2022-2025 – $1.15M funded by GRDC

Dr Patrick Filippi, Professor Thomas Bishop, Associate Professor Brett Whelan, Professor Willem Vervoort, Professor Richard Trethowan, Associate Professor Floris Van Ogtrop, Professor Daniel Tan

This project aims to develop scalable precision-agriculture analytics to identify, map, and quantify the impacts of frost and heat stress on yield and grain quality across Australian cropping systems. By integrating on-farm yield data, spatial layers (soil, topography, satellite imagery), and temperature and phenology models, it seeks to pinpoint high-risk zones within paddocks and distinguish yield losses caused by temperature extremes. These insights will underpin new data-driven decision tools that support pre-sowing and in-crop management decisions—such as sowing time, variety choice, and harvest options—and provide growers with practical means to manage variability, reduce risk, and enhance profitability under increasing climate stress.

2022-2025 – $2M funded by GRDC

Professor Thomas Bishop, Dr Patrick Filippi, Associate Professor Brett Whelan, Dr Lianna Pozza

By harnessing machine learning, remote sensing, and deep soil sampling across 75 farms nationally, the project seeks to map soil constraints (e.g., sodicity, salinity, pH) and plant available water capacity (PAWC) in the full soil profile, at fine resolutions within fields. These 3-D maps will enable growers and advisors to identify zones where root growth or water supply is limited, align variable-rate soil amelioration and input decisions accordingly, and integrate into user-friendly software via PCT Agcloud platforms.

2022-2025 –$313K funded by GRDC

Professor Thomas Bishop, Dr Patrick Filippi, Associate Professor Brett Whelan, Professor Brent Kaiser

This project aims to quantify and understand the yield gap and spatial variability within and between paddocks for commercial pulse crops across Australia. By analysing yield-monitor and spatial data for pulses, the project seeks to identify the on-farm potential yields, map the magnitude of variation in actual yields, and determine the key agronomic and environmental causes of those lower-yielding zones. The end-goal is to provide growers and advisers with insights and tools to reduce downside variability, improve reliability of pulse crops in rotations and enhance profitability by closing the gap between actual and potential yields.

2025–2027 – €1 million funded by the EU H2020

Professor Willem Vervoort working with 5 small to medium enterprises (eLeaf, Hydrologic, Hidromod, Hydro&Meteo, WaterTechnology).

This work builds on the initial WaterSENSE project, using the developed algorithms to quantify evapotranspiration and other water balance components to estimate sustainability indices at large scales. This project links to UN Sustainable Development Goals 6 to improve access to water for all. For the project we have developed remote sensing approach to estimate field level irrigation water applications and developing a machine learning model as a surrogate of a large complex landscape model to predict soil moisture in space and near real-time.

2025–2027 – $329K funded by the Cotton Research and Development Corporation

Professor Willem Vervoort working with 4 small to medium enterprises (eLeaf, Hidromod, Hydro&Meteo, WaterTechnology).

This project is a direct demonstration of the REINFORM algorithms developed to quantify cotton water use efficiency indices from the field to the region and industry scale.

2024–2028 – $1.1M Philanthropic funding

Professor Willem Vervoort Dr Sabrina Lomax, Professor Alex McBratney, Dr Vanessa Pino, Professor Thomas Bishop and others.

The Landscape Rehydration Project at Llara farm in Narrabri specifically aims at testing typical regenerative agriculture practices for Australia, but this can be seen in the larger context of Nature Based Solutions for drought and flooding.

The Landscape Rehydration project (LRP), experimental fields have been established between 2020 - 2022 including fencing and cattle water points. Contour banks have been installed in the treatment areas to reduce overland flow velocities and to enhance water spreading. In 2025, streambed erosion control structures have been installed to reduce flow velocities in the creek bed and to encourage sediment retention and bank water infiltration.

The major objective of the LRP is to test whether landscape rehydration can provide drought resilience for pasture production. The evidence to support this objective focuses on three main areas:

• Changes in the overall water balance
• Changes in pasture production and animal production
• Changes in soil quality and health

2025–2028 - $876k

Assocaite Professor Thomas Roberts, Dr Claudia Keitel, Associate Professor Tina Bell, Dr Ali Khoddami, Dr Rebecca Cross, Associate Professor Floris van Ogtrop

Food Quality of Australian Indigenous Grains: Impacts of Plant Environment. Little is documented about the viability of grains from Australian native grasses for commercial food applications and how this is influenced by plant growth environment. This project aims to fill this gap in our understanding by co-designing and disseminating knowledge with Gomeroi researchers. The project expects to (1) develop recommendations for native grain production based on insights into the environmental effects on grain quality for four native grasses, (2) train research students, and (3) enhance Indigenous partnership on Gomeroi Country in northern NSW. Benefits resulting from the project are the promotion of best-practice management of native grasslands and support for the development of an Indigenous-led native grains industry.

2024-2026 – $460k

Professor Thomas Bishop, Dr Patrick Filippi, Professor Zhiyong Wang

This project focuses on developing a commercially viable tool for the early detection of disease risks and active infections in grain crops at the paddock scale. It integrates earth observation data, on-farm information, mechanistic disease models, and data-driven approaches for comprehensive disease monitoring. The solution aims to reduce reliance on manual scouting, enabling growers and agronomists to target interventions more effectively. The project is being delivered in collaboration with SmartSat CRC, DataFarming, and GRDC. 

2024-2026 – $445k

Professor Thomas Bishop, Dr Patrick Filippi, Professor Zhiyong Wang

This project focuses on developing a robust, scalable system for mapping weed presence across broadacre farms using drone and satellite-based remote sensing. Delivered in collaboration with SmartSat CRC, DataFarming, and GRDC, the project integrates high-resolution imagery and deep learning to identify weed-infested regions and support variable-rate herbicide application. It takes advantage of the increasing array of commercial satellite platforms which offer spatial resolutions of less than 50 cm.

2023-2027 – $707k

Professor Thomas Bishop, Dr Patrick Filippi, Associate Professor Floris Van Ogtrop

This project examines how residual herbicides affect crop establishment and yield through soil-water-carbon coupling and plant physiology. Our role at PAHGISL focuses on the geospatial component, delivering high-resolution satellite-based observations such as soil moisture, evapotranspiration, gross primary productivity, and stress indicator in data-scarce scenarios. These data would support process-based models to simulate and understand how environmental variability modulates herbicide impacts. By integrating ecohydrology and remote sensing knowledge with crop physiology, the project enables scaling from field to regional predictions, supporting sustainable herbicide management and resilient farming systems across Australia.