Accreditation of in-abattoir Dual Energy X-ray Absorptiometry scanning apparatus to predict lamb carcass composition in Australia

Abstract

Dual Energy X-ray Absorptiometry (DXA) scanners operating at abattoir processing speeds are currently installed in six sheep meat abattoirs around Australia, predicting carcass composition as estimates of computed tomography (CT) determined fat %, lean %, and bone %. This study tested an updated bone-detection algorithm for these DXA scanners. This algorithm improved the precision of prediction for carcass fat% and lean%, but most notably for bone % (R2 = 0.92, RMSE = 0.61 %), compared to the previous algorithm (R2 = 0.51, RMSE = 1.57 %). This was due to improved allocation of bone-containing pixels, resulting from the inclusion of tissue thickness in the bone-detection equation. In a second experiment, the predictions from this new algorithm, along with an automated phantom calibration technique, were assessed relative to their ability to meet the AUS-MEAT accreditation accuracy standards required for predicting CT determined carcass fat%, lean%, and bone%. The DXA met these standards for predicting fat % (range 10.9 % - 37.1 %), lean % (range 49.0 % - 66.2 %), and bone % (range 11.6 % - 25.0 %), across three weight bands of light carcasses (<22 kg), mid-weight carcasses (22-28 kg), and heavy carcasses (>28 kg). This work allowed for the accreditation of DXA, enabling its predictions of carcass composition to be used for trading sheep carcasses in Australia. The accuracy of these predictions far exceed those provided by the historical industry measure of GR tissue depth, and hot carcass weight.