
EZ-Rhizo: integrated software for the fast and accurate measurement of root system architecture
Summary
The root system is essential for the growth and development of plants. In addition to anchoring the plant in the ground, it is the site of uptake of water and minerals from the soil. Plant root systems show an astonishing plasticity in their architecture, which allows for optimal exploitation of diverse soil structures and conditions. The signalling pathways that enable plants to sense and respond to changes in soil conditions, in particular nutrient supply, are a topic of intensive research, and root system architecture (RSA) is an important and obvious phenotypic output. At present, the quantitative description of RSA is labour intensive and time consuming, even using the currently available software, and the lack of a fast RSA measuring tool hampers forward and quantitative genetics studies. Here, we describe EZ-Rhizo: a Windows-integrated and semi-automated computer program designed to detect and quantify multiple RSA parameters from plants growing on a solid support medium. The method is non-invasive, enabling the user to follow RSA development over time. We have successfully applied EZ-Rhizoto evaluate natural variation in RSA across 23 Arabidopsis thaliana accessions, and have identified new RSA determinants as a basis for future quantitative trait locus (QTL) analysis.
The root system is essential for the growth and development of plants. In addition to anchoring the plant in the ground, it is the site of uptake of water and minerals from the soil. Plant root systems show an astonishing plasticity in their architecture, which allows for optimal exploitation of diverse soil structures and conditions. The signalling pathways that enable plants to sense and respond to changes in soil conditions, in particular nutrient supply, are a topic of intensive research, and root system architecture (RSA) is an important and obvious phenotypic output. At present, the quantitative description of RSA is labour intensive and time consuming, even using the currently available software, and the lack of a fast RSA measuring tool hampers forward and quantitative genetics studies. Here, we describe EZ-Rhizo: a Windows-integrated and semi-automated computer program designed to detect and quantify multiple RSA parameters from plants growing on a solid support medium. The method is non-invasive, enabling the user to follow RSA development over time. We have successfully applied EZ-Rhizoto evaluate natural variation in RSA across 23 Arabidopsis thaliana accessions, and have identified new RSA determinants as a basis for future quantitative trait locus (QTL) analysis.
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Keywords: Arabidopsis thaliana; image analysis; natural variation; principal component analysis; root architecture; software
Document Type: Research Article
Affiliations: 1: Plant Science Group, Faculty of Biomedical & Life Sciences, University of Glasgow, G12 8QQ Glasgow, UK 2: Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany
Publication date: March 1, 2009