Broad-spectrum infrared thermography for detection of M2 digital dermatitis lesions on hind feet of standing dairy cattle

PLoS One. 2023 Jan 17;18(1):e0280098. doi: 10.1371/journal.pone.0280098. eCollection 2023.

Abstract

Low-effort, reliable diagnostics of digital dermatitis (DD) are needed, especially for lesions warranting treatment, regardless of milking system or hygienic condition of the feet. The primary aim of this study was to test the association of infrared thermography (IRT) from unwashed hind feet with painful M2 lesions under farm conditions, with lesion detection as ultimate goal. Secondary objectives were to determine the association between IRT from washed feet and M2 lesions, and between IRT from unwashed and washed feet and the presence of any DD lesion. A total of 641 hind feet were given an M-score and IRT images of the plantar pastern were captured. Multivariable logistic regression analyses were done with DD status as dependent variable and maximum infrared temperature (IRTmax), lower leg cleanliness score and locomotion score as independent variables, and farm as fixed effect. To further our understanding of IRTmax within DD status, we divided IRTmax into two groups over the median value of IRTmax in the datasets of unwashed and washed feet, respectively, and repeated the multivariable logistic regression analyses. Higher IRTmax from unwashed hind feet were associated with M2 lesions or DD lesions, in comparison with feet without an M2 lesion or without DD, adjusted odds ratio 1.6 (95% CI 1.2-2.2) and 1.1 (95% CI 1.1-1.2), respectively. Washing of the feet resulted in similar associations. Dichotomization of IRTmax substantially enlarged the 95% CI for the association with feet with M2 lesions indicating that the association becomes less reliable. This makes it unlikely that IRTmax alone can be used for automated detection of feet with an M2 lesion. However, IRTmax can have a role in identifying feet at-risk for compromised foot health that need further examination, and could therefore function as a tool aiding in the automated monitoring of foot health on dairy herds.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cattle
  • Cattle Diseases* / diagnosis
  • Cattle Diseases* / pathology
  • Dairying / methods
  • Digital Dermatitis* / diagnosis
  • Digital Dermatitis* / pathology
  • Foot Diseases* / diagnosis
  • Foot Diseases* / pathology
  • Foot Diseases* / veterinary
  • Hoof and Claw* / pathology
  • Thermography / methods

Grants and funding

This study was funded by CAAP (Canadian Agriculture Adaptation Program; Canada; http://omaf.gov.on.ca/english/food/industry/can-agri-adapt.htm), Alberta Milk (Edmonton, Alberta, Canada; https://albertamilk.com/), and DeLaval Manufacturing (Kansas City, Missouri, United States of America; https://www.delaval.com/en-us/) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.