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Animal Individual Factors Dictate Learning Strategy: An Integrated Analysis of Cattle Adaptation to a Virtual Fencing
Severino Pinto1, Clemens Bodt2, Julia Toups2
1Department of Sensors and Modelling, Leibniz Institute for Agricultural Engineering and Bioeconomy-ATB, Max-Eyth-Allee 100, 14469 Potsdam, Germany.
Abstract:
Virtual fencing (VF) is a promising technology for pasture management, but its successful implementation depends on understanding the factors that influence the animal learning. The aim of the present study was to evaluate the significance of individual animal factors that affect the behavioural and performance-based learning process in cattle during a VF training period. We analysed collar-derived performance data from 171 mixed-age Angus and Salers breed cattle over a 12-day training trial. Learning performance was primarily measured by daily success ratio (SR) and confidence ratio (CR). Learning trajectories and the influence of animal factors were analysed using linear mixed-effects models. A significant increase was observed in the SR over the 12-day period (p < 0.0001). A significant interaction between training day and age class (p < 0.001) revealed distinct learning strategies: younger animals showed rapid initial adaptation but lower consistency, whereas adult animals exhibited a more stable final performance. Our findings suggest that breed may also influence the learning rate to virtual fencing (p < 0.001). Individual behaviour accounted for a substantial portion of performance variation (p < 0.0001). Recognising these different individual and social learning pathways is essential for developing more effective and improved animal welfare VF training protocols.
