Realistic Scenarios of Phenotypic Variation and Errors in High-Throughput Phenotyping Experiments Minimally Impact the Results of QTL Mapping Analysis.

High-throughput phenotyping technologies increase the efficiency of breeding programs, but with larger data sets, errors can accumulate. Plant breeders often conduct quantitative trait locus (QTL) mapping, where large sample size and accurate quantitative response estimates are important for detecting small effect QTL. This study examined how phenotype error, inconsistency, and replication changed QTL magnitude and location.