光谱学与光谱分析 |
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Quantitative Analysis of Cr in Soil with Laser Induced Breakdown Spectroscopy Combined With Multivariate Calibration |
GU Yan-hong1,2, ZHAO Nan-jing1*, MA Ming-jun1, MENG De-shuo1, WANG Yin1, YU Yang1, HU Li1, FANG Li1, WANG Yuan-yuan1, LIU Jian-guo1, LIU Wen-qing1 |
1. Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China 2. University of Science and Technology of China, Hefei 230026, China |
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Abstract Laser-induced breakdown spectroscopy (LIBS) was used to calibrate the concentration of Cr in soils combined with Support Vector Machine. The Nd:YAG pulse laser with the wavelength of 1 064 nm was used as the excitation source. The grating spectrometer and the charge couple device were used as spectral separation device and the spectral detection device. The multiple linear regression and support vector machine were adopted to make quantitative analysis on Cr in soils respectively. The result indicate that the multiple linear regression can get more accurate informination of the spectral lines: the correlation coefficient is increased from 0.689 to 0.980 compared with conventional quantitative method. Thereofre, the the accuracy of quantitative analysis is increased. The slope about calibration curve with support vector machine of test set is nearly about 1 and the correlation coefficient is 0.998, the relative errors for the test set all are lower than 2.57%, the quantitative analysis results about support vector machine are better than the results combined with the conventional quantitative method and the multiple linear regression. The support vector machine can correct the matrix effect and improve the accuracy of prediction on the concentration of Cr in soil.
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Received: 2015-03-20
Accepted: 2015-08-15
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Corresponding Authors:
ZHAO Nan-jing
E-mail: njzhao@aiofm.ac.cn
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[1] Samuel M Clegg, Elizabeth Sklute, M Darby Dyar, et al. Spectrochimica Acta Part B, 2009, 64: 79. [2] Giacomo A D, Gaudiuso R, Koral C, et al. Analytical Chemistry, 2013, 85, 10180.[3] Aguirre M A, Legnaioli S, Almodóvar F, et al. Spectrochimica Acta Part B, 2013, 79: 88. [4] Sarah Darwiche, Rafik Benrabbah, Malek Benmansour, et al. Spectrochimica Acta Part B, 2012, 74: 115. [5] Wainner R T, Harmon R S, Miziolek A W, et al. Spectrochimica Acta Part B, 2001, 56(6): 777. [6] Haddad J E, Villot-Kadri M, Ismal A, et al. Spectrochimica Acta Part B, 2013, 79: 51. [7] SHEN Qin-mei, ZHOU Wei-dong, LI Ke-xue(沈沁梅, 周卫东, 李科学). Acta Photonica Sinica(光子学报), 2010, 39(12): 2134. [8] Giacomo A D, Dell’Aglio M, Pascale O D, et al. Spectrochimica Acta Part B, 2014, 100: 180. [9] XU Hong-min, WANG Hai-ying, LIANG Jin, et al(徐红敏, 王海英,梁 瑾, 等). Journal of Beijing Institute of Petro-Chemical Technology(北京石油化工学院学报), 2010, 18(1): 62. [10] LIU Xiao-fei, WANG Jian-dong(刘小飞, 王建东). Informatization Research(信息化研究), 2011, 37(1): 46. [11] Eranga Ukwatta, Jagath Samarabandu, Mike Hall. Machine Vision and Applications, 2012, 23: 111. [12] Marek Hoehse, Andrea Paul, Igor Gornushkin, et al. Anal. Bioanal. Chem., 2012, 402: 1443. [13] Qi Jun, Wei Jia, Sun Changhong, et al. Frontiers of Earth Science,2011, 5(3): 245. [14] Cisewski J, Snyder E, Hanning J, et al. Journal of Chemometrics, 2012, 26(5): 143. [15] WANG Chun-long, LIU Jian-guo, ZHAO Nan-jing, et al(王春龙, 刘建国, 赵南京, 等). Acta Optica Sinica(光学学报), 2013, 33(3): 0330002. |
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