Careful gathering of reliable data has been a significant prerequisite for the success of Danish livestock production.  New technologies make it possible to monitor animal behavior in detail, even though e.g. cattle- and pig herds are increasing in size. Automatically collected data can be used to ensure the welfare and health of the animals.

"A sow with an attached accelerometer will reveal a great many details about her health condition through her patterns of movement. We can determine if the sow is sick, in heat, or in a difficult farrowing from such measurements ", says Professor Jens Peter Nielsen. In order to prevent diseases and lameness in the sows, we are developing methods to identify those animals, which are at higher risk and thus require special attention. Improved diagnostics of diseases helps towards a more targeted use of antibiotics, and thus help to reduce the development of resistant bacteria. 

In a dairy in freestall barns, even more measurements can be obtained, e.g. in connection with the examination of the milk, which is collected by the milking robots. If anything is out of the ordinary, the monitoring system will automatically detect it and alert the farmer via text message.  

User-friendliness

The task of the researchers is to handle the enormous amounts of statistical and mathematical data, analyze and interpret those data and make them useful for practical purposes. The section has a well-established cooperation with herd owners, advisors, veterinarians, and branch organizations, such as Danish Cattle (Dansk Kvæg) and Danish Pig Production (Dansk Svineproduktion).

Selected herds are attended by veterinarians and animal scientists from the section, who cooperates with internal and external partner laboratories. In the context of research, the section cooperates with such scientific groups as Population biology, which work towards balancing efficiency, health and welfare in livestock production. Another core field is a sustainable approach to agriculture, food products and people in developing countries.