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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
28/01/2021 |
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Data da última atualização: |
02/07/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
RESENDE, M. D. V. de; ALVES, R. S. |
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Afiliação: |
MARCOS DEON VILELA DE RESENDE, CNPCa; RODRIGO SILVA ALVES, UFV. |
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Título: |
Linear, generalized, hierarchical, bayesian and random regression mixed models in genetics/genomics in plant breeding. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Functional Plant Breeding Journal, v. 2, n. 2, jul./dez., 2020. p. 1-31. |
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DOI: |
http://dx.doi.org/10.35418/2526-4117/v2n2a1 |
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Idioma: |
Inglês |
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Conteúdo: |
This paper presents the state of the art of the statistical modelling as applied to plant breeding. Classes of inference, statistical models, estimation methods and model selection are emphasized in a practical way. Restricted Maximum Likelihood (REML), Hierarchical Maximum Likelihood (HIML) and Bayesian (BAYES) are highlighted. Distributions of data and effects, and dimension and structure of the models are considered for model selection and parameters estimation. Theory and practical examples referring to selection between models with different fixed effects factors are given using the Full Maximum Likelihood (FML). An analytical FML way of defining random or fixed effects is presented to avoid the subjective or conceptual usual definitions. Examples of the applications of the Hierarchical Maximum Likelihood/Hierarchical Generalized Best Linear Unbiased Prediction (HIML/HG-BLUP) procedure are also presented. Sample sizes for achieving high experimental quality and accuracy are indicated and simple interpretation of the estimates of key genetic parameters are given. Phenomics and genomics are approached. Maximum accuracy under the truest model is the key for achieving efficacy in plant breeding programs. |
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Thesagro: |
Melhoramento Genético Vegetal; Método Estatístico. |
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Thesaurus Nal: |
Plant breeding; Statistical models. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/220720/1/Linear-generalized-hierarchical.pdf
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Marc: |
LEADER 01912naa a2200193 a 4500
001 2129637
005 2021-07-02
008 2020 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.35418/2526-4117/v2n2a1$2DOI
100 1 $aRESENDE, M. D. V. de
245 $aLinear, generalized, hierarchical, bayesian and random regression mixed models in genetics/genomics in plant breeding.$h[electronic resource]
260 $c2020
520 $aThis paper presents the state of the art of the statistical modelling as applied to plant breeding. Classes of inference, statistical models, estimation methods and model selection are emphasized in a practical way. Restricted Maximum Likelihood (REML), Hierarchical Maximum Likelihood (HIML) and Bayesian (BAYES) are highlighted. Distributions of data and effects, and dimension and structure of the models are considered for model selection and parameters estimation. Theory and practical examples referring to selection between models with different fixed effects factors are given using the Full Maximum Likelihood (FML). An analytical FML way of defining random or fixed effects is presented to avoid the subjective or conceptual usual definitions. Examples of the applications of the Hierarchical Maximum Likelihood/Hierarchical Generalized Best Linear Unbiased Prediction (HIML/HG-BLUP) procedure are also presented. Sample sizes for achieving high experimental quality and accuracy are indicated and simple interpretation of the estimates of key genetic parameters are given. Phenomics and genomics are approached. Maximum accuracy under the truest model is the key for achieving efficacy in plant breeding programs.
650 $aPlant breeding
650 $aStatistical models
650 $aMelhoramento Genético Vegetal
650 $aMétodo Estatístico
700 1 $aALVES, R. S.
773 $tFunctional Plant Breeding Journal$gv. 2, n. 2, jul./dez., 2020. p. 1-31.
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Registro original: |
Embrapa Café (CNPCa) |
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Biblioteca |
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Origem |
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Registro |
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URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
16/02/2009 |
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Data da última atualização: |
15/03/2022 |
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Tipo da produção científica: |
Artigo de Divulgação na Mídia |
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Autoria: |
FERREIRA FILHO, S. M.; BETTA, M.; BENITES, V. de M. |
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Afiliação: |
SILVIO MARCOS FERREIRA FILHO, FESURV; MARCONI BETTA, FESURV; VINICIUS DE MELO BENITES, CNPS. |
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Título: |
Estoque de carbono e nutrientes em solos sob diferentes usos no Sudoeste Goiano. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
In: CENTRO TECNOLÓGICO COMIGO. Resultados do CTC 2008. Rio Verde, 2008. p. 103-106. |
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Idioma: |
Português |
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Conteúdo: |
Esse trabalho teve como objetivo avaliar os estoques de carbono e a fertilidade de solos sob diferentes usos no sudoeste goiano. |
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Palavras-Chave: |
Sudoeste Goiano. |
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Thesagro: |
Carbono; Fertilidade do Solo; Nutriente. |
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Thesaurus NAL: |
Carbon; Soil fertility; Soil nutrients. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/232546/1/Estoque-de-carbono-e-nutrientes-em-solos-sob-diferentes-usos-no-Sudoeste-Goiano-2008.pdf
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Marc: |
LEADER 00795nam a2200217 a 4500
001 1339775
005 2022-03-15
008 2008 bl uuuu u00u1 u #d
100 1 $aFERREIRA FILHO, S. M.
245 $aEstoque de carbono e nutrientes em solos sob diferentes usos no Sudoeste Goiano.$h[electronic resource]
260 $aIn: CENTRO TECNOLÓGICO COMIGO. Resultados do CTC 2008. Rio Verde, 2008. p. 103-106.$c2008
520 $aEsse trabalho teve como objetivo avaliar os estoques de carbono e a fertilidade de solos sob diferentes usos no sudoeste goiano.
650 $aCarbon
650 $aSoil fertility
650 $aSoil nutrients
650 $aCarbono
650 $aFertilidade do Solo
650 $aNutriente
653 $aSudoeste Goiano
700 1 $aBETTA, M.
700 1 $aBENITES, V. de M.
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Embrapa Solos (CNPS) |
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