Sharif Digital Repository

In the present research, ultrasonic-assisted emulsification-microextraction (USAEME) coupled with gas chromatography-mass spectrometry (GC-MS) has been proposed for analysis of thirteen environmental protection agency (EPA) polycyclic aromatic hydrocarbons (PAHs) in aqueous samples. Tetrachloroethylene was selected as extraction solvent. The main parameters of USAEME affecting the efficiency of the method were modeled and optimized using a central composite design (CCD). Under the optimum conditions (9 μL for extraction solvent, 1.15% (w/v) NaCl (salt concentration) and 10min for ultrasonication time), preconcentration factor (PF) of the PAHs was in the range of 500-950. In order to have a... 

Multivariate curve resolution-alternating least squares (MCR-ALS) as a second-order calibration algorithm was proposed for the simultaneous analysis of eighteen fatty acid methyl esters (FAMEs) in a standard mixture and pomegranate seed sample using vortex-assisted extraction-dispersive liquid-liquid microextraction (VAE-DLLME), followed by gas chromatography-mass spectrometry (GC-MS). The chemometric resolution, identification and quantification of the target FAMEs in the standard mixture and real sample (i.e., the pomegranate seed) were carried out successfully in the presence of some uncalibrated interferences. The lack of fit (LOF) and reverse match factor (RMF) were used for the... 

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... 

In the present work, the abilities of five different variable selection methods including recursive partial least squares (rPLS), variable importance in projection (VIP), selectivity ratio (SR), significance multivariate correlation (sMC), and PLS loading weights were evaluated on the supervised classification of gas chromatographic fingerprints of saffron using PLS-discriminant analysis (PLS-DA). In this regard, eighty-three saffron samples analyzed by gas chromatography-flam ionization detector (GC-FID), were used as a case study. The GC-FID chromatograms of saffron samples were baseline corrected and aligned using asymmetric least squares (AsLS) and correlation optimized warping (COW)... 

In the present study, the profiling of 17 fatty acids (FAs) in avocado seed and pulp was investigated. The fatty acids were extracted with vortex-assisted extraction, methyl esterified and finally preconcentrated by dispersive liquid–liquid microextraction. The preconcentrated fatty acid methyl esters (FAMEs) were analyzed using gas chromatography–mass spectrometry (GC–MS) to obtain qualitative and quantitative information. The GC–MS data were analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) method to overcome general chromatographic problems such as overlapped peaks, background interference and peak shifts. The calibration data were prepared using pure... 

Chromatographic fingerprinting is an effective methodology for authentication and quality control of herbal products. In the presented study, a chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and multivariate pattern recognition methods was used to establish a gas chromatography-mass spectrometry (GC-MS) fingerprint of saffron. For this purpose, the volatile metabolites of 17 Iranian saffron samples, collected from different geographical regions, were determined using the combined method of ultrasound-assisted solvent extraction (UASE) and dispersive liquid-liquid microextraction (DLLME), coupled with GC-MS. The resolved elution profiles and... 

Gas chromatography-mass spectrometry (GC-MS) combined with Chemometric resolution techniques were proposed as a method for the analysis of volatile components of Iranian damask rose oil. The essential oil of damask rose was extracted using hydrodistillation method and analyzed with GC-MS in optimized conditions. A total of 70 components were identified using similarity searches between mass spectra and MS database. This number was extended to 95 components with concentrations higher than 0.01% accounting for 94.75% of the total relative content using Chemometric techniques. For the first time in this work, an approach based upon subspace comparison is used for determination of the chemical... 

A novel method for extraction and analysis of volatile compounds of Artemisia haussknechtii Boiss., using simultaneous hydro-distillation and static headspace liquid microextraction followed by gas chromatography-mass spectrometry (SHD-SHLPME-GCMS) is developed. SHLPME parameters including nature of extracting solvent, headspace volume and design, extraction time, sample weight and microdrop volume were optimized. Comparison of hydro-distillation gas chromatography-mass spectrometry and HD-SHLPME-GCMS showed that the latter method is fast, simple, inexpensive and effective for the analysis of volatile compounds of aromatic plants. By using this method, 56 compounds were extracted and... 

Gas chromatography-mass spectrometry combined with iterative and non-iterative resolution methods was used to characterize the essential oil components of Iranian cumin and caraway. Orthogonal projection resolution (OPR) as a non-iterative and distance-selection-multivariate curve resolution-alternative least squares (DS-MCR-ALS) as an iterative method were used as auxiliary means to the analysis in the case of overlapping peaks. A total of 19 and 39 components were identified by direct similarity searches for cumin and caraway oils, respectively. These numbers were extended to 49 and 98 components, respectively with the help of chemometric techniques. Major constituents in cumin are... 

