Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) Coupled with Chemometrics, to Control the Botanical Authenticity and Quality of Cold-Pressed Functional Oils Commercialized in Romania

Characterizing Edible Oils by Oblique-Incidence Reflectivity Difference Combined with Machine Learning Algorithms

Due to the significant price differences among different types of edible oils, expensive oils like olive oil are often blended with cheaper edible oils. This practice of adulteration in edible oils, aimed at increasing profits for producers, poses a major concern for consumers. Furthermore, adulteration in edible oils can lead to various health issues impacting consumer well-being. In order to meet the requirements of fast, non-destructive, universal, accurate, and reliable quality testing for edible oil, the oblique-incidence reflectivity difference (OIRD) method combined with machine learning algorithms was introduced to detect a variety of edible oils. The prediction accuracy of Gradient Boosting, K-Nearest Neighbor, and Random Forest models all exceeded 95%. Moreover, the contribution rates of the OIRD signal, DC signal, and fundamental frequency signal to the classification results were 45.7%, 34.1%, and 20.2%, respectively. In a quality evaluation experiment on olive oil, the feature importance scores of three signals reached 63.4%, 18.9%, and 17.6%. The results suggested that the feature importance score of the OIRD signal was significantly higher than that of the DC and fundamental frequency signals. The experimental results indicate that the OIRD method can serve as a powerful tool for detecting edible oils.

Rapid analysis technologies with chemometrics for food authenticity field: A review

In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.

Recycling of silver nanoparticles from electronic waste via green synthesis and application of AgNPs-chitosan based nanocomposite on textile material

The main thrust of this project is the fabrication of silver nanoparticles (AgNPs) from electronic waste (PCB board) and applying it on 100% cotton fabric as an antimicrobial agent. The nanoparticle formation of silver was done by green synthesis way using an aqueous leaf extract of Eichhornia crassipes. Furthermore, chitosan was also applied to the fabric with silver nanoparticles by coating. FTIR and SEM tests characterized the fabricated silver nanoparticles, and antimicrobial tests were followed by the disc diffusion method. The SEM analysis showed an average particle size of 76.91 nm. The FTIR analysis showed the successful reduction of silver nanoparticles and the bonding with chitosan and cellulose. Besides, the EDX reports confirmed the existence of AgNPs by indicating a strong signal in the silver region. In addition, SEM characteristics analysis confirmed the uniform deposition of silver nanoparticles. Finally, the antimicrobial property was tested against gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli) bacteria. The antimicrobial result was found satisfactory in the case of green-synthesized recycled AgNPs. However, the effectiveness was not observed to be higher than green-synthesized pure AgNPs. In this study, the zone of inhibition of AgNPs was also compared to the reference antibiotics Ciprofloxacin.

A natural blue colorant from butterfly pea (Clitoria ternatea) petals for traditional rice cooking

Butterfly pea (Clitoria ternatea) flowers are widely used for culinary purposes in southern Asian countries. We assessed the optimal level of a butterfly pea petal extract (BPPE) to produce blue rice. Dried butterfly pea petals were extracted with water at 0.2, 0.4, 0.6, and 0.8% (w/v), and the extract was used to color boiled rice before cooking was completed. Rice cooked with BPPE acquired various shades of blue from light to dark. Significantly decreased lightness/darkness (L*), redness/greenness (a*), yellowness/blueness (b*), and color difference (∆E*) were observed in response to BPPE levels, while hue (h*) and chroma (C*) were significantly increased (p < 0.05). Total phenolic (TPC) and total anthocyanin (TAC) contents of cooked rice increased with BPPE levels (p < 0.05), and both constituents contributed significant radical scavenging activity (r = 0.886 to 0.994, p < 0.01, n = 20). Sensory evaluation by consumers indicated a suitable level of BPPE at 0.6%. The color of blue cooked rice was stable under an opaque cover for 8 days, whereas TPC and TAC decreased significantly with storage time. Findings from the current study can be used to produce blue rice in traditional cooking, and to produce other ready-to-use BPPE products.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05752-w.

Phytochemical Profile of Eight Categories of Functional Edible Oils: A Metabolomic Approach Based on Chromatography Coupled with Mass Spectrometry

Functional vegetable oils are highly considered not only for their nutritional value, but also for their health benefits. The profile of phytochemicals responsible for their quality is useful also for the identification of possible mislabeling or adulteration. The comparative composition of eight categories (sunflower, pumpkin, hempseed, linseed, soybean, walnut, sea buckthorn and olive) of commercial vs. authentic oils was determined. Fatty acids, volatiles, carotenoids, tocopherols, and phenolic components were analyzed by gas- and liquid chromatography-based techniques coupled with diode array, mass spectrometry, or fluorescence detection. Classification models, commonly used in metabolomics, e.g., principal component analysis, partial least squares discriminant analysis, hierarchical clusters and heatmaps have been applied to discriminate each category and individual samples. Carotenoids, tocopherols, and phenolics contributed mostly, qualitatively, and quantitatively to the discrimination between the eight categories of oils, as well as between the authentic and the commercial ones. This metabolomic approach can be easily implemented and the heatmaps can be considered as “identity” cards of each oil category and the quality of commercial oils, comparative to the authentic ones of the same botanical and geographical origin.

