化学
拉曼光谱
选择(遗传算法)
随机森林
分析化学(期刊)
变量(数学)
表面增强拉曼光谱
特征选择
生物系统
环境化学
人工智能
光学
拉曼散射
物理
生物
数学分析
数学
计算机科学
作者
Shizhuang Weng,Mengqing Qiu,Ronglu Dong,Fang Wang,Linsheng Huang,Dongyan Zhang,Jinling Zhao
标识
DOI:10.1016/j.saa.2018.04.012
摘要
Dynamic surface-enhanced Raman spectroscopy (D-SERS) based on the state change of the substrate not only significantly enhances but also provides a highly reproducible Raman signal. Hence, we develop a fast and accurate method for the detection of fenthion on fruit and vegetable peel using D-SERS and random forests (RF) with variable selection. With uniform Ag nanoparticles, the dynamic spectra of fenthion solution at different concentrations were obtained using D-SERS, and fenthion solution greater than or equal to 0.05 mg/L can be detected. Then, the quantitative analysis models of fenthion were developed by RF with variable selection for spectra of different range. The model of best performance is developed by RF and spectra of characteristic range with higher RF importance (top 40%), and the root mean square error of cross-validation is 0.0101 mg/L. Moreover, the fenthion residue of tomato, pear, and cabbage peel were extracted by a swab dipped in ethanol and analyzed using the above method to further validate the practical effect. Compared to gas chromatography, the maximal relative deviation is below 12.5%, and the predicted recovery is between 87.5% and 112.5%. Accordingly, D-SERS and RF with variable selection can realize the fast, simple, ultrasensitive, and accurate analysis of fenthion residue on fruit and vegetable peel.
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