| Evaluating methods of updating training data in long-term genomewide selection JL Neyhart, T Tiede, AJ Lorenz, KP Smith G3: Genes, Genomes, Genetics 7 (5), 1499-1510, 2017 | 52 | 2017 |
| Multi-trait improvement by predicting genetic correlations in breeding crosses JL Neyhart, AJ Lorenz, KP Smith G3: Genes, Genomes, Genetics 9 (10), 3153-3165, 2019 | 51 | 2019 |
| Validating genomewide predictions of genetic variance in a contemporary breeding program JL Neyhart, KP Smith Crop Science 59 (3), 1062-1072, 2019 | 22 | 2019 |
| Genetic loci mediating circadian clock output plasticity and crop productivity under barley domestication MR Prusty, E Bdolach, E Yamamoto, LD Tiwari, R Silberman, ... New Phytologist 230 (5), 1787-1801, 2021 | 16 | 2021 |
| Nested association mapping reveals the genetic architecture of spike emergence and anthesis timing in intermediate wheatgrass KR Altendorf, S Larson, LR DeHaan, J Crain, J Neyhart, KM Dorn, ... G3 Genes| Genomes| Genetics, 2021 | 13 | 2021 |
| A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory D Rippner, P Raja, J Earles, M Momayyezi, A Buchko, F Duong, ... Frontiers in plant science 13, 2022 | 12 | 2022 |
| Registration of the S2MET barley mapping population for multi‐environment genomewide selection JL Neyhart, D Sweeney, M Sorrells, C Kapp, KD Kephart, J Sherman, ... Journal of Plant Registrations 13 (2), 270-280, 2019 | 12 | 2019 |
| Optimizing the choice of test locations for multitrait genotypic evaluation JL Neyhart, L Gutierrez, KP Smith Crop Science 62 (1), 192-202, 2022 | 7 | 2022 |
| Using environmental similarities to design training sets for genomewide selection JL Neyhart, L Gutiérrez, KP Smith Crop Science 61 (1), 396-409, 2021 | 7 | 2021 |
| An active learning tool for quantitative genetics instruction using R and shiny JL Neyhart, E Watkins Natural Sciences Education 49 (1), e20026, 2020 | 7 | 2020 |
| Adapting perennial grain and oilseed crops for climate resiliency J Jungers, B Runck, PM Ewing, T Maaz, C Carlson, J Neyhart, N Fumia, ... Crop Science 63 (4), 1701-1721, 2023 | 4 | 2023 |
| Genomic-environmental associations in wild cranberry (Vaccinium macrocarpon Ait.) JL Neyhart, MB Kantar, J Zalapa, N Vorsa G3 Genes| Genomes| Genetics 12 (10), 2022 | 3 | 2022 |
| Accurate predictions of barley phenotypes using genomewide markers and environmental covariates JL Neyhart, KAT Silverstein, KP Smith Crop Science 62 (5), 1821-1833, 2022 | 3 | 2022 |
| The many‐faced Janus of plant breeding MB Kantar, BC Runck, B Raghavan, AB Joglekar, S Senay, B Krohn, ... Plants, People, Planet 1 (4), 306-309, 2019 | 2 | 2019 |
| Where the wild things are: genetic associations of environmental adaptation in the Oryza rufipogon species complex DR Wang, MB Kantar, V Murugaiyan, J Neyhart G3: Genes, Genomes, Genetics 13 (8), jkad128, 2023 | 1 | 2023 |
| Local adaptation and broad performance are synergistic to productivity in modern barley PM Ewing, MB Kantar, E Killian, JL Neyhart, JD Sherman, JL Williams, ... Crop Science 64 (1), 192-199, 2024 | | 2024 |
| IMPLEMENTING CROSS SELECTION USING GENOMEWIDE PREDICTIONS FOR SUPERIOR PROGENY MEAN AND TRAIT CORRELATIONS WITH FUSARIUM HEAD BLIGHT SEVERITY KP Smith, J Neyhart, A Lorenz 2019 National Fusarium Head Blight Forum, 118, 2019 | | 2019 |
| SNP Genotyping Data for the Barley Population in" Registration of the S2MET Barley Mapping Population for Multi-Environment Genomewide Selection" JL Neyhart, KP Smith | | 2019 |
| Applications of Genomewide Selection in a New Plant Breeding Program JL Neyhart University of Minnesota, 2019 | | 2019 |
| USING GENOMEWIDE MARKERS AND SIMULATED POPULATIONS TO PREDICT GENETIC VARIANCE AND CORRELATION FOR FUSARIUM HEAD BLIGHT RESISTANCE IN BARLEY JL Neyhart, KP Smith 2018 National Fusarium Head Blight Forum, 129, 2018 | | 2018 |
Aaron LorenzProfessor of Agronomy and Plant GeneticsVerified email at umn.edu
