| Parametric and nonparametric statistical methods for genomic selection of traits with additive and epistatic genetic architectures R Howard, AL Carriquiry, WD Beavis G3: Genes, Genomes, Genetics 4 (6), 1027-1046, 2014 | 219 | 2014 |
| A chickpea genetic variation map based on the sequencing of 3,366 genomes RK Varshney, M Roorkiwal, S Sun, P Bajaj, A Chitikineni, M Thudi, ... Nature 599 (7886), 622-627, 2021 | 118 | 2021 |
| Increasing genomic‐enabled prediction accuracy by modeling genotype× environment interactions in Kansas wheat D Jarquín, C Lemes da Silva, RC Gaynor, J Poland, A Fritz, R Howard, ... The plant genome 10 (2), plantgenome2016.12.0130, 2017 | 115 | 2017 |
| Climate and agronomy, not genetics, underpin recent maize yield gains in favorable environments G Rizzo, JP Monzon, FA Tenorio, R Howard, KG Cassman, P Grassini Proceedings of the National Academy of Sciences 119 (4), e2113629119, 2022 | 94 | 2022 |
| Genome-wide analysis of grain yield stability and environmental interactions in a multiparental soybean population A Xavier, D Jarquin, R Howard, V Ramasubramanian, JE Specht, ... G3: Genes, Genomes, Genetics 8 (2), 519-529, 2018 | 80 | 2018 |
| Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype× environment interaction on prediction accuracy in chickpea M Roorkiwal, D Jarquin, MK Singh, PM Gaur, C Bharadwaj, A Rathore, ... Scientific reports 8 (1), 11701, 2018 | 75 | 2018 |
| Genomic prediction enhanced sparse testing for multi-environment trials D Jarquin, R Howard, J Crossa, Y Beyene, M Gowda, JWR Martini, ... G3: Genes, Genomes, Genetics 10 (8), 2725-2739, 2020 | 74 | 2020 |
| The local stability of a modified multi-strain SIR model for emerging viral strains M Fudolig, R Howard PloS one 15 (12), e0243408, 2020 | 68 | 2020 |
| Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery J Li, AN Veeranampalayam-Sivakumar, M Bhatta, ND Garst, H Stoll, ... Plant Methods 15, 1-13, 2019 | 39 | 2019 |
| Assessing variation in maize grain nitrogen concentration and its implications for estimating nitrogen balance in the US North Central region FAM Tenorio, AJ Eagle, EL McLellan, KG Cassman, R Howard, FE Below, ... Field Crops Research 240, 185-193, 2019 | 36 | 2019 |
| Increasing genomic-enabled prediction accuracy by modeling genotype× environment interactions in Kansas wheat. Plant Genome 10: 1–15 D Jarquín, CL da Silva, RC Gaynor, J Poland, A Fritz, R Howard, ... | 30 | 2017 |
| Enhancing hybrid prediction in pearl millet using genomic and/or multi-environment phenotypic information of inbreds D Jarquin, R Howard, Z Liang, SK Gupta, JC Schnable, J Crossa Frontiers in Genetics 10, 496995, 2020 | 26 | 2020 |
| Increasing predictive ability by modeling interactions between environments, genotype and canopy coverage image data for soybeans D Jarquin, R Howard, A Xavier, S Das Choudhury Agronomy 8 (4), 51, 2018 | 26 | 2018 |
| Comparing a mixed model approach to traditional stability estimators for mapping genotype by environment interactions and yield stability in soybean [Glycine max (L.) Merr.] MM Happ, GL Graef, H Wang, R Howard, L Posadas, DL Hyten Frontiers in plant science 12, 630175, 2021 | 20 | 2021 |
| Genome‐enabled prediction for sparse testing in multi‐environmental wheat trials L Crespo‐Herrera, R Howard, HP Piepho, P Pérez‐Rodríguez, ... The plant genome 14 (3), e20151, 2021 | 18 | 2021 |
| Joint use of genome, pedigree, and their interaction with environment for predicting the performance of wheat lines in new environments R Howard, D Gianola, O Montesinos-López, P Juliana, R Singh, J Poland, ... G3: Genes, Genomes, Genetics 9 (9), 2925-2934, 2019 | 16 | 2019 |
| Genomic predictions for common bunt, FHB, stripe rust, leaf rust, and leaf spotting resistance in spring wheat K Semagn, M Iqbal, D Jarquin, J Crossa, R Howard, I Ciechanowska, ... Genes 13 (4), 565, 2022 | 13 | 2022 |
| Genomic prediction using canopy coverage image and genotypic information in soybean via a hybrid model R Howard, D Jarquin Evolutionary Bioinformatics 15, 1176934319840026, 2019 | 12 | 2019 |
| Response surface analysis of genomic prediction accuracy values using quality control covariates in soybean D Jarquín, R Howard, G Graef, A Lorenz Evolutionary Bioinformatics 15, 1176934319831307, 2019 | 11 | 2019 |
| Genome-wide analysis of grain yield stability and environmental interactions in a multiparental soybean population. G3 (Bethesda) 8: 519–529 A Xavier, D Jarquin, R Howard, V Ramasubramanian, JE Specht | 9 | 2018 |
Diego JarquinUniversity of FloridaVerified email at ufl.edu
