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Registro Completo |
Biblioteca(s): |
Embrapa Semiárido. |
Data corrente: |
12/11/1997 |
Data da última atualização: |
10/01/2023 |
Autoria: |
ARAUJO FILHO, J. C. de; RIBEIRO, M. R. |
Título: |
Caracteristicas de cambissolos do Baixio de Irece (BA) e suas relacoes com a infiltracao e disponibilidade de agua. |
Ano de publicação: |
1994 |
Fonte/Imprenta: |
Revista Brasileira de Ciencia do Solo, Piracicaba, v.18, n.3, p.521-527, 1994. |
Idioma: |
Português |
Conteúdo: |
Caracteristicas morfologicas, micromorfologicas, fisicas, quimicas e mineralogicas de cambissolos do Baixio de Irece, BA, foram estudadas com o objetivo de explicar o comportamento atipico desses solos com relacao ao movimento e a disponibilidade de agua. Selecionaram-se quatro subareas para descricao morfologica e amostragem dos solos, duas em cambissolos argilosos e duas em cambissolos muito argilosos, com perfis profundos e muito profundos, e sequencia de horizontes A, Bi e R. A estrutura e moderada a forte, granular e em blocos subangulares, na superficie, e moderada a fraca em blocos angulares e subangulares, na subsuperficie. Apesar de a CTC ser indicativa de argilas de atividade alta, s perfis sao essencialmente cauliniticos. A micromorfologia mostra que os solos apresentam uma microagregacao bem desenvolvida, com largos espacos porosos interagregados, bastante interconectados. Conclui-se que os aspectos morfologicos e micromorfologicos observados sao compativeis com as altas taxas de infiltracao constatadas em estudos anteriores. As caracteristicas texturais e estruturais, entretanto, indicam solos de media disponibilidade hidrica. |
Palavras-Chave: |
Bahia; Baixio; Irece; Mineraologia; Morfologia; Recursos naturais. |
Thesagro: |
Água; Cambissolo; Física; Infiltração; Química; Solo. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01920naa a2200277 a 4500 001 1126375 005 2023-01-10 008 1994 bl uuuu u00u1 u #d 100 1 $aARAUJO FILHO, J. C. de 245 $aCaracteristicas de cambissolos do Baixio de Irece (BA) e suas relacoes com a infiltracao e disponibilidade de agua. 260 $c1994 520 $aCaracteristicas morfologicas, micromorfologicas, fisicas, quimicas e mineralogicas de cambissolos do Baixio de Irece, BA, foram estudadas com o objetivo de explicar o comportamento atipico desses solos com relacao ao movimento e a disponibilidade de agua. Selecionaram-se quatro subareas para descricao morfologica e amostragem dos solos, duas em cambissolos argilosos e duas em cambissolos muito argilosos, com perfis profundos e muito profundos, e sequencia de horizontes A, Bi e R. A estrutura e moderada a forte, granular e em blocos subangulares, na superficie, e moderada a fraca em blocos angulares e subangulares, na subsuperficie. Apesar de a CTC ser indicativa de argilas de atividade alta, s perfis sao essencialmente cauliniticos. A micromorfologia mostra que os solos apresentam uma microagregacao bem desenvolvida, com largos espacos porosos interagregados, bastante interconectados. Conclui-se que os aspectos morfologicos e micromorfologicos observados sao compativeis com as altas taxas de infiltracao constatadas em estudos anteriores. As caracteristicas texturais e estruturais, entretanto, indicam solos de media disponibilidade hidrica. 650 $aÁgua 650 $aCambissolo 650 $aFísica 650 $aInfiltração 650 $aQuímica 650 $aSolo 653 $aBahia 653 $aBaixio 653 $aIrece 653 $aMineraologia 653 $aMorfologia 653 $aRecursos naturais 700 1 $aRIBEIRO, M. R. 773 $tRevista Brasileira de Ciencia do Solo, Piracicaba$gv.18, n.3, p.521-527, 1994.
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Embrapa Semiárido (CPATSA) |
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Registro Completo
Biblioteca(s): |
Embrapa Florestas; Embrapa Mandioca e Fruticultura. |
Data corrente: |
26/07/2019 |
Data da última atualização: |
30/10/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
LIMA, L. P.; AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; OLIVEIRA, E. J. de. |
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. |
Título: |
Triple categorical regression for genomic selection: application to cassava breeding. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Scientia Agricola, v. 76, n. 5, p. 368-375, Sept./Oct. 2019. |
DOI: |
10.1590/1678-992X-2017-0369 |
Idioma: |
Inglês |
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 |
Palavras-Chave: |
BLASSO; G-BLUP; Genética quantitativa; Genomic heritability; Genomic prediction; Herdabilidade genômica; Molecular markers; Predição genômica; Quantitative genetics theory; Ridge. |
Thesagro: |
Marcador Molecular. |
Thesaurus NAL: |
Prediction. |
Categoria do assunto: |
G Melhoramento Genético |
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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