Reka Howard
Cited by
Cited by
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
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), 1-15, 2017
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
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), 1-11, 2018
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
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
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), 123, 2019
Application of response surface methods to determine conditions for optimal genomic prediction
R Howard, AL Carriquiry, WD Beavis
G3: Genes, Genomes, Genetics 7 (9), 3103-3113, 2017
Genomic prediction using canopy coverage image and genotypic information in soybean via a hybrid model
R Howard, D Jarquin
Evolutionary Bioinformatics 15, 1176934319840026, 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
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, 2019
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
Evaluation of parametric and nonparametric statistical methods in genomic prediction
R Howard
Predicting Yield by Modeling Interactions between Canopy Coverage Image Data, Genotypic and Environmental Information for Soybeans
D Jarquin, R Howard, A Xavier, SD Choudhury
Intelligent Image Analysis for Plant Phenotyping, 267-286, 2020
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
The local stability of a modified multi-strain SIR model for emerging viral strains
M Fudolig, R Howard
medRxiv, 2020
Package ‘SoyNAM’
A Xavier, W Beavis, J Specht, B Diers, R Howard, W Muir, K Rainey, ...
Achieving Higher Genetic Gain by Enhancing Precision through Genomic Selection Breeding in Chickpea
M Roorkiwal, N Santantonio, D Jarquin, B Chellapilla, M Singh, PM Gaur, ...
Plant and Animal Genome XXVII Conference (January 12-16, 2019), 2019
Principal Variable Selection to Explain Grain Yield Variation in Winter Wheat from UAV-derived Phenotypic Traits
J Li, M Bhatta, ND Garst, H Stoll, AN Veeranampalayam-Sivakumar, ...
2019 ASABE Annual International Meeting, 1, 2019
Response Surface Methodology in Genomic Selection
R Howard
Plant and Animal Genome XXIV Conference, 2016
The system can't perform the operation now. Try again later.
Articles 1–20