Big data modelling to forecast crop yield to enable precision fertilisation

该项目旨在为通用数据驱动的方法奠定基础，以更精确地管理我们的农业景观。现在，种植者可以使用大量与农业相关的数据流来评估他们的产量、管理、土壤和天气。 然而，目前还没有一种方法能够消化所有这些不同的数据流，使管理决策。该项目将开发一种方法，利用所有这些数据流来指导氮肥的空间可变应用，重点是谷物种植。 这应该提供机会，根据当地土壤和天气条件，在精细的空间尺度上分配所需的肥料投入，以最大限度地提高利润，并最大限度地减少过度施肥对农场的影响。

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.