Rapid and sensitive methods for the quantification of deoxynivalenol (DON), a type B trichothecene mycotoxin, in wheat and wheat-based food products are strongly demanded by private and public quality control laboratories. Chromatographic methods are the most widely used for quantitative determination of DON in foodstuffs and feedstuffs. However, these methods are destructive, time-consuming, expensive, unsuitable for screening purposes, and require a preliminary cleanup of the extracts. Recently, the feasibility of using Fourier-transform near infrared (FT-NIR) spectroscopy for rapid and non-invasive analysis of DON in unprocessed wheat at levels below the EU regulatory level has been reported. Calibration models for durum wheat, common wheat and durum+common wheat samples were obtained by using Partial Least Squares (PLS) regression with the external validation technique. A good fit between HPLC and FT-NIR data (r = 0.84-0.91) was achieved in the three PLS models in the measured range (from not detected to about 3000 µg/kg). Coefficients of determination (r2) indicated an "approximate to good" level of prediction of the DON content by FT-NIR spectroscopy in the PLS calibration models (r2 = 0.71-0.83), and a "good" discrimination between low and high DON contents in the PLS validation models (r2 = 0.58-0.63). Furthermore, values of root mean square error of prediction (RMSEP 310-380 µg/kg) were comparable and not too far from values of root mean square error of calibration (RMSEC 240-390 µg/kg), confirming the ability of the models to predict DON levels in wheat samples in the tested range. The validity of using FT-NIR spectroscopy to qualitatively discriminate wheat samples based on their content of DON was also investigated using a wider range of contamination levels. Discriminant analysis was performed on about 400 samples of durum wheat from different cultivars naturally contaminated with DON at levels up to about 18000 µg/kg. Results indicated that FT-NIR analysis was able to correctly discriminate up to about 90% of wheat samples depending on the cut-off limit fixed to distinguish the classes of samples. Performances of discriminant analysis and of PLS regression models indicate that FT-NIR analysis might be used for rapid, non-invasive, inexpensive and user-friendly screening of large numbers of unprocessed durum wheat samples
Rapid and non-destructive FT-NIR method for screening deoxynivalenol in wheat.
De Girolamo A;Pascale M;Lippolis V;Visconti A
2011
Abstract
Rapid and sensitive methods for the quantification of deoxynivalenol (DON), a type B trichothecene mycotoxin, in wheat and wheat-based food products are strongly demanded by private and public quality control laboratories. Chromatographic methods are the most widely used for quantitative determination of DON in foodstuffs and feedstuffs. However, these methods are destructive, time-consuming, expensive, unsuitable for screening purposes, and require a preliminary cleanup of the extracts. Recently, the feasibility of using Fourier-transform near infrared (FT-NIR) spectroscopy for rapid and non-invasive analysis of DON in unprocessed wheat at levels below the EU regulatory level has been reported. Calibration models for durum wheat, common wheat and durum+common wheat samples were obtained by using Partial Least Squares (PLS) regression with the external validation technique. A good fit between HPLC and FT-NIR data (r = 0.84-0.91) was achieved in the three PLS models in the measured range (from not detected to about 3000 µg/kg). Coefficients of determination (r2) indicated an "approximate to good" level of prediction of the DON content by FT-NIR spectroscopy in the PLS calibration models (r2 = 0.71-0.83), and a "good" discrimination between low and high DON contents in the PLS validation models (r2 = 0.58-0.63). Furthermore, values of root mean square error of prediction (RMSEP 310-380 µg/kg) were comparable and not too far from values of root mean square error of calibration (RMSEC 240-390 µg/kg), confirming the ability of the models to predict DON levels in wheat samples in the tested range. The validity of using FT-NIR spectroscopy to qualitatively discriminate wheat samples based on their content of DON was also investigated using a wider range of contamination levels. Discriminant analysis was performed on about 400 samples of durum wheat from different cultivars naturally contaminated with DON at levels up to about 18000 µg/kg. Results indicated that FT-NIR analysis was able to correctly discriminate up to about 90% of wheat samples depending on the cut-off limit fixed to distinguish the classes of samples. Performances of discriminant analysis and of PLS regression models indicate that FT-NIR analysis might be used for rapid, non-invasive, inexpensive and user-friendly screening of large numbers of unprocessed durum wheat samplesI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
