CropGxE-GenomicSelection-Synthetic

CropGxE-GenomicSelection-Synthetic simulates a 400-line breeding population genotyped at 800 SNP-style markers across 10 chromosomes, generated with realistic linkage disequilibrium (a haplotype-copying process, not independent random markers) and real pedigree relatedness (simulated biparental crosses with actual meiotic recombination). Four traits (grain yield, days to flowering, disease resistance score, plant height) follow a major-QTL-plus-polygenic-background genetic architecture, extended with dominance deviations, additive-by-additive epistasis, and deliberately shared (pleiotropic) QTL between trait pairs to induce genetic correlation. A trait-specific fraction of QTL are environment-plastic, modulated by developmental-stage-appropriate environmental covariates -- flowering time responds to temperature at flowering specifically, yield responds to rainfall during grain-fill, not season-long averages. The genomic relationship matrix is computed with the standard VanRaden method used throughout real genomic prediction. Multi-environment trials use a realistic sparse design supporting the standard cross-validation schemes used in genomic selection research. Unlike any real breeding trial dataset, this dataset ships the ground-truth QTL, dominance, and epistatic effects used to generate every phenotype, enabling direct benchmarking of a prediction method's estimates against known truth.