Shawn McGrath

Dr Shawn McGrath

Agricultural Scientist, Senior Research Fellow, Gulbali Institute

Gulbali Institute

Biography

Shawn is currently leading a National Lamb Feedlotting Research Program and is continuing to pursue research interests in farming systems, livestock production and the use of sensor technology in these systems.

Shawn has worked on several farming systems projects notably “Step Changes in Meat Production Systems from dual-purpose crops in the feedbase”, an MLA funded research program (2013-2017) where he managed field work at the CSU Wagga Wagga node and a stint as a visiting scientist with CSIRO at Canberra helping analyse results from the Canberra node.

He was Livestock Systems Pathway Leader in the former Graham Centre and represented Charles Sturt University at SALRC and within the international ECLIPSE project.

Research
  • Animal production
  • Whole Farm Management
Publications
Full publications list on CRO

Recent Publications

  • Habib, M., Kabir, A., Zheng, L., & McGrath, S. (2024). LEI: Livestock Event Information Schema for Enabling Data Sharing. Computers and Electronics in Agriculture, 220, Article 108874. https://doi.org/10.1016/j.compag.2024.108874
  • Prell, M. M., McGrath, S. R., Kirkland, P. D., & Allworth, M. B. (2024). An investigation into the transmission and control of pestivirus in sheep in Australia. Australian Veterinary Journal, 102(3), 60-66. https://doi.org/10.1111/avj.13298
  • Bates, A., McGrath, S., Allworth, B., Robertson, S., & Refshauge, G. (2023). A cross-sectional study of commercial ewe management practices for different sheep breeds across southern Australia. Animals, 13(3), [388]. https://doi.org/10.3390/ani13030388
  • Allworth, M. B., McQuillan, M., McGrath, S. R., Wilson, C. S., & Hernandez-Jover, M. (2023). A survey on bloat in southern Australian beef production systems. Australian Veterinary Journal, 101(3), 121-126. https://doi.org/10.1111/avj.13226
  • Dulal, R., Zheng, L., Kabir, A., McGrath, S., Medway, J., Swain, D., & Swain, W. (2023). Automatic cattle identification using YOLOv5 and Mosaic Augmentation: A comparative analysis. In The International Conference on Digital Image Computing: Techniques and Applications (DICTA) IEEE. http://arxiv.org/abs/2210.11939