| |
|
|
| Registros recuperados : 18 | |
| 2. |  | PROITE, K.; LEAL-BERTIOLI, S. C. M.; BERTIOLI, D.; FONSECA, F. C. A.; GUIMARÃES, P. M. Isolamento de análogos a genes de resistência de uma biblioteca genômica de Arachis stenosperma para mapeamento físico. In: ENCONTRO LATINO AMERICANO DE ESPECIALISTAS EM ARACHIS, 4., 2004, Brasília, DF. IV Encontro Latino-Americano de Especialistas em Arachis. Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia, 2004. Não paginado. (Embrapa Recursos Genéticos e Biotecnologia. Documentos, 127).| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
|    |
| 3. | | FONSECA, F. C. A.; SANTOS, R. F.; FÁVERO, A. P.; VALLS, J. F. M. Contagem de cromossomos de híbridos interespecíficos de Arachis. ENCONTRO DO TALENTO ESTUDANTIL DA EMBRAPA RECURSOS GENETICOS E BIOTECNOLOGIA, 8., 2003, Brasília, DF. Anais: resumos dos trabalhos. Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia, 2003. p. 67| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 4. | | FONSECA, F. C. A.; NIELEN, S.; LEAL-BERTIOLI, S. C. M.; GUIMARÃES, P. M.; BERTIOLI, D. J. Clonagem e caracterização de seqüências repetitivas no genoma de diferentes espécies de Arachis. In: ENCONTRO DA SOCIEDADE BRASILEIRA DE MELHORAMENTO DE PLANTAS REGIONAL DF, 1., 2005, Brasília, DF. [Anais...]. Brasília: Embrapa Recursos Genéticos e Biotecnologia, 2005. p. 148. (Embrapa Recursos Genéticos e Biotecnologia. Documentos, 144).| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 5. | | FONSECA, F. C. A.; NIELEN, S.; LEAL-BERTIOLI, S. C. M.; GUIMARÃES, P. M.; BERTIOLI, D. J. Caracterização e análise filogenética de retrotransposons LTR em três diferentes espécies de Arachis. In: ENCONTRO DO TALENTO ESTUDANTIL DA EMBRAPA RECURSOS GENÉTICOS E BIOTECNOLOGIA, 11., 2006, Brasília, DF. Anais: resumos dos trabalhos. Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia, 2006. p. 66.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 6. | | FONSECA, F. C. A.; NIELEN, S.; LEAL-BERTIOLI, S. C. M.; GUIMARÃES, P. M.; BERTIOLI, D. J. Isolamento e caracterização de seqüências repetitivas em espécies silvestres de Arachis. In: ENCONTRO DO TALENTO ESTUDANTIL DA EMBRAPA RECURSOS GENÉTICOS E BIOTECNOLOGIA, 10., 2005, Brasília, DF. Anais: resumos dos trabalhos. Brasília, DF: Embrapa Recursos Genéticos e Biotecnologia, 2005. p. 72.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 7. | | SANTOS, M. de L.; ALVES, G. S. C.; COTTA, M. G.; FONSECA, F. C. A.; TOGAWA, R. C.; COSTA, M. M. do C.; ALVES, A. A.; MILLER, R. N. G.; SOUZA JUNIOR, M. T. A large-scale analysis of resistance gene analogs (RGAs) encoding NBS domains in the genus Elaeis. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 50., 2017, Uberlândia. Anais... [S.l.]: SBF, 2017.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 8. | | SANTOS, M. de L.; COTTA, M. G.; FONSECA, F. C. A.; TOGAWA, R. C.; COSTA, M. M. do C.; ALVES, A. A.; MILLER, R. N. G.; SOUZA JUNIOR, M. T. A large-scale analysis of resistance gene analogs (RGAs) encoding NBS domains in the genus Elaeis. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 50., 2017, Uberlândia. Do manejo à edição do genoma: resumos. Brasília, DF: SBF, 2017. Não paginado. Poster 637.| Biblioteca(s): Embrapa Agroenergia. |
| |
| 9. | | FIRMINO, A. A. P.; FONSECA, F. C. A.; MACEDO, L. L. P.; TOGAWA, R. C.; SILVA JUNIOR, O. B. da; PAPPAS JUNIOR, G. J.; SA, M. F. G. de. Cotton boll weevil (Anthonomus Grandis) transcriptome pyrosequencing and insect-pest control by RNAI gene silencing. In: CONGRESSO BRASILEIRO DE BIOTECNOLOGIA, 3., 2010, Fortaleza. Programa e resumos. Brasília, DF: SBBiotec, 2010. p. 279.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 10. | | NORIEGA, D. D.; ARRAES, F. B. M.; ANTONINO, J. D.; MACEDO, L. L. P.; FONSECA, F. C. A.; TOGAWA, R. C.; GRYNBERG, P.; SILVA, M. C. M.; NEGRISOLI JUNIOR, A. S.; MORGANTE, C. V.; GROSSI-DE-SA, M. F. Comparative gut transcriptome analysis of Diatraea saccharalis in response to the dietary source. PLoS ONE, v. 15, n. 8, e0235575, 2020.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia; Embrapa Semiárido; Embrapa Tabuleiros Costeiros. |
