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Article

Assessment of the Authenticity of Whisky Samples Based on the Multi-Elemental and Multivariate Analysis

by
Magdalena Gajek
1,*,
Aleksandra Pawlaczyk
1,
Elżbieta Maćkiewicz
1,
Jadwiga Albińska
1,
Piotr Wysocki
1,
Krzysztof Jóźwik
2 and
Małgorzata Iwona Szynkowska-Jóźwik
1
1
Faculty of Chemistry, Institute of General and Ecological Chemistry, Lodz University of Technology, Zeromskiego 116, 90-924 Lodz, Poland
2
Faculty of Mechanical Engineering, Institute of Turbomachinery, Lodz University of Technology, Wolczanska 219/223, 90-924 Lodz, Poland
*
Author to whom correspondence should be addressed.
Foods 2022, 11(18), 2810; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11182810
Submission received: 4 August 2022 / Revised: 25 August 2022 / Accepted: 29 August 2022 / Published: 12 September 2022
(This article belongs to the Special Issue Advances of Spectrometric Techniques in Food Analysis and Authentication)
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Versions Notes

Abstract

:
Two hundred and five samples of whisky, including 170 authentic and 35 fake products, were analyzed in terms of their elemental profiles in order to distinguish them according to the parameter of their authenticity. The study of 31 elements (Ag, Al, B, Ba, Be, Bi, Cd, Co, Cr, Cu, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, U, V, Ca, Fe, K, Mg, P, S, Ti and Zn) was performed using the Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and Cold Vapor-Atomic Absorption (CVAAS) techniques. Additionally, the pH values of all samples were determined by pH-meter, and their isotopic ratios of 88Sr/86Sr, 84Sr/86Sr, 87Sr/86Sr and 63Cu/65Cu were assessed, based on the number of counts by ICP-MS. As a result of conducted research, elements, such as Mn, K, P and S, were identified as markers of whisky adulteration related to the age of alcohol. The concentrations of manganese, potassium and phosphorus were significantly lower in the fake samples (which were not aged, or the aging period was much shorter than legally required), compared to the original samples (in all cases subjected to the aging process). The observed differences were related to the migration of these elements from wooden barrels to the alcohol contained in them. On the other hand, the sulfur concentration in the processed samples was much higher in the counterfeit samples than in the authentic ones. The total sulfur content, such as that of alkyl sulfides, decreases in alcohol with aging in the barrels. Furthermore, counterfeit samples can be of variable origin and composition, so they cannot be characterized as one group with identical or comparable features. Repeatedly, the element of randomness dominates in the production of these kinds of alcohols. However, as indicated in this work, the extensive elemental analysis supported by statistical tools can be helpful, especially in the context of detecting age-related adulteration of whisky. The results presented in this paper are the final part of a comprehensive study on the influence of selected factors on the elemental composition of whisky.

1. Introduction

Extremely fast development of trade and international exchange of products and food mobility brought an unprecedented variety of food products to consumers. However, nowadays, consumer awareness regarding the quality and authenticity of the food they buy and consume was raised significantly. Moreover, a study conducted over a decade ago indicated that as many as 82% of the customers considered geographical origin as a quality indicator before purchasing food products [1]. Literature reports clearly suggest that numerous cases of food adulteration have been reported, including the use of substances that pose a threat to the health and life of consumers. Examples of such activities can be given as follows: mixing melamine and wheat gluten to increase the protein content [2], contamination of paprika powder with lead oxide [3], addition of red lead (Pb3O4) to cayenne pepper to achieve a vibrant color [4]. In turn, honeys are often adulterated to increase their shelf-life and nutritional value, by adding glucose–fructose syrups, corn syrups, invert sugar syrups or by admixing with imported honeys of poorer quality [5,6]. Thus, food authenticity is an important matter in the case of quality control and assurance of food safety. The authentication of food concerns many aspects, including misleading about origin, mislabeling and adulteration, which is defined as a process by which the quality or the nature of a given product is reduced due to the addition of a foreign or an inferior substance and removing a vital element [7,8].
The need for precise and valid analytical techniques for food investigations is increasing because of the continuously rising food deception around the world [9,10,11]. Fortunately, a range of potential analytical techniques for the authenticity termination and traceability of food products is extensive. Among them, the following methods can be distinguished: spectroscopic techniques [12,13,14,15] (including those based on isotopic ratios [16,17]), separation techniques [6,18], neutron and proton-based nuclear techniques [19], as well as advanced DNA-based techniques [10,20]. Elemental analysis has long been used in research connected with food authenticity, including discrimination of geographical origin [7], organic versus conventional cultivation [21] or free range to compare with conventionally farmed products [22]. Numerous literature reports indicate that elemental fingerprinting also proved its usefulness for the differentiation of origin of wine [15,23], olive oil [24], honey [6,25], coffee [26], tea [27], cheese [28], vegetables and fruits [29] and also spices and food additives [30]. Food products consist of numerous compounds, including carbohydrates, peptides, lipids, fatty acids, amino acids, organic acids, nucleic acids and other small molecules (aromas, dyes, preservatives and other exogenous compounds) [31]. Due to the complexity of the ingredients in the food, using chromatographic methods it makes possible to obtain unique molecular fingerprints, which has a huge potential in differentiation during the authentication process [30]. Separation techniques were used for food authentication and geographic identification of the following: apple juice [32], kiwifruit juices [33], wine [34], honey [6], saffron [35], tomatoes [36], ginger [37], whisky [38,39,40,41,42] and fruit spirits [43]. Moreover, the isotopic ratios were successfully used in food authentication because stable isotope ratios are dependent on the climatic and soil conditions, as well as geographical origin of food ingredients [30]. The isotope ratios mostly investigated in food authentication are 2H/1H, 13C/12C, 15N/14N, 18O/16O, 34S/32S, 84Sr/86Sr, 87Sr/86Sr, 88Sr/86Sr 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb [44,45]. Literature reports indicate that techniques based on the measurement of isotope ratios are most often used for authentication of cheeses [46], sweet cherries [47], lentils [48] bell pepper [49], wheat [50], wine [51,52] and vodka [53].
Due to the great popularity and high price, premium whisky is one of the most frequently counterfeited alcoholic beverages. The process of counterfeiting whisky usually involves blending a cheaper version of whisky belonging to the same category as the genuine brand, mixing a cheap local alcohol with the original brand of whisky or using a cheap local alcohol with added flavorings and coloring as a genuine product [54]. Another possibility of counterfeits in the case of whisky is the use of a different type of barrel, as well as a much shorter aging period compared to the manufacturer’s declarations. The most important quality characteristics, particularly in the case of premium brands, are the maturation period and the history of the casks in which whisky was matured. Thus, during the authentication process of whisky, a number of facts have to be taken into consideration. The water, the cereals, the use of peat smoke during grain malting and the equipment applied in the distillation process will have an influence, to a greater or lesser extent, on the final product. During the aging of the raw distillate in the barrel, significant changes take place in the chemical composition of the alcohol, which results in the “softening” of the product [42,55]. As previously noted, the analytical techniques most commonly used to authenticate and identify the geographical origin of whisky are chromatographic methods [38,39,40,41,42]. They allow finding characteristic compounds and determine aroma profiles, which can then be used to define the quality and authenticity of the tested whisky [56]. Especially the analysis of esters, which have the greatest impact on the aroma of the alcohol, enables an assessment of the aging process and, as a result, the verification of the authenticity of the age of whisky [57,58].
Taking into account the number of scientific studies dealing with the authentication and identification of the origin of food products, most of articles refer to wines; then fruit, vegetables and cereals; and, finally, meats, oils and fats. The available scientific data show that less than 10% of all publications devoted to food authentication concern the analysis of beverages (including spirit, beers, soft drinks and mineral waters) [30]. To the authors’ knowledge, very few papers on metal analysis in whisky are available [59,60,61,62]. However, the use of the elemental profile to establish authenticity and provenance is extremely rare in the literature [60]. In the first part of the scientific study (The Elemental Fingerprints of Different Types of Whisky as Determined by ICP-OES and ICP-MS Techniques in Relation to Their Type, Age, and Origin [61]), the extensive elemental characterization of whisky samples was performed, including distinguishing alcohol samples based on their origin, type and age using statistical analysis and chemometric tests. The authors in this paper have not discussed the issues related to the authenticity of products or its possible identification.
The main purpose of this work was to assess the authenticity parameter based on an extensive elemental analysis supported by appropriate statistical and chemometric tests. It should be emphasized that in this study wide range of measurements were carried out with the use of 3 analytical techniques (ICP-MS, ICP-OES and CV-AAS) to determine the concentrations of 31 elements in 205 whisky samples (170 authentic and 35 fake samples). Additionally, the pH value was measured for each of the analyzed alcohol samples, and the collected semi-quantitative data were used to determine the isotope ratios.

