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Registro Completo |
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Biblioteca(s): |
Embrapa Soja. |
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Data corrente: |
11/07/2018 |
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Data da última atualização: |
20/12/2018 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
FRANCHINI, J. C.; JORGE, L. A. de C.; CORREA, F. B.; GREGGIO, F.; DEBIASI, H.; BALBINOT JUNIOR, A. A.; PEREIRA, G. S. |
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Afiliação: |
JULIO CEZAR FRANCHINI DOS SANTOS, CNPSO; LUCIO ANDRE DE CASTRO JORGE, CNPDIA; COAMO, CAMPO MOURÃO; ENGENHEIRO AGRÔNOMO; HENRIQUE DEBIASI, CNPSO; ALVADI ANTONIO BALBINOT JUNIOR, CNPSO; UEL. |
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Título: |
Estimativa da produtividade da soja pelo uso de imagens aéreas. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE SOJA, 8., 2018, Goiânia. Inovação, tecnologias digitais e sustentabilidade da soja: anais. Brasília, DF: Embrapa, 2018. |
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Páginas: |
p. 380-382. |
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Idioma: |
Português |
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Thesagro: |
Estimativa; Produtividade; Reconhecimento Aéreo; Soja. |
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Thesaurus Nal: |
Aerial application; Seed productivity; Soybeans. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/179649/1/Estimativa-da-produtividade-p.380-382.pdf
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Marc: |
LEADER 00855nam a2200265 a 4500
001 2093204
005 2018-12-20
008 2018 bl uuuu u00u1 u #d
100 1 $aFRANCHINI, J. C.
245 $aEstimativa da produtividade da soja pelo uso de imagens aéreas.$h[electronic resource]
260 $aIn: CONGRESSO BRASILEIRO DE SOJA, 8., 2018, Goiânia. Inovação, tecnologias digitais e sustentabilidade da soja: anais. Brasília, DF: Embrapa$c2018
300 $ap. 380-382.
650 $aAerial application
650 $aSeed productivity
650 $aSoybeans
650 $aEstimativa
650 $aProdutividade
650 $aReconhecimento Aéreo
650 $aSoja
700 1 $aJORGE, L. A. de C.
700 1 $aCORREA, F. B.
700 1 $aGREGGIO, F.
700 1 $aDEBIASI, H.
700 1 $aBALBINOT JUNIOR, A. A.
700 1 $aPEREIRA, G. S.
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Registro original: |
Embrapa Soja (CNPSO) |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
08/12/2023 |
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Data da última atualização: |
08/12/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 4 |
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Autoria: |
FERREIRA, F. M.; CHAVES, S. F. da S.; PEIXOTO, M. A.; ALVES, R. S.; COELHO, I. F.; RESENDE, M. D. V. de; SANTOS, G. A. dos; BHERING, L. L. |
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Afiliação: |
FILIPE MANOEL FERREIRA, UNIVERSIDADE FEDERAL DE VIÇOSA; SAULO FABRÍCIO DA SILVA CHAVES, UNIVERSIDADE FEDERAL DE VIÇOSA; MARCO ANTÔNIO PEIXOTO, UNIVERSIDADE FEDERAL DE VIÇOSA; RODRIGO SILVA ALVES, INSTITUTO NACIONAL DE CIÊNCIA E TECNOLOGIA DO CAFÉ; IGOR FERREIRA COELHO, UNIVERSIDADE FEDERAL DE VIÇOSA; MARCOS DEON VILELA DE RESENDE, CNPCa; GLEISON AUGUSTO DOS SANTOS, UNIVERSIDADE FEDERAL DE VIÇOSA; LEONARDO LOPES BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA. |
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Título: |
Multi-trait multi-environment models for selecting high-performance and stable eucalyptus clones. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Acta Scientiarum. Agronomy, v. 45, e61626, 2023. |
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Páginas: |
9 p. |
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DOI: |
https://doi.org/10.4025/actasciagron.v45i1.61626 |
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Idioma: |
Inglês |
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Conteúdo: |
Multi-trait multi-environment (MTME) models were fitted to eucalyptus breeding trials data to assess residual variance structure, genetic stability and adaptability. To do so, 215 eucalyptus clones were evaluated in a randomized complete block design with 30 replicates and one plant per plot in four environments. At 36 months of age, tree diameter at breast height (DBH) and pilodyn penetration (PP) were measured. Two MTME models were fitted, for which residuals were considered homoscedastic and heteroscedastic, with the best MTME model selected using Bayesian information criterion. The harmonic mean of the relative performance of the genotypic values (HMRPGV) was used to determine stability and adaptability. Of the two models, the heteroscedastic MTME model had better fit and provided greater accuracy. In addition, genotype-by-environment interaction was complex, and there was low genetic correlation between DBH and PP. Rank correlation between the clones selected by the MTME models was high for DBH but low for PP. The HMRPGV facilitated clone selection through simultaneous evaluation of stability, adaptability, and productivity. Thus, our results suggest that heteroscedastic MTME model / HMRPGV can be efficiently applied in the genetic evaluation and selection of eucalyptus clones. |
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Thesaurus NAL: |
Clones; Eucalyptus; Genetic variance; Genotype-environment interaction; Multivariate analysis; Quantitative genetics. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1159359/1/Multi-trait-multi-environment-models.pdf
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Marc: |
LEADER 02224naa a2200301 a 4500
001 2159359
005 2023-12-08
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.4025/actasciagron.v45i1.61626$2DOI
100 1 $aFERREIRA, F. M.
245 $aMulti-trait multi-environment models for selecting high-performance and stable eucalyptus clones.$h[electronic resource]
260 $c2023
300 $a9 p.
520 $aMulti-trait multi-environment (MTME) models were fitted to eucalyptus breeding trials data to assess residual variance structure, genetic stability and adaptability. To do so, 215 eucalyptus clones were evaluated in a randomized complete block design with 30 replicates and one plant per plot in four environments. At 36 months of age, tree diameter at breast height (DBH) and pilodyn penetration (PP) were measured. Two MTME models were fitted, for which residuals were considered homoscedastic and heteroscedastic, with the best MTME model selected using Bayesian information criterion. The harmonic mean of the relative performance of the genotypic values (HMRPGV) was used to determine stability and adaptability. Of the two models, the heteroscedastic MTME model had better fit and provided greater accuracy. In addition, genotype-by-environment interaction was complex, and there was low genetic correlation between DBH and PP. Rank correlation between the clones selected by the MTME models was high for DBH but low for PP. The HMRPGV facilitated clone selection through simultaneous evaluation of stability, adaptability, and productivity. Thus, our results suggest that heteroscedastic MTME model / HMRPGV can be efficiently applied in the genetic evaluation and selection of eucalyptus clones.
650 $aClones
650 $aEucalyptus
650 $aGenetic variance
650 $aGenotype-environment interaction
650 $aMultivariate analysis
650 $aQuantitative genetics
700 1 $aCHAVES, S. F. da S.
700 1 $aPEIXOTO, M. A.
700 1 $aALVES, R. S.
700 1 $aCOELHO, I. F.
700 1 $aRESENDE, M. D. V. de
700 1 $aSANTOS, G. A. dos
700 1 $aBHERING, L. L.
773 $tActa Scientiarum. Agronomy$gv. 45, e61626, 2023.
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Embrapa Café (CNPCa) |
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