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Artigo de periodico
Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize (2023)
Gevartosky, Raysa ; Carvalho, Humberto Fanelli; Costa-Neto, Germano; Montesinos-López, Osval A ; Crossa, José; Fritsche-Neto, Roberto
Source: BMC Plant Biology. Unidade: ESALQ
Subjects: ALOCAÇÃO DE RECURSOS, INTERAÇÃO GENÓTIPO-AMBIENTE, GENÔMICA, MILHO, SELEÇÃO GENÉTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GEVARTOSKY, Raysa et al. Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize. BMC Plant Biology, v. 23, p. 1-20, 2023Tradução . . Disponível em: https://doi.org/10.1186/s12870-022-03975-1. Acesso em: 02 nov. 2024.
APA
Gevartosky, R., Carvalho, H. F., Costa-Neto, G., Montesinos-López, O. A., Crossa, J., & Fritsche-Neto, R. (2023). Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize. BMC Plant Biology, 23, 1-20. doi:10.1186/s12870-022-03975-1
NLM
Gevartosky R, Carvalho HF, Costa-Neto G, Montesinos-López OA, Crossa J, Fritsche-Neto R. Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize [Internet]. BMC Plant Biology. 2023 ; 23 1-20.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1186/s12870-022-03975-1
Vancouver
Gevartosky R, Carvalho HF, Costa-Neto G, Montesinos-López OA, Crossa J, Fritsche-Neto R. Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize [Internet]. BMC Plant Biology. 2023 ; 23 1-20.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1186/s12870-022-03975-1
Artigo de periodico
Enviromic prediction is useful to define the limits of climate adaptation: a case study of common bean in Brazil (2022)
Heinemann, Alexandre Bryan; Costa-Neto, Germano; Fritsche-Neto, Roberto ; Matta, David Henriques da; Fernandes, Igor Kuivjogi
Source: Field Crops Research. Unidade: ESALQ
Subjects: ADAPTAÇÃO AMBIENTAL, FEIJÃO, GERMOPLASMA VEGETAL, IMPACTOS AMBIENTAIS, MELHORAMENTO GENÉTICO VEGETAL, MODELOS MATEMÁTICOS, MUDANÇA CLIMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HEINEMANN, Alexandre Bryan et al. Enviromic prediction is useful to define the limits of climate adaptation: a case study of common bean in Brazil. Field Crops Research, v. 286, p. 1-19, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.fcr.2022.108628. Acesso em: 02 nov. 2024.
APA
Heinemann, A. B., Costa-Neto, G., Fritsche-Neto, R., Matta, D. H. da, & Fernandes, I. K. (2022). Enviromic prediction is useful to define the limits of climate adaptation: a case study of common bean in Brazil. Field Crops Research, 286, 1-19. doi:10.1016/j.fcr.2022.108628
NLM
Heinemann AB, Costa-Neto G, Fritsche-Neto R, Matta DH da, Fernandes IK. Enviromic prediction is useful to define the limits of climate adaptation: a case study of common bean in Brazil [Internet]. Field Crops Research. 2022 ; 286 1-19.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1016/j.fcr.2022.108628
Vancouver
Heinemann AB, Costa-Neto G, Fritsche-Neto R, Matta DH da, Fernandes IK. Enviromic prediction is useful to define the limits of climate adaptation: a case study of common bean in Brazil [Internet]. Field Crops Research. 2022 ; 286 1-19.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1016/j.fcr.2022.108628
Artigo de periodico
EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture (2021)
Costa-Neto, Germano ; Galli, Giovanni ; Carvalho, Humberto Fanelli ; Crossa, José ; Fritsche-Neto, Roberto
Source: G3: Genes | Genomes | Genetics. Unidade: ESALQ
Subjects: AGRICULTURA, GENÉTICA QUANTITATIVA, GENÔMICA, INTERAÇÃO GENÓTIPO-AMBIENTE, SOFTWARES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COSTA-NETO, Germano et al. EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture. G3: Genes | Genomes | Genetics, v. 11, n. 4, p. 1-20, 2021Tradução . . Disponível em: https://doi.org/10.1093/g3journal/jkab040. Acesso em: 02 nov. 2024.
APA
Costa-Neto, G., Galli, G., Carvalho, H. F., Crossa, J., & Fritsche-Neto, R. (2021). EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture. G3: Genes | Genomes | Genetics, 11( 4), 1-20. doi:10.1093/g3journal/jkab040
NLM
Costa-Neto G, Galli G, Carvalho HF, Crossa J, Fritsche-Neto R. EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture [Internet]. G3: Genes | Genomes | Genetics. 2021 ; 11( 4): 1-20.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1093/g3journal/jkab040
Vancouver
Costa-Neto G, Galli G, Carvalho HF, Crossa J, Fritsche-Neto R. EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture [Internet]. G3: Genes | Genomes | Genetics. 2021 ; 11( 4): 1-20.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1093/g3journal/jkab040

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