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Continuous surveillance of animal welfare in housed dairy cows using image analysis technology

The project aims to identify biomarkers of animal health and welfare in order to increase knowledge of animal behavior and basic needs in general, and the importance of locomotion disorders in particular. With larger herds and higher production requirements less space is given for supervision of the individual animal. In milk production a reduction of the estimated management hours per cow and year has been halved from 40 h in a tie stall barn to 20 h in a cubicle system with automatic milking (AMS). This means that it will be more difficult to detect disease before it endangers animal welfare. We also know that euthanized and dead cows increase in cubicle systems, which is an indication that the disease was not detected in time and that the animal suffered unnecessarily. Using image analysis the animals are supervised with cameras and the information is analyzed mathematically. With so called algorithms the animals are identified as well as their positions, movements and interactions with other animals and the equipment. The system can identify animals that have disease problems or disturbed behavior in order to be able to treat these in time or correct the cause of the disorders before it's gone too far. In addition, the system can also be used to evaluate and correct risk factors for disturbed animal behavior that affects the function of the system and threaten to cause disease problems or disturbed behavior. Healthy, sustainable cows also mean less environment load.

Main applicant:

Christer Bergsten,
SLU Biosystem och teknologi


Kalle Åström.
LU, Matematikcentrum

Anders Herlin.
SLU, Biosystem och teknologi

Funded by FORMAS.
Period: 2014-2016.