Whole-farm modelling of grazing dairy systems in the temperate-hot summer climate region of South America

Context: Modelling grazing dairy systems from the temperate hot-summer climate region of South America is challenging due to the absence of suitable whole-farm models developed or evaluated in this region. The use of whole-farm models developed in other regions represents an opportunity. However, the accuracy and precision of their predictions need to be assessed. Objectives: The present study evaluated the predictive ability of Farmax Dairy Pro, a whole-farm model developed in New Zealand, to simulate grazing dairy systems in Uruguay. Methods: Data used for the model evaluation was obtained from a dairy farmlet study carried out in Uruguay. The study aimed to explore four intensification strategies based on increasing home-grown forage utilisation and milk output per hectare. The field experiment consisted of four farmlets using two feeding strategies: [Grass Maximum (GMAX) and Grass Fixed (GFIX), based on the amount of grazed herbage in the diet], and two cow genotypes [New Zealand (NZHF) or North American Holstein-Friesian (NAHF)]. The four farmlets were modelled with Farmax for two consecutive years. Model evaluation was performed using standard regression, dimensionless and error index statistics. The model was evaluated by comparing predicted versus observed monthly patterns of milk, milk fat, milk protein and milk solids (MS; milk fat + milk protein) yields, body condition score (BCS), body weight (BW), DM intake (DMI) and net pasture growth rate (PGR). An application of the model was demonstrated by modelling three scenarios for the GMAX-NZHF farmlet. Results and Conclusions: The predictive ability of Farmax was similar for the four farmlets modelled, including patterns over time, for all the variables evaluated. The model provided a robust prediction for monthly patterns of milk and milk components yields at a herd level for total DMI and PGR. The model had a moderate ability to predict monthly patterns of individual milk and milk components yields and BCS, and a poor ability to predict BW. The scenario modelling results indicate that the model could be used with confidence to simulate different farm system alternatives. Overall, the Farmax Dairy Pro model had the potential to provide adequate predictions for grazing dairy systems from Uruguay. Significance: This model will allow the exploration of future intensification pathways for grazing dairy systems in Uruguay and the region, including changes in the forage sequence, stocking rate and calving season. Further adjustments of the model will expand the range of systems and latitudes for this model to be utilised.