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 by a farmer of abnormal milk or swelling of the udder. However, the scientific literature says that not all cows with visual signs of mastitis require antibiotic treatment and whilst most dairy farmers have extensive data on each cow in their herd, they don’t have ready means by which to interpret and make informed decisions on which cows to use antibiotics to treat.
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 cows with clinical mastitisso they can reduce the use of antibiotics and improve animal health and welfare.
The digital tool will bring together information about the individual health history of each dairy cow and the causative pathogen, and powered by model-driven artificial intelligence, it will provide tailored, individual cow management advice to farmers and vets based on the animal’s own data.
The project team will conduct research and trials on Australian dairy farms across New South Wales, and Victoria, with a prototype tool to be extensively tested on farm in the next six months.
This project is creating new scientific knowledge in the fields of:
The final tool will be released free to Australian DairyFarmers, via a smartphone app which can be used cow-side in the dairy.
Through better use of data to inform decision making, the project aims to:
