Development of a model to predict pasture intake for grazing dairy cows in Argentina
J. BAUDRACCO, N. LOPEZ-VILLALOBOS, C.W. HOLMES, I.M. BROOKES, P. KEMP, E. COMERON, L.A. ROMERO, B. HORAN, P. DILLON AND D. BERRY
Proceedings of the New Zealand Society of Animal Production 66: 35-41.
Milk production in Argentina is based on grazed pastures and supplementary feeds. Pasture dry matter intake affects markedly the performance of grazing dairy systems. The objective of this study was to develop a simple model to predict daily pasture dry matter intake (DMI) of grazing dairy cows in Argentina, which in turn, would enable the effects of stocking rate on pasture DMI, farm productivity and profitability to be explored. The model assumed that potential DMI of cows fed only pasture is initially limited by either rumen fill or energy demand. Cow live weight, stage of lactation, and concentration of neutral detergent fibre in the pasture account for the rumen fill effect, while requirements for maintenance, pregnancy, and potential milk production influence the cow’s energy demand. Potential pasture intake is then estimated from the potential DMI, by taking into account the reduction in potential intake that occurs when supplements are consumed. Finally, actual pasture intake is estimated as a function of pasture allowance and potential pasture intake, based on an empirical equation derived from grazing experiments in Argentina, mainly with lucerne pastures. The fitness of the model was evaluated by the square root of the mean-square prediction error (RMSPE), expressed as a percentage of the mean actual pasture intake. The accuracy of the model was satisfactory, with RMSPE of 9.6% and 7.3% for two Argentine datasets (lucerne pastures), and 8.1% for one Irish dataset (ryegrass-clover pastures). The model can be used as a part of a whole-farm model to predict the effects of stocking rate on farm productivity and profitability.
Keywords: NZSAPAB; pasture intake, prediction, grazing, dairy cow
Last Updated 2/07/2006