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2024 Conference Publication Dissecting the genetics of canopy dynamics in mungbean using longitudinal modelling of UAV-derived traitsVan Haeften, Shanice, Kang, Yichen, Smith, Daniel, Robinson, Hannah, Chapman, Scott, Potgieter, Andries, Hickey, Lee and Smith, Millicent (2024). Dissecting the genetics of canopy dynamics in mungbean using longitudinal modelling of UAV-derived traits. 11th International Conference on Legume Genetics and Genomics (ICLGG) 2024, Brisbane, QLD, Australia, 30 September - 3 October 2024. |
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2024 Conference Publication Environment characterisation of wheat national variety trials in AustraliaFernandez, 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, 22-27 September 2024. |
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2024 Conference Publication From drones to satellites: biophysics-informed machine learning provides remote estimation of dynamic biomass across scalesChen, 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. |
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2024 Journal Article Estimating aboveground biomass dynamics of wheat at small spatial scale by integrating crop growth and radiative transfer models with satellite remote sensing dataHu, Pengcheng, Zheng, Bangyou, Chen, Qiaomin, Grunefeld, Swaantje, Choudhury, Malini Roy, Fernandez, Javier, Potgieter, Andries and Chapman, Scott C. (2024). Estimating aboveground biomass dynamics of wheat at small spatial scale by integrating crop growth and radiative transfer models with satellite remote sensing data. Remote Sensing of Environment, 311 114277, 1-15. doi: 10.1016/j.rse.2024.114277 |
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2024 Conference Publication Insights in the ability of high-resolution narrow band multispectral and thermal sensors to estimate cotton production in AustraliaDevoto, F., Reynolds-Massey-Reed, S., Segura, Pinzon C., Bell, M., Mclaren, T., Awale, R., Camino, C., Bange, M., Woodgate, W., Chapman, S. and Potgieter, A. B. (2024). Insights in the ability of high-resolution narrow band multispectral and thermal sensors to estimate cotton production in Australia. 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 7-12 July 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/igarss53475.2024.10642663 |
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2024 Newspaper Article Enhancing crop trial data to strengthen variety decisionsFernandez, Javier and Chapman, Scott (2024, 07 01). Enhancing crop trial data to strengthen variety decisions GRDC GroundCover Supplement: Analytics, Data and Phenomics 12-13. |
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2024 Journal Article Seasonal dynamics of fallow and cropping lands in the broadacre cropping region of AustraliaXie, Zunyi, Zhao, Yan, Jiang, Ruizhu, Zhang, Miao, Hammer, Graeme, Chapman, Scott, Brider, Jason and Potgieter, Andries B. (2024). Seasonal dynamics of fallow and cropping lands in the broadacre cropping region of Australia. Remote Sensing of Environment, 305 114070, 1-14. doi: 10.1016/j.rse.2024.114070 |
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2024 Conference Publication Unravelling the genetics of mungbean canopy dynamics using UAV-derived prediction modelsVan Haeften, Shanice, Smith, Daniel, Dudley, Caitlin, Kang, Yichen, Douglas, Colin, Robinson, Hannah, Chapman, Scott, Potgieter, Andries, Hickey, Lee and Smith, Millicent (2024). Unravelling the genetics of mungbean canopy dynamics using UAV-derived prediction models. German Plant Breeding Conference 2024, Geisenheim, Germany, 19-21 March 2024. |
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2024 Journal Article GrainPointNet: a deep-learning framework for non-invasive sorghum panicle grain count phenotypingJames, 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 |
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2023 Journal Article Preliminary results in innovative solutions for soil carbon estimation: integrating remote sensing, machine learning, and proximal sensing spectroscopyLi, Tong, Xia, Anquan, McLaren, Timothy I., Pandey, Rajiv, Xu, Zhihong, Liu, Hongdou, Manning, Sean, Madgett, Oli, Duncan, Sam, Rasmussen, Peter, Ruhnke, Florian, Yüzügüllü, Onur, Fajraoui, Noura, Beniwal, Deeksha, Chapman, Scott, Tsiminis, Georgios, Smith, Chaya, Dalal, Ram C. and Dang, Yash P. (2023). Preliminary results in innovative solutions for soil carbon estimation: integrating remote sensing, machine learning, and proximal sensing spectroscopy. Remote Sensing, 15 (23) 5571, 1-17. doi: 10.3390/rs15235571 |
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2023 Conference Publication Toward a unified framework for RGB and RGB-D visual navigationDu, Heming, Huang, Zi, Chapman, Scott and Yu, Xin (2023). Toward a unified framework for RGB and RGB-D visual navigation. 36th Australasian Joint Conference on Artificial Intelligence, AJCAI 2023, Brisbane, QLD Australia, 28 November –1 December 2023. Singapore: Springer. doi: 10.1007/978-981-99-8391-9_29 |
