EFFECT OF USING SELECTED INFORMATION FROM HPLC-DAD AND PLS IN THE ELIMINATION OF INTERFERENCES FOR THE RESOLUTION OF A COMPLEX PESTICIDE MIXTURE

Abstract

Partial Least Squares (PLS) and Principal Component Regression (PCR) methods were applied to the simultaneous determination of a mixture of twelve pesticides by high performance liquid chromatography (HPLC). Calibration models at two different wavelengths were developed to resolve mixtures of the pesticides with overlapping chromatographic peaks. The first model carried out at 205 nm, as first detector compromise wavelength, yielded satisfactory sensitivity and selectivity for estimation of the concentration of iprodione, procymidone, triadimefon, and vinclozolin. The other model at 250 nm, as second detector compromise wavelength, was used for estimation of chlorothalonil, clorfenvinphos, fenamiphos, parathion-methyl, parathion-ethyl, and triazophos. However, two pesticides of the mixture, malathion and tebuconazole, showed bad prediction ability and were not determined, perhaps owing to their low signal relative to the other compounds. Both calibration models were evaluated by predicting the concentration of independent test set samples, and were successfully applied to the determination of these pesticides in groundwater samples. In all cases the PLS calibration method showed superior quantitative prediction ability than the PCR method.

ACKNOWLEDGMENT

The authors are grateful to DGICYT (project PB95-1226) for the financial support.