The use of remote monitoring technologies for early detection of lameness in beef bulls during the breeding season

Lameness during the breeding season can impair bulls' reproductive performance, but early detection may enable timely treatments or replacements to mitigate pregnancy losses. This study used remote monitoring technologies to investigate whether changes in beef bulls' behavior could be used for early identification of lameness during the breeding season. Twenty-five Angus bulls (12 in year 1; 13 in year 2) considered satisfactory at the breeding soundness exam were enrolled. Collars with GPS and accelerometers were placed on bulls at the start of the breeding season. Bulls were monitored on pastures by video recording 3 times a week, on alternate days, during 2 breeding seasons to identify signs of lameness. Blinded raters analyzed videos, assigning a locomotion score (LS; 0-3 scale). Bulls with LS 2 or 3 were considered lame. The day lameness was identified was D0, and the xth days prior were D-x (e.g., D-1). Machine learning algorithms were used to estimate behaviors from the accelerometer data, including Activity (AC), Fighting (FI), Grazing (GR), Resting (RE), Ruminating (RU), and Walking (WA). State-space models were used to estimate the GPS trajectory to calculate the distance traveled (DIST), the average velocity (VEL), and the home range (HR). Statistical analyses were performed using generalized mixed-effect models. Behaviors of lame and non-lame bulls within the same period and breeding pasture were compared. 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 of lame bulls were compared to their baseline for each day. Behaviors of non-lame bulls were compared to their baseline during the same period that lame bulls were observed. Lame bulls presented lower AC (D-1, -4.2 percentage points, p.p., P = 0.02), WA (D-2, -2.22 p.p., P = 0.03), DIST (D-1, -1,253 m, P = 0.02), VEL (D-2, -0.015 m/s, P = 0.01; D-1, -0.022 m/s, P < 0.001), and HR (D-1, -158,145 m2 P < 0.001), and higher RU (D-1,+4.4 p.p., P = 0.03) than non-lame bulls. Lame bulls presented a reduction in FI (D-1, -0.66 p.p., P = 0.03), WA (D-3, -2.09 p.p., P = 0.02; D-1, -3.02 p.p., P < 0.001), DIST (D-2, -1,051 m, P = 0.02; D-1, -1,562 m P < 0.001), VEL (D-2, -0.01 m/s, P = 0.04; D-1, -0.02 m/s, P = 0.002), and HR (D-1, -150,189 m2 P = 0.01) prior to lameness. Non-lame bulls presented a reduction in FI (D-3, -1.01 p.p., P < 0.001; D-1, -1.32 p.p., P < 0.001) and an increase in GR (D-3, +3.6 p.p., P < 0.001; D-1, 3 p.p., P = 0.005) within the period lame bulls were identified. Reductions in movement-related metrics (WA, DIST, and VEL) up to 3 days before lameness suggest these metrics may enable earlier lameness detection than visual observation. These results provide insights into key behaviors for early lameness detection in breeding beef bulls and inform future development of monitoring technologies.

Authors

Institutions

Publication Details

Journal
Journal of Animal Science
Published
2026-03-03
DOI
https://doi.org/10.1093/jas/skag072
Primary Topic
Animal Behavior and Welfare Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The use of remote monitoring technologies for early detection of lameness in beef bulls during the breeding season

Edmond A. Pajor, Sayeh Bayat, Mathieu Pruvot, Vinicius A. Camargo et al.
Journal of Animal Science
Animal Behavior and Welfare Studies
article

The use of remote monitoring technologies for early detection of lameness in beef bulls during the breeding season

Edmond A. Pajor, Sayeh Bayat, Mathieu Pruvot, Vinicius A. Camargo, Jennifer M Pearson
article en

Abstract

Lameness during the breeding season can impair bulls' reproductive performance, but early detection may enable timely treatments or replacements to mitigate pregnancy losses. This study used remote monitoring technologies to investigate whether changes in beef bulls' behavior could be used for early identification of lameness during the breeding season. Twenty-five Angus bulls (12 in year 1; 13 in year 2) considered satisfactory at the breeding soundness exam were enrolled. Collars with GPS and accelerometers were placed on bulls at the start of the breeding season. Bulls were monitored on pastures by video recording 3 times a week, on alternate days, during 2 breeding seasons to identify signs of lameness. Blinded raters analyzed videos, assigning a locomotion score (LS; 0-3 scale). Bulls with LS 2 or 3 were considered lame. The day lameness was identified was D0, and the xth days prior were D-x (e.g., D-1). Machine learning algorithms were used to estimate behaviors from the accelerometer data, including Activity (AC), Fighting (FI), Grazing (GR), Resting (RE), Ruminating (RU), and Walking (WA). State-space models were used to estimate the GPS trajectory to calculate the distance traveled (DIST), the average velocity (VEL), and the home range (HR). Statistical analyses were performed using generalized mixed-effect models. Behaviors of lame and non-lame bulls within the same period and breeding pasture were compared. 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 of lame bulls were compared to their baseline for each day. Behaviors of non-lame bulls were compared to their baseline during the same period that lame bulls were observed. Lame bulls presented lower AC (D-1, -4.2 percentage points, p.p., P = 0.02), WA (D-2, -2.22 p.p., P = 0.03), DIST (D-1, -1,253 m, P = 0.02), VEL (D-2, -0.015 m/s, P = 0.01; D-1, -0.022 m/s, P < 0.001), and HR (D-1, -158,145 m2 P < 0.001), and higher RU (D-1,+4.4 p.p., P = 0.03) than non-lame bulls. Lame bulls presented a reduction in FI (D-1, -0.66 p.p., P = 0.03), WA (D-3, -2.09 p.p., P = 0.02; D-1, -3.02 p.p., P < 0.001), DIST (D-2, -1,051 m, P = 0.02; D-1, -1,562 m P < 0.001), VEL (D-2, -0.01 m/s, P = 0.04; D-1, -0.02 m/s, P = 0.002), and HR (D-1, -150,189 m2 P = 0.01) prior to lameness. Non-lame bulls presented a reduction in FI (D-3, -1.01 p.p., P < 0.001; D-1, -1.32 p.p., P < 0.001) and an increase in GR (D-3, +3.6 p.p., P < 0.001; D-1, 3 p.p., P = 0.005) within the period lame bulls were identified. Reductions in movement-related metrics (WA, DIST, and VEL) up to 3 days before lameness suggest these metrics may enable earlier lameness detection than visual observation. These results provide insights into key behaviors for early lameness detection in breeding beef bulls and inform future development of monitoring technologies.

Journal of Animal Science
University of Calgary (CA)
Openalex Percentile: Top 27%
Animal Behavior and Welfare Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.