A - Papers appearing in refereed journals
Corcoran, E., Siles-Suarez, L., Kurup, S. and Ahnert, S. 2023. Automated extraction of pod phenotype data from micro-computed tomograph. Frontiers in Plant Science. 14, p. 1120182. https://doi.org/10.3389/fpls.2023.1120182
Authors | Corcoran, E., Siles-Suarez, L., Kurup, S. and Ahnert, S. |
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Abstract | Introduction: Plant image datasets have the potential to greatly improve our understanding of the phenotypic response of plants to environmental and genetic factors. However, manual data extraction from such datasets are known to be time-consuming and resource intensive. Therefore, the development of efficient and reliable machine learning methods for extracting phenotype data from plant imagery is crucial. |
Keywords | Phenotyping; Plant development; Machine learning; Computer vision; Microcompute tomography |
Year of Publication | 2023 |
Journal | Frontiers in Plant Science |
Journal citation | 14, p. 1120182 |
Digital Object Identifier (DOI) | https://doi.org/10.3389/fpls.2023.1120182 |
Open access | Published as ‘gold’ (paid) open access |
Funder | Biotechnology and Biological Sciences Research Council |
Funder project or code | Tailoring Plant Metabolism (TPM) - Work package 1 (WP1) - High value lipids for health and industry |
Brassica Rapeseed And Vegetable Optimisation (BRAVO) | |
Publisher's version | |
Output status | Published |
Publication dates | |
Online | 24 Feb 2023 |
Publication process dates | |
Accepted | 13 Feb 2023 |
Publisher | Frontiers Media SA |
ISSN | 1664-462X |
Permalink - https://repository.rothamsted.ac.uk/item/98v87/automated-extraction-of-pod-phenotype-data-from-micro-computed-tomograph