The increased resolving power provided by comprehensive two-dimensional gas chromatography (GCxGC) extends the chromatographer's ability to rapidly detect and measure smaller components in complex mixtures beyond that which was possible previously, allowing for the identification of hazardous components in complex mixtures such as foodstuffs or emergency response samples. In target analysis, the increased numbers of peaks resulting from the sample matrix can be largely ignored during the review of data. However, when the nature of the analyte of interest is not entirely known, analysis of the samples might require screening through the entire peak table for compounds with specific chemical characteristics. For example, in the analysis of foodstuffs for pesticides (1,2), GCxGC coupled with a time-of-flight mass spectrometry (GCxGC–TOF-MS) can provide low detection limits for multiple analytes in these complex samples. Yet the question remains as to whether other toxic compounds, not included in the target list, are present in the sample. The application of automated techniques for the identification of compounds based upon characteristics detectable in mass spectral data assists greatly in answering this question.

Methods for attempting to identify chemical compounds based upon the chromatographic properties and spectral characteristics are not new and have shown further development since the introduction of comprehensive two-dimensional gas chromatography (GCxGC). Welthagen and colleagues (3) were able to demonstrate a series of selection rules that provide discrimination between at least seven chemical classes in GCxGC chromatograms of airborne particulate matter. These rules identify compounds based upon ratios of abundances of specific masses in the spectra. Richenbach and colleagues (4) developed a computer language with its own syntax, allowing for the application of these compound class selection rules.

This work was expanded further by Vogt and colleagues (5) by applying rules based upon the knowledge-based classifiers developed by Welthagen as well as classifiers derived from chemometric analysis of spectra from the work of Varmuza and Werther (6) and the category-type classifiers of Lohninger and Varmuza (7). The work of Vogt was applied to deconvoluted spectra obtained from GCxGC–time-of-flight mass spectrometry (TOF-MS) chromatograms, and it employed the VBScript language, a dialect of BASIC language, available in the scripting option in later versions of the LECO ChromaTOF software (Leco, St. Joseph, Michigan).

In some types of analyses, ratios of abundances of specific masses might not be particularly helpful in identifying compound classes. The relevant masses arise as isotope abundances seen with a molecular ion or as neutral losses from a molecular ion. If one can identify the molecular ion, then one can use techniques applied routinely in the interpretation of mass spectra (8) to identify compounds or classes of compounds. In a search for toxic compounds in food or environmental samples, there are no unique mass spectral identifiers for the classification "toxic." Yet particular types of functionality are more likely to indicate a hazardous compound. For example, chlorinated and brominated compounds typically are accompanied by health risks. Frequently, these halogenated compounds can be identified by isotope ratios in molecular ions and neutral losses, indicating loss of the specific halogen atoms. In a screening method for toxic compounds, the general identification of chlorinated and brominated compounds can provide a selected list of compounds to be examined further. Similarly, sulfur-containing compounds are not as common in the environment as compounds containing carbon, hydrogen, oxygen, and nitrogen. Sulfur is found in many pesticides. Thus, a filter for sulfur-containing compounds might be useful as well.

In this work, scripts (functions written in VBScript language) are developed to locate a parent ion and test it to determine if it matches the abundance ratio expected for compounds containing specified numbers of chlorine, bromine, or sulfur atoms.

Experimental

Samples and Chromatographic Conditions

Table I: Chromatographic conditions used for acquisition of GCxGC chromatograms

Performance of the scripts was evaluated using previously acquired data (9). In this work, undiluted samples of commercially available citrus oils were analyzed under the conditions shown in Table I.

Method of Identification of Compounds