Analysis of Maize (Zea mays L.) Seedling Roots with the High-Throughput Image Analysis Tool ARIA (Automatic Root Image Analysis)

The maize root system is crucial for plant establishment as well as water and nutrient uptake. There is substantial genetic and phenotypic variation for root architecture, which gives opportunity for selection. Root traits, however, have not been used as selection criterion mainly due to the difficulty in measuring them, as well as their quantitative mode of inheritance. Seedling root traits offer an opportunity to study multiple individuals and to enable repeated measurements per year as compared to adult root phenotyping. We developed a new software framework to capture various traits from a single image of seedling roots. This framework is based on the mathematical notion of converting images of roots into an equivalent graph. This allows automated querying of multiple traits simply as graph operations. This framework is furthermore extendable to 3D tomography image data. In order to evaluate this tool, a subset of the 384 inbred lines from the Ames panel, for which extensive genotype by sequencing data are available, was investigated. A genome wide association study was applied to this panel for two traits, Total Root Length and Total Surface Area, captured from seedling root images from WinRhizo Pro 9.0 and the current framework (called ARIA) for comparison using 135,311 single nucleotide polymorphism markers. The trait Total Root Length was found to have significant SNPs in similar regions of the genome when analyzed by both programs. This high-throughput trait capture software system allows for large phenotyping experiments and can help to establish relationships between developmental stages between seedling and adult traits in the future.     

Genome-wide association mapping and agronomic impact of cowpea root architecture

Key message

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance.

Abstract

Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

     

