Dr Daniel Smith
Postdoctoral Research Fellow
School of Agriculture and Food Sustainability
Researcher biography
I am a Postdoctoral Research Fellow at the University of Queensland, specialising in crop physiology, remote sensing, and high-throughput phenotyping. My work focuses on using drone-based imaging systems, 3D modelling, and machine learning to estimate complex plant traits in the field. I currently lead the UQ node of the Australian Plant Phenomics Network (APPN), where I support a range of research projects focused on improving how we measure crop performance. My recent work has involved developing UAV-based pipelines to estimate biomass and radiation-use efficiency in wheat, and applying image-based methods to improve trait prediction in a range of crops.
My areas of expertise include:
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UAV and sensor-based crop monitoring
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Multispectral and RGB imagery analysis
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Data pipelines for variety trials
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Field-based trait modelling and phenotyping automation
Publications
Journal Articles
Van Haeften, Shanice, Smith, Daniel, Robinson, Hannah, Dudley, Caitlin, Kang, Yichen, Douglas, Colin A., Hickey, Lee T., Potgieter, Andries, Chapman, Scott and Smith, Millicent R. (2025). Unmanned aerial vehicle phenotyping of agronomic and physiological traits in mungbean. The Plant Phenome Journal, 8 (1) e70016, 1-18. doi: 10.1002/ppj2.70016
Alahmad, Samir, Smith, Daniel, Katsikis, Christina, Aldiss, Zachary, Brunner, Stephanie M., Meer, Sarah V., Meijer, Lotus, Heidariask, Bita, Chenu, Karine, Chapman, Scott, Potgieter, Andries B., Wasson, Anton, Baraibar, Silvina, Godoy, Jayfred, Moody, David, Robinson, Hannah and Hickey, Lee T. (2025). Phenotyping the hidden half: combining UAV phenotyping and machine learning to predict barley root traits in the field. Journal of Experimental Botany, 76 (17) eraf268, 5161-5178. doi: 10.1093/jxb/eraf268
Smith, Daniel T. L., Chen, Qiaomin, Massey-Reed, Sean Reynolds, Potgieter, Andries B. and Chapman, Scott C. (2024). Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location. Plant Methods, 20 (1) 129, 129. doi: 10.1186/s13007-024-01236-w
James, Chrisbin, Smith, Daniel, He, Weigao, Chandra, Shekhar S. and Chapman, Scott C. (2024). GrainPointNet: a deep-learning framework for non-invasive sorghum panicle grain count phenotyping. Computers and Electronics in Agriculture, 217 108485, 108485. doi: 10.1016/j.compag.2023.108485
David, Etienne, Ogidi, Franklin, Smith, Daniel, Chapman, Scott, de Solan, Benoit, Guo, Wei, Baret, Frederic and Stavness, Ian (2023). Global wheat head detection challenges: winning models and application for head counting. Plant Phenomics, 5 0059, 1-14. doi: 10.34133/plantphenomics.0059
Van Haeften, Shanice, Dudley, Caitlin, Kang, Yichen, Smith, Daniel, Nair, Ramakrishnan M., Douglas, Colin A., Potgieter, Andries, Robinson, Hannah, Hickey, Lee T. and Smith, Millicent R. (2023). Building a better Mungbean: breeding for reproductive resilience in a changing climate. Food and Energy Security, 12 (6) e467. doi: 10.1002/fes3.467
Madec, Simon, Irfan, Kamran, Velumani, Kaaviya, Baret, Frederic, David, Etienne, Daubige, Gaetan, Samatan, Lucas Bernigaud, Serouart, Mario, Smith, Daniel, James, Chrisbin, Camacho, Fernando, Guo, Wei, De Solan, Benoit, Chapman, Scott C. and Weiss, Marie (2023). VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation. Scientific Data, 10 (1) 302, 1-12. doi: 10.1038/s41597-023-02098-y
Dang, Yash P., Martinez, Cristina, Smith, Daniel, Rowlings, David, Grace, Peter and Bell, Mike (2021). Maize production and nitrous oxide emissions from enhanced efficiency nitrogen fertilizers. Nutrient Cycling in Agroecosystems, 121 (2-3), 191-208. doi: 10.1007/s10705-021-10171-4
David, Etienne, Serouart, Mario, Smith, Daniel, Madec, Simon, Velumani, Kaaviya, Liu, Shouyang, Wang, Xu, Pinto, Francisco, Shafiee, Shahameh, Tahir, Izzat S. A., Tsujimoto, Hisashi, Nasuda, Shuhei, Zheng, Bangyou, Kirchgessner, Norbert, Aasen, Helge, Hund, Andreas, Sadhegi-Tehran, Pouria, Nagasawa, Koichi, Ishikawa, Goro, Dandrifosse, Sébastien, Carlier, Alexis, Dumont, Benjamin, Mercatoris, Benoit, Evers, Byron, Kuroki, Ken, Wang, Haozhou, Ishii, Masanori, Badhon, Minhajul A., Pozniak, Curtis ... Guo, Wei (2021). Global Wheat Head Detection 2021: an improved dataset for benchmarking wheat head detection methods. Plant Phenomics, 2021 9846158, 1-9. doi: 10.34133/2021/9846158
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
Conference 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, 21-24 October 2024. Australian Society of Agronomy.
Chen, Qiaomin, Chen, Zhi, Hu, Pengcheng, Zheng, Bangyou, Smith, Daniel T.L., Fernandez, Javier, Garba, Ismail I. and Chapman, Scott C. (2024). From drones to satellites: biophysics-informed machine learning provides remote estimation of dynamic biomass across scales. 3rd International Wheat Congress, Perth, WA Australia, 22-27 September 2024. Perth, WA Australia: IWC.
Thesis
Smith, Daniel (2025). Estimating biomass and radiation-use-efficiency in wheat variety trials using unmanned aerial vehicles. PhD Thesis, School of Agriculture and Food Sustainability, The University of Queensland. doi: 10.14264/e2a7de4
Seminar Paper
Alahmad, Samir, Kang, Yichen, Rambla, Charlotte, Van Der Meer, Sarah, Smith, Millicent, Christopher, Jack, Chenu, Karine, Able, Jason A., Voss-Fels, Kai, Jordan, David R., Borrell, Andrew K., Smith, Daniel, Chapman, Scott, Watt, Michelle, Ober, Eric, Potgieter, Andries B., Wasson, Anton, Hickey, Lee T. and Robinson, Hannah (2022). Exploring root-shoot dynamics to enhance yield potential and stability of future wheat cultivars. Australian Breeding Assembly, August 2022, Narrabri, NSW, Australia. Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane.
Data Collections
Gho Brito, Carla, Chapman, Scott, Smith, Daniel, Chen, Xiaolong, James, Chris, MUGAMBA, Edward, Oya, Riku and Cave, Lleyton (2025). 2024 Scott Teaching Trial. The University of Queensland. (Dataset) doi: 10.48610/808c370
Chapman, Scott and Smith, Daniel (2023). INVITA Core site UAV dataset. The University of Queensland. (Dataset) doi: 10.48610/951f13c
Chapman, Scott and Smith, Daniel (2023). INVITA Core site Ground-Based HTP platform Data. The University of Queensland. (Dataset) doi: 10.48610/346651e