Uncovering the hidden half of plants using new advances in root phenotyping

Atkinson, Jonathan A. and Pound, Michael P. and Bennett, Malcolm J. and Wells, Darren M. (2019) Uncovering the hidden half of plants using new advances in root phenotyping. Current Opinion in Biotechnology, 55 . pp. 1-8. ISSN 1879-0429

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Abstract

Major increases in crop yield are required to keep pace with population growth and climate change. Improvements to the architecture of crop roots promise to deliver increases in water and nutrient use efficiency but profiling the root phenome (i.e., its structure and function) represents a major bottleneck. We describe how advances in imaging and sensor technologies are making root phenomic studies possible. However, methodological advances in acquisition, handling and processing of the resulting ‘big-data’ is becoming increasingly important. Advances in automated image analysis approaches such as Deep Learning promise to transform the root phenotyping landscape. Collectively, these innovations are helping drive the selection of the next-generation of crops to deliver real world impact for ongoing global food security efforts.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/951064
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Biosciences
University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1016/j.copbio.2018.06.002
Depositing User: Eprints, Support
Date Deposited: 26 Jun 2018 08:02
Last Modified: 04 May 2020 19:50
URI: http://eprints.nottingham.ac.uk/id/eprint/52603

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