Bridging Time-series Image Phenotyping and Functional–Structural Plant Modeling to Predict Adventitious Root System Architecture

Root system architecture (RSA) is an essential characteristic for efficient water and nutrient absorption in terrestrial plants; its plasticity enables plants to respond to different soil environments. Better understanding of root plasticity is important in developing stress-tolerant crops. Non-invasive techniques that can measure roots in soils nondestructively, such as X-ray computed tomography (CT), are useful to evaluate RSA plasticity. However, although RSA plasticity can be measured by tracking individual root growth, only a few methods are available for tracking individual roots from time-series three-dimensional (3D) images. We developed a semi-automatic workflow that tracks individual root growth by vectorizing RSA from time-series 3D images via two major steps. The first step involves 3D alignment of the time-series RSA images by iterative closest point registration with point clouds generated by high-intensity particles in potted soils. This alignment ensures that the time-series RSA images overlap. The second step consists of backward prediction of vectorization, which is based on the phenomenon that the root length of the RSA vector at the earlier time point is shorter than that at the last time point. In other words, when CT scanning is performed at time point A and again at time point B for the same pot, the CT data and RSA vectors at time points A and B will almost overlap, but not where the roots have grown. We assumed that given a manually created RSA vector at the last time point of the time series, all RSA vectors except those at the last time point could be automatically predicted by referring to the corresponding RSA images. Using 21 time-series CT volumes of a potted plant of upland rice (Oryza sativa), this workflow revealed that the root elongation speed increased with age. Compared with a workflow that does not use backward prediction, the workflow with backward prediction reduced the manual labor time by 95%. We developed a workflow to efficiently generate time-series RSA vectors from time-series X-ray CT volumes. We named this workflow 'RSAtrace4D' and are confident that it can be applied to the time-series analysis of RSA development and plasticity.

The root system is critical for the survival of nearly all land plants and a key target for improving abiotic stress tolerance, nutrient accumulation, and yield in crop species. Although many methods of root phenotyping exist, within field studies, one of the most popular methods is the extraction and measurement of the upper portion of the root system, known as the root crown, followed by trait quantification based on manual measurements or 2D imaging. However, 2D techniques are inherently limited by the information available from single points of view. Here, we used X-ray computed tomography to generate highly accurate 3D models of maize root crowns and created computational pipelines capable of measuring 71 features from each sample. This approach improves estimates of the genetic contribution to root system architecture and is refined enough to detect various changes in global root system architecture over developmental time as well as more subtle changes in root distributions as a result of environmental differences. We demonstrate that root pulling force, a high-throughput method of root extraction that provides an estimate of root mass, is associated with multiple 3D traits from our pipeline. Our combined methodology can therefore be used to calibrate and interpret root pulling force measurements across a range of experimental contexts or scaled up as a stand-alone approach in large genetic studies of root system architecture.

Hydrogen sulfide (H2S) is regarded as a “New Warrior” for managing plant stress. It also plays an important role in plant growth and development. The regulation of root system architecture (RSA) by H2S has been widely recognized. Plants are dependent on the RSA to meet their water and nutritional requirements. They are also partially dependent on the RSA for adapting to environment change. Therefore, a good understanding of how H2S affects the RSA could lead to improvements in both crop function and resistance to environmental change. In this review, we summarized the regulating effects of H2S on the RSA in terms of primary root growth, lateral and adventitious root formation, root hair development, and the formation of nodules. We also discussed the genes involved in the regulation of the RSA by H2S, and the relationships with other signal pathways. In addition, we discussed how H2S regulates root growth in response to abiotic stress. This review could provide a comprehensive understanding of the role of H2S in roots during development and under abiotic stress.

Plant root system architecture (RSA) has an important role in crop production, particularly for water and nutrient uptake under limiting conditions. In the last few years, several root phenotyping methods have been developed. Here we present a new technique which has been developed for non-destructive, inexpensive and high-throughput root growth studies and RSA analyses. To illustrate the potential applications, this method was tested in an experiment with nitrogen and phosphorous deficiencies in a nutrient solution, affecting RSA parameters of two spring barley varieties (Bojos and Barke). This technique is based on root growth on vertically positioned black filter paper (30 × 60 cm) placed between two black plastic (PVC-P) foils and micro-irrigation systems providing the recirculation of nutrient solution. The pre-germinated seeds were placed in the slit between two plastic bars which carry the filter paper and plastic sheets and fix the plant in the vertical position. This system allows easy repeated non-invasive access to roots for their measuring and sampling. Eighteen days after transplanting the root imaging was done using an RGB digital camera. To evaluate the root architecture parameters the "SmartRoot" software was used. The results revealed that the system is able to detect changes in RSA which are caused mainly by P deficiency (particularly changes in lateral root length and total root area). It can be concluded that this technique has a great potential for non-destructive root growth studies, RSA measurement and root sampling.

