Plant growth and development involve the integration of numerous processes, influenced by both endogenous and exogenous factors. At any given time during a plant's life cycle, the plant architecture is a readout of this continuous integration. However, untangling the individual factors and processes involved in the plant development and quantifying their influence on the plant developmental process is experimentally challenging. Here we used a combination of computational plant models to help understand experimental findings about how local phloem anatomical features influence the root system architecture. In particular, we simulated the mutual interplay between the root system architecture development and the carbohydrate distribution to provide a plausible mechanistic explanation for several experimental results. Our in silico study highlighted the strong influence of local phloem hydraulics on the root growth rates, growth duration and final length. The model result showed that a higher phloem resistivity leads to shorter roots due to the reduced flow of carbon within the root system. This effect was due to local properties of individual roots, and not linked to any of the pleiotropic effects at the root system level. Our results open the door to a better representation of growth processes in plant computational models.
48 | Grain size modulates volcanic ash retention on crop foliage and potential yield loss
2022 | Ligot N, Bogaert P, Biass S, Lobet G, Delmelle P
Grain size modulates volcanic ash retention on crop foliage and potential yield loss
Plant phenotyping platforms generate large amounts of high dimensional data at different scales of plant organization. The possibility to use this information as inputs of models is an opportunity to develop models that integrate new processes and genetic inputs. We assessed to what extent the phenomics and modelling communities can address the issues of interoperability and data exchange, using a science mapping approach (i.e. visualization and analysis of a broad range of scientific and technological activities as a whole). In this paper, we (i) evaluate connections, (ii) identify compatible and connectable research topics, and (iii) propose strategies to facilitate connection across communities. We applied a science mapping approach based on reference and term analyses to a set of 4332 scientific papers published by the plant phenomics and modelling communities from 1980 to 2019, retrieved using the Elsevier’s Scopus database and the quantitative-plant.org website. The number of papers on phenotyping and modelling dramatically increased during the past decade, boosted by progress in phenotyping technologies and by key developments at hard- and software levels. The science mapping approach indicated a large diversity of research topics studied in each community. Despite compatibilities of research topics, the level of connection between the phenomics and modelling communities was low. Although phenomics and modelling crucially need to exchange data, the two communities appeared to be weakly connected. We encourage these communities to work on ontologies, harmonized formats, translators and connectors to facilitate transparent data exchange.
47 | Connecting plant phenotyping and modelling communities. lessons from science mapping and operational perspectives
2022 | Saint Cast C, Lobet G, Cabrera-Bosquet L, Couvreur V, Pradal C, Tardieu F, Draye X
Connecting plant phenotyping and modelling communities. lessons from science mapping and operational perspectives
Ash fall from volcanic eruptions endangers crop production and food security and jeopardises agricultural livelihoods. As population in the vicinity of volcanoes continues to grow, strategies to reduce volcanic risks to and impacts on crops are increasingly needed. This effort involves the use of quantitative relationships for anticipating crop damage from ash exposure. However, current models of crop vulnerability to ash rely solely on ash thickness (or loading) and fail to reproduce the complex interplay of other volcanic and non-volcanic factors that drive impact. Ash retention on crop leaves affects photosynthesis and is ultimately responsible for widespread damage to crops. In this context, we carried out greenhouse experiments to assess how ash grain size, leaf pubescence and humidity conditions at leaf surfaces influence the retention of ash (defined as the percentage of foliar cover coated with ash) in tomato and chilli pepper plants, two crop types commonly grown in volcanic regions. For a fixed ash mass load (~570 g m-2), we found that ash retention decreases exponentially with increasing grain size and is enhanced when leaves are pubescent (such as in tomato) or their surfaces are wet. Assuming that leaf area index (LAI) diminishes with ash retention in tomato and chilli pepper, we derived a new expression for predicting potential crop yield loss after an ash fall event. A corollary result is that the measurement of crop LAI in ash-affected areas may serve as a useful impact metric. Our study demonstrates that quantitative insights into crop vulnerability can be gained rapidly from controlled experiments, thereby providing a mean to improve models that can predict ash risks to crops accurately. We advocate this approach to broaden our understanding of ash-plant interaction and to validate the use of remote sensing methods for assessing crop damage and recovery at various spatial and time scales after an eruption.
46 | Genetic Variability of Arabidopsis thaliana Mature Root System Architecture and Genome-Wide Association Study
2022 | Deja-Muylle A, Opdenacker D, Parizot B, Motte H, Lobet G, Storme V, Clauw P, Njo M, Beeckman T
Genetic Variability of Arabidopsis thaliana Mature Root System Architecture and Genome-Wide Association Study
Root system architecture (RSA) has a direct influence on the efficiency of nutrient uptake and plant growth, but the genetics of RSA are often studied only at the seedling stage. To get an insight into the genetic blueprint of a more mature RSA, we exploited natural variation and performed a detailed in vitro study of 241 Arabidopsis thaliana accessions using large petri dishes. A comprehensive analysis of 17 RSA traits showed high variability among the different accessions, unveiling correlations between traits and conditions of the natural habitat of the plants. A sub-selection of these accessions was grown in water-limiting conditions in a rhizotron set-up, which revealed that especially the spatial distribution showed a high consistency between in vitro and ex vitro conditions, while in particular, a large root area in the lower zone favored drought tolerance. The collected RSA phenotype data were used to perform genome-wide association studies (GWAS), which stands out from the previous studies by its exhaustive measurements of RSA traits on more mature Arabidopsis accessions used for GWAS. As a result, we found not only several genes involved in the lateral root (LR) development or auxin signaling pathways to be associated with RSA traits but also new candidate genes that are potentially involved in the adaptation to the natural habitats.
45 | Combining deep learning and automated feature extraction to analyze minirhizotron images. Development and validation of a new pipeline
2022 | Bauer F, Lärm L, Morandage S, Lobet G, Vanderborght J, Vereecken H, Schnepf A
Combining deep learning and automated feature extraction to analyze minirhizotron images. Development and validation of a new pipeline
Root systems of crops play a significant role in agro-ecosystems. The root system is essential for water and nutrient uptake, plant stability, symbiosis with microbes and a good soil structure. Minirhizotrons, consisting of transparent tubes that create windows into the soil, have shown to be effective to non-invasively investigate the root system. Root traits, like root length observed around the tubes of minirhizotron, can therefore be obtained throughout the crop growing season. Analyzing datasets from minirhizotrons using common manual annotation methods, with conventional software tools, are time consuming and labor intensive. Therefore, an objective method for high throughput image analysis that provides data for field root-phenotyping is necessary. In this study we developed a pipeline combining state-of-the-art software tools, using deep neural networks and automated feature extraction. This pipeline consists of two major components and was applied to large root image datasets from minirhizotrons. First, a segmentation by a neural network model, trained with a small image sample is performed. Training and segmentation are done using “Root-Painter”. Then, an automated feature extraction from the segments is carried out by “RhizoVision Explorer”. To validate the results of our automated analysis pipeline, a comparison of root length between manually annotated and automatically processed data was realized with more than 58,000 images. Mainly the results show a high correlation (R=0.81) between manually and automatically determined root lengths. With respect to the processing time, our new pipeline outperforms manual annotation by 98.1 - 99.6 %. Our pipeline,combining state-of-the-art software tools, significantly reduces the processing time for minirhizotron images. Thus, image analysis is no longer the bottle-neck in high throughput phenotyping approaches.
