Executive Summary An Automated Beef Rib Cutting system has been developed by Scott Automation Robotics (SCOTT)which is currently in production in an Australian beef abattoir.The system utilises a dual-energy x-ray(DEXA)system in order to identify cut placement for that carcase.This system consists of separate source-detector pairs for each of the low-energy and high- energy x-ray images.These two images are then stitched together into one DEXA image. There is a need in the red meat industry to move towards methods of measuring carcase attributes in an objective manner.DEXA is one technological enabler for such measurement.Utilising DEXA technology for both automation and OCM concurrently,in one integrated system,presents a number of benefits,particularly surrounding the cost-benefit of such a system. This project thus aimed to evaluate the feasibility in utilising a system which has been designed and built for beef automation for OCM tasks as well.It will also explore the hardware requirements and commercial considerations for designing such systems in the future as well as the suitability of dual-hardware DEXA systems for the application. The first task was to get an initial assessment of whether the hardware was capable of producing consistent values for OCM measurements.This was achieved by scanning a tissue phantom-an object consisting of homogenous blocks of lean and fat,at varying compositions,which have been tested for chemical lean.The scans were completed successfully and analysis suggested the system was capable of producing consistent enough x-ray values to enable OCM calculation. Six beef sides were then selected and scanned with the system.These sides were then cut up and scanned with a CT scanner.The CT data was then used to predict the amount of fat, lean and bone in each of the sides.The DEXA images were analysed to see if the information could be modelled to predict CT composition.A number of challenges were experienced however which prevented an accurate model to be generated.One factor contributing to this was an effect along the height of the detector.The detectors in the system are 2500mm long and thus have significantly different x-ray flux along their lengths Compensating for this improved results significantly.Another effect found was that thin tissue information(approximately 10mm and less)was saturated in the low energy image. In the work completed in lamb,these tissue depths are known to contribute significantly to the OCM models.The loss of such information thus impacted the results negatively. Another set of trials was then conducted whereby scans were taken at production currents as well as a current low enough to avoid saturation of the detectors.Phantom scans were first performed which vindicated the positive effect of running at these lower currents-the information in the thinnest phantom were now visible and demonstrating consistent results. Another eight sides were then DEXA scanned,CT scanned and analysed. The results of the analysis on the additional eight sides yielded better results,particularly for predicting bone content.Fat and lean content however were unable to be modelled with a significant level of accuracy.R2 values of 0.4,0.45 and 0.82 achieved for lean,fat and bone,respectively.A number of possible limitations have been identified which may explain why this system is not able to achieve accurate OCM.It is suspected that the alignment Page 3 of 44Page 3 of 44 Executive Summary An Automated Beef Rib Cutting system has been developed by Scott Automation & Robotics (SCOTT) which is currently in production in an Australian beef abattoir. The system utilises a dual-energy x-ray (DEXA) system in order to identify cut placement for that carcase. This system consists of separate source-detector pairs for each of the low-energy and high￾energy x-ray images. These two images are then stitched together into one DEXA image. There is a need in the red meat industry to move towards methods of measuring carcase attributes in an objective manner. DEXA is one technological enabler for such measurement. Utilising DEXA technology for both automation and OCM concurrently, in one integrated system, presents a number of benefits, particularly surrounding the cost-benefit of such a system. This project thus aimed to evaluate the feasibility in utilising a system which has been designed and built for beef automation for OCM tasks as well. It will also explore the hardware requirements and commercial considerations for designing such systems in the future as well as the suitability of dual-hardware DEXA systems for the application. The first task was to get an initial assessment of whether the hardware was capable of producing consistent values for OCM measurements. This was achieved by scanning a tissue phantom – an object consisting of homogenous blocks of lean and fat, at varying compositions, which have been tested for chemical lean. The scans were completed successfully and analysis suggested the system was capable of producing consistent enough x-ray values to enable OCM calculation. Six beef sides were then selected and scanned with the system. These sides were then cut up and scanned with a CT scanner. The CT data was then used to predict the amount of fat, lean and bone in each of the sides. The DEXA images were analysed to see if the information could be modelled to predict CT composition. A number of challenges were experienced however which prevented an accurate model to be generated. One factor contributing to this was an effect along the height of the detector. The detectors in the system are 2500mm long and thus have significantly different x-ray flux along their lengths. Compensating for this improved results significantly. Another effect found was that thin tissue information (approximately 10mm and less) was saturated in the low energy image. In the work completed in lamb, these tissue depths are known to contribute significantly to the OCM models. The loss of such information thus impacted the results negatively. Another set of trials was then conducted whereby scans were taken at production currents as well as a current low enough to avoid saturation of the detectors. Phantom scans were first performed which vindicated the positive effect of running at these lower currents – the information in the thinnest phantom were now visible and demonstrating consistent results. Another eight sides were then DEXA scanned, CT scanned and analysed. The results of the analysis on the additional eight sides yielded better results, particularly for predicting bone content. Fat and lean content however were unable to be modelled with a significant level of accuracy. R 2 values of 0.4, 0.45 and 0.82 achieved for lean, fat and bone, respectively. A number of possible limitations have been identified which may explain why this system is not able to achieve accurate OCM. It is suspected that the alignment