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 | Acesso ao texto completo restrito à biblioteca da Embrapa Recursos Genéticos e Biotecnologia. Para informações adicionais entre em contato com cenargen.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Café; Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
10/12/2020 |
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Data da última atualização: |
17/12/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
RESENDE, R. T.; PIEPHO,H.-P.; ROSA, G. J. M.; SILVA JUNIOR, O. B. da; SILVA, F. F. e; RESENDE, M. D. V. de; GRATTAPAGLIA, D. |
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Afiliação: |
RAFAEL T. RESENDE, UFG; HANS-PETER PIEPHO, UNIVERSITY OF HOHENHEIM, GERMANY; GUILHERME J. M. ROSA, UNIVERSITY OF WISCONSIN-MADISON, USA; ORZENIL BONFIM DA SILVA JUNIOR, Cenargen; FABYANO F. E SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; DARIO GRATTAPAGLIA, Cenargen. |
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Título: |
Enviromics in breeding: applications and perspectives on envirotypic-assisted selection. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Theoretical and Applied Genetics, v. 134, n. 1, 2021. p. 95-112. |
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DOI: |
https://doi.org/10.1007/s00122-020-03684-z |
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Idioma: |
Inglês |
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Conteúdo: |
Genotype by environment interaction (GEI) studies in plant breeding have focused mainly on estimating genetic parameters over a limited number of experimental trials. However, recent geographic information system (GIS) techniques have opened new frontiers for better understanding and dealing with GEI. These advances allow increasing selection accuracy across all sites of interest, including those where experimental trials have not yet been deployed. Here, we introduce the term enviromics, within an envirotypic-assisted breeding framework. In summary, likewise genotypes at DNA markers, any particular site is characterized by a set of "envirotypes" at multiple "enviromic" markers corresponding to environmental variables that may interact with the genetic background, thus providing informative breeding re-rankings for optimized decisions over different environments. Based on simulated data, we illustrate an index-based enviromics method (the "GIS-GEI") which, due to its higher granular resolution than standard methods, allows for: (1) accurate matching of sites to their most appropriate genotypes; (2) better definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (3) efficient determination of the best sites to carry out experiments for further analyses. Environmental scenarios can also be optimized for productivity improvement and genetic resources management, especially in the current outlook of dynamic climate change. Envirotyping provides a new class of markers for genetic studies, which are fairly inexpensive, increasingly available and transferable across species. We envision a promising future for the integration of enviromics approaches into plant breeding when coupled with next-generation genotyping/phenotyping and powerful statistical modeling of genetic diversity. MenosGenotype by environment interaction (GEI) studies in plant breeding have focused mainly on estimating genetic parameters over a limited number of experimental trials. However, recent geographic information system (GIS) techniques have opened new frontiers for better understanding and dealing with GEI. These advances allow increasing selection accuracy across all sites of interest, including those where experimental trials have not yet been deployed. Here, we introduce the term enviromics, within an envirotypic-assisted breeding framework. In summary, likewise genotypes at DNA markers, any particular site is characterized by a set of "envirotypes" at multiple "enviromic" markers corresponding to environmental variables that may interact with the genetic background, thus providing informative breeding re-rankings for optimized decisions over different environments. Based on simulated data, we illustrate an index-based enviromics method (the "GIS-GEI") which, due to its higher granular resolution than standard methods, allows for: (1) accurate matching of sites to their most appropriate genotypes; (2) better definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (3) efficient determination of the best sites to carry out experiments for further analyses. Environmental scenarios can also be optimized for productivity improvement and genetic resources management, especially in the current outlook of dynamic climate change... Mostrar Tudo |
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Thesagro: |
Interação Genética; Melhoramento Genético Vegetal; Sistema de Informação Geográfica. |
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Thesaurus Nal: |
Breeding; Genotype-environment interaction; Geographic information systems; Plant breeding. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02814naa a2200289 a 4500
001 2129641
005 2021-12-17
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s00122-020-03684-z$2DOI
100 1 $aRESENDE, R. T.
245 $aEnviromics in breeding$bapplications and perspectives on envirotypic-assisted selection.$h[electronic resource]
260 $c2021
520 $aGenotype by environment interaction (GEI) studies in plant breeding have focused mainly on estimating genetic parameters over a limited number of experimental trials. However, recent geographic information system (GIS) techniques have opened new frontiers for better understanding and dealing with GEI. These advances allow increasing selection accuracy across all sites of interest, including those where experimental trials have not yet been deployed. Here, we introduce the term enviromics, within an envirotypic-assisted breeding framework. In summary, likewise genotypes at DNA markers, any particular site is characterized by a set of "envirotypes" at multiple "enviromic" markers corresponding to environmental variables that may interact with the genetic background, thus providing informative breeding re-rankings for optimized decisions over different environments. Based on simulated data, we illustrate an index-based enviromics method (the "GIS-GEI") which, due to its higher granular resolution than standard methods, allows for: (1) accurate matching of sites to their most appropriate genotypes; (2) better definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (3) efficient determination of the best sites to carry out experiments for further analyses. Environmental scenarios can also be optimized for productivity improvement and genetic resources management, especially in the current outlook of dynamic climate change. Envirotyping provides a new class of markers for genetic studies, which are fairly inexpensive, increasingly available and transferable across species. We envision a promising future for the integration of enviromics approaches into plant breeding when coupled with next-generation genotyping/phenotyping and powerful statistical modeling of genetic diversity.
