Managing subsoil constraints for increased productivity and water use efficiency. Subsoil constraints limit crop production in up to 60% of agricultural land. This project examines the impacts of organic matter incoporation, deep placement of nutrients, use of primer crops, calcium addition and their combination on amelioration of subsoil constraints and thereby on the improvement of root growth, water use and crop yield in high-rainfall region. The best-bet management strategy will be developed ....Managing subsoil constraints for increased productivity and water use efficiency. Subsoil constraints limit crop production in up to 60% of agricultural land. This project examines the impacts of organic matter incoporation, deep placement of nutrients, use of primer crops, calcium addition and their combination on amelioration of subsoil constraints and thereby on the improvement of root growth, water use and crop yield in high-rainfall region. The best-bet management strategy will be developed.Read moreRead less
Big data modelling to forecast crop yield to enable precision fertilisation. 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 appro ....Big data modelling to forecast crop yield to enable precision fertilisation. 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.Read moreRead less
Co-variant analysis and statistical modelling for improved crop yield. This project plans to develop mathematical tools that will help to identify cereal plant varieties with the highest yield. This is a critical responsibility of plant breeders and many Australian breeders acquire and store important information related to the issue. However, there are as yet no mathematical tools that are able to co-analyse the heterogeneous and high-dimensional data in order to understand how external and int ....Co-variant analysis and statistical modelling for improved crop yield. This project plans to develop mathematical tools that will help to identify cereal plant varieties with the highest yield. This is a critical responsibility of plant breeders and many Australian breeders acquire and store important information related to the issue. However, there are as yet no mathematical tools that are able to co-analyse the heterogeneous and high-dimensional data in order to understand how external and internal factors correlate with the major growth and development stages at the crop level. This project seeks to develop and implement mathematical and statistical tools to analyse genetic, agronomic and phenomic factors that affect plant performance, to deliver advanced yield prediction.Read moreRead less