Livestock scientists at Scotland’s Rural College (SRUC), who use deep learning to help tackle the problem of bovine tuberculosis (bTB), have received funding to further advance their project.

bTB is estimated to cost the UK dairy industry roughly £175 million a year. Using machine learning, the SRUC’s technology could accelerate the process of analysing millions of milk samples with a greater degree of accuracy than ever before. Employing specialised algorithms and techniques, the software should be able to better utilise the huge data-sets collected by the team.

This work will build upon the success of previous research carried out by SRUC and collaborators, which led to the creation of the first national genetic and genomic evaluation for bTB resistance of the Holstein breed. It also led to the launch of TB Advantage – a genetic index for use by farmers to assist in breeding cows that have a heightened resistance to bTB – by the Agricultural and Horticultural Development Board.

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Previously, after analysing mid infrared (MIR) spectroscopy of milk samples from National Milk Records, SRUC researchers were able to confirm the existence of significant genetic variation among individual animals for resistance to bTB infection.

The funding is part of DEFRA’s review of its 25-year bTB eradication strategy, which now specifically includes ‘improved genetic resistance and improved diagnostic tests’.

This new project will produce data that can be used for management and diagnostic purposes, and potentially for inclusion in national genetic evaluations for bTB.

Professor Mike Coffey, who is leading the project, said: “This is potentially a great step forward in the fight against TB. Being able to use routinely collected milk samples to alert a cow that may have been exposed to infection will allow the farmer to take remedial action long before the normal testing regime comes in.

“The early removal of infected cows should lower the background level of TB and contribute to enabling more effective outcomes from the existing tools deployed to eradicate the disease.”