Observing grazing patterns with collar-mounted accelerometers and spatial data - Obermeyer, Kilian; Kayser, Manfred; Isselstein, Johannes (Frontiers in Animal Science, 2025)
In pasture-based dairy farming, animal behavior data can improve data-driven pasture management. Information on the grazing behavior of dairy cows can be retrieved from sensor-based data. However, this approach generally requires sophisticated sensor equipment and involves labor-intensive animal observations. As an alternative, the use of data from simple and commonly used collar-mounted accelerometers and global navigation system services (GNSS) receivers was investigated. In our on-farm study, cows grazed in a rotational or in a continuous grazing system, with a higher sward or a lower sward height, respectively. As an indicator of grazing activity, the overall dynamic body acceleration (ODBA) was calculated from the accelerometer data. After differentiating the grazing process (forage uptake) into grazing with grazing steps (i.e., moving to the next feeding station) and grazing without grazing steps (i.e., true standing) from the GNSS data, only a negligible effect of grazing steps on ODBA was found. The ODBA was higher in short swards (3.47 m s−2) than in tall swards (2.88 m s−2). The ODBA was also affected by the time of the day, with major grazing activity around dusk. These findings show the potential of simple accelerometers on collars in research on grazing patterns and cattle monitoring and for use in pasture management. The ODBA can be calculated from any three-dimensional accelerometer also from existing commercial technology, which allows a wide in-field application.