Rapid Detection of Benzo[a]pyrene in Extra Virgin Olive Oil Using Fluorescence Spectroscopy.

Extra virgin olive oil (EVOO) should be naturally free of polycyclic aromatic hydrocarbon (PAH) contamination. PAHs are carcinogenic and toxic, and may cause human health and safety problems. This work aims to detect benzo[a]pyrene residues in EVOO using an easily adaptive optical methodology. This approach, which is based on fluorescence spectroscopy, does not require any sample pretreatment or prior extraction of PAH content from the sample, and is reported for the first time herein. The detection of benzo[a]pyrene even at low concentrations in extra virgin olive oil samples demonstrates fluorescence spectroscopy's capability to ensure food safety.

Comparative Evaluation of Different Targeted and Untargeted Analytical Approaches to Assess Greek Extra Virgin Olive Oil Quality and Authentication.

Extra virgin olive oil (EVOO) is a key component of the Mediterranean diet, with several health benefits derived from its consumption. Moreover, due to its eminent market position, EVOO has been thoroughly studied over the last several years, aiming at its authentication, but also to reveal the chemical profile inherent to its beneficial properties. In the present work, a comparative study was conducted to assess Greek EVOOs' quality and authentication utilizing different analytical approaches, both targeted and untargeted. 173 monovarietal EVOOs from three emblematic Greek cultivars (Koroneiki, Kolovi and Adramytiani), obtained during the harvesting years of 2018-2020, were analyzed and quantified as per their fatty acids methyl esters (FAMEs) composition via the official method (EEC) No 2568/91, as well as their bioactive content through liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) methodology. In addition to FAMEs analysis, EVOO samples were also analyzed via HRMS-untargeted metabolomics and optical spectroscopy techniques (visible absorption, fluorescence and Raman). The data retrieved from all applied techniques were analyzed with Machine Learning methods for the authentication of the EVOOs' variety. The models' predictive performance was calculated through test samples, while for further evaluation 30 commercially available EVOO samples were also examined in terms of variety. To the best of our knowledge, this is the first study where different techniques from the fields of standard analysis, spectrometry and optical spectroscopy are applied to the same EVOO samples, providing strong insight into EVOOs chemical profile and a comparative evaluation through the different platforms.

Optical spectroscopy methods combined with multivariate statistical analysis for the classification of Cretan thyme, multi-floral and honeydew honey.

BACKGROUND: The botanical origin of honey attracts both commercial and research interest. Consumers' preferences and medicinal uses of particular honey types drive the demand for the determination of their authenticity with regard to their botanical origin. This study presents the discrimination of thyme, multi-floral. and honeydew honeys by Fourier-transform infrared (FTIR) and ultraviolet (UV) absorption spectroscopy combined with multivariate statistical analysis. UV absorption spectroscopy was applied without any dilution of the sample using a custom-made cuvette. FTIR and UV absorption spectroscopic data were processed by means of the orthogonal partial least squares discriminant analysis. RESULTS: The optimal classification of floral and honeydew honeys was accomplished with UV spectroscopy with a successful estimation of 92.65% for floral honey and 91.30% for honeydew honey. The discrimination of thyme versus the multi-floral honey was best achieved with FTIR, with a correct classification of 95.56% and 100% for multi-floral and thyme honey respectively. Furthermore, our findings revealed the region of 2400-4000 cm-1 of the FTIR spectra as the most significant for this discrimination. CONCLUSION: This work demonstrates that optical spectroscopic techniques in combination with multivariate statistical analysis can be a rapid, low-cost, easy-to-use approach for the determination of the botanical origin of honey without sample pretreatment. © 2021 Society of Chemical Industry.

Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of Cretan Wines.

The present study was aimed at the identification, differentiation and characterization of red and white Cretan wines, which are described with Protected Geographical Indication (PGI), using ultraviolet-visible absorption spectroscopy. Specifically, the grape variety, the wine aging process and the role of barrel/container type were investigated. The combination of spectroscopic results with machine learning-based modelling demonstrated the use of absorption spectroscopy as a facile and low-cost technique in wine analysis. In this study, a clear discrimination among grape varieties was revealed. Moreover, a grouping of samples according to aging period and container type of maturation was accomplished, for the first time.

Verifying the Geographical Origin and Authenticity of Greek Olive Oils by Means of Optical Spectroscopy and Multivariate Analysis.

