The establishment of winter wheat root system architecture in field soils: The effect of soil type on root development in a temperate climate.

Winter wheat (Triticum aestivum L.) is an important cereal crop in the temperate climates of western Europe. Root system architecture is a significant contributor to resource capture and plant resilience. However, the impact of soil type on root system architecture (RSA) in field structured soils is yet to be fully assessed. This work studied the development of root growth using deep cultivation (250 mm) during the tillering phase stage (Zadock stage 25) of winter wheat across three soil types. The three sites of contrasting soil types covered a geographical area in the UK and Ireland in October 2018. Root samples were analysed using two methods: X-ray computed tomography (CT) which provides 3D images of the undisturbed roots in the soil, and a WinRHIZO™ scanner used to generate 2D images of washed roots and to measure further root parameters. Important negative relationships existed between soil bulk density and root properties (root length density, root volume, surface area and length) across the three sites. The results revealed that despite reduced root growth, the clay (Southoe) site had a significantly higher crop yield irrespective of root depth. The loamy sand (Harper Adams) site had significantly higher root volume, surface area and root length density compared with the other sites. However, a reduction in grain yield of 2.42 Mt ha-1 was incurred compared with the clay site and 1.6 Mt ha-1 compared with the clay loam site. The significantly higher rooting characteristics found in the loamy sand site were a result of the significantly lower soil bulk density compared with the other two sites. The loamy sand site had a lower soil bulk density, but no significant difference in macroporosity between sites (p > 0.05). This suggests that soil type and structure directly influence crop yield to greater extent than root parameters, but the interactions between both need simultaneous assessment in field sites.

Source partitioning using N2O isotopomers and soil WFPS to establish dominant N2O production pathways from different pasture sward compositions.

Nitrous oxide (N2O) is a potent greenhouse gas (GHG) emitted from agricultural soils and is influenced by nitrogen (N) fertiliser management and weather and soil conditions. Source partitioning N2O emissions related to management practices and soil conditions could suggest effective mitigation strategies. Multispecies swards can maintain herbage yields at reduced N fertiliser rates compared to grass monocultures and may reduce N losses to the wider environment. A restricted-simplex centroid experiment was used to measure daily N2O fluxes and associated isotopomers from eight experimental plots (7.8 m2) post a urea-N fertiliser application (40 kg N ha-1). Experimental pastures consisted of differing proportions of grass, legume and forage herb represented by perennial ryegrass (Lolium perenne), white clover (Trifolium repens) and ribwort plantain (Plantago lanceolata), respectively. N2O isotopomers were measured using a cavity ring down spectroscopy (CRDS) instrument adapted with a small sample isotope module (SSIM) for the analysis of gas samples ≤20 mL. Site preference (SP = δ15Nα - δ15Nß) and δ15Nbulk ((δ15Nα + δ15Nß) / 2) values were used to attribute N2O production to nitrification, denitrification or a mixture of both nitrification and denitrification over a range of soil WFPS (%). Daily N2O fluxes ranged from 8.26 to 86.86 g N2O-N ha-1 d-1. Overall, 34.2% of daily N2O fluxes were attributed to nitrification, 29.0% to denitrification and 36.8% to a mixture of both. A significant diversity effect of white clover and ribwort plantain on predicted SP and δ15Nbulk indicated that the inclusion of ribwort plantain may decrease N2O emission through biological nitrification inhibition under drier soil conditions (31%-75% WFPS). Likewise, a sharp decline in predicted SP indicates that increased white clover content could increase N2O emissions associated with denitrification under elevated soil moisture conditions (43%-77% WFPS). Biological nitrification inhibition from ribwort plantain inclusion in grassland swards and management of N fertiliser source and application timing to match soil moisture conditions could be useful N2O mitigation strategies.

Development and verification of a novel isotopic N2 O measurement technique for discrete static chamber samples using cavity ring-down spectroscopy.