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2023 Other Outputs Capacity building and knowledge transfer in seaweed mapping in IndonesiaAbdul Aziz, Ammar, Wicaksono, Prama, Arjasakusuma, Sanjiwana, Chapman, Scott, Langford, Zannie, Grunefeld, Swaantje, Azizan, Fathin Ayuni and Maishella, Amanda (2023). Capacity building and knowledge transfer in seaweed mapping in Indonesia. Melbourne, VIC, Australia: The Australia-Indonesia Centre. |
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2023 Conference Publication Advances in the study of biochemical, morphological and physiological traits of wheat and sorghum crops in australia using hyperspectral data and machine learningPotgieter, A. B., Camino, C., Poblete, T., Zhi, X., Reynolds-Massey-Reed, S., Zhao, Y., Belwalkar, A., Ruizhu, J., George-Jaeggli, B., Chapman, S., Jordan, D., Wu, A., Hammer, G. L. and J, Zarco-Tejada P. (2023). Advances in the study of biochemical, morphological and physiological traits of wheat and sorghum crops in australia using hyperspectral data and machine learning. 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA USA, 16-21 July 2023. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/igarss52108.2023.10282230 |
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2023 Journal Article Modelling the impacts of diverse cover crops on soil water and nitrogen and cash crop yields in a sub-tropical drylandGarba, Ismail I., Bell, Lindsay W., Chapman, Scott, deVoil, Peter, Kamara, Alpha Y. and Williams, Alwyn (2023). Modelling the impacts of diverse cover crops on soil water and nitrogen and cash crop yields in a sub-tropical dryland. Field Crops Research, 301 109019, 1-14. doi: 10.1016/j.fcr.2023.109019 |
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2023 Conference Publication Physiological insight and selection tools to support pulse crop improvementSmith, Millicent, Van Haeften, Shanice, Dudley, Caitlin, Dinglasan, Eric, Robinson, Hannah, Chapman, Scott, Potgieter, Andries, Hayes, Ben and Hickey, Lee (2023). Physiological insight and selection tools to support pulse crop improvement. Plant and Animal Genome Conference, Australia, Perth, WA, Australia, 20-22 September 2023. |
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2023 Journal Article Utilisation of unmanned aerial vehicle imagery to assess growth parameters in mungbean (Vigna radiata (L.) Wilczek)Xiong, Yiyi, Chiau, Lucas Mauro Rogerio, Wenham, Kylie, Collins, Marisa and Chapman, Scott C. (2023). Utilisation of unmanned aerial vehicle imagery to assess growth parameters in mungbean (Vigna radiata (L.) Wilczek). Crop and Pasture Science, 75 (1) CP22335CO. doi: 10.1071/cp22335 |
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2023 Conference Publication Predicting yield in multi-environment breeding trials using penalized regression and multiple-covariate random-regression modelsRamakers, Jip, Hemerik, Jesse, Boer, Martin, Bustos-Korts, Daniela, Fernandez, Javier A., Pengcheng Hu, Noviati, Vivi, Chapman, Scott and van Eeuwijk, Fred (2023). Predicting yield in multi-environment breeding trials using penalized regression and multiple-covariate random-regression models. Channel Network Conference 2023, Wageningen, Netherlands, 23-25 August 2023. |
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2023 Conference Publication Environment characterisation of sorghum GxE in Australia: Integrating APSIM and satellite imagery in NVT case studyFernandez, Javier A., Garba, Ismail, Hu, Pengcheng, Segura Pinzon, Camilo, Arief, Vivi, Gho, Carla, Ramakers, Jip, Hemerik, Jesse, Zheng, Bangyou, van Eeuwijk, Fred and Chapman, Scott C. (2023). Environment characterisation of sorghum GxE in Australia: Integrating APSIM and satellite imagery in NVT case study. AuSoRGM, Toowoomba, QLD, Australia, 8-9 August 2023. |
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2023 Journal Article Coherent Terahertz laser feedback interferometry for hydration sensing in leavesKashyap, Mayuri, Torniainen, Jari, Bertling, Karl, Kundu, Urbi, Singh, Khushboo, Donose, Bogdan, Gillespie, Tim, Lim, Yah Leng, Indjin, Dragan, Li, Lian He, Linfield, Edmund, Davies, Giles, Dean, Paul, Smith, Millicent, Chapman, Scott, Bandyopadhyay, Aparajita, Sengupta, Amartya and Rakic, Aleksandar (2023). Coherent Terahertz laser feedback interferometry for hydration sensing in leaves. Optics Express, 31 (15), 23877-23888. doi: 10.1364/oe.490217 |
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2023 Conference Publication In-season phenotyping of wheat growth by integrating imaging, bio-physical modelling and machine learningChen, Q., Zheng, B., Chenu, K., Chen, T., Hu, P. and Chapman, S.C. (2023). In-season phenotyping of wheat growth by integrating imaging, bio-physical modelling and machine learning. Asia-Pacific Plant Phenomics Conference, Sanya, China, 7-10 July 2023. |
