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2024

Conference Publication

From drones to satellites: biophysics-informed machine learning provides remote estimation of dynamic biomass across scales

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.

From drones to satellites: biophysics-informed machine learning provides remote estimation of dynamic biomass across scales

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 data

Hu, 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

Estimating aboveground biomass dynamics of wheat at small spatial scale by integrating crop growth and radiative transfer models with satellite remote sensing data

2024

Conference Publication

Insights in the ability of high-resolution narrow band multispectral and thermal sensors to estimate cotton production in Australia

Devoto, 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

Insights in the ability of high-resolution narrow band multispectral and thermal sensors to estimate cotton production in Australia

2024

Other Outputs

Enhancing crop trial data to strengthen variety decisions

Fernandez, Javier and Chapman, Scott (2024, 07 01). Enhancing crop trial data to strengthen variety decisions GRDC GroundCover Supplement: Analytics, Data and Phenomics 12-13.

Enhancing crop trial data to strengthen variety decisions

2024

Journal Article

Seasonal dynamics of fallow and cropping lands in the broadacre cropping region of Australia

Xie, 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

Seasonal dynamics of fallow and cropping lands in the broadacre cropping region of Australia

2024

Conference Publication

Unravelling the genetics of mungbean canopy dynamics using UAV-derived prediction models

Van 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.

Unravelling the genetics of mungbean canopy dynamics using UAV-derived prediction models

2024

Journal Article

GrainPointNet: a deep-learning framework for non-invasive sorghum panicle grain count phenotyping

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

GrainPointNet: a deep-learning framework for non-invasive sorghum panicle grain count phenotyping

2023

Journal Article

Preliminary results in innovative solutions for soil carbon estimation: integrating remote sensing, machine learning, and proximal sensing spectroscopy

Li, 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

Preliminary results in innovative solutions for soil carbon estimation: integrating remote sensing, machine learning, and proximal sensing spectroscopy

2023

Conference Publication

Toward a unified framework for RGB and RGB-D visual navigation

Du, 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

Toward a unified framework for RGB and RGB-D visual navigation

2023

Other Outputs

Capacity building and knowledge transfer in seaweed mapping in Indonesia

Abdul 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.

Capacity building and knowledge transfer in seaweed mapping in Indonesia

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 learning

Potgieter, 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

Advances in the study of biochemical, morphological and physiological traits of wheat and sorghum crops in australia using hyperspectral data and machine learning

2023

Journal Article

Modelling the impacts of diverse cover crops on soil water and nitrogen and cash crop yields in a sub-tropical dryland

Garba, 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

Modelling the impacts of diverse cover crops on soil water and nitrogen and cash crop yields in a sub-tropical dryland

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

Utilisation of unmanned aerial vehicle imagery to assess growth parameters in mungbean (Vigna radiata (L.) Wilczek)

2023

Conference Publication

Predicting yield in multi-environment breeding trials using penalized regression and multiple-covariate random-regression models

Ramakers, 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.

Predicting yield in multi-environment breeding trials using penalized regression and multiple-covariate random-regression models

2023

Conference Publication

Environment characterisation of sorghum GxE in Australia: Integrating APSIM and satellite imagery in NVT case study

Fernandez, 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.

Environment characterisation of sorghum GxE in Australia: Integrating APSIM and satellite imagery in NVT case study

2023

Journal Article

Coherent Terahertz laser feedback interferometry for hydration sensing in leaves

Kashyap, 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

Coherent Terahertz laser feedback interferometry for hydration sensing in leaves

2023

Conference Publication

In-season phenotyping of wheat growth by integrating imaging, bio-physical modelling and machine learning

Chen, 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.

In-season phenotyping of wheat growth by integrating imaging, bio-physical modelling and machine learning

2023

Journal Article

Global wheat head detection challenges: winning models and application for head counting

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

Global wheat head detection challenges: winning models and application for head counting

2023

Conference Publication

Evaluating variation in stem strength in response to artificial drought stress amongst sorghum genotypes

Geetika, Geetika, Borrell, Andrew, Thornton, Erin, Hunt, Colleen, Chapman, Scott, Philp, Trevor, Fekybelu, Solomon, Potgieter, Andries, Godwin, Ian, Hammer, Graeme, Mace, Emma and Jordan, David (2023). Evaluating variation in stem strength in response to artificial drought stress amongst sorghum genotypes. Global Sorghum Conference Sorghum in the 21st Century, Montpellier, France, 5-9 June 2023.

Evaluating variation in stem strength in response to artificial drought stress amongst sorghum genotypes

2023

Conference Publication

Environment characterisation of sorghum (Sorghum bicolor L.) crops using climate, satellite imagery, and crop simulation modelling in Australia

Javier A. Fernandez, Hu, Pengcheng, Chen, Zhi, Gho Brito, Carla, Segura Pinzon, Camilo, Chen, Qiaomin, Smith, Daniel, Arief, Vivi, Zheng, Bangyou, Potgieter, Andries, Zhao, Yan, Ramakers, Jip, Hemerik, Jesse, van Eeuwijk, Fred and Chapman, Scott C. (2023). Environment characterisation of sorghum (Sorghum bicolor L.) crops using climate, satellite imagery, and crop simulation modelling in Australia. Global Sorghum Conference, Montpellier, France, 5-9 June 2023.

Environment characterisation of sorghum (Sorghum bicolor L.) crops using climate, satellite imagery, and crop simulation modelling in Australia