Acceloremeters are increasingly used for monitoring behaviour and welfare of farm animals. As researchers and farmers can get much more data over 24 hours from acceloremeterts than by doing direct observations this technique also gives more reliable information about the animals state. 3D-accelerometers, is the most commonly used technique on farms and several devices are commercially available. The data from the 3D-accelerometers can be compared with various health and welfare impairments where the activity level is expected to be affected. Validations of this technique has been carried out in cattle, horses and pigs, but it has been missing in sheep, and specifically growing lambs. The objective of this study was therefore to assess the validity of two commercially available loggers, i.e. IceTag and IceQube (IceRobotics Ltd, Edinburgh, UK) in growing lambs, by comparison to a gold standard (Video observation).
The study included ten growing lambs divided into two weight classes. They were fitted with an IceTag on the right hind leg and an IceQube on the left hind leg. The IceTag reports activity per second, whereas the IceQube reports activity in 15-min periods. To enable comparison between loggers, IceTag data were also summarized in 15-min periods. Computed indications for the start of a lying bout of durations>10 s and>30 s was performed to enable filtering of lying bout data. Analyses of the lambs body posture and number of steps per second from 50 h of video recordings were used as a gold standard to determine the accuracy of the two loggers. Two observers scored the two different groups and interobserver reliability was consistent for standing, lying and number of lying bouts (κ = 0.99). However, the observers defined step count differently and no agreement was found (κ = -0.05; -0.11).
The results showed that based on Bland-Altman comparison both loggers can be used to record standing and lying time. The positive predictive value (PPV), sensitivity and specificity of the IceTag compared to video recordings per second for standing and lying were all>91.5 %. The IceTag showed a poor PPV (< 44 %) and sensitivity (< 91 %) for lying bouts, whereas the IceQube showed a better PPV (< 92 %) but somewhat lower sensitivity (< 88 %). The performance improved with the computed indications for lying bouts, for IceTag (LB_10: PPV: 100 %; sensitivity: 89 %; LB_30: PPV: 100 %; sensitivity: 100 %) and IceQube (LB_10: PPV: 98 %; sensitivity: 89 %; LB_30: PPV: 100 %; sensitivity: 100 %)), respectively. However, based on Bland-Altman comparisons, no agreement between video recording and logger recordings could be found for step count.
The authors conclude that both loggers are able to record standing and lying time in growing lambs accurately. However, the ability to record number of lying bouts is poorer for the IceTag than IceQube but increases if bouts<30 s is disregarded. Furthermore, none of the loggers should be used for step count recordings in growing lambs.
Högberg, N., Höglund, J., Carlsson, A., Saint-Jeveint, M., Lidfors, L. (2020). Validation of accelerometers to automatically record postures and number of steps in growing lambs. Applied Animal Behaviours Science, 229; 10514. https://doi.org/10.1016/j.applanim.2020.105014
This article has not been revised since publication.
This post was created by Lena Lidfors on February 17, 2022.