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Tilse, M.J
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Authors
Tilse, M.J
Filippi, P
Bishop, T
Tilse, M.J
Bishop, T
Poole, S
Filippi, P
Bishop, T
Yu, Y
Tilse, M.J
Filippi, P
Topics
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Predictive Modeling, Phenotyping, and Digital Tools for Decision Support
Type
Oral
Year
2024
2026
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Filter results3 paper(s) found.

1. Predicting, Mapping, and Understanding the Drivers of Grain Protein Content Variability – Utilising John Deere’s New Harvestlab 3000 Grain Sensing System

Grain protein content (GPC) is a key determinant of the prices that grain growers receive, and the rising cost of production is shifting management focus towards optimising this to maximise return on investment. In 2023, John Deere released the HarvestLab 3000TM Grain Sensing system in Australia for real-time, on-the-go measurement of protein, starch, and oil values for wheat, barley, and canola. However, while the uptake of these sensors is increasing, GPC maps are not available for... M.J. Tilse, P. Filippi, T. Bishop

2. A Counterfactual Modelling Framework with On-farm Experimentation for Guiding Site-specific Nitrogen Applications

Nitrogen (N) fertiliser is a key driver of wheat grain protein content (GPC) and yield, and represents one of the largest variable input costs and sources of emissions in Australian grain production. Yet estimating optimal N fertiliser rates remains challenging due to spatio-temporal variability in soil N supply and crop nutrient demand, as well as dynamic interactions between yield, GPC, and water availability. On-farm experimentation (OFE) provides valuable insights into crop responses... M.J. Tilse, T. Bishop, S. Poole, P. Filippi

3. Soil Water Nowcasting for Site-specific Yield Potential Estimation

Knowing how much plant available water (PAW) is stored across a field at key decision points in the growing season is fundamental to precision agriculture. Spatial variability in soil water translates directly into variability in water-limited yield potential, yet most growers lack the tools to quantify this at the within-field scale. Here we present a Soil Water-Energy Balance (SWEB) model that offers a framework to deliver daily, 30 m resolution estimates of PAW across any dryland paddock... T. Bishop, Y. Yu, M.J. Tilse, P. Filippi