Α stable isotope ratio mass spectrometer was used for stable isotope ratio (i.e., δ13C, δ18O, and δ2H) measurements, achieving geographical discrimination using orthogonal projections to latent structures discriminant analysis. A total of 100 Greek monovarietal olive oil samples from three different olive cultivars (cv. Koroneiki, cv. Lianolia Kerkyras, and cv. Maurolia), derived from Central Greece and Peloponnese, were collected during the 2019–2020 harvest year aiming to investigate the effect of botanical and geographical origin on their discrimination through isotopic data. The selection of these samples was made from traditionally olive-growing areas in which no significant research has been done so far. Samples were discriminated mainly by olive cultivar and, partially, by geographical origin, which is congruent with other authors. Based on this model, correct recognition of 93.75% in the training samples and correct prediction of 100% in the test set were achieved. The overall correct classification of the model was 91%. The predictability based on the externally validated method of discrimination was good (Q2 (cum)  =  0.681) and illustrated that δ18O and δ2H were the most important isotope markers for the discrimination of olive oil samples. The authenticity of olive oil based on the examined olive varieties can be determined using this technique.

Food adulteration is an issue of major concern, as numerous foodstuffs and beverages do not follow their labeling. Our research interest is in the field of authenticity of dairy products and particularly cheese. Adulteration of dairy products is a well‐known phenomenon, and there are numerous published studies specifically on the authenticity of cheese. In fact, substitution of a portion of fat and/or proteins, adulteration with milk of other species’ origin, and mislabeling of ingredients are some of the main issues that the science of dairy products’ authenticity is regularly facing. Discrimination of dairy products can be determined through several chemical or microbiological methods as presented in the literature. In addition, chemometric analysis is an important tool for interpretation of a huge load of measurements. The aim of this study is to discriminate between various milk samples, which is the primary ingredient of dairy products. Milk samples with different trademarks were analyzed. That data was combined with Halloumi cheese samples for chemometric discrimination of species’ origin. The innovative point of this study is the fact that it is the first time that a research study related to dairy products includes Halloumi cheese which is a traditional Cypriot cheese, not well‐studied until now. The first step of the methodology was the freeze‐drying via lyophilization of the samples. Fourier transformed infrared spectroscopy (FTIR) was chosen for their chemical characterization. Moreover, interpretation of the measurements was carried out by chemometric analysis using SIMCA software. For this study, FTIR data combined with chemometrics have given a very good discrimination of the samples according to their species’ origin. Chemometric methods such as PCA and OPLS‐DA have been used with great success. In the future, this model will be studied regarding geographical origin of the samples.

A limited number of substances are authorised for the treatment of bees. Maximum residue limits (MRLs) are set for tetracyclines in several matrices, but not for honey. Nevertheless, tetracycline antibiotics may be used in order to prevent bacterial diseases and the loss of honey bee populations. In this study, a sensitive multi-residue LC-MS/MS method was developed and optimised for the quantitative and qualitative determination of tetracycline residues in honey. Homogenisation of samples under acidic conditions was performed and solid-phase extraction was carried out. The eluate was evaporated under nitrogen and dissolved in an aqueous methanol solution prior to filtration. A mobile phase composed of acetic acid-water and acetic acid-acetonitrile was used. Separation of tetracycline, oxytetracycline, chlortetracycline and doxytetracycline was achieved by using gradient elution on a C18 chromatography column. The analytical method was validated according to Commission Decision 2002/657/EC by the analysis of spiked samples around the recommended concentration of 20 μg kg(-1) by EURL Guidance Paper, December 2007. A matrix effect was observed, so quantification was based on an external matrix calibration curve. Calculated decision limits (CCα) were lower than 10 μg kg(-1) for all tetracyclines. Good linearity, repeatability and within-laboratory reproducibility were achieved.

