|
2026 Journal Article Distinguishing knowledge mapping from biophysical evidence: A Rejoinder to "Comment on 'Mapping Soil Organic Carbon Research in Conservation Agriculture'"Liu, Qingyang, Tian, Xin, Dalal, Ram C., Wu, Jinran, Xia, Anquan, Wu, Xiaoxuan, Li, Tong, McLachlan, Geoffrey J., Chapman, Scott and Dang, Yash P. (2026). Distinguishing knowledge mapping from biophysical evidence: A Rejoinder to "Comment on 'Mapping Soil Organic Carbon Research in Conservation Agriculture'". Farming System, 4 (4) 100255, 100255. doi: 10.1016/j.farsys.2026.100255 |
|
2026 Journal Article Synthesizing crop modelling and deep learning for remote estimation of wheat biomass dynamics from multispectral and weather observationsChen, Qiaomin, Chen, Zhi, Hu, Pengcheng, Zheng, Bangyou, Smith, Daniel T. L., Fernandez, Javier, Garba, Ismail I. and Chapman, Scott C. (2026). Synthesizing crop modelling and deep learning for remote estimation of wheat biomass dynamics from multispectral and weather observations. Artificial Intelligence in Agriculture. doi: 10.1016/j.aiia.2026.06.007 |
|
2026 Journal Article Versioned soil organic carbon maps for climate-resilient and sustainable cities: a ridge-penalised linear mixed-effects ensemble of MIR-based predictionsTian, Xin, Liu, Qingyang, Dalal, Ram C., Li, Tong, Wu, Jinran, McLachlan, Geoffrey J., Chapman, Scott and Dang, Yash P. (2026). Versioned soil organic carbon maps for climate-resilient and sustainable cities: a ridge-penalised linear mixed-effects ensemble of MIR-based predictions. Physics and Chemistry of the Earth, 143 104390, 1-15. doi: 10.1016/j.pce.2026.104390 |
|
2026 Journal Article From plots to commercial fields: scalable, transferable cotton morphology and productivity estimation using functional growth proxies from UAV and PlanetScope time seriesDevoto, Francesca, Bange, Michael, Camino, Carlos, Woodgate, William, Chapman, Scott and Potgieter, Andries (2026). From plots to commercial fields: scalable, transferable cotton morphology and productivity estimation using functional growth proxies from UAV and PlanetScope time series. Plant Phenomics, 8 (3) 100220, 100220. doi: 10.1016/j.plaphe.2026.100220 |
|
2026 Journal Article Mapping soil organic carbon research in conservation agriculture: a systematic reviewLiu, Qingyang, Tian, Xin, Dalal, Ram C., Wu, Jinran, Xia, Anquan, Wu, Xiaoxuan, Li, Tong, McLachlan, Geoffrey J., Chapman, Scott and Dang, Yash P. (2026). Mapping soil organic carbon research in conservation agriculture: a systematic review. Farming System, 4 (4) 100241, 100241. doi: 10.1016/j.farsys.2026.100241 |
|
2026 Journal Article Corrigendum to “Machine learning approaches for wheat yield prediction integrating biophysical modeling and remote sensing: Effects of sample size, dimensionality, and transferability” [Smart Agricultural Technology, Volume 13 (2026), Article 101936]Ashourloo, Davoud, Brider, Jason, Zhao, Yan, Jiang, Ruizhu, Zhang, Miao, Chapman, Scott, Hammer, Graeme and Potgieter, Andries B. (2026). Corrigendum to “Machine learning approaches for wheat yield prediction integrating biophysical modeling and remote sensing: Effects of sample size, dimensionality, and transferability” [Smart Agricultural Technology, Volume 13 (2026), Article 101936]. Smart Agricultural Technology 101983, 101983. doi: 10.1016/j.atech.2026.101983 |
|
2026 Other Outputs Sorghum diversity head counting datasetKarannagoda, Rukshan, Baktashmotlagh, Mahsa, Chapman, Scott, Wang, Zijian, Guo, Kaiyu, Luo, Yadan, James, Chrisbin and Zheng, Bangyou (2026). Sorghum diversity head counting dataset. The University of Queensland. (Dataset) doi: 10.48610/45beb77 |
|
2026 Journal Article Machine learning approaches for wheat yield prediction integrating biophysical modeling and remote sensing: effects of sample size, dimensionality, and transferabilityAshourloo, Davoud, Brader, Jason, Zhao, Yan, Jiang, Ruizhu, Zhang, Miao, Chapman, Scott, Hammer, Graeme and Potgieter, Andries B (2026). Machine learning approaches for wheat yield prediction integrating biophysical modeling and remote sensing: effects of sample size, dimensionality, and transferability. Smart Agricultural Technology, 13 101936, 1-13. doi: 10.1016/j.atech.2026.101936 |
|
2026 Journal Article A Large-Scale In-the-wild Dataset for Plant Disease SegmentationWei, Tianqi, Chen, Zhi, Yu, Xin, Chapman, Scott, Melloy, Paul and Huang, Zi (2026). A Large-Scale In-the-wild Dataset for Plant Disease Segmentation. Scientific Data, 13 (1) 205, 205. doi: 10.1038/s41597-025-06513-4 |
|