RATIONALE: N2 O isotopomers are a useful tool to study soil N cycling processes. The reliability of such measurements requires a consistent set of international N2 O isotope reference materials to improve inter-laboratory and inter-instrument comparability and avoid reporting inaccurate results. All these are the more important given the role of N2 O in anthropogenic climate change and the pressing need to develop our understanding of soil N cycling and N2 O emission to mitigate such emissions. Cavity ring-down spectroscopy (CRDS) could potentially overcome resource requirements and technical challenges, making N2 O isotopomer measurements more feasible and less expensive than previous approaches (e.g., gas chromatography [GC] and isotope ratio mass spectrometry [IRMS]). METHODS: A combined laser spectrometer and small sample isotope module (CRDS & SSIM) method enabled N2 O concentration, δ15 Nbulk , δ15 Nα , δ15 Nß and site preference (SP) measurements of sample volumes <20 mL, such as static chamber samples. Sample dilution and isotopic mixing as well as N2 O concentration dependence were corrected numerically. A two-point calibration procedure normalised δ values to the international isotope-ratio scales. The CRDS & SSIM repeatability was determined using a reference gas (Ref Gas). CRDS & SSIM concentration measurements were compared with those obtained by GC, and the isotope ratio measurements from two different mass spectrometers were compared. RESULTS: The repeatability (mean ± 1σ; n = 10) of the CRDS & SSIM measurements of the Ref Gas was 710.64 ppb (± 8.64), 2.82‰ (± 0.91), 5.41‰ (± 2.00), 0.23‰ (± 0.22) and 5.18‰ (± 2.18) for N2 O concentration, δ15 Nbulk , δ15 Nα , δ15 Nß and SP, respectively. The CRDS & SSIM concentration measurements were strongly correlated with GC (r = 0.99), and they were more precise than those obtained using GC except when the N2 O concentrations exceeded the specified operating range. Normalising CRDS & SSIM δ values to the international isotope-ratio scales using isotopic N2 O standards (AK1 and Mix1) produced accurate results when the samples were bracketed within the range of the δ values of the standards. The CRDS & SSIM δ15 Nbulk and SP precision was approximately one order of magnitude less than the typical IRMS precision. CONCLUSIONS: CRDS & SSIM is a promising approach that enables N2 O concentrations and isotope ratios to be measured by CRDS for samples <20 mL. The CRDS & SSIM repeatability makes this approach suitable for N2 O "isotopomer mapping" to distinguish dominant source pathways, such as nitrification and denitrification, and requires less extensive lab resources than the traditionally used GC/IRMS. Current study limitations highlighted potential improvements for future users of this approach to consider, such as automation and physical removal of interfering trace gases before sample analysis.

Sward composition and soil moisture conditions affect nitrous oxide emissions and soil nitrogen dynamics following urea-nitrogen application.

Increased emissions of N2O, a potent greenhouse gas (GHG), from agricultural soils is a major concern for the sustainability of grassland agriculture. Emissions of N2O are closely associated with the rates and forms of N fertilisers applied as well as prevailing weather and soil conditions. Evidence suggests that multispecies swards require less fertiliser N input, and may cycle N differently, thus reducing N loss to the environment. This study used a restricted simplex-centroid experimental design to investigate N2O emissions and soil N cycling following application of urea-N (40 kg N ha-1) to eight experimental swards (7.8 m2) with differing proportions of three plant functional groups (grass, legume, herb) represented by perennial ryegrass (PRG, Lolium perenne), white clover (WC, Trifolium repens) and ribwort plantain (PLAN, Plantago lanceolata), respectively. Swards were maintained under two contrasting soil moisture conditions to examine the balance between nitrification and denitrification. Two N2O peaks coincided with fertiliser application and heavy rainfall events; 13.4 and 17.7 g N2O-N ha-1 day-1 (ambient soil moisture) and 39.8 and 86.9 g N2O-N ha-1 day-1 (wet soil moisture). Overall, cumulative N2O emissions post-fertiliser application were higher under wet soil conditions. Increasing legume (WC) proportions from 0% to 60% in multispecies swards resulted in model predicted N2O emissions increasing from 22.3 to 96.2 g N2O-N ha-1 (ambient soil conditions) and from 59.0 to 219.3 g N2O-N ha-1 (wet soil conditions), after a uniform N application rate. Soil N dynamics support denitrification as the dominant source of N2O especially under wet soil conditions. Significant interactions of PRG or WC with PLAN on soil mineral N concentrations indicated that multispecies swards containing PLAN potentially inhibit nitrification and could be a useful mitigation strategy for N loss to the environment from grassland agriculture.

Crop Improvement from Phenotyping Roots: Highlights Reveal Expanding Opportunities.

Root systems determine the water and nutrients for photosynthesis and harvested products, underpinning agricultural productivity. We highlight 11 programs that integrated root traits into germplasm for breeding, relying on phenotyping. Progress was successful but slow. Today's phenotyping technologies will speed up root trait improvement. They combine multiple new alleles in germplasm for target environments, in parallel. Roots and shoots are detected simultaneously and nondestructively, seed to seed measures are automated, and field and laboratory technologies are increasingly linked. Available simulation models can aid all phenotyping decisions. This century will see a shift from single root traits to rhizosphere selections that can be managed dynamically on farms and a shift to phenotype-based improvement to accommodate the dynamic complexity of whole crop systems.

