In-situ Detection and Analysis of Chlorpyrifos Concentration in Water Based on Near-infrared Spectroscopy, Adaboost and PLS

In order to explore the feasibility of in-situ detection of Chlorpyrifos in water by near-infrared spectroscopy, NIRQuest512 near-infrared spectrometer produced by American ocean company was used to build a near-infrared spectrum acquisition system to obtain spectrum data of Chlorpyrifos samples in different concentration ranges. Based on AdaBoost algorithm and PLS partial least square algorithm, the whole band quantitative model of Chlorpyrifos sample spectrum data was established respectively. The results showed that AdaBoost algorithm had better prediction ability than PLS. In addition, the characteristic band of Chlorpyrifos sample spectrum was selected by calculating the correlation coefficient through correlation analysis, and the characteristic band of the experimental spectrum with concentration range of 1–100 ug/mL was 898-1358nm, 1448-1626nm, 1661-1703nm. The quantitative model of the sample characteristic band spectrum data was established by combining the algorithm. Compared with the full band model, the calibration set determination coefficients of the experimental spectral characteristic band model with concentration range of 1–100 ug/mL were increased to 0.999 and 0.963, respectively. The decision coefficients of prediction set were increased to 0.944 and 0.748, respectively. The RMS error of the correction set was reduced to 0.657 and 6.521 respectively. The RMS error of the prediction set was reduced to 6.81 and 14.212 respectively, and the RPD value increased to 4.24 and 2.131. Compared with the prediction ability of the quantitative model of Chlorpyrifos based on the characteristic band and PLS method, the quantitative model of Chlorpyrifos based on the characteristic band and Adaboost method had a high precision prediction ability, which can meet the quantitative analysis conditions. Therefore, the rapid detection of chlorpyrifos pesticide by this method was feasible. The results of this study was applicable to the application of near infrared spectroscopy The detection technology provided theoretical basis and practical application value for the rapid in-situ detection of organophosphorus pesticide and other non-point source pollutants.