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Collaborative project: Automated behaviour assessment in dairy goats - subproject A (VerZi)

Project


Project code: 281C503A21
Contract period: 01.06.2023 - 31.05.2026
Budget: 192,013 Euro
Purpose of research: Applied research
Keywords: AI Artificial Intelligence, animal health, Precision livestock farming, software, small ruminants, goats, prevention, husbandry techniques, animal welfare

Group housing of farm animals in any form of husbandry involves the potential for competition for scarce resources such as the best place to lie down, the watering place or the best feeding place, e.g. in the form of a concentrated feeding station. In addition, there are situations – such as technical disturbances but also biological processes in the context of mating behaviour – in which this competition is intensified. In all animal species, the agonistic interactions resulting from competition involve an increased risk of injury for conspecifics but also for the humans who handle the animals. In horned goats, this increased risk can have particularly serious consequences. Deep wounds and fatal injuries are not uncommon. Attentive animal observation and, if necessary, prompt intervention by the stable staff therefore play a decisive role for good animal health and welfare. However, animal observation is a major hurdle for animal keepers due to time constraints and thus for economic reasons. The aim of this project is therefore to automate the process of herd monitoring with the help of artificial intelligence (AI), to signal conspicuous animal behaviour to the keeper and to automatically document the events. This provides farmers, but also advisors and veterinarians, with a tool that enables them to objectively evaluate the effectiveness of measures to reduce the risk of injury. In this sense, the planned system represents a procedure for monitoring, evaluating and improving the animal welfare of housing environments. The effectiveness of the behavioural assessment and its practical usefulness will be tested on German farms during the project.

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