A strategic partnership to empower grain growers through advanced analytics.
Analytics for the Australian Grains Industry (AAGI) brings together analytics research capabilities from across The University of Queensland to focus on research outputs for the Australian grains industry.
AAGI is an investment of the Grains Research and Development Corporation (GRDC), led by strategic partners Curtin University, UQ and the University of Adelaide, working with other supporting partners.
Our mission is to use analytics on grains data to help Australian grain growers to be more profitable and globally competitive.
Supporting field trials
UQ researchers bring expertise in statistics, on-farm experimentation, agronomy, remote sensing and environmental characterisation.
These capabilities support AAGI in designing, managing and analysing field trials to generate robust and scalable insights for agricultural systems.
Skills:
- small / large experimental design
- on-farm experimentation
- statistical modelling
- data analysis
- genotype
- environment interaction
- multi-environment trials
- multivariate analysis
- mixed models
- trial protocols
- agronomic evaluation
- sustainable practices
- satellite imagery analysis
- drone imagery
- vegetation indices
- climate modelling
- crop simulation
- GIS .
Supporting plant breeding
Our team supports plant breeding programs through advanced phenomics, genetics, bioinformatics, and breeding design.
These capabilities accelerate genetic gain, trait integration, and decision-making in breeding pipelines.
Skills:
- high-throughput phenotyping
- trait measurement
- molecular genetics
- genetic mapping
- genomic selection
- marker-assisted selection
- breeding program design
- hybridisation techniques
- quantitative genetics
- sequence alignment,
- data integration.
Adding value to experimental data
We enhance experimental data through computer vision, simulation, machine learning, sustainability modelling and supply chain analysis.
These capabilities enable predictive insights and strategic decisions across the production system.
Skills:
- crop simulation
- synthetic data generation
- predictive modelling
- yield prediction
- nitrogen estimation
- deep learning
- computer vision
- automated image analysis
- sustainability indicators
- stakeholder modelling
- economic assessment
- supply chain logistics.
Pipelines
We deliver streamlined tools to support spatial and temporal analyses in agricultural R&D.
Some of our tools are:
- Sentinel-2 Downloader: multi-date image extraction from Google Earth Engine using polygons
- SILO Downloader: historical BOM weather data download by geolocation in CSV format.
Please contact Dr Robert Armstrong or Professor Scott Chapman to access these tools.
Journal articles
Vaisman R, Scovell M, Kinaev N, Fernandez J. (2024). On the benefit of robust Bayesian confirmatory factor analysis. Structural Equation Modeling: A Multidisciplinary Journal. doi.org/10.1080/10705511.2024.2431981
Nguyen D, de Voil P, Potgieter A, Dang YP, Orton TG, Nyuyen DT, Nguyen TT, Chapman SC. (2025). Multimodal sequential cross-modal transformer for predicting plant available water capacity (PAWC) from time series of weather and crop biological data. Agric Water Manager, 307, 109124. doi.org/10.1016/j.agwat.2024.109124
Zijian Wang, Radek Zenkl, Latifa Greche , Benoit De Solan, Lucas Bernigaud Samatan, Safaa Ouahid, Andrea Visioni , Carlos A. Robles-Zazueta, Francisco Pinto, Ivan Perez-Olivera, Matthew P. Reynolds, Chen Zhu, Shouyang Liu, Marie-Pia D’argaignon, Raul Lopez-Lozano, Marie Weiss , Afef Marzougui, Lukas Roth, Sebastien Dandrifosse, Alexis Carlier, Benjamin Dumont, Benoıt Mercatoris, Javier Fernandez, Scott Chapman, Keyhan Najafian, Ian Stavness, Haozhou Wang, Wei Guo, Nicolas Virlet, Malcolm J Hawkesford, Zhi Chen, Etienne David, Joss Gillet, Kamran Irfan, Alexis Comar, and Andreas Hund. (2025). The Global Wheat Full Semantic Organ Segmentation (GWFSS) Dataset. bioRxiv. doi.org/10.1101/2025.03.18.642594
Conference papers
Li Y, Moghadam P, Peng C, Ye N, Koniusz P. (2025). Inductive Graph Few-shot Class Incremental Learning. The 18th ACM International Conference on Web Search and Data Mining, Hannover, Germany. wsdm-conference.org/2025/accepted-papers
Fernandez, J. A., Gho, C., Smith, D., Zheng, B., and Chapman, S.C. (2024). Assessing crop water use in wheat and sorghum National Variety Trials in Australia. 21st Australian Society of Agronomy Conference, Albany, WA, Australia. agronomyaustraliaproceedings.org/images/sampledata/2024/2024ASAfernandez_javier-194-1069-Fernandez-Javier.pdf
Conference abstracts
Arief Vivi, Jip Ramakers, Javier Hernandez, Martin Boer, Carla Gho, Fred van Eeuwijk, Scott Chapman. (2024). Evaluation of the trialing efficiency of Australia’s National Variety Trial Main Season among the Three Growing Regions. Genotype by Environment by Management Interactions (GxExM) Symposium III, Wageningen, Netherlands. 16.
