
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:
- Not available for supervision
Fields of research
Qualifications
- Doctor of Philosophy, University of Southern Queensland
Works
Search Professor Andries Potgieter’s works on UQ eSpace
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
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
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
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
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
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
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.
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
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.
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.
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
Funding
Current funding
Supervision
Availability
- Associate Professor Andries Potgieter is:
- Not available for supervision
Supervision history
Current supervision
-
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
-
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
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
-
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
-
2025
Doctor Philosophy
Estimating biomass and radiation-use-efficiency in wheat variety trials using unmanned aerial vehicles
Associate Advisor
Other advisors: Professor Scott Chapman
-
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
-
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
-
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
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