A novel method for qualitative analysis of edible oil oxidation using an electronic nose

Pickering emulsion of camellia oil stabilized by Octenyl succinic acid starch: Interaction, lipid oxidation and digestibility

The application of camellia oil is limited by its susceptibility to oxidation and insolubility in water, particularly under high humidity and temperature conditions. In order to effectively reduce the oxidation rate of camellia oil, prolong the shelf life in order to improve the stability in storage under different conditions, this study encapsulates camellia oil in Pickering emulsions stabilized by Octenyl succinic acid (OSA) starch, achieving a 100-fold reduction in release rate and enhanced lipid oxidation stability. The smooth surface and complete particles of the emulsion were observed and no new chemical bonds were formed. The minimum particle sizes were 1.72 μm and 2.73 μm, when the Pickering emulsion was set at pH 6 and 0.1 M NaCl. In the digestion process, the microstructures observed that Pickering emulsion possessed super stability against oral and gastric digestions, prolonged the release time and improved the bioavailability compared with camellia oil, and the digestibility of the emulsion was 56.16 % within 120 min. All these results indicate that OSA-starch stabilized camellia oil can effectively increase solubility, improve stability and expand the application range.

Classification of Sesame Oil Based on Processing-Originated Differences in the Volatile Organic Compound Profile by a Colorimetric Sensor

Fragrant edible sesame oil is popular for its unique aroma. The aroma of sesame oil is determined by its volatile organic compound (VOC) profile. Sesame oils produced by different techniques could have different VOC profiles. In addition, blending fragrant sesame oil with refined oil could also alter the VOC profile of the final product. Current practices in aroma analysis, such as sensory evaluation and gas chromatography (GC), still face many restraints. Hence, there is a need for alternatives. We present a novel 14-unit multiplexed paper-based colorimetric sensor for fragrant sesame oil VOC analysis. The sensor was designed to visualize the VOC profile as a color "fingerprint". The sensor was validated with 55 branded sesame oil samples produced by two different techniques, i.e., hot pressing and small milling; the experimental results suggested a processing dependency in color VOC fingerprints. The sensor also demonstrated the potential to detect the change in sesame oil VOC profile due to blending with refined oil, with an estimated limit of detection down to 20% v/v of the refined oil. The colorimetric sensor might be used as a simple, rapid, and cost-effective analytical tool in the production and quality control of fragrant sesame oil.

Evaluation of the effect of Torulaspora delbrueckii on important volatile compounds in navel orange original brandy using E-nose combined with HS-SPME-GC-MS

Simultaneous inoculation of non-Saccharomyces cerevisiae during the alcoholic fermentation process has been found to be an effective strategy for enhancing wine flavor. This study aimed to investigate the effect of Torulaspora delbrueckii NCUF305.2 on the flavor of navel orange original brandy (NOOB) using E-nose combined with HS-SPME-GC-MS. The results showed a significant increase (p < 0.05) in the sensitivity of NOOB to W5C, W3C, W1S, and W3S sensors by mixed fermentation (MF). Esters in NOOB increased by 4.13%, while higher alcohols increased by 21.93% (p < 0.001), terpenes and others increased by 52.07% and 40.99% (p < 0.01), respectively. Notably, several important volatile compounds with relative odor activity values above 10 showed an increase. Sensory analysis revealed that a more pronounced citrus-like flavor and higher overall appearance scores were found in MF than in pure fermentation (PF). These findings offer valuable theoretical guidance for enhancing the quality of fruit brandies.

An overview of the detection methods to the edible oil oxidation degree: Recent progress, challenges, and perspectives

Oil oxidation, the main quality-deteriorated reaction, would significantly and negatively influence its quality and safety during processing and storage. Evaluating oil oxidation degree is an effective strategy to enable early warning and ensure food safety. Herein, principles, recent progresses, advantages and shortcomings, representative applications, current challenges and promising perspectives, and summary tables of traditional (titration), instrumental (chromatography and spectroscopy), and especially rapid detection methods (chemical colorimetric methods and portable miniaturized devices) for evaluating oil oxidation degree are presented and reviewed. It is believed that rapid detection methods are the most promising practical candidate for detecting oil oxidation. Also, the interaction between advanced data-processing techniques and detection methods, and the systematic integration of whole analytical processes is proposed as next-generation perspectives in the oil oxidation evaluation. We wish to provide the knowledge of oil oxidation degree determination and enlighten novel strategies.

