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

BMC Bioinformatics

Software

Nils Stein¹  Anja Hartmann¹  Tobias Czauderna¹  Falk Schreiber²  Roberto Hoffmann³ 

[1] Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, 06466, Gatersleben, Germany;Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, 06466, Gatersleben, Germany;Martin Luther University Halle-Wittenberg, Institute of Computer Science, Von-Seckendor-Platz 1, 06120, Halle, Germany;Martin Luther University Halle-Wittenberg, Institute of Computer Science, Von-Seckendor-Platz 1, 06120, Halle, Germany;

关键词: Colour Space;    Phenotypic Parameter;    Automatic Image Processing;    Side View Image;    Analyse Colour Image;   

DOI  :  10.1186/1471-2105-12-148

 received in 2010-10-29, accepted in 2011-05-12,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundIn 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.ResultsThis 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.ConclusionsHTPheno, 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.

【 授权许可】

Unknown   
© Hartmann et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.