Elischer M F, Arceo M E, Karcher E L, Siegford J M
Department of Animal Science, Michigan State University, East Lansing 48824.
J Dairy Sci. 2013 Oct;96(10):6412-22. doi: 10.3168/jds.2013-6790. Epub 2013 Aug 16.
Behavioral observations are important in detecting illness, injury, and reproductive status as well as performance of normal behaviors. However, conducting live observations in extensive systems, such as pasture-based dairies, can be difficult and time consuming. Activity monitors, such as those created for use with automatic milking systems (AMS), have been developed to automatically and remotely collect individual behavioral data. Each cow wears a collar transponder for identification by the AMS, which can collect data on individual activity and rumination. The first aim of this study was to examine whether cow activity levels as reported by the AMS activity monitor (ACT) are accurate compared with live observations and previously validated pedometers [IceQube (IQ), IceRobotics, Edinburgh, UK]. The second aim of the study was to determine if the AMS rumination monitors (RUM) provide an accurate account of time spent ruminating compared with live observations. Fifteen lactating Holstein cows with pasture access were fitted with ACT, RUM, and IQ. Continuous focal observations (0600-2000 h) generated data on lying and active behaviors (standing and walking), as well as rumination. Activity recorded by live observation and IQ included walking and standing, whereas IQ steps measured cow movement (i.e., acceleration). Active behaviors were analyzed separately and in combination to ascertain exactly what behavioral components contributed to calculation of ACT "activity." Pearson correlations (rp) were computed between variables related to ACT, RUM, IQ, and live observations of behavior. A linear model was used to assess significance differences in the correlation coefficients of the 4 most relevant groups of variables. Significant but moderate correlations were found between ACT and observations of walking (r(p)=0.61), standing (r(p)=0.46), lying (r(p)=-0.57), and activity (r(p)=0.52), and between ACT and IQ steps (r(p)=0.75) and activity (r(p)=0.58) as well as between RUM and observations of rumination (rp=0.65). These data indicate that ACT and RUM do reflect cow walking and rumination, respectively, but not with a high degree of accuracy, and lying cannot be distinguished from standing.
行为观察对于检测疾病、损伤、繁殖状态以及正常行为的表现非常重要。然而，在诸如基于牧场的奶牛场等大型系统中进行现场观察可能既困难又耗时。已经开发出活动监测器，例如为与自动挤奶系统（AMS）配合使用而设计的监测器，用于自动和远程收集个体行为数据。每头奶牛都佩戴一个项圈应答器，以便AMS进行识别，AMS可以收集有关个体活动和反刍的数据。本研究的首要目的是检验与现场观察以及先前经验证的计步器[IceQube（IQ），英国爱丁堡的IceRobotics公司]相比，AMS活动监测器（ACT）报告的奶牛活动水平是否准确。该研究的第二个目的是确定与现场观察相比，AMS反刍监测器（RUM）对反刍时间的记录是否准确。给15头可以进入牧场的泌乳荷斯坦奶牛安装了ACT、RUM和IQ。连续的焦点观察（06:00 - 20:00时）产生了关于躺卧和活动行为（站立和行走）以及反刍的数据。现场观察和IQ记录的活动包括行走和站立，而IQ步数测量的是奶牛的运动（即加速度）。分别对活动行为进行单独分析和综合分析，以确切确定哪些行为成分对ACT“活动”的计算有贡献。计算了与ACT、RUM、IQ以及行为的现场观察相关变量之间的皮尔逊相关性（rp）。使用线性模型评估4组最相关变量的相关系数中的显著差异。发现ACT与行走观察（r(p)=0.61）、站立观察（r(p)=0.46）、躺卧观察（r(p)= - 0.57）和活动观察（r(p)=0.52）之间，以及ACT与IQ步数（r(p)=0.75）和活动（r(p)=0.58）之间，还有RUM与反刍观察（rp=0.65）之间存在显著但中等程度的相关性。这些数据表明，ACT和RUM分别确实反映了奶牛的行走和反刍，但准确性不高，并且无法区分躺卧和站立。