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

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.Crucial factors for plant development are light quantity and quality as well as water and nutrient availability in soils. Regarding water and nutrient uptake, root architecture is the main aspect of plant productivity (Lynch, 2007; Smith and De Smet, 2012) and needs to be accurately considered when describing root processes. Currently, 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).Root architectural development includes architectural, morphological, anatomical, as well as physiological traits. For the systematic investigation of such complex biological systems, mathematical modeling is inevitable (Roose and Schnepf, 2008). Ideally, experiments and theoretical models are developed to mutually support each other. In this way, models are created that include state-of-the-art knowledge and have significant parameters. There are various root architectural models incorporating a multitude of processes (Dunbabin et al., 2013) that are originally based on Pagès et al. (1989) and Diggle (1988). Generally, the parameterization of such models is difficult and demands elaborate experimental effort. In this work, 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.Imaging techniques for the visualization of soil-grown 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. 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).Images of root architecture contain a huge amount of information, and image analysis helps to recover parameters describing certain root architectural and morphological traits. The majority of imaging systems for root systems are designed for two-dimensional images, such as RootReader2D (Clark et al., 2013), GiA Roots (Galkovskyi et al., 2012), SmartRoot (Lobet et al., 2011), EZ-Rhizo (Armengaud et al., 2009), and Growscreen (Nagel et al., 2012). See also Le Bot et al. (2010) for a review of available software. A starting point for image analysis is commonly a grayscale image of a root system. The first step is to create a binary image by segmentation. Further steps include skeletonization, root tracking, and data analysis. The most common segmentation method is some form of thresholding (e.g. RootReader2D, GiA Roots, SmartRoot, EZ-Rhizo; Stingaciu et al. [2013]). Other methods include the livewire algorithm (Basu and Pal, 2012) or the levelset method (RootTrak; Mairhofer et al., 2012) that determine the borders of each root. The creation of a root system skeleton is either done manually (e.g. DART; Le Bot et al., 2010) or based on morphological operators such as thinning and closing (GiA Roots, RootReader2D, EZ-Rhizo), sometimes with options for the user to correct skeleton points (EZ-Rhizo). The root tracking step can be performed manually (DART) or based on creating a graph representation of the root system combined with Dijkstra’s algorithm, a search algorithm that finds the shortest path between two nodes inside a graph (RootReader2D; Stingaciu et al. [2013]). Furthermore, algorithms can operate on the skeleton (EZ-Rhizo) or directly on the image source (SmartRoot). In SmartRoot, the user selects a root in the original image with a mouse click and then a skeletonization algorithm determines the skeleton of the selected root. The output of all root tracking algorithms is a data structure of a set of roots that stores information such as connectivity between roots and their position in space.Global traits of the root system are obtained directly from the segmented image or the skeleton (GiA Roots, RooTrak). Global traits include convex hull, network depth, network length distribution, maximum number of roots, maximum width of the root system, network length, and specific root length. Furthermore, the data structure from a root tracking procedure is used to obtain individual, local root parameters (DART, RootReader2D, EZ-Rhizo, SmartRoot). The latter are able to obtain root architectural parameters that can be used for model parameterization. An additional aspect is the dealing with dynamic data (i.e. images of the same root system taken at several times). Analysis of such sequences may lead to better insight into the development of the root system (e.g. DART, SmartRoot) or even reveal growth zones and their local growth velocities (Basu and Pal, 2012).Analysis software for two-dimensional images of soil-grown root systems currently work in a semiautomated way with respect to tracing individual roots. This requires considerable user input for larger root systems. We present a new, fully automated approach for recovering root architectural parameters from two-dimensional images of root systems. The software Root System Analyzer is, to our knowledge, the first algorithm for two-dimensional analysis of soil-grown root systems that features fully automated root tracking. Only primary roots have to be initiated manually by the user. The user is also free to initiate any laterals, but this is not mandatory. Further growth of primary roots and laterals is then tracked in a fully automated way. In addition, there is a user interface that allows for manual correction of individual roots if required. In this work, we do not go into the details about the segmentation step but focus on the root tracking step and the parameterization of a root system model (Leitner et al., 2010). The described algorithm starts with a sequence of segmented two-dimensional images showing the dynamic development of a root system. For each image, morphological operators are used for skeletonization. Based on this, a graph representation of the root system is created. A dynamic root architecture model helps to determine which edges of the graph belong to an individual root. The algorithm elongates each root at the root tip and simulates growth confined within the already existing graph representation. The increment of root elongation is calculated assuming constant growth. For each root, the algorithm finds all possible paths and elongates the root in the direction of the optimal path. In this way, each edge of the graph is assigned to one or more coherent roots. The algorithm considers the fact that new branches can only emerge after the apical zone has developed, which helps in the decision of whether the root is branching or two roots are crossing or overlapping. Image sequences of root systems are handled in such a way that the previous image is used as a starting point for the current image. This is helpful in the analysis of complex root systems as well as for retrieving dynamic parameters such as elongation rates. The algorithm is implemented in a set of Matlab m-files, which makes the code flexible so that it can easily be adjusted to specific experimental setups or mathematical models.We exemplify the approach with two-dimensional neutron radiography images of lupine (Lupinus albus) root systems grown in mesocosms filled with a sandy soil. Furthermore, we compare our approach with the approaches of SmartRoot and RootReader2D and demonstrate how our approach can be used to analyze large root systems.     

Functional traits and root morphology of alpine plants

Background and Aims

Vegetation has long been recognized to protect the soil from erosion. Understanding species differences in root morphology and functional traits is an important step to assess which species and species mixtures may provide erosion control. Furthermore, extending classification of plant functional types towards root traits may be a useful procedure in understanding important root functions.

Methods

In this study, pioneer data on traits of alpine plant species, i.e. plant height and shoot biomass, root depth, horizontal root spreading, root length, diameter, tensile strength, plant age and root biomass, from a disturbed site in the Swiss Alps are presented. The applicability of three classifications of plant functional types (PFTs), i.e. life form, growth form and root type, was examined for above- and below-ground plant traits.

Key Results

Plant traits differed considerably among species even of the same life form, e.g. in the case of total root length by more than two orders of magnitude. Within the same root diameter, species differed significantly in tensile strength: some species (Geum reptans and Luzula spicata) had roots more than twice as strong as those of other species. Species of different life forms provided different root functions (e.g. root depth and horizontal root spreading) that may be important for soil physical processes. All classifications of PFTs were helpful to categorize plant traits; however, the PFTs according to root type explained total root length far better than the other PFTs.

