Oregano is native to the Mediterranean region and it has been reported to contain several phenolic compounds particularly flavonoids that have been related with multiple bioactivities towards certain diseases. Oregano is cultivated in the island of Lemnos where the climate promotes its growth and thus it could be further used in promoting local economy. The aim of the present study was to establish a methodology for the extraction of total phenolic content along with the antioxidant capacity of oregano by using response surface methodology. A Box–Behnken design was applied to optimize the extraction conditions with regard to the extraction time, temperature, and solvent mixture with the use of ultrasound-assisted extraction. For the optimized extracts, identification of the most abundant flavonoids (luteolin, kaempferol, and apigenin) was performed with an analytical HPLC-PDA and UPLC-Q-TOF MS methodology. The predicted optimal conditions of the statistical model were identified, and the predicted values confirmed. The linear factors evaluated, temperature, time, and ethanol concentration, all showed significant effect (p < 0.05), and the regression coefficient (R²) presented a good correlation between predicted and experimental data. Actual values under optimum conditions were 362.1 ± 1.8 and 108.6 ± 0.9 mg/g dry oregano with regard to total phenolic content and antioxidant activity based on 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assay, respectively. Additionally, further antioxidant activities by 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) (115.2 ± 1.2 mg/g dry oregano), Ferric Reducing Antioxidant Power (FRAP) (13.7 ± 0.8 mg/g dry oregano), and Cupric Reducing Antioxidant Capacity (CUPRAC) (1.2 ± 0.2 mg/g dry oregano) assays were performed for the optimized extract. The extract acquired under the optimum conditions contain an adequate quantity of phenolic compounds that could be used in the production of functional foods by food enrichment procedure.

The national infrastructure FoodOmicsGR_RI coordinates research efforts from eight Greek Universities and Research Centers in a network aiming to support research and development (R&D) in the agri-food sector. The goals of FoodOmicsGR_RI are the comprehensive in-depth characterization of foods using cutting-edge omics technologies and the support of dietary/nutrition studies. The network combines strong omics expertise with expert field/application scientists (food/nutrition sciences, plant protection/plant growth, animal husbandry, apiculture and 10 other fields). Human resources involve more than 60 staff scientists and more than 30 recruits. State-of-the-art technologies and instrumentation is available for the comprehensive mapping of the food composition and available genetic resources, the assessment of the distinct value of foods, and the effect of nutritional intervention on the metabolic profile of biological samples of consumers and animal models. The consortium has the know-how and expertise that covers the breadth of the Greek agri-food sector. Metabolomics teams have developed and implemented a variety of methods for profiling and quantitative analysis. The implementation plan includes the following research axes: development of a detailed database of Greek food constituents; exploitation of “omics” technologies to assess domestic agricultural biodiversity aiding authenticity-traceability control/certification of geographical/genetic origin; highlighting unique characteristics of Greek products with an emphasis on quality, sustainability and food safety; assessment of diet’s effect on health and well-being; creating added value from agri-food waste. FoodOmicsGR_RI develops new tools to evaluate the nutritional value of Greek foods, study the role of traditional foods and Greek functional foods in the prevention of chronic diseases and support health claims of Greek traditional products. FoodOmicsGR_RI provides access to state-of-the-art facilities, unique, well-characterised sample sets, obtained from precision/experimental farming/breeding (milk, honey, meat, olive oil and so forth) along with more than 20 complementary scientific disciplines. FoodOmicsGR_RI is open for collaboration with national and international stakeholders.

