Detection of herbicides in drinking water by surface-enhanced Raman spectroscopy coupled with gold nanostructures

作者：Song Xuesong; Li Hao; Al Qadiri Hamzah M; Lin Mengshi^*

来源：Journal of Food Measurement and Characterization, 2013, 7(3): 107-113.

DOI：10.1007/s11694-013-9145-4

• Arsenic trioxide
• Chemical contaminants
• Confidence interval
• Gold nanostructures
• Partial least squares analysis
• Quantitative models
• SERS
• Surface enhanced Raman spectroscopy

This study aimed to use surface-enhanced Raman spectroscopy (SERS) to detect herbicide residues (atrazine and arsenic trioxide) in drinking water. Gold-coated nanosubstrates were used in the SERS measurements to acquire enhanced Raman signals of herbicides in drinking water. Compared with the control, characteristic patterns of SERS spectra were distinguishable for atrazine at 3 ppb and arsenic trioxide at 1 ppb. Partial least squares analysis was used to develop quantitative models for detection of two herbicides in drinking water and calibration curves were plotted with R2 of 0.988 and 0.991 for atrazine and arsenic trioxide, respectively. The study of limit of detection (LOD) demonstrates that at 99.86 % confidence interval, SERS can detect both herbicides at 0.1 ppm in drinking water. Satisfactory recoveries were obtained for samples with concentration at and higher than the LOD (92.3-119.3 % for atrazine and 88.2-102.1 % for arsenic trioxide). These results demonstrate that SERS coupled with gold nanostructures holds great potential for rapid detection of herbicide residues and other chemical contaminants in drinking water.

• 出版日期2013
• 单位University of Missouri