Conclusions

The results of the study illustrate the remarkable differences between root traits of alpine plants, some of which cannot be assessed from simple morphological inspection, e.g. tensile strength. PFT classification based on root traits seems useful to categorize plant traits, even though some patterns are better explained at the individual species level.     

Patterns in root traits of woody species hosting arbuscular and ectomycorrhizas: implications for the evolution of belowground strategies

Root traits vary enormously among plant species but we have little understanding of how this variation affects their functioning. Of central interest is how root traits are related to plant resource acquisition strategies from soil. We examined root traits of 33 woody species from northeastern US forests that form two of the most common types of mutualisms with fungi, arbuscular mycorrhizas (AM) and ectomycorrhizas (EM). We examined root trait distribution with respect to plant phylogeny, quantifying the phylogenetic signal (K statistic) in fine root morphology and architecture, and used phylogenetically independent contrasts (PICs) to test whether taxa forming different mycorrhizal associations had different root traits. We found a pattern of species forming roots with thinner diameters as species diversified across time. Given moderate phylogenetic signals (K = 0.44–0.68), we used PICs to examine traits variation among taxa forming AM or EM, revealing that hosts of AM were associated with lower branching intensity (r_PIC = −0.77) and thicker root diameter (r_PIC = −0.41). Because EM evolved relatively more recently and intermittently across plant phylogenies, significant differences in root traits and colonization between plants forming AM and EM imply linkages between the evolution of these biotic interactions and root traits and suggest a history of selection pressures, with trade-offs for supporting different types of associations. Finally, across plant hosts of both EM and AM, species with thinner root diameters and longer specific root length (SRL) had less colonization (r_PIC = 0.85, −0.87), suggesting constraints on colonization linked to the evolution of root morphology.     

High‐throughput two‐dimensional root system phenotyping platform facilitates genetic analysis of root growth and development

High‐throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user‐guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large‐scale phenotyping studies. To demonstrate the unique capabilities and high‐throughput capacity of this phenotyping platform for studying root systems, genome‐wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population.     

Genetic dissection of nitrogen nutrition in pea through a QTL approach of root, nodule, and shoot variability

Pea (Pisum sativum L.) is the third most important grain legume worldwide, and the increasing demand for protein-rich raw material has led to a great interest in this crop as a protein source. Seed yield and protein content in crops are strongly determined by nitrogen (N) nutrition, which in legumes relies on two complementary pathways: absorption by roots of soil mineral nitrogen, and fixation in nodules of atmospheric dinitrogen through the plant–Rhizobium symbiosis. This study assessed the potential of naturally occurring genetic variability of nodulated root structure and functioning traits to improve N nutrition in pea. Glasshouse and field experiments were performed on seven pea genotypes and on the ‘Cameor’ × ‘Ballet’ population of recombinant inbred lines selected on the basis of parental contrast for root and nodule traits. Significant variation was observed for most traits, which were obtained from non-destructive kinetic measurements of nodulated root and shoot in pouches, root and shoot image analysis, ¹⁵N quantification, or seed yield and protein content determination. A significant positive relationship was found between nodule establishment and root system growth, both among the seven genotypes and the RIL population. Moreover, several quantitative trait loci for root or nodule traits and seed N accumulation were mapped in similar locations, highlighting the possibility of breeding new pea cultivars with increased root system size, sustained nodule number, and improved N nutrition. The impact on both root or nodule traits and N nutrition of the genomic regions of the major developmental genes Le and Af was also underlined.     