2. Materials and Methods

2.1. Samples

In this study, a total of 205 whisky samples were analyzed, including 170 samples of original products, which were discussed in the first part of the publication (The Elemental Fingerprints of Different Types of Whisky as Determined by ICP-OES and ICP-MS Techniques in Relation to Their Type, Age, and Origin [63]), as well as 35 samples of unidentified identity, called fake products, which were used as a reference group for the authenticity studies. Among the 35 samples, 9 different sources of their origin can be distinguished. The source of origin is understood to mean the producer or the place where the product was manufactured. These alcohols were distributed on various scales as analog of whisky products. To the authors’ knowledge, fake alcohols were not matured in wooden barrels or this stage was significantly reduced. However, the counterfeits whisky products were from sources that remain anonymous. The analysis was performed using the ICP-MS, ICP-OES and CVAAS techniques.
The information about whisky products categories was coded, and the manufacturers’ names are not given in this paper. Basic characteristics of the tested samples are included in Table 1.

2.2. Samples Preparation and Equipment

  • ICP-OES, ICP-MS and CV-AAS
The sample preparation procedures and the measurement conditions are described in detail in the publication Elemental Fingerprint of Different Types of Whisky Determined by ICP-OES and ICP-MS techniques in Relation to Their Type, Age and Origin [61] and in our preliminary study (Multielemental Analysis of Various Kinds of Whisky [63]). Moreover, all validation procedures were analogous to those described in the first part of the paper.
  • pH-Metr
Basic 20+ pH-meter (CARISON INSTRUMENTS S.A., Barcelona, Spain) was used to measure the pH values of the tested whisky samples. The pH-meter consists of a magnetic stirrer with automatic temperature stabilization and a combined electrode with glass and a silver chloride electrode placed in one holder. Before the measurement, the necessary calibration process was performed using buffers at pH 4.01, 7.00 and 9.21 (HACH Company, Düsseldorf, Germany). Measurements were carried out during a three-day analytical cycle. Three replicates were performed for each sample, and the average result was taken as the final result. After analyzing 20 samples, calibration was repeated.

2.3. Data Analysis

The STATISTICA 12.5 (New York, NY, USA) software was employed for raw data processing. The first step was to check the normality of the distribution of the studied variables. In this order, Kołmogorow–Smirnow tests were applied. On the basis of the tests, the hypothesis of normal distribution was rejected for all studied elements and isotope ratios, as well as pH-value (for the significance level α = 0.05). Then, the existence of statistically significant differences was checked. For this purpose, the Kruskal–Wallis non-parametric test was used. In the final phase, data were investigated by multivariate chemometric analysis. To increase the interpretability of the results, principal component analysis (PCA) was applied.

3. Results and Discussion

3.1. Level of Metals in Analyzed Whisky Samples

In this study, the concentration of 31 elements in 205 whisky samples and products of unknown identity was determined. A total of 170 samples are authentic products, the concentrations of which were listed in the first part. The remaining 35 items are false objects and the obtained results for this group regarding their elemental profile were given in this paper. The ICP-MS technique was used to determine the concentration of the following elements: Ag, Al, B, Ba, Be, Bi, Cd, Co, Cr, Cu, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, U and V, while elements, such as Ca, Fe, K, Mg, P, S, Ti and Zn, were measured with the ICP-OES technique. The CVAAS technique was used to determine the total mercury content.
In terms of 35 samples of counterfeit products, some of the obtained results were below the quantification limits. The Hg concentration was below the limit of quantification in each case. Te was not determined in 31 samples. Ag was not determined in 19 samples, P in 15 and Fe in 13. Sb and Bi were not detected in 12 samples, while Cd and Ti in 9 samples. Zn was not found in six samples; Mo and Tl in four; and Al, V, Sn and Pb in three samples. U was not identified in two independent samples, while Li, Be and B were not quantified in one sample.
In the first part of the publication, the basic statistical parameters of authentic products (170 samples) were summarized. Therefore, in Table 2 the same type of the information was given, such as the mean, median, minimum and maximum, but for the group of counterfeit products (35 samples). In each case, due to the rejection of the hypothesis of normal distribution, in order to assess statistically significant differences between the groups under consideration, the non-parametric Kruskal–Wallis test was applied.
The average contents of median values for the elements in the alcohol samples of unidentified origin decreased in the following order: Ca > K > S > B > Mg > Zn > Ba > Al > Cr > Sr > P > Fe > Cu > Ni > Mn > Ti > Li > Sn > Pb > Co > Mo > V > Cd > Bi > Sb > U > Be > Tl > Ag > Te > Hg. The order of elements for authentic samples was similar with the general trend from macro to micro elements. However, it should be noted that in the case of original products, elements, such as P and Cu, are listed higher in this order, while S lower than the presented order for non-original samples.
The authors of this paper referred to the internal national standards that define the maximum permissible content of selected metals (Cd, Pb) in high-percentage alcohols [64], which were presented in the first part of the manuscript, decided also to check potential exceedances of heavy metals (Cd and Pb) in fake whisky samples. In the mentioned standards, the maximum lead content was set at 0.3 mg/L, and the cadmium one at 0.03 mg/L. This time, there were only exceedances in the case of cadmium. The exceedances of the maximum allowable concentrations concerned three samples (F10, F11 and F12), which came from a common source. The values recorded for Cd in these cases ranged from 32.25–65.90 µg/L.

