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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
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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: 05 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. 05 ] 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. 05 ] Available from: https://doi.org/10.1186/s12870-022-03975-1
Artigo de periodico
Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next breeding cycles (2023)
Fritsche-Neto, Roberto ; Sabadin, Felipe; Vale, Julio César do; Souza, Pedro Henrique; Borges, Karina Lima Reis; Crossa, Jose; Garbuglio, Deoclécio Domingos
Source: Crop Science. Unidade: ESALQ
Subjects: CROMOSSOMOS VEGETAIS, GENÉTICA DE POPULAÇÕES VEGETAIS, MELHORAMENTO GENÉTICO VEGETAL, MILHO, SELEÇÃO GENÉTICA, SIMULAÇÃO (ESTATÍSTICA)
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ABNT
FRITSCHE-NETO, Roberto et al. Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next breeding cycles. Crop Science, p. 1-12, 2023Tradução . . Disponível em: https://doi.org/10.1002/csc2.21081. Acesso em: 05 nov. 2024.
APA
Fritsche-Neto, R., Sabadin, F., Vale, J. C. do, Souza, P. H., Borges, K. L. R., Crossa, J., & Garbuglio, D. D. (2023). Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next breeding cycles. Crop Science, 1-12. doi:10.1002/csc2.21081
NLM
Fritsche-Neto R, Sabadin F, Vale JC do, Souza PH, Borges KLR, Crossa J, Garbuglio DD. Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next breeding cycles [Internet]. Crop Science. 2023 ; 1-12.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1002/csc2.21081
Vancouver
Fritsche-Neto R, Sabadin F, Vale JC do, Souza PH, Borges KLR, Crossa J, Garbuglio DD. Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next breeding cycles [Internet]. Crop Science. 2023 ; 1-12.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1002/csc2.21081
Artigo de periodico
Automated machine learning: a case study of genomic “image-based” prediction in maize hybrids (2022)
Galli, Giovanni ; Sabadin, F; Yassue, Rafael Massahiro ; Galves, C; Carvalho, H. F; Crossa, J; Montesinos-López, O. A; Fritsche-Neto, Roberto
Source: Frontiers in Plant Science. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, GENÔMICA, HIBRIDAÇÃO VEGETAL, MILHO, REDES NEURAIS
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GALLI, Giovanni et al. Automated machine learning: a case study of genomic “image-based” prediction in maize hybrids. Frontiers in Plant Science, v. 13, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.3389/fpls.2022.845524. Acesso em: 05 nov. 2024.
APA
Galli, G., Sabadin, F., Yassue, R. M., Galves, C., Carvalho, H. F., Crossa, J., et al. (2022). Automated machine learning: a case study of genomic “image-based” prediction in maize hybrids. Frontiers in Plant Science, 13, 1-13. doi:10.3389/fpls.2022.845524
NLM
Galli G, Sabadin F, Yassue RM, Galves C, Carvalho HF, Crossa J, Montesinos-López OA, Fritsche-Neto R. Automated machine learning: a case study of genomic “image-based” prediction in maize hybrids [Internet]. Frontiers in Plant Science. 2022 ; 13 1-13.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2022.845524
Vancouver
Galli G, Sabadin F, Yassue RM, Galves C, Carvalho HF, Crossa J, Montesinos-López OA, Fritsche-Neto R. Automated machine learning: a case study of genomic “image-based” prediction in maize hybrids [Internet]. Frontiers in Plant Science. 2022 ; 13 1-13.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2022.845524
Artigo de periodico
Partial least squares enhances genomic prediction of new environments (2022)
Montesinos-López, Osval A; Montesinos-López, Abelardo; Kismiantini; Roman-Gallardo, Armando; Gardner, Keith; Lillemo, Morten; Fritsche-Neto, Roberto ; Crossa, José
Source: Frontiers in Genetics. Unidade: ESALQ
Subjects: GENÔMICA, INFERÊNCIA BAYESIANA, INTERAÇÃO GENÓTIPO-AMBIENTE, MELHORAMENTO GENÉTICO VEGETAL, MILHO, MÍNIMOS QUADRADOS, SELEÇÃO GENÉTICA, TRIGO
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MONTESINOS-LÓPEZ, Osval A et al. Partial least squares enhances genomic prediction of new environments. Frontiers in Genetics, v. 13, p. 1-17, 2022Tradução . . Disponível em: https://doi.org/10.3389/fgene.2022.920689. Acesso em: 05 nov. 2024.
APA
Montesinos-López, O. A., Montesinos-López, A., Kismiantini,, Roman-Gallardo, A., Gardner, K., Lillemo, M., et al. (2022). Partial least squares enhances genomic prediction of new environments. Frontiers in Genetics, 13, 1-17. doi:10.3389/fgene.2022.920689
NLM
Montesinos-López OA, Montesinos-López A, Kismiantini, Roman-Gallardo A, Gardner K, Lillemo M, Fritsche-Neto R, Crossa J. Partial least squares enhances genomic prediction of new environments [Internet]. Frontiers in Genetics. 2022 ; 13 1-17.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fgene.2022.920689
Vancouver
Montesinos-López OA, Montesinos-López A, Kismiantini, Roman-Gallardo A, Gardner K, Lillemo M, Fritsche-Neto R, Crossa J. Partial least squares enhances genomic prediction of new environments [Internet]. Frontiers in Genetics. 2022 ; 13 1-17.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fgene.2022.920689
Artigo de periodico
Trends of extreme air temperature and precipitation and their impact on corn and soybean yields in Nebraska, USA (2022)
Santos, Carlos A. C. dos ; Neale, Christopher M. U; Mekonnen, Mesfin M; Gonçalves, Ivo Zution; Oliveira, Gabriel de; Ruiz‑Alvarez, Osias; Safa, Babak; Rowe, Clinton M
Source: Theoretical and Applied Climatology. Unidade: ESALQ
Subjects: AQUECIMENTO GLOBAL, CULTIVO DE SEQUEIRO, MILHO, MUDANÇA CLIMÁTICA, PRECIPITAÇÃO ATMOSFÉRICA, PRODUÇÃO AGRÍCOLA, SOJA, TEMPERATURAS EXTREMAS
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SANTOS, Carlos A. C. dos et al. Trends of extreme air temperature and precipitation and their impact on corn and soybean yields in Nebraska, USA. Theoretical and Applied Climatology, 2022Tradução . . Disponível em: https://doi.org/10.1007/s00704-021-03903-7. Acesso em: 05 nov. 2024.
APA
Santos, C. A. C. dos, Neale, C. M. U., Mekonnen, M. M., Gonçalves, I. Z., Oliveira, G. de, Ruiz‑Alvarez, O., et al. (2022). Trends of extreme air temperature and precipitation and their impact on corn and soybean yields in Nebraska, USA. Theoretical and Applied Climatology. doi:10.1007/s00704-021-03903-7
NLM
Santos CAC dos, Neale CMU, Mekonnen MM, Gonçalves IZ, Oliveira G de, Ruiz‑Alvarez O, Safa B, Rowe CM. Trends of extreme air temperature and precipitation and their impact on corn and soybean yields in Nebraska, USA [Internet]. Theoretical and Applied Climatology. 2022 ;[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00704-021-03903-7
Vancouver
Santos CAC dos, Neale CMU, Mekonnen MM, Gonçalves IZ, Oliveira G de, Ruiz‑Alvarez O, Safa B, Rowe CM. Trends of extreme air temperature and precipitation and their impact on corn and soybean yields in Nebraska, USA [Internet]. Theoretical and Applied Climatology. 2022 ;[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00704-021-03903-7
Artigo de periodico
Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America (2022)
Costa, Flaviane Malaquias ; Silva, Natalia Carolina de Almeida; Vidal, Rafael; Clement, Charles Roland; Freitas, Fabio de Oliveira; Alves-Pereira, Alessandro; Petroli, César Daniel; Zucchi, Maria Imaculada; Ann-Veasey, Elizabeth
Source: Annals of Botany. Unidade: ESALQ
Subjects: DIVERSIDADE GENÉTICA, DOMESTICAÇÃO DE PLANTAS, MARCADOR MOLECULAR, MILHO, POLIMORFISMO, VARIEDADES VEGETAIS
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COSTA, Flaviane Malaquias et al. Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America. Annals of Botany, v. 20, p. 1-15, 2022Tradução . . Disponível em: https://doi.org/10.1093/aob/mcac049. Acesso em: 05 nov. 2024.
