PhD project title and outline, including interdisciplinary dimension:
A Platform for Precision Phenotyping of Farmed Animals
The efficiency of livestock production is a crucial element of agricultural practice. Farming enterprises are continually aiming to improve the efficiency of production systems with intensification practices often limited by the negative impacts they have on animal health and welfare. An animal that is ill or lame or otherwise compromised will commonly show a reduction in the efficiency of food conversion and will take longer to reach slaughter weight. Similarly, an animal kept under stressful or inadequate conditions or in pain will also show a decrease in weight gain or other measureable output (meat, milk or wool production etc.). Increasing demands for intensification in farming present challenges for the producers such as: maintaining efficient feed conversion rates, limiting disease transfer among densely packed animals; making the best use of the space available and maintaining a high level of animal welfare as demanded by the consumer. The rapid evolution of electronic sensor technologies has hastened the drive for so-called ‘precision farming’ approaches to be applied to individual farmed animals to provide data on physiological measures of animal health/welfare. In addition to measuring physiological traits, such technologies can be used to monitor subtle changes in animal behaviour that provide early warning signs of changes in health/welfare, including changes in disease status and/or the levels of stress. The ability to rapidly identify and detect subtle changes in animal phenotypes would provide commercial enterprises with a competitive advantage through the ability to respond more rapidly to emerging problems before the onset of obvious symptoms. Further, such systems would provide accurate data on practices that induce (and reduce) stress and, therefore, health risk.
The project takes an interdisciplinary approach incorporating expertise in the fields of parasitology, disease diagnostics, the use of remote sensors and forensics providing the PhD candidate with a diverse training and expertise that is both locally and internationally relevant.
Primary supervisor: Dr Nikki Marks (Biological Sciences)
Secondary supervisor: Dr Colin Fleming (Senior researcher - Sustainable Agri-Food Sciences Division, Agri-Food and Biosciences Institute)
External Partner/Organisation: First Forensic Solutions
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