Chemometric approach for the resolution and quantification of unresolved peaks in gas chromatography–selected-ion mass spectrometry data

Abstract

A semiautomated and integrated chemometric approach is presented for the resolution and quantification of unresolved target-analyte signals in gas chromatography-selected-ion monitoring (GC-SIM) data collected using scanning mass spectrometers. The chemometric approach utilizes an unskewing algorithm and two multivariate chemometric methods known as rank alignment and the generalized rank annihilation method (GRAM). The unskewing algorithm corrects the retention-time differences within a single GC-SIM data matrix caused by using a scanning mass spectrometer. Rank alignment objectively corrects the run-to-run retention-time difference between a sample GC-SIM data matrix and a standard addition GC-SIM data matrix. GRAM analysis uses the sample and standard addition data matrices to mathematically resolve and quantify the target-analyte signal(s). The resolution and quantification of severely unresolved target-analyte signals are demonstrated using GC-SIM data obtained from conventional heart-cut two-dimensional gas chromatography with mass spectrometric detection. In addition, the GC-SIM data is used to demonstrate the result of chemometric analysis when the absence of a target-analyte signal is obscured by interference. Chemometric analysis is shown to unambiguously detect an analyte based on its resolved mass chromatograms in situations where the traditional approach of measuring peak height fails to positively detect it. The predicted analyte concentrations are within 8% of the reference concentrations.