Field studies characterizing equine grazing activity primarily rely on observational protocols, limiting the quantity and accuracy of collected data. The objectives of this study were to validate an automated chew sensor technology, the EquiWatch System (EWS), for detecting grazing behaviors and to demonstrate potential applications of the EWS in equine grazing research. Eight mature standardbred mares were used in this study. EquiWatch System validation was completed in two phases: grazing time was evaluated in experiment 1 and chew counts in experiment 2. The correlation between visual observations and system-recorded grazing time was high (concordance correlation coefficient [CCC] = 0.997). There was also a high agreement between the sum of manually counted bites and chews and total chew counts reported by the EWS (CCC = 0.979). Following validation, a pilot study was conducted using the EWS to assess feeding behaviors of horses with unrestricted pasture access (PAS) versus horses offered ad libitum hay (HAY). Horses spent more time engaged in feeding behavior on PAS (14.79 ± 0.48 hr/d) than HAY (11.98 ± 0.48 hr/d; P < .0001). Chewing rate also differed by forage (PAS 83.92 ± 1.61; HAY 68.50 ± 1.61 chews/min; P < .0001). However, although the magnitude of these behavioral parameters was influenced by treatment, the underlying 24-hour patterns were largely preserved regardless of forage type. These results demonstrate that the EWS can generate data necessary for characterizing feeding behavior in horses. Future studies implementing this tool could provide a greater understanding of biological, environmental, and nutritive factors driving grazing behavior in horses.
Keywords: Chew sensor; EquiWatch; Grazing behavior; RumiWatch.
Copyright © 2020. Published by Elsevier Inc.