McPhee M J, Oltjen J W, Fadel J G, Perry D, Sainz R D
Department of Animal Science, University of California, Davis 95616, USA.
J Anim Sci. 2008 Aug;86(8):1984-95. doi: 10.2527/jas.2008-0840. Epub 2008 Mar 28.
The Davis growth model (DGM) simulates growth and body composition of beef cattle and predicts development of 4 fat depots. Model development and evaluation require quantitative data on fat weights, but sometimes it is necessary to use carcass data that are more commonly reported. Regression equations were developed based on published data to interconvert between carcass characteristics and kilograms of fat in various depots and to predict the initial conditions for the DGM. Equations include those evaluating the relationship between the following: subcutaneous fat (SUB, kg) and 12th-rib fat thickness (mm); visceral fat (VIS, kg) and KPH (kg); DNA (g) in intermuscular, intramuscular, subcutaneous, and visceral fat depots and empty body weight; and contributions of fat (kg) in intramuscular (INTRA), SUB, and VIS fat depots and total body fat (kg). The intermuscular fat (INTER, kg) contribution was found by difference. The linear regression equations were as follows: SUB vs. 12th-rib fat thickness (n = 75; P < 0.01) with R(2) = 0.88 and SE = 10.00; VIS vs. KPH (kg; n = 78; P < 0.01) with R(2) = 0.95 and SE = 2.82; the DNA (g) equations for INTER, INTRA, SUB, and VIS fat depots vs. empty body weight (n = 6, 5, 6, and 6; P = 0.08, P < 0.01, P < 0.01, and P = 0.05) with R(2) = 0.57, 0.93, 0.93, and 0.66, and SE = 0.03, 0.003, 0.02, and 0.03, respectively; and initial contribution of INTRA, SUB, and VIS fat depots vs. total body fat (n = 23; P < 0.01) for each depot, with R(2) = 0.97, 0.99, and 0.97, and SE = 0.61, 0.93, and 1.41, respectively. All empirical equations except for DNA were challenged with independent data sets (n = 12 and 10 for SUB and VIS equations and n = 9 for the initial INTER, INTRA, SUB, and VIS fat depots). The mean biases were -2.21 (P = 0.12) and 2.11 (P < 0.01) kg for the SUB and VIS equations, respectively, and 0.05 (P = 0.97), -0.37 (P = 0.27), 1.82 (P = 0.08), and -1.50 (P = 0.06) kg for the initial contributions of INTER, INTRA, SUB, and VIS fat depots, respectively. The random components of the mean square error of prediction were 73 and 26% for the SUB and VIS equations, respectively, and similarly were 99, 85, 62, and 61% for the initial contributions of INTER, INTRA, SUB, and VIS fat depots, respectively. Both the SUB and VIS equations predicted accurately within the bounds of experimental error. The equations to predict initial fat contribution (kg) were considered adequate for initializing the fat depot differential equations for the DGM and other beef cattle simulation models.
戴维斯生长模型(DGM)可模拟肉牛的生长和体成分,并预测4个脂肪沉积部位的发育情况。模型的开发和评估需要脂肪重量的定量数据,但有时有必要使用更常报告的胴体数据。基于已发表的数据建立了回归方程,用于在胴体特征与各部位脂肪千克数之间进行相互转换,并预测DGM的初始条件。这些方程包括评估以下各项之间关系的方程:皮下脂肪(SUB,千克)与第12肋骨处脂肪厚度(毫米);内脏脂肪(VIS,千克)与肾周脂肪(KPH,千克);肌间、肌内、皮下和内脏脂肪沉积部位的DNA(克)与空体重;以及肌内(INTRA)、SUB和VIS脂肪沉积部位的脂肪(千克)贡献与全身脂肪(千克)。肌间脂肪(INTER,千克)的贡献通过差值计算得出。线性回归方程如下:SUB与第12肋骨处脂肪厚度的关系(n = 75;P < 0.01),R² = 0.88,标准误(SE) = 10.00;VIS与KPH(千克)的关系(n = 78;P < 0.01),R² = 0.95,SE = 2.82;肌间、肌内、皮下和内脏脂肪沉积部位的DNA(克)与空体重的方程(n分别为6、5、6和6;P = 0.08、P < 0.01、P < 0.01和P = 0.05),R²分别为0.57、0.93、0.93和0.66,SE分别为0.03、0.003、0.02和0.03;以及INTRA、SUB和VIS脂肪沉积部位对全身脂肪的初始贡献(n = 23;P < 0.01),每个部位的R²分别为0.97、0.99和0.97,SE分别为0.61、0.93和1.41。除DNA方程外,所有经验方程均用独立数据集进行了验证(SUB和VIS方程的n分别为12和10,肌间、肌内、皮下和内脏脂肪沉积部位初始贡献的n为9)。SUB和VIS方程的平均偏差分别为 -2.21(P = 0.12)千克和2.11(P < 0.01)千克,肌间、肌内、皮下和内脏脂肪沉积部位初始贡献的平均偏差分别为0.05(P = 0.97)千克、 -0.37(P = 0.27)千克、1.82(P = 0.08)千克和 -1.50(P = 0.06)千克。SUB和VIS方程预测的均方误差的随机成分分别为73%和26%,肌间、肌内、皮下和内脏脂肪沉积部位初始贡献的均方误差的随机成分分别为99%、85%、62%和61%。SUB和VIS方程在实验误差范围内预测准确。预测初始脂肪贡献(千克)的方程被认为足以初始化DGM和其他肉牛模拟模型的脂肪沉积部位微分方程。