摘要
Simple Summary Sensors, routinely collected on-farm tests, and other repeatable, high-throughput measurements can provide novel phenotype information on a frequent basis. Information from these sensors and high-throughput measurements could be harnessed to monitor or predict individual dairy cow feed intake. Predictive algorithms would allow for genetic selection of animals that consume less feed while producing the same amount of milk. Improved monitoring of feed intake could reduce the cost of milk production, improve animal health, and reduce the environmental impact of the dairy industry. Moreover, data from these information sources could aid in animal management (e.g., precision feeding and health detection). In order to implement tools, the relationship of measurements with feed intake needs to be established and prediction equations developed. Lastly, consideration should be given to the frequency of data collection, the need for standardization of data and other potential limitations of tools in the prediction of feed intake. This review summarizes measurements of feed efficiency, factors that may impact the efficiency and feed consumption of an animal, tools that have been researched and new traits that could be utilized for the prediction of feed intake and efficiency, and prediction equations for feed intake and efficiency presented in the literature to date.
摘要译文
简单的摘要传感器，常规收集的农场测试以及其他可重复的高通量测量值可以频繁地提供新颖的表型信息。可以利用这些传感器和高通量测量的信息来监视或预测单个奶牛饲料摄入量。预测算法将允许在产生相同数量的牛奶的同时减少饲料的动物的遗传选择。改善对饲料摄入量的监测可以降低牛奶产量的成本，改善动物健康状况，并减少乳制品行业的环境影响。此外，来自这些信息来源的数据可以帮助动物管理（例如，精确喂养和健康检测）。为了实施工具，需要建立测量与进料摄入的关系，并开发预测方程。最后，应考虑数据收集的频率，数据标准化的需求以及在预测进料摄入量中的工具的其他潜在局限性。这篇综述总结了饲料效率的测量，可能影响动物的效率和饲料消耗的因素，已研究的工具以及可以用于预测饲料摄入量和效率的新特征以及用于进食摄入量的预测方程迄今为止在文献中提出。
Cori J. Siberski-Cooper*;James E. Koltes. Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle[J]. Animals : an Open Access Journal from MDPI, 2022,12(1)