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 | Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Milho e Sorgo. |
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Data corrente: |
10/07/2017 |
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Data da última atualização: |
24/01/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
RIBEIRO, A. P.; SOUZA, W. R. de; MARTINS, P. K.; VINECKY, F.; DUARTE, K. E.; BASSO, M. F.; DIAS, B. B. A.; CAMPANHA, R. B.; OLIVEIRA, P. A. de; CENTENO, D. C.; CANÇADO, G. M. de A.; MAGALHÃES, J. V. de; SOUSA, C. A. F. de; ANDRADE, A. C.; KOBAYASHI, A. K.; MOLINARI, H. B. C. |
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Afiliação: |
WAGNER R. DE SOUZA, UFLA; POLYANA K. MARTINS, UFLA; FELIPE VINECKY, UFLA; KAROLINE E. DUARTE, UFLA; MARCOS F. BASSO, UFLA; BARBARA ANDRADE DIAS BRITO DA CUNHA, CNPAE; RAQUEL BOMBARDA CAMPANHA, CNPAE; PATRICIA ABRAO DE OLIVEIRA, CNPAE; DANILO C. CENTENO, UFABC; GERALDO MAGELA DE ALMEIDA CANCADO, CNPTIA; JURANDIR VIEIRA DE MAGALHAES, CNPMS; CARLOS A. F. DE SOUSA, UFLA; ALAN CARVALHO ANDRADE, SAPC; ADILSON KENJI KOBAYASHI, CNPAE; HUGO BRUNO CORREA MOLINARI, CNPAE. |
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Título: |
Overexpression of BdMATE gene improves aluminum tolerance in Setaria viridis. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Frontiers in Plant Science, v. 8, p. 1-12, June 2017. |
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Páginas: |
12 p. |
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DOI: |
10.3389/fpls.2017.00865 |
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Idioma: |
Inglês |
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Conteúdo: |
Acidic soils are distributed worldwide, predominantly in tropical and subtropical areas,reaching around 50% of the arable soil. This type of soil strongly reduces crop production, mainly because of the presence of aluminum, which has its solubility increased at low pH levels. A well-known physiological mechanism used by plants to cope with Al stress involves activation of membrane transporters responsible for organic acid anions secretion from the root apex to the rhizosphere, which chelate Al, preventing its absorption by roots. In sorghum, a membrane transporter gene belonging to multidrug and toxic compound extrusion (MATE) family was identified and characterized as an aluminum-activated citrate transporter gene responsible for Al tolerance in this crop. Setaria viridis is an emerging model for C4 species and it is an important model to validate some genes for further C4 crops transformation, such as sugarcane, maize, and wheat. In the present work, Setaria viridis was used as a model plant to overexpress a newly identified MATE gene from Brachypodium distachyon(BdMATE), closely related to SbMATE, for aluminum tolerance assays. Transgenic S. viridis plants overexpressing a BdMATE presented an improved Al tolerance phenotype, characterized by sustained root growth and exclusion of aluminum from the root apex in transgenic plants, as confirmed by hematoxylin assay. In addition, transgenic plants showed higher root citrate exudation into the rhizosphere, suggesting that Al tolerance improvement in these plants could be related to the chelation of the metal by the organic acid anion. These results suggest that BdMATE gene can be used to transform C4 crops of economic importance with improved aluminum tolerance. MenosAcidic soils are distributed worldwide, predominantly in tropical and subtropical areas,reaching around 50% of the arable soil. This type of soil strongly reduces crop production, mainly because of the presence of aluminum, which has its solubility increased at low pH levels. A well-known physiological mechanism used by plants to cope with Al stress involves activation of membrane transporters responsible for organic acid anions secretion from the root apex to the rhizosphere, which chelate Al, preventing its absorption by roots. In sorghum, a membrane transporter gene belonging to multidrug and toxic compound extrusion (MATE) family was identified and characterized as an aluminum-activated citrate transporter gene responsible for Al tolerance in this crop. Setaria viridis is an emerging model for C4 species and it is an important model to validate some genes for further C4 crops transformation, such as sugarcane, maize, and wheat. In the present work, Setaria viridis was used as a model plant to overexpress a newly identified MATE gene from Brachypodium distachyon(BdMATE), closely related to SbMATE, for aluminum tolerance assays. Transgenic S. viridis plants overexpressing a BdMATE presented an improved Al tolerance phenotype, characterized by sustained root growth and exclusion of aluminum from the root apex in transgenic plants, as confirmed by hematoxylin assay. In addition, transgenic plants showed higher root citrate exudation into the rhizosphere, suggesting that Al t... Mostrar Tudo |
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Palavras-Chave: |
BdMate; Hydroponic system; Organismo geneticamente modificado; Tolerância ao alumínio. |
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Thesagro: |
Aluminio. |
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Thesaurus Nal: |
Abiotic stress; Aluminum; Genetically modified organisms; Setaria viridis. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02981naa a2200433 a 4500
001 2080632
005 2018-01-24
008 2017 bl uuuu u00u1 u #d
024 7 $a10.3389/fpls.2017.00865$2DOI
100 1 $aRIBEIRO, A. P.
