Abstract
Simple SummarySensors attached to the legs of cows are used to record behaviours such as lying times and step count. It is important that the information recorded by sensors is accurate, as changes to behaviour could indicate to the farmer that a cow is sick or in heat. Therefore, this study compared the behaviours recorded by IceQube sensors to those visually observed by humans, when the cows where housed at pasture, in a straw yard and in cubicle housing. The results showed that lying and standing times, the number of times the cows stood up and laid down and the number of steps recorded by the sensors and human observers was similar. Sensors accurately recording cow activity could potentially be worn by cows throughout their lives and could be used to predict and detect sick cows. This could allow the farmer to respond quicker and treat sick cows sooner, increasing animal welfare.The accuracy of CowAlert IceQube sensors (IceRobotics Ltd., Edinburgh, UK) for recording lying duration, standing and lying transitions and number of steps when dairy cows where at pasture, in cubicle housing and in a straw yard, was investigated. Holstein Friesian cows at Harper Adams University, UK were fitted with IceQube sensors; one on the back left (BL) leg and one on the front left (FL) leg. Cows at pasture (n = 48), in cubicle housing (n = 46) and in a straw yard (n = 45) were visually observed. Data were analysed in two stages: (1) an initial exploratory phase determined the correlation level between sensor measurements andvisual observations. Subsequently, (2) a mixed effects modelling framework was used to check whether sensors provide significantly different measures of cow’s activities compared to the observations. Results indicate that lying and standing times are similar between the observed and recorded times, in all three locations. In terms of sensor placement, significant differences were found between the number of steps recorded between BL and FL on straw and pasture, but all other activities were similar, in each location. The accuracy of CowAlert IceQube sensors on the BL leg gives them the potential to be used as lifelong sensors.
Highlights
Cattle behaviour is influenced by the productivity, reproductive and disease state of the animal [1–3]
As part of a long-term study investigating the activity of Holstein Friesian cows throughout their production cycle, IceQube® accelerometer-based sensors (IceRobotics Ltd., Edinburgh, UK) were attached to both their back left (BL) and front left (FL) leg, using
There was no difference between the data recorded by IceQubes on the BL and FL legs (p > 0.05; Table 3) and correlations were strong (CCC > 0.91; Table 4)
Summary
Cattle behaviour is influenced by the productivity, reproductive and disease state of the animal [1–3]. Changes in the behaviour of cattle can be used to assist in predicting and detecting health problems in dairy cattle [4]. Ito et al found that severely lame cows spent longer lying down and had longer duration of lying bouts compared to cows that were not severely lame [6], while the study of Blackie et al suggests that more subtle changes in gait may be detected by changes in lying times [5]. Cows that subsequently suffered dystocia reduced their transitions from standing to lying positions more frequently than cows with eutocia [7]. Mastitic cows had reduced lying times, a higher number of daily lying bouts and took more steps than control cows [8]. Cows with hock and knee injuries lay down for less time each day than cows without lesions [9] and cows with Johnes disease lie down for less time [10]
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