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2023 Journal Article Building a better Mungbean: breeding for reproductive resilience in a changing climateVan Haeften, Shanice, Dudley, Caitlin, Kang, Yichen, Smith, Daniel, Nair, Ramakrishnan M., Douglas, Colin A., Potgieter, Andries, Robinson, Hannah, Hickey, Lee T. and Smith, Millicent R. (2023). Building a better Mungbean: breeding for reproductive resilience in a changing climate. Food and Energy Security, 12 (6) e467. doi: 10.1002/fes3.467 |
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2023 Journal Article Using digital photography to monitor changes in biocrusts and ground cover in a savanna rangelandMyint Swe, Than, Williams, Wendy J., Schmidt, Susanne, Potgieter, Andries, Cowley, Robyn, Mellor, Vincent, Driscoll, Colin and Zhao, Yan (2023). Using digital photography to monitor changes in biocrusts and ground cover in a savanna rangeland. The Rangeland Journal, 44 (6), 263-278. doi: 10.1071/rj22019 |
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2023 Journal Article From prototype to inference: a pipeline to apply deep learning in sorghum panicle detectionJames, Chrisbin, Gu, Yanyang, Potgieter, Andries, David, Etienne, Madec, Simon, Guo, Wei, Baret, Frédéric, Eriksson, Anders and Chapman, Scott (2023). From prototype to inference: a pipeline to apply deep learning in sorghum panicle detection. Plant Phenomics, 5 0017, 1-16. doi: 10.34133/plantphenomics.0017 |
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Featured 2023 Journal Article A cross‐scale analysis to understand and quantify effects of photosynthetic enhancement on crop growth and yield across environmentsWu, Alex, Brider, Jason, Busch, Florian A., Chen, Min, Chenu, Karine, Clarke, Victoria C., Collins, Brian, Ermakova, Maria, Evans, John R., Farquhar, Graham D., Forster, Britta, Furbank, Robert T., Gorszmann, Michael, Hernandez, Miguel A., Long, Benedict M., Mclean, Greg, Potgieter, Andries, Dean Price, G., Sharwood, Robert E., Stower, Michael, van Oosterom, Erik, von Caemmerer, Susanne, Whitney, Spencer M. and Hammer, Graeme L. (2023). A cross‐scale analysis to understand and quantify effects of photosynthetic enhancement on crop growth and yield across environments. Plant, Cell & Environment, 46 (1), 23-44. doi: 10.1111/pce.14453 |
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2022 Journal Article Challenges and opportunities in remote sensing-based crop monitoring: a reviewWu, Bingfang, Zhang, Miao, Zeng, Hongwei, Tian, Fuyou, Potgieter, Andries B., Qin, Xingli, Yan, Nana, Chang, Sheng, Zhao, Yan, Dong, Qinghan, Boken, Vijendra, Plotnikov, Dmitry, Guo, Huadong, Wu, Fangming, Zhao, Hang, Deronde, Bart, Tits, Laurent and Loupian, Evgeny (2022). Challenges and opportunities in remote sensing-based crop monitoring: a review. National Science Review, 10 (4) nwac290, 1-34. doi: 10.1093/nsr/nwac290 |
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2022 Journal Article Cover ImageWu, Alex, Brider, Jason, Busch, Florian A., Chen, Min, Chenu, Karine, Clarke, Victoria C., Collins, Brian, Ermakova, Maria, Evans, John R., Farquhar, Graham D., Forster, Britta, Furbank, Robert T., Groszmann, Michael, Hernandez‐Prieto, Miguel A., Long, Benedict M., Mclean, Greg, Potgieter, Andries, Price, G. Dean, Sharwood, Robert E., Stower, Michael, van Oosterom, Erik, von Caemmerer, Susanne, Whitney, Spencer M. and Hammer, Graeme L. (2022). Cover Image. Plant, Cell & Environment, 46 (1). doi: 10.1111/pce.14512 |
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2022 Journal Article Lead time and skill of Australian wheat yield forecasts based on ENSO-analogue or GCM-derived seasonal climate forecasts – A comparative analysisPotgieter, Andries B, Schepen, Andrew, Brider, Jason and Hammer, Graeme L (2022). Lead time and skill of Australian wheat yield forecasts based on ENSO-analogue or GCM-derived seasonal climate forecasts – A comparative analysis. Agricultural and Forest Meteorology, 324 109116, 1-12. doi: 10.1016/j.agrformet.2022.109116 |
