Quantitative Imaging of Infiltration, Root Growth, and Root Water Uptake via Neutron Radiography

Oswald, Sascha E.; Menon, Manoj; Carminati, Andrea; Vontobel, Peter; Lehmann, Eberhard; Schulin, Rainer

doi:10.2136/vzj2007.0156

Cited by 117 publications

(87 citation statements)

References 54 publications

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“…Imaging techniques for the visualization of soilgrown root systems in two and three dimensions include x-ray computed tomography (Heeraman et al, 1997;Tracy et al, 2010;Mooney et al, 2012), neutron radiography (NR; Oswald et al, 2008), and magnetic resonance imaging (Pohlmeier et al, 2008). NR is one of the most suitable techniques to investigate roots grown in soil, because it allows a high throughput, provides a strong contrast between roots and soil, and therefore requires little effort for image processing.…”

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confidence: 99%

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Recovering Root System Traits Using Image Analysis Exemplified by Two-Dimensional Neutron Radiography Images of Lupine

et al. 2013

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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 imageanalysis 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.

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confidence: 99%

“…A major advantage of NR as well as magnetic resonance imaging is the possibility to monitor water distribution and roots simultaneously (Menon et al, 2007;Oswald et al, 2008;Moradi et al, 2009;Carminati et al, 2010;Stingaciu et al, 2013). This is especially useful as water is a crucial factor ruling root allocation in soil (Hodge, 2010).…”

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Recovering Root System Traits Using Image Analysis Exemplified by Two-Dimensional Neutron Radiography Images of Lupine

et al. 2013

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“…While root system architecture has in the past been derived from a range of computational models, it is now possible to measure it in situ (i.e., in the soil) using imaging techniques such as magnetic resonance imaging (MRI), X-ray computed tomography (X-ray CT) and neutron tomography, see Carminati et al (2010); Gregory et al (2003); Koebernick et al (2014);Metzner et al (2015); Mooney et al (2012); Moradi et al (2011);Oswald et al (2008) as a good starting point for the literature. These images can be utilised to build an image-based model for water and/or nutrient uptake by the root system.…”

Section: Modelling Rhizosphere Processes: State Of the Artmentioning

confidence: 99%

“…4) has been used to study root and water distribution in soils in quasi twodimensional thin slabs (Menon et al 2007;Moradi et al 2009;Oswald et al 2008). More recently, experiments with time-resolved neutron radiography revealed unexpected water dynamics in the rhizosphere.…”

Section: Structural/water Imaging Using Neutron Radiography and Tomogmentioning

confidence: 99%

Challenges in imaging and predictive modeling of rhizosphere processes

et al. 2016

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Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes.

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“…thickness, transparency etc. ), roots can be either directly photographed or the neutron, x-ray computed tomography, NMR, 2D light transition imaging technique can be applied (de Dorlodot et al, 2007;Doussan et al, 2006;Garrigues et al, 2006;Moradi et al, 2009Moradi et al, , 2010Moradi et al, , 2013Moran et al, 2000;Oswald et al, 2008;Rudolph et al, 2012Rudolph et al, , 2013Rudolph-Mohr et al, 2014;Stingaciu et al, 2013). These techniques were mostly applied to analyze root development in the early stage of plant and roots growth.…”

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confidence: 99%

Root distributions in a laboratory box evaluated using two different techniques (gravimetric and image processing) and their impact on root water uptake simulated with HYDRUS

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et al. 2016

Journal of Hydrology and Hydromechanics

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Knowledge of the distribution of plant roots in a soil profile (i.e. root density) is needed when simulating root water uptake from soil. Therefore, this study focused on evaluating barley and wheat root densities in a sand-vermiculite substrate. Barley and wheat were planted in a flat laboratory box under greenhouse conditions. The box was always divided into two parts, where a single plant row and rows cross section (respectively) was simulated. Roots were excavated at the end of the experiment and root densities were assessed using root zone image processing and by weighing. For this purpose, the entire area (width of 40 and height of 50 cm) of each scenario was divided into 80 segments (area of 5x5 cm). Root density in each segment was expressed as a root percentage of the entire root cluster. Vertical root distributions (i.e. root density with respect to depth) were also calculated as a sum of root densities in each 5 cm layer. Resulting vertical root densities, measured evaporation from the water table (used as the potential root water uptake), and the Feddes stress response function model were used for simulating substrate water regime and actual root water uptake for all scenarios using HYDRUS-1D. All scenarios were also simulated using HYDRUS-2D. One scenario (areal root density of barley sown in a single row, obtained using image analysis) is presented in this paper (because most scenarios showed root water uptakes similar to results of 1D scenarios).The application of two root detecting techniques resulted in noticeably different root density distributions. Differences were mainly attributed to the fact that fine roots of high density (located mostly at the deeper part of the box) had lower weights in comparison to the weight of few large roots (at the box top). Thus, at the deeper part, higher root density (with respect to the entire root zone) was obtained using the image analysis in comparison to that from the gravimetric analysis. Conversely, lower root density was obtained using the image analysis at the upper part in comparison to that from the gravimetric analysis. On the other hand, fine roots overlapped each other and therefore were not visible in the image, which resulted in lower root density values from image analysis. Root water uptakes simulated with HYDRUS-1D using diverse root densities obtained for each cereal declined differently from the potential root water uptake values depending on water scarcity at depths of higher root density. Usually, an earlier downtrend associated with gradual root water uptake decreases and vice versa. Similar root water uptakes were simulated for the presented scenario using the HYDRUS-1D and HYDRUS-2D models. The impact of the horizontal root density distribution on root water uptake was, in this case, less important than the impact of the vertical root distribution resulting from different techniques and sowing scenarios.

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Quantitative Imaging of Infiltration, Root Growth, and Root Water Uptake via Neutron Radiography

Cited by 117 publications

References 54 publications

Recovering Root System Traits Using Image Analysis Exemplified by Two-Dimensional Neutron Radiography Images of Lupine

Recovering Root System Traits Using Image Analysis Exemplified by Two-Dimensional Neutron Radiography Images of Lupine

Challenges in imaging and predictive modeling of rhizosphere processes

Root distributions in a laboratory box evaluated using two different techniques (gravimetric and image processing) and their impact on root water uptake simulated with HYDRUS

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