水果表面的农药残留严重危害身体健康, 而常规检测方法需要采样处理, 耗时、 费力。 激光诱导击穿光谱技术具有多元素分析和原位测量的能力, 在水果表面农药残留检测方面潜力巨大。 但是较差的检测灵敏度, 限制了此技术在水果表面微量有害元素检测方面的应用。 提高激光诱导击穿光谱系统的检测能力是目前的研究热点领域, 研究了纳米粒子表面增强技术对苹果表面残留的毒死蜱农药的激光诱导击穿光谱信号的增强效果。 通过在被测样品表面涂抹币族金属纳米粒子, 然后利用激光诱导击穿光谱激发样品表面, 对诱导出的原子发射光谱信号进行测量, 实验结果表明, 苹果表面涂抹金属纳米粒子后毒死蜱农药中磷元素的特征峰有4倍的增强。 此方法的应用对提高果蔬表面微量有害元素的检测能力具有重要意义。 然后我们对币族金属纳米粒子的增强效果进行了优化。 研究了金纳米粒子和银纳米粒子的增强能力, 同时对纳米粒子的粒径的增强效果进行了比较, 通过对20 nm的金纳米粒子、 20 nm的银纳米粒子和80 nm的银纳米粒子的增强效果比较, 发现80 nm的银纳米粒子对苹果表面毒死蜱农药光谱的增强效果最好。 研究了信号采集延时时间对光谱信噪比的影响, 确定了0.2 μs的延时时间可以获得较为理想的信噪比。 在以上研究的基础上, 采用最优的实验参数(80 nm银粒子增强、 0.2 μs的延时时间), 以毒死蜱中磷元素在213.62, 214.91, 253.56和255.33 nm处的特征峰峰强作为依据, 对苹果表面残留的毒死蜱农药进行了定量化分析。 分别采集了毒死蜱残留浓度分别为30, 20, 15, 12, 10和6 μg·cm-2的苹果表面的LIBS光谱, 然后分别利用磷元素的四个特征峰峰强进行了定量化曲线拟合, 结果发现LIBS对残留的毒死蜱具有很好的定量化预测能力, R2在0.89以上。 根据定量化拟合曲线, 探讨了纳米增强LIBS的检测限, 计算得到, 利用纳米增强LIBS技术测量苹果表面的毒死蜱农药最低可以做到1.61 μg·cm-2的检测限。 研究证明了金属纳米粒显著提高了LIBS对苹果表面农药残留的检测灵敏度。

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.