Proceedings
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| Filter results5 paper(s) found. |
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1. Predicting, Mapping, and Understanding the Drivers of Grain Protein Content Variability – Utilising John Deere’s New Harvestlab 3000 Grain Sensing SystemGrain 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. Are Pulses Really More Variable Than Cereals? a Country-wide Analysis of Within-field VariabilityIn Australia, pulses are underutilised by growers relative to cereal crops. There is significant global interest in growing pulses to provide more plant protein, and they also provide a string of agronomic and environmental benefits, such as their ability to fix nitrogen, and provide a pest and disease break for cereal crops. Many studies attribute this underutilisation to pulses exhibiting greater within-field yield variability than cereals. However, this has never been comprehensively examined... P. Filippi, T. Bishop, D. Al-shammari, T. Mcpherson |
3. On Data-driven Crop Yield Modelling, Predicting, and Forecasting and the Common Flaws in Published StudiesThere has been a recent surge in the number of studies that aim to model crop yield using data-driven approaches. This has largely come about due to the increasing amounts of remote sensing (e.g. satellite imagery) and precision agriculture data available (e.g. high-resolution crop yield monitor data), and abundance of machine learning modelling approaches. This is a particular problem in the field of Precision Agriculture, where many studies will take a crop yield map (or a small number), create... P. Filippi, T. Bishop, S. Han, I. Rund |
4. A Counterfactual Modelling Framework with On-farm Experimentation for Guiding Site-specific Nitrogen ApplicationsNitrogen (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 |
5. Soil Water Nowcasting for Site-specific Yield Potential EstimationKnowing 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 |