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 | Acesso ao texto completo restrito à biblioteca da Embrapa Cerrados. Para informações adicionais entre em contato com cpac.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Cerrados. |
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Data corrente: |
01/03/2024 |
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Data da última atualização: |
01/03/2024 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MARCIEL, R. S.; CARVALHO, A. M. de; OLIVEIRA, A. D. de; SOUSA, T. R. de; RIBEIRO, F. P.; FONSECA, A. C. P. da; SILVA, F. R. da C.; JESUS, D. R. de; RIBEIRO, H. C.; SANTOS, V. A. dos. |
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Afiliação: |
RAYANE SILVINO MARCIEL, UNIVERSIDADE DE BRASÍLIA; ARMINDA MOREIRA DE CARVALHO, CPAC; ALEXSANDRA DUARTE DE OLIVEIRA, CPAC; THAIS RODRIGUES DE SOUSA, UNIVERSIDADE DE BRASÍLIA; FABIANA PIONTEKOWSKI RIBEIRO, CONSELHO NACIONAL DE DESENVOLVIMETO CIENTÍFICA E TECNOLÓGICO; ANA CAROLINE PEREIRA DA FONSECA, UNIVERSIDADE DE BRASÍLIA; FERNANDA RODRIGUES DA COSTA SILVA, UNIVERSIDADE DE BRASÍLIA; DOUGLAS RODRIGUES DE JESUS, UNIVERSIDADE DE BRASÍLIA; HELOISA CARVALHO RIBEIRO, UNIVERSIDADE DE BRASÍLIA; VINICIUS ARAÚJO DOS SANTOS. |
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Título: |
Soja em rotação com o milho e sucessão às plantas de cobertura em sistema plantio direto no cerrado. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 22., 2023, Natal. A agrometeorologia e a agropecuária: adaptação às mudanças climáticas: anais. Natal: Sociedade Brasileira de Agrometeorologia, 2023. |
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Páginas: |
p. 2193-2196 |
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Idioma: |
Português |
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Conteúdo: |
A soja (Glycine max L.) é a principal cultura brasileira, com o devido ao aumento populacional e a grande necessidade por alimentos o Cerrado se tornou o responsável por mais de 52% da produção nacional. Com isso, objetivou-se determinar o rendimento da soja em sucessão às plantas de coberturas (PCs) em sistema plantio direto no Cerrado. |
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Thesagro: |
Planta de Cobertura; Plantio Direto; Rendimento; Soja. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 01323nam a2200277 a 4500
001 2162479
005 2024-03-01
008 2023 bl uuuu u00u1 u #d
100 1 $aMARCIEL, R. S.
245 $aSoja em rotação com o milho e sucessão às plantas de cobertura em sistema plantio direto no cerrado.$h[electronic resource]
260 $aIn: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 22., 2023, Natal. A agrometeorologia e a agropecuária: adaptação às mudanças climáticas: anais. Natal: Sociedade Brasileira de Agrometeorologia$c2023
300 $ap. 2193-2196
520 $aA soja (Glycine max L.) é a principal cultura brasileira, com o devido ao aumento populacional e a grande necessidade por alimentos o Cerrado se tornou o responsável por mais de 52% da produção nacional. Com isso, objetivou-se determinar o rendimento da soja em sucessão às plantas de coberturas (PCs) em sistema plantio direto no Cerrado.
650 $aPlanta de Cobertura
650 $aPlantio Direto
650 $aRendimento
650 $aSoja
700 1 $aCARVALHO, A. M. de
700 1 $aOLIVEIRA, A. D. de
700 1 $aSOUSA, T. R. de
700 1 $aRIBEIRO, F. P.
700 1 $aFONSECA, A. C. P. da
700 1 $aSILVA, F. R. da C.
700 1 $aJESUS, D. R. de
700 1 $aRIBEIRO, H. C.
