Better crops for a sustainable future
Empowering European plant science with cutting-edge phenotyping infrastructure.
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Empowering European plant science with cutting-edge phenotyping infrastructure.
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More information coming soon
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Digital infrastructure that ensures plant phenotyping data are FAIR — Findable, Accessible, Interoperable, and Reusable — so research outputs remain discoverable and valuable over time. EMPHASIS supports harmonised data management across installations, aligning metadata, workflows, and quality standards to improve interoperability and scientific reproducibility.
Services under development include user-friendly repositories, dataset-finder tools, and support for data visualisation, modelling, and simulation — extending experimental results across time, space, and environmental scenarios. Training and self-evaluation resources help installations improve data maturity and adopt best practices for long-term data stewardship.
By connecting with European digital infrastructures such as the European Open Science Cloud (EOSC) and related research initiatives, EMPHASIS ensures that data generated across the infrastructure can be shared, reused, and built upon, strengthening collaboration and innovation across the European Research Area.
Network of multi-environment trial sites with lean, efficient phenotyping
Field phenotyping under real agricultural and breeding conditions, using portable or lightweight equipment to assess hundreds to thousands of plots across diverse environments. These trials capture genetic and phenotypic variation in response to management, soil, and climate differences, providing insight into how crops perform in realistic production systems.
Environmental monitoring typically includes sensor networks measuring temperature, radiation, rainfall, humidity, and soil water potential at hourly or finer resolution, mirroring data standards used in intensive field sites. Mobile or drone-based platforms deploy imaging and sensing tools (RGB, multispectral, hyperspectral, thermal) for efficient, repeatable data collection.
A key EMPHASIS goal is to expand and coordinate networks of such field trials across Europe — enhancing geographical and climatic coverage and integrating datasets to analyse crop performance across gradients and scales. These efforts bring together biologists, geneticists, agronomists, breeders, modellers, and data specialists in a shared research framework.
Smart/ Intensive field experimental sites for high throughput phenomics
Highly instrumented field sites that maintain natural light and climate regimes, enabling detailed study of hundreds of micro-plots through frequent, non-invasive measurements. These platforms combine plant performance monitoring with environmental sensing (soil moisture, temperature, radiation, soil chemistry) to capture growth dynamics and genotype–environment interactions over time. Mobile or gantry-mounted sensors (RGB, multispectral/hyperspectral, LiDAR, thermal) and drone-based imaging record trait responses with high temporal resolution.
Some installations, known as semi-controlled field sites, can manipulate key environmental factors to simulate future climatic scenarios — for example, using rainout shelters to induce drought or FACE systems to elevate CO₂. With ‘deep phenotyping’ options utilising even more sensors or destructive sampling, these installations support experiments designed to decipher complex traits in settings that reflect real agricultural conditions.
High-throughput phenotyping in greenhouses and growth chambers with tightly controlled environments.
These platforms let researchers test trait variation under defined abiotic/biotic conditions (e.g., light, temperature, humidity, CO₂, soil water/nutrients) and simulate stress scenarios with high repeatability. Automation either moves plants past fixed stations (weighing/watering and imaging) or brings sensors to stationary plants.
Typical sensing suites include RGB, multispectral/hyperspectral, thermal, and chlorophyll-fluorescence imaging, often paired with gravimetric watering and gas-exchange to derive growth, water-use, and stress metrics. Throughput commonly spans hundreds to thousands of plants, while ‘deep phenotyping’ setups trade throughput (tens to hundreds) for finer physiological resolution at minutes-to-hours timescales.