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2021

Journal Article

Detecting sorghum plant and head features from multispectral UAV imagery

Zhao, 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

Detecting sorghum plant and head features from multispectral UAV imagery

2021

Journal Article

Scaling up high-throughput phenotyping for abiotic stress selection in the field

Smith, 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

Scaling up high-throughput phenotyping for abiotic stress selection in the field

2021

Journal Article

Evolution and application of digital technologies to predict crop type and crop phenology in agriculture

Potgieter, 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

Evolution and application of digital technologies to predict crop type and crop phenology in agriculture

2021

Conference Publication

Domain adaptation for plant organ detection with style transfer

James, 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

Domain adaptation for plant organ detection with style transfer

2020

Journal Article

High-throughput phenotyping of dynamic canopy traits associated with stay-green in grain sorghum

Liedtke, 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

High-throughput phenotyping of dynamic canopy traits associated with stay-green in grain sorghum

2020

Journal Article

Predicting wheat yield at the field scale by combining high-resolution sentinel-2 satellite imagery and crop modelling

Zhao, 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

Predicting wheat yield at the field scale by combining high-resolution sentinel-2 satellite imagery and crop modelling

2020

Conference Publication

Quantifying drought tolerant crop traits using sensing technologies to enhance selection in sorghum breeding trials

Potgieter, 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.

Quantifying drought tolerant crop traits using sensing technologies to enhance selection in sorghum breeding trials

2020

Book Chapter

Sorghum management systems and production technology around the globe

Ciampitti, I. A., Prasad, P. V. Vara, Kumar, S. R., Kubsad, V. S., Adam, M., Eyre, J. X., Potgieter, A. B., Clarke, S. J. and Gambin, B. (2020). Sorghum management systems and production technology around the globe. Sorghum in the 21st Century: Food - Fodder - Feed - Fuel for a Rapidly Changing World. (pp. 251-293) edited by Vilas A. Tonapi, Harvinder Singh Talwar, Ashok Kumar Are, B. Venkatesh Bhat, Ch. Ravinder Reddy and Timothy J. Dalton. Singapore: Springer. doi: 10.1007/978-981-15-8249-3_11

Sorghum management systems and production technology around the globe

2019

Journal Article

An integrated framework for predicting the risk of experiencing temperature conditions that may trigger late-maturity alpha-amylase in wheat across Australia

Armstrong, 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

An integrated framework for predicting the risk of experiencing temperature conditions that may trigger late-maturity alpha-amylase in wheat across Australia

2019

Journal Article

Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops

Furbank, 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

Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops

2019

Journal Article

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Cai, 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

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

2019

Journal Article

A weakly supervised deep learning framework for sorghum head detection and counting

Ghosal, 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

A weakly supervised deep learning framework for sorghum head detection and counting

2019

Journal Article

Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications

Newlands, 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

Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications

2019

Conference Publication

High-throughput phenotyping of canopy radiation use efficiency and its component traits

George-Jaeggli, Barbara, Potgieter, Andries, Zhi, Xiaoyu, Reynolds Massey-Reed, Sean, Watson, James, Lamprecht, Marnie, Chapman, Scott, Laws, Kenneth, Hunt, Colleen, Borrell, Andrew, Jordan, David, van Oosterom, Erik, Wu, Alex and Hammer, Graeme (2019). High-throughput phenotyping of canopy radiation use efficiency and its component traits. 6th International Plant Phenotyping Symposium, Nanjing, China, 22-26 October 2019.

High-throughput phenotyping of canopy radiation use efficiency and its component traits

2019

Conference Publication

Determining of targeted crop characteristics utilising sensing technologies to enhance selection of higher yielding varieties in sorghum breeding trials

Potgieter, Andries, Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Guo, Wei, Watson, James, Reynolds Massey-Reed, Sean, Chapman, Scott, Hammer, Graeme and Jordan, David (2019). Determining of targeted crop characteristics utilising sensing technologies to enhance selection of higher yielding varieties in sorghum breeding trials. Australian Summer Grains Conference, Gold Coast, QLD, Australia, 8-10 July 2019.

