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Behavior assessment and applications for BRD diagnosis: beef

Published online by Cambridge University Press:  08 March 2021

John T. Richeson Open the ORCID record for John T. Richeson [Opens in a new window]
John T. Richeson*
Affiliation:
Department of Agricultural Sciences, West Texas A&M University, PO Box 60998, Canyon, TX79016, USA
*
Author for correspondence: John T. Richeson, Department of Agricultural Sciences, West Texas A&M University, PO Box 60998, Canyon, TX79016, USA. E-mail: [email protected]
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Abstract

Assessment of behavior is a longstanding strategy to assist the diagnosis of clinical bovine respiratory disease (BRD) in beef cattle. Cattle with systemic inflammation caused by infectious pathogen(s) display predictable behavioral adaptations compared to healthy cohorts. Behavioral alterations in BRD-affected cattle include lethargy, social isolation, and anorexia. However, behavior assessment to support BRD case definition in the production setting is challenging because: (1) other bovine diseases cause behavior alterations similar to BRD; (2) cattle have inherent prey instinct to disguise sickness behavior during human evaluation; (3) labor constraints dictate very brief observation of animal behavior; and (4) traditional behavior assessment is subjective and agreement is often poor. Some of these challenges may be overcome with the use of advanced technologies that allow continuous, remote, and objective behavior assessment of individual cattle. Automated methodologies for behavior assessment include three-axis accelerometers that quantify physical behaviors, systems that document feeding/watering behavior, and triangulation systems that document spatial behavior. Each of these behavior-monitoring approaches generates unique information and may facilitate early detection of BRD compared to traditional methods. Nevertheless, adoption of behavior assessment technologies for BRD diagnosis in beef operations hinges upon improved detection, positive return on investment, and successful integration within existing BRD management practices.

Keywords

Beef cattlebehaviorbovine respiratory diseasetechnology
Type
Special issue: Papers from Bovine Respiratory Disease Symposium
Information
Animal Health Research Reviews , Volume 21 , Issue 2 , December 2020 , pp. 192 - 195
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Hart, BL (1988) Biological basis of the behavior of sick animals. Neuroscience & Biobehavioral Reviews 12, 123–137.CrossRefGoogle ScholarPubMed
Pillen, JL, Pinedo, PJ, Ives, SE, Covey, TL, Naikare, HK and Richeson, JT (2016) Alteration of activity variables relative to clinical diagnosis of bovine respiratory disease in newly received feedlot cattle. Bovine Practitioner 50, 1–8.Google Scholar
Richeson, JT, Lawrence, TE and White, BJ (2018) Using advanced technologies to quantify beef cattle behavior. Journal of Animal Science 2, 223–229.Google ScholarPubMed
Richeson, JT, Samuelson, KL and Tomczak, DJ (2019) Beef species-ruminant nutrition cactus beef symposium: energy and roughage levels in cattle receiving diets and impacts on health, performance, and immune responses. Journal of Animal Science 97, 3596–3604.CrossRefGoogle Scholar
Taylor, JD, Fulton, RW, Lehenbauer, TW, Step, DL and Confer, AW (2010) The epidemiology of bovine respiratory disease: What is the evidence for predisposing factors? Canadian Veterinary Journal 51, 1095–1102.Google ScholarPubMed
Tennant, TC, Ives, SE, Harper, LB, Renter, DG and Lawrence, TE (2014) Comparison of tulathromycin and tilmicosin on the prevalence and severity of bovine respiratory disease in feedlot cattle in association with feedlot performance, carcass characteristics, and economic factors. Journal of Animal Science 92, 5203–5213.CrossRefGoogle ScholarPubMed
Theurer, ME, Amrine, DE and White, BJ (2013) Remote noninvasive assessment of pain and health status in cattle. Veterinary Clinics: Food Animal 29, 59–74.Google ScholarPubMed
Thompson, PN, Stone, A and Schultheiss, WA (2006) Use of treatment records and lung lesion scoring to estimate the effect of respiratory disease on growth during early and late finishing periods in South African feedlot cattle. Journal of Animal Science 84, 488–498.CrossRefGoogle ScholarPubMed
Tomczak, DJ, Samuelson, KL, Jennings, JS and Richeson, JT (2019) Oral hydration therapy with water and bovine respiratory disease incidence affects rumination behavior, rumen pH, and rumen temperature in high-risk, newly received beef calves. Journal of Animal Science 97, 2015–2024.CrossRefGoogle ScholarPubMed
White, BJ and Renter, DG (2009) Bayesian estimation of the performance of using clinical observations and harvest lung lesions for diagnosing bovine respiratory disease in post-weaned beef calves. The Journal of Veterinary Diagnostic Investigation 21, 446–453.CrossRefGoogle ScholarPubMed
Wittum, TE, Woollen, NE, Perino, LJ and Littledlike, ET (1996) Relationships among treatment for respiratory tract disease, pulmonary lesions evident at slaughter and rate of weight gain in feedlot cattle. Journal of the American Veterinary Medical Association 209, 814–818.Google ScholarPubMed
Wolfger, B, Timsit, E, White, BJ and Orsel, K (2015) A systematic review of bovine respiratory disease diagnosis focused on diagnostic confirmation, early detection, and prediction of unfavorable outcomes in feedlot cattle. Veterinary Clinics: Food Animal 31, 351–365.Google ScholarPubMed