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Adaptive models for online estimation of individual milk yield response to concentrate intake and milking interval length of dairy cows

Published online by Cambridge University Press:  08 April 2011

G. ANDRÉ ,
B. ENGEL ,
P. B. M. BERENTSEN ,
G. VAN DUINKERKEN  and
A. G. J. M. OUDE LANSINK
G. ANDRÉ*
Affiliation:
Livestock Research, Wageningen University and Research Centre, P.O. Box 65, 8200 AB Lelystad, The Netherlands
B. ENGEL
Affiliation:
Biometris, Wageningen University and Research Centre, P.O. Box 100, 6700 AC Wageningen, The Netherlands
P. B. M. BERENTSEN
Affiliation:
Business Economics Group, Wageningen University and Research Centre, P.O. Box 8130, 6700 EW Wageningen, The Netherlands
G. VAN DUINKERKEN
Affiliation:
Livestock Research, Wageningen University and Research Centre, P.O. Box 65, 8200 AB Lelystad, The Netherlands
A. G. J. M. OUDE LANSINK
Affiliation:
Business Economics Group, Wageningen University and Research Centre, P.O. Box 8130, 6700 EW Wageningen, The Netherlands
*
*To whom all correspondence should be addressed. Email: geert.andre@wur.nl
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Summary

Automated feeding and milking of dairy cows enables the application of individual cow settings for concentrate supply and milking frequency. Currently, general settings are used, based on knowledge about energy and nutrient requirements in relation to milk production at the group level. Individual settings, based on the actual individual response in milk yield, have the potential for a marked increase in economic profits. In the present study, adaptive dynamic models for online estimation of milk yield response to concentrate intake and length of milking interval are evaluated. The parameters in these models may change over time and are updated through a Bayesian approach for online analysis of time series. The main use of dynamic models lies in their ability to determine economically optimal settings for concentrate intake and milking interval length for individual cows at any day in lactation. Three adaptive dynamic models are evaluated, a model with linear terms for concentrate intake and length of milking interval, a model that also comprises quadratic terms, and an enhanced model (EM) in order to obtain more stable parameter estimates. The linear model is useful only for forecasting milk production and the estimated parameters of the quadratic model were found to be unstable. The parsimony of the EM leads to far more stable parameter estimates. It is shown that the EM is suitable for control and monitoring, and therefore promises to be a valuable tool for application within precision livestock farming.

Type
Modelling Animal Systems
Information
The Journal of Agricultural Science , Volume 149 , Issue 6 , December 2011 , pp. 769 - 781
Copyright
Copyright © Cambridge University Press 2011

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