Interests:
Animal Health and welfare, infectious diseases of wild, domestic and farm animals, epidemiology, antimicrobial resistance, microbiology, molecular biology, proteomics/mass spectrometry, precision livestock technologies
Research projects:
- Unravelling Enterococcus cecorum infection on UK broiler farms: correlating clinical signs with pathogenesis and persistence using precision genomics, camera technology and farming practices (2022-2023, BBSRC endemic livestock disease initiative in collaboration with QUB, led by AHPA)
- Reducing, refining and monitoring antibiotic use in dairy production (QMMS/University of Nottingham 2018-20210)
- Novel animal-mounted sensor technologies for early detection of calving and calving problems in beef and dairy cattle (Writtle University College/SRUC, 2017-2018)
- Persistence of Dichelobacter nodosus, the causal agent of ovine footrot (University of Warwick 2013-2017)
Qualifications:
- PGA in Teaching and Learning in Higher Education
- Fellow of the Higher Education Academy
- PgCert in Academic Practice, University of Gloucestershire, 2021
- Mclaughlin, D., Bradley, A., Dottorini, T., Giebel, K., Leach, K., Hyde, R., Green, M. (2022) Identifying associations between management practices and antimicrobial resistances of sentinel bacteria recovered from bulk tank milk on dairy farms. Preventative Veterinary Medicine, 105666, https://doi.org/10.1016/j.prevetmed.2022.105666
- Esener, N., Marciel-Guerra, A., Giebel, K., Lea, D., Green., M.J., Bradley, A.J., Dottotini, T. (2021) Mass spectrometry and machine learning for the accurate diagnosis of benzylpenicillin and multi-drug resistance of Staphylococcus aureus in bovine mastitis. PLOS Computational Biology 17 (6) https://doi.org/10.1371/journal.pcbi.1009108
- Maciel-Guerra, A., Esener, N., Giebel, K. et al. (2021) Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning, Nature Scientific Reports 11, 7736. https://doi.org/10.1038/s41598-021-87300-0
- Giebel K., Green L.E., Purdy K.J. (2021). A Pilot Study to Investigate the Feasibility of a Multiple Locus Variable Number Tandem Repeat Analysis to Understand the Epidemiology of Dichelobacter nodosus in Ovine Footrot. Frontiers in Veterinary Science, 7,581342. https://doi.org/10.1016/j.vetmic.2017.11.017
- Miller, G., Mitchell, M., Barker, Z., Giebel, K., Codling, E., Amory, J., Michie, C., Davison, Tachtatzis, C., Andonovic, I. and Duthie, C.-A, (2020). Using animal-mounted sensor technology and machine learning to predict time-to-calving in beef and dairy cows. Animal, 1-9. https://doi.org/10.1017/S1751731119003380
- Clifton, R.1, Giebel, K.1, Liu, N.L.B.H., Purdy, K.J., Green. L.E. (2019) A paradigm shift on the persistence of Dichelobacter nodosus and Fusobacterium necrophorum in sheep and their environment. Nature Scientific Reports. 9, 14429. https://doi.org/10.1038/s41598-019-50822-9
- Giebel, K, Green, L.E., Purdy, K.J.P. (2017) Persistence of Dichelobacter nodosus, the causal agent of ovine footrot. Proceedings of the British Society of Animal Science, 8 (1), p94.
- Giebel, K. and Blackie N. (2013) The effect of providing a plant extract or a high intensity sweetener in the drinking water on the welfare and performance of weanling pigs. Proceedings of the British Society of Animal Science, 4 (1), p96.