3.2. Comparison of Elemental Profiles of Authentic and Counterfeit Whisky

In this experiment, a set of counterfeit and authentic samples was analyzed to reveal the possible differences between them, as well as to detect and identify the elemental fingerprint group of genuine and fake whisky. Apart from the above-mentioned 30 elements (Hg was omitted because its concentration in each sample was below the limit of quantification) and the pH value, in the analysis, the values of Sr and Cu isotope ratios were also used. These ratios were calculated based on the number of counts for each of the isotope as a result of the semi-quantitative analysis. In the case of Sr isotopes, the interference from Rb was corrected. For copper, an analysis was performed on the basis of the 63Cu/65Cu isotope ratio. In turn, for Sr, the following isotopic ratios were used: 88Sr/86Sr, 84Sr/86Sr, 87Sr/86Sr, as these are the parameters most frequently used in food authentication [45].
On the basis of the Kruskal–Wallis test, the existence of statistically significant differences in the concentration of the following elements was demonstrated: Be, Ca, Cu, Li, Mg, Mo, S, Sn, Sr and pH value (Table 3). In all mentioned cases the level of significance (p) was less than 0.05.
Comparing the median values of the two groups under consideration (fake and authentic whisky samples) in each case, except for copper, higher values were noted for products with unidentified identity. Although the highest content of copper was recorded in the fake sample (33.21 µg/L), the median and mean values of the samples belonging to the group of authentic products were much higher. However, it should be noted that in the group of false samples there were five objects with a much higher concentration of copper. These were samples coded as F4 and F5 and from F9 to F11 with a copper content in the range from 12.89 to 33.21 µg/L. As emphasized in the first part of the work, the presence of copper in alcohol is undoubtedly related to the material of the apparatus used in the production process, and more specifically during distillation. Therefore, the alcohols coded as F4, F5, F9, F10 and F11 have most certainly been distilled in copper stills, resembling the high-quality single malt whisky. As it was underlined in the previous paper, differentiation of the authentic samples may be influenced by several overlapping parameters. Moreover, counterfeit samples can be of variable origin and composition, so it is impossible to characterize them as one group with identical or comparable attributes. When the influence of overlapping parameters was eliminated, in the case of authentic samples, the increasing concentration of V, Cr, Ni, Sr, Sb, Bi, Zn, Mg, K and P with the age of the analyzed samples was revealed (despite the lack of statistically significant differences). A similar result was recorded for the comparison of authentic and false objects in this study. Despite the lack of statistically significant differences, higher values of both the median and mean of Mn and P and the median value for K were recorded for the genuine samples, which were maturated (minimum 3 years). Thus, it is possible to clearly indicate the influence of aging on the levels of phosphorus and manganese and potassium, as these elements can be selected as markers for the identification of products with adulterated maturation. The chemical composition of wood is the explanation for the higher content of the above-mentioned elements in the authentic samples in relation to the false ones. Unadulterated whisky is matured in oak barrels, usually incinerated from the inside. The presence of phosphorus and potassium is directly related to the oxides formed during the firing of wooden barrels for aging alcohol. On the other hand, phosphorus, as a macroelement necessary for plant development, may accumulate in various parts of plants when migrating from the soil. The main form of phosphorus in soil is phosphates, including manganese phosphates [65,66]. In addition, manganese compounds are used as wood preservatives, which may also affect the content of this element in alcohol stored in oak barrels [67]. Thus, the longer the alcohol stays in contact with wooden barrels, the greater the migration of these elements into the product. It is true that the aforementioned average concentration of copper was higher in authentic samples, i.e., those subjected to the aging process, however, the content of this element should be associated with the equipment used for production rather than with the age parameter.
Among the elements listed in Table 3, for which the existence of statistically significant differences has been demonstrated, the presence of sulfur should be commented on. As reported in the literature data, sulfur volatile compounds generated during the whisky production process influence their quality to a large degree [68]. The selected alkyl sulfides (dimethyl sulfide (DMS), dimethyl disulfide (DMDS) and dimethyl trisulfide (DMTS)) have been recognized as age markers for whisky, as the level decreases with the time the alcohol spends in the barrel [69,70]. Comparing the mean and the median values of the groups of false and authentic samples, it is clear that the concentration of S in the set of counterfeit samples (not subjected to aging or with a falsified aging period) was an order of magnitude higher than in the original ones (which in each case were samples aged by at least 3 years). Thus, both the concentration of sulfur compounds, as evidenced by the literature, and the total sulfur content, as shown in this study, decrease with the aging of alcohol.
Also, the much higher pH value in the case of fake samples, as compared to the authentic ones, is worth emphasizing. This applies to both the mean and the median values. Although the set of authentic samples is much more numerous than the samples of unidentified identity, the pH values obtained in this group were much more similar and were in the acidic pH range. The counterfeit alcohol samples, on the other hand, had the pH ranging from 2.79 to 8.70, i.e., from acid to alkaline. Adherence to strict standards in the whisky production process ensures that certain physical and chemical parameters of alcohol are maintained within a given brand, including the characteristic pH value of the product. The large discrepancy in the results of the pH value in a small group of fake samples (including samples from a common source) suggests a lack of compliance with production standards and certain randomness during the production of this type of alcohol.
The comparison of the Cu and Sr isotope ratios of the genuine and false sample groups did not provide significant information allowing their better differentiation.
In the next step, the projection of cases on the factor plane for reduced data set was made. Since the significant influence of aging on the elemental profile of whisky had already been proven in earlier work, the age parameter was eliminated. Therefore, during the comparison of false and genuine samples, only the original samples were taken into account, which were aged for the legally required period (3 years).
As shown in Figure 1, quite a good separation between genuine and counterfeit samples using PCA was achieved. The vast majority of authentic samples are accumulated in one area of the graph (around the point of intersection of the coordinate axes), while the points belonging to the false samples are scattered over throughout the plot. This area contains over 70% of alcohol samples with unidentified identity. Despite the much smaller number of counterfeit samples, their large diversity in composition makes it impossible to characterize them as one group with similar physicochemical characteristics. Repeatedly, other authors have indicated that it is extremely difficult to find a marker occurring only in fake samples [42,71,72,73,74,75]. Most often, the problem arises from the type and nature of the adulterations. Depending on whether the adulteration concerns a lower alcohol content than the standard required [73] or on the addition of esters, aldehydes or organic acids [71,72], in order to reflect the age, taste, smell and quality of a given brand, a different and individual approach should be taken. Nonetheless, under such conditions, nontargeted screening followed by chemometric analysis can be a powerful instrument to uncover deviations from typical authentic whisky fingerprints.
Figure 1 resembles an analogous projection presented in the work of Stupak et al. [42]. The authors of the aforementioned work separated the samples of counterfeit and original whisky on the basis of selected markers measured with chromatographic techniques. In this case, in the PCA plot, all points belonging to the group of genuine products (both single malt and blended) were clustered in one common area, while objects belonging to the fake samples are dispersed across the graph.