Waste Point Identification of Frying Oil Based on Gas Chromatography-Ion Mobility Spectrometry (GC-IMS)

This study described the quality detection and rapid identification of frying oil waste points based on gas chromatography-ion mobility spectrometry (GC-IMS). A total of 48 volatile substances were identified, among which the levels of 11 components, including 2-pentylfuran, 2-butylfuran, and 2-hexanone, increased with prolonged frying time after 40 h in cottonseed oil. Conversely, the levels of hexanal, heptanal, and E,E-2,4-heptadienal decreased as frying time extended. Correlation analysis revealed a significant association between volatile substances of the oil and acid value (p < 0.05) and polar components with volatile substances (p < 0.05). Furthermore, significant differences in the types and contents of flavor substances were observed in cottonseed oil at different frying times (including before and after reaching the discard point) (p < 0.05). Subsequently, principal component analysis (PCA) results clearly showed that the cottonseed oil samples at different frying times were well distinguished by the volatile compounds; moreover, discriminant model analysis indicated a model accuracy rate of 100%. These results showed the potential of GC-IMS-based approaches in discriminating the waste points of frying oil.

Multifaceted analysis of the effects of roasting conditions on the flavor of fragrant Camellia oleifera Abel. seed oil

Fragrant Camellia oleifera Abel. seed oil (FCSO), produced by a roasting process, is popular for its characteristic aroma. This study investigated the effects of various roasting temperatures (90℃, 120℃, 150℃, 180℃) and durations (20 min, 40 min, 60 min) on the flavor of FCSO by physicochemical properties, hazardous substances, sensory evaluation, and flavor analyses. The results showed that FCSO roasted at 120℃/20 min had a reasonable fatty acid composition with a lower acid value (0.16 mg/g), peroxide value (0.13 g/100 g), p-anisidine value (2.27), dibutyl phthalate content (0.04 mg/kg), and higher 1,1-diphenyl-2-picrylhydrazyl free radical scavenging activity (224.51 μmol TE/kg) than other samples. A multivariate analysis of FCSO flavor revealed that the 120℃/20 min group had a higher grassy flavor score (5.3 score) from nonanoic acid and a lower off-flavor score (2.2 score) from 2-methylbutyric acid. The principal component analysis showed that 120℃/20 min could guarantee the best flavor and quality of FCSO. Therefore, this information can guide the preparation of FCSO.

Microwave pretreatment effects on the aroma precursors, sensory characteristics and flavor profiles of fragrant rapeseed oil

Microwave technology offers a rapid and uniform heating method. This study investigated how microwave pretreatment affects the aroma precursors and flavor of fragrant rapeseed oils (FROs). Microwave pretreatment led to decreased levels of polyunsaturated fatty acids, sugars, protein-bound amino acids, and glucosinolates. Using gas chromatography-mass spectrometry, we identified 66 volatile compounds in the oil samples. Among these, based on odor activity values (OAV ≥ 1), we found 9 aldehydes, 1 ketone, 6 pyrazines, 1 isothiocyanate, and 7 nitriles as the key aroma-active compounds, contributing fatty-like, nutty-like, and pungent-like odors, respectively. The electronic nose results highlighted W5S and W1W as primary sensors for determining the flavor profiles of FROs. Notably, aroma-active pyrazines exhibited strong negative correlations with sucrose, cysteine, lysine, and isoleucine. This research provides essential insights for enhancing the aroma of FROs.

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.

Vegetable oils: Classification, quality analysis, nutritional value and lipidomics applications

Lipids are widespread in nature and play a pivotal role as a source of energy and nutrition for the human body. Vegetable oils (VOs) constitute a significant category in the food industry, containing various lipid components that have garnered attention for being natural, environmentally friendly and health-promoting. The review presented the classification of raw materials (RMs) from oil crops and quality analysis techniques of VOs, with the aim of improving comprehension and facilitating in-depth research of VOs. Brief descriptions were provided for four categories of VOs, and quality analysis techniques for both RMs and VOs were generalized. Furthermore, this study discussed the applications of lipidomics technology in component analysis, processing and utilization, quality determination, as well as nutritional function assessment of VOs. Through reviewing RMs and quality analysis techniques of VOs, this study aims to encourage further refinement and development in the processing and utilization of VOs, offering valuable references for theoretical and applied research in food chemistry and food science.

Influence of the Degree of Fruitiness on the Quality Assessment of Virgin Olive Oils Using Electronic Nose Technology

The electronic nose is a non-invasive technology suitable for the analysis of edible oils. One of the practical applications in the olive oil industry is the classification of virgin oils based on their sensory characteristics. Notwithstanding that this technology, at this stage, cannot realistically replace the currently used methods, it is fruitful for a preliminary analysis of the oil quality. This work makes use of this technology to develop a methodology for the detection of the threshold by which an extra-virgin olive oil (EVOO) drops into the virgin olive oil (VOO) category. With this aim, two features were studied: the level of fruitiness level and the type of defect. The results showed a greater influence of the level of fruitiness than the type of defect in the determination of the detection threshold. Furthermore, three of the sensors (S2, S7 and S9) of the commercial e-nose PEN3 were identified as the most discriminating in the classification between EVOO and VOO oils.

