Efficient dairy grazing systems
Milk production systems, which rely heavily on grazed herbage, need to apply strategies to reduce costs of production and maintain dairy farm incomes in the face of declining milk prices. GRAZEMORE, a major EU-funded initiative, brought together scientists from six European countries to develop a decision support system (DSS) to help farmers optimize the use of grazed grass in milk production. The GRAZEMORE DSS was developed for rotational grazing systems with dominant grass species for feeding dairy cows, such as perennial ryegrass (Lolium perenne L.) and white clover (Trifolium repens L.) swards. The DSS is a large simulation platform displaying the effect of weather conditions on growth grass as well as the effect of variance of management and environment to animal intake and milk production. With the use of a currently developed herbage growth (HG) model, grass growth can be predicted by measuring and forecasting weather conditions such as air temperature, light and rainfall. Additional inputs such as soil types, fertilizer application and grass species enhance and alter the model output. The paddocks consist of grass with individual growth rates as predicted by the HG model. The paddocks' composition act as an input for the prediction of herbage intake and milk production from the swards with the use of an Herbage Intake model (HI). The DSS performs daily predictions of herbage mass, herbage growth, organic matter digestibility crude protein and white clover contribution for each paddock. Milk yield and Herbage Intake are predicted as herd averages for the residence period in each individual paddock. The DSS allows the biological and economic evaluation of different grazing scenarios under various climatic conditions. This tool significantly aids decision making concerning issues such as paddock size, time of grazing, grazing order, removing paddocks for silage, rate of fertilizer, ration formulation and other factors, leading to well-managed grassland systems.