2026 Conference Publication Augment to segment: tackling pixel-level imbalance in wheat disease and pest segmentationWei, Tianqi, Yu, Xin, Chen, Zhi, Chapman, Scott and Huang, Zi (2026). Augment to segment: tackling pixel-level imbalance in wheat disease and pest segmentation. 36th Australasian Database Conference, Sydney, NSW Australia and Bali, Indonesia, 4-6 December 2025. Singapore: Springer Singapore. doi: 10.1007/978-981-95-6196-4_3 |
|
2026 Conference Publication Dynamic orchestration of multi-agent system for real-world multi-image agricultural VQAKe, Yan, Yu, Xin, Du, Heming, Chapman, Scott and Huang, Helen (2026). Dynamic orchestration of multi-agent system for real-world multi-image agricultural VQA. 36th Australasian Database Conference, Sydney, NSW Australia and Bali, Indonesia, 4-6 December 2025. Singapore: Springer Singapore. doi: 10.1007/978-981-95-6196-4_11 |
|
2026 Journal Article Sensor-based estimation of evapotranspiration and water use efficiency in Australian wheat variety trialsFernandez, Javier A, Gho, Carla, Smith, Daniel T, Hu, Pengcheng, Zheng, Bangyou and Chapman, Scott C (2026). Sensor-based estimation of evapotranspiration and water use efficiency in Australian wheat variety trials. in silico Plants, 8 (1) diag009, 1. doi: 10.1093/insilicoplants/diag009 |
|
2025 Conference Publication Cost-effective agronomic practices could unlock Australian wheat yield potentialLi, Siyi, Zheng, Bangyou, Hu, Pengcheng, Fernandez, Javier, Lei, Yeming, James, Chris, Chen, Qiaomin, Arief, Vivi and Chapman, Scott (2025). Cost-effective agronomic practices could unlock Australian wheat yield potential. The 26th International Congress on Modelling and Simulation (MODSIM2025), Adelaide, SA, Australia, 30 November-4 December 2025. |
|
2025 Conference Publication Integrating crop modelling and machine learning for non-destructive estimation of crop traitsChen, Qiaomin, Hu, Pengcheng, Zheng, Bangyou and Chapman, Scott (2025). Integrating crop modelling and machine learning for non-destructive estimation of crop traits. The 26th International Congress on Modelling and Simulation (MODSIM2025), Adelaide, SA Australia, 30 November-4 December 2025. |
|
2025 Journal Article Unmanned aerial vehicle phenotyping of agronomic and physiological traits in mungbeanVan 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 |
|
2025 Journal Article Phenotyping the hidden half: combining UAV phenotyping and machine learning to predict barley root traits in the fieldAlahmad, 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 |
|
2025 Journal Article The Global Wheat Full Semantic Organ Segmentation (GWFSS) datasetWang, Zijian, Zenkl, Radek, Greche, Latifa, De Solan, Benoit, Samatan, Lucas Bernigaud, Ouahid, Safaa, Visioni, Andrea, Robles-Zazueta, Carlos A., Pinto, Francisco, Perez-Olivera, Ivan, Reynolds, Matthew P., Zhu, Chen, Liu, Shouyang, D’argaignon, Marie-Pia, Lopez-Lozano, Raul, Weiss, Marie, Marzougui, Afef, Roth, Lukas, Dandrifosse, Sébastien, Carlier, Alexis, Dumont, Benjamin, Mercatoris, Benoît, Fernandez, Javier, Chapman, Scott, Najafian, Keyhan, Stavness, Ian, Wang, Haozhou, Guo, Wei, Virlet, Nicolas ... Hund, Andreas (2025). The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset. Plant Phenomics, 7 (3) 100084, 1-16. doi: 10.1016/j.plaphe.2025.100084 |
|
2025 Journal Article Characterising wheat and barley growth and phenology using multispectral remote sensing for site-specific precision agricultureZhao, Yan, Jiang, Ruizhu, Brider, Jason, Chapman, Scott and Potgieter, Andries (2025). Characterising wheat and barley growth and phenology using multispectral remote sensing for site-specific precision agriculture. In Silico Plants, 7 (2) diaf013. doi: 10.1093/insilicoplants/diaf013 |
|
2025 Conference Publication Physics-informed machine learning offers muti-scale remote estimation of wheat biomass dynamicsQiaomin, Chen, Chen, Zhi, Hu, Pengcheng, Zheng, Bangyou, Smith, Daniel, Fernandez, Javier, Garba, Ismail and Chapman, Scott (2025). Physics-informed machine learning offers muti-scale remote estimation of wheat biomass dynamics. 2025 IEEE International Geoscience and Remote Sensing Symposium, Brisbane, QLD Australia, 3-8 August 2025. |
|
2025 Conference Publication Quantifying cotton growth rate from multispectral UAV imagery at plot scaleDevoto, Francesca, Ashourloo, Davoud, Zhao, Yan, Jiang, Ruizhu, Awale, Rakesh, Bell, Michael, McLaren, Tim, Reynolds-Massey-Reed, Sean, Otto, Loren, Bange, Michael, Woodgate, William, Chapman, Scott and Potgieter, Andries (2025). Quantifying cotton growth rate from multispectral UAV imagery at plot scale. IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium, Brisbane, QLD, Australia, 3-8 August 2025. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/igarss55030.2025.11243794 |