| |
| 11. | | LUCENA, W. A.; PELEGRINI, P. B.; MARTINS-DE-SA, D.; FONSECA, F. C. A.; GOMES JÚNIOR, J. E.; MACEDO, L. L. P. de; SILVA, M. C. M. da; OLIVEIRA, R. D.; GROSSI DE SA, M. F. Molecular approaches to improve the insecticidal activity of Bacillus thuringiensis cry toxins. Toxins, v. 6, p. 2393-2423, 2014.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 12. | | SILVA, M. C. M. da; GOMES JÚNIOR, J. E.; MACEDO, L. L. P.; LUCENA, W. A.; FONSECA, F. C. A.; SOUZA JUNIOR, J. D. de; SÁ, D. M.; PELEGRINI, P. B.; SA, M. F. G. de. Molecular evolution in vitro of cry toxins for the control of pests in sugarcane. In: CONGRESSO BRASILEIRO DE GENÉTICA, 57., 2011, Águas de Lindóia. Anais... Águas de Lindóia: SBG, 2011. p. 41| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
|  |
| 13. | | NORIEGA, D. D.; ARRAES, F. B. M.; ANTONINO, J. D.; MACEDO, L. L. P.; FONSECA, F. C. A.; TOGAWA, R. C.; GRYNBERG, P.; SILVA, M. C. M.; NEGRISOLI JUNIOR, A. S.; GROSSI-DE-SA, M. F. Transcriptome analysis and knockdown of the juvenile hormone esterase gene reveal abnormal feeding behavior in the sugarcane giant borer. Frontiers in Physiology, v. 11, article 588450, 2020.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 14. | | NORIEGA, D. D.; ARRAES, F. B. M.; ANTONINO, J. D.; MACEDO, L. L. P. de; FONSECA, F. C. A.; TOGAWA, R. C.; GRYNBERG, P.; SILVA, M. C. M. da; NEGRISOLI JUNIOR, A. S.; SA, M. F. G. de. Transcriptome Analysis and Knockdown of the Juvenile Hormone Esterase Gene Reveal Abnormal Feeding Behavior in the Sugarcane Giant Borer. Frontiers in Physiology, v. 11, 588450, jul. 2020.| Biblioteca(s): Embrapa Tabuleiros Costeiros. |
| |
| 15. | | CRAVEIRO, K. I. C.; GOMES JÚNIOR, J. E.; RAMOS, H. B.; ANTONINO SOUZA JÚNIOR, J. D.; FONSECA, F. C. A.; SILVA, M. C. M.; GROSSI DE SÁ, M. M. Screening for new cry toxins to sugarcane giant borer insect pest. In: ANNUAL MEETING OF SBBQ, 37.; CONGRESS OF THE PABMB, 11., 2008, Águas de Lindóia, SP. Abstracts... Águas de Lindóia: SBBq, 2008. 1 CD-ROM.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 16. | | ALBUQUERQUE, G. M. R.; FONSECA, F. C. A.; BOITEUX, L. S.; BORGES, R. C. F.; MILLER, R. N. G.; LOPES, C. A.; SOUZA, E. B.; FONSECA, M. E. N. Stability analysis of reference genes for RT-qPCR assays involving compatible and incompatible Ralstonia solanacearum-tomato 'Hawaii 7996' interactions. Scientific Reports, v. 11, p. 18719, 2021.| Biblioteca(s): Embrapa Hortaliças. |
| |
| 17. | | MACEDO, L. L. P.; SOUZA JUNIOR, J. D. D. de; COELHO, R. R.; FONSECA, F. C. A.; FIRMINO, A. A. P.; SILVA, M. C. M.; FRAGOSO, R. R.; ALBUQUERQUE, E. V. S.; SILVA, M. S.; ENGLER, J. de A.; TERRA, W. R.; GROSSI-DE-SA, M. F. Knocking down chitin synthase 2 by RNAi is lethal to the cotton boll weevil. Biotechnology Research and Innovation, v. 1, p. 72-86, 2017.| Biblioteca(s): Embrapa Cerrados; Embrapa Recursos Genéticos e Biotecnologia. |
| |
| 18. | | COELHO, R. R.; SOUZA JUNIOR, J. D. A. de; FIRMINO, A. A. P.; MACEDO, L. L. P. de; FONSECA, F. C. A.; TERRA, W. R.; ENGLER, G.; ENGLER, J. de A.; SILVA, M. C. M. da; GROSSI-DE-SA, M. F. Vitellogenin knockdown strongly affects cotton boll weevil egg viability but not the number of eggs laid by females. Meta Gene, v. 9, p. 173-180, 2016.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
| |
| Registros recuperados : 18 | |
|
|
|
Registro Completo
|
Biblioteca(s): |
Embrapa Arroz e Feijão. |
|
Data corrente: |
28/07/2022 |
|
Data da última atualização: |
03/02/2023 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
B - 1 |
|
Autoria: |
ARENAS-CALLE, L. N.; HEINEMANN, A. B.; SILVA, M. A. S. da; SANTOS, A. B. dos; RAMIREZ-VILLEGAS, J.; WHITFIELD, S.; CHALLINOR, A. J. |
|
Afiliação: |
LAURA N. ARENAS-CALLE, University of Leeds; ALEXANDRE BRYAN HEINEMANN, CNPAF; MELLISSA ANANIAS SOLER DA SILVA, CNPAF; ALBERTO BAETA DOS SANTOS, CNPAF; JULIAN RAMIREZ-VILLEGAS, Alliance of Biodiversity International and CIAT; STEPHEN WHITFIELD, University of Leeds, Leeds; ANDREW J. CHALLINOR, University of Leeds, Leeds. |
