Artificial Intelligence in Wool

Using patented scientific technology the project aims to enable producers to scan wool in-shed and detect micron, colour and crimp of the wool, by creating machine learning models accessed by affordable non-connected devices. This project will benefit the producer by providing real time wool test results cheaper and quicker than current laboratory options, allowing more sheep to be tested.

This project will explore the potential for developing an alternative to conventional shearing through R&D directed towards a novel approach, based on delivering a product by feed or injection, which creates a weakened zone in the fleece. The fleece can then be removed by unskilled labour or an automated high-throughput system. If successful, this project will revolutionise wool harvesting, by improving wool quality, eliminating shearer injuries, allowing producers to decide harvesting time, harvesting small numbers of sheep and improving sheep welfare.

The purpose of this project is to research and develop for adoption alternative technologies for wool follicle removal (lambs 8-12 weeks old) that could apply to mulesing and crutching as well as animal husbandry for the meat industry on older sheep. This project builds on the previous project “Duetto Laser Technology for sheep husbandry” which will validate Laser technology for this application in a controlled lab study.