High-accuracy quantitative model for phosphate anions in solution based on absorption spectroscopy and machine learning algorithms.

The eutrophication pollution caused by excessive phosphorus seriously affects production and daily life of the people. Accurate and rapid detection of phosphate is crucial for water quality management and cleaner production. Currently, most analytical methods for phosphates involve the addition of multiple chemical reagents and are incapable of simultaneous quantification of total phosphorus (TP) and phosphate anions. The environmental friendliness and analytical performance of the methods need to be improved. Here, we established a green and high-accuracy quantitative model based on absorption spectroscopy and machine learning algorithms, which achieved the analysis of TP, H 2 PO 4 − and HPO 4 2−. Based on the pH and absorption spectra of phosphate anions, classification and regression tree (CART), random forest (RF), and extreme gradient boosting (XGBoost) algorithms were used to train the original absorption spectra data, first-order derivative spectra data, and multiple feature parameter data of phosphate solutions with pH 4.7–10.0. By comparing the R2, root mean square error (RMSE) and mean absolute error (MAE) evaluation indicators, it was found that the phosphate anions quantitative model established using the CART based on the feature parameters of 187 nm performed the best, R2 > 0.9999, RMSE <3.4 × 10−6, MAE <8.1 × 10−7. The quantitative ranges of TP, H 2 PO 4 −, and HPO 4 2− were 3.98 × 10−4—9.33 × 10−4 mol/L, 5.98 × 10−6—4.20 × 10−4 mol/L and 1.53 × 10−6—7.43 × 10−4 mol/L, respectively. Moreover, the quantitative model was optimized based on the spectral characteristics of 14 interfering ions, to improve the model analytical performance for unknown samples. The quantitative model developed in the study achieves accurate analysis of TP, H 2 PO 4 − and HPO 4 2−, which is in line with green chemistry concept, and has the potential for prediction and early warning of water environment quality. [Display omitted] [ABSTRACT FROM AUTHOR]