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Registro Completo |
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Biblioteca(s): |
Embrapa Pantanal. |
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Data corrente: |
27/03/1996 |
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Data da última atualização: |
06/04/2017 |
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Autoria: |
SILVA, J. dos S. V. da; KUX, H. J. H. |
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Afiliação: |
EMBRAPA. Centro de Pesquisa Agropecuaria do Pantanal (Corumba, MS); Instituto Nacional de Pesquisas Espaciais (Sao Jose dos Campos, SP). |
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Título: |
Recurrence periods of flooding associated to TM data within the Pantanal, Brazil. |
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Ano de publicação: |
1992 |
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Fonte/Imprenta: |
International Archives Photogrammetry and Remote Sensing, v.29, n.B7, p.235-240, 1992. |
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Idioma: |
Inglês |
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Conteúdo: |
Within the Pantanal, vegetation, wildlife and extensive cattle raising is adapted to the yearly flooding cycle. Quantitative information on the dynamics of flooding is extremely important for any self-sustained management of this region. In this context, using temporal series of hydrographs located at the rio Paraguai (Ladario) and at rio Miranda (Ticao de Fogo), the recurrence periods of flooding for 5, 10 and 15 years were estimated. These recurrence periods were associated to the flooded area, obtained during the hydrological year 1989 with TM-Landsat images, data takes from April 9, 89; May 11, 89; June 12, 89; July 14, 89 and September 16,89. |
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Palavras-Chave: |
Flooding; Hidrology. |
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Thesagro: |
Hidrologia; Inundação; Sensoriamento Remoto. |
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Thesaurus Nal: |
Pantanal; remote sensing. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01285naa a2200217 a 4500
001 1788032
005 2017-04-06
008 1992 bl --- 0-- u #d
100 1 $aSILVA, J. dos S. V. da
245 $aRecurrence periods of flooding associated to TM data within the Pantanal, Brazil.
260 $c1992
520 $aWithin the Pantanal, vegetation, wildlife and extensive cattle raising is adapted to the yearly flooding cycle. Quantitative information on the dynamics of flooding is extremely important for any self-sustained management of this region. In this context, using temporal series of hydrographs located at the rio Paraguai (Ladario) and at rio Miranda (Ticao de Fogo), the recurrence periods of flooding for 5, 10 and 15 years were estimated. These recurrence periods were associated to the flooded area, obtained during the hydrological year 1989 with TM-Landsat images, data takes from April 9, 89; May 11, 89; June 12, 89; July 14, 89 and September 16,89.
650 $aPantanal
650 $aremote sensing
650 $aHidrologia
650 $aInundação
650 $aSensoriamento Remoto
653 $aFlooding
653 $aHidrology
700 1 $aKUX, H. J. H.
773 $tInternational Archives Photogrammetry and Remote Sensing$gv.29, n.B7, p.235-240, 1992.
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Registro original: |
Embrapa Pantanal (CPAP) |
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Registro Completo
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Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
07/03/2013 |
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Data da última atualização: |
07/03/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
MURAD, A. M.; RECH FILHO, E. L. |
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Afiliação: |
ANDRE MELRO MURAD, CENARGEN; ELIBIO LEOPOLDO RECH FILHO, CENARGEN. |
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Título: |
NanoUPLC-MSE proteomic data assessment of soybean seeds using the Uniprot database. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
BMC Biotechnology, v. 12, n. 82, 2012. |
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Idioma: |
Português |
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Conteúdo: |
Background: Recombinant DNA technology has been extensively employed to generate a variety of products from genetically modified organisms (GMOs) over the last decade, and the development of technologies capable of analyzing these products is crucial to understanding gene expression patterns. Liquid chromatography coupled with mass spectrometry is a powerful tool for analyzing protein contents and possible expression modifications in GMOs. Specifically, the NanoUPLC-MSE technique provides rapid protein analyses of complex mixtures with supported steps for high sample throughput, identification and quantization using low sample quantities with outstanding repeatability. Here, we present an assessment of the peptide and protein identification and quantification of soybean seed EMBRAPA BR16 cultivar contents using NanoUPLC-MSE and provide a comparison to the theoretical tryptic digestion of soybean sequences from Uniprot database. Results: The NanoUPLC-MSE peptide analysis resulted in 3,400 identified peptides, 58% of which were identified to have no miscleavages. The experiment revealed that 13% of the peptides underwent in-source fragmentation, and 82% of the peptides were identified with a mass measurement accuracy of less than 5 ppm. More than 75% of the identified proteins have at least 10 matched peptides, 88% of the identified proteins have greater than 30% of coverage, and 87% of the identified proteins occur in all four replicates. 