Theory of Analytical Chemistry

Application of quantitative chemometric analysis techniques to direct sampling mass spectrometry

This paper explores the use of direct sampling mass spectrometry coupled with multivariate chemometric analysis techniques for the analysis of sample mixtures containing analytes with similar mass spectra. Water samples containing varying mixtures of toluene, ethyl benzene, and cumene were analyzed by purge-and-trap/direct sampling mass spectrometry. Multivariate calibration models were built using partial least-squares regression (PLS), trilinear partial least-squares regression (tri-PLS), and parallel factor analysis (PARAFAC), with the latter two methods taking advantage of the differences in the temporal profiles of the analytes. The prediction errors for each model were compared to those obtained with simple univariate regression. Multivariate quantitative methods were found to be superior to univariate regression when a unique ion for quantitation could not be found. For prediction samples that contained unmodeled, interfering compounds, PARAFAC outperformed the other analysis methods. The uniqueness of the PARAFAC model allows for estimation of the mass spectra of the interfering compounds, which can be subsequently identified via visual inspection or a library search.

Relationships between (1)H NMR relaxation data and some technological parameters of meat: a chemometric approach

In this paper chemometrics (ANOVA and PCR) is used to measure unbiased correlations between NMR spin-echo decays of pork M. Longissimus dorsi obtained through Carr-Purcell-Meiboom-Gill (CPMG) experiments at low frequency (20 MHz) and the values of 14 technological parameters commonly used to assess pork meat quality. On the basis of the ANOVA results, it is also found that the CPMG decays of meat cannot be best interpreted with a "discrete" model (i.e., by expanding the decays in a series of a discrete number of exponential components, each with a different transverse relaxation time), but rather with a "continuous" model, by which a continuous distribution of T(2)'s is allowed. The latter model also agrees with literature histological results.

Resolution of overlapped peaks of amino acid derivatives in capillary electrophoresis using multivariate curve resolution based on alternating least squares

The application of chemometric techniques to the resolution of overlapped peaks in capillary electrophoresis (CE) is described. When a physical separation can not be completely accomplished, chemometrics might still resolve the determination of the analytes mathematically. CE with diode array detection can provide a large amount of data consisting of spectra registered over time. In this study, the capillary electrophoretic separation of 1,2-naphthoquinone-4-sulfonate derivatives of amino acids is studied. Most of the common amino acid derivatives can be separated at 30 kV in a fused-silica capillary by using a 40 mM sodium tetraborate + isopropanol (3:1 v/v) solution as background electrolyte. However, peaks of certain derivatives (Phe, His, Leu and Ile) still overlap. A multivariate curve resolution method based on an alternating least squares optimization procedure is used for the resolution of the overlapped electrophoretic peaks. The method takes advantage of spectral and electrophoretic differences of analytes to recover their pure electrophoretic and spectral profiles. In addition, each analyte in the mixture can be quantified using the corresponding standards.