A Non-invasive Method for Screening Sodium Hydroxymethanesulfonate in Wheat Flour by Near-Infrared Spectroscopy

A rapid and non-invasive method, based on near infrared diffuse reflectance spectroscopy, was established for screening sodium hydroxymethanesulfonate in wheat flour. Successive projection algorithm was used for spectral variable selection. The selected variables were applied as inputs to partial least square discriminant analysis (PLS-DA) and advanced K-means dynamic clustering. The first two principal components extracted by PLS-DA had been applied as inputs to least squares support vector machine (LS-SVM). Three algorithms, including PLS-DA, advanced K-means dynamic clustering, and LS-SVM, were used to establish the calibration model. The results of LS-SVM outperformed that of the other two methods, with the classification accuracy of 92.0% for the validation and 94.7% for the prediction. The results of the study showed the potential of near-infrared spectroscopy as a non-invasive and environmentally acceptable method for the screening of sodium hydroxymethanesulfonate in wheat flour.