Magdalena Śliwińska

Food Analysis Using Artificial Senses

Nowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring and determining the quality and authenticity of foods. This paper summarizes achievements in the field of artificial senses. It includes a brief history of these systems, descriptions of most commonly used sensors (conductometric, potentiometric, amperometic/voltammetric, impedimetric, colorimetric, piezoelectric), data analysis methods (for example, artificial neural network (ANN), principal component analysis (PCA), model CIE L*a*b*), and application of artificial senses to food analysis, in particular quality control, authenticity and falsification assessment, and monitoring of production processes.

Differentiation Between Spirits According to Their Botanical Origin

Agricultural distillates are used for the production of spirit beverages. As more and more products with a specific botanical composition specified on the label are produced (e.g. rye vodkas, wheat vodkas and Polish Vodka, which cannot be produced with the addition of maize distillate), it is necessary to look for quicker and more accurate methods allowing the determination of botanical origin of alcoholic beverages and materials used to their production. The aim of this study is to verify the usefulness of the electronic nose based on the ultra-fast gas chromatography for quick differentiation between agricultural distillates according to their botanical origin. Nineteen samples included distillates from rye, triticale, wheat and maize were used for the research. For data analysis, the following methods were used: PCA—Principal Component Analysis, DFA—Discriminant Function Analysis, SIMCA classification (SIMCA—Soft Independent Modeling of Class Analogies) and SQC—Statistical Quality Control. The use of the electronic nose with ultra-fast gas chromatography and the use of DFA and SIMCA analyses allowed differentiation between agricultural distillates according to their botanical origin.

The Analysis of Vodka: A Review Paper

Vodka is the most popular alcoholic beverage in Poland, Russia and other Eastern European countries, made from ethyl alcohol of agricultural origin that has been produced via fermentation of potatoes, grains or other agricultural products. Despite distillation and multiple filtering, it is not possible to produce 100 % ethanol. The solution with a minimum ethanol content of 96 %, which is used to produce vodkas, also contains trace amounts of other compounds such as, esters, aldehydes, higher alcohols, methanol, acetates, acetic acid and fusel oil. Regarding that fact, it is very important to carry on research on the analysis of the composition and verifying the authenticity of the produced vodkas. This paper summarizes the studies of vodka composition and verifying the authenticity and detection of falsified products. It also includes the methods for analysing vodkas, such as: using gas, ion and liquid chromatography coupled with different types of detectors, electronic nose, electronic tongue, conductivity measurements, isotope analysis, atomic absorption spectroscopy, near infrared spectroscopy, spectrofluorometry and mass spectrometry. In some cases, the use of chemometric methods and preparation techniques were also described.

Application of the electronic nose technique to differentiation between model mixtures with COPD markers.

The paper presents the potential of an electronic nose technique in the field of fast diagnostics of patients suspected of Chronic Obstructive Pulmonary Disease (COPD). The investigations were performed using a simple electronic nose prototype equipped with a set of six semiconductor sensors manufactured by FIGARO Co. They were aimed at verification of a possibility of differentiation between model reference mixtures with potential COPD markers (N,N-dimethylformamide and N,N-dimethylacetamide). These mixtures contained volatile organic compounds (VOCs) such as acetone, isoprene, carbon disulphide, propan-2-ol, formamide, benzene, toluene, acetonitrile, acetic acid, dimethyl ether, dimethyl sulphide, acrolein, furan, propanol and pyridine, recognized as the components of exhaled air. The model reference mixtures were prepared at three concentration levels—10 ppb, 25 ppb, 50 ppb v/v—of each component, except for the COPD markers. Concentration of the COPD markers in the mixtures was from 0 ppb to 100 ppb v/v. Interpretation of the obtained data employed principal component analysis (PCA). The investigations revealed the usefulness of the electronic device only in the case when the concentration of the COPD markers was twice as high as the concentration of the remaining components of the mixture and for a limited number of basic mixture components.

The Verification of the Usefulness of Electronic Nose Based on Ultra-Fast Gas Chromatography and Four Different Chemometric Methods for Rapid Analysis of Spirit Beverages

Spirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose based on ultra-fast gas chromatography (fast GC e-nose) was verified. A set of 24 samples of raw spirits, 33 samples of vodkas, and 8 samples of whisky were analysed by fast GC e-nose. Four data analysis methods were used. The PCA was applied for the visualization of dataset, observation of the variation inside groups of samples, and selection of variables for the other three statistical methods. The SQC method was utilized to compare the quality of the samples. Both the DFA and SIMCA data analysis methods were used for discrimination of vodka, whisky, and spirits samples. The fast GC e-nose combined with four statistical methods can be used for rapid discrimination of raw spirits, vodkas, and whisky and in the same for preliminary determination of the composition of investigated samples.

Application of Gas Chromatography to Analysis of Spirit-Based Alcoholic Beverages

Spirit-based beverages are alcoholic drinks; their production processes are dependent on the type and origin of raw materials. The composition of this complex matrix is difficult to analyze, and scientists commonly choose gas chromatography techniques for this reason. With a wide selection of extraction methods and detectors it is possible to provide qualitative and quantitative analysis for many chemical compounds with various functional groups. This article describes different types of gas chromatography techniques and their most commonly used associated extraction techniques (e.g., LLE, SPME, SPE, SFE, and SBME) and detectors (MS, TOFMS, FID, ECD, NPD, AED, O or EPD). Additionally, brief characteristics of internationally popular spirit-based beverages and application of gas chromatography to the analysis of selected alcoholic drinks are presented.

Qualitative characteristics and comparison of volatile fraction of vodkas made from different botanical materials by comprehensive two-dimensional gas chromatography and the electronic nose based on the technology of ultra-fast gas chromatography.

BACKGROUND Vodka is a spirit-based beverage made from ethyl alcohol of agricultural origin. At present, increasingly more vodka brands have labels that specify the botanical origin of the product. Until now, the techniques for distinguishing between vodkas of different botanical origin have been costly, time-consuming and insufficient for making a distinction between vodka produced from similar raw materials. Therefore, it is of utmost importance to find a fast and relatively inexpensive technique for conducting such tests. RESULTS In the present study, we employed comprehensive two-dimensional gas chromatography (GC×GC) and an electronic nose based on the technology of ultra-fast GC with chemometric methods such as partial least square discriminant analysis, discriminant function analysis and soft independent modeling of class analogy. CONCLUSION Both techniques allow a distinction between the vodkas produced from different raw materials. In the case of GC×GC, the differences between vodkas were more noticeable than in the analysis by electronic nose; however, the electronic nose allowed the significantly faster analysis of vodkas.

Advances in Electronic Noses and Tongues for Food Authenticity Testing

Currently there is an increase of consumer awareness about the quality and authenticity of food. Nowadays, for food analysis, electronic sensors are very often used because they require less time and operate at a lower cost per analysis than other techniques. This chapter summarizes achievements in the application of the electronic tongue and nose in food authenticity tests of the following groups of food products: dairy and meat products, fruits and vegetables, oils and vinegars, teas and coffees, nonalcoholic and alcoholic beverages, and others. It also explains the similarities between human senses and their artificial counterparts and includes a description of the most commonly used electronic noses and electronic tongues.

Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy

The capability of a phthalocyanine-based voltammetric electronic tongue to analyze strong alcoholic beverages has been evaluated and compared with the performance of spectroscopic techniques coupled to chemometrics. Nalewka Polish liqueurs prepared from five apple varieties have been used as a model of strong liqueurs. Principal Component Analysis has demonstrated that the best discrimination between liqueurs prepared from different apple varieties is achieved using the e-tongue and UV-Vis spectroscopy. Raman spectra coupled to chemometrics have not been efficient in discriminating liqueurs. The calculated Euclidean distances and the k-Nearest Neighbors algorithm (kNN) confirmed these results. The main advantage of the e-tongue is that, using PLS-1, good correlations have been found simultaneously with the phenolic content measured by the Folin–Ciocalteu method (R2 of 0.97 in calibration and R2 of 0.93 in validation) and also with the density, a marker of the alcoholic content method (R2 of 0.93 in calibration and R2 of 0.88 in validation). UV-Vis coupled with chemometrics has shown good correlations only with the phenolic content (R2 of 0.99 in calibration and R2 of 0.99 in validation) but correlations with the alcoholic content were low. Raman coupled with chemometrics has shown good correlations only with density (R2 of 0.96 in calibration and R2 of 0.85 in validation). In summary, from the three holistic methods evaluated to analyze strong alcoholic liqueurs, the voltammetric electronic tongue using phthalocyanines as sensing elements is superior to Raman or UV-Vis techniques because it shows an excellent discrimination capability and remarkable correlations with both antioxidant capacity and alcoholic content—the most important parameters to be measured in this type of liqueurs.

Comparison of an Electronic Nose Based on Ultrafast Gas Chromatography, Comprehensive Two-Dimensional Gas Chromatography, and Sensory Evaluation for an Analysis of Type of Whisky

Whisky is one of the most popular alcoholic beverages. There are many types of whisky, for example, Scotch, Irish, and American whisky (called bourbon). The whisky market is highly diversified, and, because of this, it is important to have a method which would enable rapid quality evaluation and authentication of the type of whisky. The aim of this work was to compare 3 methods: an electronic nose based on the technology of ultrafast gas chromatography (Fast-GC), comprehensive two-dimensional gas chromatography (GC × GC), and sensory evaluation. The selected whisky brands included 6 blended whiskies from Scotland, 4 blended whiskies from Ireland, and 4 bourbons produced in the USA. For data analysis, peak heights of chromatograms were used. The panelists who took part in sensory evaluations included 4 women and 4 men. The obtained data were analyzed by 2 chemometric methods: partial least squares discriminant analysis (PLS-DA) and discrimination function analysis (DFA). E-nose and GC × GC allowed for differentiation between whiskies by type. Sensory analysis did not allow for differentiation between whiskies by type, but it allowed giving consumer preferences.