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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
27/09/2017 |
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Data da última atualização: |
27/09/2017 |
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Tipo da produção científica: |
Publicação em Anais de Congresso |
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Autoria: |
LOPES, J. C.; SOBREIRA, F. M.; SILVA, A. da S.; SOBREIRA, F. M.; MACEDO, C. M. P.; BREGONCI, I. dos S. |
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Afiliação: |
José Carlos Lopes, UFES; Fábio Moreira Sobreira, UFES; Camila Aparecida da Silva, UFES; Fabrício Moreira Sobreira, UFES; Célia Maria Peixoto de Macedo, UFES; Izaias dos Santos Bregonci, Incaper. |
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Título: |
Influência do estádio de maturação e tratamento com KNO3 na germinação de sementes de tomatinho. |
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Ano de publicação: |
2006 |
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Fonte/Imprenta: |
In: Congresso Brasileiro de Olericultura, 46., 2006, Goiânia-GO. Anais.... Brasília, DF: Horticultura Brasileira, 2006. v. 24. p. 2553-2556. |
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Idioma: |
Português |
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Conteúdo: |
O trabalho foi conduzido no Laboratório de Tecnologia e Análise de Sementes do Departamento de Fitotecnia do Centro de Ciências Agrárias, da Universidade Federal do Espírito Santo, Alegre-ES (CCA-UFES), utilizando-se sementes de Solanum
pimpinellifolium. A semeadura foi feita em placas de Petri sobre papel, mantidas em BOD sob temperatura de 20-30°C e luz contínua. O delineamento utilizado foi o inteiramente casualizado, com quatro repetições e os tratamentos foram constituídos por sementes
colhidas em diferentes estádios de maturação (maduro, semi-maduro e verde) e tratadas com água e KNO3,. num esquema fatorial 3 x 2. Os resultados evidenciaram que a maior germinação foi obtida nas sementes extraídas dos frutos semi-maduro e verde e que o
tratamento com KNO3 foi mais eficiente na germinação das sementes. |
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Palavras-Chave: |
Germinação; Solanum pimpinellifolium; Substrato; Temperatura; Tomatinho. |
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Categoria do assunto: |
-- |
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URL: |
http://biblioteca.incaper.es.gov.br/digital/bitstream/item/2799/1/BRT-influenciadoestadiodematuracaoetratamentocomKNO3-breegonci.pdf
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Marc: |
LEADER 01626nam a2200229 a 4500
001 1016207
005 2017-09-27
008 2006 bl uuuu u01u1 u #d
100 1 $aLOPES, J. C.
245 $aInfluência do estádio de maturação e tratamento com KNO3 na germinação de sementes de tomatinho.$h[electronic resource]
260 $aIn: Congresso Brasileiro de Olericultura, 46., 2006, Goiânia-GO. Anais.... Brasília, DF: Horticultura Brasileira, 2006. v. 24. p. 2553-2556.$c2556
520 $aO trabalho foi conduzido no Laboratório de Tecnologia e Análise de Sementes do Departamento de Fitotecnia do Centro de Ciências Agrárias, da Universidade Federal do Espírito Santo, Alegre-ES (CCA-UFES), utilizando-se sementes de Solanum pimpinellifolium. A semeadura foi feita em placas de Petri sobre papel, mantidas em BOD sob temperatura de 20-30°C e luz contínua. O delineamento utilizado foi o inteiramente casualizado, com quatro repetições e os tratamentos foram constituídos por sementes colhidas em diferentes estádios de maturação (maduro, semi-maduro e verde) e tratadas com água e KNO3,. num esquema fatorial 3 x 2. Os resultados evidenciaram que a maior germinação foi obtida nas sementes extraídas dos frutos semi-maduro e verde e que o tratamento com KNO3 foi mais eficiente na germinação das sementes.
653 $aGerminação
653 $aSolanum pimpinellifolium
653 $aSubstrato
653 $aTemperatura
653 $aTomatinho
700 1 $aSOBREIRA, F. M.
700 1 $aSILVA, A. da S.
700 1 $aSOBREIRA, F. M.
700 1 $aMACEDO, C. M. P.
700 1 $aBREGONCI, I. dos S.
