
%0 Journal Article
%A Johnson, ER 
%T The use of non-carcass parts in the prediction of beef carcass composition on the slaughter floor
%J Australian Journal of Agricultural Research
%D 1979/08/01
%V 30
%N 4
%P 751-765
%K 
%R https://doi.org/10.1071/AR9790751
%U https://www.publish.csiro.au/paper/AR9790751 
%X Ninety-five steers were used to develop a method of estimating the weights or percentages of the four carcass tissues&mdash;muscle, bone, fat and connective tissue&mdash;while the carcasses were still on the slaughter floor. From an investigation of a number of non-carcass parts it was found that three measurements could be used to estimate all four carcass components. The measurements were (a) short-cut tongue weight; (b) foreshanks weight; (c) hot side weight. Simple and multiple regression equations were developed to estimate the weights of muscle, bone and connective tissue in the chilled side, and the accuracy of the estimates was compared with that of recorded prediction methods. The most useful equations employed short-cut tongue weight and hot side weight to estimate total side muscle weight, and foreshanks weight to estimate both total side bone weight and total side connective tissue weight. Fat weight was estimated from hot side weight and the estimates of the weights of the other three carcass components. This technique was more accurate than the Australian Beef Carcase Appraisal System and Butterfield's equation, both of which use fat thickness measurement at the 10th rib. When fat thickness measurement was included in regression equations, the estimates of muscle weight and fat weight were slightly improved. Advantages of using the 'non-carcass parts' technique are as follows. All four major carcass components are predicted; the carcass components can be recorded as absolute weights or percentages of chilled side weight; chilled side components are predicted whilst the hot side is still on the slaughter floor; no commercial loss occurs in carcass, offals or by-products; all measurements used in prediction are weights; and fat thickness measurements may be included in the prediction. The additional information enables producers to make a more critical assessment of the nutritive performance and genetic progress of their herds. 
