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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
06/01/2016 |
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Data da última atualização: |
07/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
GONÇALVES, R. R. do V.; ZULLO JÚNIOR, J.; PERON, T. M.; EVANGELISTA, S. R. M.; ROMANI, L. A. S. |
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Afiliação: |
RENATA RIBEIRO DO VALLE GONÇALVES, Unicamp; JURANDIR ZULLO JÚNIOR, Unicamp; TAIS MARQUES PERON, Estagiária CNPTIA; SILVIO ROBERTO MEDEIROS EVANGELISTA, CNPTIA; LUCIANA ALVIM SANTOS ROMANI, CNPTIA. |
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Título: |
Numerical models to forecast the sugarcane production in regional scale based on time series of NDVI/AVHRR images. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTITEMPORAL REMOTE SENSING IMAGES, 8., 2015, Annecy. Proceedings... [Piscataway]: IEEE, 2015. |
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Páginas: |
Não paginado. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: The use of time series of meteorological satellite images, such as the AVHRR/NOAA, and agrometeorological data can be very useful in developing monitoring and forecasting methods for sugarcane crops because they are based on detection changes of space-time behavior. The knowledge about different sugarcane producing areas and climate in a given region is information required to develop models that can be applied simultaneously to several producing municipalities of sugarcane in order to assess the relation between NDVI and WRSI, the estimated productivity and the detection of similarity between the municipalities through distance functions. Thus, the main goal of this paper is to propose numerical models applied to monitor the sugarcane production based on time series of NDVI/AVHRR images and agrometeorological data. The regression method analyzes the relation between a single dependent variable (sugarcane production) and several independent variables (planted area, NDVI, WRSI), that is, use the independent variables whose values are known to predict the values of the selected dependent variable. The models proposed to estimate the sugarcane production using the variables planted area, NDVI and WRSI presented correlation coefficients (R2) around 0.9 and are able to estimate the sugarcane production for the state of São Paulo in Brazil |
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Palavras-Chave: |
Cana-de-açúcar; Dados de sensoriamento remoto; Linear regression; Multiple linear regression; Remote sensing data; Séries temporais. |
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Thesaurus Nal: |
Sugarcane; Time series analysis. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02310nam a2200265 a 4500
001 2033024
005 2020-01-07
008 2015 bl uuuu u00u1 u #d
100 1 $aGONÇALVES, R. R. do V.
245 $aNumerical models to forecast the sugarcane production in regional scale based on time series of NDVI/AVHRR images.$h[electronic resource]
260 $aIn: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTITEMPORAL REMOTE SENSING IMAGES, 8., 2015, Annecy. Proceedings... [Piscataway]: IEEE$c2015
300 $aNão paginado.
520 $aAbstract: The use of time series of meteorological satellite images, such as the AVHRR/NOAA, and agrometeorological data can be very useful in developing monitoring and forecasting methods for sugarcane crops because they are based on detection changes of space-time behavior. The knowledge about different sugarcane producing areas and climate in a given region is information required to develop models that can be applied simultaneously to several producing municipalities of sugarcane in order to assess the relation between NDVI and WRSI, the estimated productivity and the detection of similarity between the municipalities through distance functions. Thus, the main goal of this paper is to propose numerical models applied to monitor the sugarcane production based on time series of NDVI/AVHRR images and agrometeorological data. The regression method analyzes the relation between a single dependent variable (sugarcane production) and several independent variables (planted area, NDVI, WRSI), that is, use the independent variables whose values are known to predict the values of the selected dependent variable. The models proposed to estimate the sugarcane production using the variables planted area, NDVI and WRSI presented correlation coefficients (R2) around 0.9 and are able to estimate the sugarcane production for the state of São Paulo in Brazil
650 $aSugarcane
650 $aTime series analysis
653 $aCana-de-açúcar
653 $aDados de sensoriamento remoto
653 $aLinear regression
653 $aMultiple linear regression
653 $aRemote sensing data
653 $aSéries temporais
700 1 $aZULLO JÚNIOR, J.
700 1 $aPERON, T. M.
700 1 $aEVANGELISTA, S. R. M.
