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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
28/01/2021 |
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Data da última atualização: |
28/01/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ALVES, R. S.; RESENDE, M. D. V. de; ROCHA, J. R. do A. S. de C.; PEIXOTO, M. A.; TEODORO, P. E.; SILVA, F. F. e; BHERING, L. L.; SANTOS, G. A. dos. |
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Afiliação: |
RODRIGO SILVA ALVES, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; JOÃO ROMERO DO AMARAL SANTOS DE CARVALHO ROCHA, UFV; MARCO ANTÔNIO PEIXOTO, UFV; PAULO EDUARDO TEODORO, UFMS; FABYANO FONSECA E SILVA, UFV; LEONARDO LOPES BHERING, UFV; GLEISON AUGUSTO DOS SANTOS, UFV. |
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Título: |
Quantifying individual variation in reaction norms using random regression models fitted through Legendre polynomials: application in eucalyptus breeding. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Bragantia, v. 79, n. 4, 2020. p. 360-376. |
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DOI: |
https://doi.org/10.1590/1678-4499.20200125 |
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Idioma: |
Inglês |
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Conteúdo: |
An accurate, efficient and informative statistical method for analyses of genotype × environment (G × E) interactions is a key requirement for progress in any breeding program. Thus, the objective of this study was to quantify individual variation in reaction norms using random regression models fitted through Legendre polynomials in eucalyptus (Eucalyptus spp.) breeding. To this end, a data set with 215 eucalyptus clones of different species and hybrids evaluated in four environments for diameter at breast height (DBH) and Pilodyn penetration (PP) was used. Variance components were estimated by restricted maximum likelihood, and genetic values were predicted by best linear unbiased prediction. The best-fitted model for DBH and PP was indicated by the Akaike information criterion, and the significance of the genotype effects was tested using the likelihood ratio test. Genetic variability between eucalyptus clones and very high accuracies ( r^gg >=0.90 ) were detected for both traits. Reaction norms and eigenfunctions generated genetic insights into G × E interactions. This is the first study that quantified individual variation in reaction norms using random regression models fitted through Legendre polynomials in eucalyptus breeding and demonstrated the great potential of this technique. |
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Thesagro: |
Eucalipto; Interação Genética; Melhoramento Genético Vegetal; Método Estatístico. |
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Thesaurus Nal: |
Eucalyptus; Forest trees; Genotype-environment interaction; Plant breeding; Statistical models. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/220735/1/Quantifying-individual-variation.pdf
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Marc: |
LEADER 02377naa a2200325 a 4500
001 2129653
005 2021-01-28
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1590/1678-4499.20200125$2DOI
100 1 $aALVES, R. S.
245 $aQuantifying individual variation in reaction norms using random regression models fitted through Legendre polynomials$bapplication in eucalyptus breeding.$h[electronic resource]
260 $c2020
520 $aAn accurate, efficient and informative statistical method for analyses of genotype × environment (G × E) interactions is a key requirement for progress in any breeding program. Thus, the objective of this study was to quantify individual variation in reaction norms using random regression models fitted through Legendre polynomials in eucalyptus (Eucalyptus spp.) breeding. To this end, a data set with 215 eucalyptus clones of different species and hybrids evaluated in four environments for diameter at breast height (DBH) and Pilodyn penetration (PP) was used. Variance components were estimated by restricted maximum likelihood, and genetic values were predicted by best linear unbiased prediction. The best-fitted model for DBH and PP was indicated by the Akaike information criterion, and the significance of the genotype effects was tested using the likelihood ratio test. Genetic variability between eucalyptus clones and very high accuracies ( r^gg >=0.90 ) were detected for both traits. Reaction norms and eigenfunctions generated genetic insights into G × E interactions. This is the first study that quantified individual variation in reaction norms using random regression models fitted through Legendre polynomials in eucalyptus breeding and demonstrated the great potential of this technique.
650 $aEucalyptus
650 $aForest trees
650 $aGenotype-environment interaction
650 $aPlant breeding
650 $aStatistical models
650 $aEucalipto
650 $aInteração Genética
650 $aMelhoramento Genético Vegetal
650 $aMétodo Estatístico
700 1 $aRESENDE, M. D. V. de
700 1 $aROCHA, J. R. do A. S. de C.
700 1 $aPEIXOTO, M. A.
700 1 $aTEODORO, P. E.
700 1 $aSILVA, F. F. e
700 1 $aBHERING, L. L.
700 1 $aSANTOS, G. A. dos
773 $tBragantia$gv. 79, n. 4, 2020. p. 360-376.