3.3. Counterfeit Whisky Analysis

In the next steps, only samples marked as fake (35) were discussed separately with division to their sources of origin (1–9). On the basis of the Kruskal–Wallis test, the existence of statistically significant differences in the concentration of the following elements was demonstrated: B, Bi, Cd, Co, Fe, Mn, Mo, Ni, Pb, Sb and Zn. In each case, the level of significance (p) was less than 0.05. The most important statistical information connected with the division of fake samples against the sources is included in Table 4. It is worth noting that statistically significant differences for each of the elements, every time concerned, the source of the counterfeit whisky samples was marked as the number 2 (indicated as red color on Figure 2). Moreover, taking into account the median value for all elements listed in Table 5 (except Sn), the lowest concentrations were recorded for source 2.
In the analyzed set of fake samples, nine different, independent sources were distinguished and according to this criterion a division was made and what is worth mentioning is the fact that within these separated groups, alcohol samples of a completely different nature were observed. This means that they were produced by one manufacturer, but some of them are “raw” products, i.e., distillates that have not undergone any treatment to change their color or taste, whereas others are finished products intended for sale and consumption. However, the tendency that can be noticed in the projection of the cases on the factor plane for the fake products presented in Figure 2 is the grouping of samples within a common source. Each group has been marked with a different color. Sources 8 (F2) and 9 (F1) are represented by single samples. Sample F1 (source 9) is distinguished by the highest values of Li, Mn, Sr and Ba in relation to the other counterfeit samples, hence its extreme position on the graph presented below. Within the source 1 (marked in green), a cluster of items from F30 to F32 can be distinguished. These are samples of the same alcohol coming probably from one production batch but taken from three independent bottles. It should be mentioned that this alcohol has been enriched with wood extracts in order to give it the characteristic whisky aromas. The other samples in this group are of a completely different nature. Moreover, samples F9–12 and F30–32 contain the highest concentrations of Cd in the tested set of false ones. For items F10–12, the permissible level of this element has been exceeded. The samples from sources 2, 4, 5 and 7 in Figure 2 form the most central, individual clusters. An interesting group is consisted of the samples from source 3 marked in yellow in Figure 2. Points F3, F22 and F24 are samples of high-strength distillates. In turn, samples F20, F26 and F34 are flavored products, which are made from these distillates. They have been enriched with sugar and fruit juices. These products were supposed to resemble whisky-based fruit liqueurs.

4. Conclusions

Mn, K and P are elements with higher concentrations recorded in the case of authentic samples. Their presence is directly related to the aging period of alcohol and can be indicated as markers for the identification of fraudulent activity in this respect. Another indicator certainly associated to the whisky maturation process in barrels is S. In products that were not aged or the aging period was much shorter than legally required (fake samples), the concentration of this element was much higher, compared to the original samples (in all cases subjected to the aging process). Counterfeit samples can be of variable origin and composition, so they cannot be characterized as one group with identical or comparable attributes. Often, the element of randomness dominates in the production of such alcohols. The use of unsuitable ingredients or production equipment, as well as inadequate knowledge in this field, cause the lack of repeatability of the taste and smell characteristics of alcohol beverages. This is evidenced by, for example, the failure to meet the standards for the maximum content of heavy metals in high-percentage alcohols. The adulteration of food products, including whisky, may be of various characters. It can refer to a reduced percentage of alcohol or the addition of various organic compounds to improve the visual and flavor properties. Therefore, the identification of the falsification of a different nature requires the use of a wide range of analytical techniques and often an individual approach.
The results presented in this article constitute the final part of a broad characteristic of the elemental composition carried out for 205 whisky samples. As our research revealed, the elemental analysis supported by statistical tools may provide beneficial information, especially in the context of the differentiation of alcohol samples in regard to such parameters as type, origin and detecting age-related adulteration of whisky.

Author Contributions

A.P., P.W. and M.G. performed an elemental analysis of all samples, analyzed the data, performed the chemometric analysis, prepared the paper; E.M. and J.A. methodological and technical support for research, performed an elemental analysis of all samples, prepared the paper; K.J.—conducted substantive supervision; M.I.S.-J. conducted substantive supervision and final review. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The date are available from the corresponding author.