245 $aOverexpression of BdMATE gene improves aluminum tolerance in Setaria viridis.$h[electronic resource]
260 $c2017
300 $a12 p.
520 $aAcidic soils are distributed worldwide, predominantly in tropical and subtropical areas,reaching around 50% of the arable soil. This type of soil strongly reduces crop production, mainly because of the presence of aluminum, which has its solubility increased at low pH levels. A well-known physiological mechanism used by plants to cope with Al stress involves activation of membrane transporters responsible for organic acid anions secretion from the root apex to the rhizosphere, which chelate Al, preventing its absorption by roots. In sorghum, a membrane transporter gene belonging to multidrug and toxic compound extrusion (MATE) family was identified and characterized as an aluminum-activated citrate transporter gene responsible for Al tolerance in this crop. Setaria viridis is an emerging model for C4 species and it is an important model to validate some genes for further C4 crops transformation, such as sugarcane, maize, and wheat. In the present work, Setaria viridis was used as a model plant to overexpress a newly identified MATE gene from Brachypodium distachyon(BdMATE), closely related to SbMATE, for aluminum tolerance assays. Transgenic S. viridis plants overexpressing a BdMATE presented an improved Al tolerance phenotype, characterized by sustained root growth and exclusion of aluminum from the root apex in transgenic plants, as confirmed by hematoxylin assay. In addition, transgenic plants showed higher root citrate exudation into the rhizosphere, suggesting that Al tolerance improvement in these plants could be related to the chelation of the metal by the organic acid anion. These results suggest that BdMATE gene can be used to transform C4 crops of economic importance with improved aluminum tolerance.
650 $aAbiotic stress
650 $aAluminum
650 $aGenetically modified organisms
650 $aSetaria viridis
650 $aAluminio
653 $aBdMate
653 $aHydroponic system
653 $aOrganismo geneticamente modificado
653 $aTolerância ao alumínio
700 1 $aSOUZA, W. R. de
700 1 $aMARTINS, P. K.
700 1 $aVINECKY, F.
700 1 $aDUARTE, K. E.
700 1 $aBASSO, M. F.
700 1 $aDIAS, B. B. A.
700 1 $aCAMPANHA, R. B.
700 1 $aOLIVEIRA, P. A. de
700 1 $aCENTENO, D. C.
700 1 $aCANÇADO, G. M. de A.
700 1 $aMAGALHÃES, J. V. de
700 1 $aSOUSA, C. A. F. de
700 1 $aANDRADE, A. C.
700 1 $aKOBAYASHI, A. K.
700 1 $aMOLINARI, H. B. C.
773 $tFrontiers in Plant Science$gv. 8, p. 1-12, June 2017.
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Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
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Biblioteca |
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Origem |
Tipo/Formato |
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Registro |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
02/06/2022 |
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Data da última atualização: |
01/12/2022 |
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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: |
FERREIRA, F. M.; LEITE, R. V.; MALIKOUSKI, R. G.; PEIXOTO, M. A.; BERNARDELI, A.; ALVES, R. S.; MAGALHAES JUNIOR, W. C. P. de; ANDRADE, R. G.; BHERING, L. L.; MACHADO, J. C. |
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Afiliação: |
FILIPE MANOEL FERREIRA, Universidade Federal de Viçosa; RODRIGO VIEIRA LEITE, Universidade Federal de Viçosa; RENAN GARCIA MALIKOUSKI, Universidade Federal de Viçosa; MARCO ANTONIO PEIXOTO, Universidade Federal de Viçosa; ARTHUR BERNARDELI, Universidade Federal de Viçosa; RODRIGO SILVA ALVES, Universidade Federal de Lavras; WALTER COELHO P DE MAGALHAES JUNIOR, CNPGL; RICARDO GUIMARAES ANDRADE, CNPGL; LEONARDO LOPES BHERING, Universidade Federal de Viçosa; JUAREZ CAMPOLINA MACHADO, CNPGL. |
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Título: |
Bioenergy elephant grass genotype selection leveraged by spatial modeling of conventional and high-throughput phenotyping data. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Journal of Cleaner Production, v. 363, 132286, 2022. |
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DOI: |
https://doi.org/10.1016/j.jclepro.2022.132286 |
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Idioma: |
Inglês |
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Conteúdo: |
The burning of fossil fuels contributes to global warming. Using renewable energy sources such as elephant grass biomass mitigates anthropogenic impact on nature. The genetic selection of high-yield elephant grass genotypes is important to increase the use of this forage for energy generation. Unmanned aerial vehicles have been used for data collection and optimization of the selection of genotypes. However, statistical tests should be conducted to study the suitability of vegetation indices for predicting morphological traits. In addition, spatial sources of variation, such as soil structure heterogeneity, can disturb the selection process. This study compared the correlation between morphological traits and vegetation indices of elephant grass clones using basic linear mixed and spatial linear mixed models. In addition, we evaluated the magnitude and contribution of each index to explain the variations in traits and identify the best index for this forage. There was significant genetic variability in some morphological traits that enabled selection. Spatial models (autoregressive correlation among rows and columns) were more suitable for modeling