Tailoring production to targets

Scientists at Orange Agricultural Institute have developed a computer modelling tool that aims to substantially increase farm profitability by meeting production targets and quality specifications through better matching livestock feed demands with forage resources.

The complex modelling tool, developed by NSW DPI as part of the Grain & Graze project, is currently being evaluated for use by departmental research and advisory staff when working with livestock producers.

“The whole-farm model uses linear programming to maximise income received from a wide range of alternative crop and livestock activities for mixed farms over a single year,” said NSW DPI research scientist Randall Jones.
“It enables crop and fodder solutions to be individually tailored to the resources available for representative farms within the high, medium and low rainfall zones found across the Lachlan and Central West catchments.

“The model requires data to be entered that defines individual farm structure, forage production and energy demands of livestock.

“Using these inputs, the effects of changes to forage supply or livestock management on the economic performance of the whole farm can be assessed.

“For example, changing from spring to autumn lambing requires a host of other changes to the farm plan such as pasture types, crop and pasture rotations, and labour availability constraints that need to be taken into account,” said Geoffrey Millar, the NSW DPI technical officer responsible for collecting and collating the database used by the model.

To enable alternative management options and technologies to be investigated, the model includes a wide range of farm activities such as the choice of crop/pasture rotations, crop type and area, pasture type and area, livestock systems and species, stocking rates, hay/silage making and supplementary feeding.

“This enables it to determine optimal combination of livestock type and numbers, and the area and type of pasture species for the three rainfall zones,” Dr Jones said.

“One of the major criticisms of whole-farm models is an inability to take into account the impacts of rainfall variability on output solutions as most models use only mean production data.

“This shortcoming has been overcome in the Grain & Graze model by developing a suite of growth rates curves for different rainfall scenarios.”