Acknowledgments

The authors of this paper would like to thank the invaluable technical support Patrycja Skrzek.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Luykx, D.M.A.M.; van Ruth, S.M. An overview of analytical methods for determining the geographical origin of food products. Food Chem. 2008, 107, 897–911. [Google Scholar] [CrossRef]
  2. Lakshmi, V. Food adulteration. Int. J. Sci. Invent. Today 2012, 1, 101–113. [Google Scholar]
  3. Everstine, K. Economically Motivated Adulteration: Implications for Food Protection and Alternate Approaches to Detection. Ph.D. Thesis, University of Minnesota, Minneapolis, MN, USA, 2013. [Google Scholar]
  4. Ellis, D.I.; Brewster, V.L.; Dunn, W.B.; Allwood, J.W.; Golovanov, A.P.; Goodacre, R. Fingerprinting food: Current technologies for the detection of food adulteration and contamination. Chem. Soc. Rev. 2012, 41, 5706. [Google Scholar] [CrossRef] [PubMed]
  5. Tsagkaris, A.S.; Koulis, G.A.; Danezis, G.P.; Martakos, I.; Dasenaki, M.; Georgiou, C.A.; Thomaidis, N.S. Honey authenticity: Analytical techniques, state of the art and challenges. RSC Adv. 2021, 11, 11273. [Google Scholar] [CrossRef] [PubMed]
  6. Makowicz, E.; Jasicka-Misiak, I.; Teper, D.; Kafarski, P. HPTLC Fingerprinting—Rapid Method for the Differentiation of Honeys of Different Botanical Origin Based on the Composition of the Lipophilic Fractions. Molecules 2018, 23, 1811. [Google Scholar] [CrossRef] [PubMed]
  7. Gonzalvez, A.; Armenta, S.; de la Guardia, M. Trace-element composition and stable-isotope ratio for discrimination of foods with Protected Designation of Origin. Trends Anal. Chem. 2009, 28, 1295–1311. [Google Scholar] [CrossRef]
  8. Collins, E.J.T. Food adulteration and food safety in Britain in the 19th and early 20th centuries. Food Policy 1993, 18, 95–109. [Google Scholar] [CrossRef]
  9. Teletchea, F.; Maudet, C.; Hänni, C. Food and forensic molecular identification: Up-date and challenges. Trends Biotechnol. 2005, 23, 359–366. [Google Scholar] [CrossRef]
  10. Mori, C.; Matsumura, S. Current issues for mammalian species identification in forensic science: A review. Int. J. Legal Med. 2021, 135, 3–12. [Google Scholar] [CrossRef]
  11. Rossi Scalco, A.; Miller Devós Ganga, G.; Cristina De Oliveira, S.; Baker, G. Development and validation of a scale for identification of quality attributes of agri-food products in short chains. Geoforum 2020, 111, 165–175. [Google Scholar] [CrossRef]
  12. Lim, J.H.; Bae, D.; Fong, A. Titanium dioxide in food products: Quantitative analysis using ICP-MS and Raman spectroscopy. J. Agric. Food Chem. 2018, 66, 13533–13540. [Google Scholar] [CrossRef]
  13. Grassi, S.; Casiraghi, E.; Alamprese, C. Handheld NIR device: A non-targeted approach to assess authenticity of fish fillets and patties. Food Chem. 2018, 243, 382–388. [Google Scholar] [CrossRef]
  14. Manfredi, M.; Robotti, E.; Quasso, F.; Mazzucco, E.; Calabrese, G.; Marengo, E. Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics. Spectrochim. Acta A Mol. Biomol. Spectrosc. 2018, 189, 427–435. [Google Scholar] [CrossRef]
  15. Gajek, M.; Pawlaczyk, A.; Szynkowska-Jozwik, M.I. Multi-Elemental Analysis of Wine Samples in Relation to Their Type, Origin, and Grape Variety. Molecules 2021, 26, 214. [Google Scholar] [CrossRef]
  16. Peng, C.; Zhang, Y.; Song, W.; Cai, H.; Wang, Y.; Granato, D. Characterization of Brazilian coffee based on isotope ratio mass spectrometry (δ13C, δ18O, δ2H, and δ15N) and supervised chemometrics. Food Chem. 2019, 297, 124963. [Google Scholar] [CrossRef]
  17. Park, J.H.; Choi, S.H.; Bong, Y.S. Geographical origin authentication of onions using stable isotope ratio and compositions of C, H, O, N, and S. Food Control 2019, 101, 121–125. [Google Scholar] [CrossRef]
  18. Barberis, E.; Amede, E.; Dondero, F.; Marengo, E.; Manfredi, M. New Non-Invasive Method for the Authentication of Apple Cultivars. Foods 2022, 11, 89. [Google Scholar] [CrossRef]
  19. Datta, A.; Sharma, A.N.G.V. Quantification of minor and trace elements in raw and branded turmeric samples using instrumental neutron activation analysis utilizing apsara-U reactor for possible applications to forensic science. J. Radioanal. Nucl. Chem. 2020, 325, 967–975. [Google Scholar] [CrossRef]
  20. Saadata, S.; Pandyaa, H.; Deya, A.; Rawtani, D. Food forensics: Techniques for authenticity determination of food products. Forensic Sci. Int. 2022, 333, 111243. [Google Scholar] [CrossRef]
  21. Laursen, K.H.; Schjoerring, J.K.; Kelly, S.D.; Husted, S. Authentication of organically grown plants—Advantages and limitations of atomic spectroscopy for multi-element and stable isotope analysis. TrAC Trends Anal. Chem. 2014, 59, 73–82. [Google Scholar] [CrossRef]
  22. Barbosa, R.M.; Nacano, L.R.; Freitas, R.; Batista, B.L.; Barbosa Jr, F. The use of decision trees and naïve bayes algorithms and trace element patterns for controlling the authenticity of free-range-pastured hens’ eggs. J. Food Sci. 2014, 79, 1672–1677. [Google Scholar] [CrossRef]
  23. Rodrigues, S.M.; Otero, M.; Alves, A.A.; Coimbra, J.; Coimbra, M.A.; Pereira, E.; Duarte, A.C. Elemental analysis for categorization of wines and authentication of their certified brand of origin. J. Food Compos. Anal. 2011, 24, 548–562. [Google Scholar] [CrossRef]
  24. Farmaki, E.G.; Thomaidis, N.S.; Minioti, K.S.; Ioannou, E.; Georgiu, C.A.; Efstathiou, C.E. Geographical characterization of Greek olive oils using rare earth elements content and supervised chemometric techniques. Anal. Lett. 2012, 45, 920–932. [Google Scholar] [CrossRef]
  25. Baroni, M.V.; Podio, N.S.; Badini, R.; Inga, C.M.; Ostera, H.; Cagnoni, M.; Gautier, E.A.; Peral-Garcia, P.; Hoogewerff, J.; Wunderlin, D.A. Linking soil, water, and honey composition to assess the geo-graphical origin of Argentinean honey by multielemental and isotopic analyses. J. Agric. Food Chem. 2015, 63, 4638–4645. [Google Scholar] [CrossRef]
  26. Barbosa, R.M.; Batista, B.L.; Varrique, R.M.; Coelho, V.A.; Campiglia, A.D.; Barbosa, F., Jr. The use of advanced chemometric techniques and trace element levels for controlling the authenticity of organic coffee. Food Res. Int. 2014, 61, 246–251. [Google Scholar] [CrossRef]
