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Associate Professor Andries Potgieter
Associate Professor

Andries Potgieter

Email: 
Phone: 
+61 7 344 33465

Overview

Background

Professor Andries B. Potgieter is a Principal Research Fellow at the Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland, and an international leader in Digital Agriculture. With a career spanning over 35 years across government, industry, and academia, his research integrates remote sensing, climate forecasting, and crop–climate modelling to support resilient, data-driven decision-making in agriculture. He is currently a key research collaborator in the $36 million GRDC-funded Analytics for the Australian Grains Industry (AAGI) initiative, where he leads digital analytics activities within UQ.

Professor Potgieter’s work focuses on developing predictive tools that combine satellite Earth observation, machine learning, and crop simulation to improve seasonal forecasting, crop monitoring, and risk management. He has pioneered widely adopted innovations such as the CropID tool, now commercialised via Data Farming Pty Ltd, and his models have influenced decision frameworks at Statistics Canada and the FAO. His 114 peer-reviewed publications have accrued over 4,000 citations, and his Field-Weighted Citation Impact (FWCI) places him in the top 5% of researchers globally.

He has built a thriving interdisciplinary research program and mentoring pipeline, supervising PhD, Masters, and MoDS students, and supporting postdoctoral researchers who now work at AWS, Sugar Research Australia, and the Chinese Academy of Agricultural Sciences. His leadership in global partnerships has positioned UQ as a preferred academic collaborator for international institutions tackling climate-smart agriculture.

Current projects

  • Analytics for the Australian Grains Industry (AAGI) – Digital analytics for yield forecasting and decision tools for grain growers (GRDC)

  • CropVision – Satellite remote sensing and AI for field-scale crop production forecasting (ARC Linkage)

  • RiskSSmart – Integration of Earth observation and climate models for sorghum risk mitigation (SmartSat CRC)

  • Root Phenomics – Linking above-ground sensing to root system architecture to accelerate phenotyping of drought-tolerant cereals (GRDC; Chief Investigator)

  • ARC Training Centre for Predictive Breeding in Agricultural Futures – Developing next-generation tools and training pathways for climate-resilient crop improvement (ARC Industrial Transformation Training Centres; Collaborating Investigator)

Previous research highlights

  • Late Maturity Alpha Amylase (LMA) Risk Modelling – National-scale risk prediction framework for wheat quality (GRDC)

  • CropPhen – High-throughput phenotyping for crop type and growth stage detection via drone/UAV (GRDC)

  • SIMLESA and YieldShield – Groundbreaking work in food insecurity mapping and climate risk insurance across eastern and southern Africa

Availability

Associate Professor Andries Potgieter is:
Available for supervision

Qualifications

  • Doctor of Philosophy, University of Southern Queensland

Research impacts

Transforming agricultural decision-making through digital tools My research has led to practical innovations that help farmers, government agencies, and agribusinesses make better decisions under climate uncertainty. By combining satellite imagery, climate data, and artificial intelligence, I have created tools that support crop forecasting, risk assessment, and sustainable farming practices at local, national, and global levels.

Real-world outcomes

  • CropID, a remote sensing tool developed through my research, has been commercialised by Data Farming Pty Ltd and is now used across Australia to map and monitor crops—helping reduce fertiliser waste and improve land management.

  • My seasonal yield forecasting models have been adopted by the Queensland Government and informed policy and logistics planning.

  • Statistics Canada built their national crop forecasting system using frameworks I co-developed, showing international uptake.

  • I co-developed YieldShield™, Australia’s first climate-based crop insurance product, which helped farmers manage drought risk.

  • In 2024–2025, I was contracted by the FAO to adapt these models for use in low-income countries, supporting food security initiatives in Africa and Latin America.

Broader benefits

  • Economic impact: My tools improve supply chain planning, reduce crop losses, and inform commodity trading and insurance.

  • Environmental impact: Precision monitoring enables more efficient fertiliser use, reducing runoff and environmental harm.

  • Social impact: My training and mentoring of students and early-career researchers builds long-term capability in digital agriculture, both in Australia and internationally.

Works

Search Professor Andries Potgieter’s works on UQ eSpace

122 works between 1997 and 2025

41 - 60 of 122 works

2022

Journal Article

Lead time and skill of Australian wheat yield forecasts based on ENSO-analogue or GCM-derived seasonal climate forecasts – A comparative analysis

Potgieter, Andries B, Schepen, Andrew, Brider, Jason and Hammer, Graeme L (2022). Lead time and skill of Australian wheat yield forecasts based on ENSO-analogue or GCM-derived seasonal climate forecasts – A comparative analysis. Agricultural and Forest Meteorology, 324 109116, 1-12. doi: 10.1016/j.agrformet.2022.109116

Lead time and skill of Australian wheat yield forecasts based on ENSO-analogue or GCM-derived seasonal climate forecasts – A comparative analysis

2022

Conference Publication

A major QTL to modify root system architecture in elite durum wheat

Kang, Y., Alahmad, S., Aldiss, Z., Christopher, J., Chenu, K., Able, J.A., Voss-Fels, K.P., Potgieter, A.B., Jordan, D.R., Borrell, A.K., Wasson, A. and Hickey, L.T. (2022). A major QTL to modify root system architecture in elite durum wheat. Wheat Breeding Assembly, Narrabri, NSW Australia, 28-31 August 2022.

