Direct qualitative and quantitative determination methodology for massive screening of DON in wheat flour based on...

Deoxynivalenol (DON) contamination in wheat flour induces a number of adverse health effects to consumers and livestock, even at very low concentrations. Direct detection methods for massive screening of DON in wheat flour is still lacking. A new methodology integrating multi-molecular infrared spectroscopy (MM-IR) with two-trace two-dimensional correlation spectroscopy (2T-2DCOS) was developed for in-situ qualitative and quantitative determination of DON in wheat flour as a whole. Typical spectral variation of wheat flour samples with diverse concentration of DON were stepwise characterized by MM-IR and tiny spectral profile differences resulting from concentration variation of DON were visually disclosed by 2T-2DCOS. Based on the obtained key spectral features of DON, 180 of wheat flour samples with DON higher and lower than 1.00 mg/kg were undoubtedly classified by Principal Component Analysis (PCA) and Support Vector Machines (SVM) with an accuracy rate up to 100% (for Second derivative spectra consisted of selected bands, SD-SS). Furthermore, a robust quantitative prediction model was established based on partial least squares (PLS) of SD-SS (Rc: 0.998, RMSEC: 0.135; Rp: 0.968, RMSEP: 0.421), and its excellent predictive capacity of model was validated by both residual prediction deviation (RPD) value of 3.2 and t-test. It was demonstrated that the developed methodology was applicable for screening and quantitative detection of DON in wheat flour based on the novel correlation analysis methods (SD-2DCOS-IR and 2T-2DCOS-IR) with chemometrics tools, which could be utilized both at laboratory and industrial level for quality control purposes of a large wheat flour sample set.