Mastitis is the number one health issue in dairy cows, and management of mastitis accounts for approximately two-thirds of antibiotics supplied to dairy farmers by vets. Mastitis costs the industry an estimated $150 million annually.
The decision to use antibiotics for the treatment of cows with mastitis has historically been based on visual observation of abnormal milk by a farmer. However, the scientific literature says that not all cows with visual signs of mastitis require antibiotic treatment and farmers don’t always have ready access to the data they need about the individual animal’s history or the cause of infection.
The Clinical Mastitis Decision Support Tool Project is a $3.5 million, three year project. The project team will build a digital tool to help farmers and vets make better decisions about how they manage mastitis treatments so they can reduce the use of antibiotics and improve animal health.
The digital tool will bring together information about the individual mastitis history of each dairy cow and will be powered by model-driven artificial intelligence to provide management advice to farmers and vets based on the history of individual animals and the source of infection. Advice will include which antibiotics to administer, if any.
The project team will conduct research and trials on Australian dairy farms across New South Wales, south-west Victoria and Tasmania, with a prototype tool to be tested on farm within 18 months.
This project is creating new scientific knowledge in the fields of:
The final tool will be released more widely to Australian Dairy Farmers, via DataVat, the Australian dairy industry’s central data repository.
Through better diagnoses and treatment management, the project aims to: