Evaluation of 3D/2D Imaging and Image Processing Techniques for the Monitoring of Seed Imbibition

Seed imbibition is a very important process in plant biology by which, thanks to a simple water income, a dry seed may turn into a developing organism. In natural conditions, this process occurs in the soil, e.g., with difficult access for a direct observation. Monitoring the seed imbibition with no...

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Bibliographic Details
Main Authors: Etienne Belin, Clément Douarre, Nicolas Gillard, Florence Franconi, Julio Rojas-Varela, François Chapeau-Blondeau, Didier Demilly, Jérôme Adrien, Eric Maire, David Rousseau
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Journal of Imaging
Subjects:
MRI
Online Access:http://www.mdpi.com/2313-433X/4/7/83
Description
Summary:Seed imbibition is a very important process in plant biology by which, thanks to a simple water income, a dry seed may turn into a developing organism. In natural conditions, this process occurs in the soil, e.g., with difficult access for a direct observation. Monitoring the seed imbibition with non-invasive imaging techniques is therefore an important and possibly challenging task if one tries to perform it in natural conditions. In this report, we describe a set of four different imaging techniques that enable to addressing this task either in 3D or in 2D. For each technique, the following items are proposed. A detailed experimental protocol is provided to acquire images of the imbibition process. With the illustration of real data, the significance of the physical quantities measured in terms of their relation to the income of water in the seed is presented. Complete image analysis pipelines are then proposed to extract dynamic information on the imbibition process from such monitoring experiments. A final discussion compares the advantages and current limitations of each technique in addition to elements concerning the associated throughput and cost. These are criteria especially relevant in the field of plant phenotyping where large populations of plants are imaged to produce quantitatively significative traits after image processing.
ISSN:2313-433X