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Registros recuperados : 3 | |
3. | | MATA, M. M. da; ROCHA, P. D.; FARIAS, I. K. T. de; SILVA, J. L. B. da; MEDEIROS, E. P.; SILVA, C. S.; SIMÕES, S. da S. Distinguishing cotton seed genotypes by means of vibrational spectroscopic methods (NIR and Raman) and chemometrics. Spectrochimica Acta, v. 266, 120399, p. 1-10, 2022. 10 p. Biblioteca(s): Embrapa Algodão. |
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Registros recuperados : 3 | |
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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
Biblioteca(s): |
Embrapa Algodão. |
Data corrente: |
08/02/2022 |
Data da última atualização: |
05/02/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
MATA, M. M. da; ROCHA, P. D.; FARIAS, I. K. T. de; SILVA, J. L. B. da; MEDEIROS, E. P.; SILVA, C. S.; SIMÕES, S. da S. |
Afiliação: |
MAYARA MACEDO DA MATA, UNIVERSIDADE DO ESTADO DA PARAÍBA; PRISCILA DANTAS ROCHA, UNIVERSIDADE DO ESTADO DA PARAÍBA; INGRID KELLY TELES DE FARIAS, UNIVERSIDADE DO ESTADO DA PARAÍBA; JULIANA LIMA BRASIL DA SILVA, UNIVERSIDADE DO ESTADO DA PARAÍBA; EVERALDO PAULO MEDEIROS, UNIVERSIDADE FEDERAL DE PERNAMBUCO; CAROLINA SANTOS SILVA, CNPA; SIMONE DA SILVA SIMÕES, UNIVERSIDADE ESTADUAL DA PARAÍBA. |
Título: |
Distinguishing cotton seed genotypes by means of vibrational spectroscopic methods (NIR and Raman) and chemometrics. |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
Spectrochimica Acta, v. 266, 120399, p. 1-10, 2022. |
Páginas: |
10 p. |
ISSN: |
1386-1425 |
DOI: |
10.1016/j.saa.2021.120399 |
Idioma: |
Inglês |
Conteúdo: |
The use of vibrational spectroscopy, such as near infrared (NIR) and Raman, combined with multivariate analysis methods to analyze agricultural products are promising for investigating genetically modified organisms (GMO). In Brazil, cotton is grown under humid tropical conditions and is highly affected by pests and diseases, requiring the use of large amounts of phytosanitary chemicals. To avoid the use of those pesticides, genetic improvement can be carried out to produce species tolerant to herbicides, resistant to fungi and insects, or even to provide greater productivity and better quality. Even with these advantages, it is necessary to manage and limit the contact of transgenic species with native ones, avoiding possible contamination or even extinction of conventional species. The identification of the presence of GMOs is based on complex DNA-based analysis, which is usually laborious, expensive, timeconsuming, destructive, and generally unavailable. In the present study, a new methodology to identify GMOs using partial least squares discriminant analysis (PLS-DA) on NIR and Raman data is proposed to distinguish conventional and transgenic cotton seed genotypes, providing classification errors for prediction set of 2.23% for NIR and 0.0% for Raman. |
Thesagro: |
Algodão; DNA; Organismo Transgênico; Raio Infravermelho. |
Thesaurus NAL: |
Cotton; Infrared radiation; Transgenic plants. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02191naa a2200313 a 4500 001 2139823 005 2023-02-05 008 2022 bl uuuu u00u1 u #d 022 $a1386-1425 024 7 $a10.1016/j.saa.2021.120399$2DOI 100 1 $aMATA, M. M. da 245 $aDistinguishing cotton seed genotypes by means of vibrational spectroscopic methods (NIR and Raman) and chemometrics.$h[electronic resource] 260 $c2022 300 $a10 p. 520 $aThe use of vibrational spectroscopy, such as near infrared (NIR) and Raman, combined with multivariate analysis methods to analyze agricultural products are promising for investigating genetically modified organisms (GMO). In Brazil, cotton is grown under humid tropical conditions and is highly affected by pests and diseases, requiring the use of large amounts of phytosanitary chemicals. To avoid the use of those pesticides, genetic improvement can be carried out to produce species tolerant to herbicides, resistant to fungi and insects, or even to provide greater productivity and better quality. Even with these advantages, it is necessary to manage and limit the contact of transgenic species with native ones, avoiding possible contamination or even extinction of conventional species. The identification of the presence of GMOs is based on complex DNA-based analysis, which is usually laborious, expensive, timeconsuming, destructive, and generally unavailable. In the present study, a new methodology to identify GMOs using partial least squares discriminant analysis (PLS-DA) on NIR and Raman data is proposed to distinguish conventional and transgenic cotton seed genotypes, providing classification errors for prediction set of 2.23% for NIR and 0.0% for Raman. 650 $aCotton 650 $aInfrared radiation 650 $aTransgenic plants 650 $aAlgodão 650 $aDNA 650 $aOrganismo Transgênico 650 $aRaio Infravermelho 700 1 $aROCHA, P. D. 700 1 $aFARIAS, I. K. T. de 700 1 $aSILVA, J. L. B. da 700 1 $aMEDEIROS, E. P. 700 1 $aSILVA, C. S. 700 1 $aSIMÕES, S. da S. 773 $tSpectrochimica Acta$gv. 266, 120399, p. 1-10, 2022.
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Embrapa Algodão (CNPA) |
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