The essential oil components of geranium oil cultivated in center of Iran were identified and determined using gas chromatography-mass spectrometry data combined with the chemometric resolution techniques. A total of 61 components accounting for 91.51% were identified using similarity searches between the mass spectra and MS database. This number was extended to 85 components using chemometric techniques. Various chemometric methods such as morphological scores, simplified Borgen method (SBM) and fixed size moving window evolving factor analysis (FSMWEFA) were used for determining the number of components, pure variables, zero concentration and selective regions. Then the overlapping peak... 

The components of Iranian spearmint essential oil were identified and quantified using gas chromatography-mass spectrometry (GC-MS) combined with chemometric tools. A multivariate curve resolution (MCR) approach was used to overcome the problems of background, baseline offset and overlapping/embedded peaks in GC-MS. The peaks were resolved using heuristic evolving latent projection (HELP) and multivariate curve resolution-alternating least squares (MCR-ALS) techniques. A new pure variable selection method named multivariate curve resolution-objective function equal to zero (MCR-FEQZ) is introduced and was applied in this work. The performance of this technique was evaluated and confirmed... 

This paper focuses on characterization of the components of Iranian rosemary essential oil using gas chromatography-mass spectrometry (GC-MS). Multivariate curve resolution (MCR) approach was used to overcome the problem of background, baseline offset and overlapping/embedded peaks in GC-MS. The analysis of GC-MS data revealed that sixty eight components exist in the rosemary essential oil. However, with the help of MCR this number was extended to ninety nine components with concentrations higher than 0.01%, which accounts for 98.23% of the total relative content of the rosemary essential oil. The most important constituents of the Iranian rosemary are 1,8-cineole (23.47%), α-pinene... 

In analysis of complex natural matrices by gas chromatography-mass spectrometry (GC-MS), many disturbing factors such as baseline drift, spectral background, homoscedastic and heteroscedastic noise, peak shape deformation (non-Gaussian peaks), low S/N ratio and co-elution (overlapped and/or embedded peaks) lead the researchers to handle them to serve time, money and experimental efforts. This study aimed to improve the GC-MS analysis of complex natural matrices utilizing multivariate curve resolution (MCR) methods. In addition, to assess the peak purity of the two-dimensional data, a method called variable size moving window-evolving factor analysis (VSMW-EFA) is introduced and examined. The... 

Dispersive liquid-liquid microextraction (DLLME) coupled with gas chromatography-mass spectrometry-selective ion monitoring (GC-MS-SIM) was applied to the determination of methyl tert-butyl ether (MTBE) in water samples. The effect of main parameters affecting the extraction efficiency was studied simultaneously. From selected parameters, volume of extraction solvent, volume of dispersive solvent, and salt concentration were optimized by means of experimental design. The statistical parameters of the derived model were R 2=0.9987 and F=17.83. The optimal conditions were 42.0μL for extraction solvent, 0.30mL for disperser solvent and 5% (w/v) for sodium chloride. The calibration linear range... 

Multivariate curve resolution (MCR) and multivariate clustering methods along with other chemometric methods are proposed to improve the analysis of gas chromatography-mass spectrometry (GC-MS) fingerprints of secondary metabolites in citrus fruits peels. In this way, chromatographic problems such as baseline/background contribution, low S/N peaks, asymmetric peaks, retention time shifts, and co-elution (overlapped and embedded peaks) occurred during GC-MS analysis of chromatographic fingerprints are solved using the proposed strategy. In this study, first, informative GC-MS fingerprints of citrus secondary metabolites are generated and then, whole data sets are segmented to some... 

In the present study, multivariate analytical figures of merit (AFOM) for three well-known second-order calibration algorithms, parallel factor analysis (PARAFAC), PARAFAC2 and multivariate curve resolution-alternating least squares (MCR-ALS), were investigated in simulated hyphenated chromatographic systems including different artifacts (e.g., noise and peak shifts). Different two- and three-component systems with interferences were simulated. Resolved profiles from the target components were used to build calibration curves and to calculate the multivariate AFOMs, sensitivity (SEN), analytical sensitivity (γ), selectivity (SEL) and limit of detection (LOD). The obtained AFOMs for different...