Grad Student Competition
Behavioral changes in beef bulls preceding lameness events during the breeding season: Insights from remote monitoring technologies
| Date/Time: |
9/12/2025
09:00
|
| Author: |
Vinicius A Camargo |
| Clinic: |
University of Calgary |
| City, State, ZIP: |
Calgary, AB T2N 4N1 |
V.A. Camargo, DVM, MSc.
1
;
E.A. Pajor, PhD
1
;
J.M. Pearson, DVM, PhD, DACT
1
;
1Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, T2N 4N1, Canada
Introduction:
Lameness during the breeding season can impair the reproductive performance of beef bulls. Early detection can reduce the impact of these events by enabling timely treatments or replacements of bulls to minimize disruptions in breeding activity. This study used remote monitoring technologies to investigate if changes in beef bulls' behavior could be used to identify lameness events during the breeding season.
Materials and methods:
Twenty-five Angus bulls (12 in year 1; 13 in year 2) ranging in age from 1-6 years old were enrolled. All bulls passed the breeding soundness exam. At the start of the breeding season, collars with GPS (set to collect 1 location every 5 min) and accelerometers (set to sample at 1 Hz) were deployed on bulls. Bulls were monitored on pastures 3 times a week during two breeding seasons to identify signs of lameness through video recording, starting on the day they were moved to breeding pastures until they were removed 62 days later. After the breeding season, raters blinded to any event recorded during the breeding season analyzed videos, and assigned a locomotion score (LS; Zinpro Step-Up Lameness Management Program). Bulls with LS 2 or 3 (scale 0-3) were considered lame. Other signs of musculoskeletal injury (e.g., visible swelling and difficulty walking not covered by the LS description) were checked visually during video recording observations. The day that lameness was identified was considered to be D0, and the days prior were D- (e.g., D-1, D-2, and D-3). Day 0 was not included in the analysis as some bulls were removed or treated on pasture when identified by ranch staff as being lame on the same day. Machine learning algorithms were used to predict the individual behaviors of bulls from the accelerometer data (Activity: AC, Fighting: FI, Grazing: GR, Resting: RE, Ruminating: RU, and Walking: WA) and reported as proportion of time expressing that behavior in a 24 hour period. State-space models were used to estimate GPS trajectory to calculate the distance traveled per day (DIST, m), the average velocity per day (VEL m/s), and the home range per day (HR, m2). The baseline of each bull was calculated for all behaviors using the average of D-14 to D-4. All behaviors from D-3 to D-1 were compared to their baseline, day by day, using generalized mixed-effect models while accounting for covariates (pasture, year, age, and body weight). Lastly, a least squares mean analysis with Bonferroni corrections was conducted.
Results:
In total, 11 lameness events were identified. One bull was identified as lame in both years and was removed in year 2 to maintain independence, resulting in 10 lame bulls. Due to sensor malfunction, one day of two bulls were removed from the analysis. A significant reduction in FI (-0.66 p.p., P=0.03) was observed in D-1. No significant difference in GR (P≥0.16), RE (P=1.0), and RU (P≥0.6) were observed. Walking showed the earliest detectable change from all individual behaviors with a reduction on D-3 (-2.09 p.p., P=0.02) and D-1 (-3.02 p.p., P<0.001), although no difference on D-2 (P=0.14). Distance traveled had a reduction on D-2 (-1,051 m, P=0.02) and D-1 (-1,562 m, P<0.001). A reduction in VEL was observed as early as D-2 (-0.01 m/s, P=0.04), further decreasing on D-1 (-0.02 m/s, P=0.002). The reduction in HR was only significant on D-1 (-150,189 m2, P=0.01).
Significance:
A reduction in behaviors related to movement, such as WA, DIST, and VEL, was detected up to two days before lameness was visually identified. These results provide insights into behaviors to be monitored for early identification of lameness in breeding beef bulls and the future development of technology for remote monitoring of animal behavior. Early detection of lameness in bulls prior to visual identification and either removal, replacement, or treatment may decrease potential impacts on reproductive performance.