some of the evaluated traits. There were changes in the magnitude of the correlation between traits when we considered the best-fit model instead of the non-spatial model. The increase in efficiency using the best-fitted model instead of the non-spatial model was 15.39% for heritability and 9.54% for accuracy. The total dry biomass was the only morphological trait significantly correlated with some vegetation indices, allowing for indirect selection. The coincidence index, heritability, and gains from indirect selection indicated that the normalized difference red-edge index was the best for selecting superior elephant grass high-yielding genotypes. The spatial modeling leveraged the genetic selection of high yield elephant grass genotypes for bioenergetic purposes. MenosThe burning of fossil fuels contributes to global warming. Using renewable energy sources such as elephant grass biomass mitigates anthropogenic impact on nature. The genetic selection of high-yield elephant grass genotypes is important to increase the use of this forage for energy generation. Unmanned aerial vehicles have been used for data collection and optimization of the selection of genotypes. However, statistical tests should be conducted to study the suitability of vegetation indices for predicting morphological traits. In addition, spatial sources of variation, such as soil structure heterogeneity, can disturb the selection process. This study compared the correlation between morphological traits and vegetation indices of elephant grass clones using basic linear mixed and spatial linear mixed models. In addition, we evaluated the magnitude and contribution of each index to explain the variations in traits and identify the best index for this forage. There was significant genetic variability in some morphological traits that enabled selection. Spatial models (autoregressive correlation among rows and columns) were more suitable for modeling some of the evaluated traits. There were changes in the magnitude of the correlation between traits when we considered the best-fit model instead of the non-spatial model. The increase in efficiency using the best-fitted model instead of the non-spatial model was 15.39% for heritability and 9.54% for accuracy. The total dry biomas... Mostrar Tudo |
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Palavras-Chave: |
Forage breeding; Genetic selection; Seleção gênica. |
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Thesagro: |
Bioenergia; Capim Elefante; Seleção Fenótipa; Seleção Genética; Sensoriamento Remoto. |
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Thesaurus NAL: |
Phenomics; Remote sensing. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 03055naa a2200361 a 4500
001 2143669
005 2022-12-01
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.jclepro.2022.132286$2DOI
100 1 $aFERREIRA, F. M.
245 $aBioenergy elephant grass genotype selection leveraged by spatial modeling of conventional and high-throughput phenotyping data.$h[electronic resource]
260 $c2022
520 $aThe burning of fossil fuels contributes to global warming. Using renewable energy sources such as elephant grass biomass mitigates anthropogenic impact on nature. The genetic selection of high-yield elephant grass genotypes is important to increase the use of this forage for energy generation. Unmanned aerial vehicles have been used for data collection and optimization of the selection of genotypes. However, statistical tests should be conducted to study the suitability of vegetation indices for predicting morphological traits. In addition, spatial sources of variation, such as soil structure heterogeneity, can disturb the selection process. This study compared the correlation between morphological traits and vegetation indices of elephant grass clones using basic linear mixed and spatial linear mixed models. In addition, we evaluated the magnitude and contribution of each index to explain the variations in traits and identify the best index for this forage. There was significant genetic variability in some morphological traits that enabled selection. Spatial models (autoregressive correlation among rows and columns) were more suitable for modeling some of the evaluated traits. There were changes in the magnitude of the correlation between traits when we considered the best-fit model instead of the non-spatial model. The increase in efficiency using the best-fitted model instead of the non-spatial model was 15.39% for heritability and 9.54% for accuracy. The total dry biomass was the only morphological trait significantly correlated with some vegetation indices, allowing for indirect selection. The coincidence index, heritability, and gains from indirect selection indicated that the normalized difference red-edge index was the best for selecting superior elephant grass high-yielding genotypes. The spatial modeling leveraged the genetic selection of high yield elephant grass genotypes for bioenergetic purposes.
650 $aPhenomics
650 $aRemote sensing
650 $aBioenergia
650 $aCapim Elefante
650 $aSeleção Fenótipa
650 $aSeleção Genética
650 $aSensoriamento Remoto
653 $aForage breeding
653 $aGenetic selection
653 $aSeleção gênica
700 1 $aLEITE, R. V.
700 1 $aMALIKOUSKI, R. G.
700 1 $aPEIXOTO, M. A.
700 1 $aBERNARDELI, A.
700 1 $aALVES, R. S.
700 1 $aMAGALHAES JUNIOR, W. C. P. de
700 1 $aANDRADE, R. G.
700 1 $aBHERING, L. L.
700 1 $aMACHADO, J. C.
773 $tJournal of Cleaner Production$gv. 363, 132286, 2022.
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