PHENET works with industry to develop low-cost, AI-powered & eco-friendly devices equipped with sensors to monitor diverse traits, environmental conditions & key agroecosystem processes—especially those linked to agroecology and climate change. In RP2, WP2 built several systems & developed algorithms for phenotyping soil health, crop diseases, and orchard conditions. These tools were tested in real-world farm and field experiments. The resulting large-scale dataset will now be used to build models that extract valuable phenotypic insights. PHENET will boost the use of satellite imagery for phenotyping and envirotyping. We have developed an automated method to map intra-field structural variability using multi-year data from Copernicus Sentinel satellites. This tool will support RIs by enhancing experimental design and improving statistical analysis in field trials. Beyond research, the method could have broader applications at farm level, enabling the assessment of crop performance variability and the impact of innovative practices over time. Work is now progressing on harmonization and data fusion techniques to fully exploit EO data. A comprehensive EO image archive has been compiled to support this effort.
The PHENET Open Science services has capitalized on existing data standards, databases, storage & compute services. They have been deployed, connected together and for some of them improved in the frame of the project.
To fully exploit the data, we concentrated on the design & development of hybrid models and 3D-digital twins, and the development of services for selected UCs. Results are promising, and developed methods have been published in peer reviewed articles & open source libraries.
PHENET has been focusing on upskilling the community both on technological aspects and knowledge around increasing the attractiveness, quality and impact of training activities. Business-related stakeholders were addressed. UCs are the core of PHENET activities and all have been successfully implemented and benchmarked tools and methods co-developed with the technical WPs on their specific scientific questions. These tools and methods represent potential services that may be part of the service portfolio of the RIs involved in PHENET.
