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Registro Completo |
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Biblioteca(s): |
Embrapa Tabuleiros Costeiros. |
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Data corrente: |
13/01/2020 |
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Data da última atualização: |
24/03/2022 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
SENES, B. B.; MACHADO, A. de L.; MEIRA, A. N.; COUTINHO, L. L.; MOURAO, G. B.; AZEVEDO, H. C.; MUNIZ, E. N.; PEDROSA, V. B.; PINTO, L. F. B. |
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Afiliação: |
BEATRIZ BASTOS SENES; ALESSANDRO DE LIMA MACHADO; ARIANA NASCIEMNTO MEIRA; LUIZ LEHMANN COUTINHO; GERSON BARRETO MOURAO; HYMERSON COSTA AZEVEDO, CPATC; EVANDRO NEVES MUNIZ, CPATC; VICTOR BRENO PEDROSA; LUIS FERNANDO BATISTA PINTO. |
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Título: |
Haplótipos no gene LEP associados com medidas morfométricas em ovinos Santa Inês. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE MELHORAMENTO ANIMAL, 13., 2019, Salvador, BA. Anais... Salvador: SBMA, 2019. |
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Idioma: |
Português |
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Palavras-Chave: |
Ovino Santa Inês. |
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Thesagro: |
Ovino; Ovinocultura. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/208659/1/Haplotipos-no-gene-LEP-SBMA-2019.pdf
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Marc: |
LEADER 00728nam a2200229 a 4500
001 2118650
005 2022-03-24
008 2019 bl uuuu u00u1 u #d
100 1 $aSENES, B. B.
245 $aHaplótipos no gene LEP associados com medidas morfométricas em ovinos Santa Inês.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE MELHORAMENTO ANIMAL, 13., 2019, Salvador, BA. Anais... Salvador: SBMA$c2019
650 $aOvino
650 $aOvinocultura
653 $aOvino Santa Inês
700 1 $aMACHADO, A. de L.
700 1 $aMEIRA, A. N.
700 1 $aCOUTINHO, L. L.
700 1 $aMOURAO, G. B.
700 1 $aAZEVEDO, H. C.
700 1 $aMUNIZ, E. N.
700 1 $aPEDROSA, V. B.
700 1 $aPINTO, L. F. B.
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Registro original: |
Embrapa Tabuleiros Costeiros (CPATC) |
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Registro |
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Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
19/11/2019 |
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Data da última atualização: |
19/11/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
FONGARO, C. T.; DEMATTÊ, J. A. M.; RIZZO, R.; SAFANELLI, J. L.; MENDES, W. de S.; DOTTO, A. C.; VICENTE, L. E.; FRANCESCHINI, M. H. D.; USTIN, S. L. |
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Afiliação: |
CAIO TROULA FONGARO, ESALQ-USP; JOSE ALEXANDRE MELO DEMATTE, ESALQ-USP; RODNEI RIZZO, CENA-USP; JOSE LUCAS SAFANELLI, ESALQ-USP; WANDERSON DE SOUSA MENDES, ESALQ-USP; ANDRE CARNIELETTO DOTTO, ESALQ-USP; LUIZ EDUARDO VICENTE, CNPMA; MARSTON HERACLES DOMINGUES FRANCESCHINI, Wageningen University; SUSAN L USTIN, University of California-Davis. |
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Título: |
Improvement of clay and sand quantification based on a novel approach with a focus on multispectral satellite images. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Remote Sensing, v. 10, n. 10, p. 1-21, 2018. Article 1555. |
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DOI: |
https://doi.org/10.3390/rs10101555 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Soil mapping demands large-scale surveys that are costly and time consuming. It is necessary to identify strategies with reduced costs to obtain detailed information for soil mapping. We aimed to compare multispectral satellite image and relief parameters for the quantification and mapping of clay and sand contents. The Temporal Synthetic Spectral (TESS) reflectance and Synthetic Soil Image (SYSI) approaches were used to identify and characterize texture spectral signatures at the image level. Soil samples were collected (0?20 cm depth, 919 points) from an area of 14,614 km 2 in Brazil for reference and model calibration. We compared different prediction approaches: (a) TESS and SYSI; (b) Relief-Derived Covariates (RDC); and (c) SYSI plus RDC. The TESS method produced highly similar behavior to the laboratory convolved data. The sandy textural class showed a greater increase in average spectral reflectance from Band 1 to 7 compared with the clayey class. The prediction using SYSI produced a better result for clay (R 2 = 0.83; RMSE = 65.0 g kg − 1 ) and sand (R 2 = 0.86; RMSE = 79.9 g kg − 1 ). Multispectral satellite images were more stable for the identification of soil properties than relief parameters. |
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Palavras-Chave: |
Imagem de satélite; Mapeamento do solo. |
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Thesagro: |
Satélite; Sensoriamento Remoto; Solo Arenoso; Solo Argiloso. |
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Thesaurus NAL: |
Clay soils; Multispectral imagery; Precision agriculture; Reflectance spectroscopy; Remote sensing; Sandy soils; Satellites; Soil degradation; Soil map. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/204955/1/Vicente-Clay-Sand-AP-2019.pdf
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Marc: |
LEADER 02461naa a2200409 a 4500
001 2114592
005 2019-11-19
008 2018 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/rs10101555$2DOI
100 1 $aFONGARO, C. T.
245 $aImprovement of clay and sand quantification based on a novel approach with a focus on multispectral satellite images.$h[electronic resource]
260 $c2018
520 $aAbstract: Soil mapping demands large-scale surveys that are costly and time consuming. It is necessary to identify strategies with reduced costs to obtain detailed information for soil mapping. We aimed to compare multispectral satellite image and relief parameters for the quantification and mapping of clay and sand contents. The Temporal Synthetic Spectral (TESS) reflectance and Synthetic Soil Image (SYSI) approaches were used to identify and characterize texture spectral signatures at the image level. Soil samples were collected (0?20 cm depth, 919 points) from an area of 14,614 km 2 in Brazil for reference and model calibration. We compared different prediction approaches: (a) TESS and SYSI; (b) Relief-Derived Covariates (RDC); and (c) SYSI plus RDC. The TESS method produced highly similar behavior to the laboratory convolved data. The sandy textural class showed a greater increase in average spectral reflectance from Band 1 to 7 compared with the clayey class. The prediction using SYSI produced a better result for clay (R 2 = 0.83; RMSE = 65.0 g kg − 1 ) and sand (R 2 = 0.86; RMSE = 79.9 g kg − 1 ). Multispectral satellite images were more stable for the identification of soil properties than relief parameters.
650 $aClay soils
650 $aMultispectral imagery
650 $aPrecision agriculture
650 $aReflectance spectroscopy
650 $aRemote sensing
650 $aSandy soils
650 $aSatellites
650 $aSoil degradation
650 $aSoil map
650 $aSatélite
650 $aSensoriamento Remoto
650 $aSolo Arenoso
650 $aSolo Argiloso
653 $aImagem de satélite
653 $aMapeamento do solo
700 1 $aDEMATTÊ, J. A. M.
700 1 $aRIZZO, R.
700 1 $aSAFANELLI, J. L.
700 1 $aMENDES, W. de S.
700 1 $aDOTTO, A. C.
700 1 $aVICENTE, L. E.
700 1 $aFRANCESCHINI, M. H. D.
700 1 $aUSTIN, S. L.
773 $tRemote Sensing$gv. 10, n. 10, p. 1-21, 2018. Article 1555.
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Embrapa Meio Ambiente (CNPMA) |
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