APA
Costa, F. M., Silva, N. C. de A., Vidal, R., Clement, C. R., Freitas, F. de O., Alves-Pereira, A., et al. (2022). Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America. Annals of Botany, 20, 1-15. doi:10.1093/aob/mcac049
NLM
Costa FM, Silva NC de A, Vidal R, Clement CR, Freitas F de O, Alves-Pereira A, Petroli CD, Zucchi MI, Ann-Veasey E. Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America [Internet]. Annals of Botany. 2022 ; 20 1-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1093/aob/mcac049
Vancouver
Costa FM, Silva NC de A, Vidal R, Clement CR, Freitas F de O, Alves-Pereira A, Petroli CD, Zucchi MI, Ann-Veasey E. Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America [Internet]. Annals of Botany. 2022 ; 20 1-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1093/aob/mcac049
Artigo de periodico
Introgression of maize diversity for drought tolerance: subtropical maize landraces as source of new positive variants (2021)
Barbosa, Pedro Augusto Medeiros; Fritsche-Neto, Roberto ; Andrade, Marcela Carvalho; Petroli, César Daniel; Burgueño, Juan; Galli, Giovanni ; Willcox, Martha C; Sonder, Kai; Vidal-Martínez, Víctor A; Sifuentes-Ibarra, Ernesto; Molnar, Terence Luke
Source: Frontiers in Plant Science. Unidade: ESALQ
Subjects: MILHO, MARCADOR MOLECULAR, SECA, CRUZAMENTO VEGETAL, DIVERSIDADE GENÉTICA, BIODIVERSIDADE
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BARBOSA, Pedro Augusto Medeiros et al. Introgression of maize diversity for drought tolerance: subtropical maize landraces as source of new positive variants. Frontiers in Plant Science, v. 12, p. 1-19, 2021Tradução . . Disponível em: https://doi.org/10.3389/fpls.2021.691211. Acesso em: 05 nov. 2024.
APA
Barbosa, P. A. M., Fritsche-Neto, R., Andrade, M. C., Petroli, C. D., Burgueño, J., Galli, G., et al. (2021). Introgression of maize diversity for drought tolerance: subtropical maize landraces as source of new positive variants. Frontiers in Plant Science, 12, 1-19. doi:10.3389/fpls.2021.691211
NLM
Barbosa PAM, Fritsche-Neto R, Andrade MC, Petroli CD, Burgueño J, Galli G, Willcox MC, Sonder K, Vidal-Martínez VA, Sifuentes-Ibarra E, Molnar TL. Introgression of maize diversity for drought tolerance: subtropical maize landraces as source of new positive variants [Internet]. Frontiers in Plant Science. 2021 ; 12 1-19.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2021.691211
Vancouver
Barbosa PAM, Fritsche-Neto R, Andrade MC, Petroli CD, Burgueño J, Galli G, Willcox MC, Sonder K, Vidal-Martínez VA, Sifuentes-Ibarra E, Molnar TL. Introgression of maize diversity for drought tolerance: subtropical maize landraces as source of new positive variants [Internet]. Frontiers in Plant Science. 2021 ; 12 1-19.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2021.691211
Artigo de periodico
Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize (2021)
Costa-Neto, Germano; Crossa, Jose; Fritsche-Neto, Roberto
Source: Frontiers in Plant Science. Unidade: ESALQ
Subjects: MILHO, GENÔMICA, INTERAÇÃO GENÓTIPO-AMBIENTE, GENÉTICA QUANTITATIVA, FENÓTIPOS, CLIMA
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ABNT
COSTA-NETO, Germano e CROSSA, Jose e FRITSCHE-NETO, Roberto. Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize. Frontiers in Plant Science, v. 12, p. 1-21, 2021Tradução . . Disponível em: https://doi.org/10.3389/fpls.2021.717552. Acesso em: 05 nov. 2024.
APA
Costa-Neto, G., Crossa, J., & Fritsche-Neto, R. (2021). Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize. Frontiers in Plant Science, 12, 1-21. doi:10.3389/fpls.2021.717552
NLM
Costa-Neto G, Crossa J, Fritsche-Neto R. Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize [Internet]. Frontiers in Plant Science. 2021 ; 12 1-21.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2021.717552
Vancouver
Costa-Neto G, Crossa J, Fritsche-Neto R. Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize [Internet]. Frontiers in Plant Science. 2021 ; 12 1-21.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2021.717552
Artigo de periodico
Optimizing genomic-enabled prediction in small-scale maize hHybrid breeding programs: a roadmap review (2021)
Fritsche Neto, Roberto ; Galli, Giovanni ; Borges, Karina Lima Reis ; Costa Neto, Germano Martins Ferreira ; Alves, Filipe Couto; Sabadin, Felipe; Lyra, Danilo Hottis; Morais, Pedro Patric Pinho; Braatz de Andrade, Luciano Rogerio; Granato, Italo; Crossa, Jose
Source: Frontiers in Plant Science. Unidade: ESALQ
Subjects: GENÔMICA, HIBRIDAÇÃO VEGETAL, MELHORAMENTO GENÉTICO VEGETAL, MILHO, SELEÇÃO GENÉTICA
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ABNT
FRITSCHE NETO, Roberto et al. Optimizing genomic-enabled prediction in small-scale maize hHybrid breeding programs: a roadmap review. Frontiers in Plant Science, p. 1-16, 2021Tradução . . Disponível em: https://doi.org/10.3389/fpls.2021.658267. Acesso em: 05 nov. 2024.