44 | Loïc Pagès, founding scientist in root ecology and modelling
2021 | Root scientists
Loïc Pagès, founding scientist in root ecology and modelling
43 | Investigating Soil–Root Interactions with the Numerical Model RSWMS
2022 | Meunier F, Couvreur V, Draye X, Lobet G, Huber K, Schroeder N, Jorda H, Koch A, Landl M, Schnepf A, Vanderborght J, Vereecken H, Javaux M
Investigating Soil–Root Interactions with the Numerical Model RSWMS
In this chapter, we present the Root and Soil Water Movement and Solute transport model RSWMS, which can be used to simulate flow and transport in the soil plant system. The equations describing water flow in soil root systems are presented and numerical solutions are provided. An application of RSWMS is then briefly discussed, in which we combine in vivo and in silico experiments in order to decrypt water flow in the soil root domain. More precisely, light transmission imaging experiments were conducted to generate data that can serve as input for the RSWMS model. These data include the root system architecture, the soil hydraulic properties and the environmental conditions (initial soil water content and boundary conditions, BC). Root hydraulic properties were not acquired experimentally, but set to theoretical values found in the literature. In order to validate the results obtained by the model, the simulated and experimental water content distributions were compared. The model was then used to estimate variables that were not experimentally accessible, such as the actual root water uptake distribution and xylem water potential.
42 | Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform.
2022 | LaRue T, Lindner H, Srinivas A, Exposito-Alonso M, Lobet G, Dinneny J
Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform.
The plant kingdom contains a stunning array of complex morphologies easily observed above ground, but largely unexplored belowground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental to determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLORoots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil grown Arabidopsis thaliana plants from germination to maturity. In this study, we present the automation of GLORoots using robotics and the development of image analysis pipelines in order to examine the natural variation of RSA in Arabidopsis over time. This dataset describes the developmental dynamics of 93 accessions and reveals highly complex and polygenic RSA traits that show significant correlation with climate variables.
41 | Évaluations par Cartes Conceptuelles à trous et apprentissage par les pairs
2021 | Guisset M, Coertjens L, De Jaeger D, Lobet G, Servais O, Wertz V, Willems P, Rees JF
Évaluations par Cartes Conceptuelles à trous et apprentissage par les pairs
Cet article décrit un nouveau dispositif d’évaluation des acquis d’apprentissage basé sur des cartes conceptuelles « à trous » (CCàT) permettant également l’apprentissage par les pairs en grands auditoires durant les tests et une correction automatisée par des formulaires QCM. L’intérêt du dispositif est de garantir une évaluation qualitative (à haut niveau taxonomique) des apprentissages tout en facilitant la conception et la correction de ces évaluations par l’enseignant, même pour de grands groupes d’étudiants (>500) et en favorisant la coopération entre étudiants en amont et pendant les évaluations.
40 | Evidence for a multicellular symplasmic water pumping mechanism across vascular plant roots
2021 | Couvreur C, Heymans A, Lobet G, Draye X
Evidence for a multicellular symplasmic water pumping mechanism across vascular plant roots
With global warming, climate zones are projected to shift poleward, and the frequency and intensity of droughts to increase, driving threats to crop production and ecosystems. Plant hydraulic traits play major roles in coping with such droughts, and process-based plant hydraulics (water flowing along decreasing pressure Psip or total water potential Psitot gradients) has newly been implemented in land surface models. An enigma reported for the past 35 years is the observation of water flowing along increasing water potential gradients across roots. By combining the most advanced modelling tool from the emerging field of plant microhydrology with pioneering cell solute mapping data, we found that the current paradigm of water flow across roots of all vascular plants is incomplete. It lacks the impact of solute concentration (and thus negative osmotic potential Psio) gradients across living cells. This gradient acts as a water pump as it reduces water tension without loading solutes in plant vasculature (xylem). Importantly, water tension adjustments in roots may have large impacts in leaves due to the tension cavitation feedback along stems. Here, we mathematically demonstrate the water pumping mechanism by solving water flow equations analytically on a triple cell system. Then we show that the simplistic upscaled equations hold in 2 and 3D maize, grapevine and Arabidopsis complex hydraulic anatomies, and that water may flow “uphill” of water potential gradients toward xylem as observed experimentally. Besides its contribution to the fundamental understanding of plant water relations, this study lays new foundations for future multidisciplinary research encompassing plant physiology and ecohydrology, and has the ambition to mathematically capture a keystone process for the accurate forecasting of plant water status in crop models and LSMs.
39 | Combining cross section images and modeling tools to create high resolution root system hydraulic atlases in Zea mays
2020 | Heymans A, Couvreur C, Lobet G
Combining cross section images and modeling tools to create high resolution root system hydraulic atlases in Zea mays
Root hydraulic properties play a central role in the global water cycle, agricultural systems productivity, and ecosystem survival as they impact the global canopy water supply. However, the available experimental methods to quantify root hydraulic conductivities, such as the root pressure probing, are particularly challenging and their applicability on thin roots and small root segments is limited. There is a gap in methods enabling easy estimations of root hydraulic conductivities across a diversity of root types and at high resolution along root axes. In this case study, we analysed Zea mays (maize) plants of the var. B73 that were grown in pots for 14 days. Root cross-section data were used to extract anatomical measurements. We used the Generator of Root Anatomy in R (GRANAR) model to generate root anatomical networks from anatomical features. Then we used the Model of Explicit Cross section Hydraulic Anatomy (MECHA) to compute an estimation of the root axial and radial hydraulic conductivities (kx and kr, respectively), based on the generated anatomical networks and cell hydraulic properties from the literature. The root hydraulic conductivity maps obtained from the root cross-sections suggest significant functional variations along and between different root types. Predicted variations of kr along the root axis were strongly dependent on the maturation stage of hydrophobic barriers. The same was also true for the maturation rates of the metaxylem. The different anatomical features, as well as their evolution along the root type add significant variation to the kr estimation in between root type and along the root axe. Under the prism of root types, anatomy, and hydrophobic barriers, our results highlight the diversity of root radial and axial hydraulic conductivities, which may be veiled under low resolution measurements of the root system hydraulic conductivity. While predictions of our root hydraulic maps match the range and trend of measurements reported in the literature, future studies could focus on the quantitative validation of hydraulic maps. From now on, a novel method, which turns root cross section images into hydraulic maps will offer an inexpensive and easily applicable investigation tool for root hydraulics, in parallel to root pressure probing experiments.
