Cikkek nyilvánosan hozzáférhető megbízással - Jose CrossaTovábbi információ
Sehol sem hozzáférhető: 6
Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics
P Juliana, J Poland, J Huerta-Espino, S Shrestha, J Crossa, ...
Nature genetics 51 (10), 1530-1539, 2019
Megbízások: Bill & Melinda Gates Foundation, US Agency for International Development …
Grain quality traits of commercial durum wheat varieties and their relationships with drought stress and glutenins composition
AM Magallanes-López, K Ammar, A Morales-Dorantes, ...
Journal of Cereal Science 75, 1-9, 2017
Megbízások: CGIAR
Sources of the highly expressed wheat bread making (wbm) gene in CIMMYT spring wheat germplasm and its effect on processing and bread-making quality
C Guzmán, Y Xiao, J Crossa, H González-Santoyo, J Huerta, R Singh, ...
Euphytica 209, 689-692, 2016
Megbízások: CGIAR
Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat
K Semagn, J Crossa, J Cuevas, M Iqbal, I Ciechanowska, MA Henriquez, ...
Theoretical and Applied Genetics 135 (8), 2747-2767, 2022
Megbízások: Natural Sciences and Engineering Research Council of Canada
New wheat breeding paradigms for a warming climate
W Xiong, MP Reynolds, C Montes, J Crossa, S Snapp, B Akin, K Mesut, ...
Nature Climate Change 14 (8), 869-875, 2024
Megbízások: CGIAR
Assessing Payne score accuracy through a bread wheat multi-genotype and multi-environment set from CIMMYT
F Tabbita, MI Ibba, F Andrade, J Crossa, C Guzman
Journal of Cereal Science 115, 103830, 2024
Megbízások: Government of Spain
Valahol hozzáférhető: 240
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
Megbízások: US National Institutes of Health
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
Megbízások: US National Science Foundation, Bill & Melinda Gates Foundation, Department …
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
Megbízások: Swedish Research Council, UK Biotechnology and Biological Sciences Research …
Genetic gains in grain yield through genomic selection in eight bi‐parental maize populations under drought stress
Y Beyene, K Semagn, S Mugo, A Tarekegne, R Babu, B Meisel, ...
Crop Science 55 (1), 154-163, 2015
Megbízások: Bill & Melinda Gates Foundation
Increased prediction accuracy in wheat breeding trials using a marker× environment interaction genomic selection model
M Lopez-Cruz, J Crossa, D Bonnett, S Dreisigacker, J Poland, JL Jannink, ...
G3: Genes, Genomes, Genetics 5 (4), 569-582, 2015
Megbízások: Bill & Melinda Gates Foundation, US National Institutes of Health
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
Megbízások: US National Institutes of Health
Resequencing of 429 chickpea accessions from 45 countries provides insights into genome diversity, domestication and agronomic traits
RK Varshney, M Thudi, M Roorkiwal, W He, HD Upadhyaya, W Yang, ...
Nature genetics 51 (5), 857-864, 2019
Megbízások: Bill & Melinda Gates Foundation, Department of Science & Technology, India …
Genomic‐enabled prediction based on molecular markers and pedigree using the Bayesian linear regression package in R
P Pérez, G de Los Campos, J Crossa, D Gianola
The plant genome 3 (2), 2010
Megbízások: US National Institutes of Health
META-R: A software to analyze data from multi-environment plant breeding trials
G Alvarado, FM Rodríguez, A Pacheco, J Burgueño, J Crossa, M Vargas, ...
The Crop Journal 8 (5), 745-756, 2020
Megbízások: Bill & Melinda Gates Foundation, US Agency for International Development, CGIAR
A review of deep learning applications for genomic selection
OA Montesinos-López, A Montesinos-López, P Pérez-Rodríguez, ...
BMC genomics 22, 1-23, 2021
Megbízások: Bill & Melinda Gates Foundation, US Agency for International Development
Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs
X Zhang, P Pérez-Rodríguez, K Semagn, Y Beyene, R Babu, ...
Heredity 114 (3), 291-299, 2015
Megbízások: Bill & Melinda Gates Foundation
Multitrait, random regression, or simple repeatability model in high‐throughput phenotyping data improve genomic prediction for wheat grain yield
J Sun, JE Rutkoski, JA Poland, J Crossa, JL Jannink, ME Sorrells
The plant genome 10 (2), plantgenome2016.11.0111, 2017
Megbízások: US Department of Agriculture, Indian Council of Agricultural Research
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
Megbízások: US National Science Foundation, Bill & Melinda Gates Foundation, National …
Effect of trait heritability, training population size and marker density on genomic prediction accuracy estimation in 22 bi-parental tropical maize populations
A Zhang, H Wang, Y Beyene, K Semagn, Y Liu, S Cao, Z Cui, Y Ruan, ...
Frontiers in Plant Science 8, 1916, 2017
Megbízások: Bill & Melinda Gates Foundation, National Natural Science Foundation of …
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