Evidence map›Paper›PMID 35049815›Full record

ArticleAnimals : an open access journal from MDPI2022

The Effect of Rider:Horse Bodyweight Ratio on the Superficial Body Temperature of Horse's Thoracolumbar Region Evaluated by Advanced Thermal Image Processing.

Małgorzata Domino, Marta Borowska, Anna Trojakowska, Natalia Kozłowska, Łukasz Zdrojkowski, Tomasz Jasiński, Graham Smyth, Małgorzata Maśko

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
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  3. Review
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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

8 authors.

Małgorzata DominoDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS-SGGW), 02-787 Warsaw, Poland.ORCID 0000-0001-9436-1074
Marta BorowskaInstitute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, 15-351 Bialystok, Poland.ORCID 0000-0003-0148-9912
Anna TrojakowskaThe Scientific Society of Veterinary Medicine Students, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Natalia KozłowskaDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS-SGGW), 02-787 Warsaw, Poland.ORCID 0000-0002-7140-6310
Łukasz ZdrojkowskiDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS-SGGW), 02-787 Warsaw, Poland.ORCID 0000-0002-4401-9016
Tomasz JasińskiDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS-SGGW), 02-787 Warsaw, Poland.ORCID 0000-0003-2906-9944
Graham SmythMenzies Health Institute Queensland, Griffith University School of Medicine, Southport, QLD 4222, Australia.ORCID 0000-0002-1433-2685
Małgorzata MaśkoDepartment of Animal Breeding, Institute of Animal Science, Warsaw University of Life Sciences (WULS-SGGW), 02-787 Warsaw, Poland.

Funding

Ministry of Science and Higher Education WI/WM-IIB/2/2021
6 · The paper itself

Abstract

Appropriate matching of rider-horse sizes is becoming an increasingly important issue of riding horses' care, as the human population becomes heavier. Recently, infrared thermography (IRT) was considered to be effective in differing the effect of 10.6% and 21.3% of the rider:horse bodyweight ratio, but not 10.1% and 15.3%. As IRT images contain many pixels reflecting the complexity of the body's surface, the pixel relations were assessed by image texture analysis using histogram statistics (HS), gray-level run-length matrix (GLRLM), and gray level co-occurrence matrix (GLCM) approaches. The study aimed to determine differences in texture features of thermal images under the impact of 10-12%, >12 ≤15%, >15 <18% rider:horse bodyweight ratios, respectively. Twelve horses were ridden by each of six riders assigned to light (L), moderate (M), and heavy (H) groups. Thermal images were taken pre- and post-standard exercise and underwent conventional and texture analysis. Texture analysis required image decomposition into red, green, and blue components. Among 372 returned features, 95 HS features, 48 GLRLM features, and 96 GLCH features differed dependent on exercise; whereas 29 HS features, 16 GLRLM features, and 30 GLCH features differed dependent on bodyweight ratio. Contrary to conventional thermal features, the texture heterogeneity measures, InvDefMom, SumEntrp, Entropy, DifVarnc, and DifEntrp, expressed consistent measurable differences when the red component was considered.

Indexed as

body mass indexcolor modelstexture analysisthermograph

Identifiers

PMID35049815
PMCPMC8772910

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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.