Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland.
J Anim Sci. 2013 Apr;91(4):1594-613. doi: 10.2527/jas.2012-5862. Epub 2013 Jan 23.
Increasing food production for the growing human population off a constraining land base will require greater efficiency of production. Genetic improvement of feed efficiency in cattle, which is cumulative and permanent, is one likely vehicle to achieving efficiency gains. The objective of this review is to summarize genetic parameters for feed efficiency traits in dairy and beef cattle and also to address some of the misconceptions associated with feed efficiency in these sectors, as well as discuss the potential use of feed efficiency in breeding programs. A meta-analysis of up to 39 scientific publications in growing cattle clearly showed that genetic variation in feed efficiency exists with a pooled heritability for residual feed intake (RFI) and feed conversion efficiency of 0.33 ± 0.01 (range of 0.07 to 0.62) and 0.23 ± 0.01 (range of 0.06 to 0.46), respectively. Heritability estimates for feed efficiency in cows were lower; a meta-analysis of up to 11 estimates revealed heritability estimates for gross feed efficiency and RFI of 0.06 ± 0.010 and 0.04 ± 0.008, respectively. Meta-analysis of genetic correlations between feed intake, feed efficiency and other performance traits are presented, and selection index theory is used to calculate the proportion of genetic variation in feed intake that can be explained by easy to measure, and often already collected, data. A large proportion of the genetic variation in feed intake could be explained in both growing animals and lactating animals using up to 5 predictor traits, including BW, growth rate, milk yield, body composition, and linear type traits reflecting body size and muscularity. Knowledge of genetic merit for feed intake can be used, along with estimates of genetic merit for energy sinks, to calculate genetic merit for feed efficiency. Therefore, the marginal benefit of collecting actual feed intake data, using the genetic parameters used in this study, appears to be low. There is now sufficient information available to develop a road map on how best to direct research to ensure long-term food security for a growing human population. Gaps in knowledge are identified here, and possibilities to address these gaps are discussed.
在有限的土地基础上为不断增长的人口增加粮食产量，需要提高生产效率。提高牛饲料效率的遗传改良是实现效率提高的一种可能途径，因为这种改良是累积的和永久的。本综述的目的是总结奶牛和肉牛饲料效率性状的遗传参数，并解决与这些领域饲料效率相关的一些误解，以及讨论饲料效率在育种计划中的潜在应用。对 39 篇关于生长牛的科学出版物的荟萃分析清楚地表明，饲料效率存在遗传变异，其残留饲料摄入量（RFI）和饲料转化率的综合遗传力分别为 0.33 ± 0.01（范围为 0.07 至 0.62）和 0.23 ± 0.01（范围为 0.06 至 0.46）。奶牛饲料效率的遗传力估计值较低；对多达 11 项估计值的荟萃分析表明，总饲料效率和 RFI 的遗传力估计值分别为 0.06 ± 0.010 和 0.04 ± 0.008。还介绍了饲料摄入量、饲料效率和其他性能性状之间的遗传相关性的荟萃分析，并使用选择指数理论计算了可以通过易于测量且通常已经收集的信息来解释的饲料摄入量遗传变异的比例。在生长动物和泌乳动物中，使用多达 5 个预测性状，包括体重、生长速度、产奶量、体成分和反映体型和肌肉发达程度的线性体型性状，可以解释饲料摄入量的大部分遗传变异。利用饲料摄入量的遗传优势估计值和对能量消耗的遗传优势估计值，可以计算饲料效率的遗传优势。因此，收集实际饲料摄入量数据的边际效益，使用本研究中使用的遗传参数，似乎很低。现在已经有足够的信息来制定路线图，以最好地指导研究，确保不断增长的人口的长期粮食安全。本文还确定了知识空白，并讨论了解决这些空白的可能性。
