Rapid and non-destructive composition analysis of cereal flour blends by front-face synchronous fluorescence spectroscopy

Abstract

Maize, sorghum, wheat and barley are the several most important cereals for human beings. They can be utilized mixedly in certain applications, hence the determination of the composition of these flour blends may be necessary for economic, regulatory or nutritional reasons. In this work, front-face synchronous fluorescence spectroscopy (FFSFS) was utilized for the rapid and non-destructive composition analysis of these flour blends. Both the cases of binary and quaternary flour blends were investigated. Prediction models were constructed by partial least square (PLS) regression for both the two cases, respectively. For the binary blends of maize and sorghum or wheat and barley flours, the built models produced suitable results. The coefficient of determination (R2) values of calibration and five-fold cross-validation were all larger than 0.97. For quaternary blends of the four flours, the PLS model simultaneously predicted the contents of the flours with acceptable results, with the R2 values in the range of 0.896–0.963, root mean square error of prediction (RMSEP) < 8.5% and residual predictive deviation (RPD) > 3. Additionally, most relative prediction errors for simulated real-world samples ranged in -20–20% and the intra-day and inter-day coefficients of variation (CVs) were lower than 30%. This study offers a simple and rapid method for the composition analysis of multiple cereal flour blends without any time-consuming sample preparation procedures.