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Efficient sharing of plant phenotyping data is a challenge that has been addressed during the last two decades by European infrastructures (ELIXIR, EMPHASIS) and international communities (CGIAR), that allowed to coordinate the effort of major institutes developing activities in the domain. They produced consistent and interoperable sets of resources to support plant phenotyping data management: - data standards: Minimum Information About Plant Phenotyping Experiment (MIAPPE) and the Breeding API (BrAPI) - databases: PIPPA, PHIS, GnpIS, e!DAL-PGP among others - exchange file formats: MIAPPE Template, ISA-Tab These systems and standards have been designed to be as close as possible to researchers and experimenters needs. As a consequence, important efforts have been made to ease their adoption through documentations and trainings. However all these resources remain dispersed, and it can be complicated for new users to know where to get the right information. To address this issue, ELIXIR has developed in the frame of the ELIXIR-CONVERGE project a central portal of guidelines and resources supporting FAIR data management in Life Sciences: the Research Data Management toolkit (RDMkit). RDMkit is a one stop portal that gives a general overview and understanding of the complementarity of the solutions, and links back to the extended documentation and training materials maintained for each of them. To develop and sustain this portal, ELIXIR has engaged with various communities, infrastructures and projects, among which the ELIXIR plant science community and the AGENT project. In the RDMkit, the plant community has built a set of pages and in particular is building plant phenotyping guidelines. The present poster gives an overview of the RDMkit logic and of the solutions presented in the plant sciences pages, including the procedures and contact to submit enrichment and additional solutions.

Executive Summary Objectives The objective of EMPHASIS-prep is to develop a long term, distributed, pan-European infrastructure for state-of-the-art plant phenotyping experimental installations, which aims to improve crop performance to cope with climate changes and to keep pace with population growth. Plant researchers are required to test the improvement of plant and crop performance by using all categories of plant phenotyping infrastructures (as described in the deliverable D2.1. criteria list for plant phenotyping infrastructure) which can and should be combined together in a multiscale plant phenotyping approach, ideally, within a coordinated infrastructure, linked with an integrated data management system for storing and analyzing (meta)data, and with modelling platforms associated with the phenotyping platforms. To be able to form this distributed plant phenotyping infrastructure and understand the comparability and/or differences between installations, it is essential to map the new and existing plant phenotyping platforms that uses non-destructive, image-analysis based determination of the phenotype of plants and allow for a characterization of plant traits. This exercise of mapping the infrastructures has been performed and the results can be consulted in the EMPHASIS-PREP deliverable D2.3 mapping of existing and upcoming infrastructures. Deliverable D2.4, extensively describes the analyzing of the gaps and limitations based on the mapping activities. Moreover, where possible, the gaps will be strategically addressed to define how EMPHASIS could be helpful in the future to tackle these gaps in services towards excellence in plant phenotyping science within Europe. Nevertheless, mapping and knowing the limitations of the European situation of the distributed infrastructure is not sufficient to understand the landscape of the experimental phenotyping installations in Europe and its financial impact. Knowing the life cycle of the installations, the time when updates and/or upgrades are needed and the life span before decommissioning of the installations, will complement the understanding of the operation of the installations and allow for planning and interaction between installations on a pan-European level. Rationale This deliverable, describes the analysis of life cycles of plant phenotyping experimental installations which will provide insights in when installations require updates, upgrades, in both software and hardware of the systems, or, as a last step in the life cycle, requires decommissioning. The report summarizes surveys of the way life cycle is currently managed in plant phenotyping installations, in the 5 categories identified in D2.1., on the level of updates and upgrades on hardware systems, implementation of software systems, including an analysis of the financial situation of updates. The results of the deliverable have been obtained by analysis of data from two sources: (1) interviews with 20 different installation managers of European plant phenotyping installations, within countries: The Netherlands, Belgium, France, UK, Germany, Italy and Czech Republic. All interviews have been added within the attachment of this deliverable. ; (2) Survey results of the 2021 survey of IPPN and EMPHASIS, with 396 participants of European origin.During the lifecycle of an infrastructure the costs may vary substantially for example with respect to investment, operation or decommissioning. Within the main results we observe big differences between the different phenotyping categories (see D2.1 Criteria list), updates and upgrades on fields are almost nonexistent, whereas software tools need constant updates and controlled conditions need bigger upgrades every 5 to 10 years. Data about decommissioning was not easy to find as plant phenotyping, with automated systems, is a fairly new branch in plant science.

