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Anatomical Image Analysis

PrometheusWiki2311 points 
Contributors :Brendan Choat2548 points 


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Protocols
This section is intended for protocols relating to:
- ImageJ
- hydraulic diameter
- stomatal anatomy
- vessel length distributions
- image analysis for cryoSEM

Summary

 

Contributing author

Brendan Choat

Definition

Image analysis of microscope sections allows for quantification of plant anatomical traits.

Terminology

  • Stage or ocular graticule: grid of lines used to provide scale for images collected with light microscopes.

Methodological approaches

Image analysis plays a vital role in defining phenotypes and determining plant response to environmental variation and experimental treatments. This includes changes in dimensions of specific cell type (eg. xylem vessel diameter, fibre wall thickness, palisade mesophyll area), variation in tissue composition (eg. ratio of parenchyma to fibres, sapwood area), and cell ultra structure (eg. cell wall thickness, variation in mitochondria and chloroplast structure). Image analysis can also provide qualitative data such as identification of cellular composition (eg, differentiation of lignin, cellulose, polysaccharides, etc.).

Historically, many anatomical measurements were made while using microscopes with the aid of an ocular graticule. However, with rapid progress digital imaging technology, image analysis is now overwhelmingly undertaken with digital images collected using a digital camera slaved to a microscope. Digital images can be readily manipulated and analysed using a range of software such as Adobe Photoshop, Aviso, the Gimp and imageJ. Images are typically imported into these applications and then scaled using scale bars embedded in the image or using a separate image of a stage graticule collected at the same magnification. Collection of accurate scale information is of paramount importance for image analysis and anatomical measurements. While many measurements can only be made manually, with increased computing power and sophistication, automation of anatomical traits is becoming more common. Such automation is greatly beneficial to high throughput screening and analysis of spatially complex networks.

Broadly, image analysis includes measurement of plant morphology and architecture. This includes traits such as leaf area, leaf vein density, root length, and branching architecture. In this section we deal with image analysis related to anatomical traits, ie. related to the internal structure of the plant.

Health, safety and hazardous waste disposal considerations

 

  • Light microscopy
  • Electron microscopy

 

Literature references

 


Contributors to this page: Brendan Choat2548 points  and Admin36802 points  .
Page last modified on Monday 28 of February, 2011 22:24:09 EST by Brendan Choat2548 points . (Version 10)