Rapid determination of total protein and wet gluten in commercial wheat flour using siSVR-NIR

The determination of total protein and wet gluten is of critical importance when screening commercial flour for desired processing suitability. To this end, a near-infrared spectroscopy (NIR) method with support vector regression was developed in the present study. The effects of spectral preprocessing and the synergy interval on model performance were investigated. The results showed that the models from raw spectra were not acceptable, but they were substantially improved by properly applying spectral preprocessing methods. Meanwhile, the synergy interval was validated with a good ability to improve the performance of models based on the whole spectrum. The coefficient of determination (R²), the root mean square error of prediction (RMSEP) and the standard deviation ratio (SDR) of the best models for total protein (wet gluten) were 0.906 (0.850), 0.425 (1.024) and 3.065 (2.482), respectively. These two best models have similar and lower relative errors (approximately 8.8%), which indicates their feasibility.