How can livestock farmers base their management on the individual behaviour of pigs, cows or chickens and thus provide tailor-made solutions? Knowledge about animal behaviour is needed to continue to guarantee animal welfare and animal health in increasingly complex farming systems and production chains.
The experts at Wageningen Livestock Research work with modern technologies such as sensors, decision models and RFID (identification using radio wave technology) that offer a solution.
Quick recognition of problems
Animal diseases can arise, changes in the feed can cause diarrhoea, animals that feel uncomfortable can harass and injure pen mates. The sooner such health and welfare problems are recognized, the sooner action can be taken. Sensor technology in the animal and in the stable and associated decision models thus support the craftsmanship of the farmer.
Sensors in the individual animal
Sensors for registering feed and water intake in groups of animals are already established in the livestock sector. Sick animals eat less, feverish animals drink more. Developments in IT and sensor technology ensure that a new batch of non-invasive sensors can also be used to measure the eating and drinking behaviour of individual animals in larger groups. In the vicinity of, for example, a feeding trough or drinking nipple, the identification number is recorded to monitor individual behaviour.
Measurements in the stable
Modern technology also helps livestock farmers respond better to the changing heat and climate needs of growing animals, so that they feel comfortable in every growth phase. The ammonia level in the stable is also monitored to prevent irritated eyes and damage to the respiratory tract.
Big data analysis
Our experts use data and observations about animal behaviour to assess the specific needs of the animal in different circumstances and to translate this into concrete advice for the farmer. When does the animal feel good and healthy and when does it experience stress? Is the stable climate optimal? We use big data analysis and self-learning algorithms to develop models for this.
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