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Registro Completo |
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Biblioteca(s): |
Embrapa Agroindústria Tropical; Embrapa Amapá; Embrapa Amazônia Ocidental; Embrapa Amazônia Oriental; Embrapa Meio Norte / UEP-Parnaíba; Embrapa Meio-Norte; Embrapa Rondônia; Embrapa Semiárido. |
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Data corrente: |
28/04/2004 |
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Data da última atualização: |
05/08/2011 |
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Autoria: |
CRISÓSTOMO, J. R.; CARDOSO, J. W.; SANTOS, A. A. dos; CARDOSO, J. E.; BLEICHER, E.; ROSSETTI, A. G.; LIMA, R. N.; FREITAS, J. G. |
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Título: |
Desempenho de híbridos de melão amarelo no Ceará e Rio Grande do Norte, no período 1999 - 2001. |
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Ano de publicação: |
2003 |
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Fonte/Imprenta: |
Fortaleza: Embrapa Agroindústria Tropical, 2003. |
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Páginas: |
8 p. |
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Série: |
(Embrapa Agroindústria Tropical. Comunicado Técnico, 85). |
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Idioma: |
Português |
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Conteúdo: |
Para a comercialização de cultivares no Brasil, é adotado pelo MAPA, desde 1997, o Registro Nacional de Cultivares (RNC) que ordena o mercado, protegendo o produtor da venda indiscriminada de sementes e mudas, de cultivares que não tenham sido testadas nas condições da agricultura brasileira ou de cultivares que já perderam suas características de pureza genética. No caso do melão, os híbridos e cultivares em uso no Nordeste, ainda não fazem parte do RNC, não sendo exigido, até o momento, a rede necessária de experimentos para definir o grau de adaptação às nossas condições, dos diversos híbridos que são periodicamente disponibilizados no mercado. |
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Palavras-Chave: |
Amarelo; Avaliação de brix; Brasil; Ceará; Cultivo; Desempenho de produção; Índice de precocidade; Melão - Agronegócio - Economia - Ceará - Rio Grande do Norte; Melão amarelo; Reação a doenças; Rio Grande do Norte. |
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Thesagro: |
Hibrido; Melão; Mercado; Performance; Produção; Variedade. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/CNPAT-2010/9005/1/Ct-085.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/CNPAT/7850/1/ct_85.pdf
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Marc: |
LEADER 01890nam a2200421 a 4500
001 1425890
005 2011-08-05
008 2003 bl uuuu u0uu1 u #d
100 1 $aCRISÓSTOMO, J. R.
245 $aDesempenho de híbridos de melão amarelo no Ceará e Rio Grande do Norte, no período 1999 - 2001.
260 $aFortaleza: Embrapa Agroindústria Tropical$c2003
300 $a8 p.
490 $a(Embrapa Agroindústria Tropical. Comunicado Técnico, 85).
520 $aPara a comercialização de cultivares no Brasil, é adotado pelo MAPA, desde 1997, o Registro Nacional de Cultivares (RNC) que ordena o mercado, protegendo o produtor da venda indiscriminada de sementes e mudas, de cultivares que não tenham sido testadas nas condições da agricultura brasileira ou de cultivares que já perderam suas características de pureza genética. No caso do melão, os híbridos e cultivares em uso no Nordeste, ainda não fazem parte do RNC, não sendo exigido, até o momento, a rede necessária de experimentos para definir o grau de adaptação às nossas condições, dos diversos híbridos que são periodicamente disponibilizados no mercado.
650 $aHibrido
650 $aMelão
650 $aMercado
650 $aPerformance
650 $aProdução
650 $aVariedade
653 $aAmarelo
653 $aAvaliação de brix
653 $aBrasil
653 $aCeará
653 $aCultivo
653 $aDesempenho de produção
653 $aÍndice de precocidade
653 $aMelão - Agronegócio - Economia - Ceará - Rio Grande do Norte
653 $aMelão amarelo
653 $aReação a doenças
653 $aRio Grande do Norte
700 1 $aCARDOSO, J. W.
700 1 $aSANTOS, A. A. dos
700 1 $aCARDOSO, J. E.
700 1 $aBLEICHER, E.
700 1 $aROSSETTI, A. G.
700 1 $aLIMA, R. N.
700 1 $aFREITAS, J. G.