700 1 $aSANTOS, V. A. dos
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Registro original: |
Embrapa Cerrados (CPAC) |
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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
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Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas; Embrapa Mandioca e Fruticultura. |
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Data corrente: |
26/07/2019 |
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Data da última atualização: |
30/10/2019 |
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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: |
LIMA, L. P.; AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; OLIVEIRA, E. J. de. |
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Afiliação: |
Leísa Pires Lima, UFV; Camila Ferreira Azevedo, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; Fabyano Fonseca e Silva, UFC; José Marcelo Soriano Viana, UFV; EDER JORGE DE OLIVEIRA, CNPMF. |
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Título: |
Triple categorical regression for genomic selection: application to cassava breeding. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Scientia Agricola, v. 76, n. 5, p. 368-375, Sept./Oct. 2019. |
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DOI: |
10.1590/1678-992X-2017-0369 |
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Idioma: |
Inglês |
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Conteúdo: |
Genome-wide selection (GWS) is currently a technique of great importance in plant breeding, since it improves efficiency of genetic evaluations by increasing genetic gains. The process is based on genomic estimated breeding values (GEBVs) obtained through phenotypic and dense marker genomic information. In this context, GEBVs of N individuals are calculated through appropriate models, which estimate the effect of each marker on phenotypes, allowing the early identification of genetically superior individuals. However, GWS leads to statistical challenges, due to high dimensionality and multicollinearity problems. These challenges require the use of statistical methods to approach the regularization of the estimation process. Therefore, we aimed to propose a method denominated as triple categorical regression (TCR) and compare it with the genomic best linear unbiased predictor (G-BLUP) and Bayesian least absolute shrinkage and selection operator (BLASSO) methods that have been widely applied to GWS. The methods were evaluated in simulated populations considering four different scenarios. Additionally, a modification of the G-BLUP method was proposed based on the TCR-estimated (TCR/G-BLUP) results. All methods were applied to real data of cassava (Manihot esculenta) with to increase efficiency of a current breeding program. The methods were compared through independent validation and efficiency measures, such as prediction accuracy, bias, and recovered genomic heritability. The TCR method was suitable to estimate variance components and heritability, and the TCR/G-BLUP method provided efficient GEBV predictions. Thus, the proposed methods provide new insights for GWS. MenosGenome-wide selection (GWS) is currently a technique of great importance in plant breeding, since it improves efficiency of genetic evaluations by increasing genetic gains. The process is based on genomic estimated breeding values (GEBVs) obtained through phenotypic and dense marker genomic information. In this context, GEBVs of N individuals are calculated through appropriate models, which estimate the effect of each marker on phenotypes, allowing the early identification of genetically superior individuals. However, GWS leads to statistical challenges, due to high dimensionality and multicollinearity problems. These challenges require the use of statistical methods to approach the regularization of the estimation process. Therefore, we aimed to propose a method denominated as triple categorical regression (TCR) and compare it with the genomic best linear unbiased predictor (G-BLUP) and Bayesian least absolute shrinkage and selection operator (BLASSO) methods that have been widely applied to GWS. The methods were evaluated in simulated populations considering four different scenarios. Additionally, a modification of the G-BLUP method was proposed based on the TCR-estimated (TCR/G-BLUP) results. All methods were applied to real data of cassava (Manihot esculenta) with to increase efficiency of a current breeding program. The methods were compared through independent validation and efficiency measures, such as prediction accuracy, bias, and recovered genomic heritability. The... Mostrar Tudo |
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Palavras-Chave: |
BLASSO; G-BLUP; Genética quantitativa; Genomic heritability; Genomic prediction; Herdabilidade genômica; Molecular markers; Predição genômica; Quantitative genetics theory; Ridge. |
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Thesagro: |
Marcador Molecular. |
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Thesaurus NAL: |
Prediction. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/199876/1/2019-M.Deon-SA-Triple.pdf
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Marc: |
LEADER 02695naa a2200337 a 4500
001 2110879
005 2019-10-30
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1590/1678-992X-2017-0369$2DOI
100 1 $aLIMA, L. P.
245 $aTriple categorical regression for genomic selection$bapplication to cassava breeding.$h[electronic resource]
260 $c2019
520 $aGenome-wide selection (GWS) is currently a technique of great importance in plant breeding, since it improves efficiency of genetic evaluations by increasing genetic gains. The process is based on genomic estimated breeding values (GEBVs) obtained through phenotypic and dense marker genomic information. In this context, GEBVs of N individuals are calculated through appropriate models, which estimate the effect of each marker on phenotypes, allowing the early identification of genetically superior individuals. However, GWS leads to statistical challenges, due to high dimensionality and multicollinearity problems. These challenges require the use of statistical methods to approach the regularization of the estimation process. Therefore, we aimed to propose a method denominated as triple categorical regression (TCR) and compare it with the genomic best linear unbiased predictor (G-BLUP) and Bayesian least absolute shrinkage and selection operator (BLASSO) methods that have been widely applied to GWS. The methods were evaluated in simulated populations considering four different scenarios. Additionally, a modification of the G-BLUP method was proposed based on the TCR-estimated (TCR/G-BLUP) results. All methods were applied to real data of cassava (Manihot esculenta) with to increase efficiency of a current breeding program. The methods were compared through independent validation and efficiency measures, such as prediction accuracy, bias, and recovered genomic heritability. The TCR method was suitable to estimate variance components and heritability, and the TCR/G-BLUP method provided efficient GEBV predictions. Thus, the proposed methods provide new insights for GWS.
650 $aPrediction
650 $aMarcador Molecular
653 $aBLASSO
653 $aG-BLUP
653 $aGenética quantitativa
653 $aGenomic heritability
653 $aGenomic prediction
653 $aHerdabilidade genômica
653 $aMolecular markers
653 $aPredição genômica
653 $aQuantitative genetics theory
653 $aRidge
700 1 $aAZEVEDO, C. F.
700 1 $aRESENDE, M. D. V. de
700 1 $aSILVA, F. F. e
700 1 $aVIANA, J. M. S.
700 1 $aOLIVEIRA, E. J. de
773 $tScientia Agricola$gv. 76, n. 5, p. 368-375, Sept./Oct. 2019.
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