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

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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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Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced software por Crossa, José, Martini, Johannes W.R., Vitale, Paolo, Perez-Rodriguez, Paulino, Costa-Neto, Germano, Fritsche-Neto, Roberto, Runcie, Daniel E., Cuevas, Jaime, Toledo, Fernando H., Huihui Li, De Vita, Pasquale, Gerard, Guillermo S., Dreisigacker, Susanne, Crespo-Herrera, Leonardo A., Saint Pierre, Carolina, Bentley, Alison R., Lillemo, Morten, Ortiz, Rodomiro, Montesinos-Lopez, Osval A., Montesinos-López, Abelardo

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