Modulation of Arabidopsis and monocot root architecture by CLAVATA3/EMBRYO SURROUNDING REGION 26 peptide

Plant roots are important for a wide range of processes, including nutrient and water uptake, anchoring and mechanical support, storage functions, and as the major interface with the soil environment. Several small signalling peptides and receptor kinases have been shown to affect primary root growth, but very little is known about their role in lateral root development. In this context, the CLE family, a group of small signalling peptides that has been shown to affect a wide range of developmental processes, were the focus of this study. Here, the expression pattern during lateral root initiation for several CLE family members is explored and to what extent CLE1, CLE4, CLE7, CLE26, and CLE27, which show specific expression patterns in the root, are involved in regulating root architecture in Arabidopsis thaliana is assessed. Using chemically synthesized peptide variants, it was found that CLE26 plays an important role in regulating A. thaliana root architecture and interacts with auxin signalling. In addition, through alanine scanning and in silico structural modelling, key residues in the CLE26 peptide sequence that affect its activity are pinpointed. Finally, some interesting similarities and differences regarding the role of CLE26 in regulating monocot root architecture are presented

Nitrogen forms affect root structure and water uptake in the hybrid poplar

The study analyses the effects of two different forms of nitrogen fertilisation (nitrate and ammonium) on root structure and water uptake of two hybrid poplar (Populus maximowiczii x P. balsamifera) clones in a field experiment. Water uptake was studied using sap flow gauges on individual proximal roots and coarse root structure was examined by excavating 18 whole-root systems. Finer roots were scanned and analyzed for architecture. Nitrogen forms did not affect coarse-root system development, but had a significant effect on fine-root development. Nitrate-treated trees presented higher fine:coarse root ratios and higher specific root lengths than control or ammonium treated trees. These allocation differences affected the water uptake capacity of the plants as reflected by the higher sapflow rate in the nitrate treatment. The diameter of proximal roots at the tree base predicted well the total root biomass and length. The diameter of smaller lateral roots also predicted the lateral root mass, length, surface area and the number of tips. The effect of nitrogen fertilisation on the fine root structure translated into an effect on the functioning of the fine roots forming a link between form (architecture) and function (water uptake)

Root architecture of provenances, seedlings and cuttings of Melia volkensii: implications for crop yield in dryland agroforestry

Melia volkensii (Gürke) is being increasingly promoted as an on-farm tree in Kenya. Researchers’ and farmers’ views on its competitiveness with crops differ; research station studies have found it to be highly competitive whereas farmers do not consider it to be so. Because of difficulties in seed germination, it is probable that dissemination programmes will rely upon plants produced from root and stem cuttings, rather than on seedlings. This study evaluates differences in root system architecture of plants raised from seed (of four provenances), stem or root cuttings and the relationships between the competitivity index (CI) and crop yield. Cuttings were more shallowly rooting than seedlings, and had higher competitivity indices, and there was a negative relationship between CI and crop yield. No differences in root architecture between provenances were found. Therefore, to reduce tree-crop competition, the use of seedlings rather than cuttings should be recommended when promoting the use of this species on dryland farms. If cuttings are used to circumvent the problems of seed germination, alternative methods of controlling competition, such as root pruning, need to be considered

Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data

The purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system

Phosphate availability regulates root system architecture in Arabidopsis

Plant root systems are highly plastic in their development and can adapt their architecture in response to the prevailing environmental conditions. One important parameter is the availability of phosphate, which is highly immobile in soil such that the arrangement of roots within the soil will profoundly affect the ability of the plant to acquire this essential nutrient. Consistent with this, the availability of phosphate was found to have a marked effect on the root system architecture of Arabidopsis. Low phosphate availability favored lateral root growth over primary root growth, through increased lateral root density and length, and reduced primary root growth mediated by reduced cell elongation. The ability of the root system to respond to phosphate availability was found to be independent of sucrose supply and auxin signaling. In contrast, shoot phosphate status was found to influence the root system architecture response to phosphate availability