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2022 Journal Article Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiencyZhi, Xiaoyu, Hammer, Graeme, Borrell, Andrew, Tao, Yongfu, Wu, Alex, Hunt, Colleen, van Oosterom, Erik, Massey-Reed, Sean Reynolds, Cruickshank, Alan, Potgieter, Andries B., Jordan, David, Mace, Emma and George-Jaeggli, Barbara (2022). Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency. Theoretical and Applied Genetics, 135 (9), 3057-3071. doi: 10.1007/s00122-022-04167-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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2021 Journal Article Genetic control of leaf angle in sorghum and its effect on light interceptionZhi, Xiaoyu, Tao, Yongfu, Jordan, David, Borrell, Andrew, Hunt, Colleen, Cruickshank, Alan, Potgieter, Andries, Wu, Alex, Hammer, Graeme, George-Jaeggli, Barbara and Mace, Emma (2021). Genetic control of leaf angle in sorghum and its effect on light interception. Journal of Experimental Botany, 73 (3) erab467, 801-816. doi: 10.1093/jxb/erab467 |
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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 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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Featured 2020 Journal Article High-throughput phenotyping of dynamic canopy traits associated with stay-green in grain sorghumLiedtke, J. D., Hunt, C. H., George-Jaeggli, B., Laws, K., Watson, J., Potgieter, A. B., Cruickshank, A. and Jordan, D. R. (2020). High-throughput phenotyping of dynamic canopy traits associated with stay-green in grain sorghum. Plant Phenomics, 2020 4635153, 1-10. doi: 10.34133/2020/4635153 |
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2020 Journal Article Predicting wheat yield at the field scale by combining high-resolution sentinel-2 satellite imagery and crop modellingZhao, Yan, Potgieter, Andries B., Zhang, Miao, Wu, Bingfang and Hammer, Graeme L. (2020). Predicting wheat yield at the field scale by combining high-resolution sentinel-2 satellite imagery and crop modelling. Remote Sensing, 12 (6) 1024, 1024. doi: 10.3390/rs12061024 |
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2019 Journal Article An integrated framework for predicting the risk of experiencing temperature conditions that may trigger late-maturity alpha-amylase in wheat across AustraliaArmstrong, Robert N., Potgieter, Andries B., Mares, Daryl J., Mrva, Kolumbina, Brider, Jason and Hammer, Graeme L. (2019). An integrated framework for predicting the risk of experiencing temperature conditions that may trigger late-maturity alpha-amylase in wheat across Australia. Crop and Pasture Science, 71 (1), 1-11. doi: 10.1071/cp19005 |
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2019 Journal Article Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal cropsFurbank, Robert T., Jimenez‐Berni, Jose A., George‐Jaeggli, Barbara, Potgieter, Andries B. and Deery, David M. (2019). Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops. New Phytologist, 223 (4) nph.15817, 1714-1727. doi: 10.1111/nph.15817 |
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2019 Journal Article Integrating satellite and climate data to predict wheat yield in Australia using machine learning approachesCai, Yaping, Guan, Kaiyu, Lobell, David, Potgieter, Andries B., Wang, Shaowen, Peng, Jian, Xu, Tianfang, Asseng, Senthold, Zhang, Yongguang, You, Liangzhi and Peng, Bin (2019). Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches. Agricultural and Forest Meteorology, 274, 144-159. doi: 10.1016/j.agrformet.2019.03.010 |
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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 Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applicationsNewlands, Nathaniel K., Porcelli, Tracy A., Potgieter, Andries B., Kouadio, Louis, Huete, Alfredo and Guo, Wei (2019). Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications. Frontiers in Environmental Science, 7 (May) 71. doi: 10.3389/fenvs.2019.00071 |
