Beef and Sheep Research Centre, Department of Agriculture, Horticulture and Engineering Sciences, SRUC, Kings Buildings, West Mains Road, Edinburgh EH9 3JG, UK.
Beef and Sheep Research Centre, Department of Agriculture, Horticulture and Engineering Sciences, SRUC, Kings Buildings, West Mains Road, Edinburgh EH9 3JG, UK.
Animal. 2021 Mar;15(3):100150. doi: 10.1016/j.animal.2020.100150. Epub 2020 Dec 23.
Across the industry, there is large variation in health status of dairy calves and as a result, disease incidence and antibiotic use is high. This has significant implications for animal welfare, productivity and profitability of dairy and dairy-beef production systems. Technology-based early detection systems could alleviate these issues; however, methods of early detection of disease in dairy calves have not been widely explored. This study aimed to determine whether changes in activity and feeding behaviour can be used as early warning indicators of respiratory disease in calves. In total, 100 pre-weaned male Holstein calves (age: ~8-42 days) were used. Calves were group-housed and provided with starter diet, straw bedding and ad libitum water. Calves were fed milk replacer ad libitum through an automatic calf feeder, and each calf was fitted with a leg-mounted activity monitor. Daily activity and feeding behaviour variables were calculated for each calf. Each calf was assessed daily using a modified version of the Wisconsin Scoring System to assess respiratory disease status. Calves were classed as 'Diseased', 'Intermediate' or 'Healthy' based on their cumulative health score. The peak day of the most extreme illness event was identified for each calf. Data from Diseased and Healthy calves were paired for analysis based on age and BW. Data were compared for the day of peak illness, and for the 3 days previous and post. Compared to healthy calves, diseased calves lay for longer and tended to have longer lying bouts (daily lying: 17.6 ± 0.3 vs 16.7 ± 0.2 h, P < 0.01; bout length: 74.8 ± 10.6 vs 56.0 ± 3.7 min, P = 0.09 for diseased and healthy calves, respectively). Diseased calves fed for a shorter time and had fewer feeder visits (with intake) each day compared to healthy calves (feeding time (min): 19.3 ± 1.4 vs 22.8 ± 1.5; P < 0.05; visits: 2.1 ± 0.2 vs 3.2 ± 0.4; P < 0.05). Importantly, differences between diseased and healthy calves were evident in both activity and feeding behaviour on the days prior to the peak day of disease. Lying bout length was greater in diseased calves for the 2 days prior to the peak day (P < 0.05), lying time was longer on day -1 (P < 0.05) and feeder visits with milk intake were less frequent on day -3 (P < 0.05). Thus, measurement of feeding and activity using precision technology within early detection systems could facilitate early intervention and optimized treatment.
在整个行业中,奶牛犊牛的健康状况存在很大差异,因此疾病发病率和抗生素使用量很高。这对动物福利、奶牛和奶牛-肉牛生产系统的生产力和盈利能力都有重大影响。基于技术的早期检测系统可以缓解这些问题;然而,奶牛犊牛疾病的早期检测方法尚未得到广泛探索。本研究旨在确定活动和喂养行为的变化是否可以作为犊牛呼吸疾病的预警指标。总共使用了 100 头未断奶的雄性荷斯坦奶牛(年龄:~8-42 天)。犊牛分组饲养,提供犊牛代乳料、稻草垫料和自由饮水。犊牛通过自动犊牛喂养器自由饮用代乳料,每头犊牛都配备了腿部活动监测器。为每头犊牛计算了每日活动和喂养行为变量。使用威斯康星评分系统的改良版本对每头犊牛进行日常评估,以评估呼吸疾病状况。根据累积健康评分,犊牛被归类为“患病”、“中度”或“健康”。确定了每头犊牛最严重疾病事件的高峰日。根据年龄和体重,对患病和健康犊牛的数据进行配对分析。比较了发病日、发病前 3 天和发病后 3 天的数据。与健康犊牛相比,患病犊牛的卧床时间更长,并且倾向于有更长的卧床时间(每日卧床:17.6±0.3 小时对 16.7±0.2 小时,P<0.01;卧床时间:74.8±10.6 分钟对 56.0±3.7 分钟,患病和健康犊牛分别为 P<0.09)。与健康犊牛相比,患病犊牛每天的进食时间更短,采食次数也更少(进食时间(分钟):19.3±1.4 分钟对 22.8±1.5 分钟;P<0.05;采食次数:2.1±0.2 次对 3.2±0.4 次;P<0.05)。重要的是,在疾病高峰日前的几天,患病和健康犊牛的活动和喂养行为就已经出现差异。在发病高峰日前的 2 天,患病犊牛的卧床时间更长(P<0.05),发病前一天的卧床时间更长(P<0.05),发病前三天的采食次数更少(P<0.05)。因此,使用早期检测系统中的精密技术测量喂养和活动,可以促进早期干预和优化治疗。