Person: Crossa, J.
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Crossa
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J.
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Crossa, J.
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34 results
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- Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel(Oxford University Press, 2024) LaPorte, M.F.; Suwarno, W.B.; Hannok, P.; Koide, A.; Bradbury, P.; Crossa, J.; Palacios-Rojas, N.; Diepenbrock, C.
Publication - Multispectral and thermal infrared data, visual scores for severity of common rust symptoms, and genotypic single nucleotide polymorphism data of three F2-derived biparental doubled-haploid maize populations(Elsevier, 2024) Loladze, A.; Rodrigues, F.; Petroli, C.; Muñoz-Zavala, C.; Naranjo, S.; San Vicente Garcia, F.M.; Gerard, B.; Montesinos-Lopez, O.A.; Crossa, J.; Martini, J.W.R.
Publication - Modeling within and between sub-genomes epistasis of synthetic hexaploid wheat for genome-enabled prediction of diseases(MDPI, 2024) Cuevas, J.; González-Diéguez, D.; Dreisigacker, S.; Martini, J.W.R.; Crespo Herrera, L.A.; Lozano, N.; Singh, P.K.; Xinyao He; Huerta-Espino, J.; Crossa, J.
Publication - Deep learning methods improve genomic prediction of wheat breeding(Frontiers Media S.A., 2024) Montesinos-Lopez, A.; Crespo Herrera, L.A.; Dreisigacker, S.; Gerard, G.S.; Vitale, P.; Saint Pierre, C.; Velu, G.; Tarekegn, Z.T.; Chavira-Flores, M.; Pérez-Rodríguez, P.; Ramos-Pulido, S.; Lillemo, M.; Huihui Li; Montesinos-Lopez, O.A.; Crossa, J.
Publication - Multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits(Genetics Society of America, 2018) Montesinos-Lopez, O.A.; Montesinos-Lopez, A.; Crossa, J.; Gianola, D.; Hernández Suárez, C.M.; Martin Vallejo, F.J.
Publication - Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat(Springer Netherlands, 2024) Mróz, T.; Shafee, S.; Crossa, J.; Montesinos-Lopez, O.A.; Lillemo, M.
Publication - A marker weighting approach for enhancing within-family accuracy in genomic prediction(Genetics Society of America, 2024) Montesinos-Lopez, O.A.; Crespo Herrera, L.A.; Xavier, A.; Gowda, M.; Beyene, Y.; Saint Pierre, C.; Rosa-Santamaria, R. de la; Salinas Ruiz, J.; Gerard, G.S.; Vitale, P.; Dreisigacker, S.; Lillemo, M.; Grignola, F.; Sarinelli, M.; Pozzo, E.; Quiroga, M.; Montesinos-Lopez, A.; Crossa, J.
Publication - Multi-environment genomic prediction of plant traits using deep learners with dense architecture(Genetics Society of America, 2018) Montesinos-Lopez, A.; Montesinos-Lopez, O.A.; Gianola, D.; Crossa, J.; Hernández Suárez, C.M.
Publication - Do feature selection methods for selecting environmental covariables enhance genomic prediction accuracy?(Frontiers Media S.A., 2023) Montesinos-Lopez, O.A.; Crespo Herrera, L.A.; Saint Pierre, C.; Bentley, A.R.; Rosa-Santamaria, R. de la; Ascencio-Laguna, J.A.; Agbona, A.; Gerard, G.S.; Montesinos-López, A.; Crossa, J.
Publication - A novel method for genomic-enabled prediction of cultivars in new environments(Frontiers Media S.A., 2023) Montesinos-Lopez, O.A.; Ramos-Pulido, S.; Hernández Suárez, C.M.; Mosqueda-Gonzalez, B.A.; Valladares-Anguiano, F.A.; Vitale, P.; Montesinos-López, A.; Crossa, J.
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