Omics and AI for future-proof crops
About this expertise
In short- Genome and metabolite analysis
- High-throughput phenotyping
- AI-driven predictions
- Data integration and modeling
- From lab to practice
Omics technologies and artificial intelligence make it possible to develop more effective knowledge about the genetic and phenotypic characteristics and biochemical composition of plants. This enables faster breeding of varieties that are resistant to climate stress and diseases and that meet market requirements, thereby improving the quality of plant production and plant-based (food) products. We offer partners the expertise and facilities to translate data into practical breeding solutions.
Plant breeding is under pressure from climate change, emerging diseases, and the growing demand for productive and sustainable crops. WUR supports companies and governments with a unique combination of in-depth crop knowledge, breeding-support software, high-tech facilities, and data science expertise.
Using advanced omics platforms (DNA/RNA, proteins, metabolites) and the Netherlands Plant Eco-phenotyping Centre (NPEC), we integrate genetic, molecular, and phenotypic information. Artificial intelligence and bioinformatics translate these large datasets into predictive models and smart decision-support tools. This enables breeders to select the right parent lines more quickly, link traits to genes, and optimize breeding programs. Food and ingredient companies can use these insights to monitor and improve the quality of their plant-based products.
Thanks to our integrated approach — from laboratory to field trial — we co-develop with partners crop varieties that are better suited to future climate conditions, production chains, and consumer demands.
Omics techniques such as genomics, transcriptomics, proteomics, metabolomics, and receptomics provide insights from DNA to metabolite level. Using these data, WUR can uncover the genetic and molecular basis of traits such as flavor, nutritional value, disease resistance, and drought tolerance. This accelerates the development of improved crop varieties and plant-based products.
At the Netherlands Plant Eco-phenotyping Centre (NPEC), thousands of plants are monitored automatically at the same time. Cameras, sensors, and drones record parameters such as growth, stress responses, and photosynthesis. This generates objective, large-scale datasets that are essential for linking DNA information to plant performance in both greenhouse and field conditions.
Machine learning and deep learning transform complex datasets into actionable predictions about genes and their functions. AI models can, for example, predict which young plants will achieve the best yield or resistance - even before extensive field trials are conducted. Algorithms also optimize crossing strategies and simulate breeding schemes across multiple generations.
WUR integrates omics, phenotyping, and AI into a data-driven approach. Partners benefit from our facilities, expertise, and networks — from developing molecular markers to building predictive models that span from gene to ecosystem or agrosystem. Together, we accelerate the breeding of innovative, climate-resilient varieties and sustainable plant-based products.
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prof.dr. HJ (Dirk) Bosch
Expert omics and AI