Identifying, naming and interoperating data in a Phenotyping platform network : the good, the bad and the ugly

The EPPN2020 is a research project funded by Horizon 2020 Programme of the EU that will provide European public and private scientific sectors with access to a wide range of state-of-the-art plant phenotyping installations, techniques and methods. Specifically, EPPN2020 includes access to 31 plant phenotyping installations, and joint research activities to develop: novel technologies and methods for environmental and plant measurements.Here we present the results of the discussions of the 2019 annual project meeting to adopt community-approved architectural choices. It focuses on persistent identification of data and real objects, the naming of variables and the priorities for increasing interoperability among phenotyping installations. We describe the main elements to prioritize (the good) in order to enhance Findable, Accessible, Interoperable and Reusable (FAIR) quality for each data management system with a pragmatic concern for all partners. The plant phenotyping community gathers different actors with various means and practices. Among all the recommendations (including the bad: avoiding bad practices), the community requests identification methods (including the use of ontologies) compatible with the ‘local’ pre-existing ones. The identification scheme being adopted is based on Uniform Resource Identifiers (URIs) with independant left and right parts for each identifier. It focuses on the associated objects and variables common to all EPPN2020 members, namely the experimental units (which can be a plant in a pot or a plot), sensors and variables. A common architecture for identifiers and variable names is presented in order to enable a first level of interoperation between information systems.In conclusion, we present some of the next challenges (the ugly) that need to be addressed by the EPPN2020 community related with i) the partial reuse of pre-existing ontologies, ii) the persistence of long-term access to data iii) interoperation between all potential users of the phenotyping data

Modification of the expression of the aquaporin ZmPIP2;5 affects water relations and plant growth

The maize plasma membrane PIP2;5 aquaporin plays a role in controlling root radial water movement, leaf hydraulic conductivity, and plant growth. The plasma membrane intrinsic protein PIP2;5 is the most highly expressed aquaporin in maize (Zea mays) roots. Here, we investigated how deregulation of PIP2;5 expression affects water relations and growth using maize overexpression (OE; B104 inbred) or knockout (KO; W22 inbred) lines. The hydraulic conductivity of the cortex cells of roots grown hydroponically was higher in PIP2;5 OE and lower in pip2;5 KO lines compared with the corresponding wild-type plants. While whole-root conductivity decreased in the KO lines compared to the wild type, no difference was observed in OE plants. This paradox was interpreted using the MECHA hydraulic model, which computes the radial flow of water within root sections. The model hints that the plasma membrane permeability of the cells is not radially uniform but that PIP2;5 may be saturated in cell layers with apoplastic barriers, i.e. the endodermis and exodermis, suggesting the presence of posttranslational mechanisms controlling the abundance of PIP in the plasma membrane in these cells. At the leaf level, where the PIP2;5 gene is weakly expressed in wild-type plants, the hydraulic conductance was higher in the PIP2;5 OE lines compared with the wild-type plants, whereas no difference was observed in the pip2;5 KO lines. The temporal trend of leaf elongation rate, used as a proxy for that of xylem water potential, was faster in PIP2;5 OE plants upon mild stress, but not in well-watered conditions, demonstrating that PIP2;5 may play a beneficial role in plant growth under specific conditions

Xeml Lab: a tool that supports the design of experiments at a graphical interface and generates computer-readable metadata files, which capture information about genotypes, growth conditions, environmental perturbations and sampling strategy

Data mining depends on the ability to access machine-readable metadata that describe genotypes, environmental conditions, and sampling times and strategy. This article presents Xeml Lab. The Xeml Interactive Designer provides an interactive graphical interface at which complex experiments can be designed, and concomitantly generates machine-readable metadata files. It uses a new eXtensible Mark-up Language (XML)-derived dialect termed XEML. Xeml Lab includes a new ontology for environmental conditions, called Xeml Environment Ontology. However, to provide versatility, it is designed to be generic and also accepts other commonly used ontology formats, including OBO and OWL. A review summarizing important environmental conditions that need to be controlled, monitored and captured as metadata is posted in a Wiki (http://www.codeplex.com/ XeO) to promote community discussion. The usefulness of Xeml Lab is illustrated by two meta-analyses of a large set of experiments that were performed with Arabidopsis thaliana during 5 years. The first reveals sources of noise that affect measurements of metabolite levels and enzyme activities. The second shows that Arabidopsis maintains remarkably stable levels of sugars and amino acids across a wide range of photoperiod treatments, and that adjustment of starch turnover and the leaf protein content contribute to this metabolic homeostasis