The impact of limited soil moisture and waterlogging stress conditions on morphological and anatomical root traits in maize (Zea mays L.) hybrids of different drought tolerance

Effects of soil drought or waterlogging on the morphological traits of the root system and internal root anatomy were studied in maize hybrids of different drought tolerance. The investigations comprised quantitative and qualitative analyses of a developed plant root system through determining the number, length and dry matter of the particular components of the root system and some traits of the anatomical structure of the seminal root. Obtained results have demonstrated a relatively broad variation in the habit of the root system. This mainly refers, to the number, length and dry matter of lateral roots, developed by seminal root, seminal adventitious and nodal roots as well as to some anatomical properties of the stele, cortex and metaxylem elements. Plants grown under waterlogging or drought conditions showed a smaller number and less dry matter of lateral branching than plants grown in control conditions. The harmful effect of waterlogging conditions on the growth of roots was greater when compared with that of plants exposed to drought. In the measurements of the root morphological traits, the effect of soil drought on the internal root anatomical characteristic was weaker than the effect of soil waterlogging. The observed effects of both treatments were more distinct in a drought sensitive hybrid Pioneer D than in drought resistant Pioneer C one. The drought resistant hybrid Pioneer C distinguished by a more extensive rooting and by smaller alterations in the root morphology caused by the stress conditions than drought sensitive hybrid Pioneer D one. Also the differences between the resistant and the sensitive maize hybrids were apparent for examined root anatomical traits. Results confirm that the hybrid Pioneer D of a high drought susceptibility was found to be also more sensitive to periodieal soil water excess. A more efficient water use and a lower shoot to root (S:R) ratio were found to be major reasons for a higher stress resistance of the hybrid Pioneer C. The reasons for a different response of the examined hybrids to the conditions of drought or waterlogging may be a more economical water balance and more favourable relations between the shoot and root dimensions in the drought resistant genotype. The observed modifications of the internal root structure caused by water deficit in plant tissues may partly influence on water conductivity and transport within roots. The results suggest that the morphological and anatomical traits of the maize root system may be used in practice as direct or indirect selection criteria in maize breeding.     

The use of novel phenotyping methods for validation of equine conformation scoring results

In this experiment, which is based on a cohort of 44 Lipizzan mares from the Austrian state stud farm of Piber, we present new statistical techniques for the analysis of shape and equine conformation using image data. In addition, we examined which strategies and procedures of image processing techniques led to a successful interpretation of the traits implemented in horse breeding programs. A total of 246 two-dimensional anatomical and somatometric landmarks were digitized from standardized photographs, and the variation of shape has been analyzed by the use of generalized orthogonal least-squares Procrustes (generalized Procrustes analysis (GPA)) procedures. The resulting shape variables have been regressed on the results from linear type trait classifications. In addition, the rating scores of six conformation classifiers were tested for agreement, yielding an inter-rater correlation (inter-class correlation) ranging from 0.41 to 0.68, respectively, a κ coefficient ranging from 0.16 to 0.53. From the 12 linear type traits assessed on a valuating scale, only the type-related traits (type, breed-type and harmony) revealed significant (P<0.05) results in the regression analysis of shape variables on linear type traits. The other nine traits were characterized by a lower agreement between classifiers and did not result in a significant ‘shape regression’. Finally, the ‘horse shape space’ defined by shape variables resulting from GPA procedures offered the possibility to assist in trait definition and in the evaluation of ratings, and it is an adequate biological and objective scale to human perception of conformation, which is expressed in numerical data only.     

