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A time series model of daily milk yields and its possible use for detection of a disease (ketosis)

Published online by Cambridge University Press:  18 August 2016

R. M. Lark
Affiliation:
Mathematics and Decision Systems Group, Silsoe Research Institute, Wrest Park, Silsoe, Bedford MK45 4HS
B. L. Nielsen
Affiliation:
Scottish Agricultural College, Edinburgh Genetics and Behavioural Sciences Department, Bush Estate, Penicuik, Midlothian EH26 OQE
T. T. Mottram
Affiliation:
Livestock Engineering Group, Silsoe Research Institute, Wrest Park, Silsoe, Bedford MK45 4HS
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Abstract

A time series model was used to describe the daily milk yield of healthy cows in the first 48 days of lactation. A moving average (MA) model of order 1 on the first-order differences of the data was selected — the same chosen in a previous study by Deluyker et al. (1990). When the model was used to generate predicted daily yields in a second data set, for cows in which clinical ketosis had been diagnosed, it was found that significant deviations of actual yield below the daily forecast occurred from 3 days before the day of diagnosis. The model appeared to be transportable to healthy cows from another herd. Threshold values were defined to identify ailing animals by their deviation from predicted yield. However, the thresholds were not very sensitive, and required that a fairly high level of false positives be accepted (25% of a healthy herd over a 5-day period).

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1999

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