Simultaneous voltammetric determination of four triazine herbicides in water samples with the aid of chemometrics

• Published in: Journal of environmental science and health. Part B, Pesticides, food contaminants, and agricultural wastes Pesticides, food contaminants, and agricultural wastes, 2014-01, Vol.49 (10), p.722-729
• Main Authors: Qiu, Ping, Ni, Yongnian, Kokot, Serge
• Format: Article
• Language: English
• Subjects: Agronomy. Soil science and plant productions; Algorithms; Animal, plant and microbial ecology; Applied ecology; artificial neural networks; Atrazine - analysis; Biological and medical sciences; Calibration; chemometrics; differential pulse voltammetry; Electrodes; Environmental Monitoring - instrumentation; Environmental Monitoring - methods; Fundamental and applied biological sciences. Psychology; Gas Chromatography-Mass Spectrometry; Herbicides; Herbicides - analysis; Least-Squares Analysis; Models, Chemical; Models, Statistical; Neural Networks (Computer); Parasitic plants. Weeds; Phytopathology. Animal pests. Plant and forest protection; Principal Component Analysis; Principal components analysis; Simazine - analysis; Triazine herbicides; Triazines - analysis; Voltammetry; Water; Water Pollutants, Chemical - analysis; Weeds
• ISSN: 0360-1234; 1532-4109
• DOI: 10.1080/03601234.2014.929480

A novel differential pulse voltammetry (DPV) method was developed for the simultaneous analysis of herbicides in water. A mixture of four herbicides, atrazine, simazine, propazine and terbuthylazine was analyzed simultaneously and the complex, overlapping DPV voltammograms were resolved by several chemometrics methods such as partial least squares (PLS), principal component regression (PCR) and principal component-artificial networks (PC-ANN). The complex profiles of the voltammograms collected from a synthetic set of samples were best resolved with the use of the PC-ANN method, and the best predictions of the concentrations of the analytes were obtained with the PC-ANN model (%RPE T = 6.1 and average %Recovery = 99.0). The new method was also used for analysis of real samples, and the obtained results were compared well with those from the GC-MS technique. Such conclusions suggest that the novel method is a viable alternative to the other commonly used methods such as GC, HPLC and GC-MS.