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

  • Theron, J., Crabbe, R. A., Horta, A., & McGrath, S. (2025). A preliminary investigation of the potential of an all-weather satellite to discriminate dual-purpose crops. Crop and Pasture Science, 76(11), 1-13. Article CP24225. https://doi.org/10.1071/CP24225
  • McGrath, S., Keogh, T., Holman, B., Allworth, B., & Oddy, H. (2025). CT scanning of live lambs is a useful tool for deriving carcase weight and composition in lamb growth rate studies. Abstract from British Society of Animal Sciences Annual Conference 2025, Galway, Ireland.
  • Hossain, M. R. H., Islam, R., McGrath, S. R., Islam, M. Z., & Lamb, D. (2025). Learning-based estimation of cattle weight gain and its influencing factors. Computers and Electronics in Agriculture, 231, 1-20. Article 110033. https://doi.org/10.1016/j.compag.2025.110033
  • McGrath, S., Harris, F. A. J., McCormick, J., Wyse, J., Haque, S., Horta, A., Bond, J., Storer, C., Kabir, A., & Walsh, M. (2025). Managing through a challenging Autumn: Reflections on the dry start to 2025 and management of our mixed-farming systems trial. Southern NSW Drought Resilience Adoption and Innovation Hub/CSU. https://www.csu.edu.au/research/southern-nsw-drought-resilience-hub/projects/southern-nsw-drought-resilient-mixed-farming-system-trials 
  • Hossain, M. R. H., Islam, M. R., McGrath, S. R., Islam, M. Z., & Lamb, D. (2025). Mob-based cattle weight gain forecasting using ML models. Smart Agricultural Technology, 12, 1-13. Article 101428. https://doi.org/10.1016/j.atech.2025.101428