A sampling strategy for the determination of infrared temperature of relevant external body surfaces of dairy cows

Abstract

Infrared thermography is a tool to investigate the welfare of cattle. This study aimed to identify a sampling strategy for recording infrared thermograms in dairy cows, in order to most efficiently determine biologically relevant changes in the maximum infrared temperature (IRT) of the eyes and coronary band of forelimbs. Thirty-one dairy cows were used for the study. They were assessed with four replicates of thermograms for each of the head and lower forelimb per cow for 6 mostly consecutive days (sessions). The data obtained were subjected to random effects Analysis of Variance which was used to estimate the variance components for this sampling model, using maximum IRT of both eyes; (left + right eye)/2 and both limbs; (left + right coronary band of forelimb)/2 as dependant variables. The variance components were used to calculate least significant differences (LSD) between two theoretical treatment groups under different sampling scenarios. Analysis showed that there was minimal improvement in precision beyond 2 thermograms within a session but there was improvement with increasing the number of sessions from 2 to 3. The LSD of both eyes and both limbs reached a biologically relevant difference (0.4 and 0.9 °C, respectively) at a minimum number of 14 - 16 cows monitored for 2 consecutive thermography sessions, or 10 – 12 cows for 3 sessions. We conclude that no more than 2 replicate IRT measures are required per session but that measuring on 3 consecutive days should be considered, depending on whether time or number of cows used is the primary limitation.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3

References

  1. Alsaaod M, Syring C, Dietrich J, Doherr MG, Gujan T, Steiner A (2014) A field trial of infrared thermography as a non-invasive diagnostic tool for early detection of digital dermatitis in dairy cows. Vet J 199:281–285. https://doi.org/10.1016/j.tvjl.2013.11.028

    Article  Google Scholar 

  2. Byrne DT, Berry DP, Esmonde H, McHugh N (2017) Temporal, spatial, inter-, and intra-cow repeatability of thermal imaging. J Anim Sci 95:970–979. https://doi.org/10.2527/jas.2016.1005

    Article  Google Scholar 

  3. Byrne DT, Berry DP, Esmonde H, McGovern F, Creighton P, McHugh N (2019) Infrared thermography as a tool to detect hoof lesions in sheep. TAS 3:577–588. https://doi.org/10.1093/tas/txy132

    Article  Google Scholar 

  4. Church JS, Hegadoren PR, Paetkau MJ, Miller CC, Regev-Shoshani G, Schaefer AL, Schwartzkopf-Genswein KS (2014) Influence of environmental factors on infrared eye temperature measurements in cattle. Res Vet Sci 96:220–226. https://doi.org/10.1016/j.rvsc.2013.11.006

    Article  Google Scholar 

  5. George WD, Godfrey RW, Ketring RC, Vinson MC, Willard ST (2014) Relationship among eye and muzzle temperatures measured using digital infrared thermal imaging and vaginal and rectal temperatures in hair sheep and cattle. J Anim Sci 92:4949–4955. https://doi.org/10.2527/jas.2014-8087

    Article  Google Scholar 

  6. Giro A, de Campos Bernardi AC, Junior WB, Lemes AP, Botta D, Romanello N, do Nascimento Barreto A, Garcia AR (2019). Application of microchip and infrared thermography for monitoring body temperature of beef cattle kept on pasture. J Therm Biol 84: 121-128. https://doi.org/10.1016/j.jtherbio.2019.06.009

  7. Gloster J, Ebert K, Gubbins S, Bashiruddin J, Paton DJ (2011) Normal variation in thermal radiated temperature in cattle: implications for foot-and-mouth disease detection. BMC Vet Res 7:73. https://doi.org/10.1186/1746-6148-7-73

    Article  Google Scholar 

  8. Godyń D, Herbut P, Angrecka S (2019) Measurements of peripheral and deep body temperature in cattle–a review. J Therm Biol 79:42–49. https://doi.org/10.1016/j.jtherbio.2018.11.011

    Article  Google Scholar 

  9. Gómez Y, Bieler R, Hankele AK, Zähner M, Savary P, Hillmann E (2018) Evaluation of visible eye white and maximum eye temperature as non-invasive indicators of stress in dairy cows. Appl Anim Behav Sci 198:1–8. https://doi.org/10.1016/j.applanim.2017.10.001

    Article  Google Scholar 

  10. Harris-Bridge G, Young L, Handel I, Farish M, Mason C, Mitchell M, Haskell M (2018) The use of infrared thermography for detecting digital dermatitis in dairy cattle: What is the best measure of temperature and foot location to use? Vet J 237:26–33. https://doi.org/10.1016/j.tvjl.2018.05.008

