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| 4. |  | GUARÇONI M., A.; BURAK, D. L.; SOUZA, G. S. de. Tema: solo, água e agricultura de baixo carbono. In: CONGRESSO CAPIXABA DE PESQUISA AGROPECUÁRIA, 1., Vitória, ES. Anais 2021 : congresso capixaba de pesquisa agropecuária [recurso eletrônico]. Vitória, ES: Incaper, 2021. color. PDF ; 25,4 MB.
E-book, no formato PDF. (Incaper, Documentos, 289). Pedro Luís Pereira Teixeira de Carvalho, Carlos Henrique Rodrigues de Oliveira, José Aires Ventura, Marcos Vinicius Winckler Caldeira e Romário Gava Ferrão, editores. p. 77-78| Biblioteca(s): Biblioteca Rui Tendinha. |
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| 6. | | KROHLING, C. A.; LANI, J. A.; SOUZA, G. S. de.; APOSTÓLICO, M. A. Colheita semimecanizada de café arábica na região das montanhas capixabas. In: CONGRESSO BRASILEIRO DE PESQUISAS CAFEEIRAS, 44., 2018, Franca, SP. Nosso café, melhorado desde o pé: anais... Brasília, DF: Embrapa Café, 2018.| Biblioteca(s): Biblioteca Rui Tendinha. |
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| 10. | | OLIVEIRA, P. A.; SOUZA, G. S. de.; PEREIRA, L. L.; SOUZA, T. da S. de. Produtividade e qualidade de bebida do café conilon consorciado e a pleno sol. In: SEMINÁRIO DE INICIAÇÃO CIENTÍFICA E TECNOLÓGICA (SICT) DO INCAPER, 2., 2017. JORNADA DE INICIAÇÃO CIENTÍFICA, DESENVOLVIMENTO TECNOLÓGICO E INOVAÇÃO DO IFES, 12., 2017. Colatina, ES : IFES; Incaper, 2017. Resumo.| Biblioteca(s): Biblioteca Rui Tendinha. |
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| 15. | | ALVES, D. I.; ALTOÉ, M. S.; SOUZA, G. S. de.; SILVA, S. de A.; LIMA, J. S. de S. Análise de agrupamento de atributos físicos do solo em lavoura de cafeeiro conilon consorciado. In: REVISTA UNIVAP, São José dos Campos, v. 22, n. 40, 2016. Número especial da Revista UNIVAP Online, com o resumo de todos os artigos os melhores artigos de cada área do XX Encontro de Iniciação Científica, XVI Encontro de Pós-Graduação, X INIC Jr da UNIVAP, VI INID. Resumo.| Biblioteca(s): Biblioteca Rui Tendinha. |
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| 19. | | SOUZA, G. S. de.; LANI, J. A.; INFANTINI, M. B.; KROHLING, C. A.; SENRA, J. F. de B. Comportamento de clones em diferentes velocidades da máquina na colheita de café conilon. In: CONGRESSO CAPIXABA DE PESQUISA AGROPECUÁRIA, 1., Vitória, ES. Anais 2021 : congresso capixaba de pesquisa agropecuária [recurso eletrônico]. Vitória, ES: Incaper, 2021. color. PDF ; 25,4 MB. E-book, no formato PDF. (Incaper, Documentos, 289). Pedro Luís Pereira Teixeira de Carvalho, Carlos Henrique Rodrigues de Oliveira, José Aires Ventura, Marcos Vinicius Winckler Caldeira e Romário Gava Ferrão, editores. p. 110| Biblioteca(s): Biblioteca Rui Tendinha. |
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| 20. | | CHAVES, I. de S.; RODRIGUES, W. P.; MACHADO FILHO, J. A.; SOUZA, G. S. de.; DOUSSEAU, S. Conilon em sistemas agroflorestais. In: PARTELLI, F. L.; MORAES, W. B. (Ed.). Café conilon : qualidade e sucessão familiar. Alegre, ES CAUFES, p. 157-170, 2018.| Biblioteca(s): Biblioteca Rui Tendinha. |
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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
29/11/2016 |
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Data da última atualização: |
28/09/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
COSTA, A. F. da.; TEODORO, P. E.; BHERING, L.L.; LEAL, N. R.; TARDIN, F. D.; DAHER, R. F. |
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Afiliação: |
Andrea Ferreira da Costa, Incaper; UFV; UFV; UENF; Embrapa Milho e Sorgo; UENF. |
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Título: |
Biplot analysis of strawberry genotypes recommended for the State of Espírito Santo. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v. 15, p. 1-9, 2016. |
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Idioma: |
Português |
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Conteúdo: |
Most strawberry genotypes grown commercially in Brazil originate from breeding programs in the United States, and are therefore not adapted to the various soil and climatic conditions found in Brazil. Thus, quantifying the magnitude of genotype x environment (GE) interactions serves as a primary means for increasing average Brazilian strawberry yields, and helps provide specific recommendations for farmers on which genotypes meet high yield and phenotypic stability thresholds. The aim of this study was to use AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction) analyses to identify high-yield, stable strawberry genotypes grown at three locations in Espírito Santo for two agricultural years. We evaluated seven strawberry genotypes (Dover, Camino Real, Ventana, Camarosa, Seascape, Diamante, and Aromas) at three locations (Domingos Martins, Iúna, and Muniz Freire) in agricultural years 2006 and 2007, totaling six study environments. Joint analysis of variance was calculated using yield data (t/ha), and AMMI and GGE biplot analysis was conducted following the detection of a significant genotypes x agricultural years x locations (G x A x L) interaction. During the two agricultural years, evaluated locations were allocated to different regions on biplot graphics using both methods, indicating distinctions among them. Based on the results obtained from the two methods used in this study to investigate the G x A x L interaction, we recommend growing the Camarosa genotype for production at the three locations assessed due to the high frequency of favorable alleles, which were expressed in all localities evaluated