|
Título: |
Rice management decisions using process-based models with climate-smart indicators. |
|
Ano de publicação: |
2022 |
|
Fonte/Imprenta: |
Frontiers in Sustainable Food Systems, v. 6, article 873957, Jul. 2022. |
|
ISSN: |
2571-581X |
|
Idioma: |
Inglês |
|
Conteúdo: |
Irrigation strategies are keys to fostering sustainable and climate-resilient rice production by increasing efficiency, building resilience and reducing Greenhouse Gas (GHG) emissions. These strategies are aligned with the Climate-Smart Agriculture (CSA) principles, which aim to maximize productivity whilst adapting to and mitigating climate change. Achieve such mitigation, adaptation, and productivity goals- to the extent possible- is described as climate smartness. Measuring climate smartness is challenging, with recent progress focusing on the use of agronomic indicators in a limited range of contexts. One way to broaden the ability to measure climate-smartness is to use modeling tools, expanding the scope of climate smartness assessments. Accordingly, and as a proof-of-concept, this study uses modeling tools with CSA indicators (i.e., Greenhouse Intensity and Water Productivity) to quantify the climate-smartness of irrigation management in rice and to assess sensitivity to climate. We focus on a field experiment that assessed four irrigation strategies in tropical conditions, Continuous Flooding (CF), Intermittent Irrigation (II), Intermittent Irrigation until Flowering (IIF), and Continuous soil saturation (CSS). The DNDC model was used to simulate rice yields, GHG emissions and water inputs. We used model outputs to calculate a previously developed Climate-Smartness Index (CSI) based on water productivity and greenhouse gas intensity, which score on a scale between - 1 (lack of climate-smartness) to 1 (high climate smartness) the climate-smartness of irrigation strategies. The CSS exhibited the highest simulation-based CSI, and CF showed the lowest. A sensitivity analysis served to explore the impacts of climate on CSI. While higher temperatures reduced CSI, rainfall mostly showed no signal. The climate smartness decreasing in warmer temperatures was associated with increased GHG emissions and, to some extent, a reduction in Water Productivity (WP). Overall, CSI varied with the climate-management interaction, demonstrating that climate variability can influence the performance of CSA practices. We conclude that combining models with climate-smart indicators can broaden he CSA-based evidence and provide reproducible research findings. The methodological approach used in this study can be useful to fill gaps in observational evidence of climate-smartness and project the impact of future climates in regions where calibrated crop models perform well. MenosIrrigation strategies are keys to fostering sustainable and climate-resilient rice production by increasing efficiency, building resilience and reducing Greenhouse Gas (GHG) emissions. These strategies are aligned with the Climate-Smart Agriculture (CSA) principles, which aim to maximize productivity whilst adapting to and mitigating climate change. Achieve such mitigation, adaptation, and productivity goals- to the extent possible- is described as climate smartness. Measuring climate smartness is challenging, with recent progress focusing on the use of agronomic indicators in a limited range of contexts. One way to broaden the ability to measure climate-smartness is to use modeling tools, expanding the scope of climate smartness assessments. Accordingly, and as a proof-of-concept, this study uses modeling tools with CSA indicators (i.e., Greenhouse Intensity and Water Productivity) to quantify the climate-smartness of irrigation management in rice and to assess sensitivity to climate. We focus on a field experiment that assessed four irrigation strategies in tropical conditions, Continuous Flooding (CF), Intermittent Irrigation (II), Intermittent Irrigation until Flowering (IIF), and Continuous soil saturation (CSS). The DNDC model was used to simulate rice yields, GHG emissions and water inputs. We used model outputs to calculate a previously developed Climate-Smartness Index (CSI) based on water productivity and greenhouse gas intensity, which score on a scale between - 1... Mostrar Tudo |
