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Registro Completo |
Biblioteca(s): |
Embrapa Agroindústria de Alimentos; Embrapa Agroindústria Tropical; Embrapa Amapá; Embrapa Amazônia Oriental; Embrapa Florestas; Embrapa Pantanal; Embrapa Rondônia; Embrapa Semiárido; Embrapa Soja; Embrapa Solos; Embrapa Trigo; Embrapa Unidades Centrais. MenosEmbrapa Agroindústria de Alimentos; Embrapa Agroindústria Tropical; Embrapa Amapá; Embrapa Amazônia Oriental; Embrapa Florestas; Embrapa Pantanal; Embrapa Rondônia; Embrapa Semiárido; Embrapa Soja; Embrapa Solos... Mostrar Todas |
Data corrente: |
19/01/2006 |
Data da última atualização: |
11/08/2011 |
Tipo da produção científica: |
Documentos |
Autoria: |
EMBRAPA FLORESTAS. |
Título: |
III Plano Diretor da Embrapa Florestas 2004 a 2007. |
Ano de publicação: |
2005 |
Fonte/Imprenta: |
Colombo, 2005. |
Páginas: |
40 p. |
Série: |
(Embrapa Florestas. Documentos, 111). |
ISSN: |
1517-526X |
Idioma: |
Português |
Conteúdo: |
Introdução; Visão de futuro; Missão, visão, valores e foco de atuação; Objetivos estratégicos e metas; Diretrizes estratégicas e metas; Projetos estruturantes e integrantes. |
Palavras-Chave: |
Brasil; Embrapa Florestas; Embrapa Florestas - Plano diretor; Instituição; instituição de pesquisa - Plano diretor - Brasil; Master plan; Missão; Objetivos e Projetos; Plano diretor. |
Thesagro: |
Agricultura; Floresta; Gestão; Instituição de Pesquisa; Pesquisa; Pesquisa Florestal; Planejamento; Planejamento Estratégico; Setor Florestal. |
Categoria do assunto: |
-- X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/CNPF-2009-09/38950/1/doc111.pdf
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Marc: |
LEADER 01161nam a2200361 a 4500 001 1278580 005 2011-08-11 008 2005 bl uuuu u0uu1 u #d 022 $a1517-526X 100 1 $aEMBRAPA FLORESTAS. 245 $aIII Plano Diretor da Embrapa Florestas 2004 a 2007. 260 $aColombo$c2005 300 $a40 p. 490 $a(Embrapa Florestas. Documentos, 111). 520 $aIntrodução; Visão de futuro; Missão, visão, valores e foco de atuação; Objetivos estratégicos e metas; Diretrizes estratégicas e metas; Projetos estruturantes e integrantes. 650 $aAgricultura 650 $aFloresta 650 $aGestão 650 $aInstituição de Pesquisa 650 $aPesquisa 650 $aPesquisa Florestal 650 $aPlanejamento 650 $aPlanejamento Estratégico 650 $aSetor Florestal 653 $aBrasil 653 $aEmbrapa Florestas 653 $aEmbrapa Florestas - Plano diretor 653 $aInstituição 653 $ainstituição de pesquisa - Plano diretor - Brasil 653 $aMaster plan 653 $aMissão 653 $aObjetivos e Projetos 653 $aPlano diretor
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Registro original: |
Embrapa Florestas (CNPF) |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
06/03/2020 |
Data da última atualização: |
20/04/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
RAMIREZ-VILLEGAS, J.; MOLERO MILAN, A.; ALEXANDROV, N.; ASSENG, S.; CHALLINOR, A. J.; CROSSA, J.; VAN EEUWIJK, F.; GHANEM, M. E.; GRENIER, C.; HEINEMANN, A. B.; WANG, J.; JULIANA, P.; KEHEL, Z.; KHOLOVA, J; KOO, J.; PEQUENO, D.; QUIROZ, R.; REBOLLEDO, M. C.; SUKUMARAN, S.; VADEZ, V.; WHITE, J. W.; REYNOLDS, M. |
Afiliação: |
