Jose Crossa
Jose Crossa
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Cited by
Cited by
Biometrical methods in quantitative genetic analysis.
RK Singh, BD Chaudhary
Biometrical methods in quantitative genetic analysis., 1977
Statistical analyses of multilocation trials
J Crossa
Advances in agronomy 44, 55-85, 1990
Additive main effects and multiplicative interaction analysis of two international maize cultivar trials
J Crossa, HG Gauch Jr, RW Zobel
Crop science 30 (3), 493-500, 1990
Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers
J Crossa, G Campos, P Pérez, D Gianola, J Burgueño, JL Araus, ...
Genetics 186 (2), 713-724, 2010
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
Genomic selection in wheat breeding using genotyping-by-sequencing
JA Poland, J Endelman, J Dawson, J Rutkoski, S Wu, Y Manes, ...
Plant Genome 5 (3), 103-113, 2012
Genomic selection in plant breeding: methods, models, and perspectives
J Crossa, P Pérez-Rodríguez, J Cuevas, O Montesinos-López, D Jarquín, ...
Trends in plant science 22 (11), 961-975, 2017
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
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
Statistical tests and estimators of multiplicative models for genotype-by-environment interaction. Genotype by Environment Interaction.
PL Cornelius, J Crossa, MS Seyedsadr
^ TGenotype by Environment Interaction^ AKang, MS Gauch, HG^ ABoca Raton, FL …, 1996
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
Stem reserve mobilisation supports wheat-grain filling under heat stress
A Blum, B Sinmena, J Mayer, G Golan, L Shpiler
Functional Plant Biology 21 (6), 771-781, 1994
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 (1), 27-37, 1991
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
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
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 (3), 595-607, 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
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
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
Sites regression and shifted multiplicative model clustering of cultivar trial sites under heterogeneity of error variances
J Crossa, PL Cornelius
Crop Science 37 (2), 406-415, 1997
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