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Rumination time and monitoring of health disorders during early lactation

Published online by Cambridge University Press:  16 November 2017

S. Paudyal ,
F. P. Maunsell ,
J. T. Richeson ,
C. A. Risco ,
D. A. Donovan  and
P. J. Pinedo
S. Paudyal
Affiliation:
Department of Agricultural Sciences, West Texas A&M University, Canyon, TX 79016, USA
F. P. Maunsell
Affiliation:
Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL 32610, USA
J. T. Richeson
Affiliation:
Department of Agricultural Sciences, West Texas A&M University, Canyon, TX 79016, USA
C. A. Risco
Affiliation:
Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL 32610, USA
D. A. Donovan
Affiliation:
Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL 32610, USA
P. J. Pinedo*
Affiliation:
Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523, USA
*
†E-mail: pablo.pinedo@colostate.edu
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Abstract

The objective was to evaluate the association between changes in daily rumination time (dRT) and early stages of disease during early lactation and to assess the performance of two proposed disease detection indices. This cohort study included 210 multiparous Holstein cows at the University of Florida Dairy Unit. Cows were affixed with a neck collar containing rumination loggers providing rumination time. The occurrence of health disorders (mastitis, metritis, clinical hypocalcemia, depression/dehydration/fever (DDF), digestive conditions, lameness and clinical ketosis) was assessed until 60 days in milk. Two indices were developed to explore the association between dRT and disease: (i) Cow index (CIx), based on changes in dRT in the affected cow during the days before the diagnosis of health disorders; (ii) Mates index (MIx), index based on deviations in dRT relative to previous days and healthy pen mate cohorts. Subsequently, an alert model was proposed for each index (ACIx and AMIx) considering the reference alert cut-off values as the differences between average index values in healthy and sick cows for each specific disease. The sensitivity (SE) of ACIx detecting disease ranged from 42% (digestive conditions and DDF) to 80% (clinical hypocalcemia) with 84% specificity (SP). The SE of AMIx ranged from 46% (digestive conditions and DDF) to 100% (clinical hypocalcemia) with 85% SP. Consistent reductions in rumination activity, both within cow and relative to healthy mate cohorts, were observed for each health disorder at the day of diagnosis. However, the ability of the proposed algorithms for detecting each specific disease was variable.

Keywords

bovinehealthruminationmonitoringdairy

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Type
Research Article
Information
animal , Volume 12 , Issue 7 , July 2018 , pp. 1484 - 1492
Copyright
© The Animal Consortium 2017 

