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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
20/06/2003 |
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Data da última atualização: |
19/04/2024 |
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Autoria: |
NEVES, P. de C. F. |
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Afiliação: |
PERICLES DE CARVALHO FERREIRA NEVES, CNPAF. |
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Título: |
Introgression of agronomic traits associated with molecular markers from Oryza nivara Sharma & Shastry into O. sativa L. |
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Ano de publicação: |
2002 |
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Fonte/Imprenta: |
2002. |
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Páginas: |
151 f. |
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Idioma: |
Inglês |
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Notas: |
Dissertation (Doctor of Philosophy in Plant Genetics) - University of California, Davis. |
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Conteúdo: |
The purpose of this study was to identify quantitative trait loci (QTL) associated with agronomic traits using simple sequence length polymorphisms. A BC2F2 population of 192 families was developed from a cross between the high yielding japonica cultivar M-202 and the wild species Oryza nivara. |
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Palavras-Chave: |
Diversidade genética; Melhoramento genético. |
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Thesagro: |
Arroz; Oryza Sativa. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 00890nam a2200181 a 4500
001 1211203
005 2024-04-19
008 2002 bl uuuu m 00u1 u #d
100 1 $aNEVES, P. de C. F.
245 $aIntrogression of agronomic traits associated with molecular markers from Oryza nivara Sharma & Shastry into O. sativa L.
260 $a2002.$c2002
300 $a151 f.
500 $aDissertation (Doctor of Philosophy in Plant Genetics) - University of California, Davis.
520 $aThe purpose of this study was to identify quantitative trait loci (QTL) associated with agronomic traits using simple sequence length polymorphisms. A BC2F2 population of 192 families was developed from a cross between the high yielding japonica cultivar M-202 and the wild species Oryza nivara.
650 $aArroz
650 $aOryza Sativa
653 $aDiversidade genética
653 $aMelhoramento genético
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Algodão. Para informações adicionais entre em contato com cnpa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Algodão; Embrapa Instrumentação. |
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Data corrente: |
04/07/2022 |
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Data da última atualização: |
29/08/2022 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
BRANDAO, Z. N.; GREGO, C. R.; JORGE, L. A. de C.; MANJOLIN, R. C. |
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Afiliação: |
ZIANY NEIVA BRANDAO, CNPA; CELIA REGINA GREGO, CNPTIA; LUCIO ANDRE DE CASTRO JORGE, CNPDIA; RODOLFO CORREA MANJOLIN, Unicamp. |
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Título: |
Multispectral reflectance and geostatistic methods to estimate leaf nitrogen content and cotton yield. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
In: SILVA-MATOS, R. R. S. da; MORAES, L. F.; SILVA, F. L. de S. (org.). Desenvolvimento da pesquisa científica, tecnologia e inovação na agronomia 3. Ponta Grossa: Atena, 2022. cap. 14, p. 143-154. |
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ISBN: |
978-65-258-0377-7 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT: Satellite images and geostatistics are useful tools to assess the nutritional status of plants, and thus, understanding the variability of cotton yield in farmers´ fields, within the precision agriculture onfarm experiments. The objective of this study was the spatial identification of the NDVI index and spatial distribution of nitrogen contents and cotton yield through different phenological
stages of the crop 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, as well as leaf samples were collected for laboratory analysis. Satellite images of AWiFS sensor were acquired on two fenological states, 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, 2012. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and ordinary kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering at 70DAE, 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 area with high values of NDVI 70DAE, as well as the highest values of cotton yield due to excellent
plant vigor in the cotton flowering stage. By using geostatistics methods with remote sensing data retrieved by satellite images of medium resolution, it was possible a spatial identification of differences in plant development and also to predict cotton yield MenosABSTRACT: Satellite images and geostatistics are useful tools to assess the nutritional status of plants, and thus, understanding the variability of cotton yield in farmers´ fields, within the precision agriculture onfarm experiments. The objective of this study was the spatial identification of the NDVI index and spatial distribution of nitrogen contents and cotton yield through different phenological
stages of the crop 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, as well as leaf samples were collected for laboratory analysis. Satellite images of AWiFS sensor were acquired on two fenological states, 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, 2012. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and ordinary kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering at 70DAE, the NDVI and cotton yield showed strong spatial dependence, while fo... Mostrar Tudo |
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Palavras-Chave: |
Algodoeiro; Análises geoestatísticas; Geostatistical analysis; Índice de vegetação da diferença normalizada; Métodos geoestatísticos; Nitrogênio foliar; Nutrients spatial variability; Reflectancia multiespectral; Variabilidade espacial de nutrientes. |
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Thesagro: |
Agricultura de Precisão; Algodão. |
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Thesaurus NAL: |
Cotton; Normalized difference vegetation index; Precision agriculture. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03257naa a2200337 a 4500
001 2144425
005 2022-08-29
008 2022 bl uuuu u00u1 u #d
020 $a978-65-258-0377-7
100 1 $aBRANDAO, Z. N.
245 $aMultispectral reflectance and geostatistic methods to estimate leaf nitrogen content and cotton yield.$h[electronic resource]
260 $c2022
520 $aABSTRACT: Satellite images and geostatistics are useful tools to assess the nutritional status of plants, and thus, understanding the variability of cotton yield in farmers´ fields, within the precision agriculture onfarm experiments. The objective of this study was the spatial identification of the NDVI index and spatial distribution of nitrogen contents and cotton yield through different phenological stages of the crop 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, as well as leaf samples were collected for laboratory analysis. Satellite images of AWiFS sensor were acquired on two fenological states, 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, 2012. Data were analyzed using descriptive statistics, correlation and geostatistical analyses by building and setting semivariograms and ordinary kriging interpolation. Best correlation was found between NDVI and cotton yield at 120DAE. At first flowering at 70DAE, 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 area with high values of NDVI 70DAE, as well as the highest values of cotton yield due to excellent plant vigor in the cotton flowering stage. By using geostatistics methods with remote sensing data retrieved by satellite images of medium resolution, it was possible a spatial identification of differences in plant development and also to predict cotton yield
650 $aCotton
650 $aNormalized difference vegetation index
650 $aPrecision agriculture
650 $aAgricultura de Precisão
650 $aAlgodão
653 $aAlgodoeiro
653 $aAnálises geoestatísticas
653 $aGeostatistical analysis
653 $aÍndice de vegetação da diferença normalizada
653 $aMétodos geoestatísticos
653 $aNitrogênio foliar
653 $aNutrients spatial variability
653 $aReflectancia multiespectral
653 $aVariabilidade espacial de nutrientes
700 1 $aGREGO, C. R.
700 1 $aJORGE, L. A. de C.
700 1 $aMANJOLIN, R. C.
773 $tIn: SILVA-MATOS, R. R. S. da; MORAES, L. F.; SILVA, F. L. de S. (org.). Desenvolvimento da pesquisa científica, tecnologia e inovação na agronomia 3. Ponta Grossa: Atena, 2022. cap. 14, p. 143-154.
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