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Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography
by
Scotson, Callum P.
, Askew, Karen
, Williams, Kevin
, Sauze, Colin
, Doonan, John H.
, Hughes, Aoife
, Nibau, Candida
, Corke, Fiona
in
3D vision
/ Agricultural production
/ Animal feed
/ Automation
/ Background radiation
/ Biological Techniques
/ Climate change
/ Computation
/ Computed tomography
/ Content analysis
/ Crop production
/ crops
/ CT imaging
/ Domestication
/ Economic analysis
/ Economic importance
/ Environmental effects
/ Feeds
/ Food
/ Food supply
/ genes
/ Genotype & phenotype
/ Grain
/ Grain size
/ Grain traits
/ Growth
/ High temperature
/ Image acquisition
/ Image analysis
/ Image processing
/ Life Sciences
/ Medical imaging
/ micro-computed tomography
/ Morphology
/ morphometry
/ NMR
/ nondestructive methods
/ Nondestructive testing
/ Nuclear magnetic resonance
/ Personality
/ phenotype
/ Phenotypes
/ Physiological aspects
/ Plant Sciences
/ Plants in Computer Vision
/ population growth
/ Population studies
/ Qualitative research
/ Scanners
/ Seeds
/ Software
/ Spikes
/ temperate zones
/ temperature
/ Water regimes
/ Wheat
/ X-radiation
/ X-ray micro computed tomography
/ X-rays
/ μCT
2017
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Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography
by
Scotson, Callum P.
, Askew, Karen
, Williams, Kevin
, Sauze, Colin
, Doonan, John H.
, Hughes, Aoife
, Nibau, Candida
, Corke, Fiona
in
3D vision
/ Agricultural production
/ Animal feed
/ Automation
/ Background radiation
/ Biological Techniques
/ Climate change
/ Computation
/ Computed tomography
/ Content analysis
/ Crop production
/ crops
/ CT imaging
/ Domestication
/ Economic analysis
/ Economic importance
/ Environmental effects
/ Feeds
/ Food
/ Food supply
/ genes
/ Genotype & phenotype
/ Grain
/ Grain size
/ Grain traits
/ Growth
/ High temperature
/ Image acquisition
/ Image analysis
/ Image processing
/ Life Sciences
/ Medical imaging
/ micro-computed tomography
/ Morphology
/ morphometry
/ NMR
/ nondestructive methods
/ Nondestructive testing
/ Nuclear magnetic resonance
/ Personality
/ phenotype
/ Phenotypes
/ Physiological aspects
/ Plant Sciences
/ Plants in Computer Vision
/ population growth
/ Population studies
/ Qualitative research
/ Scanners
/ Seeds
/ Software
/ Spikes
/ temperate zones
/ temperature
/ Water regimes
/ Wheat
/ X-radiation
/ X-ray micro computed tomography
/ X-rays
/ μCT
2017
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Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography
by
Scotson, Callum P.
, Askew, Karen
, Williams, Kevin
, Sauze, Colin
, Doonan, John H.
, Hughes, Aoife
, Nibau, Candida
, Corke, Fiona
in
3D vision
/ Agricultural production
/ Animal feed
/ Automation
/ Background radiation
/ Biological Techniques
/ Climate change
/ Computation
/ Computed tomography
/ Content analysis
/ Crop production
/ crops
/ CT imaging
/ Domestication
/ Economic analysis
/ Economic importance
/ Environmental effects
/ Feeds
/ Food
/ Food supply
/ genes
/ Genotype & phenotype
/ Grain
/ Grain size
/ Grain traits
/ Growth
/ High temperature
/ Image acquisition
/ Image analysis
/ Image processing
/ Life Sciences
/ Medical imaging
/ micro-computed tomography
/ Morphology
/ morphometry
/ NMR
/ nondestructive methods
/ Nondestructive testing
/ Nuclear magnetic resonance
/ Personality
/ phenotype
/ Phenotypes
/ Physiological aspects
/ Plant Sciences
/ Plants in Computer Vision
/ population growth
/ Population studies
/ Qualitative research
/ Scanners
/ Seeds
/ Software
/ Spikes
/ temperate zones
/ temperature
/ Water regimes
/ Wheat
/ X-radiation
/ X-ray micro computed tomography
/ X-rays
/ μCT
2017
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Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography
Journal Article
Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography
2017
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Overview
Background
Wheat is one of the most widely grown crop in temperate climates for food and animal feed. In order to meet the demands of the predicted population increase in an ever-changing climate, wheat production needs to dramatically increase. Spike and grain traits are critical determinants of final yield and grain uniformity a commercially desired trait, but their analysis is laborious and often requires destructive harvest. One of the current challenges is to develop an accurate, non-destructive method for spike and grain trait analysis capable of handling large populations.
Results
In this study we describe the development of a robust method for the accurate extraction and measurement of spike and grain morphometric parameters from images acquired by X-ray micro-computed tomography (μCT). The image analysis pipeline developed automatically identifies plant material of interest in μCT images, performs image analysis, and extracts morphometric data. As a proof of principle, this integrated methodology was used to analyse the spikes from a population of wheat plants subjected to high temperatures under two different water regimes. Temperature has a negative effect on spike height and grain number with the middle of the spike being the most affected region. The data also confirmed that increased grain volume was correlated with the decrease in grain number under mild stress.
Conclusions
Being able to quickly measure plant phenotypes in a non-destructive manner is crucial to advance our understanding of gene function and the effects of the environment. We report on the development of an image analysis pipeline capable of accurately and reliably extracting spike and grain traits from crops without the loss of positional information. This methodology was applied to the analysis of wheat spikes can be readily applied to other economically important crop species.
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