Including Internet of Things (IoT) technology in horse-rearing management can potentially mitigate problems such as human resource shortages and time limitations in performing daily behavior monitoring. In this study, a small and inexpensive activity meter used to monitor dogs and cats (PLUS CYCLE^®, JARMeC, Kanagawa, Japan) was used to monitor the daily behavior of horses. A study was performed to examine the suitability of the PLUS CYCLE^® device for monitoring horses and to determine whether it could estimate horse behavior. The device was equipped with an accelerometer and was used to monitor Kiso horses in horse stalls and pastures after installing the devices at specific locations on headcollars and girths. The amount of activity from the accelerometer showed differences among the horses’ behavioral types (lying, standing, walking, and feeding) in the stall, suggesting that it functions in horses. In the pasture, the amount of activity was correlated with GPS movement speed. Then, we tried to establish restricted cubic spline regression models to predict the locomotion speed in the pasture based on the amount of activity, but the prediction accuracy was low. This study showed that PLUS CYCLE^® can be used to monitor horse activity amount during the daily management of individual horses. However, to achieve higher precision in monitoring detailed behaviors, additional investigation and data pertaining to the amount of activity for each horse during rearing in different environments are needed.

We investigated the changes in inbreeding levels in Japanese Thoroughbred horses over the past 46 years. Our results show a significant increase in inbreeding over the past 30 years, primarily due to the influence of two sires, Northern Dancer and Sunday Silence. Northern Dancer’s bloodline spread gradually through descendants like Northern Taste, leading to a slower increase in the inbreeding coefficient. In contrast, Sunday Silence was directly imported and became a leading sire, causing a rapid increase in his blood proportion and inbreeding coefficient. Our findings suggest that monitoring the trajectories of successful sires and considering historical factors can help predict and control potential inbreeding depression in the future.