The Australian Farmer

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the australian farmer

the grains industry from grain growers to researchers. Modelling and simulation provide an avenue to pre- dict consequences of crop management decision op- tions, support their relevance by assessing broad-scale impact , as well as test new cultivar ideas and climatic conditions that may not currently exist. This helps the formulation of robust ideas that can be followed by re- al-world testing, supporting the delivery of innovations. Tangible benefits of crop modelling The concepts related to using crop models as agricul- tural decision/discussion support has matured over the past many decades and forms a critical part of the grains industry research and development. Crop science research and modelling supported by the grains industry has enabled the development of ad- vanced computer modelling capability (Hammer et al., 2010). This capability has been used with long-term se- quences of climatic data to test probabilistic estimates of yield for a range of decision options, such as planting time, antecedent soil moisture status, cultivar matur- ity, and moisture conserving agronomic practices like single- and double-skip row systems (Muchow et al., 1994). It has also provided avenues to test G × E × M op- tions for likely future climates (Hammer et al., 2020). This capability has also been utilised for plant breeding. In addressing the stagnation in the improve- ment of crop yield, a major Australian government

Poor seasonal conditions can wipe off tens of mil- lion tonnes of grain production and multi-billion dol- lar reduction in the total farmgate value each year. Achieving productivity gains and yield stability are thus sustained focal areas in the grains industry. This requires the synergetic effort of many individ- uals and entities spanning the grains industry: farmers to grow the most suitable crops based on informed decisions, with the support of breeders, agronomists, and extension experts in providing cultivars and pro- duction advice, which are powered by research and development. A platform to integrate these collective efforts will be most valuable. What is crop modelling? The Australian grains industry already has extensive ex- perience with existing crop cultivars, management prac- tices, and production environments. This helps growers to achieve good crop outcomes and minimise the odds of bad productivity performance and financial losses. The sustained focus on increasing yield and yield stabil- ity will require continual supply of innovations to improve management practices and cultivar attributes. One of the means to generate innovation is via com- puter simulation. Via modelling and simulation, it is feas- ible to look at anticipated yield and production risk ‘a priori’ by examining outcomes over many years and loca- tions. The best way to do this is by using a reliable crop model with relevant long-term climate data and soil data to simulate what might happen when agronomic practi- ces and/or cultivar attributes are changed. Broadacre crops can be thought of as a complex soil–plant–environment system with many interacting biological (underpinned by the genetics of the plant, G), environmental (E), and crop management practice (M) components. Crop modelling is an exercise that formalises our knowledge in how G × E × M can interact into math- ematical equations, connecting knowledge from across DID YOU KNOW Total Australian agricultural R&D funding in 2023-24 was $2.98 billion, increasing slightly from 2022-23 ($2.91 billion). Source: ABARES / DAFF. ?

Some of the entities with close connections to crop mod- elling efforts. The output of each decision-maker can be enhanced with a two-way connection with others. Crop modelling plays a key role in facilitating information exchange and decision/discussion support.