Evaluation of total phenolic content in virgin olive oil using fluorescence excitation-emission spectroscopy coupled with chemometrics

Adulteration Detection and Quantification in Olive Oil Using Excitation-Emission Matrix Fluorescence Spectroscopy and Chemometrics

This research investigates the use of excitation-emission matrix fluorescence (EEMF) in conjunction with chemometric models to rapidly identify and quantify adulteration in olive oil, a critical concern where sample availability is limited. Adulteration is simulated by blending soybean, peanut, and linseed oils into olive oil, creating diverse adulterated samples. Principal component analysis (PCA) was applied to the EEMF spectral data as an initial exploratory measure to cluster and differentiate adulterated samples. Spatial clustering enabled vivid visualization of the variations and trends in the spectra. The novel application of parallel factor analysis (PARAFAC) for data decomposition in this paper focuses on unraveling correlations between the decomposed components and the actual adulterated components, which offers a novel perspective for accurately quantifying adulteration levels. Additionally, a comparative analysis was conducted between the PCA and PARAFAC methodologies. Our study not only unveils a new avenue for the quantitative analysis of adulterants in olive oil through spectral detection but also highlights the potential for applying these insights in practical, real-world scenarios, thereby enhancing detection capabilities for various edible oil samples. This promises to improve the detection of adulteration across a range of edible oil samples, offering significant contributions to food safety and quality assurance.

Enhancing the Recovery of Bioactive Compounds of Soybean Fermented with Rhizopus oligosporus Using Supercritical CO2: Antioxidant, Anti-Inflammatory, and Oxidative Proprieties of the Resulting Extract

The aim of the present study was to evaluate the use of supercritical CO₂ combined with cosolvent for the recovery of bioactive compounds of soybean fermented with Rhizopus oligosporus NRRL 2710. Soxhlet extractions using seven different organic solvents (n-hexane, petroleum ether, ethyl acetate, acetone, ethanol, methanol, and water) were initially performed for comparative purposes. The extracts obtained were characterized by physicochemical, antioxidant, total phenolic, and oxidative proprieties. For the Soxhlet extractions, the highest and lowest yields obtained were 45.24% and 15.56%, using methanol and hexane, respectively. The extraction using supercritical CO₂ combined with ethanol as a static modifier (scCO₂ + EtOH) presented, at a high pressure (25 MPa) and temperature (80 °C), a phenolic compound content of 1391.9 μg GAE g⁻¹ and scavenging of 0.17 g, reaching a 42.87% yield. The extracts obtained by sCO₂ + EtOH were characterized by high contents of essential fatty acids (linoleic acid and oleic acid) and bioactive compounds (gallic acid, trans-cinnamic acid, daidzein, and genistein). These extracts also showed a great potential for inhibiting hyaluronidase enzymes (i.e., anti-inflammatory activity). Thermogravimetric analyses of the samples showed similar profiles, with oil degradation values in the range from 145 to 540 °C, indicating progressive oil decomposition with a mass loss ranging from 93 to 98.7%. In summary, this study demonstrated the flexibility of scCO₂ + EtOH as a green technology that can be used to obtain high-value-added products from fermented soybean.

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.

Multiblock Analysis Applied to Fluorescence and Absorbance Spectra to Estimate Total Polyphenol Content in Extra Virgin Olive Oil

A fast and easy methodology to estimate total polyphenol content in extra virgin olive oil was developed by applying the chemometric multiblock method sequential and orthogonalized partial least squares (SO-PLS) in order to combine front-face emission fluorescence spectra (270 nm excitation wavelength) and absorbance spectra. The hypothesis of this work stated that inner-filter effects in fluorescence spectra that would reduce the estimation performance of a single block model could be overcome by incorporating the absorbance spectral information of the compounds causing them. Different spectral preprocessing algorithms were applied. Double cross-validation with 50 iterations was implemented to improve the robustness of the obtained results. The PLSR model on the single block of fluorescence raw spectra achieved an RMSEP of 177.11 mg·kg⁻¹ as the median value, and the complexity of the model was high, as the median value of latent variables (LVs) was eight. Multiblock SO-PLS models with pretreated fluorescence and absorbance spectra provided better performance, although artefacts could be introduced by transformation. The combination of fluorescence and absorbance raw data decreased the RMSEP median to 134.45 mg·kg⁻¹. Moreover, the complexity of the model was greatly reduced, which contributed to an increase in robustness. The median value of LVs was three for fluorescence data and only one for absorbance data. Validation of the methodology could be addressed by further work considering a higher number of samples and a detailed composition of polyphenols.