  27. Ma, G.; Zhang, Y.; Zhang, J.; Wang, G.; Chen, L.; Zhang, M.; Liu, T.; Liu, X.; Lu, C. Determining the geographical origin of Chinese green tea by linear discriminant analysis of trace metals and rare earth elements: Taking Dongting Biluochun as an example. Food Control 2016, 59, 714–720. [Google Scholar] [CrossRef]
  28. Camin, F.; Wehrens, R.; Bertoldi, D.; Bontempo, L.; Ziller, L.; Perini, M.; Nicolini, G.; Nocetti, M.; Larcher, R. H, C, N and S stable isotopes and mineral profiles to objectively guarantee the authenticity of grated hard cheeses. Anal. Chim. Acta 2012, 711, 54–59. [Google Scholar] [CrossRef]
  29. Drivelos, S.A.; Higgins, K.; Kalivas, J.H.; Haroutounian, S.A.; Georgiou, C.A. Data fusion for food authentication. Combining rare earth elements and trace metals to discriminate ‘‘Fava Santorinis’’ from other yellow split peas using chemometric tools. Food Chem. 2014, 165, 316–322. [Google Scholar] [CrossRef]
  30. Danezis, G.P.; Tsagkaris, A.S.; Brusic, V.; Georgiou, C.A. Food authentication: State of the art and prospects. Curr. Opin. Food Sci. 2016, 10, 22–31. [Google Scholar] [CrossRef]
  31. Ibáñez, C.; García-Cañas, V.; Valdés, A.; Simó, C. Novel MS-based approaches and applications in food metabolomics. Trends Anal. Chem. 2013, 52, 100–111. [Google Scholar] [CrossRef]
  32. Bat, K.B.; Vodopivec, B.M.; Eler, K.; Ogrinc, N.; Mulič, I.; Masuero, D.; Vrhovšek, U. Primary and secondary metabolites as a tool for differentiation of apple juice according to cultivar and geographical origin. LWT 2018, 90, 238–245. [Google Scholar] [CrossRef]
  33. Guo, J.; Yuan, Y.; Dou, P.; Yue, T. Multivariate statistical analysis of the polyphenolic constituents in kiwifruit juices to trace fruit varieties and geographical origins. Food Chem. 2017, 232, 552–559. [Google Scholar] [CrossRef] [PubMed]
  34. Sagratini, G.; Maggi, F.; Caprioli, G.; Cristalli, G.; Ricciutelli, M.; Torregiani, E.; Vittori, S. Comparative study of aroma profile and phenolic content of montepulcano monovarietal red wines from the marches and abruzzo regions of Italy using HS-SPME–GC–MS and HPLC–MS. Food Chem. 2012, 132, 1592–1599. [Google Scholar] [CrossRef] [PubMed]
  35. Liu, J.; Chen, N.; Yang, J.; Yang, B.; Ouyang, Z.; Wu, C.; Yuan, Y.; Wang, W.; Chen, M. An integrated approach combining HPLC, GC/MS, NIRS, and chemometrics for the geographical discrimination and commercial categorization of saffron. Food Chem. 2018, 253, 284–292. [Google Scholar] [CrossRef]
  36. Opatić, A.M.; Nečemer, M.; Lojen, S.; Masten, J.; Zlatić, E.; Šircelj, H.; Stopar, D.; Vidrih, R. Determination of geographical origin of commercial tomato through analysis of stable isotopes, elemental composition and chemical markers. Food Control 2018, 89, 133–141. [Google Scholar] [CrossRef]
  37. Yudthavorasit, S.; Wongravee, K.; Leepipatpiboon, N. Characteristic fingerprint based on gingerol derivative analysis for discrimination of ginger (Zingiber officnale) according to geographical origin using HPLC-DAD combined with chemometrics. Food Chem. 2014, 158, 101–111. [Google Scholar] [CrossRef]
  38. Wisniewska, P.; Sliwinska, M.; Namiesnik, J.; Wardencki, W.; Dymerski, T. 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. J. Anal. Methods Chem. 2016, 5, 1–12. [Google Scholar] [CrossRef]
  39. Heinz, H.A.; Elkins, J.T. Comparison of unaged and barrel aged whiskies from the same Mash Bill using gas chromatography/mass spectrometry. J. Brew. Distill. 2019, 8, 1–6. [Google Scholar]
  40. Daute, M.; Jack, F.; Baxter, I.; Harrison, B.; Grigor, J.; Walker, G. Comparison of Three Approaches to Assess the Flavour Characteristics of Scotch Whisky Spirit. Appl. Sci. 2021, 11, 1410. [Google Scholar] [CrossRef]
  41. Wisniewska, P.; Boqué, R.; Borràs, E.; Busto, O.; Wardencki, W.; Namieśnik, J.; Dymerski, T. Authentication of whisky due to its botanical origin and way of production by instrumental analysis and multivariate classification methods. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2017, 173, 849–853. [Google Scholar] [CrossRef]
  42. Stupak, M.; Goodall, I.; Tomaniova, M.; Pulkrabova, J.; Hajslova, J. A novel approach to assess the quality and authenticity of Scotch Whisky based on gas chromatography coupled to high resolution mass spectrometry. Anal. Chim. Acta 2018, 1042, 60–70. [Google Scholar] [CrossRef]
  43. Cvetkovic, D.; Stojilkovic, P.; Zvezdanovic, J.; Stanojevic, J.; Stanojevic, L.; Karabegovic, I. The identification of volatile aroma compounds from local fruit based spirits using a headspace solid-phase microextraction technique coupled with the gas chromatography-mass spectrometry. Adv. Technol. 2020, 9, 19–28. [Google Scholar] [CrossRef]
  44. Fortunato, G.; Mumic, K.; Wunderli, S.; Pillonel, L.; Bosset, J.O.; Gremaud, G. Application of strontium isotope abundance ratios measured by MC-ICP-MS for food authentication. J. Anal. At. Spectrom. 2004, 19, 227–234. [Google Scholar] [CrossRef]
  45. Kelly, S.; Heaton, K.; Hoogewerff, J. Tracing the geographical origin of food: The application of multi-element and multi-isotope analysis. Trends Food Sci. Tech. 2005, 16, 555–567. [Google Scholar] [CrossRef]
  46. Manca, G.; Franco, M.A.; Versini, G.; Camin, F.; Rossmann, A.; Tola, A. Correlation between multielement stable isotope ratio and geographical origin in Peretta cows’ milk cheese. J. Dairy Sci. 2006, 89, 831. [Google Scholar] [CrossRef]
  47. Longobardi, F.; Casiello, G.; Ventrella, A.; Mazzilli, V.; Nardelli, A.; Sacco, D.; Catucci, L.; Agostiano, A. Electronic nose and isotope ratio mass spectrometry in combination with chemometrics for the characterization of the geographical origin of Italian sweet cherries. Food Chem. 2015, 170, 90–96. [Google Scholar] [CrossRef]
  48. Longobardi, F.; Casiello, G.; Cortese, M.; Perini, M.; Camin, F.; Catucci, L.; Agostiano, A. Discrimination of geographical origin of lentils (Lens culinaris Medik.) using isotope ratio mass spectrometry combined with chemometrics. Food Chem. 2015, 188, 343–349. [Google Scholar] [CrossRef]
