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Article
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Modelación de la interacción genotipo x ambiente en rendimiento de hibridos de maiz blanco en ambientes múltiples 

Lozano-Ramírez, A.; Santacruz-Varela, A.; San-Vicente-García, F.; Crossa, J.; Burgueño, J.; Molina-Galán, J.D. (Sociedad Mexicana de Fitogenética, 2015)
Los programas de fitomejoramiento enfocados a la obtención de genotipos con mayor rendimiento y estables en una amplia gama de condiciones ambientales enfrentan factores ambientales que enmascaran el potencial de los ...
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IBFIELDBOOK, an integrated breeding field book for plant breeding 

Lugo-Espinosa, O.; Sanchez-Gutierrez, T.M.; Camarena-Sagredo, J.G.; Vargas Hernández, M.; Alvarado Beltrán, G.; Jarquin, D.; Burgueño, J.; Crossa, J.; Sanchez-Villeda, H. (Sociedad Mexicana de Fitogenética, 2013)
The development of an integrated breeding field book (IBFieldbook) for different crops involves the generation, handling and analysis of large amounts of data. Managing the integration of environmental, pedigree, and ...
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Predicting grain yield using canopy hyperspectral reflectance in wheat breeding data 

Montesinos-Lopez, O.A.; Montesinos-Lopez, A.; Crossa, J.; De los Campos, G.; Alvarado Beltrán, G.; Mondal, S.; Rutkoski, J.; Gonzalez-Perez, L.; Burgueño, J. (BioMed Central, 2017)
Modern agriculture uses hyperspectral cameras to obtain hundreds of reflectance data measured at discrete narrow bands to cover the whole visible light spectrum and part of the infrared and ultraviolet light spectra, ...
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Genomic Bayesian functional regression models with interactions for predicting wheat grain yield using hyper‑spectral image data 

Montesinos-López, A.; Montesinos-Lopez, O.A.; Cuevas, J.; Mata-López, W.A.; Burgueño, J.; Mondal, S.; Huerta-Espino, J.; Singh, R. P.; Autrique, E.; Gonzalez-Perez, L.; Crossa, J. (BioMed Central, 2017)
Modern agriculture uses hyperspectral cameras that provide hundreds of reflectance data at discrete narrow bands in many environments. These bands often cover the whole visible light spectrum and part of the infrared and ...
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Diseños experimentales con testigos repetidos 

Burgueño, J.; Martinez-Garza, A.; Crossa, J.; Mastache-Lagunas, A. (Colegio de Postgraduados, 2005)
In some stages of the breeding of crops, breeders must select the most promising lines from a very large number of sets of new varieties. Selection is conducted via direct comparison of new varieties that are tested within ...
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QTLs asociados al contenido de carotenos en hojas de maiz (Zea mays L.) 

Silva-Perez, V.; Gomez-Merino, F.C.; Garcia-Zavala, J.J.; Burgueño-Ferreira, J.; Santacruz-Varela, A.; Palacios-Rojas, N.; Tiessen, A. (Colegio de Postgraduados, 2012)
Los carotenos son pigmentos antioxidantes que captan foto¬nes del espectro de luz visible y protegen a los tejidos de las plantas contra la foto-oxidación, lo cual está relacionado con la tasa fotosintética y rendimiento ...
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Use of genomic estimated breeding values results in rapid genetic gains for drought tolerance in maize 

Vivek, B.; Krishna, G.; Vengadessan, V.; Babu, R.; Zaidi, P.H.; Le Quy Kha; Mandal, S.S.; Grudloyma, P.; Takalkar, S.; Krothapalli, K.; Singh, I.S.; Ocampo, E.T.M.; Fan, X.M.; Burgueño, J.; Azrai, M.; Singh, R.P.; Crossa, J. (Crop Science Society of America, 2017)
More than 80% of the 19 million ha of maize (Zea mays L.) in tropical Asia is rainfed and prone to drought. The breeding methods for improving drought tolerance (DT), including genomic selection (GS), are geared to increase ...
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Unlocking the genetic diversity of Creole wheats 

Vikram, P.; Franco, J.; Burgueño, J.; Huihui Li; Sehgal, D.; Saint Pierre, C.; Ortiz, C.; Sneller, C.; Tattaris, M.; Guzman, C.; Sansaloni, C.P.; Fuentes Dávila, G.; Reynolds, M.P.; Sonder, K.; Singh, P.K.; Payne, T.S.; Wenzl, P.; Sharma, A.R.; Bains, N.; Gyanendra Pratap Singh; Crossa, J.; Sukhwinder-Singh (Nuture Publishing Group, 2016)
Climate change and slow yield gains pose a major threat to global wheat production. Underutilized genetic resources including landraces and wild relatives are key elements for developing high-yielding and climate-resilient ...
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Identification of genomic associations for adult plant resistance in the background of popular South Asian wheat cultivar, PBW343 

Huihui Li; Sukhwinder-Singh; Bhavani, S.; Singh, R.P.; Sehgal, D.; Basnet, B.R.; Vikram, P.; Burgueño, J.; Huerta-Espino, J. (Frontiers, 2016)
Rusts, a fungal disease as old as its host plant wheat, has caused havoc for over 8000 years. As the rust pathogens can evolve into new virulent races which quickly defeat the resistance that primarily rely on race ...
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Genomic prediction of genotype x environment interaction kernel regression models 

Cuevas, J.; Crossa, J.; Soberanis, V.; Pérez-Elizalde, S.; Pérez-Rodríguez, P.; De los Campos, G.; Montesinos-López, O.A.; Burgueño, J. (Crop Science Society of America, 2016)
In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this ...
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Genetic ResourcesInstitutionalMaizeSocioeconomicsSustainable Agrifood SystemsSustainable IntensificationWheat

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Author
Burgueño, J. (78)
Crossa, J. (46)Pérez-Rodríguez, P. (20)Montesinos-Lopez, O.A. (12)Prasanna, B.M. (12)Singh, S. (12)De Los Campos, G. (11)Sansaloni, C. (11)Olsen, M. (9)Vikram, P. (9)... View More
Date Issued
2020 - 2023 (26)2010 - 2019 (51)2005 - 2009 (1)
Type
Article (78)
Agrovoc
MAIZE (26)GENOTYPE ENVIRONMENT INTERACTION (17)WHEAT (16)BAYESIAN THEORY (12)GENOMICS (12)STATISTICAL METHODS (12)DATA ANALYSIS (9)GENETIC MARKERS (8)PLANT BREEDING (8)FORECASTING (7)... View More
Keywords
Genomic Selection (11)GenPred (7)Shared Data Resources (7)Prediction Accuracy (5)Genome-Wide Association Study (3)Bayesian Functional Regression (2)Fourier Regression (2)GBLUP (2)Genomic Enabled Prediction Accuracy (2)Genotyping by Sequencing (2)... View More
Region
Global (4)Mexico (2)South Asia (1)Uruguay (1)
CGIAR Initiative
Breeding Resources (1)
CGIAR Impact Area
Poverty reduction, livelihoods & jobs (1)
CGIAR Action Area
Resilient Agrifood Systems (1)
CGIAR Donor or Funder
Bill & Melinda Gates Foundation (1)CIMMYT CRP (maize and wheat) (1)USAID (1)


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