A major QTL to modify root system architecture in elite durum wheat

2022

Conference Publication

Exploring root-shoot dynamics to enhance yield potential and stability of future wheat cultivars

Alahmad, S., Kang, Y., Rambla, C., Meer, S.V., Smith, M., Christopher, J., Chenu, K., Able, J.A., Voss-Fels, K.P., Jordan, D.R., Borrell, A.K., Smith, D., Chapman, S., Watt, M., Ober, E., Potgieter, A.B., Wasson, A. and Hickey, L.T. (2022). Exploring root-shoot dynamics to enhance yield potential and stability of future wheat cultivars. Wheat Breeding Assembly, Narrabri, NSW Australia, 28-31 August 2022.

Exploring root-shoot dynamics to enhance yield potential and stability of future wheat cultivars

2022

Journal Article

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency

Zhi, Xiaoyu, Hammer, Graeme, Borrell, Andrew, Tao, Yongfu, Wu, Alex, Hunt, Colleen, van Oosterom, Erik, Massey-Reed, Sean Reynolds, Cruickshank, Alan, Potgieter, Andries B., Jordan, David, Mace, Emma and George-Jaeggli, Barbara (2022). Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency. Theoretical and Applied Genetics, 135 (9), 3057-3071. doi: 10.1007/s00122-022-04167-z

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency

2022

Conference Publication

New technologies to accelerate mungbean improvement

Van Haeften, Shanice, Dudley, Caitlin, Douglas, Colin, Udvardi, Michael, Massel, Karen, Beveridge, Christine, Robinson, Hannah, Hickey, Lee, Potgieter, Andries and Smith, Millicent (2022). New technologies to accelerate mungbean improvement. Queensland Legume Symposium, Brisbane, QLD, Australia, 22 July 2022.

New technologies to accelerate mungbean improvement

2022

Conference Publication

UAV-based technologies to reveal the secrets of mungbean yield

Van Haeften, Shanice, Hickey, Lee, Douglas, Colin, Smith, Millicent, Robinson, Hannah and Potgieter, Andries (2022). UAV-based technologies to reveal the secrets of mungbean yield. Australasian Plant Breeding Conference, Gold Coast, QLD, Australia, 9-11 May 2022.

UAV-based technologies to reveal the secrets of mungbean yield

2022

Journal Article

Estimating photosynthetic attributes from high-throughput canopy hyperspectral sensing in sorghum

Zhi, Xiaoyu, Massey-Reed, Sean Reynolds, Wu, Alex, Potgieter, Andries, Borrell, Andrew, Hunt, Colleen, Jordan, David, Zhao, Yan, Chapman, Scott, Hammer, Graeme and George-Jaeggli, Barbara (2022). Estimating photosynthetic attributes from high-throughput canopy hyperspectral sensing in sorghum. Plant Phenomics, 2022 9768502, 1-18. doi: 10.34133/2022/9768502

Estimating photosynthetic attributes from high-throughput canopy hyperspectral sensing in sorghum

2022

Conference Publication

Frequency analysis of environment types associated with late-maturity alpha-amylase for Australian wheat under current and future climates

Armstrong, Robert, Hammer, Graeme and Potgieter, Andries (2022). Frequency analysis of environment types associated with late-maturity alpha-amylase for Australian wheat under current and future climates. 20th Australian Agronomy Conference , Toowoomba, QLD Australia, 19-22 September 2022. Australian Society of Agronomy.

Frequency analysis of environment types associated with late-maturity alpha-amylase for Australian wheat under current and future climates

2022

Conference Publication

A high-throughput phenotyping pipeline for rapid evaluation of morphological and physiological crop traits across large fields

Das, Sumanta, Massey-Reed, Sean Reynolds, Mahuika, Jenny, Watson, James, Cordova, Celso, Otto, Loren, Zhao, Yan, Chapman, Scott, George-Jaeggli, Barbara, Jordan, David, Hammer, Graeme L. and Potgieter, Andries B. (2022). A high-throughput phenotyping pipeline for rapid evaluation of morphological and physiological crop traits across large fields. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/IGARSS46834.2022.9884530

A high-throughput phenotyping pipeline for rapid evaluation of morphological and physiological crop traits across large fields

2022

Conference Publication

Crop type prediction utilising a long short-term memory with a self-attention for winter crops in Australia

Nguyen, Dung, Zhao, Yan, Zhang, Yifan, Huynh, Anh Ngoc-Lan, Roosta, Fred, Hammer, Graeme, Chapman, Scott and Potgieter, Andries (2022). Crop type prediction utilising a long short-term memory with a self-attention for winter crops in Australia. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IGARSS46834.2022.9883737

Crop type prediction utilising a long short-term memory with a self-attention for winter crops in Australia

2021

Conference Publication

Improving mungbean productivity

Van Haeften, Shanice, Kang, Yichen, Douglas, Colin, Potgieter, Andries, Voss-Fels, Kai, Hickey, Lee and Smith, Millicent (2021). Improving mungbean productivity. Australian Society of Plant Scientists Conference, Brisbane/Hybrid, 25 November 2021.

Improving mungbean productivity

2021

Conference Publication

Exploring variation in key traits to improve mungbean productivity

Van Haeften, Shanice, Kang, Yichen, Douglas, Colin, Potgieter, Andries, Voss-Fels, Kai, Hickey, Lee and Smith, Millicent (2021). Exploring variation in key traits to improve mungbean productivity. Bean Improvement Co-operative & North American Pulse Improvement Association Biennial Meeting, Virtual, 2-3 November 2021.

Exploring variation in key traits to improve mungbean productivity

2021

Journal Article

Genetic control of leaf angle in sorghum and its effect on light interception

Zhi, Xiaoyu, Tao, Yongfu, Jordan, David, Borrell, Andrew, Hunt, Colleen, Cruickshank, Alan, Potgieter, Andries, Wu, Alex, Hammer, Graeme, George-Jaeggli, Barbara and Mace, Emma (2021). Genetic control of leaf angle in sorghum and its effect on light interception. Journal of Experimental Botany, 73 (3) erab467, 801-816. doi: 10.1093/jxb/erab467

Genetic control of leaf angle in sorghum and its effect on light interception

2021

Journal Article

Detecting sorghum plant and head features from multispectral UAV imagery

Zhao, Yan, Zheng, Bangyou, Chapman, Scott C., Laws, Kenneth, George-Jaeggli, Barbara, Hammer, Graeme L., Jordan, David R. and Potgieter, Andries B. (2021). Detecting sorghum plant and head features from multispectral UAV imagery. Plant Phenomics, 2021 9874650, 9874650-14. doi: 10.34133/2021/9874650

Detecting sorghum plant and head features from multispectral UAV imagery

2021

Journal Article

Scaling up high-throughput phenotyping for abiotic stress selection in the field

Smith, Daniel T., Potgieter, Andries B. and Chapman, Scott C. (2021). Scaling up high-throughput phenotyping for abiotic stress selection in the field. Theoretical and Applied Genetics, 134 (6), 1845-1866. doi: 10.1007/s00122-021-03864-5

Scaling up high-throughput phenotyping for abiotic stress selection in the field

2021

Journal Article

Evolution and application of digital technologies to predict crop type and crop phenology in agriculture

Potgieter, A. B., Zhao, Yan, Zarco-Tejada, Pablo J, Chenu, Karine, Zhang, Yifan, Porker, Kenton, Biddulph, Ben, Dang, Yash P., Neale, Tim, Roosta, Fred and Chapman, Scott (2021). Evolution and application of digital technologies to predict crop type and crop phenology in agriculture. In Silico Plants, 3 (1) diab017, 1-23. doi: 10.1093/insilicoplants/diab017

Evolution and application of digital technologies to predict crop type and crop phenology in agriculture

2021

Conference Publication

Domain adaptation for plant organ detection with style transfer

James, Chrisbin, Gu, Yanyang, Chapman, Scott, Guo, Wei, David, Etienne, Madec, Simon, Potgieter, Andries and Eriksson, Anders (2021). Domain adaptation for plant organ detection with style transfer. International Conference on Digital Image Computing - Techniques and Applications (DICTA), Online, 29 November - 1 December 2021. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA52665.2021.9647293

Domain adaptation for plant organ detection with style transfer

2020

Journal Article

High-throughput phenotyping of dynamic canopy traits associated with stay-green in grain sorghum

Liedtke, J. D., Hunt, C. H., George-Jaeggli, B., Laws, K., Watson, J., Potgieter, A. B., Cruickshank, A. and Jordan, D. R. (2020). High-throughput phenotyping of dynamic canopy traits associated with stay-green in grain sorghum. Plant Phenomics, 2020 4635153, 1-10. doi: 10.34133/2020/4635153

