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
Understanding the risk of microplastics in Australian agricultural soils. Biosolids following wastewater treatment are a significant source of microplastics (MPs) that are contaminants of concern. MPs in biosolids pose potential unknown risks to agriculture, food security and ecosystem health through their application to farmlands. Currently, the lack of knowledge on the MPs contamination of agricultural soils is a significant knowledge gap. This project aims to generate new knowledge of MPs' fa ....Understanding the risk of microplastics in Australian agricultural soils. Biosolids following wastewater treatment are a significant source of microplastics (MPs) that are contaminants of concern. MPs in biosolids pose potential unknown risks to agriculture, food security and ecosystem health through their application to farmlands. Currently, the lack of knowledge on the MPs contamination of agricultural soils is a significant knowledge gap. This project aims to generate new knowledge of MPs' fate, behaviour, risk and associated contaminants in biosolids and sludge-amended agricultural soils. The new knowledge generated in this project is expected to help devise better management options to minimise the MP associated risks in agricultural soils, thereby safeguarding the food security and soil health.Read moreRead less