APA
Fritsche Neto, R., Galli, G., Borges, K. L. R., Costa Neto, G. M. F., Alves, F. C., Sabadin, F., et al. (2021). Optimizing genomic-enabled prediction in small-scale maize hHybrid breeding programs: a roadmap review. Frontiers in Plant Science, 1-16. doi:10.3389/fpls.2021.658267
NLM
Fritsche Neto R, Galli G, Borges KLR, Costa Neto GMF, Alves FC, Sabadin F, Lyra DH, Morais PPP, Braatz de Andrade LR, Granato I, Crossa J. Optimizing genomic-enabled prediction in small-scale maize hHybrid breeding programs: a roadmap review [Internet]. Frontiers in Plant Science. 2021 ; 1-16.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2021.658267
Vancouver
Fritsche Neto R, Galli G, Borges KLR, Costa Neto GMF, Alves FC, Sabadin F, Lyra DH, Morais PPP, Braatz de Andrade LR, Granato I, Crossa J. Optimizing genomic-enabled prediction in small-scale maize hHybrid breeding programs: a roadmap review [Internet]. Frontiers in Plant Science. 2021 ; 1-16.[citado 2024 nov. 05 ] Available from: https://doi.org/10.3389/fpls.2021.658267
Artigo de periodico
Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials (2020)
Costa Neto, Germano Martins Ferreira ; Fritsche Neto, Roberto ; Crossa, José
Source: Heredity. Unidade: ESALQ
Subjects: GENOMAS, GENÔMICA, INTERAÇÃO GENÓTIPO-AMBIENTE, MILHO, MODELOS MATEMÁTICOS
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ABNT
COSTA NETO, Germano Martins Ferreira e FRITSCHE NETO, Roberto e CROSSA, José. Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials. Heredity, p. 1-15, 2020Tradução . . Disponível em: https://doi.org/10.1038/s41437-020-00353-1. Acesso em: 05 nov. 2024.
APA
Costa Neto, G. M. F., Fritsche Neto, R., & Crossa, J. (2020). Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials. Heredity, 1-15. doi:10.1038/s41437-020-00353-1
NLM
Costa Neto GMF, Fritsche Neto R, Crossa J. Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials [Internet]. Heredity. 2020 ; 1-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1038/s41437-020-00353-1
Vancouver
Costa Neto GMF, Fritsche Neto R, Crossa J. Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials [Internet]. Heredity. 2020 ; 1-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1038/s41437-020-00353-1
Artigo de periodico
Modeling copy number variation in the genomic prediction of maize hybrids (2019)
Lyra, Danilo Hottis; Galli, Giovanni; Alves, Filipe Couto; Granato, Ítalo Stefanine Correia; Vidotti, Miriam Suzane; Bandeira e Sousa, Massaine; Morosini, Júlia Silva; Crossa, José; Fritsche-Neto, Roberto
Source: Theoretical and Applied Genetics. Unidade: ESALQ
Subjects: MILHO, HIBRIDAÇÃO VEGETAL, GENÔMICA, MARCADOR MOLECULAR, VARIAÇÃO GENÉTICA EM PLANTAS
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LYRA, Danilo Hottis et al. Modeling copy number variation in the genomic prediction of maize hybrids. Theoretical and Applied Genetics, v. 132, p. 273-288, 2019Tradução . . Disponível em: https://doi.org/10.1007/s00122-018-3215-2. Acesso em: 05 nov. 2024.
