Visualization of Arabidopsis root system architecture in 3D by refraction-contrast X-ray micro-computed tomography.

In numerous studies dealing with roots of woody plants, a description of the root system architecture is needed. During the twentieth century, several manual measurement methods were used, depending on the objectives of study. Due to the difficulties in accessing the roots and the duration of measurements, the studies generally involved a low number of root systems, were often qualitative and focused only on one specific application. Quantitative methods in plant architecture were largely developed in the last 40 years for aerial architecture. However, root systems have particular features and often need specific procedures. Since the end of the 1990s, new devices and techniques have been available for coarse root architecture measurements including volume location techniques (non-invasive or destructive) and manual or semi-automatic 3D digitising. Full 3D root system architecture dynamics was also reconstructed from partial measurements using modelling procedures. On the one hand, non-invasive and automatic techniques need more development to obtain full 3D architecture, i.e. geometry and topology. On the other hand, both one inexpensive manual and one semi-automatic digitizing procedure are now available to measure precisely and rapidly the full 3D architecture of uprooted and excavated coarse root systems. Specific software and a large number of functions are also available for an in-depth analysis of root architecture and have already been used in a dozen of research papers including a fairly large sample of mature trees. A comprehensive analysis of root architecture can be achieved by classifying individual roots in several root types through architectural analysis. The objective of this paper is both to give a detailed overview of the state of the art techniques for 3D root system architecture measurement and analysis and to give examples of applications in this field. Practical details are also given so that this paper can be used as a sort of manual for people who want to improve their practice or to enter this quite new research field.

Potato plants are often exposed to soil drought, which results in crop losses, because potato root system is shallow. The aim of our study was to examine the relationship between root system architecture and drought tolerance. We measured rooting depth, total length, surface area, average diameter, and dry weight of the root system every 20 cm of soil depth. We examined four potato cultivars, two that were more tolerant to drought (Gwiazda and Tajfun), and two that were more sensitive (Oberon and Cekin). Our results showed different responses by the tested cultivars to drought. The root dry mass decreased in response to drought and this decrease was smaller in the more drought-tolerant cultivars. In response to drought, the more drought-tolerant cultivars developed elongated roots, but the roots of the less-tolerant cultivars remained the same length. The decrease in root diameter was also smaller in the more drought-tolerant cultivars.

Environmental events, such as drought, are predicted to increase in frequency and duration, and coupled with an expanding global population, improving cereal crop productivity and yield stability is crucial. A body of research suggests that roots may be fundamental to increasing crop yields, whereby optimised root systems could capture more water and nutrients with minimal metabolic costs. For efficient resource capture in most water-limited environments, a narrow and deep root architecture is likely advantageous. The central importance of the root system in plant productivity cannot be underestimated, yet the functional and genetic basis of root system architecture in cereal crops is relatively unknown.In this thesis, the genetics underpinning root system architecture in barley (Hordeum vulgare L.) were investigated and the value of roots as a drought adaptive trait in barley was examined. In addition, the genetic variation in delayed-foliar senescence and flowering time were also explored to investigate any shared genetic control between above- and below-ground drought adaptation traits. Through the characterisation of three diverse barley populations, key genes influencing root system architecture were identified. Preliminary evidence for shared genetic control between delayed foliar senescence and root architecture was observed through co-located quantitative trait loci (QTL), specifically the gibberellic acid biosynthesis gene, Hv20ox1. Preliminary associations between time to flowering and seminal root traits were confirmed through the identification of VERNALIZATION1 (VRN1) as a major gene influencing root architecture in barley. Whereby, VRN1 is a key regulator of flowering behaviour in cereal crops. The research described in this thesis provides novel insight into the genetic control of root system architecture and reveals a new role for the previously described pathway for regulation of flowering in modulating the largely unexplored genetic architecture of root development in barley. The knowledge generated from this research may be harnessed in barley breeding programs to assist in the development of robust cultivars better adapted to the increasingly variable future climate.

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 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.

Root systems of woody plants generally display a strong relationship between the cross-sectional area or cross-sectional diameter (CSD) of a root and the dry weight of biomass (DWd) or root volume (Vd) that has grown (i.e., is descendent) from a point. Specification of this relationship allows one to quantify root architectural patterns and estimate the amount of material lost when root systems are extracted from the soil. However, specifications of this relationship generally do not account for the fact that root systems are comprised of multiple types of roots. We assessed whether the relationship between CSD and Vd varies as a function of root type. Additionally, we sought to identify a more accurate and time-efficient method for estimating missing root volume than is currently available. We used a database that described the 3D root architecture of Pinus pinaster root systems (5, 12, or 19 years) from a stand in southwest France. We determined the relationship between CSD and Vd for 10,000 root segments from intact root branches. Models were specified that did and did not account for root type. The relationships were then applied to the diameters of 11,000 broken root ends to estimate the volume of missing roots. CSD was nearly linearly related to the square root of Vd, but the slope of the curve varied greatly as a function of root type. Sinkers and deep roots tapered rapidly, as they were limited by available soil depth. Distal shallow roots tapered gradually, as they were less limited spatially. We estimated that younger trees lost an average of 17% of root volume when excavated, while older trees lost 4%. Missing volumes were smallest in the central parts of root systems and largest in distal shallow roots. The slopes of the curves for each root type are synthetic parameters that account for differentiation due to genetics, soil properties, or mechanical stimuli. Accounting for this differentiation is critical to estimating root loss accurately.

