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An integrated approach in predicting the major crops of Australia

August 15, 2016 By Editor


Description given on Youtube:
QAAFI Science Seminar – 7 April 2015

Presented by Dr Andries Potgieter
Research Fellow, QAAFI Centre for Plant Science

ABSTRACT

Since early settlement, the existence of most rural communities in Australia has depended on agriculture. Dry land cropping has been one of the main activities contributing towards the long-term viability and sustainability of these communities. This is still true today. However, the operating environment of producers has become more challenging. Food producers are increasingly exposed to variability and change in world markets, commodity prices and climate, thus increasing their vulnerability and threatening their livelihoods. Advance knowledge of the associated risk in crop production, however, can mitigate some of the impacts of such factors. Hence, easily accessible, near real-time, objective and accurate crop production information is becoming increasingly valuable in decision-making for agricultural industry and government agencies. To date, industry and crop forecasters have had a good idea of the potential crop yield for a specific season, but advance, accurate, timely and objective information on crop area for a shire or region has been mostly unavailable. Here we present a holistic approach to bridging the information gap, which is exacerbated by the lack of accurate and timely information and a projected increase in market and climate volatility within Australia and globally. In addition, the integration of remote sensing technologies in assessing food security is also discussed.

About Dr Andries Potgieter

Dr Potgieter holds a Bachelor of Science, Honours and Master’s degrees in Mathematical Statistics and a PhD specialising in remote sensing. He has more than 24 years of experience in predictive biophysical spatial modelling systems. He is currently a Research Fellow at the University of Queensland, Australia.

His main research interest is in the complex integration of spatial production modelling, climate forecasting and remotely sensed systems at a regional scale. In particular, his interest targets agricultural research that enhances the profitability and sustainability of spatial production systems through a better understanding of the linkages and interactions of such systems across a range of spatial (e.g. field, farm, catchment, national), and temporal (i.e. seasons to decades) scales.

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