Recovering root system traits using image analysis exemplified by two-dimensional neutron radiography images of lupine.

Daniel Leitner,Bernd Felderer,Peter Vontobel,Andrea Schnepf

doi:10.1104/pp.113.227892

Abstract

Root system traits are important in view of current challenges such as sustainable crop production with reduced fertilizer input or in resource-limited environments. We present a novel approach for recovering root architectural parameters based on image-analysis techniques. It is based on a graph representation of the segmented and skeletonized image of the root system, where individual roots are tracked in a fully automated way. Using a dynamic root architecture model for deciding whether a specific path in the graph is likely to represent a root helps to distinguish root overlaps from branches and favors the analysis of root development over a sequence of images. After the root tracking step, global traits such as topological characteristics as well as root architectural parameters are computed. Analysis of neutron radiographic root system images of lupine (Lupinus albus) grown in mesocosms filled with sandy soil results in a set of root architectural parameters. They are used to simulate the dynamic development of the root system and to compute the corresponding root length densities in the mesocosm. The graph representation of the root system provides global information about connectivity inside the graph. The underlying root growth model helps to determine which path inside the graph is most likely for a given root. This facilitates the systematic investigation of root architectural traits, in particular with respect to the parameterization of dynamic root architecture models.

Highlights

Root system traits are important in view of current challenges such as sustainable crop production with reduced fertilizer input or in resource-limited environments
The root systems were imaged by neutron radiography; the different colors indicate three different measurement times
We present a novel approach for root tracking from two-dimensional images of root systems

Summary

Introduction

Root system traits are important in view of current challenges such as sustainable crop production with reduced fertilizer input or in resource-limited environments. The underlying root growth model helps to determine which path inside the graph is most likely for a given root This facilitates the systematic investigation of root architectural traits, in particular with respect to the parameterization of dynamic root architecture models. Understanding the impact of roots and rhizosphere traits on plant resource efficiency is of highest relevance (Hinsinger et al, 2011) Development in this area will increase food security by enabling more sustainable production with reduced fertilizer input by improving cropping systems and cultivars for resource-limited environments (de Dorlodot et al, 2007). We present a novel approach for recovering root system parameters based on image-analysis techniques In this way, we simplify the systematic investigation of root architectural traits, in particular with respect to the parameterization of root system models. This is especially useful as water is a crucial factor ruling root allocation in soil (Hodge, 2010)

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Conclusion