Author: Deborah Piette & Tomas Norton (KUL) - Date: July 17, 2018
Nowadays, the presence of health disorders in the dairy cow herds has increased, probably due to an increase in milk yield and production stress. Mastitis and ketosis are two of the most prevalent diseases in dairy cows.
Mastitis is an intramammary infection caused by bacteria. Clinical ketosis is a metabolic and digestive disorder, in which cows show loss of appetite and depression. These diseases induce losses in milk production, therefore reducing farm profitability. The mean total cost for a cow suffering from mastitis or ketosis is estimated on 240€ and 257€ per cow per year, respectively. Thus, an algorithm to automatically detect the onset of a disease can improve both dairy cow’s health and farmer’s work load and income.
Nowadays, Real-Time-Positioning-Systems (RTLS) allow quantifying cows’ location in the barn at all times. It is possible to use this information to develop detailed individual cow time budgets for each activity performed by the cows, such as walking, feeding or resting. At KU Leuven an early warning system to detect the first stages of a mastitis or ketosis health event has been developed. The daily activities performed by each individual cow are monitored by the algorithm in real-time. Whenever there is a deviation in these behaviours, the algorithm notifies the farmer about the cow exhibiting this deviation, so he can take action. The prototype system still needs further development and is not available on the market yet.