Search Results - Fritsche-Neto, Roberto

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

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Enviromics: bridging different sources of data, building one framework by 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 by 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 by 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 by 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 by 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 by 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... by Massahiro Yassue, Rafael, Galli, Giovanni, James Chen, Chun-Peng, Fritsche-Neto, Roberto, Morota, Gota

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Editorial: Enviromics in plant breeding by 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 by 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 by 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 by 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 by 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 by 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 by 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 by 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 by 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 by 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 by 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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