Direct qualitative and quantitative determination methodology for massive screening of DON in wheat flour based on multi-molecular infrared spectroscopy (MM-IR) with 2T-2DCOS.

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.

Direct identification and quantitation of fluorescent whitening agent in wheat flour based on multi-molecular infrared (MM-IR) spectroscopy and stereomicroscopy.

Fluorescent brighteners, illegally used to whitening wheat flour, are detrimental to people health. The aim was to establish a rapid and direct method to identify and quantify fluorescent whitening agent OB-1 (FWA OB-1) in wheat flour by using multi-molecular infrared (MM-IR) spectroscopy combined with stereomicroscopy. Characteristic peak profile of FWA OB-1 used as a judgment basis was spatially revealed by stereomicroscopy with group-peak matching of MM-IR at 1614 cm-1, 1501 cm-1 and 893 cm-1 and were further unveiled by the second derivative infrared spectroscopy (SD-IR) and its two-dimensional correlation infrared (SD-2DCOS IR) spectroscopy for higher resolution, and were validated by high-performance liquid chromatography (HPLC). Moreover, a quantitative prediction model based on IR spectra was established by partial least squares 1 (PLS1) (R2, 98.361; SEE, 5.032; SEP, 5.581). The developed method was applicable for rapid and direct analysis of FWA OB-1 (low to 10 ppm) in flour with relative standard deviation (RSD) of 5%. The capabilities of MM-IR with spectral qualitative and quantitative analysis would be applicable to direct identification and quantitation of fluorescent whitening agents or other IR-active compounds in powder objects.

Simultaneous detection of trace adulterants in food based on multi-molecular infrared (MM-IR) spectroscopy.

Simultaneously rapid detection of trace adulterants in the complex systems of food without extraction is considered highly challenging. Herein, a high-throughput and rapid methodology, multi-molecular infrared (MM-IR) spectroscopy was developed for simultaneous detection of multiple trace adulterants in food. Flour was applied to demonstrate the capabilities of MM-IR with spatial resolution, spectral qualitative and quantitative analysis. Signals of 5 trace adulterants (rongalit, potassium bromate, borax, aluminum potassium sulfate and fluorescent brighter) were spatially revealed by IR hyperspectral imaging with group-peak matching, and further unveiled spectrally with second derivative two dimensional correlation infrared (SD-2DCOS IR) spectroscopy for higher resolution. Moreover, quantitative analysis of trace adulterants was conducted with partial least squares (PLS) modeling in ppm level. Composed of the above techniques and a series of resolution enhancement techniques (MW-2DCOS IR, 2T-2DCOS IR, etc.), MM-IR presented significant advantages on simultaneous detection of trace adulterants in food and therefore possessed the potential for food comprehensive analysis.