Abstract：In this study, the fast and effective quantitative prediction analysis model was established by using the absorption spectrum data of different concentration gradients of malathion in the ultraviolet/visible wavelength range. In the process of establishing a prediction model, the quality of the calibration set samples and wavelength variables involved in the modeling plays a decisive role in the predictive ability of the quantitative analysis model. Therefore, firstly checked whether there were abnormal samples in the experimental samples, then used the different preprocessing methods for the spectral data in the wavelength range of 200.08 to 750.04 nm and then established corresponding PLS model, Further based on the spectral data of the optimal preprocessing result (mean centering), competitive adaptive weighted algorithm (CARS) and Monte Carlo-uninformative variable elimination method (MC-UVE) were used to select the key wavelength variables respectively and established corresponding PLSprediction model. Model results indicated that CARS algorithm was superior to MC-UVE algorithm in the performance of key variable screening; then 18 wavelength variables (1.137 8% of the original variable number) selected by CARS algorithm combined with the 44 modeled samples (88% of the original sample number) respectively obtained from Kennard-Stone (K-S) algorithm method and Monte Carlo cross-validation method (MCCV) to establish CARS-K-Ss-PLS and CARS-CCVs-PLS quantitative prediction model, which R2p were 0.998 2 and 0.998 9, RMSEP were 0.863 4 and 1.026 2, and RPD were 24.163 5 and 20.330 1, as a result the CARS-K-Ss-PLS model was slightly better CARS-CCVs-PLS model. The experimental results showed that the CARS algorithm could eliminate variables with weak correlation with sample concentration and effectively eliminate irrelevant spectral information. The K-S algorithm can help to select a better modeling sample set. UV-Vis absorption spectrum of malathion pesticides combined with the CARS-K-Ss-PLS model established by the CARS algorithm and K-S algorithm can predict malathion pesticide concentration. This study provides a certain of the important theoretical basis and experimental basis for the rapid detection of organophosphorus pesticide concentration by spectroscopy technology, and has a good application prospect in the field of rapid detection of organophosphorus pesticide.
甄欢仪，马瑞峻，陈 瑜，孙小鹏，马创立. 基于CARS和K-S的马拉硫磷农药浓度吸收光谱预测模型研究[J]. 光谱学与光谱分析, 2020, 40(05): 1601-1606.
ZHEN Huan-yi, MA Rui-jun, CHEN Yu, SUN Xiao-peng, MA Chuang-li. Study on Prediction Model of Malathion Pesticide Concentration Absorption Spectra Based on CARS and K-S. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(05): 1601-1606.
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