  49. De Rijke, E.; Schoorl, J.C.; Cerli, C.; Vonhof, H.B.; Verdegaal, S.J.A.; Vivó-Truyols, G.; Lopatka, M.; Dekter, R.; Bakker, D.; Sjerps, M.J.; et al. The use of δ2H and δ18O isotopic analyses combined with chemometrics as a traceability tool for the geographical origin of bell peppers. Food Chem. 2016, 204, 122–128. [Google Scholar] [CrossRef]
  50. Luo, D.; Dong, H.; Luo, H.; Xian, Y.; Wan, J.; Guo, X.; Wu, Y. The application of stable isotope ratio analysis to determine the geographical origin of wheat. Food Chem. 2015, 174, 197–201. [Google Scholar] [CrossRef]
  51. Fan, S.; Zhong, Q.; Gao, H.; Wang, D.; Li, G.; Huang, Z. Elemental profile and oxygen isotope ratio (δ18 O) for verifying the geographical origin of Chinese wines. J. Food Drug Anal. 2018, 26, 1033–1044. [Google Scholar] [CrossRef]
  52. Dinca, O.R.; Ionete, R.E.; Costinel, D.; Geana, I.E.; Popescu, R.; Stefanescu, I.; Radu, G.L. Regional and vintage discrimination of romanian wines based on elemental and isotopic fingerprinting. Food Anal. Methods. 2016, 9, 2406–2417. [Google Scholar] [CrossRef]
  53. Ciepielowski, G.; Pacholczyk-Sienicka, B.; Fraczek, T.; Klajman, K.; Paneth, P.; Albrecht, L. Comparison of quantitative NMR and IRMS spectrometry for the authentication of “Polish Vodka”. J. Sci. Food Agric. 2019, 99, 263–268. [Google Scholar] [CrossRef] [PubMed]
  54. Aylott, R. Chapter 16—Analytical strategies supporting protected designations of origin for alcoholic beverages. In Comprehensive Analytical Chemistry, 2nd ed.; de la Guardia, M., Gonzálvez, A., Eds.; Elsevier: London, UK, 2013; Volume 60, pp. 409–438. [Google Scholar] [CrossRef]
  55. Reid, K.J.G.; Swan, J.S.; Gutteridge, C.S. Assessment of Scotch whisky quality by pyrolysis-mass spectrometry and the subsequent correlation of quality with the oak wood cask. J. Anal. Appl. Pyrolysis 1993, 25, 49–62. [Google Scholar] [CrossRef]
  56. Wisniewska, P.; Dymerski, T.; Wardencki, W.; Namiesnik, J. Chemical composition analysis and authentication of whisky. J. Sci. Food Agric. 2015, 95, 2159–2166. [Google Scholar] [CrossRef]
  57. Campo, E.; Cacho, J.; Ferreira, V. Solid phase extraction, multidimensional gas chromatography mass spectrometry determination of four novel aroma powerful ethyl esters: Assessment of their occurrence and importance in wine and other alcoholic beverages. J. Chromatogr. A 2007, 1140, 180–188. [Google Scholar] [CrossRef]
  58. Campillo, N.; Peñalver, R.; Hernández-Córdoba, M. Solid-phase microextraction for the determination of haloanisoles in wines and other alcoholic beverages using gas chromatography and atomic emission detection. J. Chromatogr. A 2008, 1210, 222–228. [Google Scholar] [CrossRef]
  59. Barbeira, P.J.S.; Stradiotto, N.R. Anodic stripping voltammetric determination of Zn, Pb and Cu traces in whisky samples. Fresen. J. Anal. Chem. 1998, 361, 507–509. [Google Scholar] [CrossRef]
  60. Adam, T.; Duthie, E.; Feldmann, J. Investigations into the use of copper and other metals as indicators for the authenticity of Scotch whiskies. J. Inst. Brew. 2002, 108, 459–464. [Google Scholar] [CrossRef]
  61. Gajek, M.; Pawlaczyk, A.; Jozwik, K.; Szynkowska-Jozwik, M.I. The Elemental Fingerprints of Different Types of Whisky as Determined by ICP-OES and ICP-MS Techniques in Relation to Their Type, Age, and Origin. Foods 2022, 11, 1616. [Google Scholar] [CrossRef]
  62. Shand, C.A.; Wendler, R.; Dawson, D.; Yates, K.; Stephenson, H. Multivariate analysis of Scotch whisky by total reflection x-ray fluorescence and chemometric methods: A potential tool in the identification of counterfeits. Anal. Chim. Acta 2017, 976, 14–24. [Google Scholar] [CrossRef]
  63. Pawlaczyk, A.; Gajek, M.; Jozwik, K.; Szynkowska, M.I. Multielemental Analysis of Various Kinds of Whisky. Molecules 2019, 24, 1193. [Google Scholar] [CrossRef]
  64. Regulation of the Minister of Health on the Maximum Levels of Biological and Chemical Contaminants that May Be Present in Food, Food Ingredients, Permitted Additives, Processing Aids or on the Surface of Food of 13 January 2003 (Journal of Laws of 2003). Available online: Sejm.gov.pl (accessed on 10 December 2021).
  65. Phosphorus, Soil Phosphorus. Forest Encyclopedia. Available online: https://www.encyklopedialesna.pl/haslo/fosfor-fosfor-glebowy/ (accessed on 12 May 2022).
  66. Jama, A.; Nowak, W. Uptaking of Macronutrients from the Soil Covered with Sewage Sludge by Willow (Salix viminalis L.) and Its Hybrids. Nauka Przyr. Technol. 2011, 5, 6. [Google Scholar]
  67. Surgiewicz, J. Mangan i jego związki. Podstawy I Metod. Oceny Sr. Pr. 2012, 1, 111–116. [Google Scholar]
  68. Wanikawa, A.; Sugimoto, T. A Narrative Review of Sulfur Compounds in Whisk(e)y. Molecules 2022, 27, 1672. [Google Scholar] [CrossRef]
  69. Leppänen, O.; Ronkainen, P.; Denslow, J.; Laakso, R.; Lindeman, A.; Nykanen, I. Polysulphides and thiophenes in whisky. In Flavour of Distilled Beverages: Origin and Development; Piggott, J.R., Ed.; E. Horwood Ltd.: Chichester, UK, 1983; pp. 206–214. [Google Scholar]
  70. Leppänen, O.; Denslow, J.; Ronkainen, P. A gas chromatographic method for the accurate determination of low concentrations of volatile sulphur compounds in alcoholic beverages. J. Inst. Brew. 1979, 85, 350–353. [Google Scholar] [CrossRef]
  71. Ashok, P.C.; Praveen, B.B.; Dholakia, K. Near infrared spectroscopic analysis of single malt Scotch whisky on an optofluidic chip. Opt. Express 2011, 19, 22982–22992. [Google Scholar] [CrossRef]
  72. Backhaus, A.; Ashok, P.C.; Praveen, B.B.; Dholakia, K.; Seiffert, U. Classifying Scotch whisky from near-infrared Raman spectra with a radial basis function network with relevance learning. In Proceedings of the 20th European Symposium on Artificial Neural Networks, Bruges, Belgium, 25–27 April 2012. [Google Scholar]
  73. McIntyre, A.C.; Bilyk, M.L.; Nordon, A.; Colquhoun, G.; Littlejohn, D. Detection of counterfeit Scotch whisky samples using mid-infrared spectrometry with an attenuated total reflectance probe incorporating polycrystalline silver halide fibres. Anal. Chim. Acta 2011, 690, 228–233. [Google Scholar] [CrossRef]
