Discovery Early Career Researcher Award - Grant ID: DE170101132
Funder
Australian Research Council
Funding Amount
$372,000.00
Summary
How social relationships improve sheep productivity. This project aims to determine how the social network structure of a flock and different individuals’ experience and leadership abilities improve a population’s well-being and productivity (wool clip and lambing rates). This project will use social network theory and collective behaviour in animals to manage sheep in Australia’s arid rangelands, which are important for the pastoral industry, but where ecological challenges reduce livestock pro ....How social relationships improve sheep productivity. This project aims to determine how the social network structure of a flock and different individuals’ experience and leadership abilities improve a population’s well-being and productivity (wool clip and lambing rates). This project will use social network theory and collective behaviour in animals to manage sheep in Australia’s arid rangelands, which are important for the pastoral industry, but where ecological challenges reduce livestock productivity. An expected outcome is management guidelines for the sheep industry to improve wool and meat production.Read moreRead less
Intelligent and objective measurement of wool fibre diameter. More than a half million tones of wool produced in Australia per year are visually evaluated by human woolclassers. This fibre-classing process is subjective and heavily dependent on the experience of the classers. In this project, we will objectively measure wool fibre diameter by extracting features used by human woolclassers and by combining image processing and artificial intelligence. The fractal dimension calculated by fracta ....Intelligent and objective measurement of wool fibre diameter. More than a half million tones of wool produced in Australia per year are visually evaluated by human woolclassers. This fibre-classing process is subjective and heavily dependent on the experience of the classers. In this project, we will objectively measure wool fibre diameter by extracting features used by human woolclassers and by combining image processing and artificial intelligence. The fractal dimension calculated by fractal based texture analysis will be correlated to fibre diameter. This approach will provide an insight into an on farm and/or in shed objective measurement of wool fibre diameter.Read moreRead less