Rapid quantitative authentication and analysis of camellia oil adulterated with edible oils by electronic nose and FTIR spectroscopy

Camellia oil, recognized as a high-quality edible oil endorsed by the Food and Agriculture Organization, is confronted with authenticity issues arising from fraudulent adulteration practices. These practices not only pose health risks but also lead to economic losses. This study proposes a novel machine learning framework, referred to as a transformer encoder backbone with a support vector machine regressor (TES), coupled with an electronic nose (E-nose), for detecting varying adulteration levels in camellia oil. Experimental results indicate that the proposed TES model exhibits the best performance in identifying the adulterated concentration of camellia oi, compared with five other machine learning models (the support vector machine, random forest, XGBoost, K-nearest neighbors, and backpropagation neural network). The results obtained by E-nose detection are verified by complementary Fourier transform infrared (FTIR) spectroscopy analysis for identifying functional groups, ensuring accuracy and providing a comprehensive assessment of the types of adulterants. The proposed TES model combined with E-nose offers a rapid, effective, and practical tool for detecting camellia oil adulteration. This technique not only safeguards consumer health and economic interests but also promotes the application of E-nose in market supervision.

Fabrication and characterization of a novel zein/pectin/pumpkin seed oil Pickering emulsion and the effects of myricetin on oxidation stability

In this study, zein/pectin/pumpkin seed oil (PSO) Pickering emulsions (ZPPEs) were fabricated loading with myricetin (MYT), and the quality control methods of oxidation stability were innovatively investigated. The microstructure and particle properties of zein-pectin particles were determined. The zein to pectin ratio of 5:3 and oil phase fraction (φ = 50 %) turned out as the most optimal conditions for the stabilization of myricetin-loaded ZPPEs. The expected oil-in-water emulsion-type structure was confirmed by confocal laser scanning microscopy (CLSM). The internal 3D structure of Pickering emulsions (Lugol's solution improved the water-phase contrast) was imaged by micro-computed tomography (Micro-CT) for the first time. Results showed a sponge like structure of water phase in emulsion with 42 μm as mean droplet size. Light-induced oxidation was evaluated with the PetroOxy method and malondialdehyde (MDA) assays. Encapsuling ZPPEs with MYT could prevent the light induced oxidation, especially, loading of MYT at the core of the emulsion. The analysis of Electronic nose (E-nose) was used to analyze the odor before and after UV-induced oxidation, and showed a good discrimination. This study provided a new approach to prepare ZPPEs with high oxidation stability. Micro-CT, PetroOxy and E-nose could be new methods for characterization and quality assessment of Pickering emulsions.

Development of an Innovative Optoelectronic Nose for Detecting Adulteration in Quince Seed Oil

In this study, an innovative odor imaging system capable of detecting adulteration in quince seed edible oils mixed with sunflower oil and sesame oil based on their volatile organic compound (VOC) profiles was developed. The system comprises a colorimetric sensor array (CSA), a data acquisition unit, and a machine learning algorithm for identifying adulterants. The CSA was created using a method that involves applying a mixture of six different pH indicators (methyl violet, chlorophenol red, Nile blue, methyl orange, alizarin, cresol red) onto a Thin Layer Chromatography (TLC) silica gel plate. Subsequently, difference maps were generated by subtracting the "initial" image from the "final" image, with the resulting color changes being converted into digital data, which were then further analyzed using Principal Component Analysis (PCA). Following this, a Support Vector Machine was employed to scrutinize quince seed oil that had been adulterated with varying proportions of sunflower oil and sesame oil. The classifier was progressively supplied with an increasing number of principal components (PCs), starting from one and incrementally increasing up to five. Each time, the classifier was optimized to determine the hyperparameters utilizing a random search algorithm. With one to five PCs, the classification error accounted for a range of 37.18% to 1.29%. According to the results, this novel system is simple, cost-effective, and has potential applications in food quality control and consumer protection.

Protective mechanism of fruit vinegar polyphenols against AGEs-induced Caco-2 cell damage

Accumulation of advanced glycation end products (AGEs) is linked with development or aggravation of many degenerative processes or disorders. Fruit vinegars are rich in polyphenols that can be a good dietary source of AGEs inhibitors. In this study, eight kinds of vinegars were prepared. Among them, the highest polyphenol and flavonoid content were orange vinegar and kiwi fruit vinegar, respectively. Ferulic acid, vanillic acid, chlorogenic acid, p-coumaric acid, caffeic acid, catechin, and epicatechin were main polyphenols in eight fruit vinegars. Then, we measured the inhibitory effect of eight fruit vinegars on fluorescent AGEs, and found that orange vinegar had the highest inhibitory rate. Data here suggested that orange vinegar and its main components catechin, epicatechin, and p-coumaric acid could effectively reduce the level of ROS, RAGE, NADPH and inflammatory factors in Caco-2 cells. Our research provided theoretical basis for the application of orange vinegar as AGEs inhibitor.