  74. Meier-Augenstein, W.; Kemp, H.F.; Hardie, S.M.L. Detection of counterfeit Scotch whisky by 2H and 18O stable isotope analysis. Food Chem. 2012, 133, 1070–1074. [Google Scholar] [CrossRef]
  75. Garcia, J.S.; Vaz, B.G.; Corilo, Y.E.; Ramires, C.F.; Saraiva, S.A.; Sanvido, G.B.; Schmidt, E.M.; Maia, D.R.J.; Cosso, R.G.; Zacca, J.J.; et al. Whisky analysis by electrospray ionization-Fourier transform mass spectrometry. Food Res. Int. 2013, 51, 98–106. [Google Scholar] [CrossRef]
Foods 11 02810 g001 550
Figure 1. PCA score plot of 3-year-old authentic (A) and fake (F1–35) whisky samples.
Figure 1. PCA score plot of 3-year-old authentic (A) and fake (F1–35) whisky samples.
Foods 11 02810 g001
Foods 11 02810 g002 550
Figure 2. PCA score plot of fake whisky with division on 9 different sources of samples.
Figure 2. PCA score plot of fake whisky with division on 9 different sources of samples.
Foods 11 02810 g002
Table
Table 1. Characteristics of the tested set of samples.
Table 1. Characteristics of the tested set of samples.
nAuthenticFake
17035
Number of Samples from a Given Source
S1–7S2–9S3–6S4–2S5–3S6–4S7–2S8–1S9–1
Total205
S1–S9 code of source of origin (e.g., S1—source no 1).
Table
Table 2. Basic statistics for determined elements for all counterfeit samples (n = 35) [µg/L].
Table 2. Basic statistics for determined elements for all counterfeit samples (n = 35) [µg/L].
ElementnMeanMedianMinMaxElementnMeanMedianMinMax
Ag351.280<LOQ<LOQ8.600Sb350.5400.300<LOQ3.000
Al168.4163.3<LOQ470.7Sn13.899.810<LOQ34.70
B37942397<LOQ19,019Sr133.053.7214.146765.1
Ba199.6189.0117.3378.0Te0.060<LOQ<LOQ1.100
Be0.1300.110<LOQ0.500Tl0.2100.030<LOQ2.100
Bi3.2200.600<LOQ25.80U0.3600.190<LOQ3.100
Cd6.1100.760<LOQ65.90V1.6800.910<LOQ10.40
Co9.9205.2601.40942.20Ca35,72922,9141994271,134
Cr182.5112.354.57770.3Fe174.729.98<LOQ2735
Cu238356.861.92233,212K97,09110,882<LOQ670,611
Li67.1219.25<LOQ825.4Mg53701577465.433,074
Mn76.7551.392.377438.7P735274.29<LOQ56,793
Mo11.071.590<LOQ108.4S20,88514,679197.6231,701
Ni62.7139.862.418411.0Ti43.4925.35<LOQ316.8
Pb12.8411.21<LOQ35.60Zn2987274.8<LOQ39,815
Table
Table 3. Contents of selected elements (with statistically significant differences) in the measured fake and authentic alcohol samples (n = 205) [µg/L].
Table 3. Contents of selected elements (with statistically significant differences) in the measured fake and authentic alcohol samples (n = 205) [µg/L].
ElementCodeNMeanMedianMinMaxStd. Dev.
9BeA1700.1000.092<LOQ0.3000.050
F350.1300.120<LOQ0.5000.100
59CoA1704.5302.4680.40674.907.870
F359.9205.2601.40942.2010.10
63CuA170473.7216.016.255252736.4
F35402156.861.92233,2127367
7LiA17021.3612.270.474399.535.40
F3567.1219.25<LOQ825.4140.8
95MoA1701.7901.066<LOQ32.303.320
F3511.071.590<LOQ108.430.30
60NiA17024.0112.963.201301.333.68
F3562.7139.862.418411.073.70
118SnA1709.8004.672<LOQ44.5011.31
F3513.899.810<LOQ34.7011.00
88SrA17047.1845.8115.84119.219.80
F35133.053.7214.15765.1168.8
Ca 393.366A17014,6559185723.8175,35317,983
F3535,72922,9141994271,13450,189
Mg 279.553A17014871046208.511,54813,926
F3553701577465.433,074764
S 180.731A17071264648296.769,9078654
F3520,88514,679197.6231,70139,556
pH valueA1703.633.631.956.200.68
F354.714.392.798.701.50
Table
Table 4. Groups with statistically significant differences.
Table 4. Groups with statistically significant differences.
Statistically Significant DifferencesElements
Source 6–Source 2B
Source 3–Source 2Fe; Mn; Mo; Sn
Source 1–Source 2Bi; Cd; Co; Ni; Pb; Zn
Table
Table 5. Contents of selected elements (with statistically significant differences) in the measured fake alcohol samples (n = 35) [µg/L].
Table 5. Contents of selected elements (with statistically significant differences) in the measured fake alcohol samples (n = 35) [µg/L].
ElementNo. of SourceNMeanMedianMinMaxStd. Dev.
11B1720642238<LOQ32891055
2918031704190.737581158
362503272817043059657.0
6490788413597013.523318
209Bi1712.7510.359.38725.775.870
29<LOQ<LOQ<LOQ<LOQ<LOQ
360.8470.419<LOQ3.5431.347
642.3002.705<LOQ3.7901.618
111Cd1726.0511.063.20465.9028.11
290.019<LOQ<LOQ0.1280.042
362.6902.166<LOQ7.3252.857
640.7240.6590.1711.4100.510
59Co1726.0923.9013.7742.219.000
293.8403.4361.4097.6131.895
367.2185.5843.69812.534.056
645.9854.6903.50411.063.430
55Mn1739.5537.1816.8573.9418.72
2914.125.1922.37764.1620.26
36143.481.2764.16438.7147.1
6449.8931.596.299130.058.44
95Mo171.2801.560<LOQ2.1300.840
290.2890.242<LOQ0.9880.339
3656.6859.581.982108.456.76
642.9532.4241.2185.7501.947
60Ni1779.7557.4634.79136.243.85
2913.7710.212.41930.1110.04
36110.447.6619.14411.0150.9
6475.3674.3069.3483.496.114
208Pb1729.6530.7522.9935.604.430
293.6771.186<LOQ21.897.008
3610.7213.383.56913.424.308
6412.0912.436.55316.955.358
118Sn174.3304.737<LOQ8.6002.860
2917.0919.979.31020.414.627
3629.6329.5923.4234.653.617
648.2574.651<LOQ23.7310.55
Fe 238.2041749.0047.75<LOQ90.6733.67
290.036<LOQ<LOQ0.3160.105
36669.7233.2<LOQ27351035
647.496<LOQ<LOQ29.9814.99
Zn 213.8561711,0055668435339,81512,795
2990.470.144<LOQ429.3152.5
36859.7725.1111.21891704.8
64418977.29<LOQ16,6038276
<LOQ—limit of quantification
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Gajek, M.; Pawlaczyk, A.; Maćkiewicz, E.; Albińska, J.; Wysocki, P.; Jóźwik, K.; Szynkowska-Jóźwik, M.I. Assessment of the Authenticity of Whisky Samples Based on the Multi-Elemental and Multivariate Analysis. Foods 2022, 11, 2810. https://0-doi-org.brum.beds.ac.uk/10.3390/foods11182810

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Gajek M, Pawlaczyk A, Maćkiewicz E, Albińska J, Wysocki P, Jóźwik K, Szynkowska-Jóźwik MI. Assessment of the Authenticity of Whisky Samples Based on the Multi-Elemental and Multivariate Analysis. Foods. 2022; 11(18):2810. https://0-doi-org.brum.beds.ac.uk/10.3390/foods11182810

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Gajek, Magdalena, Aleksandra Pawlaczyk, Elżbieta Maćkiewicz, Jadwiga Albińska, Piotr Wysocki, Krzysztof Jóźwik, and Małgorzata Iwona Szynkowska-Jóźwik. 2022. "Assessment of the Authenticity of Whisky Samples Based on the Multi-Elemental and Multivariate Analysis" Foods 11, no. 18: 2810. https://0-doi-org.brum.beds.ac.uk/10.3390/foods11182810

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