Understanding the development of roots exposed to contaminants and the potential of plant-associated bacteria for optimization of growth.

The root system architecture (RSA) determines plant growth and yield. The characterization of optimal RSA and discovery of genetic loci or candidate genes that control root traits are therefore important research goals. However, the hidden nature of the root system makes it difficult to perform nondestructive, rapid analyses of RSA. In this study, we developed an automated, nondestructive, high-throughput root phenotyping platform (Root-HTP) and a corresponding data processing pipeline for efficient, large-scale characterization of wheat (Triticum aestivum L.) RSA. This system is capable of tracking root growth dynamics and RSA variation across all wheat developmental stages. In situ phenotyping using Root-HTP extracted 47 RSA traits, including 33 novel traits in wheat and 23 novel traits in other crops. We used root trait data from the phenotyping system and yield trait data to conduct a genome-wide association study (GWAS) of 155 wheat accessions, which identified 2,650 SNPs and 233 quantitative trait loci (QTLs) associated with aspects of root architecture. The candidate gene TaMYB93 was detected in a QTL for root tortuosity, and EMS mutants confirmed its effect on RSA in wheat. We explored the relationship between root- and yield-related traits and identified 20 root-related QTLs that were also associated with yield traits. Furthermore, we have built a predictive model for wheat yield based on 18 RSA traits and propose a parsimonious RSA ideotype associated with high yields. The data generated from this study provide insight into the genetic architecture of wheat RSA and support for RSA ideotype-based wheat breeding and yield prediction.

BackgroundPlant growth-promoting rhizobacteria are increasingly being seen as a way of complementing conventional inputs in agricultural systems. The effects on their host plants are diverse and include volatile-mediated growth enhancement. This study sought to assess the effects of bacterial volatiles on the biomass production and root system architecture of the model grass Brachypodium distachyon (L.) Beauv.ResultsAn in vitro experiment allowing plant-bacteria interaction throughout the gaseous phase without any physical contact was used to screen 19 bacterial strains for their growth-promotion ability over a 10-day co-cultivation period. Five groups of bacteria were defined and characterised based on their combined influence on biomass production and root system architecture. The observed effects ranged from unchanged to greatly increased biomass production coupled with increased root length and branching. Primary root length was increased only by the volatile compounds emitted by Enterobacter cloacae JM22 and Bacillus pumilus T4. Overall, the most significant results were obtained with Bacillus subtilis GB03, which induced an 81 % increase in total biomass, as well as enhancing total root length, total secondary root length and total adventitious root length by 88.5, 201.5 and 474.5 %, respectively.ConclusionsThis study is the first report on bacterial volatile-mediated growth promotion of a grass plant. Contrasting modulations of biomass production coupled with changes in root system architecture were observed. Most of the strains that increased total plant biomass also modulated adventitious root growth. Under our screening conditions, total biomass production was strongly correlated with the length and branching of the root system components, except for primary root length. An analysis of the emission kinetics of the bacterial volatile compounds is being undertaken and should lead to the identification of the compounds responsible for the observed growth-promotion effects. Within the context of the inherent characteristics of our in vitro system, this paper identifies the next critical experimental steps and discusses them from both a fundamental and an applied perspective.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-015-0585-3) contains supplementary material, which is available to authorized users.

Water uptake by roots is a key adaptation of plants to aerial life. Water uptake depends on root system architecture (RSA) and tissue hydraulic properties that, together, shape the root hydraulic architecture. This work investigates how the interplay between conductivities along radial (e.g. aquaporins) and axial (e.g. xylem vessels) pathways determines the water transport properties of highly branched RSAs as found in adult Arabidopsis (Arabidopsis thaliana) plants. A hydraulic model named HydroRoot was developed, based on multi-scale tree graph representations of RSAs. Root water flow was measured by the pressure chamber technique after successive cuts of a same root system from the tip toward the base. HydroRoot model inversion in corresponding RSAs allowed us to concomitantly determine radial and axial conductivities, providing evidence that the latter is often overestimated by classical evaluation based on the Hagen–Poiseuille law. Organizing principles of Arabidopsis primary and lateral root growth and branching were determined and used to apply the HydroRoot model to an extended set of simulated RSAs. Sensitivity analyses revealed that water transport can be co-limited by radial and axial conductances throughout the whole RSA. The number of roots that can be sectioned (intercepted) at a given distance from the base was defined as an accessible and informative indicator of RSA. The overall set of experimental and theoretical procedures was applied to plants mutated in ESKIMO1 and previously shown to have xylem collapse. This approach will be instrumental to dissect the root water transport phenotype of plants with intricate alterations in root growth or transport functions.

