The Use of Electronic Nose as Alternative Non-Destructive Technique to Discriminate Flavored and Unflavored Olive Oils

A novel method for determination of peroxide value and acid value of extra-virgin olive oil based on fluorescence internal filtering effect correction

Peroxide value (PV) and acid value (AV) are widely used indicators for evaluating oxidation degree of olive oils. Fluorescence spectroscopy has been extensively studied on the detection of oil oxidation, however, the detection accuracy is limited due to internal filtering effect (IFE). Due to the primary and secondary IFE, at least two wavelengths of absorption information are required. Least squares support vector regression (LSSVR) models for PV and AV were established based on two absorption coefficients (μa) at 375 nm and emission wavelength and one fluorescence intensity at corresponding wavelength. The regression results proved that the model based on 375 and 475 nm could reach the best performance, with the highest correlation coefficient for prediction (rp) of 0.889 and 0.960 for PV and AV respectively. Finally, the explicit formulations for PV and AV were determined by nonlinear least squares fitting, and the rp could reach above 0.94 for two indicators.

Improving the functionality of virgin and cold-pressed edible vegetable oils: Oxidative stability, sensory acceptability and safety challenges

In recent years, there has been a growing demand for minimally processed foods that offer health benefits and premium sensory characteristics. This trend has led to increased consumption of virgin (VOs) and cold-pressed (CPOs) oils, which are rich sources of bioactive substances. To meet consumer needs for new oil products conferring multi-functional properties over a longer storage period, the scientific community has been revisiting traditional enrichment practices while exploring novel fortification technologies. In the last four years, the interest has been growing faster; an ascending number of annually published studies are about the addition of different plant materials, agri-food by-products, or wastes (intact or extracts) to VOs and CPOs using traditional or innovative fortification processes. Considering this trend, the present review aims to provide an overview and summarize the key findings from relevant papers that were retrieved from extensively searched databases. Our meta-analysis focuses on exposing the most recent trends regarding the exploitation of VOs and CPOs as substrates, the fortification agents and their form of use, as well as the fortification technologies employed. The review critically discusses possible health claim and labeling issues and highlights some chemical and microbial safety concerns along with authenticity issues and gaps in quality specifications that manufacturers have yet to address. All these aspects are examined from the perspective of developing new oil products with well-balanced techno-, senso- and bio-functional characteristics.

Rapid and Low-Cost Quantification of Adulteration Content in Camellia Oil Utilizing UV-Vis-NIR Spectroscopy Combined with Feature Selection Methods

This study aims to explore the potential use of low-cost ultraviolet-visible-near infrared (UV-Vis-NIR) spectroscopy to quantify adulteration content of soybean, rapeseed, corn and peanut oils in Camellia oil. To attain this aim, test oil samples were firstly prepared with different adulterant ratios ranging from 1% to 90% at varying intervals, and their spectra were collected by an in-house built experimental platform. Next, the spectra were preprocessed using Savitzky-Golay (SG)-Continuous Wavelet Transform (CWT) and the feature wavelengths were extracted using four different algorithms. Finally, Support Vector Regression (SVR) and Random Forest (RF) models were developed to rapidly predict adulteration content. The results indicated that SG-CWT with decomposition scale of 25 and the Iterative Variable Subset Optimization (IVSO) algorithm can effectively improve the accuracy of the models. Furthermore, the SVR model performed best for predicting adulteration of camellia oil with soybean oil, while the RF models were optimal for camellia oil adulterated with rapeseed, corn, or peanut oil. Additionally, we verified the models' robustness by examining the correlation between the absorbance and adulteration content at certain feature wavelengths screened by IVSO. This study demonstrates the feasibility of using low-cost UV-Vis-NIR spectroscopy for the authentication of Camellia oil.

Characterization of Flavoured Olive Oils of ‘Madural’ Variety

Flavoured oils arouse great interest among consumers in many countries due to their variety of flavours and versatility, especially in the culinary field. The aromatization of oils seeks to improve their sensory and nutritional properties, and extend their useful life due to the added substances can be beneficial as antioxidant and antimicrobial agent. In this research, olive oils of the ‘Madural’ variety from Trasos Montes region of Portugal have been obtained and flavoured with different aromatics herbs and condiments (flower of salt and bay leaf, garlic, rosemary and dehydrated lemon peel). The objective is to study the influence of the aromatic herbs and condiments on the physicochemical parameters of the oils: quality, purity, oxidative stability and microbiological analysis. It can be noted that the flavourings do not significantly alter the quality of the monovarietal oil, although, for some parameters, the excessive contact times can affect the category of the oil. On the other hand, the high content of antioxidants provided by flavouring agents can favour its stability and prolong its expiration. In this sense, the flavouring agent that contributes to stop the oxidation of the oil over time is salt + bay leaves, as higher oxidative stability values were detected than those obtained in monovarietal oil. However, oils flavoured with rosemary or lemon show a decrease over time for this parameter, which could indicate that this flavouring accelerates oxidation. In the case of oxidative stability referred to those flavoured with garlic, they present similar values to the monovarietal. The effect exerted by flavourings on the different parameters of the oils is complex, since it is influenced by the method followed and the operating variables established for flavouring.

An Electronic Nose as a Non-Destructive Analytical Tool to Identify the Geographical Origin of Portuguese Olive Oils from Two Adjacent Regions

The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils' geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 ≤ R² ≤ 0.998 and 0.40 ≤ RMSE ≤ 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles.