Skip to menu Skip to content Skip to footer
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

61 - 80 of 122 works

2020

Book Chapter

Sorghum management systems and production technology around the globe

Ciampitti, I. A., Prasad, P. V. Vara, Kumar, S. R., Kubsad, V. S., Adam, M., Eyre, J. X., Potgieter, A. B., Clarke, S. J. and Gambin, B. (2020). Sorghum management systems and production technology around the globe. Sorghum in the 21st Century: Food - Fodder - Feed - Fuel for a Rapidly Changing World. (pp. 251-293) edited by Vilas A. Tonapi, Harvinder Singh Talwar, Ashok Kumar Are, B. Venkatesh Bhat, Ch. Ravinder Reddy and Timothy J. Dalton. Singapore: Springer. doi: 10.1007/978-981-15-8249-3_11

Sorghum management systems and production technology around the globe

2019

Journal Article

An integrated framework for predicting the risk of experiencing temperature conditions that may trigger late-maturity alpha-amylase in wheat across Australia

Armstrong, Robert N., Potgieter, Andries B., Mares, Daryl J., Mrva, Kolumbina, Brider, Jason and Hammer, Graeme L. (2019). An integrated framework for predicting the risk of experiencing temperature conditions that may trigger late-maturity alpha-amylase in wheat across Australia. Crop and Pasture Science, 71 (1), 1-11. doi: 10.1071/cp19005

An integrated framework for predicting the risk of experiencing temperature conditions that may trigger late-maturity alpha-amylase in wheat across Australia

2019

Journal Article

Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops

Furbank, Robert T., Jimenez‐Berni, Jose A., George‐Jaeggli, Barbara, Potgieter, Andries B. and Deery, David M. (2019). Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops. New Phytologist, 223 (4) nph.15817, 1714-1727. doi: 10.1111/nph.15817

Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops

2019

Journal Article

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Cai, Yaping, Guan, Kaiyu, Lobell, David, Potgieter, Andries B., Wang, Shaowen, Peng, Jian, Xu, Tianfang, Asseng, Senthold, Zhang, Yongguang, You, Liangzhi and Peng, Bin (2019). Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches. Agricultural and Forest Meteorology, 274, 144-159. doi: 10.1016/j.agrformet.2019.03.010

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

2019

Journal Article

A weakly supervised deep learning framework for sorghum head detection and counting

Ghosal, Sambuddha, Zheng, Bangyou, Chapman, Scott C., Potgieter, Andries B., Jordan, David R., Wang, Xuemin, Singh, Asheesh K., Singh, Arti, Hirafuji, Masayuki, Ninomiya, Seishi, Ganapathysubramanian, Baskar, Sarkar, Soumik and Guo, Wei (2019). A weakly supervised deep learning framework for sorghum head detection and counting. Plant Phenomics, 2019 1525874, 1525874-14. doi: 10.34133/2019/1525874

A weakly supervised deep learning framework for sorghum head detection and counting

2019

Journal Article

Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications

Newlands, Nathaniel K., Porcelli, Tracy A., Potgieter, Andries B., Kouadio, Louis, Huete, Alfredo and Guo, Wei (2019). Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications. Frontiers in Environmental Science, 7 (May) 71. doi: 10.3389/fenvs.2019.00071

Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications

2019

Conference Publication

Determining of targeted crop characteristics utilising sensing technologies to enhance selection of higher yielding varieties in sorghum breeding trials

Potgieter, Andries, Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Guo, Wei, Watson, James, Reynolds Massey-Reed, Sean, Chapman, Scott, Hammer, Graeme and Jordan, David (2019). Determining of targeted crop characteristics utilising sensing technologies to enhance selection of higher yielding varieties in sorghum breeding trials. Australian Summer Grains Conference, Gold Coast, QLD, Australia, 8-10 July 2019.

Determining of targeted crop characteristics utilising sensing technologies to enhance selection of higher yielding varieties in sorghum breeding trials

2019

Book Chapter

The use of hyperspectral proximal sensing for phenotyping of plant breeding trials

Potgieter, Andries B., Watson, James, George-Jaeggli, Barbara, McLean, Gregory, Eldridge, Mark, Chapman, Scott C., Laws, Kenneth, Christopher, Jack, Chenu, Karine, Borrell, Andrew, Hammer, Graeme and Jordan, David R. (2019). The use of hyperspectral proximal sensing for phenotyping of plant breeding trials. Fundamentals, sensor systems, spectral libraries, and data mining for vegetation. (pp. 127-148) edited by Prasad S. Thenkabail, John G. Lyon and Alfredo Huete. Boca Raton, FL United States: CRC Press. doi: 10.1201/9781315164151-5

The use of hyperspectral proximal sensing for phenotyping of plant breeding trials

2019

Conference Publication

High-throughput phenotyping tools to test whether leaf-level photosynthesis traits are measurable at the crop level

George-Jaeggli, Barbara, Potgieter, Andries, Zhi, Xiaoyu, Reynolds Massey-Reed, Sean, Watson, James, Lamprecht, Marnie, Chapman, Scott, Laws, Kenneth, Hunt, Colleen, Borrell, Andrew, Jordan, David, van Oosterom, Erik, Wu, Alex and Hammer, Graeme (2019). High-throughput phenotyping tools to test whether leaf-level photosynthesis traits are measurable at the crop level. TropAg 2019, Brisbane, QLD Australia, 10-13 November 2019.

High-throughput phenotyping tools to test whether leaf-level photosynthesis traits are measurable at the crop level

2019

Conference Publication

Seeing canopy photosynthesis through the eyes of a Gecko

George-Jaeggli, Barbara, Zhi, Xiaoyue, Wu, Alex, Potgieter, Andries, Reynolds Massey-Reed, Sean, Watson, James, Hunt, Colleen, Lamprecht, Marnie, Chapman, Scott, Borrell, Andrew, Jordan, David and Hammer, Graeme (2019). Seeing canopy photosynthesis through the eyes of a Gecko. Innovations in Agriculture for Food Security, Brisbane, QLD Australia, 30 June - 3 July 2019.

Seeing canopy photosynthesis through the eyes of a Gecko

2019

Conference Publication

Predicting lodging using sensing technologies to enhance selection in sorghum breeding trials

Potgieter, Andries, Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Guo, Wei, Reynolds Massey-Reed, Sean, Chapman, Scott, Borrell, Andrew, Mace, Emma, Hammer, Graeme and Jordan, David (2019). Predicting lodging using sensing technologies to enhance selection in sorghum breeding trials. 6th International Plant Phenotyping Symposium, Nanjing, China, 22-26 October 2019.

Predicting lodging using sensing technologies to enhance selection in sorghum breeding trials

2019

Conference Publication

High-throughput phenotyping of canopy radiation use efficiency and its component traits

George-Jaeggli, Barbara, Potgieter, Andries, Zhi, Xiaoyu, Reynolds Massey-Reed, Sean, Watson, James, Lamprecht, Marnie, Chapman, Scott, Laws, Kenneth, Hunt, Colleen, Borrell, Andrew, Jordan, David, van Oosterom, Erik, Wu, Alex and Hammer, Graeme (2019). High-throughput phenotyping of canopy radiation use efficiency and its component traits. 6th International Plant Phenotyping Symposium, Nanjing, China, 22-26 October 2019.

High-throughput phenotyping of canopy radiation use efficiency and its component traits

2018

Journal Article

Aerial imagery analysis – quantifying appearance and number of sorghum heads for applications in breeding and agronomy

Guo, Wei, Zheng, Bangyou, Potgieter, Andries B., Diot, Julien, Watanabe, Kakeru, Noshita, Koji, Jordan, David R., Wang, Xuemin, Watson, James, Ninomiya, Seishi and Chapman, Scott C. (2018). Aerial imagery analysis – quantifying appearance and number of sorghum heads for applications in breeding and agronomy. Frontiers in Plant Science, 9 1544, 1544. doi: 10.3389/fpls.2018.01544

Aerial imagery analysis – quantifying appearance and number of sorghum heads for applications in breeding and agronomy

2018

Journal Article

Estimation of plant height using a high throughput phenotyping platform based on unmanned aerial vehicle and self-calibration: Example for sorghum breeding

Hu, Pengcheng, Chapman, Scott C., Wang, Xuemin, Potgieter, Andries, Duan, Tao, Jordan, David, Guo, Yan and Zheng, Bangyou (2018). Estimation of plant height using a high throughput phenotyping platform based on unmanned aerial vehicle and self-calibration: Example for sorghum breeding. European Journal of Agronomy, 95, 24-32. doi: 10.1016/j.eja.2018.02.004

Estimation of plant height using a high throughput phenotyping platform based on unmanned aerial vehicle and self-calibration: Example for sorghum breeding

2018

Conference Publication

An integrated sensing approach to map the genetic loci associated with canopy radiation use efficiency in sorghum

George-Jaeggli, Barbara, Watson, James and Potgieter, Andries (2018). An integrated sensing approach to map the genetic loci associated with canopy radiation use efficiency in sorghum. 5th International Plant Phenotyping Symposium, Adelaide, Australia, 2-5 October 2018.

An integrated sensing approach to map the genetic loci associated with canopy radiation use efficiency in sorghum

2018

Conference Publication

Field phenotyping of sorghum breeding trials through proximal sensing technologies

Potgieter, Andries, Watson, James, Eldridge, Mark, Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Chapman, Scott, Jordan, David and Hammer, Graeme (2018). Field phenotyping of sorghum breeding trials through proximal sensing technologies. Sorghum in the 21st Century, Cape Town, South Africa, 9-12 April 2018.

Field phenotyping of sorghum breeding trials through proximal sensing technologies

2018

Conference Publication

Trial results - Tactical agronomy for sorghum and maize and agronomy for high yielding sorghum and wheat in the northern region

George-Jaeggli, Barbara, Potgieter, Andries, James, Watson, Chapman, Scott, Zheng, Bangyou, Eldridge, Mark, Laws, Kenneth, Mace, Emma, Hunt, Colleen, Hathorn, Adrian, Borrell, Andrew, Hammer, Graeme and Jordan, David (2018). Trial results - Tactical agronomy for sorghum and maize and agronomy for high yielding sorghum and wheat in the northern region. 2nd Asia-Pacific Plant Phenotyping Conference, Nanjing, China, 23- 25 March 2018.

Trial results - Tactical agronomy for sorghum and maize and agronomy for high yielding sorghum and wheat in the northern region

2018

Conference Publication

An integrated sensing platform to map the genetic loci associated with canopy radiation use efficiency in sorghum

George-Jaeggli, Barbara, Watson, James and Potgieter, Andries (2018). An integrated sensing platform to map the genetic loci associated with canopy radiation use efficiency in sorghum. Combio, Sydney, Australia, 23-26 September 2018.

An integrated sensing platform to map the genetic loci associated with canopy radiation use efficiency in sorghum

2018

Book Chapter

Visible, near infrared, and thermal spectral radiance on-board UAVs for high-throughput phenotyping of plant breeding trials

Chapman, Scott C., Zheng, Bangyou, Potgieter, Andries B., Guo, Wei, Baret, Frederic, Liu, Shouyang, Madec, Simon, Solan, Benoit, George-Jaeggli, Barbara, Hammer, Graeme L. and Jordan, David R. (2018). Visible, near infrared, and thermal spectral radiance on-board UAVs for high-throughput phenotyping of plant breeding trials. Biophysical and biochemical characterization and plant species studies. (pp. 275-299) edited by Prasad S. Thenkabail, John G. Lyon and Alfredo Huete. Boca Raton, FL, United States: CRC Press. doi: 10.1201/9780429431180-10

Visible, near infrared, and thermal spectral radiance on-board UAVs for high-throughput phenotyping of plant breeding trials

2018

Conference Publication

Determining crop growth dynamics in sorghum breeding trials through remote and proximal sensing technologies

Potgieter, Andries B., Watson, James, Eldridge, Mark, Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Borrell, Andrew, Mace, Emma, Chapman, Scott C., Jordan, David R. and Hammer, Graeme L. (2018). Determining crop growth dynamics in sorghum breeding trials through remote and proximal sensing technologies. 38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, Jul 22-27, 2018. NEW YORK: IEEE. doi: 10.1109/IGARSS.2018.8519296

Determining crop growth dynamics in sorghum breeding trials through remote and proximal sensing technologies

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

Looking for a supervisor? Read our advice on how to choose a supervisor.

Supervision history

Current supervision

Completed supervision

Media

Enquiries

For media enquiries about Associate Professor Andries Potgieter's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au