黄河三角洲滨海盐碱地11个造林树种细根解剖性状对土壤条件的响应

细根作为植物与土壤连接的重要部位,能够反映植物对生存环境的适应性。以黄河三角洲滨海盐碱地不同立地条件下11个造林树种为对象,基于细根分支等级划分1-4级根序并进行解剖特征测定,分析细根解剖性状对滨海盐碱地不同土壤条件的响应规律。结果表明：（1）不同根序的细根直径存在显著差异,细根直径随根序升高呈增大趋势,而同根序的细根直径在不同树种间表现出显著的种间差异（P < 0.05）。1-2级细根皮层厚度、3-4级细根导管密度在树种间的差异均达显著水平（P < 0.05）。（2）在较为严重盐渍化土壤条件下（立地1）,细根皮层厚度较其他立地显著增大,但细根导管密度较小;在轻度盐碱立地条件下（立地3）,细根导管密度较大;较为严重的盐碱立地具有更为发达的细根直径及维管柱直径。（3）树种1-2级细根解剖结构与土壤环境关系最为密切,其中1级根直径与土壤pH值显著正相关（P < 0.05）,与土壤硝态氮含量呈显著负相关（P < 0.05）。对土壤理化性质与细根解剖性状的冗余分析表明,前两个轴的特征值达0.640和0.196,土壤速效养分含量与轴一（RDA1）呈正相关,低级根解剖性状则与轴二（RDA2）呈显著负相关。低级根解剖结构以及土壤的pH值能解释较多树种的差异性,其中低级根直径与皮层厚度对盐碱环境表现出较强的响应。     

Phenotypic variation and water selection potential in the stem structure of invasive alligator weed

The morphological and anatomical characteristics of stems have been found to be related to drought resistance in plants. Testing the phenotypic selection of water availability on stem anatomical traits would be useful for exploring the evolutionary potential of the stem in response to water availability. To test the phenotypic variation of the stem anatomical traits of an invasive plant in response to water availability, we collected a total of 320 individuals of Alternanthera philoxeroides from 16 populations from terrestrial and aquatic habitats in 8 plots in China and then analyzed the variation, differentiation, plasticity and selection potential of water availability on the stem anatomical traits. We found that except for the thickness of the cortex, all of the examined phenotypic parameters of the A. philoxeroides stem were significantly and positively correlated with soil water availability. The phenotypic differentiation coefficient for all of the anatomical structural parameters indicated that most of the variation existed between habitats within the same plot, whereas there was little variation among plots or among individuals within the same habitat except for variation in the thickness of the cortex. A significant phenotypic plasticity response to water availability was found for all of the anatomical traits of A. philoxeroides stem except for the thickness of the cortex. The associations between fitness and some of the anatomical traits, such as the stem diameter, the cortex area-to-stem area ratio, the pith cavity area-to-stem area ratio and the density of vascular bundles, differed with heterogeneous water availability. In both the aquatic and terrestrial habitats, no significant directional selection gradient was found for the stem diameter, the cortex area-to-stem area ratio or the density of vascular bundles. These results indicated that the anatomical structure of the A. philoxeroides stem may play an important role in the adaptation to changes in water availability.     

热带亚热带26种蕨类植物的吸收根解剖特征

植物吸收根的生理功能是从土壤中吸收水分和营养物质, 研究其解剖结构有助于揭示植物的环境适应策略。热带亚热带地区蕨类植物丰富, 生态和经济价值较高, 但目前对这一重要植物类群的吸收根解剖特征的研究仍然缺乏。该研究测定了分布在热带亚热带地区4种典型森林的共26种蕨类植物吸收根的解剖特征, 分析它们的种间差异, 结合系统发育与全球自然分布区的气候因子解释根系性状的变异。同时, 通过收集亚热带木本被子植物和温带蕨类植物相关的已发表数据, 比较不同类群的根系性状相关关系的差异。结果表明: (1)这些蕨类植物吸收根特征的种间差异显著, 8个根系性状的种间变异系数范围为20.61%-41.75%。(2)除皮层厚度外根系性状无显著的系统发育信号, 说明性状变异受系统发育的影响较小; 气候因子显著影响根系特征, 根直径和皮层厚度随着最干月(季)降水量减少而增大。(3)随着吸收根直径的减小, 亚热带木本被子植物趋于具有更低的皮层厚度/中柱直径比值, 而蕨类植物则相反; 与温带蕨类相比, 该研究中蕨类植物具有更大的根直径、皮层厚度和管胞直径。该研究有助于提高对热带亚热带蕨类植物根系生理生态适应性的认识。     

