Evidence map›Paper›PMID 41245604›Full record

ArticleTranslational animal science2025

Assessment of thermal imaging to objectively body condition score mature horses and multiparous gestating beef cows.

Alexandra P Webster, Ryan K Wright, Jillian B Hammond, Naa A Kotey, Claire B Gleason, Robin R White

Abstract read
In one paragraph

Article in Translational animal science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

6 authors.

Alexandra P WebsterSchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States.ORCID https://orcid.org/0009-0003-0065-4485
Ryan K WrightSchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States.
Jillian B HammondSchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States.
Naa A KoteySchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States.
Claire B GleasonSchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States.
Robin R WhiteSchool of Animal Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explored whether thermal imaging could provide an objective means of body condition scoring (BCS) horses and multiparous, gestating beef cows. This study consisted of two parts: one part assessed BCS in horses of the Quarter Horse or Thoroughbred breed types while the other evaluated BCS of gestating beef cows. Ground truth BCS were assigned by five to eight trained scorers for each animal. Thermal images were also collected from one or both sides of the body and analyzed for surface temperature. Surface temperature and BCS were evaluated with the whole body, and for five (cows) or seven (horses) specific body regions. Covariates were monitored, including breed, ambient temperature, cloud coverage (%), housing conditions, blanketing status, individual scorer, and scorer's location. Considerable between-scorer variation in BCS assigned was apparent in both species, with 58% to 65% of observations falling within 0.5 BCS of the median. Much of the variability was attributable to scoring the degree of BCS deviation from normal, and 72% to 82% of scores agreed in directional accuracy. Scaled, centered scores within 0.5 units of the median BCS were defined as high-agreement data. Random forest regressions were derived to explore how well thermal-camera-obtained body surface temperature data could be used to estimate BCS of horses and cows using either all available data or the subset of high-agreement data. In both datasets, 15% of observations were used for hyperparameter tuning, 55% for model-training, and 30% for independent evaluation. Unique models were created for each body area assigned a BCS for horses (the neck, shoulder, withers, ribs, loin, tailhead, and overall) or beef cows (the brisket, shoulder, ribs and spine, hooks and pins, and overall). Models estimating horse BCS had lower RMSE (6.71% to 10.4%) and higher accuracy (62.7% to 90.3%) than those estimating cow BCS (RMSE: 6.39% to 15.9%; accuracy: 46.8% to 82.5%). Models derived from all data had higher RMSE (7.76% to 15.9%) and lower accuracy (53.8% to 82.3%) compared with those derived from only high-agreement data (RMSE: 5.80% to 8.18%; accuracy: 66.7% to 90.3%). Overall, thermal imaging shows promise as an objective tool for BCS assignment in both horses and beef cows. However, future refinement of the method for assigning BCS ground truth is important.

Indexed as

adipositybeef cattlebody conditionhorsesthermal imaging

Identifiers

PMID41245604
PMCPMC12614166

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.