A dedicated electronic nose combined with chemometric methods for detection of adulteration in sesame oil

Sesame oil (SO), one of the most popular and expensive edible oils, is prone to adulteration. In this study, the fatty acid profiles of pure sesame seed oil and samples adulterated with two less expensive edible oils (canola and sunflower) were analyzed using Gas Chromatography. A dedicated e-nose system was developed and tested on 15 mixtures of sesame-canola and sesame-sunflower samples. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Multi-Layered Perceptron (MLP) methods were utilized to identify adulteration through the evaluation of Volatile Organic Compound. Result of chromatography showed that most samples of sesame oil containing impurities at levels less than 30% were recognized incorrectly in the standard range of SO fatty acids. This is while the developed e-nose system was able to detect adulteration at much lower levels. According to the results, PCA and LDA methods can describe the data set variance with precision of 95.6% and 97%, respectively. The MLP model had better results compared to PCA and LDA, with high determination coefficient (R2 = 0.981) and low RMSE (0.0178). Results indicate that the e-nose system provided an effective non-destructive method to detect SO adulteration at levels as low as 5%, which GC was unable to detect.

Aromatic Fingerprints: VOC Analysis with E-Nose and GC-MS for Rapid Detection of Adulteration in Sesame Oil

Food quality assurance is an important field that directly affects public health. The organoleptic aroma of food is of crucial significance to evaluate and confirm food quality and origin. The volatile organic compound (VOC) emissions (detectable aroma) from foods are unique and provide a basis to predict and evaluate food quality. Soybean and corn oils were added to sesame oil (to simulate adulteration) at four different mixture percentages (25-100%) and then chemically analyzed using an experimental 9-sensor metal oxide semiconducting (MOS) electronic nose (e-nose) and gas chromatography-mass spectroscopy (GC-MS) for comparisons in detecting unadulterated sesame oil controls. GC-MS analysis revealed eleven major VOC components identified within 82-91% of oil samples. Principle component analysis (PCA) and linear detection analysis (LDA) were employed to visualize different levels of adulteration detected by the e-nose. Artificial neural networks (ANNs) and support vector machines (SVMs) were also used for statistical modeling. The sensitivity and specificity obtained for SVM were 0.987 and 0.977, respectively, while these values for the ANN method were 0.949 and 0.953, respectively. E-nose-based technology is a quick and effective method for the detection of sesame oil adulteration due to its simplicity (ease of application), rapid analysis, and accuracy. GC-MS data provided corroborative chemical evidence to show differences in volatile emissions from virgin and adulterated sesame oil samples and the precise VOCs explaining differences in e-nose signature patterns derived from each sample type.

Effects of blackberry polysaccharide on the quality improvement of boiled chicken breast

Blackberry polysaccharide was isolated from blackberry powder with 70% ethanol. The crude polysaccharide was composed of 95.44% glucose, 2.01% arabinose, 1.81% galactose and 0.74% glucuronic acid. Chicken breast meat was only marinated with different concentrations of the isolated blackberry polysaccharide (1 g/kg, 3 g/kg) for 24 h at a ratio of material to liquid of 1:3, and boiled at 80℃ for 1 h. The differences in texture, water distribution and volatile flavor components among different groups （adding 0,1,3 g/kg blackberry polysaccharide) were investigated. The results showed that the addition of blackberry polysaccharide could significantly improve the hardness of chicken breast, the transformation of free water to bound water, the overall flavor characteristics of the control group and the addition of different concentrations of blackberry polysaccharide were significantly different, and the concentration of volatile flavor substances in boiled chicken breast was reduced.

Determination of oxidative deterioration in edible oils by high-pressure photoionization time-of-flight mass spectrometry

Since lipid oxidation often causes serious food safety issues worldwide, determination of oil's oxidative deterioration becomes quite significant, which still calls for efficient analytical methods. In this work, high-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) was firstly introduced for rapid detection of oxidative deterioration in edible oils. Through non-targeted qualitative analysis, oxidized oils with various oxidation levels were successfully discriminated for the first time by coupling HPPI-TOFMS with the orthogonal partial least squares discriminant analysis (OPLS-DA). Furthermore, by targeted interpretation of the HPPI-TOFMS mass spectra and the subsequent regression analysis (signal intensities vs TOTOX values), good linear correlations were observed for several predominant VOCs. Those specific VOCs were promising oxidation indicators, which would play important roles as TOTOX to judge the oxidation states of tested samples. The proposed HPPI-TOFMS methodology can be used as an innovative tool for accurate and effective assessment of lipid oxidation in edible oils.