延河流域植物群落功能性状对环境梯度的响应

研究群落水平上的植物功能性状特征及其随环境梯度的变化规律,对认识不同环境梯度下植物群落的形成及其对环境的适应机制具有重要意义。以延河流域不同环境梯度下的稳定的自然植物群落为对象,测量了植物群落组成物种的叶厚度、比叶面积、叶组织密度、比根长、根组织密度、单位质量叶氮含量、单位质量根氮含量、种子质量、种子体积等9个性状,然后以物种重要值为基础加权平均得到各个性状在群落水平上的平均值(即群落性状值);以现有的环境因子栅格图为基础,利用ArcGIS提出各群落对应的环境因子值,同时测定各个群落的土壤水分,分析群落各性状值与环境因子的关系,并建立关系模型。结果表明:在群落水平上,9个植物功能性状分别与13个环境因子存在不同程度的相关性,同时这9个植物功能性状对8个环境因子梯度(土壤水分、年4-10月平均气温、年7-9月总降雨量、降雨季节变化、年平均降雨量、年平均蒸发量、坡度、坡向)的响应特征较好,不同植物功能性状间具有较好相关性。群落水平上植物功能性状及其组合随环境梯度的规律性变化,反映了延河流域植被群落构建过程中环境对功能性状的筛选效应。该研究结果对该区的植被恢复重建的物种选择及植被布局规划具有重要的实践意义。     

archiDART: an R package for the automated computation of plant root architectural traits

Background and aims

In order to analyse root system architectures (RSAs) from captured images, a variety of manual (e.g. Data Analysis of Root Tracings, DART), semi-automated and fully automated software packages have been developed. These tools offer complementary approaches to study RSAs and the use of the Root System Markup Language (RSML) to store RSA data makes the comparison of measurements obtained with different (semi-) automated root imaging platforms easier. The throughput of the data analysis process using exported RSA data, however, should benefit greatly from batch analysis in a generic data analysis environment (R software).

Methods

We developed an R package (archiDART) with five functions. It computes global RSA traits, root growth rates, root growth directions and trajectories, and lateral root distribution from DART-generated and/or RSML files. It also has specific plotting functions designed to visualise the dynamics of root system growth.

Results

The results demonstrated the ability of the package’s functions to compute relevant traits for three contrasted RSAs (Brachypodium distachyon [L.] P. Beauv., Hevea brasiliensis Müll. Arg. and Solanum lycopersicum L.).

Conclusions

This work extends the DART software package and other image analysis tools supporting the RSML format, enabling users to easily calculate a number of RSA traits in a generic data analysis environment.

     

Quantifying the effect of soil moisture content on segmenting root system architecture in X-ray computed tomography images

Aims

A commonly accepted challenge when visualising plant roots in X-ray micro Computed Tomography (μCT) images is the similar X-ray attenuation of plant roots and soil phases. Soil moisture content remains a recognised, yet currently uncharacterised source of segmentation error. This work sought to quantify the effect of soil moisture content on the ability to segment roots from soil in μCT images.

Methods

Rice (Oryza sativa) plants grown in contrasting soils (loamy sand and clay loam) were μCT scanned daily for nine days whilst drying from saturation. Root volumes were segmented from μCT images and compared with volumes derived by root washing.

Results

At saturation the overlapping attenuation values of root material, water-filled soil pores and soil organic matter significantly hindered segmentation. However, in dry soil (ca. six days of drying post-saturation) the air-filled pores increased image noise adjacent to roots and impeded accurate visualisation of root material. The root volume was most accurately segmented at field capacity.

Conclusions

Root volumes can be accurately segmented from μCT images of undisturbed soil without compromising the growth requirements of the plant providing soil moisture content is kept at field capacity. We propose all future studies in this area should consider the error associated with scanning at different soil moisture contents.     

