All Outputs (2)

Feature selection and comparison of machine learning algorithms in classification of grazing and rumination behaviour in sheep (2018)
Journal Article
Mansbridge, N., Mitsch, J., Bollard, N., Ellis, K., Miguel-Pacheco, G. G., Dottorini, T., & Kaler, J. (2018). Feature selection and comparison of machine learning algorithms in classification of grazing and rumination behaviour in sheep. Sensors, 18(10), Article 3532. https://doi.org/10.3390/s18103532

Grazing and ruminating are the most important behaviours for ruminants, as they spend most of their daily time budget performing these. Continuous surveillance of eating behaviour is an important means for monitoring ruminant health, productivity and... Read More about Feature selection and comparison of machine learning algorithms in classification of grazing and rumination behaviour in sheep.

The applied development of a tiered multilocus sequence typing (MLST) scheme for Dichelobacter nodosus (2018)
Journal Article
Blanchard, A. M., Jolley, K. A., Maiden, M. C., Coffey, T. J., Maboni, G., Staley, C. E., …Tötemeyer, S. (in press). The applied development of a tiered multilocus sequence typing (MLST) scheme for Dichelobacter nodosus. Frontiers in Microbiology, 9, Article 551. https://doi.org/10.3389/fmicb.2018.00551

Dichelobacter nodosus (D. nodosus) is the causative pathogen of ovine footrot, a disease that has a significant welfare and financial impact on the global sheep industry. Previous studies into the phylogenetics of D. nodosus have focused on Australia... Read More about The applied development of a tiered multilocus sequence typing (MLST) scheme for Dichelobacter nodosus.