Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada; Canadian Dairy Network, Guelph, Ontario, N1K 1E5, Canada.
Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada.
J Dairy Sci. 2017 Dec;100(12):10251-10271. doi: 10.3168/jds.2017-12968.
Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving, health, and workability have now been integrated into selection indices. Current research focuses on fitness, health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques, and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.
在过去的 100 年中，用于奶牛群体遗传选择的性状范围已经发展到满足行业和社会的需求。在 20 世纪之交，奶农对提高牛奶产量感兴趣；然而，当时并没有系统的选择策略。有组织的牛奶生产性能记录很快就形成了，紧接着是体型评分。本世纪中叶，遗传理论和统计学的方法学进步，以及计算技术的创新，为多性状分析铺平了道路。随着更复杂的性状分析技术的开发和纳入选择计划，产量开始迅速增加，遗传进展的车轮开始转动。到本世纪末，选择的重点已经从纯粹的生产导向转移到更加平衡的育种目标。这种转变部分归因于健康和繁殖力问题的增加，部分归因于社会压力和福利问题的关注。涵盖寿命、繁殖力、产犊、健康和工作能力的性状现在已经纳入选择指数。当前的研究重点是适应性、健康、福利、牛奶质量和环境可持续性，这突出了对更全面的育种目标的集中关注。未来，农场传感器、数据记录器、精密测量技术和其他技术手段将为选择提供更多数据，而困难不在于测量表型，而在于选择要选择哪些性状。
