Juan Burgueño
Juan Burgueño
Verified email at cgiar.org - Homepage
Cited by
Cited by
Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers
J Crossa, G de Los Campos, P Pérez, D Gianola, J Burgueño, JL Araus, ...
Genetics 186 (2), 713-724, 2010
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
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
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
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
Biplot analysis of genotype× environment interaction: Proceed with caution
RC Yang, J Crossa, PL Cornelius, J Burgueño
Crop Science 49 (5), 1564-1576, 2009
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
Genomic prediction in maize breeding populations with genotyping-by-sequencing
J Crossa, Y Beyene, S Kassa, P Pérez, JM Hickey, C Chen, ...
G3: Genes, Genomes, Genetics 3 (11), 1903-1926, 2013
A high density GBS map of bread wheat and its application for dissecting complex disease resistance traits
H Li, P Vikram, RP Singh, A Kilian, J Carling, J Song, ...
BMC genomics 16 (1), 216, 2015
Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat
P Pérez-Rodríguez, D Gianola, JM González-Camacho, J Crossa, ...
G3: Genes, Genomes, Genetics 2 (12), 1595-1605, 2012
A study of allelic diversity underlying flowering-time adaptation in maize landraces
JAR Navarro, M Willcox, J Burgueño, C Romay, K Swarts, S Trachsel, ...
Nature genetics 49 (3), 476, 2017
Transcript profiling of Zea mays roots reveals gene responses to phosphate deficiency at the plant- and species-specific levels
C Calderon-Vazquez, E Ibarra-Laclette, J Caballero-Perez, ...
Journal of Experimental Botany 59 (9), 2479-2497, 2008
Modeling genotype× environment interaction using additive genetic covariances of relatives for predicting breeding values of wheat genotypes
J Crossa, J Burgueño, PL Cornelius, G McLaren, R Trethowan, ...
Crop science 46 (4), 1722-1733, 2006
Characterization of biocontrol activity of two yeast strains from Uruguay against blue mold of apple
S Vero, P Mondino, J Burgueno, M Soubes, M Wisniewski
Postharvest Biology and Technology 26 (1), 91-98, 2002
Poor farmers’ perceived benefits from different types of maize germplasm: the case of creolization in lowland tropical Mexico
MR Bellon, M Adato, J Becerril, D Mindek
World development 34 (1), 113-129, 2006
Climate change and crop production
MP Reynolds
Cabi, 2010
SAS programs for graphing GE and GGE biplots.
J Burgueño, J Crossa, M Vargas
Using factor analytic models for joining environments and genotypes without crossover genotype× environment interaction
J Burgueño, J Crossa, PL Cornelius, RC Yang
Crop Science 48 (4), 1291-1305, 2008
Prediction assessment of linear mixed models for multienvironment trials
J Burgueño, J Crossa, JM Cotes, FS Vicente, B Das
Crop Science 51 (3), 944-954, 2011
Genomic prediction of gene bank wheat landraces
J Crossa, D Jarquín, J Franco, P Pérez-Rodríguez, J Burgueño, ...
G3: Genes, Genomes, Genetics 6 (7), 1819-1834, 2016
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