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2021 Journal Article Coupling of machine learning methods to improve estimation of ground coverage from unmanned aerial vehicle (UAV) imagery for high-throughput phenotyping of cropsHu, Pengcheng, Chapman, Scott C. and Zheng, Bangyou (2021). Coupling of machine learning methods to improve estimation of ground coverage from unmanned aerial vehicle (UAV) imagery for high-throughput phenotyping of crops. Functional Plant Biology, 48 (8), 766-779. doi: 10.1071/FP20309 |
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2021 Journal Article Scaling up high-throughput phenotyping for abiotic stress selection in the fieldSmith, Daniel T., Potgieter, Andries B. and Chapman, Scott C. (2021). Scaling up high-throughput phenotyping for abiotic stress selection in the field. Theoretical and Applied Genetics, 134 (6), 1845-1866. doi: 10.1007/s00122-021-03864-5 |
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2021 Journal Article Evolution and application of digital technologies to predict crop type and crop phenology in agriculturePotgieter, A. B., Zhao, Yan, Zarco-Tejada, Pablo J, Chenu, Karine, Zhang, Yifan, Porker, Kenton, Biddulph, Ben, Dang, Yash P., Neale, Tim, Roosta, Fred and Chapman, Scott (2021). Evolution and application of digital technologies to predict crop type and crop phenology in agriculture. In Silico Plants, 3 (1) diab017, 1-23. doi: 10.1093/insilicoplants/diab017 |
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2021 Journal Article An analysis of simulated yield data for pepper shows how genotype × environment interaction in yield can be understood in terms of yield components and their QTLsRodrigues, Paulo C., Heuvelink, Ep, Marcelis, Leo F. M., Chapman, Scott C. and van Eeuwijk, Fred A. (2021). An analysis of simulated yield data for pepper shows how genotype × environment interaction in yield can be understood in terms of yield components and their QTLs. Crop Science, 61 (3), 1826-1842. doi: 10.1002/csc2.20476 |
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2021 Journal Article UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soilDas, Sumanta, Christopher, Jack, Apan, Armando, Roy Choudhury, Malini, Chapman, Scott, Menzies, Neal W. and Dang, Yash P. (2021). UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil. ISPRS Journal of Photogrammetry and Remote Sensing, 173, 221-237. doi: 10.1016/j.isprsjprs.2021.01.014 |
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2021 Journal Article Limiting transpiration rate in high evaporative demand conditions to improve Australian wheat productivityCollins, Brian, Chapman, Scott, Hammer, Graeme and Chenu, Karine (2021). Limiting transpiration rate in high evaporative demand conditions to improve Australian wheat productivity. in silico Plants, 3 (1) diab006, 1-16. doi: 10.1093/insilicoplants/diab006 |
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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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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 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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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 |
