An empirical retention model for the optimization of on-line normal-phase LC-GC for the multi-analyte determination of hydrophobic compounds in fatty samples

Summary Normal-phase LC (NPLC) is a powerful method for the clean-up of fatty samples in the determination of organochlorine pesticides (OCPs). The injected sample deactivates the stationary phase and the triglyceride matrix therefore serves as a polarity modifier in the NPLC separation. Thus, the amount of sample injected is the key to both selectivity and sensitivity in matrixmodified LC coupled to capillary GC. In coupled LC-GC the NPLC separation becomes particularly critical because only a limited amount of the LC eluent can be transferred to the GC and the triglyceride matrix must be prevented from entering the GC, because it degrades the performance of the injector and the column. In previous applications method development was seriously hampered by these boundary conditions and tedious and lengthy trial-and-error experiments were required to determine suitable experimental conditions. In this study an empirical model was developed that describes the NPLC separation process in terms of column dimensions and fat loadability. The output is given as the probability of achieving successful LC-GC analysis of a particular set of analytes, thus furnishing a useful tool for the development of new applications in the field of exposure assessment and analysis of residues of apolar compounds in fatty samples. The limitations of current procedures—maximum transfer volumes and minimal separation—are also discussed.