Terahertz time-domain spectroscopy combined with chemometrics to quantify benzoyl peroxide content in wheat flour
The safety of wheat flour as a crucial food ingredient is paramount. Benzoyl peroxide (BPO) is banned in wheat flour in many regions due to health risks, yet it may be illegally added to enhance appearance. In the present study, BPO adulteration in wheat flour was quantitatively analyzed using terahertz time-domain spectroscopy (THz-TDS). First, the spectral characterization of wheat samples at 0.1–6 THz was obtained, and THz spectral data within specific frequency bands was processed using Savitzky-Golay (SG) filtering. Then, Competitive Adaptive Reweighted Sampling (CARS) and Variable Combination Population Analysis (VCPA) methods were used to select optimal frequency points. Finally, a chemometric model combining linear models (Lasso Regression, Ridge Regression, and Partial Least Squares Regression) with nonlinear models (Back-Propagation Neural Network, Random Forest, and Support Vector Machine) was employed for quantitative analysis. The experimental outcomes demonstrated that the detection models established through the standard analytical process met the detection requirements ( R P ≥ 0.95), and the best performance results were obtained from the chemometric models based on linear relationships. Among them, the Lasso Regression and Ridge Regression models obtained after optimization of the VCPA method had high prediction accuracy ( R P ≥ 0.97). The results showed that the THz spectroscopy technique combined with standard chemical analysis procedure could effectively realize the quantitative detection of BPO in wheat flour, providing an efficient and reliable tool for the safety detection of wheat flour.
危险品化学品经营许可证（带存储）