Application of an Electronic Nose Instrument to Fast Classification of Polish Honey Types

The paper presents practical utilization of an electronic nose prototype, based on the FIGARO semiconductor sensors, in fast classification of Polish honey types—acacia flower, linden flower, rape, buckwheat and honeydew ones. A set of thermostating modules of the prototype provided gradient temperature characteristics of barbotage-prepared gas mixtures and stable measurement conditions. Three chemometric data analysis methods were employed for the honey samples classification: principal component analysis (PCA), linear discriminant analysis (LDA) and cluster analysis (CA) with the furthest neighbour method. The investigation confirmed usefulness of this type of instrument in correct classification of all aforementioned honey types. In order to provide optimum measurement conditions during honey samples classification the following parameters were selected: volumetric flow rate of carrier gas—15 L/h, barbotage temperature—35 °C, time of sensor signal acquisition since barbotage process onset—60 s. Chemometric analysis allowed discrimination of three honey types using PCA and CA and all five honey types with LDA. The reproducibility of 96% of the results was within the range 4.9%–8.6% CV

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

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

Classification of the alcoholic beverages by using electronic nose technique based on ultra-fast GC

Each alcoholic beverage has its own distinct aroma and unique flavor. An Electronic nose (E-nose) is an instrumental tool which allows one to analyze the aroma of samples. This work illustrates the use of E-nose for the determination of characteristic aromas of seven different alcoholic beverages (bourbon, brandy, cognac, vodka, liqueurs made from pears, and fruit spirits made from lemon). The following chemometrics methods for the data analysis were employed for the classification of alcoholic beverages: principal component analysis (PCA), discriminant factorial analysis (DFA, and soft independent modelling of class analogies (SIMCA). The results show that chemometrics methods PCA and DFA allow us the determination of the individual alcoholic groups of fruit spirits, bourbon, cognac, and brandy but there is a difficulty with separation of liqueur, gin, and vodka points from one group. Only the SIMCA method allowed to distinguish the point belonging to all groups without any approximation of graph fragments

Klasifikace alkoholických nápojů technikou elektronického nosu založenou na ultrarychlé GC

Each alcoholic beverage has its own distinct aroma and unique flavor. An Electronic nose (E-nose) is an instrumental tool which allows one to analyze the aroma of samples. This work illustrates the use of E-nose for the determination of characteristic aromas of seven different alcoholic beverages (bourbon, brandy, cognac, vodka, liqueurs made from pears, and fruit spirits made from lemon). The following chemometrics methods for the data analysis were employed for the classification of alcoholic beverages: principal component analysis (PCA), discriminant factorial analysis (DFA, and soft independent modelling of class analogies (SIMCA). The results show that chemometrics methods PCA and DFA allow us the determination of the individual alcoholic groups of fruit spirits, bourbon, cognac, and brandy but there is a difficulty with separation of liqueur, gin, and vodka points from one group. Only the SIMCA method allowed to distinguish the point belonging to all groups without any approximation of graph fragments.Každý alkoholický nápoj má své vlastní aroma a jedinečnou chuť. Elektronický nos (E-nose) je nástroj, který umožňuje analyzovat aroma vzorků. Tato práce ilustruje použití E-nose pro stanovení charakteristických vůní sedmi různých alkoholických nápojů (bourbon, brandy, koňak, vodka, likéry vyrobené z hrušek a ovocné destiláty vyrobené z citronu). Pro klasifikaci alkoholických nápojů byly použity následující chemometrické metody pro analýzu dat: analýza hlavních komponent (PCA), diskriminační faktorová analýza (DFA a měkké nezávislé modelování třídy analogie (SIMCA). Výsledky ukazují, že chemometrické metody PCA a DFA dovolují určit jednotlivé skupiny ovocných destilátů, bourbonu, koňaku a brandy, ale je obtížné oddělit body likéru, ginu a vodky. Pouze metoda SIMCA umožnila rozlišit body patřící všem skupinám bez jakékoli aproximace částí grafů