Rapid and non invasive analysis of deoxynivalenol in durum and common wheat by Fourier-Transform Infrared (FT-NIR) spectroscopy
Résumé
Fourier transform near-infrared spectroscopy (FT-NIR) was used for rapid and non-invasive analysis of deoxynivalenol (DON) in durum and common wheat. The relevance of using ground wheat samples with a homogeneous particle size distribution to minimize the variation of measurements and avoid DON segregation among particles of different sizes was established. Calibration models for durum wheat, common wheat and durum+common wheat samples, with particle size < 500 µm, were obtained by using Partial Least Squares (PLS) regression with the external validation technique. Values of root mean square error of prediction (RMSEP, 306-379 µg kg-1) were comparable and not too far from values of root mean square error of cross-validation (RMSECV, 470-555 µg kg-1). 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). A “limited to good” practical utility of the models was ascertained by range error ratio (RER) values higher than 6. A qualitative model, based on 197 calibration samples, was developed to discriminate between blank and naturally contaminated wheat samples by setting a cut off at 300 µg kg-1 DON to separate the two classes. The model correctly classified 69% of the 65 validation samples with most misclassified samples (16 out of 20) showing DON contamination levels quite close to the cut off level. These findings suggest that FT-NIR analysis is suitable for the determination of DON in unprocessed wheat at levels far below the DON maximum permitted limits set by the European Commission.
Origine : Fichiers produits par l'(les) auteur(s)