The use of digital infrared thermography and measurement of oxidative stress biomarkers as tools to diagnose foot lesions in sheep

Talukder, Saranika; Gabai, Gianfranco; Celi, Pietro

doi:10.1016/j.smallrumres.2015.04.006

Cited by 24 publications

(25 citation statements)

References 43 publications

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“…In the present study, the greater level of BAP in cows with a locomotion score of 1.0 supports our previous findings of greater concentration of BAP in healthy rams compared to rams with lesions in hooves (Talukder et al, 2015a). Primiparous cows had lower levels of ceruloplasmin compared to multiparous cows.…”

Section: Lpo (Nanoeq Of Hydroperoxides/ml)supporting

confidence: 91%

Changes in milk oxidative stress biomarkers in lactating dairy cows with ovulatory and an-ovulatory oestrous cycles

Talukder

Kerrisk

Gabai

et al. 2015

Animal Reproduction Science

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Section: Lpo (Nanoeq Of Hydroperoxides/ml)supporting

confidence: 91%

Changes in milk oxidative stress biomarkers in lactating dairy cows with ovulatory and an-ovulatory oestrous cycles

Talukder

Kerrisk

Gabai

et al. 2015

Animal Reproduction Science

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“…Previous research successfully used IRT to detect lameness in cattle ( Alsaaod et al, 2015 ), respiratory disease in calves ( Schaefer et al, 2012 ), and breast cancer in humans ( Milosevic et al, 2014 ). In sheep, Talukder et al (2015) used 15 rams to demonstrate an association between hoof temperature and hoof lesions, but did not test the ability of IRT to diagnose individual hooves. Other studies have shown how ambient temperature can affect the temperature of an anatomical region, and if left unaccounted for, the diagnostic ability of IRT ( Berry et al, 2003 ; Church et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Infrared thermography as a tool to detect hoof lesions in sheep

Byrne

Berry

Esmonde

et al. 2018

Translational Animal Science

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Lameness has a major negative impact on sheep production. The objective of this study was to 1) quantify the repeatability of sheep hoof temperatures estimated using infrared thermography (IRT); 2) determine the relationship between ambient temperature, sheep hoof temperature, and sheep hoof health status; and 3) validate the use of IRT to detect infection in sheep hooves. Three experiments (a repeatability, exploratory, and validation experiment) were conducted over 10 distinct nonconsecutive days. In the repeatability experiment, 30 replicate thermal images were captured from each of the front and back hooves of nine ewes on a single day. In the exploratory experiment, hoof lesion scores, locomotion scores, and hoof thermal images were recorded every day from the same cohort of 18 healthy ewes in addition to a group of lame ewes, which ranged from one to nine ewes on each day. Hoof lesion and locomotion scores were blindly recorded by three independent operators. In the validation experiment, all of the same procedures from the exploratory experiment were applied to a new cohort of 40 ewes across 2 d. The maximum and average temperature of each hoof was extracted from the thermal images. Repeatability of IRT measurements was assessed by partitioning the variance because of ewe and error using mixed models. The relationship between ambient temperature, hoof temperature, and hoof health status was quantified using mixed models. The percentage of hooves correctly classified as healthy (i.e., specificity) and infected (i.e., sensitivity) was calculated for a range of temperature thresholds. Results showed that a small-to-moderate proportion of the IRT-estimated temperature variability in a given hoof was due to error (1.6% to 20.7%). A large temperature difference (8.5 °C) between healthy and infected hooves was also detected. The maximum temperature of infected hooves was unaffected by ambient temperature (P > 0.05), whereas the temperature of healthy hooves was associated with ambient temperature. The best sensitivity (92%) and specificity (91%) results in the exploratory experiment were observed when infected hooves were defined as having a maximum hoof temperature ≥9 °C above the average of the five coldest hooves in the flock on that day. When the same threshold was applied to the validation dataset, a sensitivity of 77% and specificity of 78% was achieved, indicating that IRT could have the potential to detect infection in sheep hooves.

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“…Similarly, in sheep, the performance was considerably better than obtained using infra-red technologies (sensitivity of 83% and specificity of 78%). 18 This method of lameness detection has the potential to be implemented as an automatic diagnostic tool for use in "precision farming" applications. Detection of lame animals would be by continuous, contactless and labour-free monitoring by placing the radar at strategic places (e.g.…”

Section: Discussionmentioning

confidence: 99%

“…The current "gold-standard" method to quantify the occurrence of lameness is by whole herd/flock visual locomotion, or mobility scoring, which, in both species, is subjective, requiring training to be sufficiently reliable, 13,14 and is labourintensive. 9,12 Recent technological advancements 15,16 have, with varying degrees of success, enabled the development of objective methods for detection of lameness, 17 such as infra-red technologies, 18,19 intra-ruminal boluses, 20 force-plate systems, 21 3D-accelerometers and tracking combined with modelling from vision-based and optoelectronic systems. 22 Although providing alternative detection methods, they require the individual provision of potentially costly devices or for animals to be restrained.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of lameness detection using radar sensing in ruminants

et al. 2019

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BackgroundLameness is a major health, welfare and production-limiting condition for the livestock industries. The current ‘gold-standard’ method of assessing lameness by visual locomotion scoring is subjective and time consuming, whereas recent technological advancements have enabled the development of alternative and more objective methods for its detection.MethodsThis study evaluated a novel lameness detection method using micro-Doppler radar signatures to categorise animals as lame or non-lame. Animals were visually scored by veterinarian and radar data were collected for the same animals.ResultsA machine learning algorithm was developed to interpret the radar signatures and provide automatic classification of the animals. Using veterinary scoring as a standard method, the classification by radar signature provided 85 per cent sensitivity and 81 per cent specificity for cattle and 96 per cent sensitivity and 94 per cent specificity for sheep.ConclusionThis radar sensing method shows promise for the development of a highly functional, rapid and reliable recognition tool of lame animals, which could be integrated into automatic, on-farm systems for sheep and cattle.

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The use of digital infrared thermography and measurement of oxidative stress biomarkers as tools to diagnose foot lesions in sheep

Cited by 24 publications

References 43 publications

Changes in milk oxidative stress biomarkers in lactating dairy cows with ovulatory and an-ovulatory oestrous cycles

Changes in milk oxidative stress biomarkers in lactating dairy cows with ovulatory and an-ovulatory oestrous cycles

Infrared thermography as a tool to detect hoof lesions in sheep

Evaluation of lameness detection using radar sensing in ruminants

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