Optimal plant growth performance requires that the presence and action of growth signals, such as gibberellins (GAs), are coordinated with the availability of photo-assimilates. Here, we studied the links between GA biosynthesis and carbon availability, and the subsequent effects on growth. We established that carbon availability, light and dark cues, and the circadian clock ensure the timing and magnitude of GA biosynthesis and that disruption of these factors results in reduced GA levels and expression of downstream genes. Carbon-dependent nighttime induction of gibberellin 3-beta-dioxygenase 1 (GA3ox1) was severely hampered when preceded by reduced daytime light availability, leading specifically to reduced bioactive GA4 levels, and coinciding with a decline in leaf expansion rate during the night. We attributed this decline in leaf expansion mostly to reduced photo-assimilates. However, plants in which GA limitation was alleviated had significantly improved leaf expansion, demonstrating the relevance of GAs in growth control under varying carbon availability. Carbon-dependent expression of upstream GA biosynthesis genes (Kaurene synthase and gibberellin 20 oxidase 1, GA20ox1) was not translated into metabolite changes within this short timeframe. We propose a model in which the extent of nighttime biosynthesis of bioactive GA4 by GA3ox1 is determined by nighttime consumption of starch reserves, thus providing day-to-day adjustments of GA responses.

Executive Summary Objectives The objective of EMPHASIS is to develop a long term, distributed, pan-European infrastructure equipped with state-of-the-art plant phenotyping experimental installations, which provide access to user community and enable excellent science that aims to improve crop performance and address future grand challenges. There is an increasing demand for use of phenotyping infrastructure which requires different infrastructure categories as described in the deliverable D2.1. Criteria list for plant phenotyping infrastructure. Access to phenotyping facilities and services requires a coordinated infrastructure, linked with an integrated data management system for storing and analysing (meta) data, and with modelling platforms associated with the phenotyping platforms. To be able to provide services related to plant phenotyping infrastructure considering the comparability and/or differences between installations, it is essential to map the new and existing plant phenotyping facilities that use non-destructive, image-analysis based determination of the phenotype of plants and allow for a characterization of plant traits. This mapping has been performed and the results are summarized in the EMPHASIS-PREP deliverable D2.3: mapping of existing and upcoming infrastructures. This deliverable, D2.4, will extensively evaluate the gaps and limitations based on the mapping activities. Moreover, where possible, the gaps will be strategically addressed by presenting in what perspective EMPHASIS could tackle these gaps and enable services to the benefit of excellent plant phenotyping science in Europe. Rationale Both the mapping and the analysis of gaps has been done by EMPHASIS-PREP partners in extensive collaborations and discussions with the plant phenotyping community in Europe driven by four regional and three topical workshops, two surveys, and workshops during the annual support group meetings. During the workshops, breakout sessions were organised to extensively discuss about the gaps of plant phenotyping in Europe and how to address these limitations. Furthermore, EMPHASIS-PREP developed two surveys, which had the purpose to assess the phenotyping landscape, and included and dedicated questions on how the participants see the future of phenotyping, what gaps there identify and how to tackle these gaps. The development of a virtual map in the scope of the mapping deliverable was very effective to find regional gaps for specific plant phenotyping infrastructure in Europe. Main Results: 1. Gaps in the mapping data extraction We mapped the plant phenotyping infrastructures in Europe in details (Deliverable 2.3) and were able to identify limitations that need to be addressed in the future. The mapping involved the plant phenotyping community from academia and industry at large but the results may be biased for installations from academia. Additional efforts to evaluate plant phenotyping within the industry sector may be required. Moreover, countries with a well-established national networks have a higher number of installations in the database. It could be assumed that well-connected national communities can be easier addressed and provide feedback on their installations in contrast to facilities that are in the process of establishing national communities. Thus further and continuous evaluation of the dynamic phenotyping landscape will be required and an important tool for service provision by EMPHASIS. 