An important adaptation of plants to phosphorus (P) deficiency is to alter root system architecture (RSA) to increase P acquisition from the soil, but soil-based observations of RSA are technically challenging, especially in mature plants. The aim of this study was to investigate the root development and RSA of oilseed rape (Brassica napus L.) under low and high soil P conditions during an entire growth cycle. A new large Brassica-rhizotron system (approx. 118-litre volume) was developed to study the RSA dynamics of B. napus 'Zhongshuang11' in soils, using top-soils supplemented with low P (LP) or high P (HP) for a full plant growth period. Total root length (TRL), root tip number (RTN), root length density (RLD), biomass and seed yield traits were measured. TRL and RTN increased more rapidly in HP than LP plants from seedling to flowering stages. Both traits declined from flowering to silique stages, and then increased slightly in HP plants; in contrast, root senescence was observed in LP plants. RSA parameters measured from the polycarbonate plates were empirically consistent with analyses of excavated roots. Seed yield and shoot dry weights were closely associated positively with root dry weights, TRL, RLD and RTN at both HP and LP. The Brassica-rhizotron system is an effective method for soil-based root phenotyping across an entire growth cycle. Given that root senescence is likely to occur earlier under low P conditions, crop P deficiency is likely to affect late water and nitrogen uptake, which is critical for efficient resource use and optimal crop yields.

An account is given on: root growth and root system architecture (components and developmental processes, root growth, tropisms and hormonal control); interactions between plant roots and the soil environment (root growth in response to soil environmental conditions, and effect of root growth and development on soil properties); and the importance of plant roots at the community scale (interactions between roots and root systems in multi-species systems, agronomic implications of multi-specific systems, and impact of root communities on climate).

Chapter 2 - Root System Architecture

State-of-the-Art models of Root System Architecture (RSA) do not allow simulating root growth around rigid obstacles. Yet, the presence of obstacles can be highly disruptive to the root system. We grew wheat seedlings in sealed petri dishes without obstacle and in custom 3D-printed rhizoboxes containing obstacles. Time-lapse photography was used to reconstruct the wheat root morphology network. We used the reconstructed wheat root network without obstacle to calibrate an RSA model implemented in the R-SWMS software. The root network with obstacles allowed calibrating the parameters of a new function that models the influence of rigid obstacles on wheat root growth. Experimental results show that the presence of a rigid obstacle does not affect the growth rate of the wheat root axes, but that it does influence the root trajectory after the main axis has passed the obstacle. The growth recovery time, i.e. the time for the main root axis to recover its geotropism-driven growth, is proportional to the time during which the main axis grows along the obstacle. Qualitative and quantitative comparisons between experimental and numerical results show that the proposed model successfully simulates wheat RSA growth around obstacles. Our results suggest that wheat roots follow patterns that could inspire the design of adaptive engineering flow networks.

Responses of soybean (Glycine max [L.] Merr.) to zinc oxide nanoparticles: Understanding changes in root system architecture, zinc tissue partitioning and soil characteristics

Although the root length density (RLD) of crops depends on their root system architecture (RSA), the root growth modules of many 1D field crop models often ignored the RSA in the simulation of the RLD. In this study, two model set‐up scenarios were used to simulate the RLD, above‐ground biomass (AGB) and grain yield (GY) of water‐stressed spring wheat in Germany, aiming to investigate the impact of improved RLD on AGB and GY predictions. In scenario 1, SlimRoot, a root growth sub‐model that does not consider the RSA of the crop, was coupled to a Lintul5‐SlimNitrogen‐SoilCN‐Hillflow1D crop model combination. In scenario 2, SlimRoot was replaced with the Somma sub‐model which considered the RSA for simulating RLD. The simulated RLD, AGB and GY were compared with observations. Scenario 2 predicted the RLD, AGB and GY with an average root mean square error (RMSE) of 0.43 cm/cm3, 0.59 t/ha and 1.03 t/ha, respectively, against 1.03 cm/cm3, 1.20 t/ha and 2.64 t/ha for scenario 1. The lower RMSE under scenario 2 shows that, even under water‐stress conditions, predictions of GY and AGB can be improved by considering the RSA of the crop for simulating the RLD.

2D Finite Element (FE) Analysis of tree overturning was carried out. The main objective was to determine the effect of particular roots on anchorage strength in two contrasted soils and to discuss acclimation of root growth with regard to mechanical constraints. The FE model was based on the description of herringbone- like root patterns. Tree overturning simulations were performed applying a lateral displacement to a rigid stem. The results showed that lateral roots are the main components of tree anchorage in clay-like soil whereas the taproot plays a more significant role in sand. The modes of failure were different in the two soils, resulting in different root-plate shapes and rotation axis positions. Anisotropic secondary growth as a response to mechanical perturbations was also discussed based on the calculation of von Mises' stresses at the surface of the root elements. In conclusion, we propose a new concept whereby Functional Structural Plant Models are linked with Biomechanical Models in order to test hypotheses concerning tree growth acclimation to mechanical stresses.