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2021 Journal Article Integrating crop growth models with remote sensing for predicting biomass yield of sorghumYang, Kai-Wei, Chapman, Scott, Carpenter, Neal, Hammer, Graeme, McLean, Greg, Zheng, Bangyou, Chen, Yuhao, Delp, Edward, Masjedi, Ali, Crawford, Melba, Ebert, David, Habib, Ayman, Thompson, Addie, Weil, Clifford and Tuinstra, Mitchell R (2021). Integrating crop growth models with remote sensing for predicting biomass yield of sorghum. In Silico Plants, 3 (1) diab001, 1-19. doi: 10.1093/insilicoplants/diab001 |
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2021 Journal Article Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functionsCooper, M., Powell, O., Voss-Fels, K. P., Messina, C. D., Gho, C., Podlich, D. W., Technow, F., Chapman, S. C., Beveridge, C. A., Ortiz-Barrientos, D. and Hammer, G. L. (2021). Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions. in silico Plants, 3 (1) diaa016, 1-21. doi: 10.1093/insilicoplants/diaa016 |
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2021 Conference Publication Domain adaptation for plant organ detection with style transferJames, Chrisbin, Gu, Yanyang, Chapman, Scott, Guo, Wei, David, Etienne, Madec, Simon, Potgieter, Andries and Eriksson, Anders (2021). Domain adaptation for plant organ detection with style transfer. International Conference on Digital Image Computing - Techniques and Applications (DICTA), Online, 29 November - 1 December 2021. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/DICTA52665.2021.9647293 |
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2020 Conference Publication UAV-thermal imaging: A robust technology to evaluate in-field crop water stress and yield variation of wheat genotypesDas, Sumanta, Christopher, Jack, Apan, Armando, Roy Choudhury, Malini, Chapman, Scott, Menzies, Neal W. and Dang, Yash P. (2020). UAV-thermal imaging: A robust technology to evaluate in-field crop water stress and yield variation of wheat genotypes. IEEE India Geoscience and Remote Sensing Symposium (InGARSS), Ahmedabad, India, 1-4 December 2020. Piscataway, NJ, United States: IEEE. doi: 10.1109/ingarss48198.2020.9358955 |
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2020 Journal Article Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high-resolution rgb-labelled images to develop and benchmark wheat head detection methodsDavid, E., Madec, Shouyang, Sadeghi-Tehran, Pouria, Aasen, Helge, Zheng, B., Liu, Simon, Kirchgessner, Norbert, Ishikawa, Goro, Nagasawa, Koichi, Badhon, Minhajul A., Pozniak, Curtis, de Solan, Benoit, Hund, Andreas, Chapman, Scott C., Baret, Fred, Stavness, Ian and Guo, Wei (2020). Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high-resolution rgb-labelled images to develop and benchmark wheat head detection methods. Plant Phenomics, 2020 3521852, 1-12. doi: 10.34133/2020/3521852 |
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2020 Journal Article Breeder friendly phenotypingReynolds, Matthew, Chapman, Scott, Crespo-Herrera, Leonardo, Molero, Gemma, Mondal, Suchismita, Pequeno, Diego N.L., Pinto, Francisco, Pinera-Chavez, Francisco J., Poland, Jesse, Rivera-Amado, Carolina, Saint Pierre, Carolina and Sukumaran, Sivakumar (2020). Breeder friendly phenotyping. Plant Science, 295 110396, 110396. doi: 10.1016/j.plantsci.2019.110396 |
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2020 Conference Publication Understanding crop environments to adapt management practices and assist breedingChenu, K., Ababaei, B., Zheng, B., Chapman, S. and Hammer, G. (2020). Understanding crop environments to adapt management practices and assist breeding. InterDrought, Mexico City, Mexico, 9-13 March 2020. |
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2020 Journal Article Linking genetic maps and simulation to optimize breeding for wheat flowering time in current and future climatesBogard, Matthieu, Biddulph, Ben, Zheng, Bangyou, Hayden, Matthew, Kuchel, Haydn, Mullan, Dan, Allard, Vincent, Gouis, Jacques Le and Chapman, Scott C. (2020). Linking genetic maps and simulation to optimize breeding for wheat flowering time in current and future climates. Crop Science, 60 (2), 678-699. doi: 10.1002/csc2.20113 |
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2020 Journal Article Designing crops for adaptation to the drought and high-temperature risks anticipated in future climatesHammer, Graeme. L., McLean, Greg, van Oosterom, Erik, Chapman, Scott, Zheng, Bangyou, Wu, Alex, Doherty, Alastair and Jordan, David (2020). Designing crops for adaptation to the drought and high-temperature risks anticipated in future climates. Crop Science, 60 (2), 605-621. doi: 10.1002/csc2.20110 |
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2020 Conference Publication APSIM platform for modelling and simulation of agricultural systems: overview, examples and applicationsHammer, G., Chapman, S., Chenu, K. and McLean, G. (2020). APSIM platform for modelling and simulation of agricultural systems: overview, examples and applications. CGIAR Webinar - Platform for Big Data in Agriculture, Virtual, 6 February 2020. |