2. Gaps in harmonizing and innovating plant phenotyping infrastructure The need for a collective harmonisation of protocols and experimental design strategies to ensure reproductive and interoperable data was clearly expressed. Moreover, innovation through knowledge and technology transfer is very much needed to ensure qualitative sustainable phenotyping. To address these limitations a harmonisation and innovation pilots were initiated and are under development (Deliverable 6.3). 3. Gaps in plant phenotyping categories Controlled condition plant phenotyping The survey indicated that there are gaps in geographical location of installations under controlled conditions. There are further limitation of required throughput rates to address mapping populations potentially driven by limited automation and the use of more advanced sensor technologies. The capacity for root phenotyping is less-developed than for shoot and canopy studies. Intensive field Geographical gaps have also been identified for intensive fields. There was a limited response with respect to intensive field and further identification and characterisation of intensive field sites is required. Networks of lean field phenotyping Networks of fields are very difficult to map. Some institutes own land for field experiments, while others have annual renting opportunities with local land owners. The latter causes the overall total of fields in the database to be substantially underestimated. Although minimal equipment, like UAVs for imaging analysis in lean field phenotyping is more commonly used, there appears to be a limitation with respect to the analysis of these imaging data. Multi-climatic trials across Europe are essential to breed for new crop varieties, needed to cope with the changing climate. Access procedure to networks field sites is rather challenging needs to be developed, a field pilot that is under development (Deliverable 6.3) will support this development. Modelling The plant model database populated through the review of the literature indicated that there are gaps in the plant models inventoried (e.g. models developed by industry are not published) and the plant model availability (i.e. not directly available). Moreover, the diversity observed between the plant models will constitute challenges to improve the interoperability between the phenomics data and the plant models through a unique portal. EMPHASIS, through the next modelling pilot that is under development (Deliverable 6.3), will encourage the modelling community to adopt and develop harmonized standards for interfacing models with phenomics data sources. Data management systems The survey revealed that a high number of local infrastructures are not using data management system that will allow interoperability of data. Thus, FAIR principles are not applied yet in many information systems. Several steps are required before these principles can be effective, enabling interoperability. The data pilot (Deliverable 6.3) that is under development will provide users some tools and standards to enable interoperability.

The phenylpropanoid cis-cinnamic acid stimulates the overall growth of different plant species. The trans-isomer is inactive when used at equimolar concentrations., Agrochemicals provide vast potential to improve plant productivity, because they are easy to implement at low cost while not being restricted by species barriers as compared with breeding strategies. Despite the general interest, only a few compounds with growth-promoting activity have been described so far. Here, we add cis-cinnamic acid (c-CA) to the small portfolio of existing plant growth stimulators. When applied at low micromolar concentrations to Arabidopsis roots, c-CA stimulates both cell division and cell expansion in leaves. Our data support a model explaining the increase in shoot biomass as the consequence of a larger root system, which allows the plant to explore larger areas for resources. The requirement of the cis-configuration for the growth-promoting activity of CA was validated by implementing stable structural analogs of both cis- and trans-CA in this study. In a complementary approach, we used specific light conditions to prevent cis/trans-isomerization of CA during the experiment. In both cases, the cis-form stimulated plant growth, whereas the trans-form was inactive. Based on these data, we conclude that c-CA is an appealing lead compound representing a novel class of growth-promoting agrochemicals. Unraveling the underlying molecular mechanism could lead to the development of innovative strategies for boosting plant biomass.

