Person: Fritsche-Neto, R.
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Fritsche-Neto
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R.
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Fritsche-Neto, R.
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0000-0003-4310-0047 21 results
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- Feature engineering of environmental covariates improves plant genomic-enabled prediction(Frontiers Media S.A., 2024) Montesinos-Lopez, O.A.; Crespo-Herrera, L.A.; Saint Pierre, C.; Cano-Paez, B.; Huerta Prado, G.I.; Mosqueda-Gonzalez, B.A.; Ramos-Pulido, S.; Gerard, G.S.; Khalid Alnowibet; Fritsche-Neto, R.; Montesinos-Lopez, A.; Crossa, J.
Publication - Data augmentation enhances plant-genomic-enabled predictions(MDPI, 2024) Montesinos-Lopez, O.A.; Solis-Camacho, M.A.; Crespo Herrera, L.A.; Saint Pierre, C.; Huerta Prado, G.I.; Ramos-Pulido, S.; Khalid Al-Nowibet; Fritsche-Neto, R.; Gerard, G.S.; Montesinos-Lopez, A.; Crossa, J.
Publication - Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance(Springer, 2024) Fritsche-Neto, R.; Ali, J.; De Asis, E.J.; Allahgholipour, M.; Labroo, M.
Publication - Effect of F1 and F2 generations on genetic variability and working steps of doubled haploid production in maize(Public Library of Science, 2019) Couto, E.; Cury, M.N.; Bandeira e Sousa, M.; Granato, I.; Vidotti, M.S.; Garbuglio, D.D.; Crossa, J.; Burgueño, J.; Fritsche-Neto, R.
Publication - Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical maize(BioMed Central, 2023) Gevartosky, R.; Fanelli Carvalho, H.; Costa-Neto, G.; Montesinos-Lopez, O.A.; Crossa, J.; Fritsche-Neto, R.
Publication - Envirome-wide associations enhance multi-year genome-based prediction of historical wheat breeding data(Genetics Society of America, 2023) Costa-Neto, G.; Crespo Herrera, L.A.; Fradgley, N.; Gardner, K.A.; Bentley, A.R.; Dreisigacker, S.; Fritsche-Neto, R.; Montesinos-Lopez, O.A.; Crossa, J.
Publication - Partial least squares enhances genomic prediction of new environments(Frontiers, 2022) Montesinos-Lopez, O.A.; Montesinos-López, A.; Kismiantini; Roman-Gallardo, A.; Gardner, K.A.; Lillemo, M.; Fritsche-Neto, R.; Crossa, J.
Publication - Chapter 9. Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction(Humana Press Inc., 2022) Crossa, J.; Montesinos-Lopez, O.A.; Pérez-Rodríguez, P.; Costa-Neto, G.; Fritsche-Neto, R.; Ortiz, R.; Martini, J.W.R.; Lillemo, M.; Montesinos-López, A.; Jarquin, D.; Breseghello, F.; Cuevas, J.; Rincent, R.
Publication - Automated Machine Learning: A Case Study of Genomic “Image-Based” Prediction in Maize Hybrids(Frontiers, 2022) Galli, G.; Sabadin, F.; Yassue, R.M.; Galves, C.; Fanelli Carvalho, H.; Crossa, J.; Montesinos-Lopez, O.A.; Fritsche-Neto, R.
Publication - Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize(Frontiers, 2021) Costa-Neto, G.; Crossa, J.; Fritsche-Neto, R.
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