Demystifying roots: A need for clarification and extended concepts in root phenotyping.

Plant roots have major roles in plant anchorage, resource acquisition and offer environmental benefits including carbon sequestration and soil erosion mitigation. As such, the study of root system architecture, anatomy and functional properties is of crucial interest to plant breeding, with the aim of sustainable yield production and environmental stewardship. Due to the importance of the root system studies, there is a need for clarification of terms and concepts in the root phenotyping community. In particular in this contribution, we advocate for the use of a reference naming system (ontologies) for roots and root phenes. Such uniformity would not only allow better understanding of research results, but would also enable a better sharing of data. In addition, we highlight the need to incorporate the concept of plasticity in breeding programs, as it is an essential component of root system development in heterogeneous environments.

Quantification of root water uptake in soil using X-ray computed tomography and image-based modelling.

Spatially averaged models of root-soil interactions are often used to calculate plant water uptake. Using a combination of X-ray computed tomography (CT) and image-based modelling, we tested the accuracy of this spatial averaging by directly calculating plant water uptake for young wheat plants in two soil types. The root system was imaged using X-ray CT at 2, 4, 6, 8 and 12 d after transplanting. The roots were segmented using semi-automated root tracking for speed and reproducibility. The segmented geometries were converted to a mesh suitable for the numerical solution of Richards' equation. Richards' equation was parameterized using existing pore scale studies of soil hydraulic properties in the rhizosphere of wheat plants. Image-based modelling allows the spatial distribution of water around the root to be visualized and the fluxes into the root to be calculated. By comparing the results obtained through image-based modelling to spatially averaged models, the impact of root architecture and geometry in water uptake was quantified. We observed that the spatially averaged models performed well in comparison to the image-based models with <2% difference in uptake. However, the spatial averaging loses important information regarding the spatial distribution of water near the root system.

Root hydrotropism is controlled via a cortex-specific growth mechanism.

Plants can acclimate by using tropisms to link the direction of growth to environmental conditions. Hydrotropism allows roots to forage for water, a process known to depend on abscisic acid (ABA) but whose molecular and cellular basis remains unclear. Here we show that hydrotropism still occurs in roots after laser ablation removed the meristem and root cap. Additionally, targeted expression studies reveal that hydrotropism depends on the ABA signalling kinase SnRK2.2 and the hydrotropism-specific MIZ1, both acting specifically in elongation zone cortical cells. Conversely, hydrotropism, but not gravitropism, is inhibited by preventing differential cell-length increases in the cortex, but not in other cell types. We conclude that root tropic responses to gravity and water are driven by distinct tissue-based mechanisms. In addition, unlike its role in root gravitropism, the elongation zone performs a dual function during a hydrotropic response, both sensing a water potential gradient and subsequently undergoing differential growth.

Non-destructive determination of floral staging in cereals using X-ray micro computed tomography (µCT).

BACKGROUND: Accurate floral staging is required to aid research into pollen and flower development, in particular male development. Pollen development is highly sensitive to stress and is critical for crop yields. Research into male development under environmental change is important to help target increased yields. This is hindered in monocots as the flower develops internally in the pseudostem. Floral staging studies therefore typically rely on destructive analysis, such as removal from the plant, fixation, staining and sectioning. This time-consuming analysis therefore prevents follow up studies and analysis past the point of the floral staging. RESULTS: This study focuses on using X-ray µCT scanning to allow quick and detailed non-destructive internal 3D phenotypic information to allow accurate staging of Arabidopsis thaliana L. and Barley (Hordeum vulgare L.) flowers. X-ray µCT has previously relied on fixation methods for above ground tissue, therefore two contrast agents (Lugol's iodine and Bismuth) were observed in Arabidopsis and Barley in planta to circumvent this step. 3D models and 2D slices were generated from the X-ray µCT images providing insightful information normally only available through destructive time-consuming processes such as sectioning and microscopy. Barley growth and development was also monitored over three weeks by X-ray µCT to observe flower development in situ. By measuring spike size in the developing tillers accurate non-destructive staging at the flower and anther stages could be performed; this staging was confirmed using traditional destructive microscopic analysis. CONCLUSION: The use of X-ray micro computed tomography (µCT) scanning of living plant tissue offers immense benefits for plant phenotyping, for successive developmental measurements and for accurate developmental timing for scientific measurements. Nevertheless, X-ray µCT remains underused in plant sciences, especially in above-ground organs, despite its unique potential in delivering detailed non-destructive internal 3D phenotypic information. This work represents a novel application of X-ray µCT that could enhance research undertaken in monocot species to enable effective non-destructive staging and developmental analysis for molecular genetic studies and to determine effects of stresses at particular growth stages.

