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2022 Journal Article Unsupervised plot-scale LAI phenotyping via UAV-based imaging, modelling, and machine learningChen, Qiaomin, Zheng, Bangyou, Chenu, Karine, Hu, Pengcheng and Chapman, Scott C. (2022). Unsupervised plot-scale LAI phenotyping via UAV-based imaging, modelling, and machine learning. Plant Phenomics, 2022 9768253, 1-19. doi: 10.34133/2022/9768253 |
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2022 Journal Article Integrating crop growth model and radiative transfer model to improve estimation of crop traits based on deep learningChen, Qiaomin, Zheng, Bangyou, Chen, Tong and Chapman, Scott C. (2022). Integrating crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning. Journal of Experimental Botany, 73 (19), 6558-6574. doi: 10.1093/jxb/erac291 |
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2022 Journal Article Phenological optimization of late reproductive phase for raising wheat yield potential in irrigated mega-environmentsHu, Pengcheng, Chapman, Scott C., Sukumaran, Sivakumar, Reynolds, Matthew and Zheng, Bangyou (2022). Phenological optimization of late reproductive phase for raising wheat yield potential in irrigated mega-environments. Journal of Experimental Botany, 73 (12), 4236-4249. doi: 10.1093/jxb/erac144 |
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2022 Conference Publication Adapting wheat to heat and drought in current and future climatesChenu, K., Collins, B., Zheng, B. and Chapman, S. (2022). Adapting wheat to heat and drought in current and future climates. Australasian Plant Breeding Conference, Gold Coast, QLD Australia, 9-12 May 2022. |
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2022 Conference Publication Integration of data across scales to predict genotype performance in National Variety TrialsChapman, Scott, Noviati, Vivi, Hu, Pengcheng, McLaren, Connar, Smith, Daniel, Choudhury, Malini, Chen, Zhi, Grunfeld, Swaantje, Zheng, Bangyou, van Eeuwijk, Fred, Bustos-Korts, Daniela, Boer, Martin, Hemerik, Jesse and Ramakers, Jip (2022). Integration of data across scales to predict genotype performance in National Variety Trials. Australasian Plant Breeding Conference, Gold Coast, QLD Australia, 9-11 May 2022. |
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2022 Journal Article Evaluation of drought tolerance of wheat genotypes in rain-fed sodic soil environments using high-resolution UAV remote sensing techniquesDas, Sumanta, Christopher, Jack, Roy Choudhury, Malini, Apan, Armando, Chapman, Scott, Menzies, Neal W. and Dang, Yash P. (2022). Evaluation of drought tolerance of wheat genotypes in rain-fed sodic soil environments using high-resolution UAV remote sensing techniques. Biosystems Engineering, 217, 68-82. doi: 10.1016/j.biosystemseng.2022.03.004 |
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2022 Journal Article A wiring diagram to integrate physiological traits of wheat yield potentialReynolds, Matthew Paul, Slafer, Gustavo Ariel, Foulkes, John Michael, Griffiths, Simon, Murchie, Erik Harry, Carmo-Silva, Elizabete, Asseng, Senthold, Chapman, Scott C., Sawkins, Mark, Gwyn, Jeff and Flavell, Richard Bailey (2022). A wiring diagram to integrate physiological traits of wheat yield potential. Nature Food, 3 (5), 318-324. doi: 10.1038/s43016-022-00512-z |
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2022 Journal Article Estimating photosynthetic attributes from high-throughput canopy hyperspectral sensing in sorghumZhi, Xiaoyu, Massey-Reed, Sean Reynolds, Wu, Alex, Potgieter, Andries, Borrell, Andrew, Hunt, Colleen, Jordan, David, Zhao, Yan, Chapman, Scott, Hammer, Graeme and George-Jaeggli, Barbara (2022). Estimating photosynthetic attributes from high-throughput canopy hyperspectral sensing in sorghum. Plant Phenomics, 2022 9768502, 1-18. doi: 10.34133/2022/9768502 |
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2022 Journal Article Detection of calcium, magnesium, and chlorophyll variations of wheat genotypes on sodic soils using hyperspectral red edge parametersRoy Choudhury, Malini, Christopher, Jack, Das, Sumanta, Apan, Armando, Menzies, Neal W., Chapman, Scott, Mellor, Vincent and Dang, Yash P. (2022). Detection of calcium, magnesium, and chlorophyll variations of wheat genotypes on sodic soils using hyperspectral red edge parameters. Environmental Technology & Innovation, 27 102469, 102469. doi: 10.1016/j.eti.2022.102469 |
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2022 Journal Article Quantifying the effects of varietal types × management on the spatial variability of sorghum biomass across US environmentsOjeda, Jonathan J., Hammer, Graeme, Yang, Kai‐Wei, Tuinstra, Mitchell R., deVoil, Peter, McLean, Greg, Huber, Isaiah, Volenec, Jeffrey J., Brouder, Sylvie M., Archontoulis, Sotirios and Chapman, Scott C. (2022). Quantifying the effects of varietal types × management on the spatial variability of sorghum biomass across US environments. GCB Bioenergy, 14 (3), 411-433. doi: 10.1111/gcbb.12919 |
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2022 Conference Publication A high-throughput phenotyping pipeline for rapid evaluation of morphological and physiological crop traits across large fieldsDas, Sumanta, Massey-Reed, Sean Reynolds, Mahuika, Jenny, Watson, James, Cordova, Celso, Otto, Loren, Zhao, Yan, Chapman, Scott, George-Jaeggli, Barbara, Jordan, David, Hammer, Graeme L. and Potgieter, Andries B. (2022). A high-throughput phenotyping pipeline for rapid evaluation of morphological and physiological crop traits across large fields. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/IGARSS46834.2022.9884530 |
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2022 Conference Publication Crop type prediction utilising a long short-term memory with a self-attention for winter crops in AustraliaNguyen, Dung, Zhao, Yan, Zhang, Yifan, Huynh, Anh Ngoc-Lan, Roosta, Fred, Hammer, Graeme, Chapman, Scott and Potgieter, Andries (2022). Crop type prediction utilising a long short-term memory with a self-attention for winter crops in Australia. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IGARSS46834.2022.9883737 |
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2021 Journal Article Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environmentsHu, Pengcheng, Chapman, Scott C., Dreisigacker, Susanne, Sukumaran, Sivakumar, Reynolds, Matthew and Zheng, Bangyou (2021). Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments. Journal of Experimental Botany, 72 (20), 7203-7218. doi: 10.1093/jxb/erab326 |
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2021 Journal Article Detecting sorghum plant and head features from multispectral UAV imageryZhao, Yan, Zheng, Bangyou, Chapman, Scott C., Laws, Kenneth, George-Jaeggli, Barbara, Hammer, Graeme L., Jordan, David R. and Potgieter, Andries B. (2021). Detecting sorghum plant and head features from multispectral UAV imagery. Plant Phenomics, 2021 9874650, 9874650-14. doi: 10.34133/2021/9874650 |
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2021 Journal Article Global Wheat Head Detection 2021: an improved dataset for benchmarking wheat head detection methodsDavid, 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 |
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2021 Journal Article Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learningDas, Sumanta, Christopher, Jack, Apan, Armando, Choudhury, Malini Roy, Chapman, Scott, Menzies, Neal W. and Dang, Yash P. (2021). Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learning. Agricultural and Forest Meteorology, 307 108477, 108477. doi: 10.1016/j.agrformet.2021.108477 |
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2021 Journal Article Improving biomass and grain yield prediction of wheat genotypes on sodic soil using integrated high-resolution multispectral, hyperspectral, 3D point cloud, and machine learning techniquesRoy Choudhury, Malini, Das, Sumanta, Christopher, Jack, Apan, Armando, Chapman, Scott, Menzies, Neal W. and Dang, Yash P. (2021). Improving biomass and grain yield prediction of wheat genotypes on sodic soil using integrated high-resolution multispectral, hyperspectral, 3D point cloud, and machine learning techniques. Remote Sensing, 13 (17) 3482, 3482. doi: 10.3390/rs13173482 |
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2021 Journal Article Improving estimation of in-season crop water use and health of wheat genotypes on sodic soils using spatial interpolation techniques and multi-component metricsChoudhury, Malini Roy, Mellor, Vincent, Das, Sumanta, Christopher, Jack, Apan, Armando, Menzies, Neal W., Chapman, Scott and Dang, Yash P. (2021). Improving estimation of in-season crop water use and health of wheat genotypes on sodic soils using spatial interpolation techniques and multi-component metrics. Agricultural Water Management, 255 107007, 1-16. doi: 10.1016/j.agwat.2021.107007 |
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2021 Journal Article UAV-thermal imaging: a technological breakthrough for monitoring and quantifying crop abiotic stress to help sustain productivity on sodic soils – a case review on wheatDas, Sumanta, Chapman, Scott, Christopher, Jack, Roy Choudhury, Malini, Menzies, Neal W., Apan, Armando and Dang, Yash P. (2021). UAV-thermal imaging: a technological breakthrough for monitoring and quantifying crop abiotic stress to help sustain productivity on sodic soils – a case review on wheat. Remote Sensing Applications: Society and Environment, 23 100583, 1-13. doi: 10.1016/j.rsase.2021.100583 |
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2021 Journal Article Comparison of modelling strategies to estimate phenotypic values from an unmanned aerial vehicle with spectral and temporal vegetation indexesHu, Pengcheng, Chapman, Scott C., Jin, Huidong, Guo, Yan and Zheng, Bangyou (2021). Comparison of modelling strategies to estimate phenotypic values from an unmanned aerial vehicle with spectral and temporal vegetation indexes. Remote Sensing, 13 (14) 2827, 1-19. doi: 10.3390/rs13142827 |