环境及遗传背景对延河流域植物叶片和细根功能性状变异的影响

研究环境筛选作用和植物系统发育背景对植物群落构建产生的影响,有助于理解植物在生长过程中对资源的分配利用和对环境的适应规律。以延河流域3个植被带(森林带、森林草原带及典型草原带)稳定的自然植物群落为研究对象,调查了31个样地107种植物,隶属于35个科78个属,测量了6种叶片和3种细根性状。分别对3个植被带和不同植物科植物的叶片和细根性状做单因素方差分析,结果表明:叶片氮含量和细根氮含量在3个植被带间无显著差异,叶厚度、比叶面积、叶组织密度、叶片磷含量、叶片氮磷比、比根长、根组织密度在3个植被带间差异极显著。由南向北随着气候干旱的加剧,植物通过调节叶片和细根性状,表现出了不同的适应策略:森林带植物叶片相对生长速率高,根系防御力强;森林草原带植物叶片防御力强,根系相对生长速率快。不同科的植物在相同的环境条件下,对于资源的竞争力和胁迫的忍耐力也有所不同,比如豆科植物具有远远高于其他科的叶片和细根氮含量,但是对养分的利用效率并不高。GLM分析结果说明,所涉及的植物功能性状的空间变异主要来自于年均降雨量的变化及植物科的差异,如16.26%的比叶面积的变异可由年均降雨量变化解释,4.02%可由植物科的差异解释。物种水平上,叶厚度、比叶面积、叶组织密度、比根长、根组织密度、叶片磷含量是对气候干燥度变化响应敏感的植物功能性状,其空间变异主要由环境差异所致。延河流域的植物群落在形成过程中,存在明显的环境筛选效应。这表明,环境异质性在植被恢复实践中必须予以考虑。     

Linking plant morphological traits to uprooting resistance in eroded marly lands (Southern Alps, France)

In marly catchments of the French Southern Alps, soils are subjected to harsh water erosion that can result in concentrated flows uprooting small plants. Evaluating and predicting plant resistance to uprooting from simple plant traits is therefore highly important so that the most efficient plant strategy for future restoration of eroded slopes can be defined. Twelve species growing on marly land were studied. For each species, in-situ lateral uprooting tests were conducted and morphological plant traits were measured on small plants at the early stages of their development. The results show that maximum uprooting force was most positively correlated with stem basal diameter. Resistance to uprooting depends on a combination of several traits. Tap root length, the proportion of fine lateral roots and root topology were the best predictors of anchorage strength.     

Exploring the interacting effect of soil texture and bulk density on root system development in tomato (Solanum lycopersicum L.)

Knowledge of the responses of root systems in horizoned heterogeneous soil is vital to optimise uptake of water and nutrients to maximise crop productivity. We explored the interacting effects of soil bulk density and texture on the development of root systems in tomato.Two main techniques were employed, X-ray micro-Computed Tomography (μCT), to provide non-destructive, three-dimensional (3D) images of root systems in situ and destructive root washing followed by WinRHIZO^® scanning. Solanum lycopersicum L. cv. Ailsa Craig plants were grown in soil columns for 10 days to measure the effect of soil compaction on selected root traits. Treatments included bulk density (1.2–1.6 Mg m⁻³), soil texture (loamy sand and clay loam) and the effects of layering.The effect of bulk density on root growth was greatest 3 days after transplanting (DAT) in both soil types. The effect of soil texture was not apparent at this stage, but was significant at 10 DAT for most root and shoot variables. The influence of bulk density differed between soil types as increasing compaction promoted plant growth in clay loam but retarded root growth in loamy sand.We observed that at 3 DAT root growth is primarily influenced by bulk density but by 10 DAT a switch in the processes regulating root growth occurs and the texture of the soil becomes very influential. Future investigations of root growth must consider soil physical properties individually and at specific time points, as their importance changes as the root system becomes established. Here we have demonstrated both positive and negative impacts across a wide range of bulk density treatments in different soil textures on root growth. This illustrates the importance of understanding the complex nature of root–soil interactions, especially for agricultural practices such as seedbed preparation.