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Registro original: |
Biblioteca Rui Tendinha (BRT) |
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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
04/07/2018 |
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Data da última atualização: |
12/04/2024 |
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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: |
FERRÃO, L. F. V.; FERRÃO, R. G.; FERRÃO, M. A. G.; FONSECA, A. F. A. da.; CARBONETTO, P.; STEPHENS, M.; GARCIA, A. A. F. |
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Afiliação: |
Luis Felipe Ventorim Ferrão, ESALQ; Romário Gava Ferrão, Incaper; Maria Amélia Gava Ferrão, Incaper/Embrapa Café; Aymbiré Francisco Almeida da Fonseca, Incaper/Embrapa Café; Peter Carbonetto, Research Computing Center, University of Chicago; Matthew Stephens, Research Computing Center, University of Chicago; Antonio Augusto Franco Garcia, ESALQ. |
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Título: |
Accurate genomic prediction of Coffea canephora in multiple environments using whole-genome statistical models. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Heredity, june 2018. |
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Idioma: |
Português |
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Conteúdo: |
Genomic selection has been proposed as the standard method to predict breeding values in animal and plant breeding. Although some crops have benefited from this methodology, studies in Coffea are still emerging. To date, there have been no studies describing how well genomic prediction models work across populations and environments for different complex traits in coffee. Considering that predictive models are based on biological and statistical assumptions, it is expected that their performance vary depending on how well these assumptions align with the true genetic architecture of the phenotype. To investigate this, we used data from two recurrent selection populations of Coffea canephora, evaluated in two locations, and single nucleotide polymorphisms identified by Genotyping-by-Sequencing. In particular, we evaluated the performance of 13 statistical approaches to predict three important traits in the coffee?production of coffee beans, leaf rust incidence and yield of green beans. Analyses were performed for predictions within-environment, across locations and across populations to assess the reliability of genomic selection. Overall, differences in the prediction accuracy of the competing models were small, although the Bayesian methods showed a modest improvement over other methods, at the cost of more computation time. As expected, predictive accuracy for within-environment analysis, on average, were higher than predictions across locations and across populations. Our results support the potential of genomic selection to reshape traditional plant breeding schemes. In practice, we expect to increase the genetic gain per unit of time by reducing the length cycle of recurrent selection in coffee. MenosGenomic selection has been proposed as the standard method to predict breeding values in animal and plant breeding. Although some crops have benefited from this methodology, studies in Coffea are still emerging. To date, there have been no studies describing how well genomic prediction models work across populations and environments for different complex traits in coffee. Considering that predictive models are based on biological and statistical assumptions, it is expected that their performance vary depending on how well these assumptions align with the true genetic architecture of the phenotype. To investigate this, we used data from two recurrent selection populations of Coffea canephora, evaluated in two locations, and single nucleotide polymorphisms identified by Genotyping-by-Sequencing. In particular, we evaluated the performance of 13 statistical approaches to predict three important traits in the coffee?production of coffee beans, leaf rust incidence and yield of green beans. Analyses were performed for predictions within-environment, across locations and across populations to assess the reliability of genomic selection. Overall, differences in the prediction accuracy of the competing models were small, although the Bayesian methods showed a modest improvement over other methods, at the cost of more computation time. As expected, predictive accuracy for within-environment analysis, on average, were higher than predictions across locations and across populations. Our... Mostrar Tudo |
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Palavras-Chave: |
Cafe conilon. |
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Thesaurus NAL: |
Coffea canephora; Genomic. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://biblioteca.incaper.es.gov.br/digital/bitstream/item/4674/1/s41437-018-0105-y.pdf
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Marc: |
LEADER 02393naa a2200229 a 4500
001 1020469
005 2024-04-12
008 2018 bl uuuu u00u1 u #d
100 1 $aFERRÃO, L. F. V.
245 $aAccurate genomic prediction of Coffea canephora in multiple environments using whole-genome statistical models.$h[electronic resource]
260 $c2018
520 $aGenomic selection has been proposed as the standard method to predict breeding values in animal and plant breeding. Although some crops have benefited from this methodology, studies in Coffea are still emerging. To date, there have been no studies describing how well genomic prediction models work across populations and environments for different complex traits in coffee. Considering that predictive models are based on biological and statistical assumptions, it is expected that their performance vary depending on how well these assumptions align with the true genetic architecture of the phenotype. To investigate this, we used data from two recurrent selection populations of Coffea canephora, evaluated in two locations, and single nucleotide polymorphisms identified by Genotyping-by-Sequencing. In particular, we evaluated the performance of 13 statistical approaches to predict three important traits in the coffee?production of coffee beans, leaf rust incidence and yield of green beans. Analyses were performed for predictions within-environment, across locations and across populations to assess the reliability of genomic selection. Overall, differences in the prediction accuracy of the competing models were small, although the Bayesian methods showed a modest improvement over other methods, at the cost of more computation time. As expected, predictive accuracy for within-environment analysis, on average, were higher than predictions across locations and across populations. Our results support the potential of genomic selection to reshape traditional plant breeding schemes. In practice, we expect to increase the genetic gain per unit of time by reducing the length cycle of recurrent selection in coffee.
650 $aCoffea canephora
650 $aGenomic
653 $aCafe conilon
700 1 $aFERRÃO, R. G.
700 1 $aFERRÃO, M. A. G.
700 1 $aFONSECA, A. F. A. da.
700 1 $aCARBONETTO, P.
700 1 $aSTEPHENS, M.
700 1 $aGARCIA, A. A. F.
773 $tHeredity, june 2018.
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Biblioteca Rui Tendinha (BRT) |
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