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NIR spectroscopy and chemometric tools to identify high content of deoxynivalenol in barley.
Caramês, Elem Tamirys Dos Santos; Piacentini, Karim C; Alves, Lucas Teixeira; Pallone, Juliana Azevedo Lima; Rocha, Liliana de Oliveira.
Afiliación
  • Caramês ETDS; Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil.
  • Piacentini KC; Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil.
  • Alves LT; Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil.
  • Pallone JAL; Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil.
  • Rocha LO; Department of Food Science, School of Food Engineering, State University of Campinas , Campinas, São Paulo, Brazil.
Food Addit Contam Part A Chem Anal Control Expo Risk Assess ; 37(9): 1542-1552, 2020 Sep.
Article en En | MEDLINE | ID: mdl-32717175
Deoxynivalenol (DON) is one of the mycotoxins produced mainly by the Fusarium graminearum species complex in small grain cereals, including barley. This toxin can cause alimentary disorders, immune function depression and gastroenteritis. The negative health effects associated with DON coupled to the increasing concern about green and rapid methods of analysis motivated this study. In this context, near infrared (NIR) spectroscopy data were applied for exploratory analysis to distinguish barley with high and low levels of DON contamination (> or <1250 µg/kg according to the European Union threshold), by Partial Least Squares-Discriminant Analysis (PLS-DA), and to verify the performance of Partial Least Squares-Regression (PLS-R) to predict DON concentration in barley samples. Maximum values of specificity and sensitivity were achieved in the calibration set; 90.9% and 81.9% were observed in the cross-validation set for the PLS-DA classification model. PLS-R quantification of DON in barley presented low values of error (RMSEC = 101.94 µg/kg and RMSEP = 160.76 µg/kg). Thus, we found that NIR in combination with adequate chemometric tools could be applied as a green technique to monitor DON contamination in barley.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tricotecenos / Hordeum / Algoritmos / Contaminación de Alimentos Tipo de estudio: Prognostic_studies Idioma: En Revista: Food Addit Contam Part A Chem Anal Control Expo Risk Assess Asunto de la revista: CIENCIAS DA NUTRICAO Año: 2020 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tricotecenos / Hordeum / Algoritmos / Contaminación de Alimentos Tipo de estudio: Prognostic_studies Idioma: En Revista: Food Addit Contam Part A Chem Anal Control Expo Risk Assess Asunto de la revista: CIENCIAS DA NUTRICAO Año: 2020 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido