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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
17/07/2022 |
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Data da última atualização: |
22/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
HEINEMANN, A. B.; COSTA-NETO, G; FRITSCHE-NETO, R.; MATTA, D. H. da; FERNANDES, I. K. |
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Afiliação: |
ALEXANDRE BRYAN HEINEMANN, CNPAF; GERMANO COSTA-NETO, Cornell University, Ithaca-NY; ROBERTO FRITSCHE-NETO, ESALQ; DAVID HENRIQUES DA MATTA, UFG; IGOR KUIVJOGI FERNANDES, UFG. |
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Título: |
Enviromic prediction is useful to define the limits of climate adaptation: a case study of common bean in Brazil. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Field Crops Research, v. 286, 108628, Oct. 2022. |
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ISSN: |
0378-4290 |
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DOI: |
https://doi.org/10.1016/j.fcr.2022.108628 |
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Idioma: |
Inglês |
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Conteúdo: |
Ongoing changes in the global environmental conditions foster plant breeding research to develop climate-smart cultivars as fast as possible. Data analytics are essential for achieving this goal, especially the so-called science of enviromics (large-scale environmental characterization of crop growing conditions) that could be used to pinpoint the relevant environment impacts driving the adaptation of a certain specie in a breeding framework. Here we quantified the effects of diverse climate factors on the current adaptation of elite common bean germplasm in Brazil. To capture the non-linearity of those impacts across a wide range of environments, we developed an ?enviromic prediction? approach by combining Generalized Additive Models (GAM), environmental covariates (EC), and grain yield (GY) from 18 years of historical breeding trials. Then, we predicted the optimum limits for ECs at each production scenario (four regions, three seasons, and two grain types) and its respective predictions of GY adaptation. Our results indicate that the nonlinear influence of air temperature, solar radiation, and rainfall led to a huge interaction of the impacts among the development stages, seasons, and regions. This revealed that seasonality differently affected the vegetative and reproductive stages, which its impact drastically vary according to the region and season, which makes unfeasible the development of a breeding strategy for selecting for broad adaptation. Conversely, with our approach it was possible to pinpoint the effects of the region- or season-specific impacts, which helped identify the ?climate limits? and critical development phases for each possible production scenario. This could allow breeders to design crop ideotypes while directing efforts to develop climate-smart varieties. Furthermore, enviromics prediction is a cost-effective way to use EC as a data analytics tool to support the visualization of regional breeding gaps for specific growing conditions. MenosOngoing changes in the global environmental conditions foster plant breeding research to develop climate-smart cultivars as fast as possible. Data analytics are essential for achieving this goal, especially the so-called science of enviromics (large-scale environmental characterization of crop growing conditions) that could be used to pinpoint the relevant environment impacts driving the adaptation of a certain specie in a breeding framework. Here we quantified the effects of diverse climate factors on the current adaptation of elite common bean germplasm in Brazil. To capture the non-linearity of those impacts across a wide range of environments, we developed an ?enviromic prediction? approach by combining Generalized Additive Models (GAM), environmental covariates (EC), and grain yield (GY) from 18 years of historical breeding trials. Then, we predicted the optimum limits for ECs at each production scenario (four regions, three seasons, and two grain types) and its respective predictions of GY adaptation. Our results indicate that the nonlinear influence of air temperature, solar radiation, and rainfall led to a huge interaction of the impacts among the development stages, seasons, and regions. This revealed that seasonality differently affected the vegetative and reproductive stages, which its impact drastically vary according to the region and season, which makes unfeasible the development of a breeding strategy for selecting for broad adaptation. Conversely, with our ap... Mostrar Tudo |
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Palavras-Chave: |
Generalized Additive Models (GAM). |
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Thesagro: |
Clima; Feijão; Melhoramento; Phaseolus Vulgaris. |
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Thesaurus Nal: |
Beans; Breeding; Climate; Environment; Plant adaptation. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02916naa a2200313 a 4500
001 2144756
005 2022-08-22
008 2022 bl uuuu u00u1 u #d
022 $a0378-4290
024 7 $ahttps://doi.org/10.1016/j.fcr.2022.108628$2DOI
100 1 $aHEINEMANN, A. B.