38 | QuoVidi, an open-source web application for the organisation of large scale biological treasure hunts
2020 | Lobet G, Descamps C, Leveau L, Guillet A, Rees JF
QuoVidi, an open-source web application for the organisation of large scale biological treasure hunts
Learning biology, and in particular systematics, requires learning a substantial amount of specific vocabulary, both for botanical and zoological studies. While crucial, the precise identification of structures serving as evolutionary traits and systematic criteria is not per se a highly motivating task for students. Teaching this in a traditional teaching setting is quite challenging especially with a large crowd of students to be kept engaged. This is even more difficult if, as during the COVID-19 crisis, students are not allowed to access laboratories for hands-on observation on fresh specimens and sometimes restricted to short-range movements outside their home. Here we present QuoVidi, a new open-source web platform for the organisation of large scale treasure hunts. The platform works as follows: students, organised in teams, receive a list of quests that contain morphologic, ecologic or systematic terms. They have to first understand the meaning of the quest, then go and find them in the environment. Once they find the organism corresponding to a quest, they upload a geotagged picture of their find and submit this on the platform. The correctness of each submission is evaluated by the staff. During the COVID-19 lockdown, previously validated pictures were also submitted for evaluation to students that were locked in low-biodiversity areas. From a research perspective, the system enables the creation of large image databases by the students, similar to citizen-science projects. Beside the enhanced motivation of students to learn the vocabulary and perform observations on self-found specimens, this system allows faculties to remotely follow and assess the work performed by large numbers of students. The interface is freely available, open source and customizable. It can be used in other disciplines with adapted quests and we expect it to be of interest in many classroom settings.
37 | Value of sun-induced chlorophyll fluorescence for quantifying hydrological states and fluxes. Current status and challenges
2020 | Jonard F, De Cannière S, Brüggeman N, Gentine P, Gianottid DJS, Lobet G, Miralles D, Montzka C, Pagán BR, Rascher U, Vereecken H
Value of sun-induced chlorophyll fluorescence for quantifying hydrological states and fluxes. Current status and challenges
Predictions of hydrological states and fluxes, especially transpiration, are poorly constrained in hydrological models due to large uncertainties in parameterization and process description. Novel technologies like remote sensing of sun induced chlorophyll fluorescence (SIF), which provides information from the photosynthetic apparatus, may help in constraining water cycle components. This paper discusses the nature of the plant physiological basis of the fluorescence signal and analyses the current literature linking hydrological states and fluxes to SIF. Given the connection between photosynthesis and transpiration, through the water use efficiency, SIF may serve as a pertinent constraint for hydrological models. The FLuorescence EXplorer (FLEX) satellite, planned to be launched in 2023, is expected to provide spatially high resolution measurements of red and far red SIF complementing the products from existing satellite missions and the high temporal resolution products from upcoming geostationary missions. This new data stream may allow us to better constrain plant transpiration, assess the impacts of water stress on plants, and infer processes occurring in the root zone through the soil plant water column. To make optimal use of this data, progress needs to be made in 1) our process representation of spatially aggregated fluorescence signals from spaceborne SIF instruments, 2) integration of fluorescence processes in hydrological models—particularly when paired with other satellite data, 3) quantifying the impact of soil moisture on SIF across scales, and 4) assessment of the accuracy of SIF measurements—especially from space.
36 | Collaborative benchmarking of functional-structural root architecture models. The case of root water uptake.
2020 | Schnepf A, Black CK, Couvreur V, Delory BM, Doussan C, Koch A, Koch T, Javaux M, Landl M, Leitner D, Lobet G, Mai TH, Meunier F, Petrich L, Postma JA, Priesack E, Schmidt V, Vanderborght J, Vereecken H, Weber M
Collaborative benchmarking of functional-structural root architecture models. The case of root water uptake.
Three-dimensional models of root growth, architecture and function are becoming important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common in many disciplines that use numerical models such as natural and engineering sciences, functional-structural root architecture models have never been systematically compared. The following reasons might induce disagreement between the simulation results of different models: different representation of root growth, sink term of root water and solute uptake and representation of the rhizosphere. Presently, the extent of discrepancies is unknown, and a framework for quantitatively comparing functional-structural root architecture models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of complex models: root architecture, water flow in soil and water flow in roots. While the latter two will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore defining common inputs that allow recreating reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled problems are defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. This benchmarking will result in a better understanding of the different models and contribute towards improving them. Improved models will allow us to simulate various scenarios with greater confidence and avoid bugs, numerical errors or conceptual misunderstandings. This work will set a standard for future model development.
35 | CPlantBox, a whole plant modelling framework for the simulation of water and carbon related processes
2020 | Zhou X, Schnepf A, Vanderborght J, Leitner D, Lacointe A, Vereecken H, Lobet G
CPlantBox, a whole plant modelling framework for the simulation of water and carbon related processes
The interaction between carbon and flows within the plant is at the center of most growth and developmental processes. Understanding how these fluxes influence each other, and how they respond to heterogeneous environmental conditions, is important to answer diverse questions in forest, agriculture and environmental sciences. However, due to the high complexity of the plant environment system, specific tools are needed to perform such quantitative analyses.Here we present CPlantBox, full plant modelling framework based on the root system model CRootBox. CPlantbox is capable of simulating the growth and development of a variety of plant architectures (root and shoot). In addition, the flexibility of CPlantBox enables its coupling with external modeling tools. Here, we connected it to an existing mechanistic model of water and carbon flows in the plant, PiafMunch.The usefulness of the CPlantBox modelling framework is exemplified in four case studies. Firstly, we illustrate the range of plant structures that can be simulated using CPlantBox. In the second example, we simulated diurnal carbon and water flows, which corroborates published experimental data. In the third case study, we simulated impacts of heterogeneous environment on carbon and water flows. Finally, we showed that our modelling framework can be used to fit phloem pressure and flow speed to (published) experimental data. The CPlantBox modelling framework is open-source, highly accessible and flexible. Its aim is to provide a quantitative framework for the understanding of plant-environment interaction.
34 | GRANAR, a new computational tool to better understand the functional importance of root anatomy
2020 | Heymans A, Couvreur V, Larue T, Paez Garcia A, Lobet G
GRANAR, a new computational tool to better understand the functional importance of root anatomy
Root hydraulic conductivity is an important determinant of plant water uptake capacity. In particular, the root radial conductivity is often thought to be a limiting factor along the water pathways between the soil and the leaf. The root radial conductivity is itself defined by cell scale hydraulic properties and anatomical features. However, quantifying the influence of anatomical features on the radial conductivity remains challenging due to complex, and time-consuming, experimental procedures. We present a new computation tool, the Generator of Root ANAtomy in R (GRANAR) that can be used to rapidly generate digital versions of root anatomical networks. GRANAR uses a limited set of root anatomical parameters, easily acquired with existing image analysis tools. The generated anatomical network can then be used in combination with hydraulic models to estimate the corresponding hydraulic properties. We used GRANAR to re-analyse large maize (Zea mays) anatomical datasets from the literature. Our model was successful at creating virtual anatomies for each experimental observation. We also used GRANAR to generate anatomies not observed experimentally, over wider ranges of anatomical parameters. The generated anatomies were then used to estimate the corresponding radial conductivities with the hydraulic model MECHA. This enabled us to quantify the effect of individual anatomical features on the root radial conductivity. In particular, our simulations highlight the large importance of the width of the stele and the cortex. GRANAR is an open-source project available here: http://granar.github.io .