Comparative Analysis of Acanthopanacis Cortex and Periplocae Cortex Using an Electronic Nose and Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis

Chinese Herbal Medicines (CHMs) can be identified by experts according to their odors. However, the identification of these medicines is subjective and requires long-term experience. The samples of Acanthopanacis Cortex and Periplocae Cortex used were dried cortexes, which are often confused in the market due to their similar appearance, but their chemical composition and odor are different. The clinical use of the two herbs is different, but the phenomenon of being confused with each other often occurs. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two species for fast and robust discrimination, in order to provide a scientific basis for avoiding confusion and misuse in the process of production, circulation and clinical use. In this study, the odor and volatile components of these two medicinal materials were detected by the E-nose and by gas chromatography-mass spectrometry (GC-MS), respectively. An E-nose combined with pattern analysis methods such as principal component analysis (PCA) and partial least squares (PLS) was used to discriminate the cortex samples. The E-nose was used to determine the odors of the samples and enable rapid differentiation of Acanthopanacis Cortex and Periplocae Cortex. GC-MS was utilized to reveal the differences between the volatile constituents of Acanthopanacis Cortex and Periplocae Cortex. In all, 82 components including 9 co-contained components were extracted by chromatographic peak integration and matching, and 24 constituents could be used as chemical markers to distinguish these two species. The E-nose detection technology is able to discriminate between Acanthopanacis Cortex and Periplocae Cortex, with GC-MS providing support to determine the material basis of the E-nose sensors' response. The proposed method is rapid, simple, eco-friendly and can successfully differentiate these two medicinal materials by their odors. It can be applied to quality control links such as online detection, and also provide reference for the establishment of other rapid detection methods. The further development and utilization of this technology is conducive to the further supervision of the quality of CHMs and the healthy development of the industry.

Analysis of the trend of volatile compounds by HS-SPME-GC-MS and the main factors affecting the formation of rancid odor during the oxidation process of infant nutrition package

In this study, headspace solid-phase micro-extraction (HS-SPME) coupled with GC-MS was used to analyze the trend of volatile compounds in fresh and oxidative infant nutrition package. Among the volatile compounds, aldehydes and ketones, alcohols, lipids, cycloalkenes, alkanes, alkenes, aromatic hydrocarbons, oxygenated compound were identified. A total of 65 volatile compounds were detected in the fresh nutrition package, whereas 9 new volatile compounds were detected during the accelerated oxidation process, which was oxidized at 45 °C for 4 weeks. The main components of the rancid flavor formed and the relative content of volatile substances gradually changed during the accelerated oxidation process. The volatile substances hexanal, nonanal, and 2-pentylfuran substantially increased. Linalool, α-terpineol, d-limonene, and 1-methoxy-nonane presented an evidently downward trend. The relative content of the newly formed compound 3-hydroxy-2-methylpyran-4-one during the oxidation process was always large, its relative content initially increased, then decreased, and finally increased again. The formation of rancid flavor of the nutrient package was speculated to have been formed by the interaction of hexanal, nonanal, 2-pentylfuran, and 3-hydroxy-2-methylpyran-4-one.

Dynamics of Bacterial Composition and Association with Quality Formation and Biogenic Amines Accumulation during Fish Sauce Spontaneous Fermentation

High-throughput sequencing and high-pressure liquid chromatography (HPLC) methods were used to investigate the influences of microbial dynamics on the quality and biogenic amine (BA) content during fish sauce fermentation. The homogeneity of total viable bacteria and lactic acid bacteria in fish sauce becomes higher as fermentation progresses. Tetragenococcus was the key genus of fish sauce fermentation. Carnobacterium (38.43%) and Lentibacillus (41.01%) were the dominant genera in the samples fermented for 3 months and 18 months, respectively. These three bacterial genera were significantly related to the physicochemical characteristics and characteristic flavors of the sauces. Tetragenococcus was significantly positively correlated with nitrogen oxides, the main characteristic flavor components in fish sauce. The BA content in fish sauce fermentation increased from 106.88 to 376.03 mg/kg, and the content of histamine reached 115.30 mg/kg at the end of fermentation, indicating that fish sauce has health risks. About 66.67% of Lentibacillus isolates were able to produce a large amount of BA, suggesting that Lentibacillus was the key genus for BA accumulation in fish sauce fermentation. Research on reducing the content of BA in fish sauce by intervening with regard to the fermentation temperature showed that a safe fish sauce product could be obtained at the fermentation temperature of about 25°C. These results help us to understand the contribution of microbial community composition to fish sauce fermentation and provide a basis for improving the quality and safety of fermented fish sauce. IMPORTANCE Traditional fermentation of fish sauce is mainly carried out by complex microbial communities from raw anchovies and processing environments. However, it is still unclear how the environmental microbiota influences the quality and the safety of fish sauce products. Therefore, this study comprehensively explained the influence of microorganisms on the quality and safety of fish sauce during the fermentation process in terms of physicochemical characters, flavors, and BA. Additionally, the accumulation of BA in fish sauce fermentation was controlled by intervening in the fermentation temperature. This finding contributes to a deeper understanding of the role of environmental microbiota during fermentation and provides data support for improving the safety of fish sauce.

