electronic noses are more and more often taken into consideration as a tool used for the quality and authenticity assessment of selected products due to their numerous advantages and the principle of operation . the electronic nose is an analytical instrument used for rapid detection and differentiation between types of gaseous samples . till now electronic nose was used for environmental monitoring ( detection of air pollution , tracking of pollution pathways , and efficiency assessment of wastewater and waste gas treatment ) , medical sciences ( identification of selected diseases , including tumors , based on odorants excreted by the infected cells and organs ) , the perfume industry ( authentication of perfumes ) , the pharmaceutical industry ( production control of medicines ) , forensic operations , and the food - processing industry . chemical sensors under the influence of the gas mixture allow for generating a characteristic odour profile , which constitutes the so - called  fingerprint  . for example , metal oxide semiconductor ( mos ) sensors require a high working temperature , and conductive polymer ( cp ) sensors are susceptible to humidity . these problems can be solved by use of e - noses based on the ultra - fast gas chromatography or mass spectrometry . example of e - nose based on the ultra - fast gas chromatography technology is heracles ii . this type of electronic nose allows for combining the features of fast gas chromatography ( fast gc ) with advantages of a sensor - based electronic nose . in this electronic nose system , hundreds of variables can be used to achieve reliable results . as a result of one analysis , it is possible to obtain information about the composition of investigated samples and their volatile fraction profile . in this way , complete information is obtained about the similarity of a given sample to the reference sample . an electronic nose based on ultra - fast gas chromatography can be used to assess quality and authenticity and to compare samples . spirit beverages are a diverse group of foodstuffs , which differ in terms of their taste , odour , and appearance . spirit beverages which are produced from grain distillates , namely vodka and whisky , belong to the most popular spirit beverages . for production of vodka and whisky is used the raw spirit which according to regulation number 110/2008 of the european parliament and of the council ( ec ) of 15 january 2008 is obtained by the distillation , after alcoholic fermentation , which does not have the characteristics of ethyl alcohol or a spirit drink but still retains the odour and flavour from the specific agricultural materials . the composition of agricultural distillates is influenced by the material , from which it is produced , and fermentation conditions [ 46 ] . raw spirits may contain a lot of harmful substances , which during the production process can pass to the vodka and whiskey . moreover , agricultural distillates can be falsified due to their botanical origin , for example , by mixing rye distillates with corn distillates . ethanol obtained during the fermentation of various agricultural materials is distilled to selectively reduce the organoleptic properties of materials . by filtering alcohol several times through charcoal and by diluting it with water , whisky , just like most of the vodkas , is a grain spirit beverage produced by the distillation of a mash made from malted cereals or cereals saccharified as a result of diastasis of malt contained in them . the flavour of whisky is closely connected with the distillation process and maturation of the intermediate product in oak barrels for at least three years , which is different from vodka . only water and pure caramel can be added to the distillate for dilution and coloring , in contrast to vodkas , to which aromas can be added ; however , in this case the name of aroma should be marked on the label , for example , if it is peach aroma on the label , it should be written as  peach vodka . the composition of vodkas and whisky is usually analysed using one - dimensional gas chromatography [ 1117 ] or two - dimensional gas chromatography . if less volatile ingredients are determined , such as coumarin , it is also possible to use the hplc technique . quality and authenticity assessments are also conducted for these matrices using infrared spectroscopy [ 2022 ] , optical spectroscopy , and sensory analysis [ 2426 ] and the use of the electronic nose based on sensors . none of these methods allows the simultaneous investigation of the matrix and quick differentiation of samples . due to their diversity and popularity , this it is important to find a method that would enable the distinction of samples because of the quality and origin and in the same time a preliminary check of the composition of the samples . there is a need to find equipment that quickly delivers information about composition and authenticity of spirit beverages . these requirements are fulfilled by heracles ii electronic nose based on ultra - fast gas chromatography . two of the most popular spirit beverages , namely , vodka and whiskey , and raw spirits used for their production were selected to check the suitability of the electronic nose for quality analysis of spirit drinks . these alcoholic beverages differ significantly from each other by methods of production but they are made from similar raw materials ; due to this fact it will be possible to check whether one method is good for a variety of spirits made from grains . a set of 24 samples of raw spirits made from different grains obtained from destylarnia sobieski s.a . samples of commercially available vodkas and whisky were obtained from local stores in gdask , poland . a set of 33 samples of vodkas produced from different mixture of different type of rye were selected . eight brands of whisky were selected from those available on the market , out of which 5 ones were produced from a mixture of barley , rye , and wheat distillates and three whiskies were produced with the addition of maize distillate . all samples were prepared using the same analytical procedure . to the vials of 20  ml 6.25  ml of deionised water and 1.75  ml of the alcoholic sample ( vodka , whisky , or raw spirit ) were added . the heracles ii electronic nose based on ultra - fast gas chromatography by alpha mos ( toulouse , france ) was used for the research . it is equipped with a sorption trap , a dispenser allowing the introduction of a gas or liquid sample , two flame ionisation detectors ( fid ) , dedicated alphasoft v12 software with implemented modules for chromatographic , chemometric , and sensory analysis of characteristics of detected chemical compounds , the arochembase v4 library , an hs100 autosampler , and a set of independent chromatographic columns with different polarity ( nonpolar mxt-5 and medium polar mxt-1701 , length 10  m each ) . parameters of operation of the electronic nose used for the analysis of spirit beverages are presented in table 1 . following chemometric analysis pca ( principal component analysis ) , dfa ( discriminant function analysis ) , simca classification ( simca ( soft independent modeling of class analogies ) ) , and sqc ( statistical quality control ) were used for data analysis . for all analyses , sensors ( area of the peaks ) with the highest discrimination power were used . at the first stage , principal component analysis is one of the most popular chemometric methods used for modelling , compression , and visualization of multidimensional data [ 28 , 29 ] . because of that all beverages listed in point 2.1 were used for data analysis ( figure 1 ) . however , this analysis is not typically used to distinguish between groups ; it allows spotting the differences between the analysed samples . for example , in figure 1(a ) , how diversified the studied groups are can be seen . groups were created due to the type of spirit drinks ( raw spirits , vodka , and whisky ) . on the basis of the distance between the samples , it can be concluded that the group of whisky comprises two substantially different groups of samples . in the case of raw spirit samples , the relatively low precision of results is caused by the fact that all samples were made from unknown mixture of grains . all vodkas were made from the same type of grain , namely , rye . in the case of whisky , the information about botanical origin of samples was available . three of them were made not only from barley , wheat , and rye , but also from corn . because of that , two separate groups of whisky of different botanical origin were created ( figure 1(b ) ) . the variables chosen for pca , namely , the most discriminant peak areas of specific compounds , were treated as an input dataset for statistical analysis . this dataset was presented in figure 2 and the names of selected substances were listed in table 2 . due to satisfactory discrimination of sample groups after application of pca method , chosen variables were also used as input data in other utilized chemometric methods . discriminant function analysis is one of the most commonly methods used to decide which variables allow correct classification of a set of objects [ 30 , 31 ] . dfa was used for discrimination of the data obtained from e - nose analysis of spirit beverages . in figure 3 the results of dfa analysis for groups of vodkas , whiskies , and raw spirits are shown , and in figure 4 the results of dfa for vodkas , whiskies made from corn , whisky made without corn , and raw spirits are shown . as opposed to pca , dfa is used to distinguish groups not to make the actual data visualization . in figure 3 it can be seen that points belonging to group of whiskies are definitely more concise than in the case of pca . the other hand differences between individial samples are disappearing when a grup of whiskey samples is defined as a one coherent group . when two groups of whiskies are created ( groups which were showed on the pca graph ( figure 1(b ) ) it can be seen that the groups are distinguished very well ( figure 4 ) . in the case of dfa , spirit beverages can be distinguishing due to the general type ( raw spirits , vodka , and whisky ) and due to the botanical origin if the information about their origin is known as in the case of whisky produced with and without corn . in the case of the pca the differences between the samples within the selected groups can not be neglected . in simca classification , next , the so - called  confidence envelope  ( a certain volume ) is created around the model . it should include with defined probability all elements belonging to a given class [ 1 , 32 ] . simca analysis was made for each reference group : vodka ( figure 5 ) , raw spirit ( figure 6 ) , whisky without corn ( figure 7 ) , and whisky with corn ( figure 8) . in all cases with one exception points belonging to the reference group were located in the blue area in the confidence envelope . in the case of exception one sample it is therefore more time - consuming than dfa . on the other hand , discrimination between different groups is more visible . due to the envelope of confidence the boundaries of analysed groups are determined . samples , which belong to one group , should be situated in the area designated using parameters on the y - axis of the graph [ 33 , 34 ] . sqc analysis was performed for four groups of samples , namely , for vodkas , whiskies without corn , whiskies with corn , and raw spirits to show capabilities of this method . sqc analysis allows seeing the differences between individual samples and excluding those that differ from others . it is the proper method for assessing the quality of products , because it is rapid and easy to use and the discrete differences in the studied group of samples can be determined . this method allows observing which sample is statistically different from the other ones in a given batch . it enables the possibility of exclusion of a sample during the final control of ready products . in figure 9 it can be seen that the differences between the points assigned to a group of vodkas are small . in contrast , the differences between the points belonging to the group of whiskies without corn in figure 10 are more noticeable . it can be noticed that the area in which points belong to the reference group should be located depending on the deviation between the samples in certain group . the greater the differences between the samples in the group , the greater the tolerance range for the whole group . due to the presence of two chromatographic columns of different polarity , it is possible to obtain two different chromatograms and identify individual compounds included in the samples . this is the difference between electronic nose based on sensors and electronic nose based on fast gc . it can be noticed that they differ considerably from each other . as compared to vodka some of chemical compounds detected in vodka , whisky , and raw spirits samples are presented in tables 3 , 4 , and 5 , respectively . compounds present in the sample were identified on the basis of comparison of calculated linear temperature - programmed retention indices ( ltpri ) for compounds from both columns with indices provided in the literature . apart from ltpri , the tables also include approximate retention times for the detected chemical compounds and odour descriptions contained in literature sources , which can be found in arochembase v4 library . compounds present in the volatile fraction of vodka can be characterized by fewer descriptors than those found in whisky and raw spirits . mostly , the aroma of compounds identified in vodka matrix was defined as fruity or green , but some of them were also described as sulphurous , winey , alcoholic , bread , straw , corn , or alkane one . in the case of whisky , compounds are mostly characterized as fruity , green , and woody . other compounds were described as spicy , winey , earthy , sweet , smoky , alcoholic , or pine . regarding the aroma of raw spirits most of the constituents of this matrix some of the compounds were described as a green , woody , minty , floral , sweet , and solvent one . as it can be noticed the decryption of compounds present in the whisky samples was more connected with aroma of barrels , forest , and sweet fruits than in the case of vodka and raw spirit samples . in this paper the usefulness of the electronic nose using ultra - fast gas chromatography for the qualitative analysis of selected spirit beverages was checked . pca and sqc analysis were used to check deviations of individual samples from groups to which they belong . pca enables the visualization of results . as a result , it was possible to quickly determine that the group of whiskies includes two different groups of samples . through an sqc analysis , it is possible to check the quality of the samples . samples of vodka had a similar composition and method of production , due to this fact they are located in one line in figures 9 and 10 . the differences in composition between whisky samples are more significant due to their different method of production and different raw materials used , which was presented in figures 9 and 10 . dfa and simca analysis , on the other hand , were used to group vodka , whisky , and spirits samples and to compare them . furthermore , in contrast to traditional electronic nose based on the sensors , the electronic nose based on a fast gas chromatography allows determining the compounds included in the sample . this is possible thanks to the presence of two chromatographic columns of different polarity and well - equipped database that allows comparison of retention indexes and retention times . additionally , each compound can be attributed to the smell which has been previously described in the literature . summing up , the use of electronic nose based on ultra - fast gas chromatography and four applied statistical methods can be used to distinguish groups of spirit beverages . it also allows finding the differences between individual samples in one group and to determine the composition of the investigated samples . by using arochembase v4 library it was possible to make an assignment of the odours described in the literature to the individual components present in the samples .