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Seventy authentic honey samples of 9 different floral types (rhododendron, chestnut, honeydew, Anzer (thymus spp.), eucalyptus, gossypium, citrus, sunflower, and multifloral) from 15 different geographical regions of Turkey were analyzed for their chemical composition and for indicators of botanical and geographical origin. The profiles of free amino acids, oligosaccharides, and volatile components together with water activity were determined to characterize chemical composition. The microscopic analysis of honey sediment (mellissopalynology) was carried out to identify and count the pollen to provide qualitative indicators to confirm botanical origin. Statistical analysis was undertaken using a bespoke toolbox for Matlab called Metabolab. Discriminant analysis was undertaken using partial least-squares (PLS) regression followed by linear discriminant analysis (LDA). Four data models were constructed and validated. Model 1 used 51 variables to predict the floral origin of the honey samples. This model was also used to identify the top 5 variable important of projection (VIP) scores, selecting those variables that most significantly affected the PLS-LDA calculation. These data related to the phthalic acid, 2-methylheptanoic acid, raffinose, maltose, and sucrose. Data from these compounds were remodeled using PLS-LDA. Model 2 used only the volatiles data, model 3 the sugars data, and model 4 the amino acids data. The combined data set allowed the floral origin of Turkish honey to be accurately predicted and thus provides a useful tool for authentication purposes. However, using variable selection techniques a smaller subset of analytes have been identified that have the capability of classifying Turkish honey according to floral type with a similar level of accuracy.

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An improved analytical method for the rapid, reliable, and sensitive determination of hydroxymethylfurfural (HMF) in baby foods is described. It entailed aqueous extraction from food matrix with simultaneous clarification using Carrez I and II reagents, solid-phase extraction cleanup using Oasis HLB, and analysis by liquid chromatography-mass spectrometry. A narrow-bore column allowed fast chromatographic separation with good resolution of HMF and matrix coextractives. In positive atmospheric pressure chemical ionization conditions, precursor and compound-specific ions were sensitively detected in selected ion monitoring mode. Sample preparation with efficient cleanup followed by fast chromatographic analysis allowed the analysis to be completed in <20 min. Recovery ranged between 91.8 and 94.7% for spiking levels of 0.25, 1.0, and 5.0 mg/kg HMF in cereal-based baby foods. The method was shown to be successful when using liquid chromatography coupled to ultraviolet detection at 285 nm.

An improved analytical method for the determination of acrylamide in coffee is described using liquid chromatography coupled to mass spectrometric detection (LC-MS). A variety of instant, ground and laboratory roasted coffee samples were analysed using this method. The sample preparation entails extraction of acrylamide with methanol, purification with Carrez I and II solutions, evaporation and solvent change to water, and clean-up with an Oasis HLB solid-phase extraction (SPE) cartridge. The chromatographic conditions allowed separation of acrylamide and the remaining matrix co-extractives with accurate and precise quantification of acrylamide during MS detection in SIM mode. Recoveries for the spiking levels of 50, 100, 250 and 500?microg/kg ranged between 99 and 100% with relative standard deviations of less than 2%. The effects of roasting on the formation of acrylamide and colour development were also investigated at 150, 200 and 225 degrees C. Change in the CIE (Commission Internationale de l'Eclairage) a* colour value was found to show a good correlation with the change in acrylamide. CIE a* and acrylamide data was fitted to a non-linear logarithmic function for the estimation of acrylamide level in coffee. Measured acrylamide levels in commercial roasted coffees compared well with the predicted acrylamide levels from the CIE a* values.