Application of Response Surface Methodology for Optimizing Test Parameters of Laser-Induced Plasma in Soil
YU Ke-qiang1, 2, ZHAO Yan-ru3, HE Yong3*
1. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
2. Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling 712100, China
3. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Abstract：The selection and optimization of the test parameters is one of the important steps in spectrochemical analysis based on laser-induced breakdown spectroscopy(LIBS). Appropriate test parameters can guarantee the accuracy of the later spectral data analysis. Here, LIBS technology was employed to study the influence of different test parameters of LIBS on the spectral characteristics of main elements in soils, and the universal soil testing parameters were obtained. Based on single variable test, the experiment of laser energy (LE), delay time (DT), and lens to sample distance (LTSD) three factors quadratic central composite design was carried out using the respond surface method (RSM). According to the mainelements(Si, Fe, Mg, Ca, Al, Na, K, etc.) in soil, the combined signal-background-ratio (SBR) of characteristic spectral lines from main elements was named as the objective function (YSBR). The interaction influences among three factors on soil plasma characteristics were explored and the optimized parameters of LIBS were summarized. Results revealed as follows: the factor LE showed a remarkable linear effect to YSBR, and factors of DT and LTSD exhibited an opposite result. The interaction of three factors displayed a non-significant relationship. Meanwhile, the quadratic terms of LE2, DT2 and LTSD2 had a significant surface relationship. Through the RSM analysis, the optimized experimental parameters were: LE: 103.09 mJ; DT: 2.92 μs; LTSD: 97.69 mm; and a peak value YSBR of 198.602 could be obtained. These optimized test parameters are the prerequisite for the LIBS data analysis in the late stage, which can offer important reference value for the soil LIBS detection in the field.
Key words：Laser-induced breakdown spectroscopy; Test parameters; Response surface methodology; Signal-background-ratio
余克强，赵艳茹，何 勇. 运用响应面分析法优化激光诱导土壤等离子体测试参数[J]. 光谱学与光谱分析, 2019, 39(02): 577-583.
YU Ke-qiang, ZHAO Yan-ru, HE Yong. Application of Response Surface Methodology for Optimizing Test Parameters of Laser-Induced Plasma in Soil. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(02): 577-583.
[1] Fortes F J, Moros J, Lucena P, et al. Analytical Chemistry, 2013, 85: 640.
[2] Hahn D, Omenetto N. Applied Spectroscopy, 2010, 74: 335A.
[3] Hahn D W, Omenetto N. Applied Spectroscopy, 2012, 66: 347.
[4] Noll R. Laser-Induced Breakdown Spectroscopy Fundaments and Application. Berlin Heidelberg: Springer-Verlag, 2012. 17.
[5] Musazzi S, Umberto P. Laser-Induced Breakdown Spectroscopy Theory and Application. Berlin Heidelberg: Springer-Verlag, 2014. 91.
[6] Tognoni E, Palleschi V, Corsi M, et al. Spectrochimica Acta Part B, 2002, 57: 1115.
[7] Unnikrishnan V K, Choudhari K S, Kulkarni S D, et al. RSC Advances, 2013, 3: 25878.
[8] ZHANG Shu-wei, WU Wei（张树玮，吴 伟）. Physics Experimentation（物理实验）, 2015, 35(8): 5.
[9] Nicolodelli G, Senesi G S, Romano R A, et al. Spectrochimica Acta Part B, 2015, 111: 23.
[10] SUN Lan-xiang, XIN Yong, CONG Zhi-bo（孙兰香, 辛 勇, 丛智博, 等）. Acta Optical Sinica（光学学报）, 2014, 34(5): 284.
[11] Kim G, Kwak J, Kim K R, et al. Journal of Hazardous Materials, 2013, 263: 754.
[12] de Carvalho G G A, Santos D, Gomes M D, et al. Spectrochimica Acta Part B, 2015, 105: 130.
[13] Gomes M D, Santos D, Nunes L C, et al. Talanta, 2011, 85: 1744.
[14] Fedotova N, Kaegi R, Koch J, et al. Spectrochimica Acta Part B, 2015, 103: 92.
[15] Yu K-Q, Zhao Y-R, Liu F, et al. Scientific Report, 2016, 6, 27574, doi: 10.1038/srep27574.
[16] Myers W R. Encyclopedia of Biopharmaceutical Statistics. New York: Marcel Dekker, 2003.
[17] Iqbal M, Iqbal N, Bhatti I A, et al. Ecological Engineering, 2016, 88: 265.
[18] Jacob S, Banerjee R. Bioresource Technology, 2016, 214: 386.
[19] LI Yun-yan，HU Chuan-rong（李云雁, 胡传荣）. Experiment Design and Data Processing（试验设计与数据处理）. 3rd ed.（第3版）. Beijing: Chemical Industry Press（北京：化学工业出版社）, 2008. 131
[20] YU Ke-qiang, HE Yong, LIU Fei（余克强，何 勇，刘 飞）. Transactions of the Chinese Society of Agricultural Engineering（农业工程学报）, 2015, 31(12): 1.
