Space-use patterns highlight behavioural differences linked to lameness, parity, and days in milk in barn-housed dairy cows
Space-use patterns highlight behavioural differences linked to lameness, parity, and days in milk in barn-housed dairy cows
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DOI：
10.1371/journal.pone.0208424
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发表时间：
2018-12-19
期刊：
影响因子：
3.7
通讯作者：
Codling, Edward A.
中科院分区：
文献类型：
--
作者：
Diosdado, Jorge A. Vazquez;Barker, Zoe E.;Codling, Edward A.
跛行是影响商业奶牛群的关键健康和福利问题，由于治疗费用和产奶量损失，可能会产生重大经济影响。现有的跛行检测方法可能是时间密集型的，并且检测不足仍然是导致延迟或错过治疗的重要问题。因此，需要能够快速且准确地检测商业奶牛群中的个体奶牛的跛行的自动化监测系统。传感器跟踪技术的最新进展使人们能够在较长的时间尺度上观察一系列动物物种的运动、行为和空间使用情况。然而，很少有人知道如何观察到的运动行为和空间使用模式在个别奶牛跛行，或其他可能的混淆因素，如奇偶校验或在牛奶中的天数。在这项横断面研究中，10只跛脚和10只非跛脚畜棚饲养的奶牛通过移动性评分进行分类，随后使用无线本地定位系统进行跟踪。总共记录了近900，000个空间位置，可以为每头奶牛确定一系列运动和空间使用措施。使用线性模型，我们强调跛足，奇偶校验，在牛奶中的天数有显着的影响所观察到的空间使用模式。非跛脚奶牛花了更多的时间，并有更高的网站保真度（在日常的基础上，他们更有可能重新访问他们以前访问过的地区），在喂养区。非跛脚奶牛在畜棚内也有较大的全范围大小。相比之下，跛脚牛花了更多的时间，并有更高的网站保真度，在隔间（休息）地区的谷仓比非跛脚牛。胎次较高的奶牛在牛棚的右侧区域花费更多时间，更接近挤奶厅的通道。在牛奶中的天数被发现积极影响核心范围的大小，但与跛行的负面相互作用的影响。使用一个简单的预测模型，我们演示了如何能够准确地确定跛足状态的所有个体奶牛在研究16只使用两个观察到的空间使用措施，在饲养区和全范围大小所花费的时间的比例。我们的研究结果表明，个体运动和空间使用行为的差异可以用作精准畜牧方法中自动监测健康状况的指标，可能会导致更快的诊断和治疗，并改善奶牛和其他管理动物物种的动物福利。
Lameness is a key health and welfare issue affecting commercial herds of dairy cattle, with potentially significant economic impacts due to the expense of treatment and lost milk production. Existing lameness detection methods can be time-intensive, and under-detection remains a significant problem leading to delayed or missed treatment. Hence, there is a need for automated monitoring systems that can quickly and accurately detect lameness in individual cows within commercial dairy herds. Recent advances in sensor tracking technology have made it possible to observe the movement, behaviour and space-use of a range of animal species over extended time-scales. However, little is known about how observed movement behaviour and space-use patterns in individual dairy cattle relate to lameness, or to other possible confounding factors such as parity or number of days in milk. In this cross-sectional study, ten lame and ten non-lame barn-housed dairy cows were classified through mobility scoring and subsequently tracked using a wireless local positioning system. Nearly 900,000 spatial locations were recorded in total, allowing a range of movement and spaceuse measures to be determined for each individual cow. Using linear models, we highlight where lameness, parity, and the number of days in milk have a significant effect on the observed space-use patterns. Non-lame cows spent more time, and had higher site fidelity (on a day-to-day basis they were more likely to revisit areas they had visited previously), in the feeding area. Non-lame cows also had a larger full range size within the barn. In contrast, lame cows spent more time, and had a higher site-fidelity, in the cubicle (resting) areas of the barn than non-lame cows. Higher parity cows were found to spend more time in the right-hand-side area of the barn, closer to the passageway to the milking parlour. The number of days in milk was found to positively affect the core range size, but with a negative interaction effect with lameness. Using a simple predictive model, we demonstrate how it is possible to accurately determine the lameness status of all individual cows within the study 16 using only two observed space-use measures, the proportion of time spent in the feeding area and the full range size. Our findings suggest that differences in individual movement and space-use behaviour could be used as indicators of health status for automated monitoring within a Precision Livestock Farming approach, potentially leading to faster diagnosis and treatment, and improved animal welfare for dairy cattle and other managed animal species.