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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
06/02/2018 |
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Data da última atualização: |
25/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
ROSSI, D. A.; DAHER, R. F.; BARBÉ, T. C.; LIMA, R. S. N.; COSTA, A. F. da.; RIBEIRO L. P.; TEODORO, P. E.; BHERING, L. L. |
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Afiliação: |
FAVENI; Laboratório de Melhoramento Genético Vegetal; Laboratório de Melhoramento Genético Vegetal; Universidade Federal de Alagoas; Andrea Ferreira da Costa, Incaper; UFV; UFV; UFV. |
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Título: |
Diversity among elephant grass genotypes using Bayesian multi-trait model. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v. 16, n. 3, gmr16039803, 2017. |
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Idioma: |
Inglês |
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Conteúdo: |
Elephant grass is a perennial tropical grass with great potential for energy generation from biomass. The objective of this study was to estimate the genetic diversity among elephant grass accessions based on morpho-agronomic and biomass quality traits and to identify promising genotypes for obtaining hybrids with high energetic biomass production capacity. The experiment was installed at experimental area of the State Agricultural College Antônio Sarlo, in Campos dos Goytacazes. Fifty-two elephant grass genotypes were evaluated in a randomized block design with two replicates. Components of variance and the genotypic means were obtained using a Bayesian multi-trait model. We considered 350,000 iterations in the Gibbs sampler algorithm for each parameter adopted, with a warm-up period (burn-in) of 50,000 Iterations. For obtaining an uncorrelated sample, we considered five iterations (thinning) as a spacing between sampled points, which resulted in a final sample size 60,000. Subsequently, the Mahalanobis distance between each pair of genotypes was estimated. Estimates of genotypic variance indicated a favorable condition for gains in all traits. Elephant grass accessions presented greater variability for biomass quality traits, for which three groups were formed, while for the agronomic traits, two groups were formed. Crosses between Mercker Pinda México x Mercker 86-México, Mercker Pinda México x Turrialba, and Mercker 86-México x Taiwan A-25 can be carried out for obtaining elephant grass hybrids for energy purposes. MenosElephant grass is a perennial tropical grass with great potential for energy generation from biomass. The objective of this study was to estimate the genetic diversity among elephant grass accessions based on morpho-agronomic and biomass quality traits and to identify promising genotypes for obtaining hybrids with high energetic biomass production capacity. The experiment was installed at experimental area of the State Agricultural College Antônio Sarlo, in Campos dos Goytacazes. Fifty-two elephant grass genotypes were evaluated in a randomized block design with two replicates. Components of variance and the genotypic means were obtained using a Bayesian multi-trait model. We considered 350,000 iterations in the Gibbs sampler algorithm for each parameter adopted, with a warm-up period (burn-in) of 50,000 Iterations. For obtaining an uncorrelated sample, we considered five iterations (thinning) as a spacing between sampled points, which resulted in a final sample size 60,000. Subsequently, the Mahalanobis distance between each pair of genotypes was estimated. Estimates of genotypic variance indicated a favorable condition for gains in all traits. Elephant grass accessions presented greater variability for biomass quality traits, for which three groups were formed, while for the agronomic traits, two groups were formed. Crosses between Mercker Pinda México x Mercker 86-México, Mercker Pinda México x Turrialba, and Mercker 86-México x Taiwan A-25 can be carried out for obtainin... Mostrar Tudo |
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Thesaurus NAL: |
Bioenergy; Biomass production; Biomass quality; Pennisetum purpureum. |
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Categoria do assunto: |
-- |
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URL: |
https://biblioteca.incaper.es.gov.br/digital/bitstream/123456789/2991/1/BRT-DiversityamongelephantgrassgenotypesusingBayesianmulti-traitmodel-costa.pdf
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Marc: |
LEADER 02278naa a2200253 a 4500
001 1018349
005 2022-08-25
008 2017 bl uuuu u00u1 u #d
100 1 $aROSSI, D. A.
245 $aDiversity among elephant grass genotypes using Bayesian multi-trait model.$h[electronic resource]
260 $c2017
520 $aElephant grass is a perennial tropical grass with great potential for energy generation from biomass. The objective of this study was to estimate the genetic diversity among elephant grass accessions based on morpho-agronomic and biomass quality traits and to identify promising genotypes for obtaining hybrids with high energetic biomass production capacity. The experiment was installed at experimental area of the State Agricultural College Antônio Sarlo, in Campos dos Goytacazes. Fifty-two elephant grass genotypes were evaluated in a randomized block design with two replicates. Components of variance and the genotypic means were obtained using a Bayesian multi-trait model. We considered 350,000 iterations in the Gibbs sampler algorithm for each parameter adopted, with a warm-up period (burn-in) of 50,000 Iterations. For obtaining an uncorrelated sample, we considered five iterations (thinning) as a spacing between sampled points, which resulted in a final sample size 60,000. Subsequently, the Mahalanobis distance between each pair of genotypes was estimated. Estimates of genotypic variance indicated a favorable condition for gains in all traits. Elephant grass accessions presented greater variability for biomass quality traits, for which three groups were formed, while for the agronomic traits, two groups were formed. Crosses between Mercker Pinda México x Mercker 86-México, Mercker Pinda México x Turrialba, and Mercker 86-México x Taiwan A-25 can be carried out for obtaining elephant grass hybrids for energy purposes.
650 $aBioenergy
650 $aBiomass production
650 $aBiomass quality
650 $aPennisetum purpureum
700 1 $aDAHER, R. F.
700 1 $aBARBÉ, T. C.
700 1 $aLIMA, R. S. N.
700 1 $aCOSTA, A. F. da.
700 1 $aRIBEIRO L. P.
700 1 $aTEODORO, P. E.
700 1 $aBHERING, L. L.
773 $tGenetics and Molecular Research$gv. 16, n. 3, gmr16039803, 2017.
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