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).

Chemo-taxonomic and biological potential of highly therapeutic plant Pedicularis groenlandica Retz. using multiple microscopic techniques

Pedicularis groenlandica is one of the most important medicinal plant of Deosai Plateau (Gilgit-Baltistan) Pakistan. The present study was aim to evaluate the micromorphological features, phytochemical screening and pharmacological potential of P. groenlandica by using multiple microscopic techniques. Six different solvents were used to prepare P. groenlandica extracts. Phytochemical and antioxidant activities were determined calorimetrically. To investigate antidiabetic, α-amylase inhibition assay was performed. Cytotoxicity was tested using brine shrimp assay. Anti-leishmanial via MTT assay. Disc-diffusion assay was used for protein kinase inhibitory, antibacterial and antifungal activities. Palyno-anatomical study showed significant variation for the authentication and correct identification of this highly therapeutic plant by using light and scanning electron microscopic techniques. All extracts were found rich in phytochemicals, significant amount of phenolic and flavonoid contents were found in methanol extract (PGM) 95.78 mg GAE/g and 66.90 mg QE/g. Highest DPPH scavenging potential with IC₅₀ 88.65 μg/mL, total antioxidant capacity (60.33 mg AAE/g sample) and total reducing power (83.97 mg AAE/g) were found for PGM. Disc-diffusion method showed significant antibacterial and antifungal activities. Noticeable growth inhibition in L. tropica was displayed by n-hexane extract (IC₅₀ 112 μg/mL). Brine shrimp with highest LD₅₀ (67.65 μg/mL) in ethyl-acetate extract. Ethanol extract gives persuasive protein kinase inhibition (26 mm) against Streptomyces 85-E hyphae. Highest alpha-amylase inhibition (74.10%) was found in n-hexane extract. In conclusion, our findings scientifically support the ethno-medicinal and biological potential of P. groenlandica. In future, the plant needs to be explored for further identification and isolation of bioactive compounds to develop new drugs to treat several aliments.

The Potential of Apulian Olive Biodiversity: The Case of Oliva Rossa Virgin Olive Oil

In this study, the drupes and virgin olive oils extracted from the Oliva Rossa landrace are characterized. Oliva Rossa is an old landrace part of the autochthonous Apulian olive germplasm for which only few data have been reported till now. During the study, the maturity patterns of the drupes had been followed. Four samplings per year were planned, one every 14 days starting from the middle of October. The pigmentation index, the oil content and the total phenolic content of the drupes were measured. Simultaneously, virgin olive oils were extracted at the lab scale and analyzed for the fatty acid composition, the basic quality parameters and the content of minor compounds. The pigmentation pattern of the drupes was different among the years and, despite this trend, at the third sampling time the stage of maximum oil accumulation was always over. The extracted virgin olive oils had a medium to high level of oleic acid. With colder temperatures, a higher level of monounsaturated fatty acids, oleic/linoleic ratio and antioxidants was observed. The phenolic profile was dominated by 3,4-DPHEA-EDA and p-HPEA-EDA while the volatile profile by (E)-2-hexenal and 3-ethyl-1,5-octadiene.

Two-Photon Fluorescence Study of Olive Oils at Different Excitation Wavelengths

Two-photon fluorescence (TPF) of olive oils is discovered and observed experimentally for the first time. Variations of the single-photon fluorescence (SPF) and TPF with the excitation wavelength are investigated for four different olive oils. The results show that fluorescence of the cosmetic olive oils (COO) is very weak and exhibits only one spectral peak around 490 nm. While for the ordinary edible oils (OEO) whether they are during their shelf life or not, their fluorescence spectra may exhibit multiple peak structures. The short-term natural expiration only slightly weakens TPF of OEO. Moreover, the excitation wavelength affects the OEO spectra considerably in terms of the spectral peak number, the spectral peak position, and spectral shapes. When the excitation wavelength decreases from 700 nm, the whole TPF of the OEO also decreases. Relatively, however, the short wave band will decrease and disappear more quickly. While for the SPF, the long wave band will decrease and disappear first. The optimal excitation wavelengths to make the TPF strongest are around 700 nm and 640 nm for OEOs and COO, respectively. And effects of temperature on SPF and TPF of extra virgin olive oil are also explored. This work may be of significance for its potential applications in TPF detection and two-photon laser.