Petroselinum crispum is native to the Mediterranean region and has been reported to contain several phenolic compounds in addition to the highest quantity of apigenin among several natural raw materials. The aim of the present study was to establish an extraction method for the most abundant phenolic compounds of Petroselinum crispum leaves by using response surface methodology. A Box–Behnken design was applied to optimize the extraction conditions with regards to the extraction time, temperature, solvent mixture, and sample to solvent ratio with the use of ultrasound-assisted extraction. An analytical HPLC-PDA methodology was developed to accurately quantify the phenolic compounds in the extracts. Identification of the most abundant phenolic compounds (luteolin, caffeic acid, and apigenin) was also performed with an UPLC-Q-TOF MS methodology. The predicted optimal conditions of the statistical model were identified, and the predicted values confirmed. Actual values of 23.92 ± 1.86 with 100 mL/g, 40% ethanol, 70 °C and 40 min, 19.10 ± 0.75 with 20 mL/g, 0% ethanol, 70 °C and 40 min, and 25.29 ± 1.82 μg/g dry parsley with and 100 mL/g, 0% ethanol, 25 °C and 40 min of luteolin, caffeic acid, and apigenin respectively, were estimated. Total phenolic content and antioxidant activities by DPPH, ABTS, FRAP, and CUPRAC assays were performed for the extracts. The extracts acquired under the optimum conditions contain an adequate quantity of phenolic compounds that could be used in the production of functional foods by food enrichment prcedure.

The purpose of this study was to examine the effects of two different feeding systems, a control or a flaxseed and lupin diet (experimental), for a sheep flock, on the microbiota and metabolome of Kefalograviera cheese samples produced by their milk. In particular, the microbiota present in Kefalograviera cheese samples was analyzed using 16S rRNA gene sequencing, while ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) was applied to investigate the chemical profile of the cheeses, considering the different feeding systems applied. The metagenomic profile was found to be altered by the experimental feeding system and significantly correlated to specific cheese metabolites, with Streptococcaceae and Lactobacillaceae establishing positive and negative correlations with the discriminant metabolites. Overall, more than 120 features were annotated and identified with high confidence level across the samples while most of them belonged to specific chemical classes. Characteristic analytes detected in different concentrations in the experimental cheese samples including arabinose, dulcitol, hypoxanthine, itaconic acid, L-arginine, L-glutamine and succinic acid. Therefore, taken together, our results provide an extensive foodomics approach for Kefalograviera cheese samples from different feeding regimes, investigating the metabolomic and metagenomic biomarkers that could be used to foresee, improve, and control cheese ripening outcomes, demonstrating the quality of the experimental Kefalograviera cheese.

The popularity of Greek-style yogurt (made from cow, ewe, and goat milk) has grown significantly in recent years thanks to its high protein content, nutritional value, and unique creamy texture, making it vulnerable to illegal practices, such as adulteration. In the present work, a fast and reliable matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based methodology was developed for the detection of yogurt adulteration with cow milk powder, exploiting the intact protein profile. An integrated protein-based workflow was established for the detection of as little as 1% cow milk powder addition into cow and goat milk yogurt. Simultaneously, markers for yogurt classification based on their animal origin (cow, ewe, or goat), type (traditional or strained), and thermal treatment of milk were revealed for the first time. Statistical analysis using chemometric tools, such as unsupervised principal component analysis (PCA) and supervised partial least squares discriminant analysis (PLS-DA) recognition techniques, were implemented for the discrimination/classification of the yogurt samples.

Τhyreostats (TSs) are veterinary drugs used in livestock farming for fattening. Their administration is banned in the European Union since 1981, and their monitoring for food quality and safety control requires sensitive and confirmatory methods. The present study describes the development and validation of a hydrophilic interaction liquid chromatography tandem mass spectrometry (HILIC-MS/MS) method for the simultaneous determination of 2-thiouracil (TU), 6-methyl-2-thiouracil (MTU), 6-propyl-2-thiouracil (PTU), 6-phenyl-2-thiouracil (PhTU), tapazole (TAP), and 2-mercaptobenzimidazole (MBI) in bovine muscle tissues. Investigation of the retention mechanism of the six analytes on the selected amide-based stationary phase showed that hydrophilic partition was the dominant interaction. The sample preparation included extraction with ACN/H₂O (80/20), followed by dispersive solid-phase extraction (d-SPE) with C18 sorbent and hexane partitioning. The method was validated according to European guidelines using internal standards, including isotopically labelled ones. The method’s LODs ranged between 2.8 ng g⁻¹ (6-phenyl-2-thiouracil) and 4.1 ng g⁻¹ (2-thiouracil). Application of the proposed method to 48 bovine tissue samples showed non-detectable results.