Alternative calibration techniques for counteracting the matrix effects in GC-MS-SPE pesticide residue analysis - a statistical approach.

This paper investigates the efficiency of application of four different multivariate calibration techniques, namely matrix-matched internal standard (MMIS), matrix-matched external standard (MMES), solvent-only internal standard (SOIS) and solvent-only external standard (SOES) on the detection and quantification of 20 organochlorine compounds from high, low and blank matrix water sample matrices by Gas Chromatography-Mass Spectrometry (GC-MS) coupled to solid phase extraction (SPE). Further statistical testing, using Statistical Package for the Social Science (SPSS) by applying MANOVA, T-tests and Levene's F tests indicates that matrix composition has a more significant effect on the efficiency of the analytical method than the calibration method of choice. Matrix effects are widely described as one of the major sources of errors in GC-MS multiresidue analysis. Descriptive and inferential statistics proved that the matrix-matched internal standard calibration was the best approach to use for samples of varying matrix composition as it produced the most precise average mean recovery of 87% across all matrices tested. The use of an internal standard calibration overall produced more precise total recoveries than external standard calibration, with mean values of 77% and 64% respectively. The internal standard calibration technique produced a particularly high overall standard deviation of 38% at 95% confidence level indicating that it is less robust than the external standard calibration method which had an overall standard error of 32% at 95% confidence level. Overall, the matrix-matched external standard calibration proved to be the best calibration approach for analysis of low matrix samples which consisted of the real sample matrix as it had the most precise recovery of 98% compared to other calibration approaches for the low-matrix samples.