245 $aEnviromic prediction is useful to define the limits of climate adaptation$ba case study of common bean in Brazil.$h[electronic resource]
260 $c2022
520 $aOngoing changes in the global environmental conditions foster plant breeding research to develop climate-smart cultivars as fast as possible. Data analytics are essential for achieving this goal, especially the so-called science of enviromics (large-scale environmental characterization of crop growing conditions) that could be used to pinpoint the relevant environment impacts driving the adaptation of a certain specie in a breeding framework. Here we quantified the effects of diverse climate factors on the current adaptation of elite common bean germplasm in Brazil. To capture the non-linearity of those impacts across a wide range of environments, we developed an ?enviromic prediction? approach by combining Generalized Additive Models (GAM), environmental covariates (EC), and grain yield (GY) from 18 years of historical breeding trials. Then, we predicted the optimum limits for ECs at each production scenario (four regions, three seasons, and two grain types) and its respective predictions of GY adaptation. Our results indicate that the nonlinear influence of air temperature, solar radiation, and rainfall led to a huge interaction of the impacts among the development stages, seasons, and regions. This revealed that seasonality differently affected the vegetative and reproductive stages, which its impact drastically vary according to the region and season, which makes unfeasible the development of a breeding strategy for selecting for broad adaptation. Conversely, with our approach it was possible to pinpoint the effects of the region- or season-specific impacts, which helped identify the ?climate limits? and critical development phases for each possible production scenario. This could allow breeders to design crop ideotypes while directing efforts to develop climate-smart varieties. Furthermore, enviromics prediction is a cost-effective way to use EC as a data analytics tool to support the visualization of regional breeding gaps for specific growing conditions.
650 $aBeans
650 $aBreeding
650 $aClimate
650 $aEnvironment
650 $aPlant adaptation
650 $aClima
650 $aFeijão
650 $aMelhoramento
650 $aPhaseolus Vulgaris
653 $aGeneralized Additive Models (GAM)
700 1 $aCOSTA-NETO, G
700 1 $aFRITSCHE-NETO, R.
700 1 $aMATTA, D. H. da
700 1 $aFERNANDES, I. K.
773 $tField Crops Research$gv. 286, 108628, Oct. 2022.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
03/08/2020 |
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Data da última atualização: |
03/08/2020 |
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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: |
VIEIRA, I. F. B.; ROLIM NETO, F. C.; CARVALHO, M. N.; CALDAS, A. M.; COSTA, R. C. A.; SILVA, K. S. da; PARAHYBA, R. da B. V.; PACHECO, F. A. L.; FERNANDES, L. F. S.; PISSARRA, T. C. T. |
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Afiliação: |
IGOR FELLIPE BATISTA VIEIRA, UFRPE; FERNANDO CARTAXO ROLIM NETO, UFRPE; MARILDA NASCIMENTO CARVALHO, UFPE; ANILDO MONTEIRO CALDAS, UFRPE; RENATA CRISTINA ARAÚJO COSTA, UNESP/FCAV; KAROLYNE SANTOS DA SILVA, UFPE; ROBERTO DA BOA VIAGEM PARAHYBA, CNPS; FERNANDO ANTONIO LEAL PACHECO, University of Trás-os-Montes and Alto Douro; LUÍS FILIPE SANCHES FERNANDES, University of Trás-os-Montes and Alto Douro; TERESA CRISTINA TARLÉ PISSARRA, UNESP/FCAV. |
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Título: |
Water security assessment of groundwater quality in an anthropized rural area from the Atlantic Forest Biome in Brazil. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Water, v. 12, n. 3, 623, 2020. |
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DOI: |
https://doi.org/10.3390/w12030623 |
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Idioma: |
Inglês |
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Conteúdo: |
The exploitation of natural resources has grown mainly due to the high rate of population growth that changed over time around the planet. Water is one of the most needed resources essential for survival. Despite all the efforts made to improve water security, an environmental impact related to anthropogenic influence remains of great concern, which is the alteration of surface and groundwater quality. In many regions around the world, there is limited or no access to rural and urban water supply while there is a need to improve sanitation facilities. This work evaluated the spatial distribution of groundwater and surface water quality as well as their changes in wet and dry seasons of the tropical climate in the Atlantic Forest Biome. The study area is under anthropogenic influence, which is in the municipality of Igarassú, Pernambuco State, Brazil. The analysis of the raw water was based on Standard Methods for Examination of Water and Wastewater, as referenced in the Brazilian Ministry of Health Consolidation Ordinance that sets standards for drinking water. The temporal analyses indicated a variation on water quality from the wet to the dry seasons, whereas the spatial results revealed deviations from the Brazilian's Water Supply Standards for some physicochemical parameters. There was an increase in the values of some parameters during the wet season in some hydrological compartments. The anthropized rural area from the Atlantic Forest Biome is affecting the water quality. It is, therefore, necessary to develop environmental policies and put them into practice by implementing engineering projects that guarantee proper treatment for raw water in order to bring the water quality back to a good status in this region. MenosThe exploitation of natural resources has grown mainly due to the high rate of population growth that changed over time around the planet. Water is one of the most needed resources essential for survival. Despite all the efforts made to improve water security, an environmental impact related to anthropogenic influence remains of great concern, which is the alteration of surface and groundwater quality. In many regions around the world, there is limited or no access to rural and urban water supply while there is a need to improve sanitation facilities. This work evaluated the spatial distribution of groundwater and surface water quality as well as their changes in wet and dry seasons of the tropical climate in the Atlantic Forest Biome. The study area is under anthropogenic influence, which is in the municipality of Igarassú, Pernambuco State, Brazil. The analysis of the raw water was based on Standard Methods for Examination of Water and Wastewater, as referenced in the Brazilian Ministry of Health Consolidation Ordinance that sets standards for drinking water. The temporal analyses indicated a variation on water quality from the wet to the dry seasons, whereas the spatial results revealed deviations from the Brazilian's Water Supply Standards for some physicochemical parameters. There was an increase in the values of some parameters during the wet season in some hydrological compartments. The anthropized rural area from the Atlantic Forest Biome is affecting the water quali... Mostrar Tudo |
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Thesagro: |
Água Potável; Lençol Freático; Qualidade da Água. |
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Thesaurus NAL: |
Drinking water; Environmental monitoring; Groundwater; Surface water; Water quality. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/215082/1/Water-security-assessment-of-groundwater-quality-in-an-anthropized-rural-area-from-the-Atlantic-Forest-Biome-in-Brazil-2020.pdf
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Marc: |
LEADER 02765naa a2200337 a 4500
001 2124163
005 2020-08-03
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/w12030623$2DOI
100 1 $aVIEIRA, I. F. B.
245 $aWater security assessment of groundwater quality in an anthropized rural area from the Atlantic Forest Biome in Brazil.$h[electronic resource]
260 $c2020
520 $aThe exploitation of natural resources has grown mainly due to the high rate of population growth that changed over time around the planet. Water is one of the most needed resources essential for survival. Despite all the efforts made to improve water security, an environmental impact related to anthropogenic influence remains of great concern, which is the alteration of surface and groundwater quality. In many regions around the world, there is limited or no access to rural and urban water supply while there is a need to improve sanitation facilities. This work evaluated the spatial distribution of groundwater and surface water quality as well as their changes in wet and dry seasons of the tropical climate in the Atlantic Forest Biome. The study area is under anthropogenic influence, which is in the municipality of Igarassú, Pernambuco State, Brazil. The analysis of the raw water was based on Standard Methods for Examination of Water and Wastewater, as referenced in the Brazilian Ministry of Health Consolidation Ordinance that sets standards for drinking water. The temporal analyses indicated a variation on water quality from the wet to the dry seasons, whereas the spatial results revealed deviations from the Brazilian's Water Supply Standards for some physicochemical parameters. There was an increase in the values of some parameters during the wet season in some hydrological compartments. The anthropized rural area from the Atlantic Forest Biome is affecting the water quality. It is, therefore, necessary to develop environmental policies and put them into practice by implementing engineering projects that guarantee proper treatment for raw water in order to bring the water quality back to a good status in this region.
650 $aDrinking water
650 $aEnvironmental monitoring
650 $aGroundwater
650 $aSurface water
650 $aWater quality
650 $aÁgua Potável
650 $aLençol Freático
650 $aQualidade da Água
700 1 $aROLIM NETO, F. C.
700 1 $aCARVALHO, M. N.
700 1 $aCALDAS, A. M.
700 1 $aCOSTA, R. C. A.
700 1 $aSILVA, K. S. da
700 1 $aPARAHYBA, R. da B. V.
700 1 $aPACHECO, F. A. L.
700 1 $aFERNANDES, L. F. S.
700 1 $aPISSARRA, T. C. T
773 $tWater$gv. 12, n. 3, 623, 2020.
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