Giorgio Calabrese

Determination of perfluorochemicals in biological, environmental and food samples by an automated on-line solid phase extraction ultra high performance liquid chromatography tandem mass spectrometry method

A rapid on-line solid phase extraction ultra high performance liquid chromatography tandem mass spectrometry method was developed for the identification and quantitation of nine perfluorinated compounds in matrices of environmental, biological and food interest. Pre-treatment, solid phase extraction, chromatographic and mass detection conditions were optimised, in order to apply the whole methodology to the analysis of different matrices. Particular attention was devoted to the evaluation of matrix effect and the correlated phenomena of ion enhancement or suppression in mass spectrometry detection. LOD and LOQ range from 3 to 15ngL(-1) and from 10 to 50ngL(-1), respectively. Method detection limits (MDLs) were also calculated for each kind of matrix. The recovery, evaluated for each analyte, does not depend on analyte concentration in the explored concentration range: average R¯% values are always greater than 82.9%. In the whole, the results obtained for samples of river waters, blood serum, blood plasma, and fish confirm the ubiquitous presence of perfluorinated compounds, as recently denounced by many sources.

Simultaneous determination of thirteen polycyclic aromatic hydrocarbons and twelve aldehydes in cooked food by an automated on-line solid phase extraction ultra high performance liquid chromatography tandem mass spectrometry.

An on-line solid phase extraction (SPE) ultra high performance liquid chromatography tandem mass spectrometry method has been developed for the simultaneous identification and determination of thirteen polycyclic aromatic hydrocarbons (PAHs) and twelve aldehydes (derivatized with 2,4-dinitrophenylhydrazine). The chromatographic conditions have been optimized to obtain the maximum of sensitivity and resolution taking into account the different retention interactions and the different ionization conditions of PAHs and derivatized aldehydes. LOD values ranging from 0.028 to 0.768 μg L(-1) for PAHs and from 0.002 to 0.125 μg L(-1) for aldehydes were obtained. The resolution permitted the separation of four couples of PAH isomers. Sample pre-treatment and SPE were optimized in order to apply the whole methodology to the analysis of different food matrices as salmon, frankfurter, steak, and pork chop, subjected to different cooking modes (smoked, grilled, cooked in oil or in butter). Particular attention was devoted to the evaluation of matrix effect that was significantly reduced through the on-line SPE treatment. For each food matrix the method detection limits, the method quantitation limits, and the recovery R were evaluated. R was shown not to depend on analyte concentration in the explored concentration range (LOQ - 50.000 μg L(-1)): the average R percent ranges from 70.6% to 120.0%.

Non-target screening of Allura Red AC photodegradation products in a beverage through ultra high performance liquid chromatography coupled with hybrid triple quadrupole/linear ion trap mass spectrometry.

The study deals with the identification of the degradation products formed by simulated sunlight photoirradiation in a commercial beverage that contains Allura Red AC dye. An UHPLC-MS/MS method, that makes use of hybrid triple quadrupole/linear ion trap, was developed. In the identification step the software tool information dependent acquisition (IDA) was used to automatically obtain information about the species present and to build a multiple reaction monitoring (MRM) method with the MS/MS fragmentation pattern of the species considered. The results indicate that the identified degradation products are formed from side-reactions and/or interactions among the dye and other ingredients present in the beverage (ascorbic acid, citric acid, sucrose, aromas, strawberry juice, and extract of chamomile flowers). The presence of aromatic amine or amide functionalities in the chemical structures proposed for the degradation products might suggest potential hazards to consumer health.

Identification of photodegradation products of Allura Red AC (E129) in a beverage by ultra high performance liquid chromatography–quadrupole-time-of-flight mass spectrometry

The study deals with the identification of the degradation products formed by simulated sunlight photoirradiation in a beverage that contains Allura Red AC (E129) dye. An UHPLC-MS/MS method that makes use of high resolution quadrupole-time-of-flight mass spectrometer, was developed. For the identification of the degradation products the software tool Information Dependent Acquisition (IDA) was used to automatically obtain information about the high resolution MS and MS/MS spectra of the species present. Accurate mass data were essential for the identification of the appropriate elemental composition: the elucidation of unknown chemical structures was obtained by using powerful software to mine the recorded chromatogram. The identified degradation products are formed from side-reactions and/or from the interactions taking place among the dye and other ingredients present in the beverage (i.e. ascorbic acid, citric acid, sucrose, aromas, strawberry juice and extract of chamomile flowers). The presence of aromatic amine or amide groups in the chemical structures of the degradation products suggests the potential hazard for the consumer health.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

GENOCOP algorithm and hierarchical grid transformation for image warping of two dimensional gel eletrophoretic maps

Hierarchical grid transformation is a powerful approach to SDS 2DPAGE maps warping. The hierarchy of the warping transformation is able to model both global and local deformations of the gels and the algorithm can be stopped when a certain degree of accuracy in the image alignment is obtained. The numerical optimization of the position of the nodes of the grid that are responsible for the image warping is a multivariate task that can be solved efficiently using Genetic Algorithms. The use of Genetic Algorithms ensures that an optimal position of the nodes can be defined with a low computational cost with respect to other methods. The optimal positions of the nodes of the grid can be successfully used for defining a good warping of the gels.

Optimization of the Extraction of the Volatile Fraction from Honey Samples by SPME-GC-MS, Experimental Design, and Multivariate Target Functions

Head space (HS) solid phase microextraction (SPME) followed by gas chromatography with mass spectrometry detection (GC-MS) is the most widespread technique to study the volatile profile of honey samples. In this paper, the experimental SPME conditions were optimized by a multivariate strategy. Both sensitivity and repeatability were optimized by experimental design techniques considering three factors: extraction temperature (from 50°C to 70°C), time of exposition of the fiber (from 20 min to 60 min), and amount of salt added (from 0 to 27.50%). Each experiment was evaluated by Principal Component Analysis (PCA) that allows to take into consideration all the analytes at the same time, preserving the information about their different characteristics. Optimal extraction conditions were identified independently for signal intensity (extraction temperature: 70°C; extraction time: 60 min; salt percentage: 27.50% w/w) and repeatability (extraction temperature: 50°C; extraction time: 60 min; salt percentage: 27.50% w/w) and a final global compromise (extraction temperature: 70°C; extraction time: 60 min; salt percentage: 27.50% w/w) was also reached. Considerations about the choice of the best internal standards were also drawn. The whole optimized procedure was than applied to the analysis of a multiflower honey sample and more than 100 compounds were identified.

Chemical profiling and multivariate data fusion methods for the identification of the botanical origin of honey

The characterization of 72 Italian honey samples from 8 botanical varieties was carried out by a comprehensive approach exploiting data fusion of IR, NIR and Raman spectroscopies, Proton Transfer Reaction - Time of Flight - Mass Spectrometry (PTR-MS) and electronic nose. High-, mid- and low-level data fusion approaches were tested to verify if the combination of several analytical sources can improve the classification ability of honeys from different botanical origins. Classification was performed on the fused data by Partial Least Squares - Discriminant Analysis; a strict validation protocol was used to estimate the predictive performances of the models. The best results were obtained with high-level data fusion combining Raman and NIR spectroscopy and PTR-MS, with classification performances better than those obtained on single analytical sources (accuracy of 99% and 100% on test and training samples respectively). The combination of just three analytical sources assures a limited time of analysis.