Ojo Ayooluwa O, Mulim Henrique A, Campos Gabriel S, Junqueira Vinícius Silva, Lemenager Ronald P, Schoonmaker Jon Patrick, Oliveira Hinayah Rojas
Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.
Department of Animal Biosciences, Interbull Centre, 75007 Uppsala, Uppland, Sweden.
Animals (Basel). 2024 Dec 17;14(24):3633. doi: 10.3390/ani14243633.
Increasing feed efficiency in beef cattle is critical for meeting the growing global demand for beef while managing rising feed costs and environmental impacts. Challenges in recording feed intake and combining genomic and nutritional models hinder improvements in feed efficiency for sustainable beef production. This review examines the progression from traditional data collection methods to modern genetic and nutritional approaches that enhance feed efficiency. We first discuss the technological advancements that allow precise measurement of individual feed intake and efficiency, providing valuable insights for research and industry. The role of genomic selection in identifying and breeding feed-efficient animals is then explored, emphasizing the benefits of combining data from multiple populations to enhance genomic prediction accuracy. Additionally, the paper highlights the importance of nutritional models that could be used synergistically with genomic selection. Together, these tools allow for optimized feed management in diverse production systems. Combining these approaches also provides a roadmap for reducing input costs and promoting a more sustainable beef industry.
提高肉牛的饲料效率对于满足全球对牛肉不断增长的需求、应对饲料成本上升和环境影响至关重要。记录采食量以及结合基因组和营养模型方面的挑战阻碍了可持续牛肉生产中饲料效率的提高。本综述探讨了从传统数据收集方法到提高饲料效率的现代遗传和营养方法的发展历程。我们首先讨论了能够精确测量个体采食量和效率的技术进步，为研究和行业提供了有价值的见解。接着探讨了基因组选择在识别和培育饲料效率高的动物方面的作用，强调了整合多个群体的数据以提高基因组预测准确性的好处。此外，本文还强调了可与基因组选择协同使用的营养模型的重要性。这些工具共同作用，可在不同生产系统中实现优化的饲料管理。结合这些方法还为降低投入成本和促进更可持续的牛肉行业提供了路线图。
