Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches

Geographical origin assessment of extra virgin olive oil (EVOO) is recognised worldwide as raising consumers’ awareness of product authenticity and the need to protect top-quality products. The need for geographical origin assessment is also related to mandatory legislation and/or the obligations of true labelling in some countries. Nevertheless, official methods for such specific authentication of EVOOs are still missing. Among the analytical techniques useful for certification of geographical origin, nuclear magnetic resonance (NMR) and mass spectroscopy (MS), combined with chemometrics, have been widely used. This review considers published works describing the use of these analytical methods, supported by statistical protocols such as multivariate analysis (MVA), for EVOO origin assessment. The research has shown that some specific countries, generally corresponding to the main worldwide producers, are more interested than others in origin assessment and certification. Some specific producers such as Italian EVOO producers may have been focused on this area because of consumers’ interest and/or intrinsic economical value, as testified also by the national concern on the topic. Both NMR- and MS-based approaches represent a mature field where a general validation method for EVOOs geographic origin assessment could be established as a reference recognised procedure.

NanoGram Detection of Drilling Fluids Additives for Uncertainty Reduction in Surface Logging

Manual sampling rock cuttings off the shale shaker for lithology and petrophysical characterization is frequently performed during mud logging. Knowing the depth origin where the cuttings were generated is very important for correlating the cuttings to the petrophysical characterization of the formation. It is a challenge to accurately determine the depth origin of the cuttings, especially in horizontal sections and in coiled tubing drilling, where conventional logging while drilling is not accessible. Additionally, even in less challenging drilling conditions, many factors can contribute to an inaccurate assessment of the depth origin of the cuttings. Inaccuracies can be caused by variation of the annulus dimension used to determine the lag time (and thus the depth of the cuttings), by the shifting or scrambling of cuttings during their return trip back to the surface, and by the mislabelling of the cuttings during sampling. In this work, we report the synthesis and application of polystyrenic nanoparticles (NanoTags) in labeling cuttings for depth origin assessment. We have successfully tagged cuttings using two NanoTags during a drilling field test in a carbonate gas well and demonstrated nanogram detection capability of the tags via pyrolysis-GCMS using an internally developed workflow. The cuttings depth determined using our tags correlates well with the depth calculated by conventional mud logging techniques.

The modern methodological approach to non-invasive assessment of the human microecological status and its deviations from homeostasis

Modern trends in medicine and healthcare suggest the development of personified approaches to assessing human health and the introduction of technologies with the potential for early diagnosis of pathological changes. This concept is fully consistent with the methodological approach based on the study of a pool of molecular markers of microbial origin: «Assessment of the microecological status of a person by chromatography-mass spectrometry», registered in 2009 as a new medical technology. Now the method of mass spectrometry of microbial markers (MSMM) has become widespread in Russia, and also arouses keen interest of the foreign medical community. The article is devoted to the key features of MSMM technology, its modern implementation, as well as its role in the development of predictive, preventive, personalized medicine.

REEs – a possible tool for geographical origin assessment?

Environmental contextRare earth element profiles of foodstuffs reflect both the soil fingerprint and the specific agricultural practice for a certain location. This review describes the advantages and limitations of using rare earth elements as markers for geographical discrimination as a function of food matrix. The technique has great potential for establishing the geographical origin of foodstuffs. AbstractThe present work aims to present the application of the content of rare earth elements (REEs) in the authentication of food and beverage studies, mainly regarding the geographical origin. Therefore, the potential, as well as the limitation, of these emerging markers are separately presented for different food matrices. It is observed that for most of the discussed matrices, the highest discrimination potential is provided by the LREEs (light REEs). It has also been suggested in the literature that the content of REEs is minimally affected by harvesting years, which enhances the potential to differentiate between samples from different origins. Reported studies have shown that the efficiency of the REEs profile is the most effective for the unprocessed food matrix (e.g. vegetables, fruits and meat) and has a low efficiency for commodities like wine, which suggests that the fractionation of REEs that occurs during the wine making process limits the use of these elements as geographical tracers.

Application of fluorescence spectroscopy using classical right angle technique in white wines classification

The potential of excitation - emission matrices (EEM) measurements using classical right angle technique, in conjunction with chemometrics, was prospected for white wine classification with respect to their cultivar and geographical origin. For this purpose, wines belonging to four cultivars (Chardonnay, Pinot Gris, Riesling and Sauvignon) from two different countries (Romania and France) were investigated. The excitation – emission matrices were statistically processed using parallel factor analysis (PARAFAC). According to Soft Independent Modeling Classification Analogy (SIMCA) model, for cultivar differentiation, only 3 out of 107 wine samples (1 Pinot Gris (Romania); 1 Riesling (Romania) and 1 Sauvignon (France)) were misclassified while for geographical origin assessment, only 2 wines (1 Romania and 1 France) were misclassified. This study demonstrates the potential of excitation – emission fluorescence matrices spectroscopy using the classical right angle technique in wine authentication, without sample dilution.