This project leverages integrative multi-omics approaches to identify high-yielding and climate-resilient crop varieties, aiming to strengthen Sweden’s food security under changing climatic conditions. We utilize high-throughput genomic and transcriptomic data, including whole-genome resequencing, RNA sequencing, and genotype-by-sequencing, from hundreds of individuals across plant populations of agronomic relevance to Sweden. By combining these large-scale datasets, we aim to associate genotypic variation with phenotypic traits to elucidate the genetic basis of adaptation and yield stability. The resulting insights will guide molecular breeding and enable predictive modeling of variety performance under future climate scenarios. This work requires substantial computational resources for data integration, statistical association analyses, and machine-learning–based projections.