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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: riccardo.moretti@unifi.it
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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 

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Footnotes

†

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

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