DigR : how to model root system in its environment? 1 - the model

Many models already exist through literature dealing with root system representation, among which pure structure models such as Root Typ (Pagès 2004), SimRoot (Lynch 1997), AmapSim (Jourdan 1997); diffusion PDE models (Bastian 2008; Bonneu 2009) and structure/function that are rather scarce and recent (Dupuy 2010)may be aroused. Nevertheless in these studies, root architecture modeling was not carried out at organ level including environmental influence and not designed for integration into a whole plant characterization. We propose here a multidisciplinary study on root system from field observations, architectural analysis, formal and mathematical modeling and finally software simulation. Each speciality is individually investigated through an integrative and coherent approach that leads to a generic model (DigR) and its software simulator that is designed for further integration into a global structure/function plant model. DigR model is based on three main key points: (i) independent root type identification (ii) architectural analysis and modeling of root system at plant level; (iii) root architecture setup indexed on root length. Architecture analysis (Barthelemy 2007) applied to root system (Atger 1994) leads to root type organisation for each species. Roots belonging to a particular type share dynamical and morphological characteristics. Root architectural setup consists in topological features as apical growth, lateral branching, senescence and death, and geometrical features as secondary growth and axes spatial positioning. These features are modeled in DigR through 23 parameters whose values can evolve as a function of length position along the root axes for each root type. Topology rules apical growth speed, delayed growth, death and self pruning probabilities. Branching is characterized by spacing and mixture of lateral root types. Geometry rules root diameter increase, branching and growth directions (including local deviations and global reorientation). DigR simulator provides a user interface to input parameter values specific to each species. It is integrated into the Xplo environment (Taugourdeau 2010). Its internal multi-scale memory representation is ready for dynamical 3D visualization, statistical analysis and saving to standard formats (MTG(Godin 2007), Obj,). DigR is simulated in a quasiparallel computing algorithm and may be used either as a standalone application or integrated in other simulation platforms. This will allow further implementation of functional - structural interactions during growth simulation. The software is distributed under free LGPL license and is dedicated both to biologists and modelers. Shown applications (fig. 1) mimic the diversity of root systems and emphasize the genericity of the model according to different sets of parameter values. Examples (fig. 2) prove that additional knowledge may be plugged to DigR to simulate root plasticity facing environmental constraints. Further work will be carried out to apply DigR to various species and to connect DigR to biophysical soil models (Gérard 2008; Zhang et al. 2002); to aerial part models (Barczi 2008); to ecophysiological models (Mathieu 2009, Bornhoffen 2007); and finally to mix this pure descriptive model to a PDE model that handles fine root diffuse modelling (Bonneu 2009). (Texte intégral

Nitrogen modulation of legume root architecture signaling pathways involves phytohormones and small regulatory molecules

Nitrogen, particularly nitrate is an important yield determinant for crops. However, current agricultural practice with excessive fertilizer usage has detrimental effects on the environment. Therefore, legumes have been suggested as a sustainable alternative for replenishing soil nitrogen. Legumes can uniquely form nitrogen-fixing nodules through symbiotic interaction with specialized soil bacteria. Legumes possess a highly plastic root system which modulates its architecture according to the nitrogen availability in the soil. Understanding how legumes regulate root development in response to nitrogen availability is an important step to improving root architecture. The nitrogen-mediated root development pathway starts with sensing soil nitrogen level followed by subsequent signal transduction pathways involving phytohormones, microRNAs and regulatory peptides that collectively modulate the growth and shape of the root system. This review focuses on the current understanding of nitrogen-mediated legume root architecture including local and systemic regulations by different N-sources and the modulations by phytohormones and small regulatory molecules.Nadiatul A. Mohd-Radzman was supported by ANU International PhD Scholarship. This work was supported by an Australian Research Council grant to Michael A. Djordjevic and Nijat Imin (DP140103714)

Hierarchical Deep Learning Architecture For 10K Objects Classification

Evolution of visual object recognition architectures based on Convolutional Neural Networks & Convolutional Deep Belief Networks paradigms has revolutionized artificial Vision Science. These architectures extract & learn the real world hierarchical visual features utilizing supervised & unsupervised learning approaches respectively. Both the approaches yet cannot scale up realistically to provide recognition for a very large number of objects as high as 10K. We propose a two level hierarchical deep learning architecture inspired by divide & conquer principle that decomposes the large scale recognition architecture into root & leaf level model architectures. Each of the root & leaf level models is trained exclusively to provide superior results than possible by any 1-level deep learning architecture prevalent today. The proposed architecture classifies objects in two steps. In the first step the root level model classifies the object in a high level category. In the second step, the leaf level recognition model for the recognized high level category is selected among all the leaf models. This leaf level model is presented with the same input object image which classifies it in a specific category. Also we propose a blend of leaf level models trained with either supervised or unsupervised learning approaches. Unsupervised learning is suitable whenever labelled data is scarce for the specific leaf level models. Currently the training of leaf level models is in progress; where we have trained 25 out of the total 47 leaf level models as of now. We have trained the leaf models with the best case top-5 error rate of 3.2% on the validation data set for the particular leaf models. Also we demonstrate that the validation error of the leaf level models saturates towards the above mentioned accuracy as the number of epochs are increased to more than sixty.Comment: As appeared in proceedings for CS & IT 2015 - Second International Conference on Computer Science & Engineering (CSEN 2015

Food for thought: how nutrients regulate root system architecture

The spatial arrangement of the plant root system (root system architecture, RSA) is very sensitive to edaphic and endogenous signals that report on the nutrient status of soil and plant. Signalling pathways underpinning RSA responses to individual nutrients, particularly nitrate and phosphate, have been unravelled. Researchers have now started to investigate interactive effects between two or more nutrients on RSA. Several proteins enabling crosstalk between signalling pathways have recently been identified. RSA is potentially an important trait for sustainable and/or marginal agriculture. It is generally assumed that RSA responses are adaptive and optimise nutrient uptake in a given environment, but hard evidence for this paradigm is still sparse. Here we summarize recent advances made in these areas of research

Environmental, developmental, and genetic factors controlling root system architecture

A better understanding of the development and architecture of roots is essential to develop strategies to increase crop yield and optimize agricultural land use. Roots control nutrient and water uptake, provide anchoring and mechanical support and can serve as important storage organs. Root growth and development is under tight genetic control and modulated by developmental cues including plant hormones and the environment. This review focuses on root architecture and its diversity and the role of environment, nutrient, and water as well as plant hormones and their interactions in shaping root architecture