title: A Robust Statistical Model to Predict the Future Value of the Milk Production of Dairy Cows Using Herd Recording Data.
abstract: The future value of an individual dairy cow depends greatly on its projected milk yield. In developed countries with developed dairy industry infrastructures, facilities exist to record individual cow production and reproduction outcomes consistently and accurately. Accurate prediction of the future value of a dairy cow requires further detailed knowledge of the costs associated with feed, management practices, production systems, and disease. Here, we present a method to predict the future value of the milk production of a dairy cow based on herd recording data only. The method consists of several steps to evaluate lifetime milk production and individual cow somatic cell counts and to finally predict the average production for each day that the cow is alive. Herd recording data from 610 Danish Holstein herds were used to train and test a model predicting milk production (including factors associated with milk yield, somatic cell count, and the survival of individual cows). All estimated parameters were either herd- or cow-specific. The model prediction deviated, on average, less than 0.5 kg from the future average milk production of dairy cows in multiple herds after adjusting for the effect of somatic cell count. We conclude that estimates of future average production can be used on a day-to-day basis to rank cows for culling, or can be implemented in simulation models of within-herd disease spread to make operational decisions, such as culling versus treatment. An advantage of the approach presented in this paper is that it requires no specific knowledge of disease status or any other information beyond herd recorded milk yields, somatic cell counts, and reproductive status.
authors.affiliation: Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark; Section for Epidemiology, National Veterinary Institute, Technical University of Denmark, Frederiksberg, Copenhagen, Denmark.
authors.forename: Kaare
authors.initials: K
authors.lastname: Græsbøll
authors.affiliation: Section for Epidemiology, National Veterinary Institute, Technical University of Denmark , Frederiksberg, Copenhagen , Denmark.
authors.forename: Carsten
authors.initials: C
authors.lastname: Kirkeby
authors.affiliation: Department of Large Animal Sciences, University of Copenhagen , Frederiksberg, Copenhagen , Denmark.
authors.forename: Søren Saxmose
authors.initials: SS
authors.lastname: Nielsen
authors.affiliation: Section for Epidemiology, National Veterinary Institute, Technical University of Denmark , Frederiksberg, Copenhagen , Denmark.
authors.forename: Tariq
authors.initials: T
authors.lastname: Halasa
authors.affiliation: Section for Epidemiology, National Veterinary Institute, Technical University of Denmark , Frederiksberg, Copenhagen , Denmark.
authors.forename: Nils
authors.initials: N
authors.lastname: Toft
authors.affiliation: Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark , Lyngby , Denmark.
authors.forename: Lasse Engbo
authors.initials: LE
authors.lastname: Christiansen
keywords: lactation curve; modeling; prediction; production parameters; simulation