
%0 Journal Article
%A Wolcott, M. L. 
%A Thompson, J. M. 
%A Perry, D. 
%T The prediction of retail beef yield from real time ultrasound measurements on live animals at three stages through growout and finishing
%J Australian Journal of Experimental Agriculture
%D 2001/10/25
%V 41
%N 7
%P 1005-1011
%K 
%R https://doi.org/10.1071/EA00017
%U https://www.publish.csiro.au/paper/EA00017 
%X Analyses were performed to test the relationship between retail beef yield percentage (RBY) and real time ultrasound measurements taken at weaning, entry to finishing and preslaughter for animals finished under pasture and feedlot conditions to meet domestic, Korean and Japanese market specifications. The first analysis tested the power of live animal measurements (scanned P8 fat depth, scanned eye muscle area and liveweight) to predict RBY and contrasted this with a model containing these live animal measurements plus a term (HERD &#215; KILL ) which accounted for all known classification variables. This indicated that scanned P8 fat depth, measured at slaughter, was the most useful predictor of retail beef yield, accounting for 52% of the variation in RBY for the equation containing live animal measurements alone. The power of live animal measurements to predict RBY decreased as the time between scanning and slaughter increased. Models which included HERD &#215; KILL predicted RBY accurately (accounting for 82&#8211;86% of the variation in RBY), but live animal measurements contributed little to this result, accounting for only 8% of the variation in RBY for measurements at slaughter in the presence of the HERD &#215; KILL term. A second analysis examined whether market category, finishing regime or breed classifications consistently influenced the relationship between the measured traits and RBY at the 3 scanning times. The magnitude of the variation between significantly different coefficients (for scanned P8 fat depth, scanned eye muscle area and liveweight) was generally small, though the results suggested that in some instances, developing separate equations for animals of different classifications would marginally improve the accuracy of RBY prediction. The final analysis investigated the improvement in RBY prediction when measurements from entry to finishing were included with those taken before slaughter. HERD &#215; KILL was included in the model to account for all known classification variables. Measurements of both P8 fat depth and EMA from the earlier measurement time were significant predictors of RBY in the presence of the corresponding measurement at slaughter, but accounted for an increase in R 2 of only 0.0007. It was concluded that a single scan and liveweight measurement, close to slaughter, would provide the best live animal measurements for RBY prediction, and that no improvement in accuracy would be achieved by additional scans taken earlier in an animal&#8217;s life. 