Executive Summary Objectives The objective of EMPHASIS-PREP is to develop a long term, distributed, pan-European infrastructure for state-of-the-art plant phenotyping experimental platforms which aims to improve crop performance needed to cope with climate changes and to keep pace with population growth. To tackle these global challenges, novel approaches to identify improved plant phenotypes and explain the genetic basis of agriculturally important traits are required. The new and existing plant phenotyping platforms uses non-destructive, image-analysis based determination of the phenotype of plants and allow for a characterization of plant traits. The criteria list provides a detailed overview of plant phenotyping infrastructure within the scope of EMPHASIS, all which can be divided into five major pillars of plant phenotyping infrastructure: 1. Plant phenotyping in (semi-)controlled conditions. 2. Intensive field experiments in highly equipped field sites or semi-controlled field sites. 3. Field sites with minimal equipment, which could be combined in a network of fields with different environmental conditions. 4. Modelling platforms to support plant phenotyping data analysis. 5. Information systems for plant phenotyping data management supporting open science. The criteria list was developed in discussion with the plant phenotyping community and by mapping the existing and upcoming infrastructures in pan-Europe. Four regional workshops have been organized to that end in different regions of Europe. Plant scientist of these regions were asked to present their plant phenotyping infrastructures and activities. Starting with this information these pillars of EMPHASIS could be confirmed. Furthermore, work package 2 (WP2), together with WP3 and WP4, has developed a survey to the community to extract more details of these infrastructures and to be able to translate this into a community driven criteria list for EMPHASIS. The current criteria list presents a result up-to-date status of the ongoing participation and discussion with the plant phenotyping community in the development of EMPHASIS. It is thus still open for modifications in the course of ongoing stakeholder engagement. Main Results By mapping the pan-Europe state-of-the-art infrastructures, the criteria list of EMPHASIS could be defined and subdivided in five pillars. Below these five pillars and their criteria are described as main results of the criteria list: Pillar 1: Plant phenotyping in (semi-)controlled conditions can be defined as automated glasshouse and growth chamber infrastructures for plant phenotyping to characterize the architecture, growth and physiology of individual plants and monitor environmental conditions. Throughputs are typically 100s-1000s plants, thereby allowing the analysis of genetic variability and calculation of allelic effects in a large range of climatic scenarios. Pillar 2: Intensive field experiments are field sites fully equipped for detailed environmental characterization at plot level, and vectors (typically ground or airborne) able to perform measurements of phenotypic variables such as leaf area, plant number, plant architecture or physiological status via, for example, hyperspectral or fluorimetric cameras. Plants are subjected to natural conditions of soil and climate, but some intensive field installations could have for example, modified rainfall or atmospheric conditions, via special equipment such as Free Air CO2 Enrichment (FACE), mobile rain-out shelters or heat shields. With throughputs of typically 100s – 1000s microplots, this allows assessing plant performance in climatic scenarios that mimics possible climate conditions of the future and novel management schemes. Pillar 3: Field trials with precise environmental monitoring equipment, and equipment for precise measurement of yield components and grain moisture in thousands of micro plots. This is potentially combined with field-based imaging or remote sensing (airborne) systems. Individual fields are usually combined into a network of field trials over multiple geographical regions with different environmental conditions, thereby allowing estimation of yield of hundreds of genotypes across diverse climate scenarios. Pillar 4: Modelling platforms are virtual platforms of different nature that have the intention to support plant phenotyping. It has been proven very difficult to form criteria for modelling phenotyping platforms, therefore, a number of different models that could be used to support plant phenotyping are described in this criteria list. Pillar 5: plant phenotyping information systems, which aim to provide methods and interfaces to manage, share, reuse and visualize heterogeneous plant phenotyping data stemming from different sources, often functioning in an interdisciplinary context.