700 1 $aROMANI, L. A. S.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
03/11/2017 |
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Data da última atualização: |
03/11/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 3 |
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Autoria: |
SOUZA, I. R. P. de; MACEDO, G. A. R.; BARBOSA, M. H. P.; BARROS, B. de A.; CARVALHO, S. G. M.; XAVIER, A. da S.; GONÇALVES, I. A. M. |
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Afiliação: |
ISABEL REGINA PRAZERES DE SOUZA, CNPMS; Geraldo Antônio Resende Macêdo, Epamig; Márcio Henrique Pereira Barbosa, Universidade Federal de Viçosa; BEATRIZ DE ALMEIDA BARROS, CNPMS; Samanta Gabriela Medeiros Carvalho, UFLA; André da Silva Xavier, Bolsista; Isabella Aparecida Maia Gonçalves, UNIFEMM. |
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Título: |
Reaction of sugarcane genotypes to strains of the sugarcane mosaic virus. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
International Journal of Current Research, v. 9, n. 10, p. 59112-59119, Oct. 2017. |
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Idioma: |
Inglês |
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Conteúdo: |
Sugarcane crops are cultivated in nearly all tropical and sub-tropical regions worldwide andhave a prominent position in the agricultural scenario in Brazil. However, viral diseases can threaten the production of this important commodity leading to large production losses. In the present study, we evaluatedthe reaction of 20 sugarcane genotypes independently inoculated with two different strains of Sugarcane mosaic virus (SCMV) isolated from naturally infected sugarcane (SCMV-SGC) and maize (SCMV-MZ). The maize inbred line L19 was used as a control of susceptibility to the SCMV-MZ strain. Symptoms intensity was evaluated through a visual scale with three levels of severity: weak, intermediate, and intense. The viral infection was confirmed by PCR and DNA sequencing. We observed that, although both strains were able to infect sugarcane genotypes and the maize inbred line, SCMV-SGC was more aggressive, resulting in only four resistant genotypes: IN84-58 (S. spontaneum), RB855536, RB 928064, and SP71-6163. Thirteen genotypes were resistant to SCMV-MZ: IN84-58 (S.spontaneum), NA56-79, CB47-355,CB49-260, RB72454, RB855113, RB855536, RB867515, RB928064, SP70-1143, SP71-1406, SP71-6163, and SP81-3250. This is the first report showingSCMV strains capable of cross-infectingand causing mosaic in sugarcane and maize. Our data emphasize the importance of continuous monitoring and screening for virus resistantgenotypes to be used in breeding programs for the development of new resistant cultivars. MenosSugarcane crops are cultivated in nearly all tropical and sub-tropical regions worldwide andhave a prominent position in the agricultural scenario in Brazil. However, viral diseases can threaten the production of this important commodity leading to large production losses. In the present study, we evaluatedthe reaction of 20 sugarcane genotypes independently inoculated with two different strains of Sugarcane mosaic virus (SCMV) isolated from naturally infected sugarcane (SCMV-SGC) and maize (SCMV-MZ). The maize inbred line L19 was used as a control of susceptibility to the SCMV-MZ strain. Symptoms intensity was evaluated through a visual scale with three levels of severity: weak, intermediate, and intense. The viral infection was confirmed by PCR and DNA sequencing. We observed that, although both strains were able to infect sugarcane genotypes and the maize inbred line, SCMV-SGC was more aggressive, resulting in only four resistant genotypes: IN84-58 (S. spontaneum), RB855536, RB 928064, and SP71-6163. Thirteen genotypes were resistant to SCMV-MZ: IN84-58 (S.spontaneum), NA56-79, CB47-355,CB49-260, RB72454, RB855113, RB855536, RB867515, RB928064, SP70-1143, SP71-1406, SP71-6163, and SP81-3250. This is the first report showingSCMV strains capable of cross-infectingand causing mosaic in sugarcane and maize. Our data emphasize the importance of continuous monitoring and screening for virus resistantgenotypes to be used in breeding programs for the development of new resistant ... Mostrar Tudo |
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Thesagro: |
Cana de açucar; Doença de planta; Mosaico. |
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Categoria do assunto: |
H Saúde e Patologia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/166067/1/Reaction-sugarcane.pdf
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Marc: |
LEADER 02211naa a2200229 a 4500
001 2078844
005 2017-11-03
008 2017 bl uuuu u00u1 u #d
100 1 $aSOUZA, I. R. P. de
245 $aReaction of sugarcane genotypes to strains of the sugarcane mosaic virus.$h[electronic resource]
260 $c2017
520 $aSugarcane crops are cultivated in nearly all tropical and sub-tropical regions worldwide andhave a prominent position in the agricultural scenario in Brazil. However, viral diseases can threaten the production of this important commodity leading to large production losses. In the present study, we evaluatedthe reaction of 20 sugarcane genotypes independently inoculated with two different strains of Sugarcane mosaic virus (SCMV) isolated from naturally infected sugarcane (SCMV-SGC) and maize (SCMV-MZ). The maize inbred line L19 was used as a control of susceptibility to the SCMV-MZ strain. Symptoms intensity was evaluated through a visual scale with three levels of severity: weak, intermediate, and intense. The viral infection was confirmed by PCR and DNA sequencing. We observed that, although both strains were able to infect sugarcane genotypes and the maize inbred line, SCMV-SGC was more aggressive, resulting in only four resistant genotypes: IN84-58 (S. spontaneum), RB855536, RB 928064, and SP71-6163. Thirteen genotypes were resistant to SCMV-MZ: IN84-58 (S.spontaneum), NA56-79, CB47-355,CB49-260, RB72454, RB855113, RB855536, RB867515, RB928064, SP70-1143, SP71-1406, SP71-6163, and SP81-3250. This is the first report showingSCMV strains capable of cross-infectingand causing mosaic in sugarcane and maize. Our data emphasize the importance of continuous monitoring and screening for virus resistantgenotypes to be used in breeding programs for the development of new resistant cultivars.
650 $aCana de açucar
650 $aDoença de planta
650 $aMosaico
700 1 $aMACEDO, G. A. R.
700 1 $aBARBOSA, M. H. P.
700 1 $aBARROS, B. de A.
700 1 $aCARVALHO, S. G. M.
700 1 $aXAVIER, A. da S.
700 1 $aGONÇALVES, I. A. M.
773 $tInternational Journal of Current Research$gv. 9, n. 10, p. 59112-59119, Oct. 2017.
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