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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 |
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2021 Journal Article Genotype specific P-spline response surfaces assist interpretation of regional wheat adaptation to climate changeBustos-Korts, Daniela, Boer, Martin P., Chenu, Karine, Zheng, Bangyou, Chapman, Scott and van Eeuwijk, Fred (2021). Genotype specific P-spline response surfaces assist interpretation of regional wheat adaptation to climate change. In Silico Plants, 3 (2) diab018. doi: 10.1093/insilicoplants/diab018 |
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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 |
