Australian researchers are looking at the possibility of bringing artificial intelligence to the wool industry

Australian researchers are looking at the possibility of bringing artificial intelligence to the wool industry

Research into applying artificial intelligence methods in the Australian wool and sheep industry is being carried out in a bid to boost productivity and quality of the country's wool supply.

Australian Wool Innovation, a not-for-profit organisation focused on enhancing the profitability, international competitiveness and sustainability of the Australian wool industry, together with Nextgen Agri Ltd, a genetic science firm that focuses on agriculture, and the University of Sydney, will investigate the potential of applying artificial intelligence (AI) in the sheep and wool industry.

The overall objective of the research project is to provide sheep breeders with tools to use advanced phenotypes and AI technologies. 

The "farm automation program" will be carried out via a number of initiatives. One of those includes working with researchers on the University of Adelaide's eChallenge Wool Innovation project - a program that looks to support new innovations in the Australian wool industry - in order to boost productivity gains and improve the profitability of Australian wool.

Other initiatives will include making remote properties fully serviced with WiFi and linking this to smart tags.

"This project, in partnership with Nextgen Agri, is just another approach to bringing technology on-farm. Exploring the potential use of artificial intelligence in everyday practises on-farm is an exciting and future focused prospect," explains Dr. Jane Littlejohn, AWI's general manager of research.

"This project will provide a proof of concept that semi-automated images captured and combined with machine learning techniques can be used to determine identification through facial recognition, wrinkle scores, face cover and live-weight in sheep. The long-term goal of the project is to evaluate the use of advanced phenotypes and artificial intelligence technologies for the prediction of lifetime performance at young ages, management of performance changes in real time, and provide advanced highly predictive phenotypes as inputs for ongoing selection decisions," she adds.

Mark Ferguson, Nextgen Agri project lead, says the potential of this project lies in the possibility of remote and automatic weighing and identification of animals without extensive infrastructure.

"This project will also lay the foundation for new and innovative ways to assess traits in sheep without additional time and effort from farm managers."

Results from the project are expected to be analysed mid-2019.