Project
COUSIN
Data is a burden, many projects are drowning in data. Therefore good tools need to be developed. COUSIN will focus to provide data integration tools for multiple-sources of information (sensors at various scales).
Our future varieties of wheat, barley, pea, lettuce, or broccoli will depend on the genetic diversity available for breeding and adaptation to global changes. Therefore, the conservation of wild relatives, accessibility to plant genetic material and knowledge of the characteristics of each of their populations is key not only to conserve biodiversity but also to secure our food supply for future generations. COUSIN will explore the potential of Crop Wild Relatives of these 5 crops. The crops will be screened on numerous traits and relevant stress settings within the Netherlands Plant Eco-phenotyping Centre (NPEC) growth rooms and greenhouse.
WU (a PhD and NPEC access) and WR are partner in COUSIN. WR will focus on good quality data analysis methods / sensor analysis based on data generated in the NPEC experiments. Data storage based on FAIRdomSeek, metadata according the Minimal Information About a Plant Phenotyping Experiment (MIAPPE) will be integrated to enable researchers from within the COUSIN consortium to use and compare the data from NPEC with their own field trials elsewhere in Europe. WR will develop these approaches to enable COUSIN to report FAIR data (findable, accessible, interoperable and re-usable)
COUSIN will generate impact by increasing the sustainability of agriculture through the conservation and use of biodiversity, particularly the wild relatives of crops. The contribution of WR focuses on approaches to make and share data in a FAIR manner, which is a knowledge gain in the data science / plant science cross-over that is essential for all data-driven projects.