High-throughput phenotyping of dynamic canopy traits associated with stay-green in grain sorghum

2020

Journal Article

Predicting wheat yield at the field scale by combining high-resolution sentinel-2 satellite imagery and crop modelling

Zhao, Yan, Potgieter, Andries B., Zhang, Miao, Wu, Bingfang and Hammer, Graeme L. (2020). Predicting wheat yield at the field scale by combining high-resolution sentinel-2 satellite imagery and crop modelling. Remote Sensing, 12 (6) 1024, 1024. doi: 10.3390/rs12061024

Predicting wheat yield at the field scale by combining high-resolution sentinel-2 satellite imagery and crop modelling

2020

Conference Publication

Quantifying drought tolerant crop traits using sensing technologies to enhance selection in sorghum breeding trials

Potgieter, A.B., Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Reynolds Massey-Reed, Sean, Lamprecht, Marnie, Liedtke, Jana D., Zhao, Yan, Chapman, Scott, Borrell, Andrew K., Mace, Emma S., Hammer, Graeme L. and Jordan, David R. (2020). Quantifying drought tolerant crop traits using sensing technologies to enhance selection in sorghum breeding trials. Interdrought 2020, Mexico City, Mexico, 9-13 March 2020.

Quantifying drought tolerant crop traits using sensing technologies to enhance selection in sorghum breeding trials

Funding

Current funding

  • 2024 - 2029
    ARC Training Centre in Predictive Breeding for Agricultural Futures
    ARC Industrial Transformation Training Centres
    Open grant
  • 2024 - 2027
    Root structure and function traits: Overcoming the root phenotyping bottleneck in cereals
    PROC-9176895 Phenomics methods and tools to enable improved resource capture efficiency in grain crops
    Open grant
  • 2023 - 2027
    Analytics for the Australian Grains Industry (AAGI)
    Grains Research & Development Corporation
    Open grant
  • 2021 - 2027
    Reducing lodging risk in sorghum to increase grower confidence and profitability
    Grains Research & Development Corporation
    Open grant
  • 2021 - 2025
    CropVision: A next-generation system for predicting crop production
    ARC Linkage Projects
    Open grant

Past funding

  • 2024 - 2025
    RiskSSmart: Digital tool for de-risking sorghum production decisions (SMART SAT CRC)
    SmartSat CRC
    Open grant
  • 2020 - 2024
    CropPhen: Remote mapping of grain crop type and phenology
    Grains Research & Development Corporation
    Open grant
  • 2020 - 2022
    Machine learning to extract maximum value from soil and crop variability (GRDC project administered by The University of Adelaide).
    University of Adelaide
    Open grant
  • 2020 - 2023
    LMA Project C: An improved model of Late Maturity Alpha-Amylase (LMA) field risk in Australian wheat
    Grains Research & Development Corporation
    Open grant
  • 2015 - 2019
    A Genetic x Environment characterization of the risk for Late Maturity Alpha-amylase across the main wheat producing shires of Australia
    Grains Research & Development Corporation
    Open grant
  • 2014 - 2019
    Sustainable intensification of maize-legume cropping systems for food security in Eastern and Southern Africa - Phase II (SIMLESA-2)
    International Maize and Wheat Improvement Centre
    Open grant
  • 2013
    Seeing is believing: The use of thermal sensing in predicting crop yield at field scale
    UQ Early Career Researcher
    Open grant
  • 2012 - 2015
    Integrating crop and livestock production for improved food security and livelihoods in rural Zimbabwe (ZimLESA; ACIAR project led by ILRI)
    International Livestock Research Institute
    Open grant
  • 2012 - 2014
    Sustainable intensification of maize-legume cropping system for food security in Eastern and Southern Africa (SIMLESA) - Ethiopian Extension
    International Maize and Wheat Improvement Centre
    Open grant
  • 2011 - 2012
    Determining the ability of crop water stress indices to capture yield, within the crop canopy/thermal space, through utilising remote sensing at a farm/paddock level
    UQ New Staff Research Start-Up Fund
    Open grant
  • 2011
    An analysis of spatial data for Zimbabwe (ACIAR project)
    Queensland Department of Employment, Economic Development and Innovation
    Open grant
  • 2010 - 2014
    Sustainable intensification of maize-legume cropping systems for enhancing food security in eastern and southern Africa (SIMLESA; CIMMYT-led ACIAR Project novated from DEEDI)
    International Maize and Wheat Improvement Centre
    Open grant
  • 2010
    Strategic Planning for investment based on agro-ecological zones
    Queensland Department of Employment, Economic Development and Innovation
    Open grant

Supervision

Availability

Associate Professor Andries Potgieter is:
Available for supervision

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Supervision history

Current supervision

Completed supervision

Media

Enquiries

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