Acción : diario de Teruel y su provincia: Año III Número 633 - (11/12/34)

New types of phenotyping tools generate large amounts of data on many aspects of plant physiology and morphology with high spatial and temporal resolution. These new phenotyping data are potentially useful to improve understanding and prediction of complex traits, like yield, that are characterized by strong environmental context dependencies, i.e., genotype by environment interactions. For an evaluation of the utility of new phenotyping information, we will look at how this information can be incorporated in different classes of genotype-to-phenotype (G2P) models. G2P models predict phenotypic traits as functions of genotypic and environmental inputs. In the last decade, access to high-density single nucleotide polymorphism markers (SNPs) and sequence information has boosted the development of a class of G2P models called genomic prediction models that predict phenotypes from genome wide marker profiles. The challenge now is to build G2P models that incorporate simultaneously extensive genomic information alongside with new phenotypic information. Beyond the modification of existing G2P models, new G2P paradigms are required. We present candidate G2P models for the integration of genomic and new phenotyping information and illustrate their use in examples. Special attention will be given to the modelling of genotype by environment interactions. The G2P models provide a framework for model based phenotyping and the evaluation of the utility of phenotyping information in the context of breeding programs.</p

Plant phenomics::history, present status and challenges

With the development of remote sensing, robotics, computer vision and artificial intelligence, plant phenomics research has been developing rapidly in recent years. Here, we first introduced a concise history of this research domain, including the theoretical foundation, research methods, biological applications, and the latest progress. Then, we introduced some important indoor and outdoor phenotyping approaches such as handheld devices, ground-based manual and automated vehicles, robotic systems, Internet of Things(IoT)based distributed platforms, automatic deep phenotyping systems, and large-scale aerial phenotyping, together with their advantages and disadvantages during the applications. In order to extract meaningful information from big image-and sensor-based datasets generated by the phenotyping process, we also specified key phenotypic analysis methods and related development procedures. Finally, we discussed the future perspective of plant phenomics, with recommendations of how to apply this research field to breeding, cultivation and agricultural practices in China

Etat structural, enracinement et alimentation hydrique du maïs. III. Disponibilite des reserves en eau du sol

Les variations de stock d’eau du sol, et la conductance stomatique des feuilles supérieures de couverts du maïs¨ ont été mesurés trois années pendant les 6 semaines qui encadrent la floraison. Les mesures ont été effectuées dans des parcelles d’états structuraux contrastés appartenant à un champ expérimental où l’état des parties aériennes et souterraines était par ailleurs suivi. Dans les parcelles où la couche labourée est de structure continue et compacte, les prélèvements d’eau ont été près de 2 fois plus faibles que dans les autres parcelles ; ceci a eu pour conséquence l’apparition (après quelques jours sans pluie) de différences entre traitements de la conductance stomatique, bien que la teneur en eau du sol soit restée en permanence plus élevée dans les parcelles d’état structural défavorable par rapport à celles d’état structural favorable. La mise en correspondance des variations de teneur en eau du sol et des caractéristiques géométriques de l’enracinement montre (1) que ces différences entre traitements de la disponibilité des réserves en eau du sol sont probablement dues à la disposition spatiale des racines et (2) qu’une partie de la variabilité spatiale du dessèchement du sol est liée aux irrégularités de cette disposition.Variations in soil water reserves and stomatal conductance of the upper leaves of maize canopies were monitored for 3 years during the 6-week period around silking. Measurements were carried out in plots of an experimental field where the ploughed layer structure was contrasted, and where root system and top growth were also studied. In compacted plots, water uptake was reduced nearly by half compared with other plots ; as a consequence, stomatal conductance was different between treatments after a few days without rain, although soil water content always remained higher in compacted plots compared with plots having a favourable structure. A correspondence between soil water content variations and the geometrical characteristics of root system showed : (1) that differences between treatments in the availabity of water reserves are probably due to the spatial distribution of roots, and (2) that part of the spatial variability of soil drying is linked with irregularities in this distribution

Etude au champ de l'enracinement du maïs : influence de l'état structural sur la répartition des racines, conséquences sur l'alimentation hydrique

125 ref. Annexe 40 p. *INRA Agronomie Centre de Versailles-Grignon Diffusion du document : INRA Agronomie Centre de Versailles-Grignon Diplôme : Dr. Ing

Root system responses to soil structural properties micro- and macro-scale

International audienc