dairy cows; eye temperature; heat stress; infrared thermography; region of interest; Veterinary (all); General Veterinary
Abstract :
[en] Eye temperature (ET) has long been used for predicting or indicating heat stress in dairy cows. However, the region of interest (ROI) and temperature parameter of the eye have not been standardized and various options were adopted by previous studies. The aim of this study was to determine the best ROI for measuring ET as the predictor of heat stress in dairy cows in consideration of repeatability and validity. The ET of 40 lactating Holstein dairy cows was measured using infrared thermography. The mean and maximum temperature of five ROIs-medial canthus (MC), lateral canthus, eyeball, whole eye (WE), and lacrimal sac (LS)-were manually captured. The results show that the ET of left eyes was slightly higher than that of right eyes. The ET taken in MC, WE, and LS within 2 min had a moderate to substantial repeatability. The maximum temperature obtained at the LS had the highest correlation coefficients with respiration rate and core body temperature (all p < 0.001). Therefore, the maximum temperature of LS should be considered by future studies that want to use ET as the predictor or indicator of heat stress in dairy cows.
Disciplines :
Animal production & animal husbandry Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Shu, Hang ; Université de Liège - ULiège > TERRA Research Centre ; Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China
Li, Yongfeng; Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China ; AgroBioChem/TERRA, Precision Livestock and Nutrition Unit, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
Fang, Tingting; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
Xing, Mingjie; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
Sun, Fuyu; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
Chen, Xiaoyang; Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
Bindelle, Jérôme ; Université de Liège - ULiège > Département GxABT > Ingénierie des productions animales et nutrition
Wang, Wensheng; Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China
Guo, Leifeng; Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China
Language :
English
Title :
Evaluation of the Best Region for Measuring Eye Temperature in Dairy Cows Exposed to Heat Stress.
This study was financed by the Major Science and Technology Program of Inner Mongolia Autonomous Region, Grant Number 2020ZD0004, the Key Research and Development Program of Hebei Province, Grant Number 20327202D, and the Key Research and Development Program of Hebei Province, Grant Number 19220119D.
Stewart M Webster J Schaefer AL Cook N Tracey S. Infrared Thermography as a Non-Invasive Tool to Study Animal Welfare. Anim Welfare. (2005) 14:319–25.
Gómez Y Bieler R Hankele AK Zähner M Savary P Hillmann E. Evaluation of visible eye white and maximum eye temperature as non-invasive indicators of stress in dairy cows. Appl Anim Behav Sci. (2018) 198:1–8. 10.1016/j.applanim.2017.10.001
Fuentes S Gonzalez Viejo C Chauhan SS Joy A Tongson E Dunshea FR. Non-invasive sheep biometrics obtained by computer vision algorithms and machine learning modeling using integrated visible/infrared thermal cameras. Sensors. (2020) 20:6334. 10.3390/s2021633433171995
Kadzere CT Murphy MR Silanikove N Maltz E. Heat stress in lactating dairy cows: a review. Livestock Prod Sci. (2002) 77:59–91. 10.1016/S0301-6226(01)00330-X
Shu H Wang W Guo L Bindelle J. Recent advances on early detection of heat strain in dairy cows using animal-based indicators: a review. Animals. (2021) 11:980. 10.3390/ani1104098033915761
Švejdová K Šoch M Šimková A Zábranský L Novák P Brouček J et al. Measuring the body surface temperature of animals using a thermographic camera. Acta Universitatis Cibiniensis Series E: Food Technology. (2013) 17:99–106. 10.2478/aucft-2013-0017
Pacheco VM Sousa RVd Rodrigues AVDS Sardinha EJdS Martello LS. Thermal imaging combined with predictive machine learning based model for the development of thermal stress level classifiers. Livestock Sci. (2020) 241. 10.1016/j.livsci.2020.104244
Idris M Uddin J Sullivan M McNeill DM Phillips CJC. Non-invasive physiological indicators of heat stress in cattle. Animals. (2021) 11:71. 10.3390/ani1101007133401687
Yan G Li H Zhao W Shi Z. Evaluation of thermal indices based on their relationships with some physiological responses of housed lactating cows under heat stress. Int J Biometeorol. (2020) 64:2077–91. 10.1007/s00484-020-01999-632851452
