Fourier transform near infrared (FT-NIR) spectroscopy is an analytical procedure generally used to detect organic compounds in food. In this work the ability to predict fumonisin B1 + B2 contents in corn meal using an FT-NIR spectrophotometer, equipped with an integration sphere, was assessed. A total of 143 corn meal samples were collected in Friuli Venezia Giulia Region (Italy) and used to define a 15 principal components regression model, applying partial least square regression algorithm with full cross validation as internal validation. External validation was performed to 25 unknown samples. Coefficients of correlation, root mean square error and standard error of calibration were 0.964, 0.630 and 0.632, respectively and the external validation confirmed a fair potential of the model in predicting FB1 + FB2 concentration. Results suggest that FT-NIR analysis is a suitable method to detect FB1 + FB2 in corn meal and to discriminate safe meals from those contaminated.

A rapid method for detection of fumonisins B(1) and B(2) in corn meal using Fourier transform near infrared (FT-NIR) spectroscopy implemented with integrating sphere.

GASPARDO, Brigitta;DEL ZOTTO, Stefania;TORELLI, Emanuela;CIVIDINO, Sirio Rossano Secondo;FIRRAO, Giuseppe;DELLA RICCIA, Giacomo;STEFANON, Bruno
2012

Abstract

Fourier transform near infrared (FT-NIR) spectroscopy is an analytical procedure generally used to detect organic compounds in food. In this work the ability to predict fumonisin B1 + B2 contents in corn meal using an FT-NIR spectrophotometer, equipped with an integration sphere, was assessed. A total of 143 corn meal samples were collected in Friuli Venezia Giulia Region (Italy) and used to define a 15 principal components regression model, applying partial least square regression algorithm with full cross validation as internal validation. External validation was performed to 25 unknown samples. Coefficients of correlation, root mean square error and standard error of calibration were 0.964, 0.630 and 0.632, respectively and the external validation confirmed a fair potential of the model in predicting FB1 + FB2 concentration. Results suggest that FT-NIR analysis is a suitable method to detect FB1 + FB2 in corn meal and to discriminate safe meals from those contaminated.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/882703
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