Utnytte KI-modeller for klimabestandige hvetesorter i bærekraftig landbruk

Offentlig prosjektsammendrag

Climate change and more frequent droughts pose major risks for Norwegian wheat production. Breeding resilient varieties requires new digital tools that go beyond traditional field trials and basic UAV imaging. In this project, we will develop digital twins and explainable AI models that integrate UAV-based sensing, crop growth models, and environmental and genomic data. The goal is to define ideotypes – plant types with optimal traits for drought resilience – and provide breeders with actionable decision-support. The R&D challenge lies in combining complex data sources into predictive, transparent models, something not available today. The project will use a systematic method: UAV data collection, model calibration, data fusion, AI development, and validation in field trials. The outcome will be new knowledge, prototype services, and advanced UAV-based analytics, enabling more robust breeding strategies and sustainable food production.