applicable for automating slaughter tasks are optical, laser and mechanical sensing systems and as such are the discussed sensing option on most tasks data sheets.
• Other emerging technologies are also presented in the project report for consideration in future automation applications.

Benefits to industry

Intelligent sensing is critical for obtaining the most favourable measurement of characteristics, such as the spatial relationship of key structural features or the intensity of quality attributes, upon which artificial intelligence can be applied.

Process automation in the unstructured and variable meat processing environment relies heavily on effective sensing and the automation of beef and lamb processing holds an enormous value proposition for the Australian red meat industry.

MLA action

This project has been critical for the subsequent development of automated lamb processing and the current progression of beef automation. The sensing learnings from this project allowed for breakthroughs in automation to occur.

This project was followed with further investments in sensing technology that has today lead to the development of DEXA and the subsequent advancements in processing automation.

Related MLA projects

A.TEC.0110; P.PSH.0619; P.PSH.0635; P.PSH.0238; P.PSH.0479; A.TEC.0062; A.TEC.0058; A.TEC.0051; A.TEC.0047; A.TEC.0042; A.TEC.0041; A.TEC.0124