78% of the identified proteins correspond to all glycinin and betaconglycinin chains. The theoretical Uniprot peptide database has 723,749 entries, and 548,336 peptides have molecular weights of greater than 500 Da. Seed proteins represent 0.86% of the protein database entries. At the peptide level, trypsin-digested seed proteins represent only 0.3% of the theoretical Uniprot peptide database. A total of 22% of all database peptides have a pI value of less than 5, and 25% of them have a pI value between 5 and 8. Based on the detection range of typical NanoUPLC-MSE experiments, i.e., 500 to 5000 Da, 64 proteins will not be identified. Conclusions: NanoUPLC-MSE experiments provide good protein coverage within a peptide error of 5 ppm and a wide MW detection range from 500 to 5000 Da. A second digestion enzyme should be used depending on the tissue or proteins to be analyzed. In the case of seed tissue, trypsin protein digestion results offer good databank coverage. The Uniprot database has many duplicate entries that may result in false protein homolog associations when using NanoUPLC-MSE analysis. The proteomic profile of the EMBRAPA BR-16 seed lacks certain described proteins relative to the profiles of transgenic soybeans reported in other works. MenosBackground: Recombinant DNA technology has been extensively employed to generate a variety of products from genetically modified organisms (GMOs) over the last decade, and the development of technologies capable of analyzing these products is crucial to understanding gene expression patterns. Liquid chromatography coupled with mass spectrometry is a powerful tool for analyzing protein contents and possible expression modifications in GMOs. Specifically, the NanoUPLC-MSE technique provides rapid protein analyses of complex mixtures with supported steps for high sample throughput, identification and quantization using low sample quantities with outstanding repeatability. Here, we present an assessment of the peptide and protein identification and quantification of soybean seed EMBRAPA BR16 cultivar contents using NanoUPLC-MSE and provide a comparison to the theoretical tryptic digestion of soybean sequences from Uniprot database. Results: The NanoUPLC-MSE peptide analysis resulted in 3,400 identified peptides, 58% of which were identified to have no miscleavages. The experiment revealed that 13% of the peptides underwent in-source fragmentation, and 82% of the peptides were identified with a mass measurement accuracy of less than 5 ppm. More than 75% of the identified proteins have at least 10 matched peptides, 88% of the identified proteins have greater than 30% of coverage, and 87% of the identified proteins occur in all four replicates. 78% of the identified proteins corres... Mostrar Tudo |
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Palavras-Chave: |
NanoUPLC-MSE; Seed proteomics; Soybean; Uniprot database. |
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Thesagro: |
Soja. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/78307/1/RECH1.pdf
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Marc: |
LEADER 03269naa a2200193 a 4500
001 1952421
005 2023-03-07
008 2012 bl uuuu u00u1 u #d
100 1 $aMURAD, A. M.
245 $aNanoUPLC-MSE proteomic data assessment of soybean seeds using the Uniprot database.$h[electronic resource]
260 $c2012
520 $aBackground: Recombinant DNA technology has been extensively employed to generate a variety of products from genetically modified organisms (GMOs) over the last decade, and the development of technologies capable of analyzing these products is crucial to understanding gene expression patterns. Liquid chromatography coupled with mass spectrometry is a powerful tool for analyzing protein contents and possible expression modifications in GMOs. Specifically, the NanoUPLC-MSE technique provides rapid protein analyses of complex mixtures with supported steps for high sample throughput, identification and quantization using low sample quantities with outstanding repeatability. Here, we present an assessment of the peptide and protein identification and quantification of soybean seed EMBRAPA BR16 cultivar contents using NanoUPLC-MSE and provide a comparison to the theoretical tryptic digestion of soybean sequences from Uniprot database. Results: The NanoUPLC-MSE peptide analysis resulted in 3,400 identified peptides, 58% of which were identified to have no miscleavages. The experiment revealed that 13% of the peptides underwent in-source fragmentation, and 82% of the peptides were identified with a mass measurement accuracy of less than 5 ppm. More than 75% of the identified proteins have at least 10 matched peptides, 88% of the identified proteins have greater than 30% of coverage, and 87% of the identified proteins occur in all four replicates. 78% of the identified proteins correspond to all glycinin and betaconglycinin chains. The theoretical Uniprot peptide database has 723,749 entries, and 548,336 peptides have molecular weights of greater than 500 Da. Seed proteins represent 0.86% of the protein database entries. At the peptide level, trypsin-digested seed proteins represent only 0.3% of the theoretical Uniprot peptide database. A total of 22% of all database peptides have a pI value of less than 5, and 25% of them have a pI value between 5 and 8. Based on the detection range of typical NanoUPLC-MSE experiments, i.e., 500 to 5000 Da, 64 proteins will not be identified. Conclusions: NanoUPLC-MSE experiments provide good protein coverage within a peptide error of 5 ppm and a wide MW detection range from 500 to 5000 Da. A second digestion enzyme should be used depending on the tissue or proteins to be analyzed. In the case of seed tissue, trypsin protein digestion results offer good databank coverage. The Uniprot database has many duplicate entries that may result in false protein homolog associations when using NanoUPLC-MSE analysis. The proteomic profile of the EMBRAPA BR-16 seed lacks certain described proteins relative to the profiles of transgenic soybeans reported in other works.
650 $aSoja
653 $aNanoUPLC-MSE
653 $aSeed proteomics
653 $aSoybean
653 $aUniprot database
700 1 $aRECH FILHO, E. L.
773 $tBMC Biotechnology$gv. 12, n. 82, 2012.
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Embrapa Recursos Genéticos e Biotecnologia (CENARGEN) |
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