Evaluation of infrared thermography compared to rectal temperature to identify illness in early postpartum dairy cows.


Journal

Research in veterinary science
ISSN: 1532-2661
Titre abrégé: Res Vet Sci
Pays: England
ID NLM: 0401300

Informations de publication

Date de publication:
Aug 2019
Historique:
received: 26 03 2019
revised: 12 07 2019
accepted: 17 07 2019
pubmed: 29 7 2019
medline: 21 11 2019
entrez: 29 7 2019
Statut: ppublish

Résumé

This study evaluated and compared infrared thermography (IRT) and rectal temperature (RT) as screening tests to identify sick transition dairy cows. Holstein cows (n = 72; 42 primiparous) had RT and IRT temperatures taken daily from 1 to 12 days in milk (DIM). Health examinations were performed daily to diagnose retained fetal membrane, milk fever and metritis, and blood was analyzed for β-hydroxybutyrate at 6 and 9 DIM to diagnose ketosis. Plasma concentrations of cortisol, interleukin-6, tumor necrosis factor α and serum amyloid A at 3, 6, 9 and 12 DIM were included as additional indicators of illness. Cows were categorized as true sick if clinically diagnosed with an illness, or if at least 2 blood parameters were above the normal range. Diagnostic test performances for RT and IRT variables were determined for each variable at a test referent value that provided the highest Youden's (J) index. The best performing screening test depended on the definition of true sickness. In general, the J index for RT was 0.15-0.17 whereas the highest J index for the IRT variables was 0.22 for the mean eye temperature and 0.19 for the mean cheek temperature. Infrared thermography was at least comparable to RT and some IRT variables performed better as a screening tests than RT. Future studies into the automation of IRT for surveillance of early postpartum diseases is warranted.

Identifiants

pubmed: 31352280
pii: S0034-5288(19)30323-6
doi: 10.1016/j.rvsc.2019.07.017
pii:
doi:

Types de publication

Comparative Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

315-322

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

Auteurs

K Macmillan (K)

Livestock Systems Section, Alberta Agriculture and Forestry, Edmonton, Alberta T6H 5T6, Canada.

M G Colazo (MG)

Livestock Systems Section, Alberta Agriculture and Forestry, Edmonton, Alberta T6H 5T6, Canada.

N J Cook (NJ)

Livestock Systems Section, Alberta Agriculture and Forestry, Edmonton, Alberta T6H 5T6, Canada. Electronic address: nigel.cook@gov.ab.ca.

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Classifications MeSH