Simultaneous ultraviolet spectrophotometric determination of sodium benzoate and potassium sorbate by BP-neural network algorithm and partial least squares

摘要

In this study, we proposed a reliable method to quickly and simultaneously determine the content of sodium benzoate and potassium sorbate simultaneously by ultraviolet (UV) spectrophotometry with BP-neural network algorithm(BP-ANN) and partial least squares regression(PLS). The pure reagents were used to prepare a series of sodium benzoate and potassium sorbate solutions and used deionized water as a reference solution. The calibration models were constructed by using 36 reference samples according to the orthogonal design and the prediction model set consisted of 9 sets of randomly configured mixed solutions. The results used BP-ANN and PLS showed that the root mean square error prediction (RMSEP) of sodium benzoate and potassium sorbate were 0.129, 0.09 and 0.155, 0.089, and the correlation coefficient (R~2) were 0.9997, 0.9994 and 0.9998, 0.9995, respectively. The recovery of the actual samples by both methods was over 97%.