Pearce K L, Ferguson M, Gardner G, Smith N, Greef J, Pethick D W
Division of Veterinary and Biomedical Science, Murdoch University, South Street, Murdoch, WA 6150, Australia; Australian Sheep Industry Cooperative Research Centre, Armidale, NSW 2350, Australia.
Meat Sci. 2009 Jan;81(1):285-93. doi: 10.1016/j.meatsci.2008.08.004. Epub 2008 Aug 15.
Fifty merino wethers (liveweight range from 44 to 81kg, average of 58.6kg) were lot fed for 42d and scanned through a dual X-ray absorptiometry (DXA) as both a live animal and whole carcass (carcass weight range from 15 to 32kg, average of 22.9kg) producing measures of total tissue, lean, fat and bone content. The carcasses were subsequently boned out into saleable cuts and the weights and yield of boned out muscle, fat and bone recorded. The relationship between chemical lean (protein+water) was highly correlated with DXA carcass lean (r(2)=0.90, RSD=0.674kg) and moderately with DXA live lean (r(2)=0.72, RSD=1.05kg). The relationship between the chemical fat was moderately correlated with DXA carcass fat (r(2)=0.86, RSD=0.42kg) and DXA live fat (r(2)=0.70, RSD=0.71kg). DXA carcass and live animal bone was not well correlated with chemical ash (both r(2)=0.38, RSD=0.3). DXA carcass lean was moderately well predicted from DXA live lean with the inclusion of bodyweight in the regression (r(2)=0.82, RSD=0.87kg). DXA carcass fat was well predicted from DXA live fat (r(2)=0.86, RSD=0.54kg). DXA carcass lean and DXA carcass fat with the inclusion of carcass weight in the regression significantly predicted boned out muscle (r(2)=0.97, RSD=0.32kg) and fat weight, respectively (r(2)=0.92, RSD=0.34kg). The use of DXA live lean and DXA live fat with the inclusion of bodyweight to predict boned out muscle (r(2)=0.83, RSD=0.75kg) and fat (r(2)=0.86, RSD=0.46kg) weight, respectively, was moderate. The use of DXA carcass and live lean and fat to predict boned out muscle and fat yield was not correlated as weight. The future for the DXA will exist in the determination of body composition in live animals and carcasses in research experiments but there is potential for the DXA to be used as an online carcass grading system.
选用50只美利奴阉羊（体重范围为44至81千克，平均体重58.6千克）进行42天的圈养，期间通过双能X线吸收法（DXA）对活体动物和整个胴体进行扫描（胴体重量范围为15至32千克，平均重量22.9千克），以测定总组织、瘦肉、脂肪和骨骼含量。随后将胴体剔骨分割成可销售的肉块，并记录剔骨后肌肉、脂肪和骨骼的重量及产出率。化学瘦肉（蛋白质+水）与DXA胴体瘦肉高度相关（r(2)=0.90，剩余标准差=0.674千克），与DXA活体瘦肉中度相关（r(2)=0.72，剩余标准差=1.05千克）。化学脂肪与DXA胴体脂肪中度相关（r(2)=0.86，剩余标准差=0.42千克），与DXA活体脂肪中度相关（r(2)=0.70，剩余标准差=0.71千克）。DXA胴体和活体动物的骨骼与化学灰分相关性不佳（r(2)均为0.38，剩余标准差=0.3）。在回归分析中纳入体重后，可根据DXA活体瘦肉较好地预测DXA胴体瘦肉（r(2)=0.82，剩余标准差=0.87千克）。根据DXA活体脂肪可较好地预测DXA胴体脂肪（r(2)=0.86，剩余标准差=0.54千克）。在回归分析中纳入胴体重量后，DXA胴体瘦肉和DXA胴体脂肪分别能显著预测剔骨后肌肉重量（r(2)=0.97，剩余标准差=0.32千克）和脂肪重量（r(2)=0.92，剩余标准差=0.34千克）。使用DXA活体瘦肉和DXA活体脂肪并纳入体重分别预测剔骨后肌肉重量（r(2)=0.83，剩余标准差=0.75千克）和脂肪重量（r(2)=0.86，剩余标准差=0.46千克）的效果中等。使用DXA胴体及活体的瘦肉和脂肪来预测剔骨后肌肉和脂肪产出率与重量无关。DXA的未来应用在于在研究实验中测定活体动物和胴体的身体组成，但DXA有潜力用作在线胴体分级系统。
