Heins B J, Pereira G M, Sharpe K T
West Central Research and Outreach Center, University of Minnesota, Morris 56267.
Maine Food and Agriculture Center, University of Maine, Orono 04469.
JDS Commun. 2023 Apr 20;4(4):318-323. doi: 10.3168/jdsc.2022-0308. eCollection 2023 Jul.
Pasture-based dairy herds continue to grow around the world as demand increases for sustainable farming practices. Grazing dairy farmers may benefit from the utilization of precision dairy technologies because these technologies have the potential to improve animal welfare, increase farm efficiency, and reduce costs. Precision dairy technologies have provided novel information about activity, rumination, and grazing behavior of various breeds in pasture-based systems. Previous research with wearable technologies has indicated that rumination, eating, and no activity have moderate to high correlations (r = 0.65 to 0.88) with visual observation; however, activity may be difficult to record in grazing herds. However, many grazing dairy farmers around the world are using activity monitors with generally positive success. Grazing is a complex behavior to define because cows may walk to an area and stop to eat or continuously walk and take bites of grass from the pasture. Wearable technologies can detect whether a cow is grazing with reasonable accuracy. However, the challenge is to determine pasture intake as bite rate and bite size because these can vary as the pasture is grazed to a low residual height. Nevertheless, grazing behavior data collected with wearable technologies was highly correlated (r = 0.92 to 0.95) with visual observations. Grazing is a behavior that should continue to be explored, especially with precision dairy technologies. As healthy and productive pastures are integral to grazing systems, accurate forage biomass measurements can improve efficiency and production of pastured dairy cows. However, few farms use technology to determine forage availability. Therefore, using dairy technologies to monitor forage dry matter from pasture may provide a potential benefit for grazing-based dairy farms. Current satellite technology with the normalized difference vegetation index and electronic rising plate meters may provide new technologies for farms to monitor forage biomass and fine-tune grazing within pastures. In the future, pasture-based dairy farms may rely on virtual fencing, drones to detect animal health issues and forage availability, and autonomous vehicles to move cattle and to detect weeds on pasture.
随着对可持续农业实践的需求增加,以牧场为基础的奶牛群在全球范围内持续增长。放牧奶牛的农民可能会从精准奶牛技术的应用中受益,因为这些技术有潜力改善动物福利、提高农场效率并降低成本。精准奶牛技术提供了关于基于牧场系统中各种品种奶牛的活动、反刍和放牧行为的新信息。先前对可穿戴技术的研究表明,反刍、进食和不活动与视觉观察有中度到高度的相关性(r = 0.65至0.88);然而,在放牧牛群中记录活动可能很困难。然而,世界各地许多放牧奶牛的农民正在使用活动监测器,总体上取得了积极的成果。放牧是一种难以定义的复杂行为,因为奶牛可能走到一个区域停下来进食,或者持续行走并从牧场吃草。可穿戴技术能够以合理的准确度检测奶牛是否在放牧。然而,挑战在于确定牧场摄入量,即咬食率和咬食大小,因为随着牧场被啃食到较低的剩余高度,这些参数可能会有所变化。尽管如此,通过可穿戴技术收集的放牧行为数据与视觉观察高度相关(r = 0.92至0.95)。放牧行为仍有待进一步探索,特别是借助精准奶牛技术。由于健康且高产的牧场是放牧系统的核心组成部分,准确的牧草生物量测量可以提高放牧奶牛的效率和产量。然而,很少有农场使用技术来确定牧草的可利用量。因此,利用奶牛技术监测牧场的牧草干物质含量可能会给基于放牧的奶牛场带来潜在益处。当前利用归一化植被指数的卫星技术和电子上升板测量仪可能为农场提供监测牧草生物量和在牧场内微调放牧的新技术。未来,基于牧场的奶牛场可能会依赖虚拟围栏、用于检测动物健康问题和牧草可利用量的无人机,以及用于移动牛群和检测牧场杂草的自动驾驶车辆。