Alawneh John, Barreto Michelle, Bome Kealeboga, Soust Martin
Good Clinical Practice Research Group (GCPRG), School of Veterinary Science, The University of Queensland, Gatton, QLD 4343, Australia.
School of Veterinary Science, The University of Queensland, Gatton, QLD 4343, Australia.
Animals (Basel). 2020 Dec 21;10(12):2452. doi: 10.3390/ani10122452.
Animals display movement patterns that can be used as health indicators. The movement of dairy cattle can be characterized into three distinct cluster types. These are cluster type 1 (resting), cluster type 2 (traveling), and cluster type 3 (searching). This study aimed to analyze the movement patterns of healthy calves and assess the relationship between the variables that constitute the three cluster types. Eleven Holstein calves were fitted with GPS data loggers, which recorded their movement over a two week period during spring. The GPS data loggers captured longitude and latitude coordinates, distance, time and speed. It was found that the calves were most active during the afternoon and at night. Slight inconsistencies from previous studies were found in the cluster movements. Cluster type 2 (traveling) reported the fastest rate of movement, whereas cluster type 1 (resting) reported the slowest. These diverse movement patterns could be used to enhance the assessment of dairy animal health and welfare on farms.
动物表现出的运动模式可作为健康指标。奶牛的运动可分为三种不同的聚类类型。它们是聚类类型1(休息)、聚类类型2(行走)和聚类类型3(搜寻)。本研究旨在分析健康犊牛的运动模式,并评估构成三种聚类类型的变量之间的关系。11头荷斯坦犊牛佩戴了GPS数据记录器,记录它们在春季为期两周的运动情况。GPS数据记录器捕捉经度和纬度坐标、距离、时间和速度。结果发现,犊牛在下午和夜间最为活跃。在聚类运动中发现了与先前研究略有不一致之处。聚类类型2(行走)的运动速度最快,而聚类类型1(休息)的运动速度最慢。这些不同的运动模式可用于加强对农场奶牛健康和福利的评估。