Impacts of salt-tolerant Staphylococcus nepalensis 5-5 on bacterial composition and biogenic amines accumulation in fish sauce fermentation

High levels of biogenic amines (BAs) in fermented food can present a health risk to consumers. Microorganisms that can reduce BAs are widely used in fermented foods. However, the mechanism by which microorganisms reduce BAs in foods has not been explored. In this study, we investigated how Staphylococcus nepalensis 5-5 (S. nepalensis 5-5), which was a BA-degrading strain isolated from fish sauce, could reduce BA accumulation in the fish sauce. High-throughput sequencing and HPLC methods were sequentially used to determine the microbial community structure and BA content in fish sauce with/without S. nepalensis 5-5. The results showed that S. nepalensis 5-5 might be a safe strain that could improve the flavor of fish sauce while still exhibiting good BA degradation ability under a high salt environment. The content of BAs in fish sauce inoculated with S. nepalensis 5-5 was significantly decreased compared with the control fish sauce, achieving maximal reductions of 15.74, 14.18 and 16.65% in putrescine, cadaverine and histamine accumulation, respectively. According to high-throughput sequencing data, S. nepalensis 5-5 reduced the abundance of the genera positively associated with BAs, while increasing the number of bacterial genera negatively correlated with BAs in the sample and changed the correlation between some genera and BAs via species interaction. In addition, analysis of amino acid metabolism showed that S. nepalensis 5-5 might use histidine to produce metabolites other than histamine, thereby reducing the production of BAs. These findings not only explained the mechanisms by which the BA level in fish sauce could be reduced but also provided a potential means to control BA production in the fish sauce during the fermentation stage.

A feasibility study for rapid evaluation of emulsion oxidation using synchronous fluorescence spectroscopy coupled with chemometrics

A rapid method based on three-dimensional synchronous fluorescence spectroscopy was developed for emulsion oxidation evaluation. This method was selected because of its high sensitivity to dissolved organic matter typically occurring in the lipid oxidation. Spectral signal and chemical reference measurements were recorded for each emulsion sample as input and output data for the model construction. Characteristic values were extracted from the spectral data by the application of parallel factor (PARAFAC) analysis. Partial least squares regression (PLSR) was then used to construct a regression model for the rapid determination of emulsion oxidation. The correlation coefficient of the calibration and prediction sets were used as the performance parameters for the PLSR models as follows: R = 0.929, 0.973 for emulsion samples stored at 25℃; R = 0.897, 0.903 for emulsion samples stored at 70℃. The overall results demonstrated that the fluorescence spectroscopy, coupled with PARAFAC and PLSR algorithms, could be successfully used as a rapid method for the emulsion oxidation evaluation.

Mechanism, indexes, methods, challenges, and perspectives of edible oil oxidation analysis

Edible oils are indispensable food components, because they are used for cooking or frying. However, during processing, transport, storage, and consumption, edible oils are susceptible to oxidation, during which various primary and secondary oxidative products are generated. These products may reduce the nutritional value and safety of edible oils and even harm human health. Therefore, analyzing the oxidation of edible oil is essential to ensure the quality and safety of oil. Oxidation is a complex process with various oxidative products, and the content of these products can be evaluated by corresponding indexes. According to the structure and properties of the oxidative products, analytical methods have been employed to quantify these products to analyze the oxidation of oil. Combined with proper chemometric analytical methods, qualitative identification has been performed to discriminate oxidized and nonoxidized oils. Oxidative products are complex and diverse. Thus, proper indexes and analytical methods should be selected depending on specific research objectives. Expanding the mechanism of the correspondence between oxidative products and analytical methods is crucial. The underlying mechanism, conventional indexes, and applications of analytical methods are summarized in this review. The challenges and perspectives for future applications of several methods in determining oxidation are also discussed. This review may serve as a reference in the selection, establishment, and improvement of methods for analyzing the oxidation of edible oil. HighlightsThe mechanism of edible oil oxidation analysis was elaborated.Conventional oxidation indexes and their limited values were discussed.Analytical methods for the determination of oxidative products and qualitative identification of oxidized and non-oxidized oils were reviewed.

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

Cv. Arbequina extra virgin olive oils (EVOO) were flavored with cinnamon, garlic, and rosemary and characterized. Although flavoring significantly affected the physicochemical quality parameters, all oils fulfilled the legal thresholds for EVOO classification. Flavoring increased (20 to 40%) the total phenolic contents, whereas oxidative stability was dependent on the flavoring agent (a slight increase for rosemary and a decrease for cinnamon and garlic). Flavoring also had a significant impact on the sensory profiles. Unflavored oils, cinnamon, and garlic flavored oils had a fruity-ripe sensation while rosemary flavored oils were fruity-green oils. Fruit-related sensations, perceived in unflavored oils, disappeared with flavoring. Flavoring decreased the sweetness, enhanced the bitterness, and did not influence the pungency of the oils. According to the EU regulations, flavored oils cannot be commercialized as EVOO. Thus, to guarantee the legal labelling requirement and to meet the expectations of the market-specific consumers for differentiated olive oils, a lab-made electronic nose was applied. The device successfully discriminated unflavored from flavored oils and identified the type of flavoring agent (90 ± 10% of correct classifications for the repeated K-fold cross-validation method). Thus, the electronic nose could be used as a practical non-destructive preliminary classification tool for recognizing olive oils’ flavoring practice.

