Registro Completo |
Biblioteca(s): |
Embrapa Algodão; Embrapa Milho e Sorgo. |
Data corrente: |
17/11/2020 |
Data da última atualização: |
13/10/2021 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
CONCEIÇÃO, R. R. P. da; SIMEONE, M. L. F.; QUEIROZ, V. A. V.; MEDEIROS, E. P. de; ARAUJO, J. B. de; COUTINHO, W. M.; SILVA, D. D. da; MIGUEL, R. de A.; LANA, U. G. de P.; STOIANOFF, M. A. R. |
Afiliação: |
Renata Regina Pereira da Conceição, Universidade Federal de Minas Gerais; MARIA LUCIA FERREIRA SIMEONE, CNPMS; VALERIA APARECIDA VIEIRA QUEIROZ, CNPMS; EVERALDO PAULO DE MEDEIROS, CNPA; JOABSON BORGES DE ARAUJO, CNPA; WIRTON MACEDO COUTINHO, CNPA; DAGMA DIONISIA DA SILVA, CNPMS; RAFAEL DE ARAUJO MIGUEL, CNPMS; UBIRACI GOMES DE PAULA LANA, CNPMS; Maria Aparecidade Resende Stoianoff, Universidade Federal de Minas Gerais. |
Título: |
Application of Near-Infrared Hyperspectral (NIR) images combined with multivariate image analysis in the differentiation of two mycotoxicogenic Fusarium species associated with maize. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Food Chemistry, v. 344, 128615, 2021. |
Idioma: |
Inglês |
Conteúdo: |
Maize (Zea mays L.) is one of the most versatile crops worldwide with high socioeconomic relevance. However, mycotoxins produced by pathogenic fungi are of constant concern in maize production, as they pose serious risks to human and animal health. Thus, the search for rapid detection and/or identification methods for mycotoxins and mycotoxin-producing fungi for application in food safety remain important. In this work, we implemented use of near infrared hyperspectral images (HSI-NIR) combined with pattern recognition analysis, partial-leastsquares discriminant analysis (PLS-DA) of images, to develop a rapid method for identification of Fusarium verticillioides and F. graminearum. Validation of the HSI-NIR method and subsequent analysis was realized using 15 Fusarium spp. isolates. The method was efficient as a rapid, non-invasive, and non-destructive assessment was achieved with 100% accuracy, sensitivity, and specificity for both fungi. |
Palavras-Chave: |
Identificação fúngica; Imagem hiperespectral. |
Thesagro: |
Micotoxina; Zea Mays. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01865naa a2200277 a 4500 001 2126662 005 2021-10-13 008 2021 bl uuuu u00u1 u #d 100 1 $aCONCEIÇÃO, R. R. P. da 245 $aApplication of Near-Infrared Hyperspectral (NIR) images combined with multivariate image analysis in the differentiation of two mycotoxicogenic Fusarium species associated with maize.$h[electronic resource] 260 $c2021 520 $aMaize (Zea mays L.) is one of the most versatile crops worldwide with high socioeconomic relevance. However, mycotoxins produced by pathogenic fungi are of constant concern in maize production, as they pose serious risks to human and animal health. Thus, the search for rapid detection and/or identification methods for mycotoxins and mycotoxin-producing fungi for application in food safety remain important. In this work, we implemented use of near infrared hyperspectral images (HSI-NIR) combined with pattern recognition analysis, partial-leastsquares discriminant analysis (PLS-DA) of images, to develop a rapid method for identification of Fusarium verticillioides and F. graminearum. Validation of the HSI-NIR method and subsequent analysis was realized using 15 Fusarium spp. isolates. The method was efficient as a rapid, non-invasive, and non-destructive assessment was achieved with 100% accuracy, sensitivity, and specificity for both fungi. 650 $aMicotoxina 650 $aZea Mays 653 $aIdentificação fúngica 653 $aImagem hiperespectral 700 1 $aSIMEONE, M. L. F. 700 1 $aQUEIROZ, V. A. V. 700 1 $aMEDEIROS, E. P. de 700 1 $aARAUJO, J. B. de 700 1 $aCOUTINHO, W. M. 700 1 $aSILVA, D. D. da 700 1 $aMIGUEL, R. de A. 700 1 $aLANA, U. G. de P. 700 1 $aSTOIANOFF, M. A. R. 773 $tFood Chemistry$gv. 344, 128615, 2021.
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Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
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