33 | MARSHAL, a novel tool for virtual phenotyping of maize root system hydraulic architectures
2020 | Meunier F, Heymans A, Draye X,Couvreur V, Lobet G, Javaux M
MARSHAL, a novel tool for virtual phenotyping of maize root system hydraulic architectures
Functional-structural root system models combine functional and structural root traits to represent the growth and development of root systems. In general, they are characterized by a large number of growth, architectural and functional root parameters, generating contrasted root systems evolving in a highly nonlinear environment (soil, atmosphere), which makes unclear what impact of each single root system on root system functioning actually is. On the other end of the root system modelling continuum, macroscopic root system models associate to each root system instance a set of plant-scale, easily interpretable parameters. However, as of today, it is unclear how these macroscopic parameters relate to root-scale traits and whether the upscaling of local root traits are compatible with macroscopic parameter measurements. The aim of this study was to bridge the gap between these two modelling approaches by providing a fast and reliable tool, which eventually can help performing plant virtual breeding. We describe here the MAize Root System Hydraulic Architecture soLver (MARSHAL), a new efficient and user-friendly computational tool that couples a root architecture model (CRootBox) with fast and accurate algorithms of water flow through hydraulic architectures and plant-scale parameter calculations, and a review of architectural and hydraulic parameters of maize. To illustrate the tool's potential, we generated contrasted maize hydraulic architectures that we compared with architectural (root length density) and hydraulic (root system conductance) observations. Observed variability of these traits was well captured by model ensemble runs We also analyzed the multivariate sensitivity of mature root system conductance, mean depth of uptake, root system volume and convex hull to the input parameters to highlight the key parameters to vary for efficient virtual root system breeding. MARSHAL enables inverse optimisations, sensitivity analyses and virtual breeding of maize hydraulic root architecture. It is available as an R package, an RMarkdown pipeline, and a web application.
32 | Lateral Roots, Random Diversity in Adversity
2019 | Muller B, Guédon Y, Passot S, Lobet G, Nacry P, Pagès L, Wissuwa M, Draye X
Lateral roots are essential for soil foraging and uptake of minerals and water. They feature a large morphological diversity that results from divergent primordia or root growth and development patterns. Besides a structured diversity, resulting from the hierarchical and developmental organization of root systems, there exists a random diversity, occurring between roots of similar age, of the same hierarchical order, and exposed to uniform conditions. The physiological bases and functional consequences of this random diversity are largely ignored. Here we review the evidence for such random diversity throughout the plant kingdom, present innovative approaches based on statistical modeling to account for such diversity, and set the list of its potential benefits in front of a variable and unpredictable soil environment.
31 | Accuracy of image analysis tools for functional root traits. A comment on Delory et al., 2017
2019 | Rose L,Lobet G
Accuracy of image analysis tools for functional root traits. A comment on Delory et al., 2017
Root traits get increasing attention as functional equivalents of aboveground traits. Image analysis software such as WinRhizo and IJRhizo facilitate root trait analyses. Delory et al., 2017 presented a comparison between the accuracy of WinRhizo and IJRhizo for measuring root length. We complement their analyses with a comparison of diameter and volume estimates and a comparison of different image resolutions with manual and automatic threshold. We analysed 100 images of fibrous and taproot systems, which were obtained by using the root model ArchiSimple. As a result, for each image, diameter, length and volume were known. The images were analysed with WinRhizo and IJRhizo and we compared the estimates of diameter, length, and volume to groundtruth values. We further computed relative errors and their magnitude and analysed their dependency on image characteristics and root system properties. At 1200 and 800 dpi, diameter and length estimates provided by WinRhizo and IJRhizo were of comparable accuracy. Diameter errors were balanced. Volume estimates were subjected to a systematic error caused by the assumption of constant diameter. WinRhizo, however, provides the opportunity to calculate correctly computed volumes from diameter classes. At 1200 dpi, IJRhizo failed to automatically find an appropriate threshold for pixel classification, which fundamentally decreased accuracy. The magnitude of diameter errors increased with root overlap for IJRhizo. The length errors increased with increasing root length, overlap and root length density for WinRhizo. The magnitude of underestimation of the volume (WinRhizo) decreased with volume. It was higher for taproot than for fibrous root systems. All errors increased with lower resolution. Our results confirm the results of Delory et al., 2017 regarding the accuracy for length. They further confirm that estimates derived from different software packages or at different resolution should not be compared directly. The characteristics of root systems should be standardized for image analysis. The dependency of errors on the response variable of interest can influence the effect size and increase the probability of errors. Validation of methods should be conducted for each analysed dataset. New image analysis tools should be validated against a real groundtruth.
30 | Going with the flow. Multiscale insights into the composite nature of water transport in roots
2018 | Couvreur V, Faget M, Lobet G, Javaux M, Chaumont F, Draye X
Going with the flow. Multiscale insights into the composite nature of water transport in roots
As water often limits crop production, a more complete understanding of plant water capture and transport is necessary. Here, we developed MECHA, a mathematical model that computes the flow of water across the root at the scale of walls, membranes, and plasmodesmata of individual cells, and used it to test hypotheses related to root water transport in maize (Zea mays). The model uses detailed root anatomical descriptions and a minimal set of experimental cell properties, including the conductivity of plasma membranes (Lp), cell walls, and plasmodesmata, which yield quantitative and scale consistent estimations of water pathways and root radial hydraulic conductivity (kr). MECHA revealed that the mainstream hydraulic theories derived independently at the cell and root segment scales are compatible only if osmotic potentials within the apoplastic domains are uniform. Results suggested that the convection-diffusion of apoplastic solutes explained most of the offset between estimated kr in pressure clamp and osmotic experiments, while the contribution of water-filled intercellular spaces was limited. Furthermore, sensitivity analyses quantified the relative impact of cortex and endodermis cell Lp on root kr and suggested that only the latter substantially contributed to kr due to the composite nature of water flow across roots. The explicit root hydraulic anatomy framework brings insights into contradictory interpretations of experiments from the literature and suggests experiments to efficiently address questions pertaining to root water relations. Its scale-consistency opens avenues for cross-scale communication in the world of root hydraulics.
We made a shiny app as companion for the paper. It is available here: [https://plantmodelling.shinyapps.io/mecha/]()
29 | Connecting the dots between computational tools to analyse soil-root water relations
2018 | Passot S, Couvreur C, Meunier F, Draye X, Javaux M, Leitner D, Pagès L, Schnepf A, Vanderborght J, Lobet G
Connecting the dots between computational tools to analyse soil-root water relations
In the recent years, many computational tools, such as image analysis, data management, process-based simulation and upscaling tools, were developed to help quantify and understand water flow in the soil-root system, at multiple scales (tissue, organ, plant and population). Several of these tools work together or, at least, are compatible. However, for the un-informed researcher, they might seem disconnected, forming a unclear and disorganised succession of tools. In this article, we present how different pieces of work can be further developed by connecting them to analyse soil-root-water relations in a comprehensive and structured network. This explicit network of soil-root computational tools informs the reader about existing tools and help them understand how their data (past and future) might fit within the network. We also demonstrate the novel possibilities of scale-consistent parameterizations made possible by the network with a set of case studies from the literature. Finally, we discuss existing gaps in the network and how we can move forward to fill them.
