Characterization of the volatile profile of thistle honey using headspace solid-phase microextraction and gas chromatography-mass spectrometry.

In this study, a headspace solid-phase microextraction method was developed for the characterization of the volatile fraction of thistle honey and compared with a dynamic headspace extraction method. A DVB/CAR/PDMS fibre was used. The effects of extraction time, equilibration time and salt addition on extraction yield were evaluated. The volatile fraction of seven Italian thistle honey samples was extracted under the optimized conditions and analyzed by gas chromatography-mass spectrometry. Characterization of the volatile profile was performed in terms of nature and relative amount of the extracted compounds. A total of 40 compounds, belonging to different chemical classes, were identified. The relative amounts of 16 compounds found in all the analyzed thistle honeys, i.e. nonanal, furfural, decanal, 3,6-dimethyl-2,3,3a,4,5,7a-hexahydrobenzofuran, benzaldehyde, α-linalool, lilac aldehyde (isomer IV), hotrienol, phenylacetaldehyde, 4-oxoisophorone, benzyl alcohol, 2-phenylethanol, a not identified compound, octanoic acid, nonanoic acid and methyl anthranilate, were calculated and submitted to statistical analysis, in order to define for each compound a typical range. On the basis of the obtained data, a characteristic set of values was defined for thistle honey volatile fingerprint. The developed model proved to be effective in recognizing the botanical origin of thistle honey.

A novel headspace solid-phase microextraction method using in situ derivatization and a diethoxydiphenylsilane fibre for the gas chromatography-mass spectrometry determination of urinary hydroxy polycyclic aromatic hydrocarbons.

An innovative and simple headspace solid-phase microextraction method using a novel diethoxydiphenylsilane fibre based on in situ derivatization with acetic anhydride was optimized and validated for the gas chromatography-mass spectrometry determination of some monohydroxy metabolites of polycyclic aromatic hydrocarbons, namely 1-hydroxynaphthalene, 2-hydroxynaphtalene, 9-hydroxyfluorene, 2-hydroxyfluorene and 1-hydroxypyrene at trace levels in human urine. Enzymatic hydrolysis was applied before derivatization, whereas extraction conditions, i.e. the effects of time and temperature of extraction and salt addition were investigated by experimental design. Regression models and desirability functions were applied to find the experimental conditions providing the highest global extraction response. These conditions were found in correspondence of an extraction temperature of 90 degrees C, an extraction time of 90 min and 25% NaCl added to urine samples. The capabilities of the developed method were proved obtaining limit of quantitations in the 0.1-2 microg/l range, thus allowing the bio-monitoring of these compounds in human urine. A good precision was observed both in terms of intra-batch and inter-batch repeatability with RSD always lower than 14%. Recoveries ranging from 98(+/-3) to 121(+/-1)% and extraction yields higher than 72% were also obtained. Finally, the analysis of urine specimens of coke-oven workers revealed analytes' concentrations in the 2.2-164 microg/l range, proving the exposure to PAHs of the involved workers.

Differentiation of the volatile profile of microbiologically contaminated canned tomatoes by dynamic headspace extraction followed by gas chromatography-mass spectrometry analysis.

The aromatic profile of microbiologically contaminated canned tomatoes was analyzed by the dynamic headspace extraction technique coupled with gas chromatography-mass spectrometry. Canned tomatoes contaminated with Escherichia coli, Saccharomyces cerevisiae and Aspergillus carbonarius were analyzed after 2 and 7 days. About 100 volatiles were detected, among which alcohols, aldehydes and ketones were the most abundant compounds. Gas chromatographic peak areas were used for statistical purposes. First, principal component analysis was carried out in order to visualize data trends and clusters. Then, linear discriminant analysis was performed in order to detect the set of volatile compounds ables to differentiate groups of analyzed samples. Five volatile compounds, i.e. ethanol, beta-myrcene, o-methyl styrene, 6-methyl-5-hepten-2-ol and 1-octanol, were found to be able to better discriminate between uncontaminated and contaminated samples. Prediction ability of the calculated model was estimated to be 100% by the "leave-one-out" cross-validation. An electronic nose device was then used to analyze the same contaminated and not contaminated canned tomato samples. Preliminary results were compared with those obtained by dynamic headspace gas chromatography-mass spectrometry, showing a good agreement.