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 B(1)+B(2) 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 FB(1)+FB(2) concentration. Results suggest that FT-NIR analysis is a suitable method to detect FB(1)+FB(2) in corn meal and to discriminate safe meals from those contaminated.
journal_name
Food Chemjournal_title
Food chemistryauthors
Gaspardo B,Del Zotto S,Torelli E,Cividino SR,Firrao G,Della Riccia G,Stefanon Bdoi
10.1016/j.foodchem.2012.06.078subject
Has Abstractpub_date
2012-12-01 00:00:00pages
1608-12issue
3eissn
0308-8146issn
1873-7072pii
S0308-8146(12)01051-5journal_volume
135pub_type
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