APA
Lyra, D. H., Galli, G., Alves, F. C., Granato, Í. S. C., Vidotti, M. S., Bandeira e Sousa, M., et al. (2019). Modeling copy number variation in the genomic prediction of maize hybrids. Theoretical and Applied Genetics, 132, 273-288. doi:10.1007/s00122-018-3215-2
NLM
Lyra DH, Galli G, Alves FC, Granato ÍSC, Vidotti MS, Bandeira e Sousa M, Morosini JS, Crossa J, Fritsche-Neto R. Modeling copy number variation in the genomic prediction of maize hybrids [Internet]. Theoretical and Applied Genetics. 2019 ; 132 273-288.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00122-018-3215-2
Vancouver
Lyra DH, Galli G, Alves FC, Granato ÍSC, Vidotti MS, Bandeira e Sousa M, Morosini JS, Crossa J, Fritsche-Neto R. Modeling copy number variation in the genomic prediction of maize hybrids [Internet]. Theoretical and Applied Genetics. 2019 ; 132 273-288.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00122-018-3215-2
Artigo de periodico
Effect of F-1 and F-2 generations on genetic variability and working steps of doubled haploid production in maize (2019)
Couto, Evellyn Giselly de Oliveira ; Cury, Mayara Neves; Souza, Massaine Bandeira e ; Granato, Italo Stefanine Correia ; Vidotti, Miriam Suzane ; Garbuglio, Deoclecio Domingos; Crossa, Jose; Burgueno, Juan; Fritsche-Neto, Roberto
Source: PLOS ONE. Unidade: ESALQ
Subjects: MILHO, CÉLULAS VEGETAIS, CROMOSSOMOS VEGETAIS, CRUZAMENTO VEGETAL, MELHORAMENTO GENÉTICO VEGETAL, VARIAÇÃO GENÉTICA EM PLANTAS
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COUTO, Evellyn Giselly de Oliveira et al. Effect of F-1 and F-2 generations on genetic variability and working steps of doubled haploid production in maize. PLOS ONE, p. 1-16, 2019Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0224631. Acesso em: 05 nov. 2024.
APA
Couto, E. G. de O., Cury, M. N., Souza, M. B. e, Granato, I. S. C., Vidotti, M. S., Garbuglio, D. D., et al. (2019). Effect of F-1 and F-2 generations on genetic variability and working steps of doubled haploid production in maize. PLOS ONE, 1-16. doi:10.1371/journal.pone.0224631
NLM
Couto EG de O, Cury MN, Souza MB e, Granato ISC, Vidotti MS, Garbuglio DD, Crossa J, Burgueno J, Fritsche-Neto R. Effect of F-1 and F-2 generations on genetic variability and working steps of doubled haploid production in maize [Internet]. PLOS ONE. 2019 ; 1-16.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1371/journal.pone.0224631
Vancouver
Couto EG de O, Cury MN, Souza MB e, Granato ISC, Vidotti MS, Garbuglio DD, Crossa J, Burgueno J, Fritsche-Neto R. Effect of F-1 and F-2 generations on genetic variability and working steps of doubled haploid production in maize [Internet]. PLOS ONE. 2019 ; 1-16.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1371/journal.pone.0224631
Artigo de periodico
Maize responsiveness to Azospirillum brasilense: insights into genetic control, heterosis and genomic prediction (2019)
Vidotti, Miriam Suzane ; Matias, Filipe Inácio ; Alves, Filipe Couto; Pérez-Rodríguez, Paulino; Beltran, Gregório Alvarado; Burgueño, Juan; Crossa, José; Fritsche-Neto, Roberto
Source: PLOS ONE. Unidade: ESALQ
Subjects: BACTÉRIAS FIXADORAS DE NITROGÊNIO, CONTROLE GENÉTICO, ESTIMULANTES DE CRESCIMENTO VEGETAL, GENÔMICA, HETEROSE, MILHO
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VIDOTTI, Miriam Suzane et al. Maize responsiveness to Azospirillum brasilense: insights into genetic control, heterosis and genomic prediction. PLOS ONE, p. 1-22, 2019Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0217571. Acesso em: 05 nov. 2024.
