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Detection of Pesticide Residues on Apple Based on Nanoparticle-Enhanced Laser-Induced Breakdown Spectroscopy |
ZHAO Xian-de1, 2, DONG Da-ming1, 2*, JIAO Lei-zi1, 2, TIAN Hong-wu1, 2, XING Zhen1, 2 |
1. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097,China
2. Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097,China |
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Abstract Pesticide residues on fruit surface are seriously harmful to human health. The conventional detection methods need sampling and processing, which are time-consuming and laborious. Laser induced breakdown spectroscopy has the ability of multi-element analysis and in situ measurement, and has great potential in the detection of pesticide residues on fruits. However, poor detection sensitivity limits the application of this technology to the detection of trace harmful elements on the surface of fruits. Improving the detection ability of laser induced breakdown spectroscopy is a hot research area. The enhancement effect of nanoparticle surface enhanced technology on the LIBS of chlorpyrifos residues on apple surface was studied in this paper. The metal nanoparticles were applied on the surface of the tested samples, and the induced atomic emission spectra were measured by laser induced breakdown spectroscopy. Through the study, it was found that the enhancement method of the metal nanoparticles can enhance the spectral peak intensity of the pesticide residue on the apple surface. The experimental results showed that the characteristic peak of phosphorus in the pesticide of chlorpyrifos increased by 5 times after the apple surface was applied metal nanoparticles. The application of this method is of great significance to the improvement of detection ability of trace harmful elements on the surface of fruits and vegetables. We then optimized the enhancement effect of metal nanoparticles. The enhancement ability of gold nanoparticles and silver nanoparticles, and the effect of particle size on the enhancement effect were studied. By comparing the enhancement effect of 20 nm gold nanoparticles, 20 nm silver nanoparticles and 80 nm silver nanoparticles, it was found that the enhanced effect of 80 nm silver nanoparticles on the pesticide spectrum of chlorpyrifos on the apple surface was the best. The effect of signal acquisition delay time on spectral signal-to-noise ratio (SNR) of laser induced breakdown spectroscopy system was studied, and it was found that the delay time of 0.2 μs can achieve an ideal signal-to-noise ratio. On the basis of the above study, using the optimal experimental parameters (80nm silver particles and 0.2 μs delay time), the quantitative analysis of chlorpyrifos residues on the surface of Apple was carried out by using the peak intensity of phosphorus in chlorpyrifos at 213.62, 214.91, 253.56 and 255.33 nm. The LIBS spectra of chlorpyrifos residues at concentrations of 30,20,15,12,10,6 μg·cm-2 were collected respectively. Then, the four characteristic peaks of phosphorus were used to quantify the curve fitting. It was found that LIBS had good quantitative predictive ability for residual chlorpyrifos, and the R2 was above 0.89. According to the quantitative fitting curve, we discussed the detection limit of nanoparticle-enhanced LIBS. It was found that the detection limit of chlorpyrifos on the apple surface can be as low as 1.61 μg·cm-2. This study proved that metal nanoparticles can significantly improve the sensitivity of LIBS to pesticide residues on apple surface.
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Received: 2018-06-11
Accepted: 2018-10-15
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Corresponding Authors:
DONG Da-ming
E-mail: dongdm@nercita.org.cn
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[1] Grimalt S, Pozo ó J, Sancho J V, et al. Anal. Chem., 2007, 79: 2833.
[2] He L, Luo X, Xie H, et al. Anal. Chim. Acta, 2009, 655: 52.
[3] Kolosova A Y, Park J, Eremin S A, et al. J. Agr. Food Chem., 2003, 51: 1107.
[4] Walz I, Schwack W. J. Agr. Food Chem., 2007, 55: 10563.
[5] Li J, Xue L, Liu M, et al. Chin. Opt. Lett., 2010, 8: 1050.
[6] Ma F, Dong D. Food Anal. Method, 2014, 7: 1858.
[7] Kim G, Kwak J, Choi J, et al. J. Agr. Food Chem., 2012, 60: 718.
[8] Multari R A, Cremers D A, Scott T, et al. J. Agr. Food Chem., 2013, 61: 2348.
[9] Du X, Dong D, Zhao X, et al. Rsc. Adv., 2015, 5:79956.
[10] Jedlinszki N,Galbacs G. Microchem. J., 2011, 97: 255.
[11] Babushok V I, DeLucia F C, Gottfried J L, et al. Spectrochimica Acta Part B Atomic Spectroscopy, 2006, 61: 999.
[12] Effenberger Jr A J,Scott J R. Sensors-Basel, 2010, 10: 4907.
[13] Hao Z, Guo L, Li C, et al. J. Anal. Atom. Spectrom., 2014, 29: 2309.
[14] Popov A M, Colao F,Fantoni R. J. Anal. Atom. Spectrom., 2009, 24: 602.
[15] Ohta T, Ito M, Kotani T, et al. Appl. Spectrosc., 2009, 63: 555.
[16] De Giacomo A, Gaudiuso R, Koral C, et al. Anal. Chem., 2013, 85: 10180.
[17] Rusak D A, Anthony T P,Bell Z T. Rev. Sci. Instrum., 2015, 86: 116106.
[18] De Giacomo A, Gaudiuso R, Koral C, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2014, 98:19. |
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