JULIAN RAMIREZ-VILLEGAS, CIAT; ANABEL MOLERO MILAN, CIMMYT; NICKOLAI ALEXANDROV, IRRI; SENTHOLD ASSENG, UNIVERSITY OF FLORIDA, Gainesville-FL; ANDREW J. CHALLINOR, UNIVERSITY OF LEEDS, Leeds-UK; JOSE CROSSA, CIMMYT; FREED VAN EEUWIJK, WAGENINGEN UNIVERSITY, The Netherlands; MICHEL EDMOND GHANEM, ICARDA; CECILE GRENIER, CIAT; ALEXANDRE BRYAN HEINEMANN, CNPAF; JIANKANG WANG, INSTITUTE OF CROP SCIENCES, Beijing; PHILOMIN JULIANA, CIMMYT; ZAKARIA KEHEL, ICARDA; JANA KHOLOVA, ICRISAT; JAWOO KOO, IFPRI; DIEGO PEQUENO, CIMMYT; ROBERTO QUIROZ, CIP; MARIA C. REBOLLEDO, CIAT; SIVAKUMAR SUKUMARAN, CIMMYT; VINCENT VADEZ, ICRISAT; JEFFREY W. WHITE, USDA-ARS; MATTHEW REYNOLDS, CIMMYT. |
Título: |
CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Crop Science, 2020. |
ISSN: |
0011-183X |
DOI: |
10.1002/csc2.20048 |
Idioma: |
Inglês |
Notas: |
Online Version of Record before inclusion in an issue. |
Conteúdo: |
Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains 'to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?'. Here, we address this question by critically reviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better-targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts. MenosCrop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains 'to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?'. Here, we address this question by critically reviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follo... Mostrar Tudo |
Palavras-Chave: |
Crop improvement; Crop modeling. |
Thesagro: |
Clima. |
Thesaurus NAL: |
Breeding; Climate change; Crops; Food security; Plant adaptation; Simulation models. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/211586/1/CNPAF-2020-cs.pdf
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Marc: |
LEADER 03114naa a2200517 a 4500 001 2121007 005 2020-04-20 008 2020 bl uuuu u00u1 u #d 022 $a0011-183X 024 7 $a10.1002/csc2.20048$2DOI 100 1 $aRAMIREZ-VILLEGAS, J. 245 $aCGIAR modeling approaches for resource-constrained scenarios$bI. Accelerating crop breeding for a changing climate.$h[electronic resource] 260 $c2020 500 $aOnline Version of Record before inclusion in an issue. 520 $aCrop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains 'to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?'. Here, we address this question by critically reviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better-targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts. 650 $aBreeding 650 $aClimate change 650 $aCrops 650 $aFood security 650 $aPlant adaptation 650 $aSimulation models 650 $aClima 653 $aCrop improvement 653 $aCrop modeling 700 1 $aMOLERO MILAN, A. 700 1 $aALEXANDROV, N. 700 1 $aASSENG, S. 700 1 $aCHALLINOR, A. J. 700 1 $aCROSSA, J. 700 1 $aVAN EEUWIJK, F. 700 1 $aGHANEM, M. E. 700 1 $aGRENIER, C. 700 1 $aHEINEMANN, A. B. 700 1 $aWANG, J. 700 1 $aJULIANA, P. 700 1 $aKEHEL, Z. 700 1 $aKHOLOVA, J 700 1 $aKOO, J. 700 1 $aPEQUENO, D. 700 1 $aQUIROZ, R. 700 1 $aREBOLLEDO, M. C. 700 1 $aSUKUMARAN, S. 700 1 $aVADEZ, V. 700 1 $aWHITE, J. W. 700 1 $aREYNOLDS, M. 773 $tCrop Science, 2020.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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