Resultados de búsqueda - Fritsche-Neto, Roberto

Optimizing QTL introgression via stochastic simulations: an example of the IRRI rice breeding program por Platten, John Damien, Fritsche-Neto, Roberto

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Optimizing quantitative trait loci introgression in elite rice germplasms: Comparing methods and population sizes to develop new recipients via stochastic simulations por Platten, John Damien, Fritsche-Neto, Roberto

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Enviromics: bridging different sources of data, building one framework por Costa-Neto, Germano, Fritsche-Neto, Roberto

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Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize por Costa-Neto, Germano, Crossa, José, Fritsche-Neto, Roberto

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Classification of plant growth‐promoting bacteria inoculation status and prediction of growth‐related traits in tropical maize using hyperspectral image and genomic data por Yassue, Rafael Massahiro, Galli, Giovanni, Fritsche-Neto, Roberto, Morota, Gota

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Optimizing self-pollinated crop breeding employing genomic selection: From schemes to updating training sets por Sabadin, Felipe, César DoVale, Julio, Platten, John Damien, Fritsche-Neto, Roberto

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EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture por Costa-Neto, Germano, Galli, Giovanni, Carvalho, Humberto Fanelli, Crossa, José, Fritsche-Neto, Roberto

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Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance por Fritsche-Neto, Roberto, Ali, Jauhar, De Asis, Erik Jon, Allahgholipour, Mehrzad, Labroo, Marlee Rose

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Genome-wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth-related traits in maize under plant growth-promoting bacteria inocu... por Massahiro Yassue, Rafael, Galli, Giovanni, James Chen, Chun-Peng, Fritsche-Neto, Roberto, Morota, Gota

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Editorial: Enviromics in plant breeding por Resende, Rafael Tassinari, Chenu, Karine, Rasmussen, Soren K., Heinemann, Alexandre Bryan, Fritsche-Neto, Roberto

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A heterochromatic knob reducing the flowering time in maize por Carvalho, Renata Flávia, Aguiar-Perecin, Margarida Lopes Rodrigues, Clarindo, Wellington Ronildo, Fritsche-Neto, Roberto, Mondin, Mateus

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Enviromic prediction is useful to define the limits of climate adaptation: A case study of common bean in Brazil por Heinemann, Alexandre Bryan, Costa-Neto, Germano, Fritsche-Neto, Roberto, da Matta, David Henriques, Fernandes, Igor Kuivjogi

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Automated machine learning: A case study of genomic "image-based" prediction in maize hybrids por Galli, Giovanni, Sabadin, Felipe, Yassue, Rafael Massahiro, Galves, Cassia, Carvalho, Humberto Fanelli, Crossa, José, Montesinos-López, Osval Antonio, Fritsche-Neto, Roberto

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Envirome-wide associations enhance multi-year genome-based prediction of historical wheat breeding data por Costa Neto, Germano, Crespo-Herrera, Leonardo A., Fradgley, Nick, Gardner, Keith A., Bentley, Alison R., Dreisigacker, Susanne, Fritsche-Neto, Roberto, Montesinos López, Osval A., Crossa, José

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A review of multimodal deep learning methods for genomic-enabled prediction in plant breeding por Montesinos-Lopez, Osval A., Chavira-Flores, Moises, Kismiantini, Crespo-Herrera, Leonardo A., Saint Pierre, Carolina, Huihui Li, Fritsche-Neto, Roberto, Khalid Al-Nowibet, Montesinos-Lopez, Abelardo, Crossa, José

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Steady agronomic and genetic interventions are essential for sustaining productivity in intensive rice cropping por Ladha, Jagdish K., Radanielson, Ando M., Rutkoski, Jessica Elaine, Buresh, Roland J., Dobermann, Achim, Angeles, Olivyn, Pabuayon, Irish Lorraine B., Santos-Medellín, Christian, Fritsche-Neto, Roberto, Chivenge, Pauline, Kohli, Ajay

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Genetic trends estimation in IRRIs rice drought breeding program and identification of high yielding drought-tolerant lines por Khanna, Apurva, Anumalla, Mahender, Catolos, Margaret, Bartholomé, Jérôme, Fritsche-Neto, Roberto, Platten, John Damien, Pisano, Daniel Joseph, Gulles, Alaine, Sta. Cruz, Ma Teresa, Ramos, Joie M., Faustino, Gem, Bhosale, Sankalp, Hussain, Waseem

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Data augmentation enhances plant-genomic-enabled predictions por Montesinos-Lopez, Osval A., Solis-Camacho, Mario Alberto, Crespo Herrera, Leonardo A., Saint Pierre, Carolina, Huerta Prado, Gloria Isabel, Ramos-Pulido, Sofia, Al-Nowibet, Khalid, Fritsche-Neto, Roberto, Gerard, Guillermo S., Montesinos-Lopez, Abelardo, Crossa, José

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Feature engineering of environmental covariates improves plant genomic-enabled prediction por Montesinos-Lopez, Osval A., Crespo-Herrera, Leonardo A., Saint Pierre, Carolina, Cano-Paez, Bernabe, Huerta Prado, Gloria Isabel, Mosqueda-Gonzalez, Brandon Alejandro, Ramos-Pulido, Sofia, Gerard, Guillermo S., Khalid Alnowibet, Fritsche-Neto, Roberto, Montesinos-Lopez, Abelardo, Crossa, José

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Machine learning algorithms translate big data into predictive breeding accuracy por Crossa, José, Montesinos-Lopez, Osval A., Costa-Neto, Germano, Vitale, Paolo, Martini, Johannes W.R., Runcie, Daniel E., Fritsche-Neto, Roberto, Montesinos-Lopez, Abelardo, Perez-Rodriguez, Paulino, Gerard, Guillermo S., Dreisigacker, Susanna, Crespo-Herrera, Leonardo A., Saint Pierre, Carolina, Lillemo, Morten, Cuevas, Jaime, Bentley, Alison R., Ortiz, Rodomiro

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