Loading...

Towards obtaining more information from gas chromatography-mass spectrometric data of essential oils: An overview of mean field independent component analysis

Jalali Heravi, M ; Sharif University of Technology | 2010

2367 Viewed
  1. Type of Document: Article
  2. DOI: 10.1016/j.chroma.2010.05.026
  3. Publisher: 2010
  4. Abstract:
  5. Mean field independent component analysis (MF-ICA) along with other chemometric techniques was proposed for obtaining more information from multi-component gas chromatographic-mass spectrometric (GC-MS) signals of essential oils (mandarin and lemon as examples). Using these techniques, some fundamental problems during the GC-MS analysis of essential oils such as varying baseline, presence of different types of noise and co-elution have been solved. The parameters affecting MF-ICA algorithm were screened using a 25 factorial design. The optimum conditions for MF-ICA algorithm were followed by deconvolution of complex GC-MS peak clusters. The number of independent components (ICs) (chemical constituents) in each peak cluster was estimated using morphological score method. Eigenvalue profiles of evolving factor analysis (EFA) and pure variables from orthogonal projection approach (OPA) were used as initial mixing matrix (chromatograms) in iterative process. The resolved mass spectra were satisfactorily identified using NIST mass spectral search system. Finally, the results of optimized MF-ICA were compared with those obtained using multivariate curve resolution-alternating least square (MCR-ALS), multivariate curve resolution-objective function minimization (MCR-FMIN) and heuristic evolving latent projection (HELP) methods. It is demonstrated that MF-ICA can be used as an alternative method for a quick and accurate analysis of real multi-component problematic systems such as essential oils
  6. Keywords:
  7. Mean field independent component analysis ; Accurate analysis ; Alternative methods ; Chemical constituents ; Chemometrices ; Chemometrics ; Eigen-value ; Evolving factor analysis ; Factorial design ; Fundamental problem ; Gas chromatography-mass spectrometry ; GC-MS analysis ; Heuristic evolving latent projections ; ICA algorithms ; Independent components ; Iterative process ; Mass spectra ; Mass spectral ; Mass spectrometric data ; Mean field ; Mixing matrix ; Multicomponents ; Multivariate curve resolution ; Multivariate curve resolution-alternating least squares ; Objective functions ; Optimum conditions ; Orthogonal projection approaches ; Peak clusters ; Chromatographic analysis ; Curve fitting ; Eigenvalues and eigenfunctions ; Essential oils ; Gas chromatography ; Gas oils ; Hemodynamics ; Heuristic methods ; Mass spectrometers ; Mass spectrometry ; Multivariant analysis ; Optimization ; Independent component analysis ; Essential oil ; Accuracy ; Algorithm ; controlled study ; Elution ; Extraction ; Information processing ; Intermethod comparison ; Lemon ; Mandarin ; Mass fragmentography ; Priority journal ; Process optimization ; Scoring system ; Algorithms ; Data Interpretation, Statistical ; Oils, Volatile ; Plant Oils ; Citrus limon
  8. Source: Journal of Chromatography A ; Volume 1217, Issue 29 , 2010 , Pages 4850-4861 ; 00219673 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0021967310006783