Skip to menu Skip to content Skip to footer
Associate Professor Andries Potgieter
Associate Professor

Andries Potgieter

Email: 
Phone: 
+61 7 535 15085

Overview

Background

Associate Professor Andries Potgieter is a Principal Research Fellow at the Queensland Alliance for Agriculture and Food Innovation (QAAFI) at the University of Queensland. He currently leads and mentor a team of researchers in the areas of seasonal climate forecasting, remote and proximal sensing with applications in the development of crop production outlooks and less risk prone cropping systems across Australia, producing highly cited publications.

With over 30 years of experience, A/Prof Potgieter’s main research interest is in the complex integration of remote sensing technologies, spatial production modelling, climate forecasting systems at a regional scale. In particular, his interest targets agricultural research that enhances the profitability and sustainability of spatial production systems through a better understanding of the linkages and interactions of such systems across a range of spatial (e.g. field, farm, catchment, national), and temporal (i.e. seasons to decades) scales. He is a leader in the field of quantitative eco-physiological systems modelling and has successfully built up a national and international recognised research profile with strong linkages to industry (farmer groups, insurance, seed companies and bulk handlers of commodities) and domestic and national agencies (State governments, ABARES and ABS) as well as international linkages with Ag-Food Canada, Maryland University, USDA, Chinese Academy of Science (CAS), the Chinese Academy of Agricultural Sciences (CAAS) including the UN and FAO.

Recent research projects

  • Spatial and image analysis modelling specifically, phenotyping of sorghum breeding plots through drones and pheno mobile platforms (funded by ARC Centre of Excellence in Translational Photosynthesis)
  • Regional commodity forecasting and crop area estimates for winter and summer crops across the main broad cropping region of Australia (supported by QLD Government)
  • Development of a model to predict and determine the Genetic by Environment characterization of Late Maturity Alpha Amylase (LMA) risk across Australia (GRDC funded)

Previous research

  • Benchmarking and developing of novel metrics for the Insurance industry for hedging farmer’s risk against crop failures due to water stress within a shire)
  • Determining crop water stress within the thermal – crop canopy space at field scale.
  • Determining of food insecure “hotspots” for the SIMELSA project that provided a baseline analysis to help identify highly vulnerable regions across eastern Africa and listing of relevant and actionable issues of potentially high impact for research, development and increased investment.

Availability

Associate Professor Andries Potgieter is:
Available for supervision

Qualifications

  • Doctor of Philosophy, University of Southern Queensland

Works

Search Professor Andries Potgieter’s works on UQ eSpace

106 works between 1997 and 2024

21 - 40 of 106 works

2023

Other Outputs

LMA Risk maps at Shire scale

Armstrong, Robert, Potgieter, Andries, Brider, Jason and Hammer, Graeme (2023). LMA Risk maps at Shire scale. The University of Queensland. (Dataset) doi: 10.48610/1774e6f

LMA Risk maps at Shire scale

2022

Journal Article

Challenges and opportunities in remote sensing-based crop monitoring: a review

Wu, Bingfang, Zhang, Miao, Zeng, Hongwei, Tian, Fuyou, Potgieter, Andries B., Qin, Xingli, Yan, Nana, Chang, Sheng, Zhao, Yan, Dong, Qinghan, Boken, Vijendra, Plotnikov, Dmitry, Guo, Huadong, Wu, Fangming, Zhao, Hang, Deronde, Bart, Tits, Laurent and Loupian, Evgeny (2022). Challenges and opportunities in remote sensing-based crop monitoring: a review. National Science Review, 10 (4) nwac290, 1-34. doi: 10.1093/nsr/nwac290

Challenges and opportunities in remote sensing-based crop monitoring: a review

2022

Journal Article

Cover Image

Wu, Alex, Brider, Jason, Busch, Florian A., Chen, Min, Chenu, Karine, Clarke, Victoria C., Collins, Brian, Ermakova, Maria, Evans, John R., Farquhar, Graham D., Forster, Britta, Furbank, Robert T., Groszmann, Michael, Hernandez‐Prieto, Miguel A., Long, Benedict M., Mclean, Greg, Potgieter, Andries, Price, G. Dean, Sharwood, Robert E., Stower, Michael, van Oosterom, Erik, von Caemmerer, Susanne, Whitney, Spencer M. and Hammer, Graeme L. (2022). Cover Image. Plant, Cell & Environment, 46 (1). doi: 10.1111/pce.14512

Cover Image

2022

Conference Publication

Physiological insight to improve mungbean productivity

Smith, Millicent, Van Haeften, Shanice, Dudley, Caitlin, Douglas, Colin, Ryan, Merrill, Potgieter, Andries, Robinson, Hannah and Hickey, Lee (2022). Physiological insight to improve mungbean productivity. TropAg International Agriculture Conference, Brisbane, QLD Australia, 31 October - 2 November 2022.

Physiological insight to improve mungbean productivity

2022

Conference Publication

Understanding the genetics of mungbean canopy development using longitudinal UAV data

Van Haeften, Shanice, Kang, Yichen, Douglas, Colin, Dudley, Caitlin, Ryan, Merrill, Smith, Millicent, Chapman, Scott, Robinson, Hannah, Potgieter, Andries and Hickey, Lee (2022). Understanding the genetics of mungbean canopy development using longitudinal UAV data. International Plant Phenotyping Symposium, Wageningen, Netherlands, 27-30 September 2022.

Understanding the genetics of mungbean canopy development using longitudinal UAV data

2022

Conference Publication

Phenotyping innovations to harness genetic diversity for climate resilience

Smith, Millicent, Campbell, Bradley, Restall, Jemma, Dudley, Caitlin, Van Haeften, Shanice, Godwin, Ian, Chapman, Scott, Sukal, Amit, Robinson, Hannah, Ryan, Merrill, Potgieter, Andries and Hickey, Lee (2022). Phenotyping innovations to harness genetic diversity for climate resilience. International Plant Phenotyping Symposium, Wageningen, Netherlands, 27-30 September 2022.

Phenotyping innovations to harness genetic diversity for climate resilience

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

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

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

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

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

Funding

Current funding

  • 2024 - 2025
    RiskSSmart: Digital tool for de-risking sorghum production decisions (SMART SAT CRC)
    SmartSat CRC
    Open grant
  • 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

  • 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

Before you email them, read our advice on how to contact a supervisor.

Available projects

  • CropVision: A next-generation system for predicting crop production

    PhD scholarship opportunity exist within the CropVision ARC LP project.

    1. PhD Research aim: Predicting of drivers of plasticity in dry land farm businesses across Australia
    2. Skills: Mathematics, Economics, Bayesian Statistics

    email A/Prof A B Potgieter directly if interested at: a.potgieter@uq.edu.au

    Due to travel restrictions Domestic students are preferred.

    CropVision Summary:

    • Accurate and timely production estimates are essential to Australia’s grain producers and industry to better deal with downside risk caused by climate extremes and market volatilities. However, current systems for predicting crop production are inaccurate and unreliable. This project aims to develop a next generation system for advance and high accuracy predictions for yield, crop type and area at field scale. This will be done by integrating the state-of-the-art global climate models (GCM), biophysical crop modelling, and high-resolution earth observation technologies. This project will deliver a next generation crop prediction system to predict crop production at field scale for improved decision-making and enhancing resilience.

Supervision history

Current supervision

  • 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

  • Doctor Philosophy

    Using phenotyping and modelling methods to improve estimation of crop performance in variety trials

    Associate Advisor

    Other advisors: Professor Scott Chapman

  • 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

  • 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

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