The experimental unit used for genetic mapping in plants is usually a plot, or a set of identical or closely related individuals grown in close proximity to each other. To score a trait, several individuals from a plot are measured, and those measurements are averaged to develop a plot-based phenotypic value. This stands in contrast to the typical experimental unit in human and animal studies, where measurements are scored on individuals. Although measuring multiple identical individuals increases accuracy, it also increases cost, time, and experimental complexity. We have developed a pipeline for genetic mapping in plants that does not depend on plot-based measurements. Instead, our pipeline uses individual phenotypes and genotypes measured on a single population. It couples a single-plant genome wide association study (spGWAS) with bulk segregant analysis (BSA), for rapid identification and corroboration of mapped results. Instead of relying on replicated individuals, our approach utilizes replication at the level of alleles within a population. To implement the pipeline, we grow a segregating population comprised of thousands of individuals, from which a random sample of several hundred are genotyped, phenotyped, and used to perform spGWAS. Next, all individuals are rapidly phenotyped, and pools of individuals belonging to extreme ends of the phenotypic distribution are genotyped for BSA. Lastly, we identify QTL implicated in both analyses, which provides immediate corroboration of results. As a proof-of-concept, we implemented this pipeline to identify plant height loci the Shoepeg maize population. We identified three strongly supported candidate regions, along with a larger collection of additional sites with support from either GWAS or BSA (but not both). Our pipeline may be extended to additional species and traits as high-throughput phenotyping of individuals becomes increasingly feasible.