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 | Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Instrumentação; Embrapa Milho e Sorgo. |
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Data corrente: |
06/08/2021 |
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Data da última atualização: |
06/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
DIB, S. R.; SILVA, T. V.; GOMES NETO, J. A.; GUIMARAES, L. J. M.; FERREIRA, E. J.; FERREIRA, E. C. |
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Afiliação: |
SAMIA RODRIGUES DIB, UNESP; TIAGO VARAO SILVA, UNESP; JOSÉ ANCHIETA GOMES NETO, UNESP; LAURO JOSE MOREIRA GUIMARAES, CNPMS; EDNALDO JOSE FERREIRA, CNPDIA; EDILENE CRISTINA FERREIRA, UNESP. |
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Título: |
Raman spectroscopy for discriminating transgenic corns. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Vibrational Spectroscopy, v. 112, 103183, 2021. |
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Idioma: |
Inglês |
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Conteúdo: |
Discrimination of genetically modified organisms is increasingly required by legislation and consumers worldwide. Currently the most commonly used detection methods for identification of transgenic crops are high cost, destructive and time-consuming, so not suitable for fast and extensive application. Raman is a noninvasive and nondestructive spectroscopic technique capable of extracting sample fingerprints. In this paper, Raman spectroscopy and chemometric tools were evaluated for discrimination of transgenic corn. Different spectral preprocessing as well as algorithms for variables selection were evaluated to fit a classifier model based on linear discriminant analysis (LDA). Results showed spectral bands assigned to carbohydrates and carotenoids responsible for classes discrimination. The best classifier achieved 87.5 % of predictive accuracy. These results suggest that genetic differences between evaluated classes are also expressed in their chemical composition, which could be detected using Raman spectroscopy. The developed method is clean, fast and can contribute for establishing normative about genetically modified foods. |
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Palavras-Chave: |
Espectroscopia. |
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Thesagro: |
Alimento Transgênico; Melhoramento Genético Vegetal; Milho. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 01794naa a2200229 a 4500
001 2133288
005 2021-08-06
008 2021 bl uuuu u00u1 u #d
100 1 $aDIB, S. R.
245 $aRaman spectroscopy for discriminating transgenic corns.$h[electronic resource]
260 $c2021
520 $aDiscrimination of genetically modified organisms is increasingly required by legislation and consumers worldwide. Currently the most commonly used detection methods for identification of transgenic crops are high cost, destructive and time-consuming, so not suitable for fast and extensive application. Raman is a noninvasive and nondestructive spectroscopic technique capable of extracting sample fingerprints. In this paper, Raman spectroscopy and chemometric tools were evaluated for discrimination of transgenic corn. Different spectral preprocessing as well as algorithms for variables selection were evaluated to fit a classifier model based on linear discriminant analysis (LDA). Results showed spectral bands assigned to carbohydrates and carotenoids responsible for classes discrimination. The best classifier achieved 87.5 % of predictive accuracy. These results suggest that genetic differences between evaluated classes are also expressed in their chemical composition, which could be detected using Raman spectroscopy. The developed method is clean, fast and can contribute for establishing normative about genetically modified foods.
650 $aAlimento Transgênico
650 $aMelhoramento Genético Vegetal
650 $aMilho
653 $aEspectroscopia
700 1 $aSILVA, T. V.
700 1 $aGOMES NETO, J. A.
700 1 $aGUIMARAES, L. J. M.
700 1 $aFERREIRA, E. J.
700 1 $aFERREIRA, E. C.
773 $tVibrational Spectroscopy$gv. 112, 103183, 2021.
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