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  • Reconstructing meristem growth via cell imaging

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Digital 3D reconstruction of a floral meristem (Arabidopsis thaliana) using confocal microscopy. Cells were automatically segmented using a series of algorithms.

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Digital 3D reconstruction of a floral meristem (Arabidopsis thaliana) using confocal microscopy. Cells were automatically segmented using a series of algorithms. The image shows a segmentation within meristem tissues, highlighting the different cell layers in false colours.

Partners

  • Ecole nationale supérieure de Lyon (ENS-Lyon)
  • Institut national de recherche en informatique et automatique (INRIA)
  • Institut national de la recherche agronomique (INRA)
  • Région Languedoc-Roussillon
  • Agence nationale de la recherche (ANR)

Further information

Fernandez R. et al., 2010. Imaging plant growth in 4D: Robust tissue reconstruction and lineaging at cell resolution. Nature Methods, 7: 547-553.

Contact

Christophe Godin
Montpellier
Genetic Improvement and Adaptation of Mediterranean and Tropical Plants (UMR AGAP)

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Reconstructing meristem growth via cell imaging

06/2011

Two CIRAD teams and their partners have just shown that it is possible to automate the recognition of meristem cells—a group of cells that generate all plant organs—in 3D and to track their division and growth over time using laser microscopy and suitable algorithms.

Two CIRAD teams and their partners have just shown that it is possible to automate the recognition of meristem cells—a group of cells that generate all plant organs—in 3D and to track their division and growth over time using laser microscopy and suitable algorithms. This work, which was carried out as part of a study on plant meristem tissue growth, combined cell imaging and mathematical image processing. It is a substantial advance that will benefit the biology community overall because it overcomes a major stumbling block to the understanding of the development of plant organisms and the role of the cell component in growth and acquisition of the final form of organs. There are many potential applications for this new method, especially for studying how the environment and genetics influence plant development.


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