Garrick D J, Golden B L
Iowa State University, Ames, Iowa 50011, USA.
J Anim Sci. 2009 Apr;87(14 Suppl):E11-8. doi: 10.2527/jas.2008-1431. Epub 2008 Oct 10.
The overall motivation for the development of an information system for beef cattle improvement is the belief that knowledge of breeding values and heterosis effects allows one to determine the consequences of alternative selection and mating options. With this information, livestock managers can easily shift populations in a desirable direction. The foundation principles for establishing a sound breeding program, including the prediction of animal performance for economically relevant traits and their incorporation into a single index of aggregate economic merit, have been well established over the last half century. Rather than this goal-based approach, the industry adopted a data-driven approach to the production of genetic evaluations that has been characterized by an overemphasis on the evaluation of productive traits, notably BW at various ages, with inadequate regard for other economically important traits, such as reproduction, animal health, and feed requirements. Production of evaluations is breed association centered, and this has delayed the introduction of national across-breed evaluations for all breeds and crosses of cattle. The computational aspects of producing evaluations are now migrating from land-grant universities to breed associations, but not yet to a single entity. The introduction of genomic information in the form of high-density SNP panels will introduce threats, challenges, and new opportunities for the production of evaluations, and represents the largest force to alter the structure of the beef improvement industry since the advent of AI. The use of evaluations has, until recently, stopped short of the provision of index merit as a basis for selection. Accordingly, the value propositions associated with annual improvement or the selection of alternative sires has not been well communicated. Technology, along with economic and other issues related to stakeholder acceptance, will collectively determine the future nature of the industry in terms of the production and use of evaluations.
开发肉牛改良信息系统的总体动机在于，人们相信掌握育种值和杂种优势效应能让人确定不同选择和交配方案的后果。有了这些信息，畜牧管理者就能轻松地将畜群朝着理想方向转变。在过去半个世纪里，建立健全育种计划的基础原则已确立，包括对与经济相关性状的动物性能进行预测，并将其纳入综合经济价值的单一指数中。该行业没有采用这种基于目标的方法，而是采取了一种数据驱动的方法来进行遗传评估，其特点是过度强调对生产性状的评估，特别是不同年龄的体重，而对其他经济上重要的性状，如繁殖、动物健康和饲料需求关注不足。评估的生产以品种协会为中心，这延迟了全国范围内对所有牛品种和杂交品种的跨品种评估的引入。目前，评估生产的计算工作正从赠地大学转移到品种协会，但尚未集中到一个单一实体。以高密度SNP面板形式引入基因组信息将给评估生产带来威胁、挑战和新机遇，并且是自人工智能出现以来改变肉牛改良行业结构的最大力量。直到最近，评估的使用还没有达到提供指数优点作为选择基础的程度。因此，与年度改良或选择替代种公牛相关的价值主张尚未得到很好的传达。技术以及与利益相关者接受度相关的经济和其他问题，将共同决定该行业在评估生产和使用方面的未来性质。
