AI in agriculture: hybrid machine learning models for nitrogen simulation. Agricultural simulation models are used to guide nitrogen management to reduce nitrogen loss and its environmental impact, but they were developed using constrained datasets, which restricts them to site- or regional-specific simulations. This project adopts a novel approach to addressing these problems by applying machine learning-based data analytics. The project will refine the linkages between nitrogen losses and thei ....AI in agriculture: hybrid machine learning models for nitrogen simulation. Agricultural simulation models are used to guide nitrogen management to reduce nitrogen loss and its environmental impact, but they were developed using constrained datasets, which restricts them to site- or regional-specific simulations. This project adopts a novel approach to addressing these problems by applying machine learning-based data analytics. The project will refine the linkages between nitrogen losses and their key drivers, and improve the existing agroecosystem models through data imputation, parameter optimisation and module enhancement. The outcomes of this project will lead to an accurate prediction of nitrogen losses from agriculture, advancement in agroecosystem models and their adaptability to a global context.Read moreRead less
Predatory protists: natural weapons for soil-borne pathogen control. This project aims to understand the mechanistic interactions of predatory protists and fungal pathogens and develop innovative biotechnologies using the protists to suppress soil-borne pathogens. By directly preying on fungal pathogens or activating plant-beneficial bacteria to combat them, the soil predatory protists will be identified, cultivated and utilised to improve disease management. Expected outcomes of this project wi ....Predatory protists: natural weapons for soil-borne pathogen control. This project aims to understand the mechanistic interactions of predatory protists and fungal pathogens and develop innovative biotechnologies using the protists to suppress soil-borne pathogens. By directly preying on fungal pathogens or activating plant-beneficial bacteria to combat them, the soil predatory protists will be identified, cultivated and utilised to improve disease management. Expected outcomes of this project will include a mechanistic understanding of the contribution of protists to pathogen suppression and an innovative, protist-based disease management tool. The novel technologies developed in this project have potentials to benefit Australian agriculture and land management.Read moreRead less