The underground reserve (root) has been an uncharted research territory with its untapped genetic variation yet to be exploited. Identifying ideal traits and breeding new rice varieties with efficient root system architecture (RSA) has great potential to increase resource-use efficiency and grain yield, especially under direct-seeded rice, by adapting to aerobic soil conditions. In this review, we tried to mine the available research information on the direct-seeded rice (DSR) root system to highlight the requirements of different root traits such as root architecture, length, number, density, thickness, diameter, and angle that play a pivotal role in determining the uptake of nutrients and moisture at different stages of plant growth. RSA also faces several stresses, due to excess or deficiency of moisture and nutrients, low or high temperature, or saline conditions. To counteract these hindrances, adaptation in response to stress becomes essential. Candidate genes such as early root growth enhancer PSTOL1, surface rooting QTL qSOR1, deep rooting gene DRO1, and numerous transporters for their respective nutrients and stress-responsive factors have been identified and validated under different circumstances. Identifying the desired QTLs and transporters underlying these traits and then designing an ideal root architecture can help in developing a suitable DSR cultivar and aid in further advancement in this direction.

A plant's ability to maintain or improve its yield under limiting conditions, such as nutrient deficiency or drought, can be strongly influenced by root system architecture (RSA), the three-dimensional distribution of the different root types in the soil. The ability to image, track and quantify these root system attributes in a dynamic fashion is a useful tool in assessing desirable genetic and physiological root traits. Recent advances in imaging technology and phenotyping software have resulted in substantive progress in describing and quantifying RSA. We have designed a hydroponic growth system which retains the three-dimensional RSA of the plant root system, while allowing for aeration, solution replenishment and the imposition of nutrient treatments, as well as high-quality imaging of the root system. The simplicity and flexibility of the system allows for modifications tailored to the RSA of different crop species and improved throughput. This paper details the recent improvements and innovations in our root growth and imaging system which allows for greater image sensitivity (detection of fine roots and other root details), higher efficiency, and a broad array of growing conditions for plants that more closely mimic those found under field conditions.

Studying the effects of small molecules on root system development in the context of a large-scale chemical genetic screen has previously been a technical challenge. The recent development of novel seedling growth devices ("Phytostrips"), used in combination with standard 96-well microtiter plates, has made it possible to perform detailed studies of changes in root morphology and root system architecture following the application of a library of chemical compounds. Phytostrips were originally designed to allow automated robotic capture of images of roots and shoots of the model species Arabidopsis thaliana, but can also be used for manual screens that are more laborious but do not require the investment in expensive robotics.Here we describe a protocol for the use of Phytostrips to perform chemical genetic screens that rely on clearly observable changes in root morphology or root system architecture. As an example, we describe the use of polyethylene glycol to impose an abiotic stress related to reduced water potential and the application of a chemical screen for small molecules that are able to rescue Arabidopsis root development from the disruptive effect of the polyethylene glycol treatment. The protocol we describe provides a template for the application of a multiplicity of other screens for compounds that can antagonize the effects of a range of abiotic stresses on root development.

Under all environments, roots are important for plant anchorage and acquiring water and nutrients. However, there is a knowledge gap regarding how root architecture contributes to stress tolerance in a changing climate. Two closely related plant species, maize and sorghum, have distinct root system architectures and different levels of stress tolerance, making comparative analysis between these two species an ideal approach to resolve this knowledge gap. However, current research has focused on shared aspects of the root system that are advantageous under abiotic stress conditions rather than on differences. Here we summarize the current state of knowledge comparing the root system architecture relative to plant performance under water deficit, salt stress, and low phosphorus in maize and sorghum. Under water deficit, steeper root angles and deeper root systems are proposed to be advantageous for both species. In saline soils, a reduction in root length and root number has been described as advantageous, but this work is limited. Under low phosphorus, root systems that are shallow and wider are beneficial for topsoil foraging. Future work investigating the differences between these species will be critical for understanding the role of root system architecture in optimizing plant production for a changing global climate.

