Hamide Senyuva

Quantitative multi-residue method for determination antibiotics in chicken meat using turbulent flow chromatography coupled to liquid chromatography–tandem mass spectrometry

A multi-class method for identification and quantification of 36 antibiotics from seven different chemical classes (aminoglycosides, macrolides, lincosamides, sulfonamides, tetracyclines, quinolones and trimethoprim) has been developed by using liquid chromatography-mass spectrometry. The method was optimised for detection of antibiotics in chicken meat. Sample preparation including extraction with a mixture of acetonitrile:2% trichloroacetic acid (45:55, v/v), centrifugation and filtration was followed by on-line clean-up using turbulent flow chromatography. Using this automated on-line technique enabled a larger number of samples to be analysed per day than with a traditional clean-up technique (e.g. solid phase extraction). The optimised method was validated according to the European Commission Directive 2002/657/EC. In-house validation was performed by fortifying the blank matrix at three levels 0.5, 1.0 and 1.5 MRL (maximum residue limit), or respectively, at concentrations as low as possible for substances without an MRL. Precision in terms of repeatability standard deviation ranged from 3 to 28% and recovery values were between 80 and 120% in most cases. All calculated validation parameters including CCα and CCβ were in the compliance with the legislative requirements.

Profiling Turkish Honeys to Determine Authenticity Using Physical and Chemical Characteristics

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.

Changes in Free Amino Acid and Sugar Levels of Dried Figs during Aflatoxin B1 Production by Aspergillus flavus and Aspergillus parasiticus

An aqueous slurry of gamma-irradiated sterilized dried figs was inoculated with toxigenic strains of Aspergillus flavus and Aspergillus parasiticus. During incubation at 28 degrees C, pH, fructose, glucose, and free amino acids were determined by high-performance liquid chromatography and liquid chromatography (LC)/mass spectrometry, respectively, over 13 time points (1-20 days). At the same 13 time points using a LC/time-of-flight mass spectrometry screening method, aflatoxin B 1 and other secondary metabolites were simultaneously monitored. During the course of incubation, the pH significantly decreased and aflatoxin B 1 formation correlated with a reduction in proline content for both fungi. Of the 22 free amino acids that were monitored, only proline and cystine were found to be critical in supporting aflatoxin production. Levels of fructose and glucose steadily declined during incubation, until glucose was almost exhausted after 21 days. These time-course experiments confirmed the need for carbon and nitrogen sources for aflatoxin production in dried figs, and the favorable composition of figs as a fungal growth medium.

Determination of Ochratoxin A in Black and White Pepper, Nutmeg, Spice Mix, Cocoa, and Drinking Chocolate by High-Performance Liquid Chromatography Coupled with Fluorescence Detection: Collaborative Study

A method validation study for the determination of ochratoxin A in black and white pepper (Piper spp.), nutmeg (Myristica fragrans), spice mix (blend of ginger, turmeric, pepper, nutmeg, and chili), cocoa powder, and drinking chocolate was conducted according to the International Harmonized Protocol of the International Union of Pure and Applied Chemistry. The method is based on the extraction of samples with aqueous methanol, followed by a cleanup of the extract with an immunoaffinity column. The determination is carried out by reversed-phase LC coupled with a fluorescence detector. The study involved 25 participants representing a cross-section of research, private, and official control laboratories from 12 European Union (EU) Member States, together with Turkey and Macedonia. Mean recoveries ranged from 71 to 85% for spices and from 85 to 88% for cocoa and drinking chocolate. The RSDr values ranged from 5.6 to 16.7% for spices and from 4.5 to 18.7% for cocoa and drinking chocolate. The RSDR values ranged from 9.5 to 22.6% for spices and from 13.7 to 30.7% for cocoa and drinking chocolate. The resulting Horwitz ratios ranged from 0.4 to 1 for spices and from 0.6 to 1.4 for cocoa and drinking chocolate according to the Horwitz function modified by Thompson. The method showed acceptable within-laboratory and between-laboratory precision for each matrix, and it conforms to requirements set by current EU legislation.