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

Hartmann, Anja; Czauderna, Tobias; Hoffmann, Roberto; Stein, Nils; Schreiber, Falk

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

Dateien

Hartmann_0-396630.pdfGröße: 2.1 MBDownloads: 310

Datum

2011

Autor:innen

Hartmann, Anja

Czauderna, Tobias

Hoffmann, Roberto

Stein, Nils

Schreiber, Falk

Open Access-Veröffentlichung

Open Access Gold

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

BMC Bioinformatics. 2011, 12(1), 148. ISSN 1471-2105. eISSN 1471-2105. Available under: doi: 10.1186/1471-2105-12-148

Zusammenfassung

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.

Fachgebiet (DDC)

004 Informatik

Zitieren

ISO 690

HARTMANN, Anja, Tobias CZAUDERNA, Roberto HOFFMANN, Nils STEIN, Falk SCHREIBER, 2011. HTPheno : an image analysis pipeline for high-throughput plant phenotyping. In: BMC Bioinformatics. 2011, 12(1), 148. ISSN 1471-2105. eISSN 1471-2105. Available under: doi: 10.1186/1471-2105-12-148

BibTex

@article{Hartmann2011HTPhe-38591,
  year={2011},
  doi={10.1186/1471-2105-12-148},
  title={HTPheno : an image analysis pipeline for high-throughput plant phenotyping},
  number={1},
  volume={12},
  issn={1471-2105},
  journal={BMC Bioinformatics},
  author={Hartmann, Anja and Czauderna, Tobias and Hoffmann, Roberto and Stein, Nils and Schreiber, Falk},
  note={Article Number: 148}
}

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