Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography

Aoife Hughes, Karen Louise Askew, Callum Paul Scotson, Kevin Stewart Williams, Colin Sauze, Fiona Corke, John Doonan, Candida Nibau

Research output: Contribution to journalArticlepeer-review

62 Citations (SciVal)
224 Downloads (Pure)

Abstract

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.
Original languageEnglish
Article number76
Number of pages16
JournalPlant Methods
Volume13
Issue number1
DOIs
Publication statusPublished - 01 Nov 2017

Keywords

  • X-ray micro computed tomography
  • μCT
  • image analysis
  • 3D vision
  • grain traits
  • wheat
  • temperature
  • Image analysis
  • Temperature
  • Grain traits
  • Wheat

Fingerprint

Dive into the research topics of 'Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography'. Together they form a unique fingerprint.

Cite this