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Crop production planning and yield distribution

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In only 200 years, the world’s population has increased from one billion to over seven billion. Based on these numbers, it has become vital for us to consider the impact of a densely-populated planet on our quality of life.

Of particular concern is the future of our food security due to this population increase, as well as decreasing availability of agricultural land, climate change and extreme weather events. Heatwaves, droughts, cyclones and flooding have all had a significant impact on food supply and prices in Australia.

In 2006 Cyclone Larry wiped out 90% of the North Queensland crop diminishing supplies and increasing consumer prices by 500%.

UniSQ is working to perfect crop production planning, optimising production and therefore profits for the farmer.
Australia’s future agricultural production and exports can expect to be adversely affected by climate change.
Climate Council

Unfortunately, our understanding of the physical world is still far from perfect and, as a result, we suffer from avoidable adverse effects of severe climate events and are unable to adequately optimise our resource use or plan agricultural production around climate behaviour for the best outcomes.

UniSQ researchers leading the way

Professor Thanh Tran-Cong
Dr Duc-Anh An-Vo
Professor Nam Mai-Duy
Dr Trevor Langlands
Dr Canh-Dung Tran
Associate Professor Dmitry Strunin
UniSQ is working on systems to perfect crop production planning - enabling farmers to optimise a production plan for maximum profit through crop growth modelling.

By providing a range of data and scenarios, farmers are able to receive insights into probable crop production outcomes and make more informed decisions around their farming practices. This, in turn, will ensure more stability in the production and exportation of food.

Affordable food and food security are vital to our quality of life and our ultimate survival and UniSQ researchers are helping to ensure that we’re prepared.

Crop production outcomes

Based on the historical data of the region, a SOI-based stochastic weather generator is able to feed probable weather data into a crop growth modeller which then outputs an estimated crop yield. Along with weather data, the crop growth modeller takes into consideration prices and input costs associated with relevant crops as well as different scenarios of irrigation, fertilisation and fertigation.

 

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