Designing research for applied beef cattle production systems has always presented challenges for Land Grant University and USDA Scientist. Specifically, creating study designs that have enough replication for statistical inference has often prompted scientists to use designs that do not closely replicate actual production systems. Past research has often used multiple replications (pens/paddocks/pastures) that utilize replication (group averages; 4 – 8 animals) means as the experimental unit. While effective in measuring average treatment responses, these types of study designs do little to describe the actual individual animal behavior and performance in a more practical production environments. Approaches to increasing statistical observations in actual production environments will be discussed in this presentation. Embracing new technologies such as GPS, activity monitors, EID tags, and feed intake monitors (C-Lock Inc, GrowSafe) combined with multiple regression modeling tools can aid in designing and publishing beef cattle production research in actual beef production environments. Research at Montana State University has utilized SmartFeed Pro and SuperSmart Feeders for strategic supplementation research on extensive rangelands and dry-land pastures for the past seven years. Results of these studies have evaluated self-fed (salt-limited; loose, pelleted, and baked molasses blocks) as well as hand-fed supplements where daily intakes are limited by the locking gate on the feeder. This presentation will summarize these studies with a focus on research designs that were successful and/or unsuccessful in respect to characterizing beef cattle performance in production settings. Our goal will be to assist the audience in the application of feed intake technology in designing future applied beef cattle research.

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4 利用 SmartFeed Pro 和 SuperSmart Feeders 进行肉牛应用研究

应用肉牛生产系统的设计研究一直给土地授予大学和美国农业部科学家带来挑战。具体来说，创建具有足够的重复性以进行统计推断的研究设计通常会促使科学家使用无法紧密复制实际生产系统的设计。过去的研究经常使用多次重复（围栏/围场/牧场），利用重复（组平均值；4-8只动物）手段作为实验单位。虽然可以有效测量平均治疗反应，但这些类型的研究设计几乎无法描述更实际的生产环境中的实际个体动物行为和表现。本演讲将讨论在实际生产环境中增加统计观察的方法。采用 GPS、活动监测器、EID 标签和采食量监测器（C-Lock Inc、GrowSafe）等新技术，结合多元回归建模工具，有助于在实际牛肉生产环境中设计和发布肉牛生产研究。蒙大拿州立大学的研究在过去七年中利用 SmartFeed Pro 和 SuperSmart Feeders 对广阔的牧场和旱地牧场进行了战略补充研究。这些研究的结果评估了自喂（限盐；松散、颗粒和烘烤糖蜜块）以及手工喂食补充剂，其中每日摄入量受到喂食器上锁门的限制。本演讲将总结这些研究，重点关注在描述生产环境中肉牛性能方面成功和/或不成功的研究设计。我们的目标是协助观众应用采食技术来设计未来的应用肉牛研究。