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

Although rice is one of the most important crops in the world, especially in Asia, and many agronomic studies have been done, information on development of the root system is limited compared with the shoot. However, most agricultural practices for growing rice (e.g., fertilization and water management) affect root growth. Several researches, in fact, suggest that the dimension and distribution of the root system have possible relations to yield in rice (Kawata et al., 1978c; Yamazaki et al., 1980; Morita et al., 1988b; Mawaki et al., 1990). Therefore, knowledge of structure and development of the root system is essential for selecting effective practices in rice cultivation, though it is quite tedious and time-consuming to study the root system of rice plants grown under flooded conditions. In this chapter, I will briefly review the structure and development of the rice root system; then I will discuss the mathematical modeling of root system morphology and the applications of such modeling (see chapter by Dickmann and Hendrick in this volume).

Roots have a central role in plant resource capture and are the interface between the plant and the soil that affect multiple ecosystem processes. Field pennycress (Thlaspi arvense L.) is a diploid annual cover crop species that has potential utility for reducing soil erosion and nutrient losses; and has rich seeds (30-35% oil) amenable to biofuel production and as a protein animal feed. The objective of this research was to (1) precisely characterize root system architecture and development, (2) understand plastic responses of pennycress roots to nitrate nutrition, (3) and determine genotypic variance available in root development and nitrate plasticity. Using a root imaging and analysis pipeline, the 4D architecture of the pennycress root system was characterized under four nitrate regimes, ranging from zero to high nitrate concentrations. These measurements were taken at four time points (days 5, 9, 13, and 17 after sowing). Significant nitrate condition response and genotype interactions were identified for many root traits, with the greatest impact observed on lateral root traits. In trace nitrate conditions, a greater lateral root count, length, density, and a steeper lateral root angle was observed compared to high nitrate conditions. Additionally, genotype-by-nitrate condition interaction was observed for root width, width:depth ratio, mean lateral root length, and lateral root density. These findings illustrate root trait variance among pennycress accessions. These traits could serve as targets for breeding programs aimed at developing improved cover crops that are responsive to nitrate, leading to enhanced productivity, resilience, and ecosystem service.

SummaryParking manoeuvring was studied in a driving simulator. Younger and older participants were classified according to the extent of their visual and attentional fields of view. The manoeuvres were made either in the presence of a spatial reference on the adjacent pavement (a pedestrian or a parking meter) or with no reference. It was found that the length of manoeuvres varied only among younger drivers depending on the type of spatial reference and the extent of their visual and attentional fields. The participants with wider fields took advantage of the presence of a pedestrian or a parking meter, whereas those with a narrower field of view did not. Furthermore, the individuals with a narrower field of view were disturbed by the presence of a pedestrian on the pavement. This study provides new information to consider in relation to the safety of manoeuvring among drivers with different visual and attentional capacities. Copyright © 2015 John Wiley & Sons, Ltd.

Winter rapeseed (Brassica rapa L.) can well‐adapt to environmental conditions such as barrenness, water deficit and low temperature in arid and semi‐arid planting regions and is the preferred rapeseed type. In this study, we analysed changes of root system morphology, antioxidant enzyme activity, endogenous hormone contents and differentially expressed proteins (DEPs) under control (CK), slight water deficit (SWD, 50–55% of maximum field water capacity), moderate water deficit (MWD, 40–45% of maximum field water capacity) and high water deficit (HWD, 30–35% of maximum field water capacity) conditions. Winter rapeseed experienced taproot elongation, decreased taproot diameter and increased lateral root number, under water deficit stress. The accumulation of reactive oxygen species (ROS) can cause membrane system peroxidation, and antioxidant enzyme activity increases to remove ROS. Changes in jasmonic acid (JA), salicylic acid (SA), cytokinin (CTK), auxin (IAA) and gibberellin (GA) levels promote the absorption of water and minerals by driving changes in the root system architecture to resist water deficit stress. A proteomic analysis has shown that DEPs are involved in energy metabolism, antioxidation response, osmotic regulation, hormone signal transduction, protein metabolism and the stress response, and these proteins are located in the peroxisome, chloroplast, mitochondrion, cell wall, vacuole, cytoplasm, extracellular space and cell membrane. In this study, multiple DEPs (malate dehydrogenase cytoplasmic 1 OS, 14‐3‐3‐like protein GF14 Psi, GA 3‐beta‐dioxygenase, glutathione reductase and jasmonate‐inducible protein) were involved in the root system architecture, revealing the complexity of the root response to water deficit. Significant/extremely significant synergistic relationships were observed between antioxidant enzyme activity and endogenous hormone contents. In conclusion, ROS, endogenous hormones and stress‐related proteins work synergistically to control the root system architecture of winter rapeseed roots in response to water deficit stress.