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Registro Completo |
Biblioteca(s): |
Embrapa Meio Ambiente. |
Data corrente: |
23/01/2020 |
Data da última atualização: |
23/01/2020 |
Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
Autoria: |
MÁRQUEZ GUTIÉRREZ, M. E.; CAPALBO, D. M. F.; ARRUDA, R. O. M.; MORAES, R. de O. |
Afiliação: |
Universidad de Havana; DEISE MARIA FONTANA CAPALBO, CNPMA; REGINA DE OLIVEIRA ARRUDA, Probiom Technology; RODRIGO DE OLIVEIRA MORAES, Probiom Technology. |
Título: |
Bacillus thuringiensis. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
In: SOUZA, B.; VÁZQUEZ, L.; MARUCCI, R. (ed). Natural enemies of insect pests in neotropical agroecosystems: biological control and functional biodiversity. Cham: Springer, 2019. cap. 21. |
Páginas: |
p. 245-259. |
ISBN: |
978-3-030-24733-1 |
DOI: |
https://doi.org/10.1007/978-3-030-24733-1_21 |
Idioma: |
Inglês |
Conteúdo: |
Abstract: The aim of this chapter is to report the processes and parameters for the fermentation of Bt by industrial technologies together with other aspects of the formulation, quality control, and commercialization. |
Thesagro: |
Bacillus Thuringiensis; Formulação. |
Thesaurus Nal: |
Bacterial insecticides; Pesticide formulations. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01062naa a2200241 a 4500 001 2119252 005 2020-01-23 008 2019 bl uuuu u00u1 u #d 020 $a978-3-030-24733-1 024 7 $ahttps://doi.org/10.1007/978-3-030-24733-1_21$2DOI 100 1 $aMÁRQUEZ GUTIÉRREZ, M. E. 245 $aBacillus thuringiensis.$h[electronic resource] 260 $c2019 300 $ap. 245-259. 520 $aAbstract: The aim of this chapter is to report the processes and parameters for the fermentation of Bt by industrial technologies together with other aspects of the formulation, quality control, and commercialization. 650 $aBacterial insecticides 650 $aPesticide formulations 650 $aBacillus Thuringiensis 650 $aFormulação 700 1 $aCAPALBO, D. M. F. 700 1 $aARRUDA, R. O. M. 700 1 $aMORAES, R. de O. 773 $tIn: SOUZA, B.; VÁZQUEZ, L.; MARUCCI, R. (ed). Natural enemies of insect pests in neotropical agroecosystems: biological control and functional biodiversity. Cham: Springer, 2019. cap. 21.
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| Acesso ao texto completo restrito à biblioteca da Embrapa Instrumentação. Para informações adicionais entre em contato com cnpdia.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Instrumentação. |
Data corrente: |
20/02/2015 |
Data da última atualização: |
31/08/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 1 |
Autoria: |
BRANDAO, Z. N.; GREGO, C. R.; INAMASU, R. Y.; JORGE, L. A. |
Afiliação: |
ZIANY NEIVA BRANDAO, CNPA; CELIA REGINA GREGO, CNPM; RICARDO YASSUSHI INAMASU, CNPDIA; LUCIO ANDRE DE CASTRO JORGE, CNPDIA. |
Título: |
Spectral reflectance of satellite images using geostatistics methods to estimate growth and cotton yield. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Proceedings of SPIE, v. 9239, p. 923920-1 - 923920-8, 2014. |
ISBN: |
0277-786X |
DOI: |
10.1117/12.2067257 |
Idioma: |
Inglês |
Notas: |
Presented at the 16th Remote Sensing for Agriculture, Ecosystems, and Hydrology. |
Conteúdo: |
The objective of this study was the spatial identification of the NDVI index and cotton yield distributions through different crop phenological stages using geostatistical methods in Goiás state, Brazil. The experiment was carried out in a commercial field with 47.4 ha, in 80x80m georeferenced grid with 74 plots. Yield monitor data and multispectral satellite images at 56 m spatial resolution were collected in a rainfed cotton field in two dates to monitor the plant vigor. Satellite images of AWiFS sensor were acquired on 08/02/2011 and 01/04/2011, during the first flowering and fruiting cotton stages, respectively, corresponding to 70 and 120DAE (days after emergence). Measures of canopy reflectance, plant height and leaf nitrogen content were determined and cotton yield was obtained by mechanical harvest in August, 2011. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering, the NDVI and cotton yield showed strong spatial dependence, while for 120DAE there was no dependence, probably due to the enlargement of vegetated coverage. There were similarities in the bottom left of the study area with high values of NDVI, as well as the highest values of cotton yield due to excellent plant vigor in the cotton flowering stage. Identifications of spatial differences were possible using geostatistical methods with remote sensing data obtained from medium resolution satellite images, allowing to identify distinct stages of plant growth and also to predict the cotton yield. MenosThe objective of this study was the spatial identification of the NDVI index and cotton yield distributions through different crop phenological stages using geostatistical methods in Goiás state, Brazil. The experiment was carried out in a commercial field with 47.4 ha, in 80x80m georeferenced grid with 74 plots. Yield monitor data and multispectral satellite images at 56 m spatial resolution were collected in a rainfed cotton field in two dates to monitor the plant vigor. Satellite images of AWiFS sensor were acquired on 08/02/2011 and 01/04/2011, during the first flowering and fruiting cotton stages, respectively, corresponding to 70 and 120DAE (days after emergence). Measures of canopy reflectance, plant height and leaf nitrogen content were determined and cotton yield was obtained by mechanical harvest in August, 2011. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering, the NDVI and cotton yield showed strong spatial dependence, while for 120DAE there was no dependence, probably due to the enlargement of vegetated coverage. There were similarities in the bottom left of the study area with high values of NDVI, as well as the highest values of cotton yield due to excellent plant vigor in the cotton flowering stage. Identifications of spatial differences were possible using geostatistic... Mostrar Tudo |
Palavras-Chave: |
Geostatistical analyses. |
Thesaurus NAL: |
Normalized difference vegetation index; Precision agriculture. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02473naa a2200229 a 4500 001 2009183 005 2018-08-31 008 2014 bl uuuu u00u1 u #d 022 $a0277-786X 024 7 $a10.1117/12.2067257$2DOI 100 1 $aBRANDAO, Z. N. 245 $aSpectral reflectance of satellite images using geostatistics methods to estimate growth and cotton yield.$h[electronic resource] 260 $c2014 500 $aPresented at the 16th Remote Sensing for Agriculture, Ecosystems, and Hydrology. 520 $aThe objective of this study was the spatial identification of the NDVI index and cotton yield distributions through different crop phenological stages using geostatistical methods in Goiás state, Brazil. The experiment was carried out in a commercial field with 47.4 ha, in 80x80m georeferenced grid with 74 plots. Yield monitor data and multispectral satellite images at 56 m spatial resolution were collected in a rainfed cotton field in two dates to monitor the plant vigor. Satellite images of AWiFS sensor were acquired on 08/02/2011 and 01/04/2011, during the first flowering and fruiting cotton stages, respectively, corresponding to 70 and 120DAE (days after emergence). Measures of canopy reflectance, plant height and leaf nitrogen content were determined and cotton yield was obtained by mechanical harvest in August, 2011. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering, the NDVI and cotton yield showed strong spatial dependence, while for 120DAE there was no dependence, probably due to the enlargement of vegetated coverage. There were similarities in the bottom left of the study area with high values of NDVI, as well as the highest values of cotton yield due to excellent plant vigor in the cotton flowering stage. Identifications of spatial differences were possible using geostatistical methods with remote sensing data obtained from medium resolution satellite images, allowing to identify distinct stages of plant growth and also to predict the cotton yield. 650 $aNormalized difference vegetation index 650 $aPrecision agriculture 653 $aGeostatistical analyses 700 1 $aGREGO, C. R. 700 1 $aINAMASU, R. Y. 700 1 $aJORGE, L. A. 773 $tProceedings of SPIE$gv. 9239, p. 923920-1 - 923920-8, 2014.
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