The X-factor: visualizing undisturbed root architecture in soils using X-ray computed tomography

Abstract

Although roots play a crucial role in plant growth and development through their acquisition and delivery of water and nutrients to the above-ground organs, our understanding of how they interact with their immediate soil environment largely remains a mystery as the opaque nature of soil has prevented undisturbed in situ root visualization (Perret et al., 2007). However, new developments in non-invasive techniques such as X-ray computed tomography (CT) provide, for the first time, an exciting opportunity to examine detailed root architecture in three dimensions (3-D) in undisturbed soil cores (Fig. 1). Although other non-invasive 3-D visualization procedures exist, X-ray CT is viewed as the most appropriate technique for studies of soil:root interactions as the presence of iron and manganese ions may provide interference when alternative techniques such as Nuclear Magnetic Resonance (NMR) are used (Heeraman et al., 1997). Detailed understanding of interactions between roots and their immediate soil environment is vital when considering issues such as land degradation as soil structure is a primary factor determining the availability of edaphic resources such as water and nutrients (Lynch, 1995), and is extrinsically linked to plant productivity (Moran et al., 2000). In view of the rapidly increasing human global population and the threat posed by climate change, maximizing crop yields and developing sustainable soil management strategies are vital for food security. X-ray CT image of roots of a 3-week-old Zea mays (L.) plant grown in a soil column (loamy sand, Newport series). 1 pixel=44 μm. X-ray CT overcomes some of the limitations associated with previous methodologies for studying roots by providing non-invasive and non-destructive 3-D images (Heeraman et al., 1997; Pierret et al., 2002; Lontoc-Roy et al., 2006). CT uses X-rays to acquire cross-sectional image slices of an object, which contain information regarding the attenuation of the X-rays, a function of the density of the sample material (Mahesh, 2002). These slices may then be reconstructed to provide 3-D visualization of the sample volume. The ability to view intact soil cores in this way enables accurate non-destructive quantification of soil parameters such as pore connectivity and tortuosity (Mooney, 2002). Previous commonly employed destructive methods such as root washing could not provide detailed information on root architecture, including branching characteristics and extension rate, which are inherently linked to conditions within the soil matrix. The use of X-ray CT to visualize roots in undisturbed soil (Watanabe et al., 1992; Heeraman et al., 1997; Jenneson et al., 1999; McNeill and Kolesik, 2004; Kaestner et al., 2006) has, until now, been limited to species with coarse roots based on images with a resolution >100 μm (Kaestner et al., 2006). Further development of the technique has been hampered by the spatial resolution of the images, which has failed to discriminate roots from the soil matrix. However, current, state-of-the-art, X-ray CT scanners can now achieve a spatial resolution of <500 nm, enabling fine roots, such as those of Arabidopsis thaliana, to be visualized in situ (Fig. 2). X-ray CT image of an Arabidopsis thaliana (L.) root growing in a soil column (loamy sand, Newport series). 1 pixel=16 μm. An additional limitation of the previous generation of X-ray CT systems for probing root architecture is that the attenuation coefficient for root material is typically similar to that of other soil organic matter, a problem which is exacerbated if the soil water content is high. Drying soil samples to address this issue may alter soil structure and root architecture. An alternative strategy has been to use substrates containing little organic matter (e.g. homogeneous sand and loamy sand) as growth media (Lontoc-Roy et al., 2006). However, as stressed by Gregory and Hinsinger (1999), our current need is for research involving complex growth media such as soil, as opposed to hydroponics, gels, and sand-culture, to represent field conditions more closely. An innovative new approach which may resolve these difficulties is the application of root-tracing software (Jassogne, 2009) capable of assigning a probability function to determine whether specific pixels within images represent root material (Fig. 3A). This software can be used to provide 3-D images of root distribution within undisturbed soil columns (Fig. 3B), thereby enabling images to be captured as roots grow or encounter soil-borne stresses such as compacted soil layers. There is strong evidence that this automated and rapid methodology for root detection can remove the subjectivity of identifying ‘root’ pixels in noisy images and enable detailed visualization of root architecture in situ. (A) Cross-section of a soil column (3 cm diameter) showing roots of Triticum aestivum (L.) traced in 3-D using Rootviz; roots are shown in purple. (B) Root architecture of a 3-week-ol