650 $aBreeding
650 $aGenotype-environment interaction
650 $aGeographic information systems
650 $aPlant breeding
650 $aInteração Genética
650 $aMelhoramento Genético Vegetal
650 $aSistema de Informação Geográfica
700 1 $aPIEPHO,H.-P.
700 1 $aROSA, G. J. M.
700 1 $aSILVA JUNIOR, O. B. da
700 1 $aSILVA, F. F. e
700 1 $aRESENDE, M. D. V. de
700 1 $aGRATTAPAGLIA, D.
773 $tTheoretical and Applied Genetics$gv. 134, n. 1, 2021. p. 95-112.
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Registro original: |
Embrapa Café (CNPCa) |
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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
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Registro |
Volume |
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URL |
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Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
21/02/2018 |
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Data da última atualização: |
02/05/2018 |
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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: |
COELHO, D. S.; SIMOES, W. L.; SALVIANO, A. M.; MESQUITA, A. C.; ALBERTO, K. da C. |
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Afiliação: |
DANIELA S. COELHO, Instituto de Meio Ambiente e Recursos Hídricos/Unidade Regional Sertão do São Francisco. Juazeiro, BA; WELSON LIMA SIMOES, CPATSA; ALESSANDRA MONTEIRO SALVIANO, CPATSA; ALESSANDRO C. MESQUITA, Universidade do Estado da Bahia/Departamento de Tecnologia e Ciências Sociais. Juazeiro, BA; KEILA DA C. ALBERTO, UPE. |
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Título: |
Gas exchange and organic solutes in forage sorghum genotypes grown under different salinity levels. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, v. 22, n. 4, p. 231-236, 2018. |
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ISSN: |
1807-1929 |
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DOI: |
10.1590/1807-1929/agriambi.v22n4p231-236 |
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Idioma: |
Inglês |
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Conteúdo: |
Adaptation of plants to saline environments depends on the activation of mechanisms that minimize the effects of excess ions on vital processes, such as photosynthesis. The objective of this study was to evaluate the leaf gas exchange, chlorophyll, and organic solute in ten genotypes of forage sorghum irrigated with solutions of different salinity levels. The experiment was conducted in a randomized block design, in a 10 x 6 factorial arrangement, with three replications, using ten genotypes - F305, BRS-655, BRS-610, Volumax, 1.015.045, 1.016.005, 1.016.009, 1.016.013, 1.016.015 and 1.016.031 - and six saline solutions, with electrical conductivity (ECw) of 0, 2.5, 5.0, 7.5, 10 and 12.5 dS m-1. The photosynthetic activity in forage sorghum plants reduces with increasing salinity, and this response was found in the ten genotypes evaluated. The chlorophyll and protein contents were not affected by salinity, whereas carbohydrates and amino acid contents increased with increasing EC w. Soluble sugars are essential for osmoregulation of forage sorghum due to its high content in leaves. |
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Palavras-Chave: |
Forage sorghum. |
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Thesagro: |
Clorofila; Fotossíntese; Salinidade; Sorghum Bicolor; Sorgo forrageiro. |
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Thesaurus NAL: |
Chlorophyll; Photosynthesis; Salt stress. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/172952/1/Welson-2018.pdf
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Marc: |
LEADER 02027naa a2200301 a 4500
001 2088009
005 2018-05-02
008 2018 bl uuuu u00u1 u #d
022 $a1807-1929
024 7 $a10.1590/1807-1929/agriambi.v22n4p231-236$2DOI
100 1 $aCOELHO, D. S.
245 $aGas exchange and organic solutes in forage sorghum genotypes grown under different salinity levels.$h[electronic resource]
260 $c2018
520 $aAdaptation of plants to saline environments depends on the activation of mechanisms that minimize the effects of excess ions on vital processes, such as photosynthesis. The objective of this study was to evaluate the leaf gas exchange, chlorophyll, and organic solute in ten genotypes of forage sorghum irrigated with solutions of different salinity levels. The experiment was conducted in a randomized block design, in a 10 x 6 factorial arrangement, with three replications, using ten genotypes - F305, BRS-655, BRS-610, Volumax, 1.015.045, 1.016.005, 1.016.009, 1.016.013, 1.016.015 and 1.016.031 - and six saline solutions, with electrical conductivity (ECw) of 0, 2.5, 5.0, 7.5, 10 and 12.5 dS m-1. The photosynthetic activity in forage sorghum plants reduces with increasing salinity, and this response was found in the ten genotypes evaluated. The chlorophyll and protein contents were not affected by salinity, whereas carbohydrates and amino acid contents increased with increasing EC w. Soluble sugars are essential for osmoregulation of forage sorghum due to its high content in leaves.
650 $aChlorophyll
650 $aPhotosynthesis
650 $aSalt stress
650 $aClorofila
650 $aFotossíntese
650 $aSalinidade
650 $aSorghum Bicolor
650 $aSorgo forrageiro
653 $aForage sorghum
700 1 $aSIMOES, W. L.
700 1 $aSALVIANO, A. M.
700 1 $aMESQUITA, A. C.
700 1 $aALBERTO, K. da C.
773 $tRevista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande$gv. 22, n. 4, p. 231-236, 2018.
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