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References

Barkema, HW, Von Keyserlingk, MA, Kastelic, JP, Lam, TJ, Luby, C, Roy, JP, LeBlanc, SJ, Keefe, GP and Kelton, DF 2015. Invited review: changes in the dairy industry affecting dairy cattle health and welfare. Journal of Dairy Science 98, 7426–7445.Google Scholar
Braun, U, Tschoner, T, Nydegger, F and Hässig, M 2013. Evaluation of eating and rumination behaviour in cows using a noseband pressure sensor. BMC Veterinary Research 9, 195.Google Scholar
Büchel, S and Sundrum, A 2014. Short communication: decrease in rumination time as an indicator of the onset of calving. Journal of Dairy Science 97, 3120–3127.CrossRefGoogle ScholarPubMed
Calamari, LU, Soriani, N, Panella, G, Petrera, F, Minuti, A and Trevisi, ER 2014. Rumination time around calving: an early signal to detect cows at greater risk of disease. Journal of Dairy Science 97, 3635–3647.Google Scholar
Clark, CE, Lyons, NA, Millapan, L, Talukder, S, Cronin, GM, Kerrisk, KL and Garcia, SC 2015. Rumination and activity levels as predictors of calving for dairy cows. Animal 9, 691–695.Google Scholar
Dohoo, I, Martin, W and Stryhn, H 2009. Veterinary epidemiologic research, 2nd edition. AVC Inc., Canada.Google Scholar
Espadamala, A, Pallares, P, Lago, A and Silva-Del-Rio, N 2016. Fresh cow-handling practices and methods for identification of health disorders on 45 dairy farms in California. Journal of Dairy Science 99, 9319–9333.CrossRefGoogle ScholarPubMed
Firk, R, Stamer, E, Junge, W and Krieter, J 2002. Automation of oestrus detection in dairy cows: a review. Livestock Production Science 75, 219–232.CrossRefGoogle Scholar
Fitzpatrick, CE, Chapinal, N, Petersson-Wolfe, CS, DeVries, TJ, Kelton, DF, Duffield, TF and Leslie, KE 2013. The effect of meloxicam on pain sensitivity, rumination time, and clinical signs in dairy cows with endotoxin-induced clinical mastitis. Journal of Dairy Science 96, 2847–2856.Google Scholar
Greiner, M, Pfeiffer, D and Smith, RD 2000. Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Preventive Veterinary Medicine 45, 23–41.Google Scholar
Guterbock, WM 2004. Diagnosis and treatment programs for fresh cows. Veterinary Clinics of North America: Food Animal Practice 20, 605–626.Google Scholar
Hansen, SS, Nørgaard, P, Pedersen, C, Jørgensen, RJ, Mellau, LS and Enemark, JD 2003. The effect of subclinical hypocalcaemia induced by Na2EDTA on the feed intake and chewing activity of dairy cows. Veterinary Research Communications 27, 193–205.CrossRefGoogle ScholarPubMed
Herskin, MS, Munksgaard, L and Ladewig, J 2004. Effects of acute stressors on nociception, adrenocortical responses and behavior of dairy cows. Physiology and Behavior 83, 411–420.Google Scholar
Huzzey, JM, Von Keyserlingk, MA and Weary, DM 2005. Changes in feeding, drinking, and standing behavior of dairy cows during the transition period. Journal of Dairy Science 88, 2454–2461.Google Scholar
Kamphuis, C, DelaRue, B, Burke, CR and Jago, J 2012. Field evaluation of 2 collar-mounted activity meters for detecting cows in estrus on a large pasture-grazed dairy farm. Journal of Dairy Science 95, 3045–3056.CrossRefGoogle ScholarPubMed
Kamphuis, C, Dela Rue, B, Mein, G and Jago, J 2013. Development of protocols to evaluate in-line mastitis-detection systems. Journal of Dairy Science 96, 4047–4058.Google Scholar
Kaufman, EI, LeBlanc, SJ, McBride, BW, Duffield, TF and DeVries, TJ 2016. Association of rumination time with subclinical ketosis in transition dairy cows. Journal of Dairy Science 99, 5604–5618.CrossRefGoogle ScholarPubMed
King, MTM, Dancy, KM, LeBlanc, SJ, Pajor, EA and DeVries, TJ 2017. Deviations in behavior and productivity data before diagnosis of health disorders in cows milked with an automated system. Journal of Dairy Science 100, 1–14.CrossRefGoogle ScholarPubMed
Kononoff, PJ, Lehman, HA and Heinrichs, AJ 2002. Technical note—a comparison of methods used to measure eating and ruminating activity in confined dairy cattle. Journal of Dairy Science 85, 1801–1803.Google Scholar
