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
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Analytics for the Australian Grains Industry (AAGI) – Digital analytics for yield forecasting and decision tools for grain growers (GRDC)
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CropVision – Satellite remote sensing and AI for field-scale crop production forecasting (ARC Linkage)
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RiskSSmart – Integration of Earth observation and climate models for sorghum risk mitigation (SmartSat CRC)
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Root Phenomics – Linking above-ground sensing to root system architecture to accelerate phenotyping of drought-tolerant cereals (GRDC; Chief Investigator)
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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
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Late Maturity Alpha Amylase (LMA) Risk Modelling – National-scale risk prediction framework for wheat quality (GRDC)
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CropPhen – High-throughput phenotyping for crop type and growth stage detection via drone/UAV (GRDC)
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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
Fields of research
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
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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.
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My seasonal yield forecasting models have been adopted by the Queensland Government and informed policy and logistics planning.
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Statistics Canada built their national crop forecasting system using frameworks I co-developed, showing international uptake.
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I co-developed YieldShield™, Australia’s first climate-based crop insurance product, which helped farmers manage drought risk.
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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
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Economic impact: My tools improve supply chain planning, reduce crop losses, and inform commodity trading and insurance.
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Environmental impact: Precision monitoring enables more efficient fertiliser use, reducing runoff and environmental harm.
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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
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
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
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
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
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
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
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.
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
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.
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.
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.
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.
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
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
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.
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.
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.
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.
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
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
Funding
Current funding
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
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Doctor Philosophy
Insights into the associations between functional above ground plant traits and root function for drought adaptation in sorghum.
Principal Advisor
Other advisors: Professor David Jordan, Dr Barbara George-Jaeggli, Dr Samir Alahmad, Dr Dongxue Zhao
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Doctor Philosophy
Determining the effects of abiotic stress on crop growth development, and yield under different nitrogen applications using remotely sensed data for cotton and wheat.
Principal Advisor
Other advisors: Professor Scott Chapman, Dr William Woodgate
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Doctor Philosophy
On-ground management of soil nutrients by integrating proximal and remote sensing platforms in northern Australian savannas grazing lands
Associate Advisor
Other advisors: Dr Yan Zhao, Professor Susanne Schmidt
Completed supervision
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2025
Doctor Philosophy
New insight and tools to increase yield potential and reliability in mungbean
Associate Advisor
Other advisors: Professor Lee Hickey, Dr Hannah Robinson, Dr Millicent Smith
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2025
Doctor Philosophy
Estimating biomass and radiation-use-efficiency in wheat variety trials using unmanned aerial vehicles
Associate Advisor
Other advisors: Professor Scott Chapman
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2024
Doctor Philosophy
New insights into designer root systems for durum wheat improvement
Associate Advisor
Other advisors: Professor David Jordan, Professor Emma Mace, Dr Samir Alahmad, Professor Lee Hickey
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2023
Master Philosophy
Crop sensing as a tool to assist data collection in maize agronomic trials
Associate Advisor
Other advisors: Dr Joe Eyre, Professor Daniel Rodriguez
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2022
Doctor Philosophy
Hyperspectral sensing methods and genome-wide association studies to improve photosynthetic capacity in sorghum
Associate Advisor
Other advisors: Professor Graeme Hammer, Dr Alex Wu, Dr Barbara George-Jaeggli
Media
Enquiries
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