The 5-6th rib cross section of beef carcasses was analyzed by an image analyzer. The measurements obtained for the prediction of carcass composition were the areas of total, lean, fat and bone in cm
2; the ratio of the total area to lean, fat, bone, subcutaneous fat, M. longissimus and M. trapezius in % ; the area (cm
2), circular length (cm), long axis length (cm) and short axis length (cm) for both the M. longissimus and M. trapezius; and the distance between the center of gravity of M. longissimus and that of M. trapezius. A stepwise regression analysis was used to choose the best regression equation to predict carcass composition as total kilograms and percentages of lean, fat and bone. The most important variable found to predict the percentage of lean was total area or fat area (cm
2), while that to predict the percentages of fat or bone was fat area percentage. Coefficents of determination adjusted for the degrees of freedom (R
2) from the regression equations for the percentages of lean, fat and bone were 0.727, 0.864 and 0.905, respectively. The most important variable to predict total kilograms of lean, fat and bone was total area (cm
2). In predicting total kilograms of fat and bone, the distance between the centers of muscles was an important independent variable. The R
2 were as high as 0.9.
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