We made a shiny app as companion for the paper. It is available here: [https://plantmodelling.shinyapps.io/water_network/]()
28 | Demystifying roots, A need for clarification and extended concepts in root phenotyping
2018 | Lobet G, Paez-Garcia A, Schneider H, Junker A, Atkinson J, Tracy S
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.
27 | EZ-Root-VIS, A Software Pipeline for the Visual Reconstruction of Averaged Root System Architecture
2018 | Shahzad Z, Kellermeier F, Armstrong E, Rogers S, Lobet G, Hills , Amtmann A
EZ-Root-VIS, A Software Pipeline for the Visual Reconstruction of Averaged Root System Architecture
If we want to understand how the environment has shaped the appearance and behavior of living creatures we need to compare groups of individuals that differ in genetic make-up and environment experience. For complex phenotypic features, such as body posture or facial expression in humans, comparison is not straightforward because some of the contributing factors cannot easily be quantified or averaged across individuals. Therefore computational methods are used to reconstruct representative prototypes using a range of algorithms for filling in missing information and calculating means. The same problem applies to the root system architecture (RSA) of plants. Several computer programs are available for extracting numerical data from root images but they usually do not offer customized data analysis or visual reconstruction of RSA. We have developed Root-VIS, a free software tool, which facilitates the determination of means and variance of many different RSA features across user-selected sets of root images. Furthermore, Root-VIS offers several options to generate visual reconstructions of root systems from the averaged data to enable screening and modelling. We have confirmed the suitability of Root-VIS, combined with a new version of EZ-Rhizo, for the rapid characterization of genotype-environment interactions and gene discovery through genome-wide association studies in Arabidopsis.
26 | Impact of crop residue management on crop production and soil chemistry after seven years of crop rotation in temperate climate, loamy soils
2018 | Hiel MP, Barbieux S, Pierreux J, Olivier C, Lobet G, Roisin C, Garré S, Colinet G, Bodson B, Dumont B
Impact of crop residue management on crop production and soil chemistry after seven years of crop rotation in temperate climate, loamy soils
Society is increasingly demanding a more sustainable management of agro-ecosystems in a context of climate change and an ever growing global population. The fate of crop residues is one of the important management aspects under debate, since it represents an unneglectable quantity of organic matter which can be kept in or removed from the agro-ecosystem. The topic of residue management is not new, but the need for global conclusion on the impact of crop residue management on the agro-ecosystem linked to local pedo-climatic conditions has become apparent with an increasing amount of studies showing a diversity of conclusions. This study specifically focusses on temperate climate and loamy soil using a seven-year data set. Between 2008 and 2016, we compared four contrasting residue management strategies differing in the amount of crop residues returned to the soil (incorporation vs. exportation of residues) and in the type of tillage (reduced tillage (10 cm depth) vs. conventional tillage (ploughing at 25 cm depth)) in a field experiment. We assessed the impact of the crop residue management on crop production (three crops—winter wheat, faba bean and maize—cultivated over six cropping seasons), soil organic carbon content, nitrate (NO3), phosphorus (P) and potassium (K) soil content and uptake by the crops. The main differences came primarily from the tillage practice and less from the restitution or removal of residues. All years and crops combined, conventional tillage resulted in a yield advantage of 3.4% as compared to reduced tillage, which can be partly explained by a lower germination rate observed under reduced tillage, especially during drier years. On average, only small differences were observed for total organic carbon (TOC) content of the soil, but reduced tillage resulted in a very clear stratification of TOC and also of P and K content as compared to conventional tillage. We observed no effect of residue management on the NO3 content, since the effect of fertilization dominated the effect of residue management. To confirm the results and enhance early tendencies, we believe that the experiment should be followed up in the future to observe whether more consistent changes in the whole agro-ecosystem functioning are present on the long term when managing residues with contrasted strategies.
25 | A New Phenotyping Pipeline Reveals Three Types of Lateral Roots and a Random Branching Pattern in Two Cereals
2018 | Passot S, Moreno-Ortega B, Moukouanga D, Balsera C, GUYOMARC'H S, Lucas M, Lobet G, Laplaze L, Muller B, Guédon Y
A New Phenotyping Pipeline Reveals Three Types of Lateral Roots and a Random Branching Pattern in Two Cereals
Recent progresses in root phenotyping focused mainly on increasing throughput for genetic studies while the identification of root developmental patterns has been comparatively underexplored. We introduce a new phenotyping pipeline for producing high-quality spatio-temporal root system development data and identifying developmental patterns within these data. This pipeline combining the SmartRoot image analysis system with temporal and spatial statistical models was applied to two cereals, pearl millet and maize. Semi-Markov switching linear models were used to cluster lateral roots based on their growth rate profiles. These models revealed three types of lateral roots with similar characteristics in both species. A first type corresponds to fast and accelerating roots, a second to rapidly arrested roots and a third to an intermediate type where roots cease elongation after a few days. These types were retrieved in different proportions in a maize mutant affected in auxin signaling while the most vigorous type was absent in maize plants exposed to severe shading. High correlations between these lateral root types and anatomical traits were found in pearl millet. Potential dependencies in the succession of lateral root types along the primary root were then analyzed using variable-order Markov chains. The lateral root type was neither influenced by the shootward neighbor root type nor by the distance from this root. This random branching pattern of primary roots was remarkably conserved despite the high variability of root systems in both species. Our pipeline opens the door to an exploration of the genetic variability of lateral root developmental patterns.
24 | CRootBox, A Structural-Functional Modelling Framework For Root Systems
2018 | Schnepf A, Leitner D, Landl M, Lobet G, Hieu Mai T, Morandage S, Sheng C, Zoerner M, Vanderborght J, Vereecken H
CRootBox, A Structural-Functional Modelling Framework For Root Systems
Root architecture development determines the sites in soil where roots provide input of carbon and take up water and solutes. However, root architecture is difficult to determine experimentally when grown in opaque soil. Thus, root architectural models have been widely used and been further developed into functional-structural models that simulate the fate of water and solutes in the soil-root system. We present a root architectural model, CRootBox, as a flexible framework to model architecture and its interactions with static and dynamic soil environments. CRootBox is a C++-based root architecture model with Python binding, so that CRootBox can be included via a shared library into any Python code. Output formats include VTP, DGF, RSML and CSV. We further created a database of published root architectural parameters. The capabilities of CRootBox for the unconfined growth of single root systems, as well as the different parameter sets, are highlighted into a freely available web application. We demonstrate the use of CRootBox for 5 different cases (1) free growth of individual root systems (2) growth of root systems in containers as a way to mimic experimental setups, (3), field scale simulation, (4) root growth as affected by heterogeneous, static soil conditions, and (5) coupling CRootBox with Soil Physics with Python code to dynamically compute water flow in soil, root water uptake, and water flow inside roots. In conclusion, we present a fast and flexible functional-structural root model which is based on state-of-the-art computational science methods. Its aim is to facilitate modelling of root responses to environmental conditions as well as the impact of root on soil. In the future, we plan to extend this approach to the aboveground part of the plant.
23 | Measuring root system traits of wheat in 2D images to parameterize 3D root architecture models
2018 | Landl M, Schnepf A, Vanderborght J, Bengough G, Bauke S, Lobet G, Bol R, Vereecken H
Measuring root system traits of wheat in 2D images to parameterize 3D root architecture models
The main difficulty in the use of 3D root architecture models is correct parameterization. We evaluated distributions of the root traits inter-branch distance, branching angle and axial root trajectories from contrasting experimental systems to improve model parameterization.. We analyzed 2D root images of different wheat varieties (Triticum Aestivum) from three different sources using automatic root tracking. Model input parameters and common parameter patterns were identified from extracted root system coordinates. Simulation studies were used to (1) link observed axial root trajectories with model input parameters (2) evaluate errors due to the 2D (versus 3D) nature of image sources and (3) investigate the effect of model parameter distributions on root foraging performance. Distributions of inter-branch distances were approximated with lognormal functions. Branching angles showed mean values <90°. Gravitropism and tortuosity parameters were quantified in relation to downwards reorientation and segment angles of root axes. Root system projection in 2D increased the variance of branching angles. Root foraging performance was very sensitive to parameter distribution and variance. Conclusions 2D image analysis can systematically and efficiently analyze root system architectures and parameterize 3D root architecture models. Effects of root system projection (2D from 3D) and deflection (at rhizotron face) on size and distribution of particular parameters are potentially significant
22 | archiDART v3.0, A new data analysis pipeline allowing the topological analysis of plant root systems
2018 | Delory B, Li M, Topp C, Lobet G
archiDART v3.0, A new data analysis pipeline allowing the topological analysis of plant root systems
Quantifying plant morphology is a very challenging task that requires methods able to capture the geometry and topology of plant organs at various spatial scales. Recently, the use of persistent homology as a mathematical framework to quantify plant morphology has been successfully demonstrated for leaves, shoots, and root systems. In this paper, we present a new data analysis pipeline implemented in the R package archiDART to analyse root system architectures using persistent homology. In addition, we also show that both geometric and topological descriptors are necessary to accurately compare root systems and assess their natural complexity.
Currently, the worldwide root research community is growing and becoming more active than ever. In the past few years, researchers have combined the latest technologies to image and quantify root systems (e.g., digital photography, x-ray computed tomography, transparent soils, high-throughput 3D reconstructions, or fluorescence-based imaging systems), generating an exciting landscape of new research strategies. In addition, recent collaborative efforts have led to the design of a common language for the description and storage of root architecture information. These technological innovations and robust standards have ushered in a new era in root research, namely, root phenomics. Phenomics is the scientific discipline concerned with the measure and study of phenotypes (physical form and function). Here, we will review the most recent advances in the phenomics of root system architecture and provide a comprehensive introduction to computational approaches that are becoming the new standards in root research.
This paper is part of the serie *Teaching Tools in Plant Biology* by The Plant Cell journal.
20 | Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies
2017 | Atkinson J*, Lobet G*, Noll M, Meyer P, Griffiths M, Wells D
Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies
Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify Quantitative Trait Loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large scale root studies. We expect that such an approach will enable the quantification ofmore complex root systems for genetic studies. We also believe that our approach could be extended to other areasof plant phenotyping
19 | Image analysis in plant science. Publish then perish
2017 | Lobet G
Image analysis in plant science. Publish then perish
Image analysis has become a powerful technique for most plant scientists. In recent years dozens of image analysis tools have been published in plant science journals. These tools cover the full spectrum of plant scales, from single cells to organs and canopies. However, the field of plant image analysis remains in its infancy. It still has to overcome important challenges, such as the lack of robust validation practices or the absence of long-term support. In this Opinion article, I: (i) present the current state of the field, based on data from the plant-image-analysis.org database; (ii) identify the challenges faced by its community; and (iii) propose workable ways of improvement.
The review made the cover of Trends in Plant Science in June 2017.
18 | An evaluation of inexpensive methods for root image acquisition when using rhizotrons
2017 | Mohamed A, Monnier Y, Mao Z, Lobet G, Maeght J-L, Ramel M, Stokes A
An evaluation of inexpensive methods for root image acquisition when using rhizotrons
Belowground processes play an essential role in ecosystem nutrient cycling and the global carbon budget cycle. Quantifying fine root growth is crucial to the understanding of ecosystem structure and function and in predicting how ecosystems respond to climate variability. A better understanding of root system growth is necessary, but choosing the best method of observation is complex, especially in the natural soil environment. Here, we compare five methods of root image acquisition using inexpensive technology that is currently available on the market: flatbed scanner, handheld scanner, manual tracing, a smartphone application scanner and a time-lapse camera. Using the five methods, root elongation rate (RER) was measured for three months, on roots of hybrid walnut (Juglans nigra × Juglans regia L.) in rhizotrons installed in agroforests. When all methods were compared together, there were no significant differences in relative cumulative root length. However, the time-lapse camera and the manual tracing method significantly overestimated the relative mean diameter of roots compared to the three scanning methods. The smartphone scanning application was found to perform best overall when considering image quality and ease of use in the field. The automatic time-lapse camera was useful for measuring RER over several months without any human intervention. Our results show that inexpensive scanning and automated methods provide correct measurements of root elongation and length (but not diameter when using the time-lapse camera). These methods are capable of detecting fine roots to a diameter of 0.1 mm and can therefore be selected by the user depending on the data required.
17 | Using a structural root system model to evaluate and improve the accuracy of root image analysis pipelines
2017 | Lobet G, Koevoets I, Tocquin P, Pagès L, Périlleux C
Using a structural root system model to evaluate and improve the accuracy of root image analysis pipelines
Root system analysis is a complex task, often performed with fully automated image analysis pipelines. However, the outcome is rarely verified by ground-truth data, which might lead to underestimated biases. We have used a root model, ArchiSimple, to create a large and diverse library of ground-truth root system images (10,000). For each image, three levels of noise were created. This library was used to evaluate the accuracy and usefulness of several image descriptors classically used in root image analysis softwares. Our analysis highlighted that the accuracy of the different traits is strongly dependent on the quality of the images and the type, size, and complexity of the root systems analyzed. Our study also demonstrated that machine learning algorithms can be trained on a synthetic library to improve the estimation of several root system traits. Overall, our analysis is a call to caution when using automatic root image analysis tools. If a thorough calibration is not performed on the dataset of interest, unexpected errors might arise, especially for large and complex root images. To facilitate such calibration, both the image library and the different codes used in the study have been made available to the community.
Molecular data concerning the involvement of roots in the genetic pathways regulating floral transition are lacking. In this study, we performed global analyses of the root transcriptome in Arabidopsis in order to identify flowering time genes that are expressed in the roots and genes that are differentially expressed in the roots during the induction of flowering. Data mining of public microarray experiments uncovered that about 200 genes whose mutations are reported to alter flowering time are expressed in the roots (i.e. were detected in more than 50% of the microarrays). However, only a few flowering integrator genes passed the analysis cutoff. Comparison of root transcriptome in short days and during synchronized induction of flowering by a single 22-h long day revealed that 595 genes were differentially expressed. Enrichment analyses of differentially expressed genes in root tissues, gene ontology categories, and cis-regulatory elements converged towards sugar signaling. We concluded that roots are integrated in systemic signaling, whereby carbon supply coordinates growth at the whole plant level during the induction of flowering. This coordination could involve the root circadian clock and cytokinin biosynthesis as a feed forward loop towards the shoot.
15 | Environmental Control of Root System Biology
2016 | Rellan-Alvarez R*, Lobet G*, Dinneny J
The plant root system traverses one of the most complex environments on earth. Understanding how roots support plant life on land requires knowing how soil properties affect the availability of nutrients and water and how roots manipulate the soil environment to optimize acquisition of these resources. Imaging of roots in soil allows the integrated analysis and modeling of environmental interactions occurring at micro- to macroscales. Advances in phenotyping of root systems is driving innovation in cross-platformcompatible methods for data analysis. Root systems acclimate to the environment through architectural changes that act at the root-type level as well as through tissue-specific changes that affect the metabolic needs of the root and the efficiency of nutrient uptake. A molecular understanding of the signaling mechanisms that guide local and systemic signaling is providing insight into the regulatory logic of environmental responses and has identified points where crosstalk between pathways occurs.
14 | FLOR-ID, an interactive database of flowering-time gene networks in Arabidopsis thaliana
2015 | Bouché F*, Lobet G*, Tocquin P, Périlleux C
FLOR-ID, an interactive database of flowering-time gene networks in Arabidopsis thaliana
Flowering is a hot topic in Plant Biology and important progress has been made in Arabidopsis thaliana toward unraveling the genetic networks involved. The increasing complexity and the explosion of literature however require development of new tools for information management and update. We therefore created an evolutive and interactive database of flowering time genes, named FLOR-ID (FloweringInteractive Database), which is freely accessible at http://www.flor-id.org. The hand-curated database contains information on 306 genes and links to 1595 publications gathering the work of >4500 authors. Gene/protein functions and interactions within the flowering pathways were inferred from the analysis of related publications, included in the database and translated into interactive manually drawn snapshots
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). 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. 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.). 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.
12 | GLO-Roots, an imaging platform enabling multidimensional characterization of soil grown root systems
2015 | Rellán-Álvarez R, Lobet G, Hildner H, Pradier PL, Sebastian J, Yee C, Yu G, LaRue T, Trontin C, Nieu R, Vogel J, Dinneny J
GLO-Roots, an imaging platform enabling multidimensional characterization of soil grown root systems
Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.
11 | Root System Markup Language. Toward an unified root architecture description language
2015 | Lobet G, Pound MP, Diener J, Pradal C, Draye X, Godin C, Javaux M, Leitner D, Meunier F, Nacry P, Pridmore TP, Schnepf A
Root System Markup Language. Toward an unified root architecture description language
The number of image analysis tools supporting the extraction of architectural features of root systems has increased in recent years. These tools offer a handy set of complementary facilities, yet it is widely accepted that none of these software tools is able to extract in an efficient way the growing array of static and dynamic features for different types of images and species. We describe the Root System Markup Language (RSML), which has been designed to overcome two major challenges: (1) to enable portability of root architecture data between different software tools in an easy and interoperable manner, allowing seamless collaborative work; and (2) to provide a standard format upon which to base central repositories that will soon arise following the expanding worldwide root phenotyping effort. RSML follows the XML standard to store two- or three-dimensional image metadata, plant and root properties and geometries, continuous functions along individual root paths, and a suite of annotations at the image, plant, or root scale at one or several time points. Plant ontologies are used to describe botanical entities that are relevant at the scale of root system architecture. An XML schema describes the features and constraints of RSML, and open-source packages have been developed in several languages (R, Excel, Java, Python, and C#) to enable researchers to integrate RSML files into popular research workflow.
10 | Rhizoponics, a novel hydroponic rhizotron for root system analyses on mature Arabidopsis thaliana plants
2015 | Mathieu L*, Lobet G*, Tocquin P, Périlleux C
Rhizoponics, a novel hydroponic rhizotron for root system analyses on mature Arabidopsis thaliana plants
Well-developed and functional roots are critical to support plant life and reach high crop yields. Their study however, is hampered by their underground growth and characterizing complex root system architecture (RSA) therefore remains a challenge. In the last few years, several phenotyping methods, including rhizotrons and x-ray computed tomography, have been developed for relatively thick roots. But in the model plant Arabidopsis thaliana, in vitro culture remains the easiest and preferred method to study root development, which technically limits the analyses to young seedlings. We present here an innovative design of hydroponic rhizotrons (rhizoponics) adapted to Arabidopsis thaliana. The setup allows to simultaneously characterize the RSA and shoot development from seedling to adult stages, i.e. from seed to seed. This system offers the advantages of hydroponics such as control of root environment and easy access to the roots for measurements or sampling. Being completely movable and low cost, it can be used in controlled cabinets. We chose the case of cadmium treatment to illustrate potential applications, from cell to organ levels. Rhizoponics makes possible, on the same plants of Arabidopsis, RSA measurements, root sampling and characterization of aerial development up to adult size. It therefore provides a valuable tool for addressing fundamental questions in whole plant physiology.
9 | Inflorescence development in tomato, gene functions within a zigzag model
2014 | Périlleux C*, Lobet G*, Tocquin P
Inflorescence development in tomato, gene functions within a zigzag model
Tomato is a major crop plant and several mutants have been selected for breeding but also for isolating important genes that regulate flowering and sympodial growth. Besides, current research in developmental biology aims at revealing mechanisms that account for diversity in inflorescence architectures. We therefore found timely to review the current knowledge of the genetic control of flowering in tomato and to integrate the emerging network into modeling attempts. We developed a kinetic model of the tomato inflorescence development where each meristem was represented by its “vegetativeness” (V), reflecting its maturation state toward flower initiation. The model followed simple rules: maturation proceeded continuously at the same rate in every meristem (dV); floral transition and floral commitment occurred at threshold levels of V; lateral meristems were initiated with a gain of V (ΔV) relative to the V level of the meristem from which they derived. This last rule created a link between successive meristems and gave to the model its zigzag shape. We next exploited the model to explore the diversity of morphotypes that could be generated by varying dV and ΔV and matched them with existing mutant phenotypes. This approach, focused on the development of the primary inflorescence, allowed us to elaborate on the genetic regulation of the kinetic model of inflorescence development. We propose that the lateral inflorescence meristem fate in tomato is more similar to an immature flower meristem than to the inflorescence meristem of Arabidopsis. In the last part of our paper, we extend our thought to spatial regulators that should be integrated in a next step for unraveling the relationships between the different meristems that participate to sympodial growth.
8 | Plant Water Uptake in Drying Soils
2014 | Lobet G, Couvreur C, Meunier F, Javaux M, Draye X
Over the last decade, investigations on root water uptake have evolved toward a deeper integration of the soil and roots compartment properties, with the goal of improving our understanding of water acquisition from drying soils. This evolution parallels the increasing attention of agronomists to suboptimal crop production environments. Recent results have led to the description of root system architectures that might contribute to deep-water extraction or to water-saving strategies. In addition, the manipulation of root hydraulic properties would provide further opportunities to improve water uptake. However, modeling studies highlight the role of soil hydraulics in the control of water uptake in drying soil and call for integrative soil-plant system approaches.