Determining of targeted crop characteristics utilising sensing technologies to enhance selection of higher yielding varieties in sorghum breeding trials

2019

Book Chapter

The use of hyperspectral proximal sensing for phenotyping of plant breeding trials

Potgieter, Andries B., Watson, James, George-Jaeggli, Barbara, McLean, Gregory, Eldridge, Mark, Chapman, Scott C., Laws, Kenneth, Christopher, Jack, Chenu, Karine, Borrell, Andrew, Hammer, Graeme and Jordan, David R. (2019). The use of hyperspectral proximal sensing for phenotyping of plant breeding trials. Fundamentals, sensor systems, spectral libraries, and data mining for vegetation. (pp. 127-148) edited by Prasad S. Thenkabail, John G. Lyon and Alfredo Huete. Boca Raton, FL United States: CRC Press. doi: 10.1201/9781315164151-5

The use of hyperspectral proximal sensing for phenotyping of plant breeding trials

2019

Conference Publication

High-throughput phenotyping tools to test whether leaf-level photosynthesis traits are measurable at the crop level

George-Jaeggli, Barbara, Potgieter, Andries, Zhi, Xiaoyu, Reynolds Massey-Reed, Sean, Watson, James, Lamprecht, Marnie, Chapman, Scott, Laws, Kenneth, Hunt, Colleen, Borrell, Andrew, Jordan, David, van Oosterom, Erik, Wu, Alex and Hammer, Graeme (2019). High-throughput phenotyping tools to test whether leaf-level photosynthesis traits are measurable at the crop level. TropAg 2019, Brisbane, QLD Australia, 10-13 November 2019.

High-throughput phenotyping tools to test whether leaf-level photosynthesis traits are measurable at the crop level

2019

Conference Publication

Seeing canopy photosynthesis through the eyes of a Gecko

George-Jaeggli, Barbara, Zhi, Xiaoyue, Wu, Alex, Potgieter, Andries, Reynolds Massey-Reed, Sean, Watson, James, Hunt, Colleen, Lamprecht, Marnie, Chapman, Scott, Borrell, Andrew, Jordan, David and Hammer, Graeme (2019). Seeing canopy photosynthesis through the eyes of a Gecko. Innovations in Agriculture for Food Security, Brisbane, QLD Australia, 30 June - 3 July 2019.

Seeing canopy photosynthesis through the eyes of a Gecko

2019

Conference Publication

Predicting lodging using sensing technologies to enhance selection in sorghum breeding trials

Potgieter, Andries, Laws, Kenneth, George-Jaeggli, Barbara, Hunt, Colleen, Guo, Wei, Reynolds Massey-Reed, Sean, Chapman, Scott, Borrell, Andrew, Mace, Emma, Hammer, Graeme and Jordan, David (2019). Predicting lodging using sensing technologies to enhance selection in sorghum breeding trials. 6th International Plant Phenotyping Symposium, Nanjing, China, 22-26 October 2019.

Predicting lodging using sensing technologies to enhance selection in sorghum breeding trials

2018

Journal Article

Aerial imagery analysis – quantifying appearance and number of sorghum heads for applications in breeding and agronomy

Guo, Wei, Zheng, Bangyou, Potgieter, Andries B., Diot, Julien, Watanabe, Kakeru, Noshita, Koji, Jordan, David R., Wang, Xuemin, Watson, James, Ninomiya, Seishi and Chapman, Scott C. (2018). Aerial imagery analysis – quantifying appearance and number of sorghum heads for applications in breeding and agronomy. Frontiers in Plant Science, 9 1544, 1544. doi: 10.3389/fpls.2018.01544

Aerial imagery analysis – quantifying appearance and number of sorghum heads for applications in breeding and agronomy