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Rumination and activity levels as predictors of calving for dairy cows

Published online by Cambridge University Press:  10 December 2014

C. E. F. Clark ,
N. A. Lyons ,
L. Millapan ,
S. Talukder ,
G. M. Cronin ,
K. L. Kerrisk  and
S. C. Garcia
C. E. F. Clark*
Affiliation:
Dairy Science Group, University of Sydney, Camden 2570, NSW, Australia
N. A. Lyons
Affiliation:
Dairy and Intensive Livestock Industries, NSW Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle NSW 2568, Australia
L. Millapan
Affiliation:
Department of Animal Production, Faculty of Agronomy, University of Buenos Aires, Buenos Aires 1417, Argentina
S. Talukder
Affiliation:
Dairy Science Group, University of Sydney, Camden 2570, NSW, Australia
G. M. Cronin
Affiliation:
Dairy Science Group, University of Sydney, Camden 2570, NSW, Australia
K. L. Kerrisk
Affiliation:
Dairy Science Group, University of Sydney, Camden 2570, NSW, Australia
S. C. Garcia
Affiliation:
Dairy Science Group, University of Sydney, Camden 2570, NSW, Australia
*
† E-mail: cameron.clark@sydney.edu.au
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Abstract

The Australian dairy herd size has doubled over the last 20 years substantially increasing the time that farmers require for individual animal attention to monitor and intervene with events such as calving. Technology will help focus this limited labour resource on individual cows that require assistance. The objective of this experiment was to first determine the profiles of rumination duration and level of activity as determined by sensors between, and within, days around calving and second to use these data to predict the day of calving for pasture-based dairy cows. After 2 weeks from the expected calving date, 27 cows were fitted with SCR HR LD Tags, located in 40×90 m2 paddock and offered ad libitum oaten hay and 2 kg grain-based concentrate/cow per day until calving. Hourly activity and rumination data for each cow, as determined by the SCR tags, were fitted with linear mixed models and all parameters were estimated using restricted maximum likelihood. Rumination duration decreased by 33% over the day prior and the day of calving, with the decline in rumination duration starting the day prepartum. Activity levels were maintained prepartum but increased in the days postpartum. The day of calving was recorded and used to determine the gold standard positive (the day before calving) and negative (all other) dates. A threshold rumination level of 0.9 (decline in rumination duration of 10%) gave the optimal combination of 70% sensitivity and 70% specificity. This experiment shows the potential to use rumination duration to predict the day of calving and the opportunity to use sensor data to monitor animal health.

Keywords

calvingpredictionsensorruminationpasture

Information

Type
Research Article
Information
animal , Volume 9 , Issue 4 , April 2015 , pp. 691 - 695
Copyright
© The Animal Consortium 2014 

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