Accurate and reliable decision support for farmers and industry
The value could be generated when used by researchers to identify opportunities, constraints and risks, and ways of managing them and extending this knowledge to growers. Furthermore, there is a need to better prioritise research investments by allowing the testing of hypotheses through modelling rather than solely in field research.
A systems approach to agricultural production systems
CSIRO has invested in APSIM which is a modelling framework with the ability to integrate models derived in fragmented research efforts. This enables research from one discipline or domain to be transported to the benefit of some other discipline or domain. It also facilitates comparison of models or submodels on a common platform.
This functionality uses a ― plug-in-pull-out approach to APSIM design. The user can configure a model by choosing a set of submodels from a suite of crop, soil, and utility modules. Any logical combination of modules can be simply specified by the user ―plugging in required modules and ―pulling out any modules no longer required. Its crop simulation models share the same modules for the simulation of the soil, water, and nitrogen balances.
APSIM can simulate more than 20 crops and forests (e.g., alfalfa, eucalyptus, cowpea, pigeonpea, peanuts, cotton, lupin, maize, wheat, barley, sunflower, sugarcane, chickpea, and tomato). APSIM outputs can be used for spatial studies by linking with geographic information systems (GIS)
Better agricultural production outcomes
CSIRO‘s investment in APSIM and associated management decision support research benefits farmers and researchers. These benefits include:
- Improved farmer and researcher understanding the management of farm resources in particular soils
- For those farmers using APSIM or a web based interface using ASPIM such as Yield Prophet®, better on-farm prioritisation of management interventions
- For the increasing number of researchers, and research managers using
- APSIM, a potential reduction in the level of field experimentation required and/or improved prioritisation of research investments – possibly rendering previously unjustifiable R&D cost effective and delivering earlier access to outcomes
- For the grains and livestock industries generally, a potential bringing forward of innovations because some early-stage research station and field trials can be avoided or abridged by using simulation modelling to pre-test hypotheses