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Registro original: |
Embrapa Café (CNPCa) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agrobiologia. Para informações adicionais entre em contato com cnpab.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agrobiologia. |
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Data corrente: |
29/10/2019 |
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Data da última atualização: |
29/10/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
GUARESHI, R. F.; MARTINS, M. dos R.; SARKIS, L. F.; ALVES, B. J. R.; JANTALIA, C. P.; BODDEY, R. M.; URQUIAGA, S. |
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Afiliação: |
Roni Fernandes Guareschi, UFRRJ; Marcio dos Reis Martins, UFRRJ; Leonardo Fernandes Sarkis, UFLA; BRUNO JOSE RODRIGUES ALVES, CNPAB; CLAUDIA POZZI JANTALIA, CNPAB; ROBERT MICHAEL BODDEY, CNPAB; SEGUNDO SACRAMENTO U CABALLERO, CNPAB. |
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Título: |
An analysis of energy efficiency and greenhouse gas emissions from organic soybean cultivation in Brazil. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Semina: Ciências Agrárias, Londrina, v. 40, n. 6, suplemento 3, p. 3461-3476, 2019 |
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DOI: |
10.5433/1679-0359.2019v40n6Supl3p3461 |
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Idioma: |
Inglês |
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Notas: |
Título em Português: Uma análise da eficiência energética e da emissão de gases de efeito estufa no cultivo orgânico de soja no Brasil. |
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Conteúdo: |
The assessment of energy efficiency (EE) and greenhouse gas (GHG) emissions can highlight the sustainability of agro-systems and decision-making regarding reduction of production costs and environmental pollution. In this context, the objective of this work was to evaluate the EE and GHG emissions (CO2, CH4 e N2O) of a soybean crop under organic cultivation in different regions of Brazil in the agricultural year 2014-2015. For this, 19 soybean areas were evaluated. The inputs and outputs of the agricultural operations and / or inputs used were calculated by multiplying the quantity used by their calorific value or energy coefficient at each stage of production. The energy efficiency was obtained by the ratio between the amount of total output energy and the total energy consumption
during the production process. In order to estimate GHG emissions, the principles of the life cycle assessment methodology and recommendations of the Intergovernmental Panel on Climate Change (IPCC) were applied. For each 1.0 MJ of energy consumed in the organic production of soybeans, an average of 7.9 MJ of renewable energy was produced in the form of grains of this crop. The main energy costs of growing these organic crops were with seeds, fuel and with tractors, machines and agricultural implements (TMI). For each 1 kg of organic grain produced from soybeans, 0.19 kg of CO2eq are emitted during their production and delivery cycles in the warehouse. The main sources of CO2eq emission to the atmosphere were the seeds, fuels and organic fertilizers MenosThe assessment of energy efficiency (EE) and greenhouse gas (GHG) emissions can highlight the sustainability of agro-systems and decision-making regarding reduction of production costs and environmental pollution. In this context, the objective of this work was to evaluate the EE and GHG emissions (CO2, CH4 e N2O) of a soybean crop under organic cultivation in different regions of Brazil in the agricultural year 2014-2015. For this, 19 soybean areas were evaluated. The inputs and outputs of the agricultural operations and / or inputs used were calculated by multiplying the quantity used by their calorific value or energy coefficient at each stage of production. The energy efficiency was obtained by the ratio between the amount of total output energy and the total energy consumption
during the production process. In order to estimate GHG emissions, the principles of the life cycle assessment methodology and recommendations of the Intergovernmental Panel on Climate Change (IPCC) were applied. For each 1.0 MJ of energy consumed in the organic production of soybeans, an average of 7.9 MJ of renewable energy was produced in the form of grains of this crop. The main energy costs of growing these organic crops were with seeds, fuel and with tractors, machines and agricultural implements (TMI). For each 1 kg of organic grain produced from soybeans, 0.19 kg of CO2eq are emitted during their production and delivery cycles in the warehouse. The main sources of CO2eq emission to the atm... Mostrar Tudo |
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Palavras-Chave: |
Energy greenhouse gases; Grain production; Organic agriculture. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02506naa a2200253 a 4500
001 2113604
005 2019-10-29
008 2019 bl --- 0-- u #d
024 7 $a10.5433/1679-0359.2019v40n6Supl3p3461$2DOI
100 1 $aGUARESHI, R. F.
245 $aAn analysis of energy efficiency and greenhouse gas emissions from organic soybean cultivation in Brazil.$h[electronic resource]
260 $c2019
500 $aTítulo em Português: Uma análise da eficiência energética e da emissão de gases de efeito estufa no cultivo orgânico de soja no Brasil.
520 $aThe assessment of energy efficiency (EE) and greenhouse gas (GHG) emissions can highlight the sustainability of agro-systems and decision-making regarding reduction of production costs and environmental pollution. In this context, the objective of this work was to evaluate the EE and GHG emissions (CO2, CH4 e N2O) of a soybean crop under organic cultivation in different regions of Brazil in the agricultural year 2014-2015. For this, 19 soybean areas were evaluated. The inputs and outputs of the agricultural operations and / or inputs used were calculated by multiplying the quantity used by their calorific value or energy coefficient at each stage of production. The energy efficiency was obtained by the ratio between the amount of total output energy and the total energy consumption during the production process. In order to estimate GHG emissions, the principles of the life cycle assessment methodology and recommendations of the Intergovernmental Panel on Climate Change (IPCC) were applied. For each 1.0 MJ of energy consumed in the organic production of soybeans, an average of 7.9 MJ of renewable energy was produced in the form of grains of this crop. The main energy costs of growing these organic crops were with seeds, fuel and with tractors, machines and agricultural implements (TMI). For each 1 kg of organic grain produced from soybeans, 0.19 kg of CO2eq are emitted during their production and delivery cycles in the warehouse. The main sources of CO2eq emission to the atmosphere were the seeds, fuels and organic fertilizers
653 $aEnergy greenhouse gases
653 $aGrain production
653 $aOrganic agriculture
700 1 $aMARTINS, M. dos R.
700 1 $aSARKIS, L. F.
700 1 $aALVES, B. J. R.
700 1 $aJANTALIA, C. P.
700 1 $aBODDEY, R. M.
700 1 $aURQUIAGA, S.
773 $tSemina: Ciências Agrárias, Londrina$gv. 40, n. 6, suplemento 3, p. 3461-3476, 2019
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