durum wheat pasta adulteration (2)

3925480647?profile=RESIZE_400xFaster screening methods are becoming increasingly important to permit rapid analyses, and FT-NIR spectroscopy offers the possibility of such a method.  Validation of screening methods requiring the application of multivariate data treatment is less frequently described in literature, thus limiting their use as routine tools in control laboratories for food fraud monitoring. Guidelines for validating screening methods for EU Official Control Laboratories involving pesticide residues, GMOs, allergens mycotoxins etc., were issued in 2013. In this research, an  EU-validation procedure for screening methods was developed and successfully applied to a multivariate FT-NIR spectroscopic method for the screening of durum wheat pasta samples adulterated with common wheat at the screening target concentration of 3%.  The results obtained demonstrated that the validation approach would be a proof-of-strategy to be used for multivariate infrared methods applied for screening purposes. 

Read the abstract here

Read more…

4439648992?profile=RESIZE_400xQuantitative DNA methods are used to detect and measure common wheat adulteration of durum wheat pasta. Italian and Argentinian researchers have validated a method for common wheat adulteration using Fourier transformed infrared spectroscopy (FT-IR) and chemomentrics. The dataset used to calibrate this infrared method was from 300 samples of both Italian and Argentinian durum wheat pasta analysed by an ELISA (enzyme-linked immunosorbent assay) method with common wheat adulteration ranging from less than 0.5% to 28%. These samples were analysed by both near- and mid-infrared spectroscopy (FT-NIR, FT-MIR) and the performance results were compared. The spectra were then analysed by two chemometric methods  - Partial-Least Squares Discriminant Analysis (PLS-DA) and Linear Discriminant Analysis (LDA). The first LDA and PLS-DA models grouped samples into three-classes, i.e. common wheat ≤1%, from 1 to ≤5% and >5%; while the second LDA and PLS-DA models grouped samples into two-classes using a cut-off of 2% common wheat adulteration. The accuracy of the validated models were between 80 and 95% for the three-classes approach, and between 91 and 97% for the two-classes approach. The three-classes approach provided better results in the FT-NIR range, while the two-classes approach provided comparable results in both spectral ranges. These results indicate the method could provide a rapid and inexpensive way of determining common what adulteration in durum wheat pasta.

Read the abstract

Read more…