Date of Award

Fall 12-15-2023

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)

Department

Animal Sciences

Advisor

Colt W. Knight

Second Committee Member

Glenda Periera

Third Committee Member

Robert Causey

Abstract

Horse behavior in pasture and grazing environments remains understudied, despite the substantial domestic horse population in the United States. This paper explores the utilization of Global Positioning System (GPS) technology to detect equine behavior, specifically focusing on grazing behaviors. By analyzing GPS data from (n=9) Standardbred horses, this study aims to establish the capabilities and accuracy of the Columbus P-1 data logger as a low-cost GPs unit for equine research, without the use of accelerometers. Through the data provided by the GPS unit, a model to distinguish grazing, resting, drinking, walking, trotting, and running was developed with satisfactory detection rates. The model is developed using a series of parameters, including speed, distance traveled, distance to water and shade, and heading changes. The model achieved the highest detection rates for resting (104.4%) and grazing (100.1%). Limitations of the model include difficulties in detecting rolling, grooming, and drinking behaviors, these behaviors are limited to due not using an accelerometer. Future research could further refine the model, validate it under different conditions, and investigate the impact of seasonal weather on equine behavior. Implications of this research include the potential improvement of equine health monitoring and pasture management. This study advances the ability to leverage GPS technology to enhance our understanding of equine behavior in pasture, which would benefit the welfare and management of domestic horses.

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