Apply gene-network inference, feature attribution, association and causal-inference methods, comparative genomics, and multi-trait ranking to identify and prioritize genes, regulatory nodes, biochemical pathways, enzyme variants, and trait stacks associated with fiber development and quality, pigment biosynthesis, stress resilience, nutrient and water-use efficiency, plant architecture, carbon allocation, and pest resistance. Benchmark models using independent or held-out data; evaluate accuracy, calibration, uncertainty, generalizability, interpretability, and bias; track computational predictions through experimental validation; and deploy reproducible workflows using version control, workflow managers, containers, high-performance computing, or cloud resources.