Krause, KM and Oetzel, GR 2006. Understanding and preventing subacute ruminal acidosis in dairy herds: a review. Animal Feed Science and Technology 126, 215–236.Google Scholar
LeBlanc, SJ, Lissemore, KD, Kelton, DF, Duffield, TF and Leslie, KE 2006. Major advances in disease prevention in dairy cattle. Journal of Dairy Science 89, 1267–1279.Google Scholar
Liboreiro, DN, Machado, KS, Silva, PR, Maturana, MM, Nishimura, TK, Brandão, AP, Endres, MI and Chebel, RC 2015. Characterization of peripartum rumination and activity of cows diagnosed with metabolic and uterine diseases. Journal of Dairy Science 98, 6812–6827.Google Scholar
National Research Council (NRC) 2001. Nutrient requirements of dairy cattle, 7th edition. National Academy Press, Washington, DC, USA.Google Scholar
Ospina, PA, Nydam, DV, Stokol, T and Overton, TR 2010. Evaluation of nonesterified fatty acids and β-hydroxybutyrate in transition dairy cattle in the northeastern United States: critical thresholds for prediction of clinical diseases. Journal of Dairy Science 93, 546–554.Google Scholar
Pahl, C, Hartung, E, Grothmann, A, Mahlkow-Nerge, K and Haeussermann, A 2014. Rumination activity of dairy cows in the 24 hours before and after calving. Journal of Dairy Science 97, 6935–6941.CrossRefGoogle ScholarPubMed
Paudyal, S, Maunsell, F, Richeson, J, Risco, C, Donovan, A and Pinedo, P 2016. Peripartal rumination dynamics and health status in cows calving in hot and cool seasons. Journal of Dairy Science 99, 9057–9068.Google Scholar
Schirmann, K, Chapinal, N, Weary, DM, Vickers, L and Von Keyserlingk, MA 2013. Short communication: rumination and feeding behavior before and after calving in dairy cows. Journal of Dairy Science 96, 7088–7092.Google Scholar
Schirmann, K, von Keyserlingk, MA, Weary, DM, Veira, DM and Heuwieser, W 2009. Technical note: validation of a system for monitoring rumination in dairy cows. Journal of Dairy Science 92, 6052–6055.Google Scholar
Siivonen, J, Taponen, S, Hovinen, M, Pastell, M, Lensink, BJ, Pyörälä, S and Hänninen, L 2011. Impact of acute clinical mastitis on cow behaviour. Applied Animal Behaviour Science 132, 101–106.Google Scholar
Soriani, N, Trevisi, E and Calamari, L 2012. Relationships between rumination time, metabolic conditions, and health status in dairy cows during the transition period. Journal of Animal Science 90, 4544–4554.CrossRefGoogle ScholarPubMed
Stangaferro, ML, Wijma, R, Caixeta, LS, Al-Abri, MA and Giordano, JO 2016a. Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part I. Metabolic and digestive disorders. Journal of Dairy Science 99, 7395–7410.Google Scholar
Stangaferro, ML, Wijma, R, Caixeta, LS, Al-Abri, MA and Giordano, JO 2016b. Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part II. Mastitis. Journal of Dairy Science 99, 7411–7421.CrossRefGoogle ScholarPubMed
Stangaferro, ML, Wijma, R, Caixeta, LS, Al-Abri, MA and Giordano, JO 2016c. Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part III. Metritis. Journal of Dairy Science 99, 7422–7433.Google Scholar
Steeneveld, W, Vernooij, JCM and Hogeveen, H 2015. Effect of sensor systems for cow management on milk production, somatic cell count, and reproduction. Journal of Dairy Science 98, 3896–3905.Google Scholar
Steensels, M, Antler, A, Bahr, C, Berckmans, D, Maltz, E and Halachmi, I 2016. A decision-tree model to detect post-calving diseases based on rumination, activity, milk yield, body weight and voluntary visits to the milking robot. Animal 10, 1493–1500.Google Scholar
Sterrett, AE, Wadsworth, BA, Harmon, RJ, Arnold, M, Clark, JD, Aalseth, EP, Ray, DL and Bewley, JM 2014. Detection of subclinical milk fever and ketosis in fresh dairy cows using rumination time, lying time, reticulorumen temperature, and neck activity. Journal of Dairy Science 97 (suppl. 1), 574.Google Scholar
van Hertem, T, Maltz, E, Antler, A, Romanini, CEB, Viazzi, S, Bahr, C, Schlageter-Tello, A, Lokhorst, C, Berckmans, D and Halachmi, I 2013. Lameness detection based on multivariate continuous sensing of milk yield, rumination, and neck activity. Journal of Dairy Science 96, 4286–4298.Google Scholar