Pilot study on the value of Raman spectroscopy in the entity assignment of salivary gland tumors

Background The entity assignment of salivary gland tumors (SGT) based on histomorphology can be challenging. Raman spectroscopy has been applied to analyze differences in the molecular composition of tissues. The aim of this study was to evaluate the suitability of RS for entity assignment in SGT. Methods Raman data were collected in deparaffinized sections of pleomorphic adenomas (PA) and adenoid cystic carcinomas (ACC). Multivariate data and chemometric analysis were completed using the Unscrambler software. Results The Raman spectra detected in ACC samples were mostly assigned to nucleic acids, lipids, and amides. In a principal component-based linear discriminant analysis (LDA) 18 of 20 tumor samples were classified correctly. Conclusion In this proof of concept study, we show that a reliable SGT diagnosis based on LDA algorithm appears possible, despite variations in the entity-specific mean spectra. However, a standardized workflow for tissue sample preparation, measurement setup, and chemometric algorithms is essential to get reliable results.

Non-destructive Fluorescence Spectroscopy as a Tool for Discriminating Between Olive Oils According to Agronomic Practices and for Assessing Quality Parameters

A non-destructive fluorescence method combined with chemometric algorithms has been developed for discriminating between olive oils. The excitation-emission matrices (EEMs) of two olive oil varieties (Arbosana and Oliana) from two crop seasons, which had undergone two different irrigation treatments (control irrigation strategy and regulated deficit irrigation (RDI)), were recorded. EEMs were analysed using parallel factor analysis (PARAFAC), followed by linear discriminant analysis (LDA) incorporating three PARAFAC components. This analysis was able to discriminate between olive oils according to crop season (100% of predictions in the validation set were correct) and variety (100% of predictions were correct). Moreover, good discrimination (80% of correct predictions) was also achieved when examining olive oils belonging to the same variety but submitted to two different irrigation treatments. Further, the olive oil quality parameters obtained using conventional methods were compared with those obtained using unfolded partial least squares (U-PLS). Good correlation coefficients were obtained for Rancimat hours (r = 0.87), K270 (r = 0.75) and total polyphenol content (r = 0.94).

Laser-Induced Breakdown Spectroscopy: An Efficient Tool for Food Science and Technology (from the Analysis of Martian Rocks to the Analysis of Olive Oil, Honey, Milk and Other Natural Earth Products)

Laser-Induced Breakdown Spectroscopy (LIBS), having reached a level of maturity during the last few years, is generally considered as a very powerful and efficient analytical tool, and it has been proposed for a broad range of applications, extending from space exploration down to terrestrial applications, from cultural heritage to food science and security. Over the last decade, there has been a rapidly growing sub-field concerning the application of LIBS for food analysis, safety, and security, which along with the implementation of machine learning and chemometric algorithms opens new perspectives and possibilities. The present review intends to provide a short overview of the current state-of-the-art research activities concerning the application of LIBS for the analysis of foodstuffs, with the emphasis given to olive oil, honey, and milk.

Romanian Organic and Conventional Red Grapes Vineyards as Potential Sources of High Value-Added Products, in a Circular Economy Approach

The use of natural ingredients with active functions has been intensively studied in the last years, as a consequence to consumer preferences for organic products. Application of circular economy principles determined a significant research activity in the viticulture field. The use or re-use of vines parts for so-called nutraceuticals or other consumer-goods applications, are basically centered on their phytochemical and microbiological characterization. Eurostat updates ranks Romania fifth among the EU member states, with a total area under vines of 183,717 hectares. Characterization of four Vitis vinifera L. varieties, out of which one pure Romanian variety (Feteasca Neagra), cultivated in organic and conventional vineyards, together with pedoclimatic conditions have been provided. Data on phytochemical parameters and antimicrobial activity of extracts obtained from different anatomic parts of grapes were included. Analytical protocols and techniques applied were presented, together with data and results interpretation. Several chemometric algorithms have been used as complementary tools for interpretation of the instrumental analytical data.

Near infrared spectroscopy coupled chemometric algorithms for prediction of the antioxidant activity of peanut seed (Arachis hypogaea)

In the present research work, near infrared (NIR) spectroscopy coupled with chemometric algorithms such as partial least-squares (PLS) regression and some effective variable selection algorithms (synergy interval-PLS (Si-PLS), Backward interval-PLS (Bi-PLS), and genetic algorithm-PLS (GA-PLS)) were used for the quantification of antioxidant properties of peanut seed samples. The compositional parameters, such as DPPH, ABTS, FRAP, TPC, FCA, TFC, and TAC, were quantified using NIR spectroscopy. The developed models were assessed using correlation coefficients of the calibration (R2) and prediction (r2); root mean standard error of cross-validation, RMSECV; root mean square error of prediction, RMSEP and residual predictive deviation, RPD. The efficiency of the developed model was significantly enhanced with the use of Si-PLS, Bi-PLS, and GA-PLS as compared to the classical PLS model. The results of the R2 and r2 set varied from 0.76 to 0.95 and 0.72 to 0.94, respectively. The obtained results revealed that NIR spectroscopy, coupled with different chemometric algorithms, has the potential to be used for rapid assessment of the antioxidant properties of peanut seed.