|
Palavras-Chave: |
Climate-smart agriculture; Climate-smart indicators; Climate-smartness; DNDC; Water productivity. |
|
Thesagro: |
Arroz; Clima. |
|
Thesaurus NAL: |
Climate models; Crop models; Greenhouse gas emissions. |
|
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/246232/1/fsfs-2022.pdf
|
|
Marc: |
LEADER 03448naa a2200325 a 4500
001 2145047
005 2023-02-03
008 2022 bl uuuu u00u1 u #d
022 $a2571-581X
100 1 $aARENAS-CALLE, L. N.
245 $aRice management decisions using process-based models with climate-smart indicators.$h[electronic resource]
260 $c2022
520 $aIrrigation strategies are keys to fostering sustainable and climate-resilient rice production by increasing efficiency, building resilience and reducing Greenhouse Gas (GHG) emissions. These strategies are aligned with the Climate-Smart Agriculture (CSA) principles, which aim to maximize productivity whilst adapting to and mitigating climate change. Achieve such mitigation, adaptation, and productivity goals- to the extent possible- is described as climate smartness. Measuring climate smartness is challenging, with recent progress focusing on the use of agronomic indicators in a limited range of contexts. One way to broaden the ability to measure climate-smartness is to use modeling tools, expanding the scope of climate smartness assessments. Accordingly, and as a proof-of-concept, this study uses modeling tools with CSA indicators (i.e., Greenhouse Intensity and Water Productivity) to quantify the climate-smartness of irrigation management in rice and to assess sensitivity to climate. We focus on a field experiment that assessed four irrigation strategies in tropical conditions, Continuous Flooding (CF), Intermittent Irrigation (II), Intermittent Irrigation until Flowering (IIF), and Continuous soil saturation (CSS). The DNDC model was used to simulate rice yields, GHG emissions and water inputs. We used model outputs to calculate a previously developed Climate-Smartness Index (CSI) based on water productivity and greenhouse gas intensity, which score on a scale between - 1 (lack of climate-smartness) to 1 (high climate smartness) the climate-smartness of irrigation strategies. The CSS exhibited the highest simulation-based CSI, and CF showed the lowest. A sensitivity analysis served to explore the impacts of climate on CSI. While higher temperatures reduced CSI, rainfall mostly showed no signal. The climate smartness decreasing in warmer temperatures was associated with increased GHG emissions and, to some extent, a reduction in Water Productivity (WP). Overall, CSI varied with the climate-management interaction, demonstrating that climate variability can influence the performance of CSA practices. We conclude that combining models with climate-smart indicators can broaden he CSA-based evidence and provide reproducible research findings. The methodological approach used in this study can be useful to fill gaps in observational evidence of climate-smartness and project the impact of future climates in regions where calibrated crop models perform well.
650 $aClimate models
650 $aCrop models
650 $aGreenhouse gas emissions
650 $aArroz
650 $aClima
653 $aClimate-smart agriculture
653 $aClimate-smart indicators
653 $aClimate-smartness
653 $aDNDC
653 $aWater productivity
700 1 $aHEINEMANN, A. B.
700 1 $aSILVA, M. A. S. da
700 1 $aSANTOS, A. B. dos
700 1 $aRAMIREZ-VILLEGAS, J.
700 1 $aWHITFIELD, S.
700 1 $aCHALLINOR, A. J.
773 $tFrontiers in Sustainable Food Systems$gv. 6, article 873957, Jul. 2022.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Expressão de busca inválida. Verifique!!! |
|
|