regardless of the agricultural year. MenosMost strawberry genotypes grown commercially in Brazil originate from breeding programs in the United States, and are therefore not adapted to the various soil and climatic conditions found in Brazil. Thus, quantifying the magnitude of genotype x environment (GE) interactions serves as a primary means for increasing average Brazilian strawberry yields, and helps provide specific recommendations for farmers on which genotypes meet high yield and phenotypic stability thresholds. The aim of this study was to use AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction) analyses to identify high-yield, stable strawberry genotypes grown at three locations in Espírito Santo for two agricultural years. We evaluated seven strawberry genotypes (Dover, Camino Real, Ventana, Camarosa, Seascape, Diamante, and Aromas) at three locations (Domingos Martins, Iúna, and Muniz Freire) in agricultural years 2006 and 2007, totaling six study environments. Joint analysis of variance was calculated using yield data (t/ha), and AMMI and GGE biplot analysis was conducted following the detection of a significant genotypes x agricultural years x locations (G x A x L) interaction. During the two agricultural years, evaluated locations were allocated to different regions on biplot graphics using both methods, indicating distinctions among them. Based on the results obtained from the two methods used in this study to investigat... Mostrar Tudo |
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Palavras-Chave: |
Fragaria x ananassa; Genotype x environment interaction; Strawberry; Yield. |
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Categoria do assunto: |
-- |
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URL: |
http://biblioteca.incaper.es.gov.br/digital/bitstream/item/2483/1/BRT-biplot.pdf
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Marc: |
LEADER 02425naa a2200229 a 4500
001 1013410
005 2017-09-28
008 2016 bl uuuu u00u1 u #d
100 1 $aCOSTA, A. F. da.
245 $aBiplot analysis of strawberry genotypes recommended for the State of Espírito Santo.$h[electronic resource]
260 $c2016
520 $aMost strawberry genotypes grown commercially in Brazil originate from breeding programs in the United States, and are therefore not adapted to the various soil and climatic conditions found in Brazil. Thus, quantifying the magnitude of genotype x environment (GE) interactions serves as a primary means for increasing average Brazilian strawberry yields, and helps provide specific recommendations for farmers on which genotypes meet high yield and phenotypic stability thresholds. The aim of this study was to use AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction) analyses to identify high-yield, stable strawberry genotypes grown at three locations in Espírito Santo for two agricultural years. We evaluated seven strawberry genotypes (Dover, Camino Real, Ventana, Camarosa, Seascape, Diamante, and Aromas) at three locations (Domingos Martins, Iúna, and Muniz Freire) in agricultural years 2006 and 2007, totaling six study environments. Joint analysis of variance was calculated using yield data (t/ha), and AMMI and GGE biplot analysis was conducted following the detection of a significant genotypes x agricultural years x locations (G x A x L) interaction. During the two agricultural years, evaluated locations were allocated to different regions on biplot graphics using both methods, indicating distinctions among them. Based on the results obtained from the two methods used in this study to investigate the G x A x L interaction, we recommend growing the Camarosa genotype for production at the three locations assessed due to the high frequency of favorable alleles, which were expressed in all localities evaluated regardless of the agricultural year.
653 $aFragaria x ananassa
653 $aGenotype x environment interaction
653 $aStrawberry
653 $aYield
700 1 $aTEODORO, P. E.
700 1 $aBHERING, L.L.
700 1 $aLEAL, N. R.
700 1 $aTARDIN, F. D.
700 1 $aDAHER, R. F.
773 $tGenetics and Molecular Research$gv. 15, p. 1-9, 2016.
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