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Different methods of processing thermographic images to evaluate the carpal temperature of healthy calves

Authors :
Pedro Augusto Cordeiro Borges
Danilo Conrado Silva
Nivan Antônio Alves da Silva
Valesca Henrique Lima
Paulo José Bastos Queiroz
Naida Cristina Borges
Luiz Antônio Franco da Silva
Source :
Ciência Animal Brasileira, Vol 23 (2022)
Publication Year :
2022
Publisher :
Universidade Federal de Goiás, 2022.

Abstract

The aim of this study was to compare three methods of processing thermographic images for the evaluation of carpal temperature in healthy calves. Additionally, we sought to evaluate the thermal symmetry between the contralateral carpi of these calves. Thermographic images were obtained from both carpi of eight healthy calves aged between 20 and 45 days with a mean weight of 38.65 ± 2.27 kg. Using GRAYESS® IRT Analyzer 7 software, the total temperature (Ttot), region-of-interest temperature (Troi), and maximum mean temperature (Tmax) were determined. There was no difference between the temperatures obtained by the Ttot and Troi methods. Tmax showed higher temperatures (p < 0.01) than the other methods. The three image processing methods showed high and significant positive correlations for the temperature of the right and left carpi of healthy calves. Tmax presented a higher correlation coefficient (r = 0.99) than the two other methods, which suggests a greater sensitivity for identifying thermal variations among the contralateral carpi. The 99% confidence interval for the difference between the temperatures of the right and left carpi (Δr-l) was between 0.03 and 0.26°C; thus, a temperature variation within that range does not refer to pathologic processes. Key words: cattle; joint; thermal symmetry; thermography

Subjects

Subjects :
Agriculture
Animal culture
SF1-1100

Details

Language :
English, Portuguese
ISSN :
15182797 and 18096891
Volume :
23
Database :
Directory of Open Access Journals
Journal :
Ciência Animal Brasileira
Publication Type :
Academic Journal
Accession number :
edsdoj.0216a89b3ba847769edfd123b1516d59
Document Type :
article