Towards the solution of the eluent elimination problem in high-performance liquid chromatography–infrared spectroscopy measurements by chemometric methods

Simultaneous chemiluminescence determination of citric acid and oxalic acid using multi-way partial least squares regression

A novel kinetic chemiluminescent method proposed for the simultaneous determination of oxalic acid and citric acid in their mixtures.

Plant metabolomics: resolution and quantification of elusive peaks in liquid chromatography-mass spectrometry profiles of complex plant extracts using multi-way decomposition methods

Previous studies on LC-MS metabolomic profiling of 127 F2 Barbarea vulgaris plants derived from a cross of parental glabrous (G) and pubescent (P) type, revealed four triterpenoid saponins (hederagenin cellobioside, oleanolic acid cellobioside, epihederagenin cellobioside, and gypsogenin cellobioside) that correlated with resistance of plants against the insect herbivore, Phyllotreta nemorum. In this study, for the first time, we demonstrate the efficiency of the multi-way decomposition method PARAllel FACtor analysis 2 (PARAFAC2) for exploring complex LC-MS data. PARAFAC2 enabled automated resolution and quantification of several elusive chromatographic peaks (e.g. overlapped, elution time shifted and low s/n ratio), which could not be detected and quantified by conventional chromatographic data analysis. Raw LC-MS data of 127 F2 B. vulgaris plants were arranged in a three-way array (elution time point×mass spectra×samples), divided into 17 different chromatographic intervals and each interval were individually modeled by PARAFAC2. Three main outputs of the PARAFAC2 models described: (1) elution time profile, (2) relative abundance, and (3) pure mass spectra of the resolved peaks modeled from each interval of the chromatographic data. PARAFAC2 scores corresponding to relative abundances of the resolved peaks were extracted and further used for correlation and partial least squares (PLS) analysis. A total of 71 PARAFAC2 components (which correspond to actual peaks, baselines and tails of neighboring peaks) were modeled from 17 different chromatographic retention time intervals of the LC-MS data. In addition to four previously known saponins, correlation- and PLS-analysis resolved five unknown saponin-like compounds that were significantly correlated with insect resistance. The method also enabled a good separation between resistant and susceptible F2 plants. PARAFAC2 spectral loadings corresponding to the pure mass spectra of chromatographic peaks matched well with experimentally recorded mass spectra (correlation based similarity >95%). This enabled to extract pure mass spectra of highly overlapped and low s/n ratio peaks.

Procedure for automated background correction in flow systems with infrared spectroscopic detection and changing liquid-phase composition

This paper describes a partial least squares (PLS) based automatic procedure to correct for changes in the spectral contribution of the solvent or solvent mixtures from solute spectra recorded in these solvents. The procedure was developed for successful on-line Fourier transform infrared (FT-IR) detection in gradient high-performance liquid chromatography (HPLC) separations. It requires a reference FT-IR data set containing all possible combinations of the expected variation in solvent composition. Furthermore, a spectral region (A) in these spectra is required where the solvents show absorption but the analytes do not. This is the case for the system ACN:H(2)O, an often-applied solvent mixture in gradient HPLC, in the spectral region from 2300-2400 cm(-1). By focusing on (A) the developed numerical method selects an appropriate background spectrum from the reference data set, which is then subtracted from the analyte spectra. The method was programmed in Matlab and tested on different isocratic and gradient on-line reversed phase liquid chromatography-Fourier transform infrared spectrometry (LC-FT-IR) data sets. This work describes a successful method to perform eluent correction in on-line coupling of FT-IR spectrometry with gradient LC.

Quantitative determination in chromatographic analysis based on n-way calibration strategies

Chemometric techniques for calibration with three-way signals are sufficiently developed for their use in routine analysis. The advantage of the second order property (the possibility of quantifying an analyte in the presence of interferents) together with the guarantee of the uniqueness of the decomposition, what means to extract the signal corresponding only to the analyte of interest, make these calibration techniques especially useful for the quantification and identification of analytes in complex samples. This has a particular interest in the identification and quantification of banned substances or substances with a specified maximum limit. The paper describes the theory of the calibration methodology in relation to the signal order and then focuses the analysis on the three-way techniques commonly used in calibration: n-way partial least squares, multivariate curve resolution and parallel factor analysis. The figures of merit needed for the accreditation of analytical methods are analyzed from the viewpoint of n-way calibrations in chromatography.