Olive oil samples from three different Greek regions (Crete, Peloponnese and Lesvos) were examined by optical spectroscopy in a wide spectral region from ultraviolet to near infrared using absorption, fluorescence and Raman spectroscopies. With the aid of machine learning methods, such as multivariate partial least squares discriminant analysis, a clear classification of samples originating from the different Greek geographical regions was revealed. Moreover, samples produced in different subareas of Crete and Peloponnese were also well discriminated. Furthermore, mixtures of olive oils from different geographical origins were studied employing partial least squares as a tool to establish a model between the actual and predicted compositions of the mixtures. The results demonstrated that optical spectroscopy combined with multivariate statistical analysis can be used as an emerging innovative alternative to the classical analytical methods for the identification of the origin and authenticity of olive oils.

Formation, Fragmentation, and Structures of YxOy(+) (x = 1, 2, y = 1 - 13) Clusters: Collision-Induced Dissociation Experiments and Density Functional Theory Calculations.

Yttrium oxide cluster cations have been experimentally and theoretically studied. We produced small, oxygen-rich yttrium oxide clusters, YxOy+ (x = 1, 2, y = 1­13), by mixing the laser-produced yttrium plasma with a molecular oxygen jet. Mass spectrometry measurements showed that the most stable clusters are those consisting of one yttrium and an odd number of oxygen atoms of the form YO(+)(2k+1) (k = 0­6). Additionally, we performed collision induced dissociation experiments, which indicated that the loss of pairs of oxygen atoms down to a YO+ core is the preferred fragmentation channel for all clusters investigated. Furthermore, we conduct DFT calculations and we obtained two types of low-energy structures: one containing an yttrium cation core and the other composed of YO+ core and O2 ligands, being in agreement with the observed fragmentation pattern. Finally, from the fragmentation studies, total collision cross sections are obtained and these are compared with geometrical cross sections of the calculated structures.

Collision-induced dissociation studies on Fe(O2)n(+) (n = 1-6) clusters: application of a new technique based on crossed molecular beams.

Gas-phase oxygen-rich iron oxide clusters Fe(O2)n(+) (n = 1-6), are produced in a molecular beam apparatus. Their stability and structure are investigated by measuring the fragmentation cross-sections from collision-induced-dissociation experiments. For this purpose, two different techniques have been employed. The first one relies on the measurement of the fragments resulting after collisional activation and subsequent dissociation of mass selected cluster ions in a molecular beam passing through a cell filled with noble gas atoms. The second one is a new approach that we introduce and is based on crossed molecular beams to measure the fragmentation cross-sections, in a more efficient manner without mass selection of the individual clusters. The cross-sections obtained with the different techniques are compared with each other as well as with theoretical ones resulting from the application of a simple geometrical projection model. Finally, the general trends observed are compared with results for other Fe-molecule clusters available in the literature.

Symmetry-switching molecular Fe(O2)n(+) clusters.

Experimental and theoretical studies based on mass spectrometry, collision-induced dissociation, and ab initio calculations are performed on the formation and stability of FeO(n)(+) clusters, as well as on their structural, electronic, and magnetic properties. In the mass spectra, clusters with an even number of oxygen atoms show increased stability, most prominently for FeO(10)(+). The extra stability of this cluster is confirmed by measurements of fragmentation cross sections through crossed molecular beam experiments. In addition, the calculations indicate a structural phase transition at this size, and most importantly, the FeO(n)(+) clusters show unique magnetic features, exhibiting isoenergetic low-spin (LS) and high-spin (HS) ground states. In the LS state, the magnetic moments of the O atoms adopt an antiferromagnetic alignment with respect to the magnetic moment of Fe(+), whereas in the HS state, the alignment is ferromagnetic. FeO(10)(+) is the largest thermodynamically stable complex, with the highest magnetic moment among the FeO(n)(+) clusters (13 µ(B) in HS).

Vibrational constants and binding energies for the low-lying electronic states of Sr+ CO2 from photodissociation spectroscopy.

By use of photodissociation spectroscopy of mass-selected ions, vibrationally resolved electronic spectra of the Sr+ CO2 complex are recorded in two energy regions, 20,780-22,990 and 16,210-17,550 cm(-1), correlating to the Sr+ 5(2)P <-- 5(2)S and 4(2)D <-- 5(2)S transitions, respectively. The spectra are analyzed to obtain the vibrational constants and dissociation energies of the molecular states. The observed spin-orbit splitting indicates a linear complex in agreement with theoretical calculations. The results are compared with similar systems and explained in the framework of electrostatic interactions.