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Validation and Implementation of an Automated Chew Sensor-Based Remote Monitoring Device as Tool for Equine Grazing Research.
Abstract: 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.
Copyright © 2020. Published by Elsevier Inc.
Publication Date: 2020-03-02 PubMed ID: 32303328DOI: 10.1016/j.jevs.2020.102971Google Scholar: Lookup The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
- Research Support
- Non-U.S. Gov't
- Research Support
- U.S. Gov't
- Non-P.H.S.
Summary
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The study focuses on validating a tool named EquiWatch System (EWS) for monitoring and analyzing equine grazing behavior. The system has shown a high accuracy level in identifying grazing time and chew counts.
Study Overview
The research assessed the validity of the EquiWatch System (EWS), an automated chew sensor technology, for remotely monitoring the grazing activity in horses.
- The study was conducted on eight mature standardbred mares.
- The validation process took place in two experiments. The first experiment looked at the grazing time, while the second was concerned with chew counts.
- Following the validation, a pilot study was carried out to compare the feeding behaviors of horses with unrestricted pasture access (PAS) and those provided with ad libitum hay (HAY).
Validation of the EquiWatch System
The first part of the study aimed at testing whether EWS can accurately detect and record grazing behaviors.
- In Experiment 1, the system-recorded grazing times were compared with visual observations. The concordance correlation coefficient (CCC) was found to be very high (0.997), indicating a strong agreement between the two measurements.
- Experiment 2 compared the manual and EWS recorded chew counts. Here, the CCC was also quite high (0.979), validating the accuracy of the system.
Pilot Study
The pilot study evaluated the feeding behaviors of two different groups of horses.
- Comparisons were made between horses with unrestricted access to pasture and horses feeding on ad libitum hay.
- Horses with pasture access spent more time feeding than those with hay availability.
- The chewing rate was also higher for pasture-fed horses.
- While the type of forage influenced the magnitude of these parameters, the overall 24-hour patterns remained similar across both groups.
Implications and Future Steps
The study’s results validate the efficiency and accuracy of the automated EquiWatch System as a tool for studying equine feeding behavior.
- The EWS has the potential to generate crucial data for characterizing horse feeding habits.
- Future research incorporating this tool may offer insights into biological, environmental, and nutritional factors shaping equine grazing behaviors.
Cite This Article
APA
Weinert JR, Werner J, Williams CA.
(2020).
Validation and Implementation of an Automated Chew Sensor-Based Remote Monitoring Device as Tool for Equine Grazing Research.
J Equine Vet Sci, 88, 102971.
https://doi.org/10.1016/j.jevs.2020.102971 Publication
Researcher Affiliations
- Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ. Electronic address: jennifer.weinert@rutgers.edu.
- Animal Nutrition and Rangeland Management in the Tropics and Subtropics, University of Hohenheim, Stuttgart, Germany.
- Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ.
MeSH Terms
- Animals
- Feeding Behavior
- Female
- Horses
- Mastication
- Pilot Projects
Citations
This article has been cited 7 times.- Petz V, Khiaosa-Ard R, Iben C, Zebeli Q. Changes in eating time, chewing activity and dust concentration in horses fed either alfalfa cubes or long-stem hay. Vet Med Sci 2023 May;9(3):1154-1162.
- Pikuła R, Zaborski D, Grzesiak W, Smugała M. An analysis of the annual mobility of Polish Konik horses depending on habitat, season, and time of the day. Arch Anim Breed 2022;65(3):239-247.
- Weinert-Nelson JR, Meyer WA, Williams CA. Crabgrass as an equine pasture forage: impact of establishment method on yield, nutrient composition, and horse preference. Transl Anim Sci 2022 Apr;6(2):txac050.
- Taylor DEF, Lancaster BE, Ellis AD. Time Budgets in Domesticated Male Icelandic Horses on Pasture Turnout in Winter and Spring. Animals (Basel) 2025 Nov 4;15(21).
- Taylor DEF, Lancaster BE, Ellis AD. The Use of Sound Recorders to Remotely Measure Grass Intake Behaviour in Horses. Animals (Basel) 2025 Aug 4;15(15).
- Torres Borda L, Roth P, Lumetzberger J, Auer U, Jenner F. Proximity tracking using ultra-wideband technology for equine social behaviour research. Sci Rep 2024 Apr 30;14(1):9971.
- Sterkenburgh TR, Hartl B, Peham C, Nowak M, Kyllar M, Kau S. Temporomandibular joint biomechanics and equine incisor occlusal plane maintenance. Front Bioeng Biotechnol 2023;11:1249316.
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