APA
Vidotti, M. S., Matias, F. I., Alves, F. C., Pérez-Rodríguez, P., Beltran, G. A., Burgueño, J., et al. (2019). Maize responsiveness to Azospirillum brasilense: insights into genetic control, heterosis and genomic prediction. PLOS ONE, 1-22. doi:10.1371/journal.pone.0217571
NLM
Vidotti MS, Matias FI, Alves FC, Pérez-Rodríguez P, Beltran GA, Burgueño J, Crossa J, Fritsche-Neto R. Maize responsiveness to Azospirillum brasilense: insights into genetic control, heterosis and genomic prediction [Internet]. PLOS ONE. 2019 ; 1-22.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1371/journal.pone.0217571
Vancouver
Vidotti MS, Matias FI, Alves FC, Pérez-Rodríguez P, Beltran GA, Burgueño J, Crossa J, Fritsche-Neto R. Maize responsiveness to Azospirillum brasilense: insights into genetic control, heterosis and genomic prediction [Internet]. PLOS ONE. 2019 ; 1-22.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1371/journal.pone.0217571
Artigo de periodico
Effect of F1 and F2 generations on genetic variability and working steps of doubled haploid production in maize (2019)
Couto, Evellyn Giselly de Oliveira ; Cury, Mayara Neves; Souza, Massaine Bandeira e; Granato, Ítalo Stefanine Correia ; Vidotti, Miriam Suzane ; Garbuglio, Deoclécio Domingos; Crossa, José; Burgueño, Juan; Fritsche-Neto, Roberto
Source: PLOS ONE. Unidade: ESALQ
Subjects: CÉLULAS VEGETAIS, CROMOSSOMOS VEGETAIS, CRUZAMENTO VEGETAL, MILHO, VARIAÇÃO GENÉTICA EM PLANTAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COUTO, Evellyn Giselly de Oliveira et al. Effect of F1 and F2 generations on genetic variability and working steps of doubled haploid production in maize. PLOS ONE, p. 1-16, 2019Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0224631. Acesso em: 05 nov. 2024.
APA
Couto, E. G. de O., Cury, M. N., Souza, M. B. e, Granato, Í. S. C., Vidotti, M. S., Garbuglio, D. D., et al. (2019). Effect of F1 and F2 generations on genetic variability and working steps of doubled haploid production in maize. PLOS ONE, 1-16. doi:10.1371/journal.pone.0224631
NLM
Couto EG de O, Cury MN, Souza MB e, Granato ÍSC, Vidotti MS, Garbuglio DD, Crossa J, Burgueño J, Fritsche-Neto R. Effect of F1 and F2 generations on genetic variability and working steps of doubled haploid production in maize [Internet]. PLOS ONE. 2019 ; 1-16.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1371/journal.pone.0224631
Vancouver
Couto EG de O, Cury MN, Souza MB e, Granato ÍSC, Vidotti MS, Garbuglio DD, Crossa J, Burgueño J, Fritsche-Neto R. Effect of F1 and F2 generations on genetic variability and working steps of doubled haploid production in maize [Internet]. PLOS ONE. 2019 ; 1-16.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1371/journal.pone.0224631
Artigo de periodico
Genomic-enabled prediction in maize using Kernel models with genotype × environment interaction (2017)
Souza, Massaine Bandeira e; Cuevas, Jaime; Couto, Evellyn Giselly de Oliveira; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose
Source: G3: Genes, Genomes, Genetics. Unidade: ESALQ
Subjects: INTERAÇÃO GENÓTIPO-AMBIENTE, GENÔMICA, MILHO, MODELOS MATEMÁTICOS, SELEÇÃO GENÉTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, Massaine Bandeira e et al. Genomic-enabled prediction in maize using Kernel models with genotype × environment interaction. G3: Genes, Genomes, Genetics, v. 7, n. 6, p. 1995-2014, 2017Tradução . . Disponível em: https://doi.org/10.1534/g3.117.042341. Acesso em: 05 nov. 2024.
APA
Souza, M. B. e, Cuevas, J., Couto, E. G. de O., Pérez-Rodríguez, P., Jarquín, D., Fritsche-Neto, R., et al. (2017). Genomic-enabled prediction in maize using Kernel models with genotype × environment interaction. G3: Genes, Genomes, Genetics, 7( 6), 1995-2014. doi:10.1534/g3.117.042341
NLM
Souza MB e, Cuevas J, Couto EG de O, Pérez-Rodríguez P, Jarquín D, Fritsche-Neto R, Burgueño J, Crossa J. Genomic-enabled prediction in maize using Kernel models with genotype × environment interaction [Internet]. G3: Genes, Genomes, Genetics. 2017 ; 7( 6): 1995-2014.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1534/g3.117.042341
Vancouver
Souza MB e, Cuevas J, Couto EG de O, Pérez-Rodríguez P, Jarquín D, Fritsche-Neto R, Burgueño J, Crossa J. Genomic-enabled prediction in maize using Kernel models with genotype × environment interaction [Internet]. G3: Genes, Genomes, Genetics. 2017 ; 7( 6): 1995-2014.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1534/g3.117.042341

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