Big data modelling to forecast crop yield to enable precision fertilisation

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This project aims to lay a foundation for a generic data-driven approach to more precise management of our agricultural landscapes. A multitude of agriculture-related data streams are now available to growers to characterise their yield, management, soil and weather. However, currently there is no approach able to digest all these disparate data streams to enable a management decision. The project will develop an approach to harness all of these data streams to guide spatially variable applications of nitrogen fertilisers with a focus on grains cropping. This should provide the opportunity to allocate fertiliser inputs as required at fine spatial scales according to local soil and weather conditions to maximise profit and minimise off-farm impacts of excessive fertilisation.