Fernandez Javier A, Pengcheng Hu, Vivi Arief, Carla Gho, Jip Ramakers, Jesse Hemerik, Martin Boer, Fred van Eeuwijk, Scott Chapman. (2024). Multivariate characterisation of envirotypes for wheat GxE in Australian variety trials. Genotype by Environment by Management Interactions (GxExM) Symposium III, Wageningen, Netherlands. 38.
Hund Andreas, Jonas Anderegg, Alexis Carlier, Scott Chapman, Zhi Chen, Alexis Comar, Marie-Pia D'Argaignon, Sebastien Dandrifosse, Etienne David, Benoît De Solan, Benjamin Dumont, Joss Gillet, Evgeny Gladilin, Latifa Greche, Wei Guo, Malcolm J. Hawkesford, Kamran Irfan, Mehdi Khalaj, Norbert Kirchgessner, Shouyang Liu, Raul Lopez-Lozano, Afef Marzougui, Matthew Reynolds, Benoît Mercatoris, Ingo Mücke, Keyhan Najafian, Kerstin Neumann, Safaa Ouahid, Ian Stavness, Carlos Robles Zazueta, Nicolas Virlet, Andrea Visioni, Shuhei Nasuda, Zijian Wang, Haozhou Wang, Marie Weiss, Radek Zenkl. (2024). Global wheat full semantic segmentation of complex canopies. European Association for Research on Plant Breeding (EUCARPIA) General Conference on 'Global Challenges for Crop Improvement', Leipzig, Germany.
Fernandez, Javier A., Arief, Vivi, Hu, Pengcheng, Zheng, Bangyou, Gho, Carla, Ramakers, Jip, Boer, Martin, van Eeuwijk, Fred, and Chapman, Scott. (2024). Environment characterisation of wheat national variety trials in Australia. 3rd International Wheat Congress, Perth, WA, Australia.
GRDC publications
Analytics, Data and Phenomics. (2024). GRDC Ground Cover Supplement, 171, 1-24. groundcover.grdc.com.au/__data/assets/pdf_file/0015/603321/GCS_2407_Pages01-24_Analytics.pdf
Competitions
Wang, Z. (2024). Shape Completion and Reconstruction of Sweet Peppers Challenge. 1st place in the 9th Computer Vision in Plant Phenotyping and Agriculture (CVPPA) challenge workshop at the European Conference on Computer Vision (ECCV), Milan, Italy. cvppa2024.github.io/challenges/#shape-completion-and-reconstruction-of-sweet-peppers-challenge
AAGI strategic partners work with several project and associate partner organisations including leading Australian and international universities, federal and state government research agencies, and commercial technology and analytics providers.
AAGI at UQ is led by Professor Scott Chapman, Emeritus Professor Kaye Basford (Deputy Project Lead) and Elizabeth Meier (Operations), and is supported by researchers and staff from different centres and schools.
View the UQ experts in this project
