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Saturday, October 21, 2017
Variables from GPS data to assess the fitness of cows

An assessment of how well we are able to derive behaviour of animals from GNSS location data is very important in terms of behavioural research and to give an idea how deviations in behaviour of individual animals can be detected that might indicate if the animal is carrying a disease.


The field trial with cattle at a dairy farm allowed us to research if variables derived from the location data could be related to the fitness of the individual animals. Visualization and initial calculation of the variables from the tracks of eight cows were done with the software developed in E-Track, TrackLab. Variables like total distance, speed, acceleration and turning angle were calculated, but the software also allowed us to determine how each individual cow uses the field. In the software, the field could be divided in zones and it shows for each individual the frequency of entering that area and the percentage of time spent in it. By including a zone for the place where silage was provided during the experiment and a zone for the watering point, we could deduce how often each individual fed or drank there. Also (based on speed) a distinction was made between location data that showed when the cows were foraging or walking. These variables were then related to the age, milk production, duration (days) of milk production and the fat and protein percentages in the milk of the eight cows that we tracked.

We found a positive correlation between the amount of time the individual cows spent on foraging and their milk production. Furthermore also a positive significant relationship was found between the fat percentage of the milk and the amount of time that the cows spent in the zone with the silage. Other significant correlations included a relationship between the maximum acceleration and the total distance covered by the animal and the finding that older cows enter the area with the watering point (zone 11, see figure) less often and supposedly drink less than younger cows, which was supported by findings on water requirement in livestock.

 

These examples nicely show how a variety of parameters can be used to monitor the behaviour and feeding strategies of cattle in relation to their productivity or fitness. When a cow clearly deviates from these patterns, this could be an indication that the cow is in oestrus or has a disease. Hence, it may not only learn us a lot about the relation between feeding behaviour and milk production, but it are the outliers that are of special interest to a farmer.

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E-Track is carried out in the context of the Galileo FP7 R&D programme supervised by the GSA (Nr. 277679-2)
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