Monitoring Virgin Olive Oil Shelf-Life by Fluorescence Spectroscopy and Sensory Characteristics: A Multidimensional Study Carried Out under Simulated Market Conditions

The control of virgin olive oil (VOO) freshness requires new tools that reflect the diverse chemical changes that take place during the market period. Fluorescence spectroscopy is one of the techniques that has been suggested for controlling virgin olive oil (VOO) freshness during its shelf-life. However, a complete interpretation of fluorescence spectra requires analyzing multiple parameters (chemical, physical–chemical, and sensory) to evaluate the pace of fluorescence spectral changes under moderate conditions with respect to other changes impacting on VOO quality. In this work, four VOOs were analyzed every month with excitation–emission fluorescence spectra. The same samples were characterized with the concentration of fluorophores (phenols, tocopherols, chlorophyll pigments), physical–chemical parameters (peroxide value, K₂₃₂, K₂₇₀, free acidity), and sensory attributes (medians of defects and of the fruity attribute). From the six components extracted with parallel factor analysis (PARAFAC), two components were assigned to chlorophyll pigments and those assigned to tocopherols, phenols, and oxidation products were selected for their ability to discriminate between fresh and aged oils. Thus, the component assigned to oxidation products correlated with K₂₇₀ in the range 0.80–0.93, while the component assigned to tocopherols–phenols correlated with the fruity attribute in the range 0.52–0.90. The sensory analysis of the samples revealed that the changes of these PARAFAC components occurred at the same time as, or even before, the changes of the sensory characteristics.

Determination of the concentration of total phenolic compounds in aged cachaça using two-dimensional fluorescence and mid-infrared spectroscopy

In this work, we investigate alternative quantification methods based on optical spectroscopy and variable selection approach, using as a case study the aging process of cachaça. The cachaça was aged in an Amburana barrel and the samples were analyzed with a traditional analytical method for total phenolic quantification (Folin-Ciocalteu), with 2-D fluorescence and infrared spectroscopy. We applied a methodology based on Ant Colony Optimization to optimize variable selection and model fitting to predict total phenolic content. Our results demonstrated that fluorescence spectroscopy was more sensitive than IR in the quantification of total phenolic compounds for both global and local models, presenting good results (R² superior to 0.979), significantly reducing the number of original variable (1995) for only 4 pairs of Ex/Em. Variable selection combined with spectroscopy reveals potential because this technique eliminates the need for sample preparation and allows the construction of customized sensors for application in the food industry.

A novel fluorescence sensing strategy based on nanoparticles combined with spectral splicing and chemometrics for the recognition of Citrus reticulata 'Chachi' and its storage year

BACKGROUND

The fluorescence sensing method has been increasingly applied in food quality control because it is fast and sensitive. However, its application in quality evaluation is challenging. Using Citri Reticulatae Pericarpium (CRP; dried mandarin orange peel) as an example, we developed a simple and low-cost fluorescence sensing strategy based on nanoparticles combined with spectral splicing and chemometrics for quality evaluation. This method can recognize Citrus reticulata 'Chachi' (CRC) from other CRP cultivars and further identify the storage year.

RESULTS

Nanogold particles and cadmium telluride quantum dots were selected as nanosensors and mixed with aqueous extracts of CRP separately to produce fluorescence quenching spectra. Then, a simple spectral splicing procedure was applied to obtain spliced spectra comprising different combinations of the self-fluorescence and fluorescence quenching spectra of CRP samples. With the aid of partial least-squares discriminant analysis, the new strategy achieved recognition rates of 100% in distinguishing CRC samples from other CRP samples, as well as recognition rates of 100% for the training set and 98.04% for the prediction set in the discrimination of the storage year of CRC. The recognition mechanism is dominated by interactions between the nanoparticles and the fluorescent components in the CRP samples, but other components also have concurrent effects.

CONCLUSIONS

This novel fluorescence sensing strategy not only provides a new tool for the quality evaluation of CRC but also has good prospects for the authentication and traceability of other foods and herbs. Crucially, the developed method is convenient, simple and effective. © 2020 Society of Chemical Industry.