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识别群体饲养牛之间饲料效率的差异。

Identifying differences in feed efficiency among group-fed cattle.

作者信息

Tedeschi L O, Fox D G, Baker M J, Kirschten D P

机构信息

Department of Animal Science, Texas A&M University, College Station, 77843, USA.

出版信息

J Anim Sci. 2006 Mar;84(3):767-76. doi: 10.2527/2006.843767x.

Abstract

Identification of efficient animals in the postweaning growth phase for use in selection for improved feed efficiency is important to improve the economic and environmental sustainability of the beef cattle industry. Progeny testing using group-fed animals in commercial feedlots is the most common and practical method used to evaluate postweaning growth on large numbers of animals. We developed the Cornell Value Discovery System (CVDS) to dynamically predict growth rate, accumulated weight, days required to reach target body composition, carcass weight, and composition of individual beef cattle fed in group pens. Observed BW, ADG, BW at 28% empty body fat (EBF), breed type, environmental conditions, and dietary ME concentration are used by the CVDS to predict, for each animal in a pen, the feed DM required for maintenance (FFM), the feed DM required for gain, and the total DM required for maintenance and gain (DMR). The CVDS then computes DMR-to-ADG ratio (DMR:ADG), which is a feed conversion measure, and ADG-to-DMR ratio (ADG:DMR), which is a feed efficiency measure, for each animal. This study used the observed F:G ratio of 362 individually fed steers to evaluate CVDS-predicted indicators of feed efficiency and the Kleiber ratio. A subset of 37 data points was used to evaluate residual feed intake (RFI) as an indicator of feed efficiency. The database included 4 published studies, each with detailed individual animal description, environment, diet, and body composition information. The CVDS-predicted DMR:ADG accounted for 84% of the variation in the actual F:G ratio with a mean bias of 1.94% (P = 0.20). The predicted FFM to actual DMI ratio had a high correlation with actual ADG (R2 = 0.76), and indicated a decay-type nonlinear dilution of FFM as ADG increased. The CVDS-predicted ADG:DMR and the Kleiber ratio had a significant (R2 = 0.88) logarithmic relationship. In an analysis of a contemporary group within the database, RFI was highly correlated with the F:G ratio (r = 0.71). There was a positive relationship between RFI and EBF. The RFIM (DMI - DMR) was moderately correlated with DMI and ADG (0.37 and -0.38; respectively), suggesting that selecting for low RFI(M) would decrease DMI and increase ADG in this database. We conclude that the CVDS model can be used to identify differences in the F:G and G:F ratios by predicting DMR for individual growing cattle fed in groups.

摘要

识别断奶后生长阶段高效的动物以用于选择提高饲料效率,对于提高肉牛产业的经济和环境可持续性非常重要。在商业饲养场中对群体饲养的动物进行后代测试,是评估大量动物断奶后生长情况最常用且实用的方法。我们开发了康奈尔价值发现系统(CVDS),以动态预测群体饲养栏中个体肉牛的生长速率、累积体重、达到目标体组成所需天数、胴体重以及体组成。CVDS利用观察到的体重(BW)、平均日增重(ADG)、28%空体脂肪(EBF)时的体重、品种类型、环境条件和日粮代谢能(ME)浓度,来预测栏中每头动物维持所需的饲料干物质(FFM)、增重所需的饲料干物质以及维持和增重所需的总干物质(DMR)。然后,CVDS计算每头动物的DMR与ADG之比(DMR:ADG),这是一种饲料转化率指标,以及ADG与DMR之比(ADG:DMR),这是一种饲料效率指标。本研究利用362头个体饲养阉牛观察到的料肉比,来评估CVDS预测的饲料效率指标和克莱伯比率。37个数据点的子集用于评估剩余采食量(RFI)作为饲料效率指标。该数据库包括4项已发表的研究,每项研究都有详细的个体动物描述、环境、日粮和体组成信息。CVDS预测的DMR:ADG占实际料肉比变异的84%,平均偏差为1.94%(P = 0.20)。预测的FFM与实际干物质采食量(DMI)之比与实际ADG高度相关(R2 = 0.76),并表明随着ADG增加,FFM呈衰减型非线性稀释。CVDS预测的ADG:DMR与克莱伯比率具有显著的对数关系(R2 = 0.88)。在对数据库中一个当代组的分析中,RFI与料肉比高度相关(r = 0.71)。RFI与EBF之间存在正相关关系。剩余采食量修正值(RFIM,即DMI - DMR)与DMI和ADG中度相关(分别为0.37和 -0.38),这表明在该数据库中选择低RFIM会降低DMI并增加ADG。我们得出结论,CVDS模型可用于通过预测群体饲养的生长中个体牛的DMR来识别料肉比和肉料比的差异。

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