Optimization of Electronic Nose Sensor Array for Tea Aroma Detecting Based on Correlation Coefficient and Cluster Analysis

The electronic nose system is widely used in tea aroma detecting, and the sensor array plays a fundamental role for obtaining good results. Here, a sensor array optimization (SAO) method based on correlation coefficient and cluster analysis (CA) is proposed. First, correlation coefficient and distinguishing performance value (DPV) are calculated to eliminate redundant sensors. Then, the sensor independence is obtained through cluster analysis and the number of sensors is confirmed. Finally, the optimized sensor array is constructed. According to the results of the proposed method, sensor array for green tea (LG), fried green tea (LF) and baked green tea (LB) are constructed, and validation experiments are carried out. The classification accuracy using methods of linear discriminant analysis (LDA) based on the average value (LDA-ave) combined with nearest-neighbor classifier (NNC) can almost reach 94.44~100%. When the proposed method is used to discriminate between various grades of West Lake Longjing tea, LF can show comparable performance to that of the German PEN2 electronic nose. The electronic nose SAO method proposed in this paper can effectively eliminate redundant sensors and improve the quality of original tea aroma data. With fewer sensors, the optimized sensor array contributes to the miniaturization and cost reduction of the electronic nose system.

E-Nose and Olfactory Assessment: Teamwork or a Challenge to the Last Data? The Case of Virgin Olive Oil Stability and Shelf Life

Electronic nose (E-nose) devices represent one of the most trailblazing innovations in current technological research, since mimicking the functioning of the biological sense of smell has always represented a fascinating challenge for technological development applied to life sciences and beyond. Sensor array tools are right now used in a plethora of applications, including, but not limited to, (bio-)medical, environmental, and food industry related. In particular, the food industry has seen a significant rise in the application of technological tools for determining the quality of edibles, progressively replacing human panelists, therefore changing the whole quality control chain in the field. To this end, the present review, conducted on PubMed, Science Direct and Web of Science, screening papers published between January 2010 and May 2021, sought to investigate the current trends in the usage of human panels and sensorized tools (E-nose and similar) in the food industry, comparing the performances between the two different approaches. In particular, the focus was mainly addressed towards the stability and shelf life assessment of olive oil, the main constituent of the renowned “Mediterranean diet”, and nowadays appreciated in cuisines from all around the world. The obtained results demonstrate that, despite the satisfying performances of both approaches, the best strategy merges the potentialities of human sensory panels and technological sensor arrays, (i.e., E-nose somewhat supported by E-tongue and/or E-eye). The current investigation can be used as a reference for future guidance towards the choice between human panelists and sensorized tools, to the benefit of food manufacturers.

Microwave pretreatment of camellia (Camellia oleifera Abel.) seeds: Effect on oil flavor

Microwave is a new pretreatment technology, and microwave processing time of camellia seeds is a factor affecting the flavor of camellia seed oil (CSO). Therefore, this study on the characteristic volatile compounds of CSO from microwaved seeds with different processing time was carried out by electronic nose (E-nose), headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The results of E-nose show that W1W, W2W and W5S were the main sensors to distinguish the flavor profile of CSOs. Through HS-SPME-GC-MS and odor activity value analysis, 80 volatile compounds were detected and 22 key aroma compounds were screened in CSOs. Compared with HS-SPME-GC-MS, 44 volatile compounds were detected by HS-GC-IMS, including 9 identical compounds and 35 different compounds. In general, the volatile compounds of 0, 2 and 3 min CSOs were mainly alcohols and esters, while the 4, 5 and 6 min CSOs were mainly heterocycles and aldehydes.

Qualitative identification of the edible oil storage period using a homemade portable electronic nose combined with multivariate analysis

BACKGROUND

The edible oil storage period is one of the important indicators for evaluating the intrinsic quality of edible oil. The present study aimed to develop a portable electronic nose device for the qualitative identification of the edible oil storage period. First, four metal oxide semiconductor gas sensors, comprising TGS2600, TGS2611, TGS2620 and MQ138, were selected to prepare a sensor array to assemble a portable electronic nose device. Second, the homemade portable electronic nose device was used to obtain the odor change information of edible oil samples during different storage periods, and the sensor features were extracted. Finally, three pattern recognition methods, comprising linear discriminant analysis (LDA), K-nearest neighbors (KNN) and support vector machines (SVM), were compared to establish a qualitative identification model of the edible oil storage period. The input features and related parameters of the model were optimized by a five-fold cross-validation during the process of model establishment.

