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Quantitative determination of ametryn in river water using surface-enhanced Raman spectroscopy coupled with an advanced chemometric model
- Source :
- Chemometrics and Intelligent Laboratory Systems. 142:166-171
- Publication Year :
- 2015
- Publisher :
- Elsevier BV, 2015.
-
Abstract
- In this contribution, surface-enhanced Raman spectroscopy (SERS) coupled with an advanced chemometric method-multiplicative effects model (MEM SERS ) has been applied to quantitative analysis of ametryn in water samples of the Xiangjiang River (Changsha, China). The adoption of MEM SERS calibration model was to eliminate the detrimental effects caused by variations in the physical properties of enhancing substrates, the intensity and alignment/focusing of laser excitation source. Experimental results showed that the combination of SERS with MEM SERS can provide quite precise concentration predictions for ametryn in water samples of the Xiangjiang River with an average relative prediction error of about 4.8%. The combination of SERS with MEM SERS can compete with LC-MS/MS in terms of precision and accuracy of quantitative results. The limit of quantification was about 0.09 μM. More importantly, no laborious reference methods (e.g., HPLC) were needed to build the MEM SERS calibration model, since the MEM SERS calibration model built on the calibration samples prepared with ultrapure water could provide satisfactory quantification results for the test samples prepared with water collected from the Xiangjiang River. Therefore, it is reasonable to expect that SERS in combination with MEM SERS model would become a competitive alternative in routine quantitative analysis of ametryn in environmental water samples.
- Subjects :
- Detection limit
Accuracy and precision
Chromatography
Chemistry
Process Chemistry and Technology
Analytical chemistry
Surface-enhanced Raman spectroscopy
River water
Quantitative determination
Computer Science Applications
Analytical Chemistry
symbols.namesake
Ultrapure water
symbols
Calibration
Raman spectroscopy
Spectroscopy
Software
Subjects
Details
- ISSN :
- 01697439
- Volume :
- 142
- Database :
- OpenAIRE
- Journal :
- Chemometrics and Intelligent Laboratory Systems
- Accession number :
- edsair.doi...........8589aa91d0d61c17f57499f5f440a7fd
- Full Text :
- https://doi.org/10.1016/j.chemolab.2015.01.012