5 research outputs found
Current Developments in Analyzing Food Volatiles by Multidimensional Gas Chromatographic Techniques
This paper presents current developments and future perspectives
on the spread of advanced analytical tasks in the field of food volatile
analysis. The topics outlined comprise (a) recent advances on miniaturized
sampling techniques; (b) the potential and challenges of multidimensional
gas chromatography coupled with mass spectrometric detection for volatile
identification and quantitation in samples with complex matrices;
(c) the potential of comprehensive two-dimensional gas chromatography
in fingerprinting studies, in particular for classifying complex samples
in routine analysis; and (d) the key role of dedicated software tools
for data elaboration with comprehensive two-dimensional separations
Effectiveness of Global, Low-Degree Polynomial Transformations for GCxGC Data Alignment
As
columns age and differ between systems, retention times for
comprehensive two-dimensional gas chromatography (GCxGC) may vary
between runs. To properly analyze GCxGC chromatograms, it often is
desirable to align the retention times of chromatographic features,
such as analyte peaks, between chromatograms. Previous work by the
authors has shown that global, low-degree polynomial transformation
functions, namely affine, second-degree polynomial, and third-degree
polynomial, are effective for aligning pairs of two-dimensional chromatograms
acquired with dual second columns and detectors (GC×2GC). This
work assesses the experimental performance of these global methods
on more general GCxGC chromatogram pairs and compares their performance
to that of a recent, robust, local alignment algorithm for GCxGC data
[Gros Anal. Chem. 2012, 84, 9033].
Measuring performance with the root-mean-square (RMS) residual differences
in retention times for matched peaks suggests that global, low-degree
polynomial transformations outperform the local algorithm given a
sufficiently large set of alignment points, and are able to improve
misalignment by over 95% based on a lower-bound benchmark of inherent
variability. However, with small sets of alignment points, the local
method demonstrated lower error rates (although with greater computational
overhead). For GCxGC chromatogram pairs with only slight initial misalignment,
none of the global or local methods performed well. In some cases
with initial misalignment near the inherent variability of the system,
these methods worsened alignment, suggesting that it may be better
not to perform alignment in such cases
Reliable Peak Selection for Multisample Analysis with Comprehensive Two-Dimensional Chromatography
Comprehensive two-dimensional chromatography
is a powerful technology for analyzing the patterns of constituent
compounds in complex samples, but matching chromatographic features
for comparative analysis across large sample sets is difficult. Various
methods have been described for pairwise peak matching between two
chromatograms, but the peaks indicated by these pairwise matches commonly
are incomplete or inconsistent across many chromatograms. This paper
describes a new, automated method for postprocessing the results of
pairwise peak matching to address incomplete and inconsistent peak
matches and thereby select chromatographic peaks that reliably correspond
across many chromatograms. Reliably corresponding peaks can be used
both for directly comparing relative compositions across large numbers
of samples and for aligning chromatographic data for comprehensive
comparative analyses. To select reliable features for a set of chromatograms,
the Consistent Cliques Method (CCM) represents all peaks from all
chromatograms and all pairwise peak matches in a graph, finds the
maximal cliques, and then combines cliques with shared peaks to extract
reliable features. The parameters of CCM are the minimum number of
chromatograms with complete pairwise peak matches and the desired
number of reliable peaks. A particular threshold for the minimum number
of chromatograms with complete pairwise matches ensures that there
are no conflicts among the pairwise matches for reliable peaks. Experimental
results with samples of complex bio-oils analyzed by comprehensive
two-dimensional gas chromatography (GCxGC) coupled with mass spectrometry
(GCxGC–MS) indicate that CCM provides a good foundation for
comparative analysis of complex chemical mixtures
Comprehensive Chemical Fingerprinting of High-Quality Cocoa at Early Stages of Processing: Effectiveness of Combined Untargeted and Targeted Approaches for Classification and Discrimination
This
study investigates chemical information of volatile fractions
of high-quality cocoa (<i>Theobroma cacao</i> L. Malvaceae)
from different origins (Mexico, Ecuador, Venezuela, Columbia, Java,
Trinidad, and Sao Tomè) produced for fine chocolate. This study
explores the evolution of the entire pattern of volatiles in relation
to cocoa processing (raw, roasted, steamed, and ground beans). Advanced
chemical fingerprinting (e.g., combined untargeted and targeted fingerprinting)
with comprehensive two-dimensional gas chromatography coupled with
mass spectrometry allows advanced pattern recognition for classification,
discrimination, and sensory-quality characterization. The entire data
set is analyzed for 595 reliable two-dimensional peak regions, including
130 known analytes and 13 potent odorants. Multivariate analysis with
unsupervised exploration (principal component analysis) and simple
supervised discrimination methods (Fisher ratios and linear regression
trees) reveal informative patterns of similarities and differences
and identify characteristic compounds related to sample origin and
manufacturing step
Alignment for Comprehensive Two-Dimensional Gas Chromatography with Dual Secondary Columns and Detectors
In each sample run, comprehensive
two-dimensional gas chromatography
with dual secondary columns and detectors (GC × 2GC) provides
complementary information in two chromatograms generated by its two
detectors. For example, a flame ionization detector (FID) produces
data that is especially effective for quantification and a mass spectrometer
(MS) produces data that is especially useful for chemical-structure
elucidation and compound identification. The greater information capacity
of two detectors is most useful for difficult analyses, such as metabolomics,
but using the joint information offered by the two complex two-dimensional
chromatograms requires data fusion. In the case that the second columns
are equivalent but flow conditions vary (e.g., related to the operative
pressure of their different detectors), data fusion can be accomplished
by aligning the chromatographic data and/or chromatographic features
such as peaks and retention-time windows. Chromatographic alignment
requires a mapping from the retention times of one chromatogram to
the retention times of the other chromatogram. This paper considers
general issues and experimental performance for global two-dimensional
mapping functions to align pairs of GC × 2GC chromatograms. Experimental
results for GC × 2GC with FID and MS for metabolomic analyses
of human urine samples suggest that low-degree polynomial mapping
functions out-perform affine transformation (as measured by root-mean-square
residuals for matched peaks) and achieve performance near a lower-bound
benchmark of inherent variability. Third-degree polynomials slightly
out-performed second-degree polynomials in these results, but second-degree
polynomials performed nearly as well and may be preferred for parametric
and computational simplicity as well as robustness