RESULTS

The research results showed that the recognition performance of the non-linear SVM model was significantly better than that of the linear LDA and KNN models, especially in terms of generalization performance, which had a correct recognition rate of 100% when predicting independent samples in the prediction set.

CONCLUSION

The overall results demonstrate that it is feasible to apply the homemade portable electronic nose device with the help of the appropriate pattern recognition methods to achieve the fast and efficient identification of the edible oil storage period, which provides an effective analysis tool for the quality detection of the edible oil storage. © 2020 Society of Chemical Industry.

Chemosensory Device Assisted-Estimation of the Quality of Edible Oils with Repetitive Frying

This study investigated chemosensory degradations of soybean and canola oils with repeated frying in order to estimate the quality of the oils. Methods: Chemical parameters including oxygen induction time, acid value, p-anisidine value, malondialdehyde, and total polar compounds were measured. Electronic nose and electronic tongue analyses were performed to assess sensory properties. Multivariate analyses were employed to investigate relationships among tastes and volatile compounds using principal component analysis (PCA) and Pearson’s correlation analysis. Results: All chemical parameters increased with repeated frying in both oils. Electronic nose analysis found ethyl butyrate, 2-heptenal, and 2,4-pentanedione as major volatiles for soybean oil and ethyl butyrate and linalool for canola oil. As the numbers of frying increased, all volatiles showed an increased concentration in various extents. In multivariate analyses, ethyl butyrate revealed strong positive correlations with sourness, umami, and sweetness, and umami showed strong positive correlations with sourness and saltiness (p < 0.05). PCA confirmed that in PC1 with 49% variance, sourness, saltiness, and umami were at similar rates while acetyl pyrazine, 2,4-pentadieone, and 1-octanol were found at similar rates. Canola oil was chemically more stable and less susceptible to deterioration in all chemical parameters compared to soybean oil, resulting in a relatively better quality oil when repeatedly fried. Conclusion: The results suggested that minimum repeated frying (5 times) degrades chemosensory characteristics of both oils, thereby compromising their quality. The findings of this study will be utilized as a foundation for quality control of fried foods in food industry, fried food development, and fast-food industry.

Influence of Two Innovative Packaging Materials on Quality Parameters and Aromatic Fingerprint of Extra-Virgin Olive Oils

The performance of two innovative packaging materials was investigated on two Sardinian extra-virgin olive oils (Nera di Gonnos and Bosana). In particular, a transparent plastic film loaded with a UV-blocker (packaging B) and a metallized material (packaging C) were compared each other and to brown-amber glass (packaging A). During accelerated shelf-life tests at 40 and 60 °C, the evolution of quality parameters (i.e., acidity, peroxide value, K₂₇₀, and phenolic content) was monitored, together with the aromatic fingerprint evaluated by electronic nose. Packaging B resulted in the best-performing material in protecting oil from oxidation, due to its lower oxygen transmission rate (0.1 ± 0.02 cm³/m² 24 h) compared to packaging C (0.23 ± 0.04 cm³/m² 24 h). At the end of storage, phenolic reduction was on average 25% for packaging B and 58% for packaging C, and the aromatic fingerprint was better preserved in packaging B. In addition, other factors such as the sanitary status of the olives at harvesting and the storage temperature were demonstrated to have a significant role in the shelf life of packaged extra-virgin olive oil.

Analytical methods for determining the peroxide value of edible oils: A mini-review

Edible oils are prone to oxidation during processing and storage that may negatively affect the oil quality and human health. Determining the peroxide value (PV) of edible oils is essential because PV is one of the most typically used quality parameters to monitor lipid oxidation and control oil quality. Many approaches have been developed to determine the PV of oils. Among them, iodometric titration is the commonly used method for PV determination. Considering the limitations related to titrimetric methods, such as time and environmental concerns, several instrumental techniques have been considered as reliable alternatives. The advantages and limitations of classical titration and instrumental methods are summarized in this review. The prospects and reformative aspects for the future applications of these approaches in PV determination are also discussed.

Novel Nondestructive Biosensors for the Food Industry

An increasing number of foodborne outbreaks, growing consumer desire for healthier products, and surging numbers of food allergy cases necessitate strict handling and screening of foods at every step of the food supply chain. Current standard procedures for detecting food toxins, contaminants, allergens, and pathogens require costly analytical devices, skilled technicians, and long sample preparation times. These challenges can be overcome with the use of biosensors because they provide accurate, rapid, selective, qualitative, and quantitative detection of analytes. Their ease of use, low-cost production, portability, and nondestructive measurement techniques also enable on-site detection of analytes. For this reason, biosensors find many applications in food safety and quality assessments. The detection mechanisms of biosensors can be varied with the use of different transducers, such as optical, electrochemical, or mechanical. These options provide a more appropriate selection of the biosensors for the intended use. In this review, recent studies focusing on the fabrication of biosensors for food safety or food quality purposes are summarized. To differentiate the detection mechanisms, the review is divided into sections based on the transducer type used.