Assessing the influence of the rhizosphere on soil hydraulic properties using X-ray computed tomography and numerical modelling.

Understanding the dynamics of water distribution in soil is crucial for enhancing our knowledge of managing soil and water resources. The application of X-ray computed tomography (CT) to the plant and soil sciences is now well established. However, few studies have utilized the technique for visualizing water in soil pore spaces. Here this method is utilized to visualize the water in soil in situ and in three-dimensions at successive reductive matric potentials in bulk and rhizosphere soil. The measurements are combined with numerical modelling to determine the unsaturated hydraulic conductivity, providing a complete picture of the hydraulic properties of the soil. The technique was performed on soil cores that were sampled adjacent to established roots (rhizosphere soil) and from soil that had not been influenced by roots (bulk soil). A water release curve was obtained for the different soil types using measurements of their pore geometries derived from CT imaging and verified using conventional methods, such as pressure plates. The water, soil, and air phases from the images were segmented and quantified using image analysis. The water release characteristics obtained for the contrasting soils showed clear differences in hydraulic properties between rhizosphere and bulk soil, especially in clay soil. The data suggest that soils influenced by roots (rhizosphere soil) are less porous due to increased aggregation when compared with bulk soil. The information and insights obtained on the hydraulic properties of rhizosphere and bulk soil will enhance our understanding of rhizosphere biophysics and improve current water uptake models.

Effects of X-Ray Dose On Rhizosphere Studies Using X-Ray Computed Tomography.

X-ray Computed Tomography (CT) is a non-destructive imaging technique originally designed for diagnostic medicine, which was adopted for rhizosphere and soil science applications in the early 1980s. X-ray CT enables researchers to simultaneously visualise and quantify the heterogeneous soil matrix of mineral grains, organic matter, air-filled pores and water-filled pores. Additionally, X-ray CT allows visualisation of plant roots in situ without the need for traditional invasive methods such as root washing. However, one routinely unreported aspect of X-ray CT is the potential effect of X-ray dose on the soil-borne microorganisms and plants in rhizosphere investigations. Here we aimed to i) highlight the need for more consistent reporting of X-ray CT parameters for dose to sample, ii) to provide an overview of previously reported impacts of X-rays on soil microorganisms and plant roots and iii) present new data investigating the response of plant roots and microbial communities to X-ray exposure. Fewer than 5% of the 126 publications included in the literature review contained sufficient information to calculate dose and only 2.4% of the publications explicitly state an estimate of dose received by each sample. We conducted a study involving rice roots growing in soil, observing no significant difference between the numbers of root tips, root volume and total root length in scanned versus unscanned samples. In parallel, a soil microbe experiment scanning samples over a total of 24 weeks observed no significant difference between the scanned and unscanned microbial biomass values. We conclude from the literature review and our own experiments that X-ray CT does not impact plant growth or soil microbial populations when employing a low level of dose (<30 Gy). However, the call for higher throughput X-ray CT means that doses that biological samples receive are likely to increase and thus should be closely monitored.

Recovering complete plant root system architectures from soil via X-ray µ-Computed Tomography.

BACKGROUND: X-ray micro-Computed Tomography (µCT) offers the ability to visualise the three-dimensional structure of plant roots growing in their natural environment - soil. Recovery of root architecture descriptions from X-ray CT data is, however, challenging. The X-ray attenuation values of roots and soil overlap, and the attenuation values of root material vary. Any successful root identification method must both explicitly target root material and be able to adapt to local changes in root properties.RooTrak meets these requirements by combining the level set method with a visual tracking framework and has been shown to be capable of segmenting a variety of plant roots from soil in X-ray µCT images. The approach provides high quality root descriptions, but tracks root systems top to bottom and so omits upward-growing (plagiotropic) branches. RESULTS: We present an extension to RooTrak which allows it to extract plagiotropic roots. An additional backward-looking step revisits the previous image, marking possible upward-growing roots. These are then tracked, leading to efficient and more complete recovery of the root system. Results show clear improvement in root extraction, without which key architectural traits would be underestimated. CONCLUSIONS: The visual tracking framework adopted in RooTrak provides the focus and flexibility needed to separate roots from soil in X-ray CT imagery and can be extended to detect plagiotropic roots. The extended software tool produces more complete descriptions of plant root structure and supports more accurate computation of architectural traits.

Quantifying the impact of soil compaction on root system architecture in tomato (Solanum lycopersicum) by X-ray micro-computed tomography.