    Article  Google Scholar 

  11. Herbut P, Angrecka S, Godyn D, Hoffmann G (2019) The physiological and productivity effetcts of heat stress in cattle -a review. Ann Anim Sci 19:579–594. https://doi.org/10.2478/aoas-2019-0011

    Article  Google Scholar 

  12. Hoffmann G, Schmidt M, Ammon C, Rose-Meierhöfer S, Burfeind O, Heuwieser W, Berg W (2013) Monitoring the body temperature of cows and calves using video recordings from an infrared thermography camera. Vet Res Commun 37:91–99. https://doi.org/10.1007/s11259-012-9549-3

    Article  Google Scholar 

  13. Kotrba R, Knížková I, Kunc P, Bartoš L (2007) Comparison between the coat temperature of the eland and dairy cattle by infrared thermography. J Therm Biol 32:355–359. https://doi.org/10.1016/j.jtherbio.2007.05.006

    Article  Google Scholar 

  14. Kou HX, Zhao YQ, Ren K, Chen XL, Lu YQ, Wang D (2017) Automated measurement of cattle surface temperature and its correlation with rectal temperature. PLoS One 12:e0175377. https://doi.org/10.1371/journal.pone.0175377

    Article  Google Scholar 

  15. Lee Y, Bok JD, Lee H, Lee HJ, Kim D, Lee I, Kang SK, Choi YJ (2016) Body temperature monitoring using subcutaneously implanted thermo-loggers from holstein steers. Asian-Australas J Anim Sci 29:299 https://doi.org/10.5713%2Fajas.15.0353

    Article  Google Scholar 

  16. Lees AM, Lees JC, Lisle AT, Sullivan ML, Gaughan JB (2018) Effect of heat stress on rumen temperature of three breeds of cattle. Int J Biometeorol 62:207–215. https://doi.org/10.1007/s00484-017-1442-x

    Article  Google Scholar 

  17. Lees AM, Salvin HE, Colditz I, Lee C (2020) The influence of temperament on body temperature response to handling in angus cattle. Animals 10:172. https://doi.org/10.3390/ani10010172

    Article  Google Scholar 

  18. McCafferty DJ, Gallon S, Nord A (2015) Challenges of measuring body temperatures of free-ranging birds and mammals. Anim Biotelem 3:33. https://doi.org/10.1186/s40317-015-0075-2

    Article  Google Scholar 

  19. McManus C, Tanure CB, Peripolli V, Seixas L, Fischer V, Gabbi AM, Menegassi SRO, Stumpf MT, Kolling GJ, Dias E, Costa JBG Jr (2016) Infrared thermography in animal production: An overview. Comput Electron Agric 123:10–16. https://doi.org/10.1016/j.compag.2016.01.027

    Article  Google Scholar 

  20. Metzner M, Sauter-Louis C, Seemueller A, Petzl W, Klee W (2014) Infrared thermography of the udder surface of dairy cattle: Characteristics, methods, and correlation with rectal temperature. Vet J 199:57–62. https://doi.org/10.1016/j.tvjl.2013.10.030

    Article  Google Scholar 

  21. Montanholi YR, Odongo NE, Swanson KC, Schenkel FS, McBride BW, Miller SP (2008) Application of infrared thermography as an indicator of heat and methane production and its use in the study of skin temperature in response to physiological events in dairy cattle (Bos taurus). J Therm Biol 33:468–475. https://doi.org/10.1016/j.jtherbio.2008.09.001

    Article  Google Scholar 

  22. Montanholi YR, Swanson KC, Palme R, Schenkel FS, McBride BW, Lu D, Miller SP (2010) Assessing feed efficiency in beef steers through feeding behavior, infrared thermography and glucocorticoids. Animal 4:692–701. https://doi.org/10.1017/S1751731109991522

    Article  Google Scholar 

  23. Proctor HS, Carder G (2015) Nasal temperatures in dairy cows are influenced by positive emotional state. Physiol Behav 138:340–344. https://doi.org/10.1016/j.physbeh.2014.11.011

    Article  Google Scholar 

  24. Proctor HS, Carder G (2016) Can changes in nasal temperature be used as an indicator of emotional state in cows? Appl Anim Behav Sci 184:1–6. https://doi.org/10.1016/j.applanim.2016.07.013

    Article  Google Scholar 

  25. Schaefer AL, Cook NJ, Bench C, Chabot JB, Colyn J, Liu T, Okine EK, Stewart M, Webster JR (2012) The non-invasive and automated detection of bovine respiratory disease onset in receiver calves using infrared thermography. Res Vet Sci 93:928–935. https://doi.org/10.1016/j.rvsc.2011.09.021

