biostudies-literatureCuevas JSwedish University of Agricultural SciencesNatural Environment Research CouncilSLUSwedish Research Council Formasjkac322https://www.ebi.ac.uk/biostudies/studies/S-EPMC9911059biostudies-literatureUnknown13(2)In this study, we extend research on genomic prediction (GP) to polysomic polyploid plant species with the main objective to investigate single-trait (ST) and multitrait (MT) multienvironment (ME) models using field trial data from 3 locations in Sweden [Helgegården (HEL), Mosslunda (MOS), Umeå (UM)] over 2 years (2020, 2021) of 253 potato cultivars and breeding clones for 5 tuber weight traits and 2 tuber flesh quality characteristics. This research investigated the GP of 4 genome-based prediction models with genotype × environment interactions (GEs): (1) ST reaction norm model (M1), (2) ST model considering covariances between environments (M2), (3) ST M2 extended to include a random vector that utilizes the environmental covariances (M3), and (4) MT model with GE (M4). Several predictioG3 (Bethesda, Md.)Modeling genotype × environment interaction for single and multitrait genomic prediction in potato (Solanum tuberosum L.).PMC9911059NE/P002692/1Cuevas JCrossa JReslow FOrtiz RfalseModeling genotype × environment interaction for single and multitrait genomic prediction in potato (Solanum tuberosum L.).In this study, we extend research on genomic prediction (GP) to polysomic polyploid plant species with the main objective to investigate single-trait (ST) and multitrait (MT) multienvironment (ME) models using field trial data from 3 locations in Sweden [Helgegården (HEL), Mosslunda (MOS), Umeå (UM)] over 2 years (2020, 2021) of 253 potato cultivars and breeding clones for 5 tuber weight traits and 2 tuber flesh quality characteristics. This research investigated the GP of 4 genome-based prediction models with genotype × environment interactions (GEs): (1) ST reaction norm model (M1), (2) ST model considering covariances between environments (M2), (3) ST M2 extended to include a random vector that utilizes the environmental covariances (M3), and (4) MT model with GE (M4). Several predictio2023-01-01T00:00:00Z2023 Feb2026-07-14T20:11:08.32Z2025-04-04T18:42:21.959ZS-EPMC99110593647730910.1093/g3journal/jkac322