On-line assessment of oil quality during deep frying using an electronic nose and proton transfer reaction mass spectrometry

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.

Olfactory system-inspired electronic nose system using numerous low-cost homogenous and hetrogenous sensors

This paper presents an electronic nose system inspired by the biological olfactory system. When comparing the human olfactory system to that of a dog, it's worth noting that dogs have 30 times more olfactory receptors and three times as many types of olfactory receptors. This implies that the number of olfactory receptors could be a more important parameter for classifying chemical compounds than the number of receptor types. Instead of using expensive precision sensors, the proposed electronic nose system relies on numerous low-cost homogeneous and heterogeneous sensors with poor cross-interference characteristics due to their low gas selectivity. Even if the same type of sensor shows a slightly different output for the same chemical compound, this variation becomes a unique signal for the target gas being measured. The electronic nose system comprises 30 sensors, the e-nose had 6 differing sensors with 5 replicates of each type. The characteristics of the electronic nose system are evaluated using three different volatile alcoholic compounds, more than 99% of which are the same. Liquid samples are supplied to the sensor chamber for 60 seconds using an air bubbler, followed by a 60-second cleaning of the chamber. Sensor signals are acquired at a sampling rate of 100 Hz. In this experimental study, the effects of data preprocessing methods and the number of sensors of the same type are investigated. By increasing the number of sensors of the same type, classification accuracy exceeds 99%, regardless of the deep learning model. The proposed electronic nose system, based on low-cost sensors, demonstrates similar results to commercial expensive electronic nose systems.

Online Exploring the Gaseous Oil Fumes from Oleic Acid Thermal Oxidation by Synchrotron Radiation Photoionization Mass Spectrometry

Cooking oil fumes are an intricate and dynamic mixture containing a variety of poisonous and hazardous substances, and their real-time study remains challenging. Based on tunable synchrotron radiation photoionization mass spectrometry (SR-PIMS), isomeric/isobaric compounds in the gaseous oil fumes from oleic acid thermal oxidation were determined in real time and distinguished by photoionization efficiency (PIE) curve simulation combined with multiple linear regression (MLR) analysis. A series of common carcinogens such as formaldehyde, acetaldehyde, acrolein, and several unreported chemicals including diethyl ether and formylcyclohexane were successfully characterized. Moreover, time-resolved profiles of certain components in gaseous oil fumes were monitored for 55 h. Distinct evolutionary processes were observed, indicating the consumption and formation of parent molecules, intermediates, and final products.

Study on the thermal oxidation of oleic, linoleic and linolenic acids by synchrotron radiation photoionization mass spectrometry

RATIONALE

Cooking oil fumes contain numerous hazardous and carcinogenic chemicals, posing potential threats to human health. However, the sources of these species remain ambiguous, impeding health risk assessment, pollution control and mechanism research.

METHODS

To address this issue, the thermal oxidation of three common unsaturated fatty acids (UFAs), namely oleic, linoleic and linolenic acids, present in vegetable oils was investigated. The volatile and semi-volatile products were comprehensively characterized by online synchrotron radiation photoionization mass spectrometry (SR-PIMS) with two modes, which were validated and complemented using offline gas chromatography (GC)/MS methods. Tunable SR-PIMS combined with photoionization efficiency curve simulation enabled the recognition of isomers/isobars in gaseous fumes.

RESULTS

SR-PIMS revealed over 100 products, including aldehydes, alkenes, furans, aromatic hydrocarbons, etc., such as small molecules of formaldehyde, acetaldehyde, acrolein, ethylene and furan, which are not readily detected by conventional GC/MS; and some unreported fractions, e.g. ketene, 4-ethylcyclohexene and cycloundecene(E), were also observed. Furthermore, real-time monitoring of product emissions during the thermal oxidation of the three UFAs via SR-PIMS revealed that linolenic acid may be the major source of acrolein.

CONCLUSION

SR-PIMS has been demonstrated as a powerful technique for online investigation of cooking oil fumes. This study achieved comprehensive characterization of volatile and semi-volatile products from the thermal oxidation of oleic, linoleic and linolenic acids, facilitating the traceability of species in cooking fumes and aiding in exploring the thermal reactions of different vegetable oils.

Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination

This study presents a comprehensive literature review that investigates the distinctions between true and false cinnamon. Given the intricate compositions of essential oils (EOs), various discrimination approaches were explored to ensure quality, safety, and authenticity, thereby establishing consumer confidence. Through the utilization of physical-chemical and instrumental analyses, the purity of EOs was evaluated via qualitative and quantitative assessments, enabling the identification of constituents or compounds within the oils. Consequently, a diverse array of techniques has been documented, encompassing organoleptic, physical, chemical, and instrumental methodologies, such as spectroscopic and chromatographic methods. Electronic noses (e-noses) exhibit significant potential for identifying cinnamon adulteration, presenting a rapid, non-destructive, and cost-effective approach. Leveraging their capability to detect and analyze volatile organic compound (VOC) profiles, e-noses can contribute to ensuring authenticity and quality in the food and fragrance industries. Continued research and development efforts in this domain will assuredly augment the capacities of this promising avenue, which is the utilization of Artificial Intelligence (AI) and Machine Learning (ML) algorithms in conjunction with spectroscopic data to combat cinnamon adulteration.

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.

