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Predicting Average Feed Intake of Lactating Holstein Cows Fed Totally Mixed Rations

J. Fuentes-Pila^*, M. Ibañez^*, J. M. De Miguel^* and D. K. Beede

^* Department of Statistics and Management Sciences in Agriculture Polytechnic University of Madrid Ciudad Universitaria s/n, Madrid 28040, Spain
Department of Animal Science Michigan State University East Lansing, MI 48824

Corresponding author:
J. Fuente-Pila; e-mail:
jfuentes{at}agricolas.upm.es.

A dry matter intake (DMI) prediction equation was estimated by using a data file that contained 124 treatment means collected from published studies. Animal factors considered for inclusion in the prediction model were body weight (BW) and its natural logarithm, BW^0.75, milk yield (MY) and its natural logarithm, milk fat and protein yields, month of lactation and its square, as well as its natural logarithm. The dietary factors considered were the percentages of neutral detergent fiber, acid detergent fiber, crude protein and hemicellulose in the ration dry matter together with the square of all these predictors. The multiple regression model selected by using the maximum R² method include both animal and dietary factors as independent variables. The accuracy of this DMI prediction equation was evaluated and compared with that of five other equations previously published by using three independent datasets also containing treatment means collected from literature. Even though the latest NRC equation was slightly more accurate than the equation proposed in this study with the three evaluation datasets, the latter can be used for some applications for which the NRC equation is not appropriate.

Key Words: feed intake • intake model • prediction equation • Holstein

Abbreviation key: FY = milk fat yield, MOL = month of lactation, MSPE = mean square prediction error, MY = milk yield, PY = milk protein percentage, RADF = ration acid detergent fiber percentage, RCP = ration crude protein percentage, RHEMI = ration hemicellulose percentage, RNDF = ration neutral detergent fiber percentage, RPE = relative prediction error

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