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Lameness is amongst the most costly health problems of dairy cows, together with mastitis and reduced fertility. The yearly cost of lameness is estimated at 53 euro per cow on an average dairy farm. With the increasing herd sizes, farmers have less time to monitor each individual cow. This means that lame cows in the herd are often detected when they are already severely lame (if they are detected at all), compromising their health and welfare.
Automatic lameness detection
Researchers have developed a variety of lameness monitoring measurement systems to help the farmers detect lame cows in their herd. This includes:
- Pressure mat-based systems: Using load cells or pressure mats features such as the weight distribution of walking or standing cows is analysed. Examples are StepMetrix, EmFit and Gaitwise.
- Camera-based systems: The shape of the cow is extracted from 2D or 3D videos of the cows. Thermal cameras are used to detect infections or lesions in the cows’ legs.
- Accelerometer-based systems: Step counters or accelerometers are attached to the head, neck or legs of the cows to monitor their activity patterns.
- Alternative methods: Data that is already available in the farm such as milk yield, feed intake and rumination time is combined to detect lameness.
So far, very limited research has been done towards integrating economic information into the lameness monitoring system in order to create actual value for the farmer. However, in order to create value for the farmer, the researchers must understand the needs and demands of the farmer when developing a lameness monitoring system. Previous studies have pointed out that researchers are not sure whether farmers want the system to detect newly lame cows or severely lame cows, and whether or not they want information on their herd’s lameness to be provided in real-time. Researchers should communicate more with the farmers and find out what they are looking for in a lameness monitoring system, and provide custom made systems if necessary.
Last update: September 1, 2016