Characterization of Polyphenol and Volatile Fractions of Californian-Style Black Olives and Innovative Application of E-nose for Acrylamide Determination

Californian-style black olives require a sterilization treatment that produces a carcinogenic contaminant, acrylamide. Thus, this compound was evaluated in two different olive cultivars using an electronic nose (E-nose). The sterilization intensity had a significant influence on the final phenol concentrations, acrylamide content, and volatile compounds. Increasing the sterilization intensity from 10 to 26 min (F0) reduced the phenol content, but it promoted acrylamide synthesis, leading to a wide range of this toxic substance. The Ester and phenol groups of volatile compounds decreased their content when the sterilization treatment increased; however, aldehyde and other volatile compound groups significantly increased their contents according to the thermal treatments. The compounds 4-ethenyl-pyridine, benzaldehyde, and 2,4-dimethyl-hexane are volatile compounds with unpleasant odours and demonstrated a high amount of influence on the differences found after the application of the thermal treatments. The “Manzanilla Cacereña” variety presented the highest amount of phenolic compounds and the lowest acrylamide content. Finally, it was found that acrylamide content is correlated with volatile compounds, which was determined using multiple linear regression analysis (R² = 0.9994). Furthermore, the aroma of table olives was analysed using an E-nose, and these results combined with Partial Least Square (PLS) were shown to be an accurate method (range to error ratio (RER) >10 and ratio of performance to deviation (RPD) >2.5) for the indirect quantification of this toxic substance.

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.

Formation of Secondary and Tertiary Volatile Compounds Resulting from the Lipid Oxidation of Rapeseed Oil

The lipid oxidation of fats and oils leads to volatile organic compounds, having a decisive influence on the sensory quality of foods. To understand formation and degradation pathways and to evaluate the suitability of lipid-derived aldehydes as marker substances for the oxidative status of foods, the formation of secondary and tertiary lipid oxidation compounds was investigated with gas chromatography in rapeseed oils. After 120 min, up to 65 compounds were detected. In addition to secondary degradation products, tertiary products such as alkyl furans, ketones, and aldol condensation products were also found. The comparison of rapeseed oils, differing in their initial peroxide values, showed that the formation rate of secondary compounds was higher in pre-damaged oils. Simultaneously, a faster degradation, especially of unsaturated aldehydes, was observed. Consequently, the formation of tertiary products (e.g., alkyl furans, aldol adducts) from well-known lipid oxidation products (i.e., propanal, hexanal, 2-hexenal, and 2-nonenal) was investigated in model systems. The experiments showed that these compounds form the new substances in subsequent reactions, especially, when other compounds such as phospholipids are present. Hexanal and propanal are suitable as marker compounds in the early phase of lipid oxidation, but at an advanced stage they are subject to aldol condensation. Consequently, the detection of tertiary degradation products needs to be considered in advanced lipid oxidation.

Revealing dynamic changes of the volatile profile of food samples using PTR-MS

Volatile compounds carry valuable information regarding the properties of foodstuffs. Volatiles emitted from food can be used as, for example, indicators of quality, shelf-life, or authenticity. A better understanding of the multitude of transformations which occur during food processing could facilitate the optimisation of production, increase the desirability of food products, and also their wholesomeness. However, as some of these transformations are fast-paced, it is necessary to monitor them using techniques which enable real-time determination of volatiles, such as proton transfer reaction-mass spectrometry (PTR-MS). Recent years have seen a marked increase in its use in food analysis, since it can be used to obtain insight into the dynamics of the monitored processes and can be the basis for precise quality control methods for food processing. This review highlights recent works in which PTR-MS was used in monitoring during foodstuffs production, preparation and storage.

Release Kinetics Studies of Early-Stage Volatile Secondary Oxidation Products of Rapeseed Oil Emitted during the Deep-Frying Process

The research concerns the use of proton transfer reaction mass spectrometer to track real-time emissions of volatile secondary oxidation products released from rapeseed oil as a result of deep-frying of potato cubes. Therefore, it was possible to observe a sudden increase of volatile organic compound (VOC) emissions caused by immersion of the food, accompanied by a sudden release of steam from a potato cube and a decrease of the oil temperature by more than 20 °C. It was possible to identify and monitor the emission of major secondary oxidation products such as saturated and unsaturated aldehydes, namely acrolein, pentanal, 2-hexenal, hexanal, 2-nonenal and 2-decenal. Each of them has an individual release characteristic. Moreover, the impact of different initial frying temperatures on release kinetics was investigated. Subsequently, it was possible to approximate the cumulative emission by a second-degree polynomial (R² ≥ 0.994). Using the proposed solution made it possible for the first time to observe the impact of the immersion of food in vegetable oil on the early emission of thermal degradation products oil.

Using Recurrent Neural Network to Optimize Electronic Nose System with Dimensionality Reduction

Electronic nose is an electronic olfactory system that simulates the biological olfactory mechanism, which mainly includes gas sensor, data pre-processing, and pattern recognition. In recent years, the proposals of electronic nose have been widely developed, which proves that electronic nose is a considerably important tool. However, the most recent studies concentrate on the applications of electronic nose, which gradually neglects the inherent technique improvement of electronic nose. Although there are some proposals on the technique improvement, they usually pay attention to the modification of gas sensor module and barely consider the improvement of the last two modules. Therefore, this paper optimizes the electronic nose system from the perspective of data pre-processing and pattern recognition. Recurrent neural network (RNN) is used to do pattern recognition and guarantee accuracy rate and stability. Regarding the high-dimensional data pre-processing, the method of locally linear embedding (LLE) is used to do dimensionality reduction. The experiments are made based on the real sensor drift dataset, and the results show that the proposed optimization mechanism not only has higher accuracy rate and stability, but also has lower response time than the three baselines. In addition, regarding the usage of RNN model, the experimental results also show its efficiency in terms of recall ratio, precision ratio, and F1 value.