Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-23T11:33:52.475Z Has data issue: false hasContentIssue false
  • English
  • Français

Rumination time as a potential predictor of common diseases in high-productive Holstein dairy cows

Published online by Cambridge University Press:  20 November 2017

Riccardo Moretti ,
Stefano Biffani ,
Francesco Tiezzi ,
Christian Maltecca ,
Stefania Chessa  and
Riccardo Bozzi
Riccardo Moretti*
Affiliation:
Dipartimento di Scienze delle Produzioni Agroalimentari e dell'Ambiente, Università di Firenze, Firenze, 50144, Italy
Stefano Biffani
Affiliation:
Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Lodi, 26900, Italy
Francesco Tiezzi
Affiliation:
Department of Animal Science, North Carolina State University, Raleigh 27695-7621, USA
Christian Maltecca
Affiliation:
Department of Animal Science, North Carolina State University, Raleigh 27695-7621, USA
Stefania Chessa
Affiliation:
Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Lodi, 26900, Italy
Riccardo Bozzi
Affiliation:
Dipartimento di Scienze delle Produzioni Agroalimentari e dell'Ambiente, Università di Firenze, Firenze, 50144, Italy
*
*For correspondence; e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

We examined the hypothesis that rumination time (RT) could serve as a useful predictor of various common diseases of high producing dairy cows and hence improve herd management and animal wellbeing. We measured the changes in rumination time (RT) in the days before the recording of diseases (specifically: mastitis, reproductive system diseases, locomotor system issues, and gastroenteric diseases). We built predictive models to assess the association between RT and these diseases, using the former as the outcome variable, and to study the effects of the latter on the former. The average Pseudo-R2 of the fitted models was moderate to low, and this could be due to the fact that RT is influenced by other additional factors which have a greater effect than the predictors used here. Although remaining in a moderate-to-low range, the average Pseudo-R2 of the models regarding locomotion issues and gastroenteric diseases was higher than the others, suggesting the greater effect of these diseases on RT. The results are encouraging, but further work is needed if these models are to become useful predictors.

Keywords

Ruminationanimal welfaredairy cowpredictive model
Type
Research Article
Information
Journal of Dairy Research , Volume 84 , Issue 4 , November 2017 , pp. 385 - 390
Copyright
Copyright © Hannah Research Foundation 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

Current affiliation: Associazione Italiana Allevatori (AIA), Rome, 00161, Italy.

References

Bates, D, Mächler, M, Bolker, B & Walker, S 2015 Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67 1–48 Google Scholar
Beauchemin, KA 1991 Ingestion and mastication of feed by dairy cattle. Veterinary Clinics of North America: Food Animal Practice 7 439–462 Google Scholar
Bristow, DJ & Holmes, DS 2007 Cortisol levels and anxiety-related behaviors in cattle. Physiology & Behavior 90 626–628 Google Scholar
Byskov, MV, Fogh, A & Løvendahl, P 2017 Genetic parameters of rumination time and feed efficiency traits in primiparous Holstein cows under research and commercial conditions. Journal of Dairy Science Epub ahead of print doi: 10.3168/jds.2016–12511 Google Scholar
Clark, CEF, Lyons, NA, Millapan, L, Talukder, S, Cronin, GM, Kerrisk, KL & Garcia, SC 2015 Rumination and activity levels as predictors of calving for dairy cows. Animal 9 691–695 CrossRefGoogle ScholarPubMed
Dolecheck, KA, Silvia, WJ, Heersche, G, Chang, YM, Ray, DL, Stone, AE, Wadsworth, BA & Bewley, JM 2015 Behavioral and physiological changes around estrus events identified using multiple automated monitoring technologies. Journal of Dairy Science 98 8723–8731 Google Scholar
Erina, S, Cziszter, LT, Acatincăi, S, Baul, S, Tripon, I, Gavojdian, D, Răducan, GG & Buzamăt, G 2013 Research on rumination time according to administration order of forages in Romanian Black and White cows. Scientific Papers Animal Science and Biotechnologies 46 302–305 Google Scholar
Fraser, D 1995 Science, values and animal welfare: exploring the ‘inextricable connection’. Animal Welfare 4 103–117 CrossRefGoogle Scholar
Hansen, SS, Nørgaard, P, Pedersen, C, Jørgensen, RJ, Mellau, LSB & 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 Google Scholar
Herskin, M, Munksgaard, L & Ladewig, J 2004 Effects of acute stressors on nociception, adrenocortical responses and behavior of dairy cows. Physiology & Behavior 83 411–420 Google Scholar
Kuznetsova, A, Brockhoff, PB & Christensen, RHB 2015 lmerTest: tests in Linear Mixed Effects models. R package version 2.0-29Google Scholar
Liboreiro, DN, Machado, KS, Silva, PRB, Maturana, MM, Nishimura, TK, Brandão, AP, Endres, MI & 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
McFadden, D 1974 Conditional Logit Analysis of Qualitative Choice Behavior. New York: Academic Press Google Scholar
Schirmann, K, von Keyserlingk, MAG, Weary, DM, Veira, DM & Heuwieser, W 2009 Technical note: validation of a system for monitoring rumination in dairy cows. Journal of Dairy Science 92 6052–6055 Google Scholar
Stangaferro, ML, Wijma, R, Caixeta, LS, Al-Abri, MA & 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 & 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 Google Scholar
Stangaferro, ML, Wijma, R, Caixeta, LS, Al-Abri, MA & 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
Szűcs, E, Geers, R, Jezierski, T, Sossidou, EN & Broom, DM 2012 Animal welfare in different human cultures, traditions and religious faiths. Asian-Australasian Journal of Animal Sciences 25 1499–1506 Google Scholar
Talukder, S, Kerrisk, K, Clark, C, Garcia, S & Celi, P 2015 Rumination patterns, locomotion activity and milk yield for a dairy cow diagnosed with a left displaced abomasum. New Zealand Veterinary Journal 63 180–181 Google Scholar
Thornton, PK 2010 Livestock production: recent trends, future prospects. Philosophical Transactions of the Royal Society B Biological Sciences 365 2853–2867 Google Scholar
Van Hertem, T, Maltz, E, Antler, A, Romanini, CEB, Viazzi, S, Bahr, C, Schlageter-Tello, A, Lokhorst, C, Berckmans, D & 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
Webster, AJF 2001 Farm animal welfare: the five freedoms and the free market. The Veterinary Journal 161 229–237 Google Scholar
Supplementary material: PDF

Moretti et al supplementary material

Moretti et al supplementary material 1

Download Moretti et al supplementary material(PDF)
PDF 687.4 KB