Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/119338
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Type: | Journal article |
Title: | High-throughput field imaging and basic image analysis in a wheat breeding programme |
Author: | Walter, J. Edwards, J. Cai, J. McDonald, G. Miklavcic, S.J. Kuchel, H. |
Citation: | Frontiers in Plant Science, 2019; 10:449-1-449-12 |
Publisher: | Frontiers Media |
Issue Date: | 2019 |
ISSN: | 1664-462X 1664-462X |
Statement of Responsibility: | James Walter, James Edwards, Jinhai Cai, Glenn McDonald, Stanley J. Miklavcic, and Haydn Kuchel |
Abstract: | Visual assessment of colour-based traits plays a key role within field-crop breeding programmes, though the process is subjective and time-consuming. Digital image analysis has previously been investigated as an objective alternative to visual assessment for a limited number of traits, showing suitability and slight improvement to throughput over visual assessment. However, easily adoptable, field-based high-throughput methods are still lacking. The aim of the current study was to produce a high-throughput digital imaging and analysis pipeline for the assessment of colour-based traits within a wheat breeding programme. This was achieved through the steps of (i) a proof-of-concept study demonstrating basic image analysis methods in a greenhouse, (ii) application of these methods to field trials using hand-held imaging, and (iii) developing a field-based high-throughput imaging infrastructure for data collection. The proof of concept study showed a strong correlation (r = 0.95) between visual and digital assessments of wheat physiological yellowing (PY) in a greenhouse environment, with both scores having similar heritability (H2 = 0.85 and 0.76, respectively). Digital assessment of hand-held field images showed strong correlations to visual scores for PY (r = 0.61 and 0.78), senescence (r = 0.74 and 0.75) and Septoria tritici blotch (STB; r = 0.76), with greater heritability of digital scores, excluding STB. Development of the high-throughput imaging infrastructure allowed for images of field plots to be collected at a rate of 7,400 plots per hour. Images of an advanced breeding trial collected with this system were analysed for canopy cover at two time-points, with digital scores correlating strongly to visual scores (r = 0.88 and 0.86) and having similar or greater heritability. This study details how high-throughput digital phenotyping can be applied to colour-based traits within field trials of a wheat breeding programme. It discusses the logistics of implementing such systems with minimal disruption to the programme, provides a detailed methodology for the basic image analysis methods utilized, and has potential for application to other field-crop breeding or research programmes. |
Keywords: | Phenotyping; physiological yellows; senescence; septoria tritici blotch; canopy cover |
Rights: | Copyright © 2019 Walter, Edwards, Cai, McDonald,Miklavcic and Kuchel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
DOI: | 10.3389/fpls.2019.00449 |
Grant ID: | http://purl.org/au-research/grants/arc/LP150100055 |
Appears in Collections: | Agriculture, Food and Wine publications Aurora harvest 4 |
Files in This Item:
File | Description | Size | Format | |
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hdl_119338.pdf | Published Version | 3.49 MB | Adobe PDF | View/Open |
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