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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agroindústria de Alimentos. Para informações adicionais entre em contato com ctaa.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agroindústria de Alimentos; Embrapa Mandioca e Fruticultura; Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
26/06/2015 |
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Data da última atualização: |
18/05/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ALMEIDA, L. A. DA H.; SANTOS, J. Z.; SOARES FILHO, W. dos S.; BIZZO, H. R.; SILVA, J. P.; VIEIRA, R. F. |
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Afiliação: |
LUCAS ARAGÃO DA HORA ALMEIDA, UFRB; JOSIANA ZANOTELLI SANTOS, UNB; WALTER DOS SANTOS SOARES FILHO, CNPMF; HUMBERTO RIBEIRO BIZZO, CTAA; JOSEANA PADILHA SILVA, CENARGEN; ROBERTO FONTES VIEIRA, CENARGEN. |
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Título: |
Chemical Characterization of Leaf Essential Oil from Seven Accessions of Sour Orange (Citrus aurantium L.). |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
Journal of Essential Oil Bearing Plants, v. 18, n. 2, p. 426-435, 2015. |
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ISSN: |
0976-5026 |
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DOI: |
10.1080/0972060X.2014.977562 |
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Idioma: |
Inglês
Português |
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Conteúdo: |
The yield and chemical composition of the essential oils from the leaves of seven accessions of sour orange from a germplasm bank, harvested in two different seasons, were analyzed by GC-FID and GCMS. The oil yields ranged from 0.2 to 0.6 % in the dry season and from traces to 1.1 % in the wet season. Major compounds found were linalool (6.6 to 48.9 %), linalyl acetate (0.4 to 33.8 %) and ?-terpineol (0.3 to 10.8 %) for most of the samples. For one accession, ?-pinene (31.3 to 46.0 %) was the major constituent, while for another, methyl N-methyl-anthranilate reached up to 30.9 % of the oil in the wet season. Within the seasons, each access presented similar profiles, as verified by Principal Component Analysis of the essential oil constituents. |
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Palavras-Chave: |
Essential oil; Germplasm variability; Petitgrain. |
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Thesagro: |
Citrus Aurantium; Fruta cítrica; Germoplasma; Olèo essencial; Variedade. |
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Thesaurus Nal: |
Essential oils; linalool. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 01721naa a2200325 a 4500
001 2020753
005 2023-05-18
008 2015 bl uuuu u00u1 u #d
022 $a0976-5026
024 7 $a10.1080/0972060X.2014.977562$2DOI
100 1 $aALMEIDA, L. A. DA H.
245 $aChemical Characterization of Leaf Essential Oil from Seven Accessions of Sour Orange (Citrus aurantium L.).$h[electronic resource]
260 $c2015
520 $aThe yield and chemical composition of the essential oils from the leaves of seven accessions of sour orange from a germplasm bank, harvested in two different seasons, were analyzed by GC-FID and GCMS. The oil yields ranged from 0.2 to 0.6 % in the dry season and from traces to 1.1 % in the wet season. Major compounds found were linalool (6.6 to 48.9 %), linalyl acetate (0.4 to 33.8 %) and ?-terpineol (0.3 to 10.8 %) for most of the samples. For one accession, ?-pinene (31.3 to 46.0 %) was the major constituent, while for another, methyl N-methyl-anthranilate reached up to 30.9 % of the oil in the wet season. Within the seasons, each access presented similar profiles, as verified by Principal Component Analysis of the essential oil constituents.
650 $aEssential oils
650 $alinalool
650 $aCitrus Aurantium
650 $aFruta cítrica
650 $aGermoplasma
650 $aOlèo essencial
650 $aVariedade
653 $aEssential oil
653 $aGermplasm variability
653 $aPetitgrain
700 1 $aSANTOS, J. Z.
700 1 $aSOARES FILHO, W. dos S.
700 1 $aBIZZO, H. R.
700 1 $aSILVA, J. P.
700 1 $aVIEIRA, R. F.
773 $tJournal of Essential Oil Bearing Plants$gv. 18, n. 2, p. 426-435, 2015.
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Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
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Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
18/01/2017 |
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Data da última atualização: |
18/01/2017 |
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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: |
ALMEIDA FILHO, J. E. de; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JUNIOR, M. F. R. |
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Afiliação: |
J. E. de Almeida Filho, University of Florida; J. F. R. Guimarães, University of Florida; F. F. e SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; P. Muñoz, University of Florida; M. Kirst, University of Florida; M. F. R. Resende JUnior, RAPiD Genomics LLC. |
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Título: |
The contribution of dominance to phenotype prediction in a pine breeding and simulated population. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Heredity, v. 117, p. 33-41, July 2016. |
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DOI: |
10.1038/hdy.2016.23 |
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Idioma: |
Inglês |
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Conteúdo: |
Pedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive?dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait. |
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Thesagro: |
Árvore conífera. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/153479/1/2016-M.Deon-H-TheContribution.pdf
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Marc: |
LEADER 02158naa a2200217 a 4500
001 2061094
005 2017-01-18
008 2016 bl uuuu u00u1 u #d
024 7 $a10.1038/hdy.2016.23$2DOI
100 1 $aALMEIDA FILHO, J. E. de
245 $aThe contribution of dominance to phenotype prediction in a pine breeding and simulated population.$h[electronic resource]
260 $c2016
520 $aPedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive?dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait.
650 $aÁrvore conífera
700 1 $aGUIMARÃES, J. F. R.
700 1 $aSILVA, F. F. e
700 1 $aRESENDE, M. D. V. de
700 1 $aMUÑOZ, P.
700 1 $aKIRST, M.
700 1 $aRESENDE JUNIOR, M. F. R.
773 $tHeredity$gv. 117, p. 33-41, July 2016.
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Embrapa Florestas (CNPF) |
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