    Article  Google Scholar 

  26. Sharp DB (1999) Measurement standards. In: John GW (ed) The measurement, instrumentation and sensors handbook. CRC Press, USA, p 5e11 http://www.kelm.ftn.uns.ac.rs/literatura/si/pdf/Measurement%20Instrumentation%20Sensors.pdf

    Google Scholar 

  27. Small JA, Kennedy AD, Kahane SH (2008) Core body temperature monitoring with passive transponder boluses in beef heifers. Can J Anim Sci 88:225–235. https://doi.org/10.4141/CJAS07023

    Article  Google Scholar 

  28. Soerensen DD, Pedersen LJ (2015) Infrared skin temperature measurements for monitoring health in pigs: a review. Acta Vet Scand 57: 5. https://doi.org/10.1186/s13028-015-0094- 2

  29. Sokabe T, Tominaga M (2009) Molecular mechanisms underlying thermosensation in mammals. Brain Nerve 61:867–873

    Google Scholar 

  30. Steketee J (1973) Spectral emissivity of skin and pericardium. Phys Med Biol 18:686–694

    Article  Google Scholar 

  31. Stewart M, Webster JR, Schaefer AL, Cook NJ, Scott SL (2005) Infrared thermography as a non-invasive tool to study animal welfare. Anim Welf 14:319–325

    Google Scholar 

  32. Stewart M, Webster JR, Verkerk GA, Schaefer AL, Colyn JJ, Stafford KJ (2007) Non-invasive measurement of stress in dairy cows using infrared thermography. Physiol Behav 92:520–525. https://doi.org/10.1016/j.physbeh.2007.04.034

    Article  Google Scholar 

  33. Stewart M, Schaefer AL, Haley DB, Colyn J, Cook NJ, Stafford KJ, Webster JR (2008) Infrared thermography as a non-invasive method for detecting fear-related responses of cattle to handling procedures. Anim Welf 17:387–393

    Google Scholar 

  34. Stokes JE, Leach KA, Main DCJ, Whay HR (2012) An investigation into the use of infrared thermography as a rapid diagnostic tool for foot lesions in dairy cattle. Vet J 193:674–678. https://doi.org/10.1016/j.tvjl.2012.06.052

    Article  Google Scholar 

  35. Sykes DJ, Couvillion JS, Cromiak A, Bowers S, Schenck E, Crenshaw M, Ryan PL (2012) The use of digital infrared thermal imaging to detect estrus in gilts. Theriogenology 78:147–152. https://doi.org/10.1016/j.theriogenology.2012.01.030

    Article  Google Scholar 

  36. Taylor NAS, Tipton MJ, Kenny GP (2014) Considerations for the measurement of core, skin and mean body temperatures. J Therm Biol 46:72–101. https://doi.org/10.1016/j.jtherbio.2014.10.006

    Article  Google Scholar 

  37. Tresoldi G, Schütz KE, Tucker CB (2018) Cooling cows with sprinklers: Timing strategy affects physiological responses to heat load. J Dairy Sci 101:11237–11246. https://doi.org/10.3168/jds.2018-14917

    Article  Google Scholar 

  38. Turner TA (1991) Thermography as an aid to the clinical lameness evaluation. Vet Clin N Am-Equine 7:311–338. https://doi.org/10.1016/S0749-0739(17)30502-3

    Article  Google Scholar 

  39. Uddin J, Phillips CJC, Goma AA, McNeill DM (2019) Relationships between infrared temperature and laterality. Appl Anim Behav Sci 220:104855. https://doi.org/10.1016/j.applanim.2019.104855

    Article  Google Scholar 

  40. US Environmental Protection Agency (2002) Guidance for quality assurance project plans EPA QA/G-5. Office of Environmental Information, Washington, DC 20460. EPA/240/R-02/009.

Download references

Acknowledgements

Authors are grateful to the staff of the University of Queensland dairy farm for their assistance. Jashim Uddin was in receipt of a University of Queensland postgraduate study award.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jashim Uddin.

Ethics declarations

Declaration of interest

The authors declare no conflicts of interest.

Ethics statement

All experimental procedures involving animals were approved by the University of Queensland Animal Ethics Committee.

Software and data repository resources

None of the data were deposited in an official repository.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Uddin, J., McNeill, D.M., Lisle, A.T. et al. A sampling strategy for the determination of infrared temperature of relevant external body surfaces of dairy cows. Int J Biometeorol (2020). https://doi.org/10.1007/s00484-020-01939-4

Download citation

Keywords

  • Infrared thermography
  • Variances
  • Least significant difference
  • Welfare