Williams C B, Jenkins T G
USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE 68933, USA.
J Anim Sci. 2003 Jun;81(6):1382-9. doi: 10.2527/2003.8161382x.
Component models were developed to predict the net efficiency of ME utilization for gain in cattle and to predict daily gain using recovered energy as the input. These models were integrated into a single model to predict daily gain from ME available for gain. One component model predicts the net efficiency of ME utilization for gain using constant partial net efficiencies of 0.2 and 0.75 for ME retention as protein and fat, respectively. This model predicts net efficiency of ME utilization for gain as a function of the ratio of the energy recovered in protein to the total energy recovered. The other component model predicts daily gain as a function of recovered energy and is represented by a system of ordinary differential equations that are numerically integrated on a daily basis. This model was developed by reformulating the equations in a published body composition model that uses daily gain to predict composition of gain since recovered energy is a function of gain and composition of gain. The equations in the two component models interact in that net efficiency is used to predict recovered energy from ME for gain, and in turn, recovered energy is used to predict gain in empty BW, which determines net efficiency through composition of gain. The numeric integration procedure provides an iterative solution for net efficiency. Simulated response of net efficiency for Hereford x Angus steers at 400 kg of empty BW decreased from 0.57 to 0.52 on diets with ME densities of 3.1 and 2.6 Mcal/kg of DM, and restricting the lower-quality diet to 75% of ad libitum intake resulted in a simulated net efficiency of 0.47. These responses in net efficiency were shown to be a result of composition of gain, with leaner gains resulting in lower net efficiencies.
构建了成分模型，用于预测牛体增重时代谢能（ME）利用的净效率，并以回收能量作为输入来预测日增重。这些模型被整合为一个单一模型，以根据可用于增重的ME来预测日增重。一个成分模型利用分别为0.2和0.75的恒定部分净效率来预测用于增重的ME保留为蛋白质和脂肪时的净效率。该模型将用于增重的ME利用净效率预测为蛋白质中回收能量与总回收能量之比的函数。另一个成分模型将日增重预测为回收能量的函数，并由一组常微分方程表示，这些方程每天进行数值积分。该模型是通过重新构建一个已发表的身体成分模型中的方程而开发的，该模型使用日增重预测增重组成，因为回收能量是增重和增重组成的函数。两个成分模型中的方程相互作用，即净效率用于预测用于增重的ME回收能量，反过来，回收能量用于预测空腹体重的增加，而空腹体重的增加通过增重组成决定净效率。数值积分程序为净效率提供了一个迭代解。对于体重400千克的赫里福德×安格斯阉牛，在干物质中ME密度为3.1和2.6兆卡/千克的日粮上，模拟的净效率从0.57降至0.52，将低质量日粮限制为自由采食量的75%，模拟的净效率为0.47。这些净效率的变化被证明是增重组成的结果，较瘦的增重导致较低的净效率。
