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Registros recuperados: 14 | |
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VALENTE, M. S. F.; CHAVES, F. C. M.; LOPES, M. T. G.; OKA, J. M.; RODRIGUES, R. A. F.. |
Desempenho produtivo, estimativa de parâmetros genéticos e seleção de sacha inchi na Amazônia central. este trabalho objetivou analisar, na região da Amazônia central, diferentes acessos dessa trepadeira oleaginosa para características de produção e qualidade de frutos e sementes, bem como estimar parâmetros genéticos, por meio de modelos mistos, com identificação de acessos superiores, para fins de melhoramento. |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Plukenetia volubilis; Euphorbiaceae; Genetic gain; Oil yield; Plant breeding; Ganho genético; Rendimento de óleo; Melhoramento vegetal. |
Ano: 2017 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1073368 |
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VIANA, J. M. S.; VALENTE, M. S. F.; SCAPIM, C. A.; RESENDE, M. D. V. de; SILVA, F. F. e. |
The objectives were to identify superior inbred lines and single-crosses, predict untested hybrids and analyze the importance of pedigree information and the prediction efficiency. We analyzed 24 experiments in the incomplete block design, including 20 tests of hybrids and 4 tests of inbred lines. The expansion volume (EV) and grain yield were measured in each plot. The analyses were made using ASReml software. Analyses of the general combining ability (GCA) effects and the additive genetic values of the inbred lines, and the genotypic values of the hybrids in relation to EV showed that no inbred line selection strategy resulted in a set of clearly superior or inferior inbred lines and hybrids. Including pedigree information resulted in an increase in the... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Milho; Melhoramento genético. |
Ano: 2011 |
URL: http://www.alice.cnptia.embrapa.br/handle/doc/914433 |
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AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F.; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; OLIVEIRA, E. J. de. |
ABSTRACT. Genomic selection is the main force driving applied breeding programs and accuracy is the main measure for evaluating its efficiency. The traditional estimator (TE) of experimental accuracy is not fully adequate. This study proposes and evaluates the performance and efficiency of two new accuracy estimators, called regularized estimator (RE) and hybrid estimator (HE), which were applied to a practical cassava breeding program and also to simulated data. The simulation study considered two individual narrow sense heritability levels and two genetic architectures for traits. TE, RE, and HE were compared under four validation procedures: without validation (WV), independent validation, ten-fold validation through jacknife allowing different markers,... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Seleção genômica; Genomic prediction; Accuracy estimator; Cross-validation; Manihot esculenta; Mandioca; Melhoramento vegetal; Cassava; Plant breeding. |
Ano: 2016 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072711 |
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AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; MUÑOZ, P.. |
Background: A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated... |
Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Modelo Bayesiano; Genética quantitativa; Melhoramento genético; Parâmetro genético; Dominance genomic models; Bayesian methods; Lasso methods; Selection accuracy. |
Ano: 2015 |
URL: http://www.alice.cnptia.embrapa.br/handle/doc/1022575 |
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Registros recuperados: 14 | |
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