玉米粉中苯甲酸的太赫兹光谱定量检测研究

为了检测玉米粉中苯甲酸的含量,控制苯甲酸在玉米粉中使用量,提高食品安全等级,采用太赫兹光谱技术对玉米粉中苯甲酸含量进行定量研究,获得了玉米粉中不同质量分数的苯甲酸在0.5THz^3THz的光谱数据。采用偏最小二乘、最小二乘支持向量机和多元线性回归构建光谱模型,未参与建模的样品用来进行模型评估,并利用预测集相关系数Rp和预测集均方根误差eRMSEP对模型进行了评价。结果表明,最小二乘支持向量机模型评价能力最强,预测集相关系数Rp=0.9958,预测集均方根误差eRMSEP=0.0057。说明太赫兹技术结合化学计量学方法可以用于定量检测玉米粉中苯甲酸的含量。

Quantitative detection of benzoic acid in corn flour by terahertz spectroscopy

In order to detect the content of benzoic acid in corn flour, control the amount of benzoic acid used in corn flour to improve food safety grade, the content of benzoic acid in corn flour was studied using terahertz spectroscopy technology, and the terahertz benzoic acid spectral data of different mass fractions in corn flour was obtained. In order to improve the accuracy of the model, pre-processing methods such as moving average smoothing algorithm, standard normal transformation, multi-scattering correction, baseline correction, and normalization were used to eliminate the original spectral noise and useless information. The least squares support vector machine(LS-SVM), partial least squares(PLS), and multiple linear regression(MLR) spectroscopy models were constructed, and the model samples were not used for model evaluation. The model was evaluated based on the prediction set correlation coefficient e_RMSEP and the prediction set root mean square error R_p. The results show that the least squares support vector machine model with the original terahertz time-domain spectral preprocessing has the strongest evaluation ability. The correlation coefficient of the prediction set R_p=0.9958, and the root mean square error of the prediction(RMSEP) set e_RMSEP=0.0057, indicating the metrology method of THz-TDS binding chemistry can be used to detect the quantitative determination of benzoic acid in corn flour.