title: Evaluation of different feed intake models for dairy cows.
abstract: The objective of the current study was to evaluate feed intake prediction models of varying complexity using individual observations of lactating cows subjected to experimental dietary treatments in periodic sequences (i.e., change-over trials). Observed or previous period animal data were combined with the current period feed data in the evaluations of the different feed intake prediction models. This would illustrate the situation and amount of available data when formulating rations for dairy cows in practice and test the robustness of the models when milk yield is used in feed intake predictions. The models to be evaluated in the current study were chosen based on the input data required in the models and the applicability to Nordic conditions. A data set comprising 2,161 total individual observations was constructed from 24 trials conducted at research barns in Denmark, Finland, Norway, and Sweden. Prediction models were evaluated by residual analysis using mixed and simple model regression. Great variation in animal and feed factors was observed in the data set, with ranges in total dry matter intake (DMI) from 10.4 to 30.8kg/d, forage DMI from 4.1 to 23.0kg/d, and milk yield from 8.4 to 51.1kg/d. The mean biases of DMI predictions for the National Research Council, the Cornell Net Carbohydrate and Protein System, the British, Finnish, and Scandinavian models were -1.71, 0.67, 2.80, 0.83, -0.60kg/d with prediction errors of 2.33, 1.71, 3.19, 1.62, and 2.03kg/d, respectively, when observed milk yield was used in the predictions. The performance of the models were ranked the same, using either mixed or simple model regression analysis, but generally the random contribution to the prediction error increased with simple rather than mixed model regression analysis. The prediction error of all models was generally greater when using previous period data compared with the observed milk yield. When the average milk yield over all periods was used in the predictions of feed intake, the increase in prediction error of all models was generally less than when compared with previous period animal data combined with current feed data. Milk yield as a model input in intake predictions can be substantially affected by current dietary factors. Milk yield can be used as model input when formulating rations aiming to sustain a given milk yield, but can generate large errors in estimates of future feed intake and milk production if the economically optimal diet deviates from the current diet.
authors: Swedish University of Agricultural Sciences, Department of Agricultural Research for Northern Sweden, S-901 83 Umeå, Sweden. Electronic address: sophie.krizsan@slu.se.
authors: S J
authors: SJ
authors: Krizsan
authors: MTT Agrifood Research Finland, North Savo Research Station, FIN-71750 Maaninka, Finland.
authors: A
authors: A
authors: Sairanen
authors: MTT Agrifood Research Finland, North Savo Research Station, FIN-71750 Maaninka, Finland.
authors: A
authors: A
authors: Höjer
authors: MTT Agrifood Research Finland, North Savo Research Station, FIN-71750 Maaninka, Finland.
authors: P
authors: P
authors: Huhtanen
mesh_terms: D000821:Animal Feed / Q000032:analysis*; D000818:Animals; D002417:Cattle; D003718:Denmark; D004032:Diet / Q000662:veterinary*; D005260:Female; D005387:Finland; D007774:Lactation; D008892:Milk; D008962:Models, Theoretical; D009664:Norway; D012044:Regression Analysis; D013548:Sweden
keywords: dairy cow; feed intake; model evaluation; prediction