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Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers J Crossa, G Campos, P Pérez, D Gianola, J Burgueno, JL Araus, ... Genetics 186 (2), 713-724, 2010 | 875 | 2010 |
Genomic selection in wheat breeding using genotyping‐by‐sequencing J Poland, J Endelman, J Dawson, J Rutkoski, S Wu, Y Manes, ... The Plant Genome 5 (3), 2012 | 805 | 2012 |
Predicting quantitative traits with regression models for dense molecular markers and pedigree G De Los Campos, H Naya, D Gianola, J Crossa, A Legarra, E Manfredi, ... Genetics 182 (1), 375-385, 2009 | 742 | 2009 |
Genomic prediction of breeding values when modeling genotype× environment interaction using pedigree and dense molecular markers J Burgueño, G de los Campos, K Weigel, J Crossa Crop Science 52 (2), 707-719, 2012 | 596 | 2012 |
A reaction norm model for genomic selection using high-dimensional genomic and environmental data D Jarquín, J Crossa, X Lacaze, P Du Cheyron, J Daucourt, J Lorgeou, ... Theoretical and applied genetics 127, 595-607, 2014 | 572 | 2014 |
Two types of GGE biplots for analyzing multi‐environment trial data W Yan, PL Cornelius, J Crossa, LA Hunt Crop Science 41 (3), 656-663, 2001 | 565 | 2001 |
Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure J Crossa, J Burgueno, S Dreisigacker, M Vargas, SA Herrera-Foessel, ... Genetics 177 (3), 1889-1913, 2007 | 551 | 2007 |
Statistical tests and estimators of multiplicative models for genotype-by-environment interaction PL Cornelius, J Crossa, MS Seyedsadr Genotype-by-environment interaction. CRC Press, Boca Raton, FL, 199-234, 1996 | 481* | 1996 |
Genomic prediction in CIMMYT maize and wheat breeding programs J Crossa, P Perez, J Hickey, J Burgueno, L Ornella, J Cerón-Rojas, ... Heredity 112 (1), 48-60, 2014 | 465 | 2014 |
Biplot analysis of genotype× environment interaction: Proceed with caution RC Yang, J Crossa, PL Cornelius, J Burgueño Crop Science 49 (5), 1564-1576, 2009 | 432 | 2009 |
AMMI adjustment for statistical analysis of an international wheat yield trial J Crossa, PN Fox, WH Pfeiffer, S Rajaram, HG Gauch Theoretical and Applied Genetics 81, 27-37, 1991 | 397 | 1991 |
High‐throughput Phenotyping and Genomic Selection: The Frontiers of Crop Breeding ConvergeF L Cabrera‐Bosquet, J Crossa, J von Zitzewitz, MD Serret, J Luis Araus Journal of integrative plant biology 54 (5), 312-320, 2012 | 395 | 2012 |
Canopy temperature and vegetation indices from high-throughput phenotyping improve accuracy of pedigree and genomic selection for grain yield in wheat J Rutkoski, J Poland, S Mondal, E Autrique, LG Pérez, J Crossa, ... G3: Genes, Genomes, Genetics 6 (9), 2799-2808, 2016 | 386 | 2016 |
Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.) FM Bassi, AR Bentley, G Charmet, R Ortiz, J Crossa Plant Science 242, 23-36, 2016 | 365 | 2016 |
Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods G de Los Campos, D Gianola, GJM Rosa, KA Weigel, J Crossa Genetics research 92 (4), 295-308, 2010 | 361 | 2010 |
Identification of drought, heat, and combined drought and heat tolerant donors in maize JE Cairns, J Crossa, PH Zaidi, P Grudloyma, C Sanchez, JL Araus, ... Crop Science 53 (4), 1335-1346, 2013 | 359 | 2013 |
Genetic characterization of CIMMYT inbred maize lines and open pollinated populations using large scale fingerprinting methods ML Warburton, X Xianchun, J Crossa, J Franco, AE Melchinger, M Frisch, ... Crop Science 42 (6), 1832-1840, 2002 | 330 | 2002 |