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2020 Conference Publication Integrated high-throughput phenotyping with high resolution multispectral, hyperspectral and 3D point cloud techniques for screening wheat genotypes on sodic soilsChoudhury, Malini Roy, Christopher, Jack, Apan, Armando, Chapman, Scott, Menzies, Neal and Dang, Yash (2020). Integrated high-throughput phenotyping with high resolution multispectral, hyperspectral and 3D point cloud techniques for screening wheat genotypes on sodic soils. Third International Tropical Agriculture Conference (TROPAG 2019), Brisbane, Australia, 11–13 November 2019. Basel, Switzerland: MDPI . doi: 10.3390/proceedings2019036206 |
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2020 Conference Publication Quantifying drought tolerant crop traits using sensing technologies to enhance selection in sorghum breeding trialsPotgieter, A.B., Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Reynolds Massey-Reed, Sean, Lamprecht, Marnie, Liedtke, Jana D., Zhao, Yan, Chapman, Scott, Borrell, Andrew K., Mace, Emma S., Hammer, Graeme L. and Jordan, David R. (2020). Quantifying drought tolerant crop traits using sensing technologies to enhance selection in sorghum breeding trials. Interdrought 2020, Mexico City, Mexico, 9-13 March 2020. |
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2019 Journal Article From QTLs to adaptation landscapes: using genotype-to-phenotype models to characterize G×E over timeBustos-Korts, Daniela, Malosetti, Marcos, Chenu, Karine, Chapman, Scott, Boer, Martin P., Zheng, Bangyou and van Eeuwijk, Fred A. (2019). From QTLs to adaptation landscapes: using genotype-to-phenotype models to characterize G×E over time. Frontiers in Plant Science, 10 1540, 1540. doi: 10.3389/fpls.2019.01540 |
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2019 Journal Article Combining crop growth modeling and statistical genetic modeling to evaluate phenotyping strategiesBustos-Korts, Daniela, Boer, Martin P., Malosetti, Marcos, Chapman, Scott, Chenu, Karine, Zheng, Bangyou and van Eeuwijk, Fred (2019). Combining crop growth modeling and statistical genetic modeling to evaluate phenotyping strategies. Frontiers in Plant Science, 10 1491, 1491. doi: 10.3389/fpls.2019.01491 |
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2019 Journal Article Pixel size of aerial imagery constrains the applications of unmanned aerial vehicle in crop breedingHu, Pengcheng, Guo, Wei, Chapman, Scott C., Guo, Yan and Zheng, Bangyou (2019). Pixel size of aerial imagery constrains the applications of unmanned aerial vehicle in crop breeding. ISPRS Journal of Photogrammetry and Remote Sensing, 154, 1-9. doi: 10.1016/j.isprsjprs.2019.05.008 |
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2019 Journal Article Evaluation of the phenotypic repeatability of canopy temperature in wheat using continuous-terrestrial and airborne measurementsDeery, David M., Rebetzke, Greg J., Jimenez-Berni, Jose A., Bovill, William D., James, Richard A., Condon, Anthony G., Furbank, Robert T., Chapman, Scott C. and Fischer, Ralph A. (2019). Evaluation of the phenotypic repeatability of canopy temperature in wheat using continuous-terrestrial and airborne measurements. Frontiers in Plant Science, 10 875, 875. doi: 10.3389/fpls.2019.00875 |
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2019 Journal Article A weakly supervised deep learning framework for sorghum head detection and countingGhosal, Sambuddha, Zheng, Bangyou, Chapman, Scott C., Potgieter, Andries B., Jordan, David R., Wang, Xuemin, Singh, Asheesh K., Singh, Arti, Hirafuji, Masayuki, Ninomiya, Seishi, Ganapathysubramanian, Baskar, Sarkar, Soumik and Guo, Wei (2019). A weakly supervised deep learning framework for sorghum head detection and counting. Plant Phenomics, 2019 1525874, 1525874-14. doi: 10.34133/2019/1525874 |
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2019 Journal Article Improving process-based crop models to better capture genotype×environment×management interactionsWang, Enli, Brown, Hamish E., Rebetzke, Greg J., Zhao, Zhigan, Zheng, Bangyou and Chapman, Scott C. (2019). Improving process-based crop models to better capture genotype×environment×management interactions. Journal of Experimental Botany, 70 (9), 2389-2401. doi: 10.1093/jxb/erz092 |
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2019 Journal Article Modelling impact of early vigour on wheat yield in dryland regionsZhao, Zhigan, Rebetzke, Greg J., Zheng, Bangyou, Chapman, Scott C. and Wang, Enli (2019). Modelling impact of early vigour on wheat yield in dryland regions. Journal of Experimental Botany, 70 (9), 2535-2548. doi: 10.1093/jxb/erz069 |
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2019 Journal Article A new probabilistic forecasting model for canopy temperature with consideration of periodicity and parameter variationShao, Quanxi, Bange, Michael, Mahan, James, Jin, Huidong, Jamali, Hizbullah, Zheng, Bangyou and Chapman, Scott C. (2019). A new probabilistic forecasting model for canopy temperature with consideration of periodicity and parameter variation. Agricultural and Forest Meteorology, 265, 88-98. doi: 10.1016/j.agrformet.2018.11.013 |
