HTPheno: An image analysis pipeline for high-throughput plant phenotyping

Background In the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time...

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Bibliographic Details
Published in:BMC bioinformatics Vol. 12; no. 1; p. 148
Main Authors: Hartmann, Anja, Czauderna, Tobias, Hoffmann, Roberto, Stein, Nils, Schreiber, Falk
Format: Journal Article
Language:English
Published: London BioMed Central 12.05.2011
BioMed Central Ltd
BMC
Subjects:
Algorithms
Bioinformatics
Biomedical and Life Sciences
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer programs
Hordeum - genetics
Hordeum vulgare
Image processing
Image Processing, Computer-Assisted - methods
Life Sciences
Microarrays
Networks analysis
Phenotype
Phylogeny (Botany)
Plants - genetics
Software
Germany
Analyse Colour Image
Colour Space
Side View Image
Phenotypic Parameter
Automatic Image Processing
ISSN:1471-2105, 1471-2105
Online Access:Get full text
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Summary:Background In the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time by means of image acquisition techniques. During such screening different images of each plant are recorded and must be analysed by applying sophisticated image analysis algorithms. Results This paper presents an image analysis pipeline (HTPheno) for high-throughput plant phenotyping. HTPheno is implemented as a plugin for ImageJ, an open source image processing software. It provides the possibility to analyse colour images of plants which are taken in two different views (top view and side view) during a screening. Within the analysis different phenotypical parameters for each plant such as height, width and projected shoot area of the plants are calculated for the duration of the screening. HTPheno is applied to analyse two barley cultivars. Conclusions HTPheno, an open source image analysis pipeline, supplies a flexible and adaptable ImageJ plugin which can be used for automated image analysis in high-throughput plant phenotyping and therefore to derive new biological insights, such as determination of fitness.
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ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-12-148