Comparison of pregnant and dry pasture-based broodmares using mask technology to monitor effects of weather conditions, physiological state, and management : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Animal Science at Massey University, Palmerston North, New Zealand

Abstract

Effective broodmare management is essential in maintaining animal welfare, reproductive performance and operational efficiency within commercial equine breeding systems. This study aimed to assess the influence of weather conditions, paddock and grouping characteristics on broodmare behaviour and spatial distribution of pregnant and dry mares with the help of a sensor mask technology. The practical application of the wearable sensor was considered for improving broodmare management and early detection of health and welfare changes. The study was conducted during September 2024 on a commercial pasture-based Thoroughbred breeding farm located in Auckland, New Zealand. A subset of mares from a larger herd was selected based on physiological state that included pregnant mares (n = 8) and dry mares (n = 7). Behavioural data was collected using wearable sensor mask equipped with accelerometer and GPS tracking. Movement patterns in broodmares were primarily structured by time of day with both pregnant and dry mares exhibiting clear diurnal rhythms characterised by increased movement during daylight hours and reduced activity overnight. Physiological state significantly influenced overall activity levels with dry mares walking on average approximately 19-20 more steps per hour than pregnant mares. Effect of day had minimal influence on movement patterns, with dry mares exhibiting almost the same step counts on days of heavy rainfall compared pregnant mares, suggesting short-term behavioural responses to adverse weather conditions. Spatial analysis revealed non-uniform paddock utilisation with distinct clusters of high and low mare density indicating space selection. Hotspots were frequently associated with paddock features such as shelter belts, water troughs and gateways, highlighting the influence of resource distribution and paddock design on mare movement patterns. Overall, the findings demonstrate that broodmare movement patterns were shaped by a combination of temporal, physiological and environmental factors. The integration of accelerometer and GPS sensor technologies provided valuable insights into individual mare behavioural patterns that are difficult to detect through conventional observation. Such technologies offer considerable potential for improving broodmare monitoring, enabling more management decisions, and potentially enhancing reproductive outcomes in commercial equine breeding programs.