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Registro original: |
Embrapa Agroindústria Tropical (CNPAT) |
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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. |
Registro Completo
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
05/05/2020 |
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Data da última atualização: |
06/05/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 5 |
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Autoria: |
AGUIAR, J. T. de; LOBO JUNIOR, M. |
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Afiliação: |
JORDENE TEIXEIRA DE AGUIAR, UFG; MURILLO LOBO JUNIOR, CNPAF. |
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Título: |
Reliability and discrepancies of rainfall and temperatures from remote sensing and Brazilian ground weather stations. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Remote Sensing Applications: Society and Environment, v. 18, 100301, Apr. 2020. |
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ISSN: |
2352-9385 |
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DOI: |
https://doi.org/10.1016/j.rsase.2020.100301 |
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Idioma: |
Inglês |
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Conteúdo: |
Insufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological stations in latitudes from 0 to 33 oS, to support agricultural research in Brazil. The dataset comprised 3600 records of monthly temperatures and rainfall from 01 Jan 2004 to 31 Dec 2014 in 30 Brazilian municipalities distributed in six regions, labeled according to their precipitation homogeneity. Climatic records from NASA?s Prediction of Worldwide Energy Resource (POWER) online database were compared with data from Brazilian surface stations managed by National Institute of Meteorology (INMET). Monthly rainfall data showed satisfactory correlation coefficients for almost all locations, between 0.75 and 0.95 (p < 0.01), and simple linear models were fit for estimated (satellite) and observed (ground) rainfall relationship (p < 0.001). Complimentary accuracy and precision tests endorsed rainfall satellite-estimated data according to the root mean square error (RMSE) and the modified index of agreement. Maximum and minimum temperatures estimated by remote sensing in the Brazilian South Region were also statistically supported, but unsuitable results were found especially in lower latitudes, based on higher RMSE. The Pearson?s correlation coefficient for temperatures increased proportionally with latitude, while rainfall did not show this correlation. These results showed satellite-data quality varies regionally and is affected by seasonal variation. Remote sensors may not detect extreme climatic events such as heavy rainfall or draught and, therefore, need to be appraised carefully. MenosInsufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological stations in latitudes from 0 to 33 oS, to support agricultural research in Brazil. The dataset comprised 3600 records of monthly temperatures and rainfall from 01 Jan 2004 to 31 Dec 2014 in 30 Brazilian municipalities distributed in six regions, labeled according to their precipitation homogeneity. Climatic records from NASA?s Prediction of Worldwide Energy Resource (POWER) online database were compared with data from Brazilian surface stations managed by National Institute of Meteorology (INMET). Monthly rainfall data showed satisfactory correlation coefficients for almost all locations, between 0.75 and 0.95 (p < 0.01), and simple linear models were fit for estimated (satellite) and observed (ground) rainfall relationship (p < 0.001). Complimentary accuracy and precision tests endorsed rainfall satellite-estimated data according to the root mean square error (RMSE) and the modified index of agreement. Maximum and minimum temperatures estimated by remote sensing in the Brazilian South Region were also statistically supported, but unsuitable results were found especially in lower latitudes, based on higher RMSE. The Pearson?s correlation coefficient for temperatures increased pro... Mostrar Tudo |
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Thesagro: |
Climatologia; Modelo de Simulação; Sensoriamento Remoto. |
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Thesaurus NAL: |
Agriculture; Climatology; Decision support systems; Remote sensing. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02613naa a2200241 a 4500
001 2122081
005 2020-05-06
008 2020 bl uuuu u00u1 u #d
022 $a2352-9385
024 7 $ahttps://doi.org/10.1016/j.rsase.2020.100301$2DOI
100 1 $aAGUIAR, J. T. de
245 $aReliability and discrepancies of rainfall and temperatures from remote sensing and Brazilian ground weather stations.$h[electronic resource]
260 $c2020
520 $aInsufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological stations in latitudes from 0 to 33 oS, to support agricultural research in Brazil. The dataset comprised 3600 records of monthly temperatures and rainfall from 01 Jan 2004 to 31 Dec 2014 in 30 Brazilian municipalities distributed in six regions, labeled according to their precipitation homogeneity. Climatic records from NASA?s Prediction of Worldwide Energy Resource (POWER) online database were compared with data from Brazilian surface stations managed by National Institute of Meteorology (INMET). Monthly rainfall data showed satisfactory correlation coefficients for almost all locations, between 0.75 and 0.95 (p < 0.01), and simple linear models were fit for estimated (satellite) and observed (ground) rainfall relationship (p < 0.001). Complimentary accuracy and precision tests endorsed rainfall satellite-estimated data according to the root mean square error (RMSE) and the modified index of agreement. Maximum and minimum temperatures estimated by remote sensing in the Brazilian South Region were also statistically supported, but unsuitable results were found especially in lower latitudes, based on higher RMSE. The Pearson?s correlation coefficient for temperatures increased proportionally with latitude, while rainfall did not show this correlation. These results showed satellite-data quality varies regionally and is affected by seasonal variation. Remote sensors may not detect extreme climatic events such as heavy rainfall or draught and, therefore, need to be appraised carefully.
650 $aAgriculture
650 $aClimatology
650 $aDecision support systems
650 $aRemote sensing
650 $aClimatologia
650 $aModelo de Simulação
650 $aSensoriamento Remoto
700 1 $aLOBO JUNIOR, M.
773 $tRemote Sensing Applications: Society and Environment$gv. 18, 100301, Apr. 2020.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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