Detection of Dimethoate Content with Laser Induced Breakdown Spectroscopy Combined with LSSVM and Internal Standard Method
SUN Tong, LIU Jin, GAN Lan-ping, WU Yi-qing, LIU Mu-hua*
Key Laboratory of Jiangxi University for Optics-Electronics Application of Biomaterials, College of Engineering, Jiangxi Agricultural University; Collaborative Innovation Center of Postharvest Key Technology and Quality Safety of Fruits and Vegetables in Jiangxi Province, Nanchang 330045，China
Abstract：In this research, collineardouble pulselaser induced breakdown spectroscopy (LIBS) was used to detect dimethoate content in solutionquantificationally. Fortune paulownia wood chip with cylinder shape was used to enrichmentdimethoate, and the spectra of samples were acquired with a two-channel high precision spectrometer in the wavelength range of 206.28~481.77 nm. Four spectral linesof phosphorus (213.618, 214.91, 253.56, 255.325 nm) were selected as analytical lines, and carbonspectral line (247.856 nm) was used as internal standard line. Then, univariatelinear fitting and least squares support vector machine (LSSVM) were used to develop univariate calibration model, LSSVM calibration model and LSSVM calibration model based on internal standard method, and the performance of threecalibration models were compared. The results indicate that collinear double pulse LIBS combined with LSSVM and internal standard method is feasible for detecting dimethoate content in solution quantificationally. The coefficient of determination (R2) of LSSVM calibration model based on internal standard method is 0.999 7, and the average relative errors in training set and validation set are 11.24% and 12.01%, respectively. In the three calibration models, LSSVM calibration model based on internal standard method has the best performance, and the performance of LSSVM calibration model is the second, while univariatecalibration model hasthe worstperformance. So it can be concluded that LSSVM and internal standard method can improve the performance of calibration model to some extent, and improve the prediction accuracy.
Key words：Laser induced breakdown spectroscopy; Least squares support vector machine; Internal standard method; Dimethoate
孙 通，刘 津，甘兰萍，吴宜青，刘木华. 最小二乘支持向量机和内标法的乐果农药含量LIBS检测[J]. 光谱学与光谱分析, 2018, 38(04): 1251-1255.
SUN Tong, LIU Jin, GAN Lan-ping, WU Yi-qing, LIU Mu-hua. Detection of Dimethoate Content with Laser Induced Breakdown Spectroscopy Combined with LSSVM and Internal Standard Method. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1251-1255.
[1] Bonta M, Gonzalez J J, Quarles C D, et al. Journal of Analytical Atomic Spectrometry, 2016, 31(1): 252.
[2] Yuan T, Wang Z, Li Z, et al. Analytica Chimica Acta, 2014, 807: 29.
[3] Qi L，Sun L，Xin Y，et al. Plasma Science and Technology, 2015, 17(8): 676.
[4] LI Yuan-dong, LU Yuan, QI Fu-jun, et al(李远东, 卢 渊, 亓夫军, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(7): 2238.
[5] Guo J, Lu Y, Cheng K, et al. Appl. Opt., 2007, 56(29): 8196.
[6] Simileanu M. Romanian Reports in Physics, 2016, 68(1): 203.
[7] YU Ke-qiang, ZHAO Yan-ru, LIU Fei, et al(余克强, 赵艳茹, 刘 飞, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2016, 32(15): 197.
[8] WU Yi-qing, LIU Jin, MO Xin-xin, et al(吴宜青, 刘 津, 莫欣欣, 等). Chinese Journal of Analytical Chemistry(分析化学), 2016, 44(12): 1919.
[9] Kim G, Kwak J, Choi J, et al. Journal of Agricultural and Food Chemistry, 2012, 60(3): 718.
[10] Multari R A, Cremers D A, Scott T, et al. Journal of Agricultural and Food Chemistry, 2013, 61(10): 2348.
[11] Ma F, Dong D. Food Analytical Methods, 2014, 7(9): 1858.
[12] Du X, Dong D, Zhao X, et al. RSC Advances, 2015, 5: 79956.
[13] Suykens J A K, Van Gestel T, De Brabanter J, et al. Least Squares Support Vector Machines. Singapore: World Scientific, 2002.
[14] Essington M E, Melnichenko G V, Stewart M A, et al. Soil Science Society of America Journal, 2009, 73(5): 1469.