Investigating the molecular structure of plasma in type 2 diabetes mellitus and diabetic nephropathy by synchrotron Fourier-transform infrared microspectroscopy

Diabetes mellitus (DM) is associated with a high incidence of morbidity and mortality which, in many cases, is derived from the progressive kidney dysfunction due to diabetic nephropathy (DN). In this study, synchrotron-Fourier-transform infrared (SR-FTIR) microspectroscopy was used to identify molecular changes in the lipid and protein regions in the plasma of patients with different stages of DN (mild, moderate, severe and end-stage), and patients with type 2 diabetes mellitus (T2DM) without DN. Our results revealed different conformational changes in the proteins secondary structure between DN stages, and between DN and T2DM groups illustrated by peak shifts and intensity alterations. End-stage DN showed the highest CH₂/CH₃ ratio and intensity of the carbonyl group in protein-carbonyl region compared to other DN stages indicating high level of unsaturation and lipid peroxidation and oxidation conditions. Moreover, end-stage DN group was characterized by a decrease in amide I and amide II absorption signals which reflected a sign of hypoalbuminemia. When compared to T2DM, DN group demonstrated a higher oxidation state as confirmed via the high intensity of the carbonyl group and the high level of malondialdehyde. The current study highlights the promising role of SR-FTIR microspectroscopy as a new sensitive analytical approach that can be used to provide better understanding of the pathophysiology of DN, and guide the development of new preventive therapies and treatments.

Validation of the Developed Zero-Order Infrared Spectrophotometry Method for Qualitative and Quantitative Analyses of Tranexamic Acid in Marketed Tablets

(1) Background: The functional groups present in tranexamic acid allow direct infrared detection analysis. This study aimed to develop, apply, and validate an infrared spectrophotometry method used for qualitative and quantitative analyses of tranexamic acid in marketed tablets. (2) Methods: This was a descriptive observational study that consisted of several stages: determining the specific wavenumber for analysis, obtaining a simple linear regression equation, analyzing tranexamic acid both qualitatively and quantitatively, and validating the developed method for routine analysis. (3) Results: The peak analysis obtained a range of baseline wavenumbers from 1679.17 to 1295.25 cm⁻¹. The regression equation obtained was Y = 310.8527 × X + 0.9718, and the coefficient of determination (R²) obtained was 0.9994. The tranexamic acids in marketed tablets overall have a similarity index value of more than 0.90 and overall have levels ranging between 97.0% and 103.0%. The infrared spectrophotometry method that was successfully developed, applied, and validated for qualitative and quantitative analyses of tranexamic acid in marketed tablets meets the requirements both qualitatively and quantitatively of the tablet monograph. (4) Conclusions: The infrared spectrophotometry method has been validated and meets the requirements for accuracy, precision, detection limit, quantitation limit, linearity, range, and specificity.

ATR-FTIR-MIR Spectrometry and Pattern Recognition of Bioactive Volatiles in Oily versus Microencapsulated Food Supplements: Authenticity, Quality, and Stability

Fourier transform infrared spectroscopy on the middle infrared region (ATR-FTIR-MIR) proved to be a convenient and reliable technique to evaluate foods' quality and authenticity. Plants' essential oils are bioactive mixtures used as such or in different oily or microencapsulated formulations, beneficial to human health. Six essential oils (thyme, oregano, juniperus, tea tree, clove, and cinnamon) were introduced in three oily formulations (Biomicin, Biomicin Forte, and Biomicin urinary) and these formulations were microencapsulated on fructose and maltodextrin matrices. To study their stability, the microencapsulated powders were kept under light irradiation for 14 days at 25 °C or introduced in biopolymer capsules. All variants were analysed by ATR-FTIR-MIR, recording wavenumbers and peak intensities (3600-650 cm^-1). The data were processed by Unscrambler and Metaboanalyst software, with specific algorithms (PCA, PLSDA, heatmaps, and random forest analysis). The results demonstrated that ATR-FTIR-MIR can be successfully applied for fingerprinting and finding essential oil biomarkers as well as to recognize this pattern in final microencapsulated food supplements. This study offers an improved ATR-FTIR-MIR procedure coupled with an adequate chemometric analysis and accurate data interpretation, to be applied for the evaluation of authenticity, quality, traceability, and stability during storage of essential oils incorporated in different matrices.

Potentialities of Rapid Analytical Strategies for the Identification of the Botanical Species of Several "Specialty" or "Gourmet" Oils

A comprehensive data collection of authentic "specialty" or "gourmet" oils, namely cold-pressed industrial virgin oils, was performed. Eight different botanical species, i.e., Almond, Apricot, Avocado, Hazelnut, Mosqueta rose, Rosehip, Sunflower, and Walnut oils were studied plus Olive oil as the gold standard of cold-pressed virgin oils. Two different analytical approaches are proposed to rapidly verify the botanical species of the oil-based raw material. The first approach is based on a multivariate statistical analysis of conventional analytical data, namely their fatty acid composition. These data have been re-elaborated in a multivariate way by Principal Component Analysis (PCA) and classification methods. The second approach proposes a fast and non-destructive spectrophotometric analysis to determine the color of these oils to discriminate among different species. In this regard, the raw diffuse reflectance spectra (380-780 nm) obtained by a UV-Vis spectrophotometer with an integrating sphere was considered and elaborated by chemometrics. This information was compared with the results obtained by the most common approach based on the CIELab parameters. A data fusion of chromatographic and spectral data was also investigated. Either fatty acid composition or color of these oils demonstrated to be two promising markers of their botanical authenticity.