Guiroy P J, Fox D G, Tedeschi L O, Baker M J, Cravey M D
Department of Animal Science, Cornell University, Ithaca, NY 14853, USA.
J Anim Sci. 2001 Aug;79(8):1983-95. doi: 10.2527/2001.7981983x.
A published model designed to predict individual feed required for the observed shrunk BW and ADG of growing cattle when fed in groups was modified and evaluated to improve its accuracy. This model is needed to accurately bill feed and compute cost of gain in marketing programs based on individual animal management. Because of its importance in predicting energy required for growth, a database of 401 steers was used to develop an equation to predict percentage of empty-body fat (EBF) from carcass measurements (12th rib fat thickness, hot carcass weight, USDA quality grade, and longissimus muscle area), which accounted for 61% of the variation in EBF with no bias (P > 0.1). When tested with an independent data set of 951 steers, the equation accounted for 51% of the variation with 1% proportional bias. The large variation in the carcass measurements at a particular EBF observed in this study indicates further improvement is limited by the inability of carcass measurements to account for variation in fat distribution in the various carcass components. Because of its importance in setting the target end point, a database of 1,355 steers and heifers was used to determine the relationship between EBF and USDA quality grade. These data indicate growing and finishing cattle reach Select and low-Choice quality grades at an EBF of 26.15 +/- 0.19 and 28.61 +/- 0.20%, respectively (P < 0.05). A data set of 228 steers from different breeds from two serial slaughter studies indicated 14.26 +/- 1.52 kg of empty BW change are required to increase EBF one percentage unit for cattle fed high-energy diets; this adjustment is needed to adjust final shrunk BW to the target EBF end point. The model to predict DM required with modifications developed in this study was evaluated with data from 365 individually fed cattle and it accounted for 74% of the variation in observed DM consumed with no bias (P > 0.1). When the revised model was applied to a commercial feedlot data set containing 12,105 steers and heifers, the total observed DM consumed was predicted with a bias of less than 1%. The model presented in this study accounts for differences known to affect animal requirements (breed type, BW and ADG, and weight at the target EBF end point) and can be used to fairly allocate feed to individuals fed in a group under commercial feedlot conditions.
一个已发表的模型旨在预测育肥牛群养时达到观察到的体重缩减和平均日增重所需的个体采食量，对其进行了修改和评估以提高准确性。在基于个体动物管理的营销计划中，需要此模型来准确计费饲料并计算增重成本。由于其在预测生长所需能量方面的重要性，使用了一个包含401头阉牛的数据库来建立一个方程，根据胴体测量值（第12肋骨处脂肪厚度、热胴体重、美国农业部质量等级和背最长肌面积）预测空体脂肪（EBF）百分比，该方程解释了EBF中61%的变异且无偏差（P>0.1）。用一个由951头阉牛组成的独立数据集进行测试时，该方程解释了51%的变异，比例偏差为1%。本研究中在特定EBF下观察到的胴体测量值存在较大变异，这表明进一步的改进受到胴体测量值无法解释不同胴体部位脂肪分布变异的限制。由于其在设定目标终点方面的重要性，使用了一个包含1355头阉牛和小母牛的数据库来确定EBF与美国农业部质量等级之间的关系。这些数据表明，生长育肥牛和育肥牛分别在EBF为26.15±0.19%和28.61±0.20%时达到选择级和低精选级质量等级（P<0.05）。来自两项连续屠宰研究的228头不同品种阉牛的数据集表明，对于高能日粮饲养的牛，将EBF提高一个百分点需要空体重变化14.26±1.52千克；需要进行此调整以将最终体重缩减调整到目标EBF终点。用本研究中开发的经过修改的预测所需干物质的模型，对365头个体饲养牛的数据进行评估，该模型解释了观察到的干物质采食量中74%的变异且无偏差（P>0.1）。当将修订后的模型应用于一个包含12105头阉牛和小母牛的商业饲养场数据集时，预测的总观察干物质采食量偏差小于1%。本研究中提出的模型考虑了已知会影响动物需求的差异（品种类型、体重和平均日增重以及目标EBF终点时的体重），可用于在商业饲养场条件下公平地为群养个体分配饲料。
