Click Breeding: Toward programmable crop design

Breeding for complex traits is constrained by limited predictive accuracy and transferability, particularly when nonadditive genetic effects and genotype-by-environment interactions dominate performance. In this review, we propose 'Click Breeding', a design-driven paradigm that shifts emphasis from ranking individual candidates to generating and stress-testing entire multigenerational breeding programs. In this framework, objectives and constraints are encoded as machine-readable plans; candidate strategies are evaluated via simulations that integrate genetics, physiology, and environment; and selected designs become traceable experimental workflows with governance checkpoints. Click Breeding connects genomic prediction, crop modeling, and laboratory automation into a coherent, auditable design cycle that complements the breeder's judgment. We discuss conceptual foundations, assess technology maturity, and identify biological, computational, and regulatory challenges to making programmable crop design operational.