Progeny data from multiple sire pastures indicates a single bull sires a larger proportion of calves compared to other bulls within the same pasture. The reason behind this is thought to be linked to behavior among the bulls. The only method to currently document bull behavior is through visual observation. Technology (i.e. accelerometers) could be used to record bull activity, without needing to visually observe the animals.
Accelerometers have been used widely in beef and dairy operations to monitor and predict behavior such as lying, standing, and walking. This technology is also being used to predict BRD in feedlot cattle(Amrine, White et al. 2014) and dairy cattle behavior in a pasture based setting(Williams, Mac Parthaláin et al. 2016). Knowing early on in a breeding season if a bull is spending more time lying rather than breeding cows could be very beneficial for overall cow-calf production and bull management decisions.
Recently, accelerometers were attached to bulls in a multiple-sire pasture to determine the predictability of breeding activity. The accelerometers were able to predict lying, standing, and walking times of each of the bulls enrolled in the study. Mounting activity was deemed more challenging to predict as the events were very infrequent. This technology proved to be an asset in understanding bull behavior in a multiple-sire pasture, and will aid in the overall management of bulls throughout a breeding season.
Amrine, D. E., B. J. White and R. L. Larson (2014). “Comparison of classification algorithms to predict outcomes of feedlot cattle identified and treated for bovine respiratory disease.” Comput Electron Agric 105: 9-19.
Williams, M. L., N. Mac Parthaláin, P. Brewer, W. P. J. James and M. T. Rose (2016). “A novel behavioral model of the pasture-based dairy cow from GPS data using data mining and machine learning techniques.” J Dairy Sci 99(3): 2063-2075.
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