农田水样中微囊藻毒素-LR拉曼检测方法的研究

Surface-enhanced Raman scattering spectroscopy for the detection of microcystin-LR in irrigation water samples

本研究建立了基于表面增强拉曼散射技术(Surface-enhanced Raman scattering,SERS)的农田水样中微囊藻毒素-LR(Microcystin-LR,MC-LR)的检测方法。采用柠檬酸钠还原法制备金种(Au nanoparticles,Au NPs),通过媒介增长法制备了刺状金纳米颗粒(Spiny gold nanoparticles,SGNPs),使用紫外-可见吸收光谱(Ultraviolet visible,UV-vis)、透射电镜(Transmission electron microscopy,TEM)和探针分子(对巯基苯甲酸,4-mercaptobenzoic acid,4-MBA)对SGNPs进行了表征及鉴定。研究以三角状金纳米颗粒作为基底,选择MC-LR在1007 cm-1和1309 cm-1处的特征峰作为定量峰,激光器激发波长为785 nm,积分时间20 s,建立检测方法。本研究建立的检测方法在1.0~100000μg·L-1的浓度范围内具有良好的线性关系,检测限(LOD)和回收率分别为1.0μg·L-1和80%~102%,使用本方法对镇江市内运粮河及古运河的灌溉水样进行检测,MC-LR的检出率为40%,含量最高达1.81μg·L-1,检测结果与LC-MS/MS比对,相关系数为0.84。本研究建立的方法快速准确,前处理简单,能满足农田水样中MC-LR的现场快速检测的要求。

In this study, a surface-enhanced Raman scattering(SERS)method based on spiny gold nanoparticles(SGNPs)was developed for detecting microcystin-LR(MC-LR) in irrigation water samples. SGNPs were prepared by the media growth method and then characterized by ultraviolet-visible(UV-vis)absorbance spectra and transmission electron microscopy(TEM). The SERS performances of SGNPs were comparatively evaluated using 4-mercaptobenzoic acid(4-MBA)as a signal reporter. According to the experimental results,the study chose Au TNs as the SERS detection base to establish a SERS method for detecting MC-LR in irrigation water samples. The characteristic peaks of MC-LR at 1 007 cm-1 and 1 309 cm-1 were chosen as the quantitative peaks. This method was performed with an excitation laser wavelength of 785 nm and the integration time for each spectrum was set to 20 s. The calibration curved showed a linear detection range from 1 μg·L-1 to 100 000 μg·L-1. The limit of detection(LOD)and recoveries of this method were 1.0 μg·L-1 and 80%~102%, respectively. The results of this method using naturally irrigation water samples showed that the concentrations of MC-LR were higher than 1 μg·L-1 in 40% of the samples, with the highest level reaching 1.81 μg·L-1. The correlation coefficient was 0.84 when compared to LC-MS/MS. Therefore, the SERS method based on SGNPs could meet the requirements of fast and on-site screening of MC-LR in irrigation water samples.