Cargando…

“Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches

BACKGROUND: The flag leaf of a wheat (Triticum aestivum L.) plant rolls up into a cylinder in response to drought conditions and then unrolls when leaf water relations improve. This is a desirable trait for extending leaf area duration and improving grain size particularly under drought. But how do...

Descripción completa

Detalles Bibliográficos
Autores principales: Sirault, X. R. R., Condon, A. G., Wood, J. T., Farquhar, G. D., Rebetzke, G. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4650205/
https://www.ncbi.nlm.nih.gov/pubmed/26583042
http://dx.doi.org/10.1186/s13007-015-0095-1
_version_ 1782401459582664704
author Sirault, X. R. R.
Condon, A. G.
Wood, J. T.
Farquhar, G. D.
Rebetzke, G. J.
author_facet Sirault, X. R. R.
Condon, A. G.
Wood, J. T.
Farquhar, G. D.
Rebetzke, G. J.
author_sort Sirault, X. R. R.
collection PubMed
description BACKGROUND: The flag leaf of a wheat (Triticum aestivum L.) plant rolls up into a cylinder in response to drought conditions and then unrolls when leaf water relations improve. This is a desirable trait for extending leaf area duration and improving grain size particularly under drought. But how do we quantify this phenotype so that different varieties of wheat or different treatments can be compared objectively since this phenotype can easily be confounded with inter-genotypic differences in root-water uptake and/or transpiration at the leaf level if using traditional methods? RESULTS: We present a new method to objectively test a range of lines/varieties/treatments for their propensity of leaves to roll. We have designed a repeatable protocol and defined an objective measure of leaf curvature called “rolled-upness” which minimises confounding factors in the assessment of leaf rolling in grass species. We induced leaf rolling by immersing leaf strips in an osmoticum of known osmotic pressure. Using micro-photographs of individual leaf cross-sections at equilibrium in the osmoticum, two approaches were used to quantify leaf rolling. The first was to use some properties of the convex hull of the leaf cross-section. The second was to use cubic smoothing splines to approximate the transverse leaf shape mathematically and then use a statistic derived from the splines for comparison. Both approaches resulted in objective measurements that could differentiate clearly between breeding lines and varieties contrasting genetically in their propensity for leaf rolling under water stress. The spline approach distinguished between upward and downward curvature and allowed detailed properties of the rolling to be examined, such as the position on the strip where maximum curvature occurs. CONCLUSIONS: A method applying smoothing splines to skeletonised images of transverse wheat leaf sections enabled objective measurements of inter-genotypic variation for hydronastic leaf rolling in wheat. Mean-curvature of the leaf cross-section was the measure selected to discriminate between genotypes, as it was straightforward to calculate and easily construed. The method has broad applicability and provides an avenue to genetically dissect the trait in cereals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-015-0095-1) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4650205
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-46502052015-11-19 “Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches Sirault, X. R. R. Condon, A. G. Wood, J. T. Farquhar, G. D. Rebetzke, G. J. Plant Methods Methodology BACKGROUND: The flag leaf of a wheat (Triticum aestivum L.) plant rolls up into a cylinder in response to drought conditions and then unrolls when leaf water relations improve. This is a desirable trait for extending leaf area duration and improving grain size particularly under drought. But how do we quantify this phenotype so that different varieties of wheat or different treatments can be compared objectively since this phenotype can easily be confounded with inter-genotypic differences in root-water uptake and/or transpiration at the leaf level if using traditional methods? RESULTS: We present a new method to objectively test a range of lines/varieties/treatments for their propensity of leaves to roll. We have designed a repeatable protocol and defined an objective measure of leaf curvature called “rolled-upness” which minimises confounding factors in the assessment of leaf rolling in grass species. We induced leaf rolling by immersing leaf strips in an osmoticum of known osmotic pressure. Using micro-photographs of individual leaf cross-sections at equilibrium in the osmoticum, two approaches were used to quantify leaf rolling. The first was to use some properties of the convex hull of the leaf cross-section. The second was to use cubic smoothing splines to approximate the transverse leaf shape mathematically and then use a statistic derived from the splines for comparison. Both approaches resulted in objective measurements that could differentiate clearly between breeding lines and varieties contrasting genetically in their propensity for leaf rolling under water stress. The spline approach distinguished between upward and downward curvature and allowed detailed properties of the rolling to be examined, such as the position on the strip where maximum curvature occurs. CONCLUSIONS: A method applying smoothing splines to skeletonised images of transverse wheat leaf sections enabled objective measurements of inter-genotypic variation for hydronastic leaf rolling in wheat. Mean-curvature of the leaf cross-section was the measure selected to discriminate between genotypes, as it was straightforward to calculate and easily construed. The method has broad applicability and provides an avenue to genetically dissect the trait in cereals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-015-0095-1) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-14 /pmc/articles/PMC4650205/ /pubmed/26583042 http://dx.doi.org/10.1186/s13007-015-0095-1 Text en © Sirault et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Sirault, X. R. R.
Condon, A. G.
Wood, J. T.
Farquhar, G. D.
Rebetzke, G. J.
“Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
title “Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
title_full “Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
title_fullStr “Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
title_full_unstemmed “Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
title_short “Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
title_sort “rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4650205/
https://www.ncbi.nlm.nih.gov/pubmed/26583042
http://dx.doi.org/10.1186/s13007-015-0095-1
work_keys_str_mv AT siraultxrr rolledupnessphenotypingleafrollingincerealsusingcomputervisionandfunctionaldataanalysisapproaches
AT condonag rolledupnessphenotypingleafrollingincerealsusingcomputervisionandfunctionaldataanalysisapproaches
AT woodjt rolledupnessphenotypingleafrollingincerealsusingcomputervisionandfunctionaldataanalysisapproaches
AT farquhargd rolledupnessphenotypingleafrollingincerealsusingcomputervisionandfunctionaldataanalysisapproaches
AT rebetzkegj rolledupnessphenotypingleafrollingincerealsusingcomputervisionandfunctionaldataanalysisapproaches