Evidence map›Paper›PMID 41803644›Full record

ArticleJournal of animal science2026

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

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

Abstract read
In one paragraph

Article in Journal of animal science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Vinicius A CamargoFaculty of Veterinary Medicine, University of Calgary, Calgary, Alberta T2N 1N4, Canada.ORCID 0000-0002-0281-0053
Edmond A PajorFaculty of Veterinary Medicine, University of Calgary, Calgary, Alberta T2N 1N4, Canada.
Mathieu PruvotFaculty of Veterinary Medicine, University of Calgary, Calgary, Alberta T2N 1N4, Canada.
Sayeh BayatDepartment of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada.
Jennifer M PearsonFaculty of Veterinary Medicine, University of Calgary, Calgary, Alberta T2N 1N4, Canada.ORCID 0000-0002-4481-8731

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Cattle DiseasesLameness, AnimalRemote Sensing TechnologyAccelerometryAnimalsBreedingCattleGeographic Information SystemsMaleSeasonsVideo Recordingaccelerometeranimal movementbeef cattleGPSlocomotion scoreprecision livestock farming

Identifiers

PMID41803644
PMCPMC13049184

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.