BACKGROUND AND AIMS: We sought to explore the interactions between roots and soil without disturbance and in four dimensions (i.e. 3-D plus time) using X-ray micro-computed tomography. METHODS: The roots of tomato Solanum lycopersicum 'Ailsa Craig' plants were visualized in undisturbed soil columns for 10 consecutive days to measure the effect of soil compaction on selected root traits including elongation rate. Treatments included bulk density (1.2 vs. 1.6 g cm(-3)) and soil type (loamy sand vs. clay loam). KEY RESULTS: Plants grown at the higher soil bulk density exploited smaller soil volumes (P < 0.05) and exhibited reductions in root surface area (P < 0.001), total root volume (P < 0.001) and total root length (P < 0.05), but had a greater mean root diameter (P < 0.05) than at low soil bulk density. Swelling of the root tip area was observed in compacted soil (P < 0.05) and the tortuosity of the root path was also greater (P < 0.01). Root elongation rates varied greatly during the 10-d observation period (P < 0.001), increasing to a maximum at day 2 before decreasing to a minimum at day 4. The emergence of lateral roots occurred later in plants grown in compacted soil (P < 0.01). Novel rooting characteristics (convex hull volume, centroid and maximum width), measured by image analysis, were successfully employed to discriminate treatment effects. The root systems of plants grown in compacted soil had smaller convex hull volumes (P < 0.05), a higher centre of mass (P < 0.05) and a smaller maximum width than roots grown in uncompacted soil. CONCLUSIONS: Soil compaction adversely affects root system architecture, influencing resource capture by limiting the volume of soil explored. Lateral roots formed later in plants grown in compacted soil and total root length and surface area were reduced. Root diameter was increased and swelling of the root tip occurred in compacted soil.

RooTrak: automated recovery of three-dimensional plant root architecture in soil from x-ray microcomputed tomography images using visual tracking.

X-ray microcomputed tomography (µCT) is an invaluable tool for visualizing plant root systems within their natural soil environment noninvasively. However, variations in the x-ray attenuation values of root material and the overlap in attenuation values between roots and soil caused by water and organic materials represent major challenges to data recovery. We report the development of automatic root segmentation methods and software that view µCT data as a sequence of images through which root objects appear to move as the x-y cross sections are traversed along the z axis of the image stack. Previous approaches have employed significant levels of user interaction and/or fixed criteria to distinguish root and nonroot material. RooTrak exploits multiple, local models of root appearance, each built while tracking a specific segment, to identify new root material. It requires minimal user interaction and is able to adapt to changing root density estimates. The model-guided search for root material arising from the adoption of a visual-tracking framework makes RooTrak less sensitive to the natural ambiguity of x-ray attenuation data. We demonstrate the utility of RooTrak using µCT scans of maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum) grown in a range of contrasting soil textures. Our results demonstrate that RooTrak can successfully extract a range of root architectures from the surrounding soil and promises to facilitate future root phenotyping efforts.

Soil compaction: a review of past and present techniques for investigating effects on root growth.

Soil compaction has been known to affect root growth for millennia. Root growth in natural soils is complex and soil compaction induces several stresses which may interact simultaneously, including increased soil strength, decreased aeration and reduced hydraulic conductivity. Yet, moderate soil compaction offers some benefits to growing roots by increasing root-soil contact so they can extract adequate resources. Until now, improving our understanding of the specific responses of roots to below-ground stimuli has been difficult. However, the advent of new technologies and practices, including X-ray computed tomography, to provide non-destructive, three-dimensional images of root systems throughout the plant's lifecycle now allows the responses of roots encountering changes in their physical, chemical or biotic environment to be established directly and non-invasively. Previous destructive methods, such as root washing, were incapable of identifying and characterising fine root architectural characteristics as these are inextricably linked to the composition of the soil matrix. X-ray computed tomography coupled with genetic approaches will provide a more comprehensive appreciation of the effect of soil compaction on root growth, and the knowledge required to generate improvements in plant breeding programmes and crop husbandry.

The veterinary drug ivermectin influences immune response in the yellow dung fly (Scathophaga stercoraria).

Phenoloxidase (PO) is a key enzyme involved in the immune response of insects. We show that egg-to-adult exposure to residues of 0.001, but not 0.0005 mgkg(-1) ivermectin elevated PO activity in yellow dung flies (Scathophaga stercoraria) developing in cattle dung. Fly fat content was unaffected by the treatments. Therefore, the response of PO was a direct effect of ivermectin and not an indirect one caused by an alteration in body 'condition'. This supports the non-intuitive conclusion that flies surviving exposure to faecal residues may have enhanced immune function. To our knowledge, this is the first study to assess the effects on PO activity of insecticidal residues in livestock dung. The non-target effects of such residues are of wide interest, given the global use of veterinary products.