Application of sensor technologies in animal breeding

Organisers: Esther Ellen & Bas Rodenburg, Wageningen University & Research

Schedule: Friday 8th June, 10:00 - 12:50, G26


Farm animals are often kept in large groups. However, in animal breeding, individually collected data is used to improve health, welfare and performance of animals. Keeping animals in large groups makes it difficult to collect individual data. Furthermore, collecting data on changes in health and behavior is a challenge when animals are kept in groups. With the upcoming use of sensor technologies and video imaging, automatic identification and monitoring of animals is possible, which provides opportunities for animal breeding. Breed4Food (B4F) is a consortium established by Wageningen University & Research and four international animal breeding companies. One of the projects of B4F is to develop methods to track and monitor individual animals kept in groups using sensor technologies. A second aim is to use this information to measure traits related to animal behavior, health and nutrient use efficiency. In this symposium, we will bring together animal breeders and researchers using state-of-the art technologies to track and monitor animals in groups. This symposium highlights research that can be implemented in the lab and commercial situations and to different taxa. The presentations will be followed by a plenary discussion to place the presented research in a broader perspective and identify future research directions.

10:00-10:20    Esther Ellen and Bas Rodenburg
Using sensor technologies in animal breeding: improving damaging behaviour of animals kept in groups
10:20-10:40    Malou van der Sluis, Esther D. Ellen, Yvette de Haas and T. Bas Rodenburg
Radiofrequency identification systems: Advantages and constraints for tracking and monitoring of individual animals
10:40-11:00    Christina Rufener, Berezowski John, Filipe Maximiano Sousa, Yandy Abreu, Lucy Asher and Michael Toscano
Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups
11:00-11:30   Coffee
11:30-11:50    Ahmed Ali and Janice Siegford
An approach for tracking directional activity of individual laying hens within a multi-tier cage-free housing system (aviary) using accelerometers
11:50-12:10    Guzhva Oleksiy
Perspectives of using deep learning and computer vision algorithms for continuous behavioural monitoring of dairy cows.
12:10-12:30    Tomas Norton
Application of sensor technologies in animal breeding
12:30-12:50    Discussion

Precision livestock breeding