Peng D Chen S Li G Chen J Wang J Gu X. Infrared thermography measured body surface temperature and its relationship with rectal temperature in dairy cows under different temperature-humidity indexes. Int J Biometeorol. (2019) 63:327–36. 10.1007/s00484-018-01666-x30680628
Brcko CC Silva JARd Martorano LG Vilela RA Nahúm BdS Silva AGM et al. Infrared thermography to assess thermoregulatory reactions of female buffaloes in a humid tropical environment. Front Vet Sci. (2020) 7:180. 10.3389/fvets.2020.0018032596262
Mendoza A Mota-Rojas D Alvarez A Mora-Medina P Trujillo M Morales-Canela A et al. Scientific findings related to changes in vascular microcirculation using infrared thermography in the river buffalo. J Animal Behav Biometeorol. (2018) 8:288–97. 10.31893/jabb.20038
Montanholi YR Lim M Macdonald A Smith BA Goldhawk C Schwartzkopf-Genswein K et al. Technological, environmental and biological factors: referent variance values for infrared imaging of the bovine. J Anim Sci Biotechnol. (2015) 6:27. 10.1186/s40104-015-0027-y26217486
Byrne DT Berry DP Esmonde H McHugh N. Temporal, spatial, inter-, and intra-cow repeatability of thermal imaging. J Anim Sci. (2017) 95:970. 10.2527/jas2016.100528380618
Gloster J Ebert K Gubbins S Bashiruddin J Paton DJ. Normal variation in thermal radiated temperature in cattle: implications for foot-and-mouth disease detection. BMC Vet Res. (2011) 7:73. 10.1186/1746-6148-7-7322104039
de Ruediger FR Yamada PH Bicas Barbosa LG Mungai Chacur MG Pinheiro Ferreira JC de Carvalho NAT et al. Effect of estrous cycle phase on vulvar, orbital area and muzzle surface temperatures as determined using digital infrared thermography in buffalo. Anim Reprod Sci. (2018) 197:154–61. 10.1016/j.anireprosci.2018.08.02330143282
Bleul U Hässig M Kluser F. Screening of febrile cows using a small handheld infrared thermography device. Tierarztliche Praxis Ausgabe G: Grosstiere - Nutztiere. (2021) 49:12–20. 10.1055/a-1307-999333588477
National Research Council. A Guide to Environmental Research on Animals. Washington, DC: National Academy of Science (1971).
Collier RJ Laun WH Rungruang S Zimbleman RB. Quantifying heat stress and its impact on metabolism and performance. In: Proceedings of the Florida Ruminant Nutrition Symposium Gainesville, FL (2012).
Jorquera-Chavez M Fuentes S Dunshea FR Warner RD Poblete T Jongman EC. Modelling and validation of computer vision techniques to assess heart rate, eye temperature, ear-base temperature and respiration rate in cattle. Animals. (2019) 9:1089. 10.3390/ani912108931817620
Jaddoa MA Gonzalez L Cuthbertson H Al-Jumaily A. Multiview eye localisation to measure cattle body temperature based on automated thermal image processing and computer vision. Infrared Phys Technol. (2021) 119:103932. 10.1016/j.infrared.2021.103932
Church J Hegadoren P Paetkau M Miller CC Regev-Shoshani G Schaefer AL et al. Influence of environmental factors on infrared eye temperature measurement in cattle. Res Vet Sci. (2013) 96:220–6. 10.1016/j.rvsc.2013.11.00624290729
Rogers LJ. Relevance of brain and behavioural lateralization to animal welfare. Appl Anim Behav Sci. (2010) 127:1–11. 10.1016/j.applanim.2010.06.008
Phillips CJC Oevermans H Syrett KL Jespersen AY Pearce GP. Lateralization of behavior in dairy cows in response to conspecifics and novel persons. J Dairy Sci. (2015) 98:2389–400. 10.3168/jds.2014-864825648820
Collier RJ Dahl GE VanBaale MJ. Major advances associated with environmental effects on dairy cattle. J Dairy Sci. (2006) 89:1244–53. 10.3168/jds.S0022-0302(06)72193-216537957
Islam MA Lomax S Doughty A Islam MR Jay O Thomson P et al. Automated monitoring of cattle heat stress and its mitigation. Front Animal Sci. (2021) 2:737213. 10.3389/fanim.2021.73721332867225
George WD Godfrey R Ketring RC Vinson MC Willard ST. 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. (2014) 92:4949–55. 10.2527/jas.2014-808725253816
Yan G Liu K Hao Z Li H Shi Z. Development and evaluation of thermal models for predicting skin temperature of dairy cattle. Comput Electron Agric. (2021) 188:106363. 10.1016/j.compag.2021.106363
Uddin J Phillips C Ahmed A McNeill D. Relationships between infrared temperature and laterality. Appl Anim Behav Sci. (2019) 220:104855. 10.1016/j.applanim.2019.104855
Mota-Rojas D Pereira AMF Wang D Martínez-Burnes J Ghezzi M Hernández-Avalos I et al. Clinical applications and factors involved in validating thermal windows used in infrared thermography in cattle and river buffalo to assess health and productivity. Animals. (2021) 11:2247. 10.3390/ani1108224734438705
Dartt DA. Neural regulation of lacrimal gland secretory processes: relevance in dry eye diseases. Prog Retin Eye Res. (2009) 28:155–77. 10.1016/j.preteyeres.2009.04.003 19376264