Cheddar and Kefalotyri cheese belong to the category of hard cheeses. Cheddar has an English origin, while Kefalotyri is a traditional cheese in Greece and a well-consumed dairy product in Cyprus. Discrimination of dairy products can be determined through several chemical methods. The aim of this study was to discriminate the samples of Cheddar and Kefalotyri cheese by analyzing various samples, from different brands. Two spectroscopic techniques namely proton nuclear magnetic resonance (1 H-NMR) and Fourier-transformed infrared (FTIR) spectroscopy were chosen in order to chemically characterise the samples. The first step of the methodology was the freeze-drying process for lyophilisation of the samples. The number of samples reached 28, including 14 Cheddar samples and 14 samples of Kefalotyri cheese. After that, measurements for each sample have been obtained by FTIR (% transmittance-wavenumber in cm-1) and 1 H-NMR (signal intensity-chemical shift in ppm) techniques. The data were analysed using SIMCA software. The proposed techniques along with chemometrics allow the discrimination of those two types of cheese. Both techniques employed are of significant importance, since they provide information about good classification of the samples when they are combined together. Interpretation of results and classification by using chemometric methods confirmed the different recipe of the two types of cheese. This study is the initial step of the future work. Future research will focus on discrimination based on the species' origin of milk of these and other cheese samples.

Major, minor and trace elements in wines from Greece were determined by inductively coupled plasma–mass spectrometry (ICP–MS). The concentrations of 44 elements (Na, Mg, P, K, Ca, Cu, Co, Cr, Zn, Sn, Fe, Mn, Li, Be, B, V, Sr, Ba, Al, Ag, Ni, As, Sn, Hg, Pb, Sb, Cd, Ti, Ga, Zr, Nb, Pd, Te, La, Sm, Ho, Tm, Yb, W, Os, Au, Tl, Th, U) in 90 white and red wines from six different regions in Greece for two consecutive vinification years, 2017 and 2018, were determined. Results for the elements aforementioned were evaluated by multivariate statistical methods, such as discriminant analysis and cluster analysis, and the wines were discriminated according to wine variety and geographical origin. Due to the specific choice of the analytes for multivariate statistical investigation, a prediction rate by cross-validation of 98% could be achieved. The aim of this study was not only to reveal specific relationships between the wine samples or between the chemical variables in order to classify the wines from different regions and varieties according to their elemental profile (wine authentication), but also to observe the annual fluctuation in the mineral content of the studied wine samples.

The selection and prioritization of pharmaceuticals and their transformation products for evaluating effects on the environment and human health is a challenging task. One common approach is based on compounds (e.g., mixture composition, concentrations), and another on biology (e.g., relevant endpoint, biological organizational level). Both of these approaches often resemble a Lernaean Hydra-they can create more questions than answers. The present study embraces this complexity, providing an integrated approach toward assessing the potential effects of transformation products of pharmaceuticals by means of mutagenicity, estrogenicity, and differences in the gene expression profiles. Mutagenicity using the tk kinase assay was applied to assess a list of 11 priority pharmaceuticals, namely, atenolol, azithromycin, carbamazepine, diclofenac, ibuprofen, erythromycin, metoprolol, ofloxacin, propranolol, sulfamethoxazole, and trimethoprim. The most mutagenic compounds were found to be β-blockers. In parallel, the photolabile pharmaceuticals were assessed for their mixture effects on mutagenicity (tk assay), estrogenicity (T47D- KBluc assay), and gene expression (microarrays). Interestingly, the mixtures were mutagenic at the µg/L level, indicating a synergistic effect. None of the photolysed mixtures were statistically significantly estrogenic. Gene expression profiling revealed effects related mainly to certain pathways, those of the p53 gene, mitogen-activated protein kinase, alanine, aspartate, and glutamate metabolism, and translation-related (spliceosome). Fourteen phototransformation products are proposed based on the m/z values found through ultra-performance liquid chromatography-tandem mass spectrometry analysis. The transformation routes of the photolysed mixtures indicate a strong similarity with those obtained for each pharmaceutical separately. This finding reinforces the view that transformation products are to be expected in naturally occurring mixtures. Environ Toxicol Chem 2016;35:2753-2764. © 2016 SETAC.

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The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing.