This summary has been extracted from the application. A copy of the student’s Abstract/Thesis has not been received.
Owing to the extensive nature of the sheep industry and the difficulty monitoring animals, producers are becoming increasingly interested in the development of a remote monitoring technology to track the reproductive behaviour of individual animals. In particular identifying mating events between rams and ewes and lambing events. Both of which would provide insight into sources of reproductive wastage in the Australian Wool Industry.
University of Sydney researchers have recently established a mating signature of ram behaviour using an accelerometer-based on-animal sensor developed by AWI and Digibale. This project will further this preliminary research through the integration of Bluetooth and trilateration technology. With this additional technology, I will utilise machine learning models to evaluate the ability of the sensor to: 1) accurately determine when a mating event occurs, 2) identify the animals a mating event occurs between, and 3) predict onset of oestrus in ewes through validation with blood hormone profile and/or transrectal ultrasound.
The same technology will also be used to monitor lambing ewes to determine a signature of a lambing event. The data collected will then be used to develop algorithms to incorporate into the Smart Tag in order to provide the industry with cutting edge technology beneficial for improving the efficiency and success rate of sheep production.