7 | A modeling approach to determine the importance of dynamic regulation of plant hydraulic conductivities on the water uptake dynamics in the soil-plant-atmosphere system
2014 | Lobet G, Pagès P, Draye X
A modeling approach to determine the importance of dynamic regulation of plant hydraulic conductivities on the water uptake dynamics in the soil-plant-atmosphere system
We present here a new model, PlaNet-Maize, with the purpose of investigating the effect of environmental and endogenous factors on the growth and water relations of the maize plant. This functional–structural plant model (FSPM) encompasses the entire soil-plant-atmosphere continuum with a sub-organ resolution. The model simulates the growth and development of an individual maize plant and the flux of water through the plant structure, from the rhizosphere to the leaf boundary layer. Leaf stomatal conductance and root radial and axial conductivities are considered as functions of local water potential. Finally, a simple carbon allocation rule is included in the model to allow the feedback effect of water deficit on plant growth. The model was successfully used to reproduce experimental plant hydraulic behavior in response to water deficit. The quantitative contribution of leaf conductance and root conductivities were assessed individually and in combination. Our results highlight the importance of regulating hydraulic properties in FSPM as these can strongly modify the water uptake dynamics and lead to emerging water uptake behaviors. The modeling results also indicate that plant hydraulic properties can theoretically be tailored to improve plant water use in challenging environments.
6 | Comparative analysis of Cd and Zn impacts on root distribution and morphology of Lolium perenne and Trifolium repens. Implications for phytostabilization
2014 | Lambrechts T, Lequeue G, Lobet G, Godin B, Bielders CL, Lutts S
Comparative analysis of Cd and Zn impacts on root distribution and morphology of Lolium perenne and Trifolium repens. Implications for phytostabilization
The phytostabilization potential of plants is a direct function of their root systems. An experimental design was developed to investigate the impact of Cd and Zn on the root distribution and morphology of Lolium perenne and Trifolium repens. Seedlings were transplanted into columns filled with washed quartz and irrigated daily with Cd- or Zn-containing nutrient solutions during 1 month. Root biomass, root length density (RLD) and diameter were subsequently quantified as a function of depth. Pot experiments were also performed to quantify metal, lignin and structural polysaccharides concentrations as well as cell viability. Lolium perenne accumulated Cd and Zn in the roots whereas T. repens was unable to restrict heavy metal translocation. Cadmium and Zn reduced rooting depth and RLD but induced thick shoot-borne roots in L. perenne. Cd-induced root swelling was related to lignification occurring in the exodermis and parenchyma of central cylinder. Hemicelluloses and lignin did not play a key role in root metal retention. Cadmium slightly reduced mean root cell viability whereas Zn increased this parameter in comparison to Cd. Even though plant species like Lolium perenne and Trifolium repens may appear suitable for a phytostabilization scheme based on their shoot metal tolerance, exposure to toxic heavy metals drastically impairs their root distribution. This could jeopardize the setting up of phytostabilization trials. The metal-induced alterations of root system properties are clearly metal- and species-specific. At sites polluted with multiple metals, it is therefore recommended to first test their impact on the root system of multiple plant species so as to select the most appropriate species for each site.
5 | Root systems biology, integrative modeling across scales, from gene regulatory networks to the rhizosphere
2013 | Hill K, Porco S, Lobet G, Zappala S, Mooney S, Draye X, Bennett MJ
Root systems biology, integrative modeling across scales, from gene regulatory networks to the rhizosphere
Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment.
4 | An online database for plant image analysis software tools
2013 | Lobet G, Draye X, Périlleux C
An online database for plant image analysis software tools
Recent years have seen an increase in methods for plant phenotyping using image analyses. These methods require new software solutions for data extraction and treatment. These solutions are instrumental in supporting various research pipelines, ranging from the localisation of cellular compounds to the quantification of tree canopies. However, due to the variety of existing tools and the lack of central repository, it is challenging for researchers to identify the software that is best suited for their research. We present an online, manually curated, database referencing more than 90 plant image analysis software solutions. The website, plant-image-analysis.org, presents each software in a uniform and concise manner enabling users to identify the available solutions for their experimental needs. The website also enables user feedback, evaluations and new software submissions. The plant-image-analysis.org database provides an overview of existing plant image analysis software. The aim of such a toolbox is to help users to find solutions, and to provide developers a way to exchange and communicate about their work.
By the end of 2017, the database contained 159 tools. It has been extended to reference plant image datasets (1 800 000 images referenced). It has an average trafic of 10 000 monthly page views.
3 | Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems
2013 | Lobet G, Draye X
Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems
This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1) separate the root system into a small number of large pieces to reduce root overlap, (2) scan these pieces one by one, (3) analyze separate images with a root tracing software and (4) combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns.
2 | A novel image-analysis toolbox enabling quantitative analysis of root system architecture
2011 | Lobet G, Pagès L, Draye X
A novel image-analysis toolbox enabling quantitative analysis of root system architecture
We present in this paper a novel, semiautomated image-analysis software to streamline the quantitative analysis of root growth and architecture of complex root systems. The software combines a vectorial representation of root objects with a powerful tracing algorithm that accommodates a wide range of image sources and quality. The root system is treated as a collection of roots (possibly connected) that are individually represented as parsimonious sets of connected segments. Pixel coordinates and gray level are therefore turned into intuitive biological attributes such as segment diameter and orientation as well as distance to any other segment or topological position. As a consequence, user interaction and data analysis directly operate on biological entities (roots) and are not hampered by the spatially discrete, pixel-based nature of the original image. The software supports a sampling-based analysis of root system images, in which detailed information is collected on a limited number of roots selected by the user according to specific research requirements. The use of the software is illustrated with a time-lapse analysis of cluster root formation in lupin (Lupinus albus) and an architectural analysis of the maize (Zea mays) root system. The software, SmartRoot, is an operating system-independent freeware based on ImageJ and relies on cross-platform standards for communication with data-analysis software.
1 | Model-assisted integration of physiological and environmental constraints affecting the dynamic and spatial patterns of root water uptake from soils
2010 | Draye X, Kim YX, Lobet G, Javaux M
Model-assisted integration of physiological and environmental constraints affecting the dynamic and spatial patterns of root water uptake from soils
Due in part to recent progress in root genetics and genomics, increasing attention is being devoted to root system architecture (RSA) for the improvement of drought tolerance. The focus is generally set on deep roots, expected to improve access to soil water resources during water deficit episodes. Surprisingly, our quantitative understanding of the role of RSA in the uptake of soil water remains extremely limited, which is mainly due to the inherent complexity of the soil–plant continuum. Evidently, there is a need for plant biologists and hydrologists to develop together their understanding of water movement in the soil–plant system. Using recent quantitative models coupling the hydraulic behaviour of soil and roots in an explicit 3D framework, this paper illustrates that the contribution of RSA to root water uptake is hardly separable from the hydraulic properties of the roots and of the soil. It is also argued that the traditional view that either the plant or the soil should be dominating the patterns of water extraction is not generally appropriate for crops growing with a sub-optimal water supply. Hopefully, in silico experiments using this type of model will help explore how water fluxes driven by soil and plant processes affect soil water availability and uptake throughout a growth cycle and will embed the study of RSA within the domains of root hydraulic architecture and sub-surface hydrology.