Untargeted flavor profiling of lager beers by stir bar sorptive extraction -capillary gas chromatography - time-of-flight mass spectrometry: High analytical performance with a green touch.

Beer is one of the most popular beverages in the world and its complex flavor is widely appreciated. Beer flavor profiling is important for brewers to optimize beer production and to guarantee odor quality and taste stability of the final products. This is especially the case for pale lager beers that represent the beer type with the largest worldwide production volume. In this study, the combination of stir bar sorptive extraction (SBSE) with capillary gas chromatography (GC) hyphenated to time-of-flight mass spectrometry (TOFMS) was used to perform a detailed aroma profiling of lager beer samples originating from Belgium, The Netherlands, and France. A generic SBSE method was applied resulting in a very broad extraction coverage of odor solutes, while the extraction process is miniaturized, unattended and solventless, meeting green analytical chemistry requirements. Using GC-TOFMS analysis operated in untargeted mode, MS deconvolution and statistical data analysis, with principal component and hierarchical clustering analysis, it was possible to clearly differentiate brands and origins of the beer samples and to identify marker compounds for flavor profiling of these closely related beer samples. An extended database of beer aroma compounds was created. The developed method can be applied in beer quality optimization and quality control in routine laboratories.

How much are we exposed to alcohol in electronic media? Development of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA).

BACKGROUND: Evidence demonstrates that seeing alcoholic beverages in electronic media increases alcohol initiation and frequent and excessive drinking, particularly among young people. To efficiently assess this exposure, the aim was to develop the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA) to automatically identify beer, wine and champagne/sparkling wine from images. METHODS: Using a specifically developed software, three coders annotated 57,186 images downloaded from Google. Supplemented by 10,000 images from ImageNet, images were split randomly into training data (70 %), validation data (10 %) and testing data (20 %). For retest reliability, a fourth coder re-annotated a random subset of 2004 images. Algorithms were trained using two state-of-the-art convolutional neural networks, Resnet (with different depths) and Densenet-121. RESULTS: With a correct classification (accuracy) of 73.75 % when using six beverage categories (beer glass, beer bottle, beer can, wine, champagne, and other images), 84.09 % with three (beer, wine/champagne, others) and 85.22 % with two (beer/wine/champagne, others), Densenet-121 slightly outperformed all Resnet models. The highest accuracy was obtained for wine (78.91 %) followed by beer can (77.43 %) and beer cup (73.56 %). Interrater reliability was almost perfect between the coders and the expert (Kappa = .903) and substantial between Densenet-121 and the coders (Kappa = .681). CONCLUSIONS: Free from any response or coding burden and with a relatively high accuracy, the ABIDLA offers the possibility to screen all kinds of electronic media for images of alcohol. Providing more comprehensive evidence on exposure to alcoholic beverages is important because exposure instigates alcohol initiation and frequent and excessive drinking.

What are the perceived target groups and occasions for wines and beers labelled with verbal and numerical descriptors of lower alcohol strength? An experimental study.

OBJECTIVES: Alcohol consumption is the fifth leading cause of morbidity and mortality globally. The development and promotion of lower strength alcohol products may help reduce alcohol consumption and associated harms. This study assessed what a sample of UK weekly drinkers perceived to be the target groups and occasions for drinking wines and beers labelled with different verbal and numerical descriptors of lower alcohol strength. DESIGN AND PARTICIPANTS: 3390 adults (1697 wine and 1693 beer drinkers) were sampled from a nationally representative UK panel, and participated in a between-subjects experiment in which participants were randomised to 1 of 18 groups with one of three levels of verbal descriptor (Low vs. Super Low vs. No verbal descriptor) and six levels of %ABV (five levels varying for wine and beer, and no level given). MEASURES: The study gauged participants' perceptions of the type of person that would find the randomised beverage appealing and the type of occasion on which the beverage is likely to be drunk at. RESULTS: A principal component analysis showed that participants perceived pregnant women, sportspeople and those aged 6-13 years old were the target groups for products labelled with 0%ABV or the verbal descriptors Low or Super Low, whereas men, women, and those aged above 18 were perceived as the target groups for products labelled with higher %ABV. Participants also rated the products labelled with 0%ABV or the verbal descriptors Low or Super Low as targeting consumption on weekday lunches, whereas products labelled with higher %ABV were rated as targeting dinner/evening occasions, including parties, holidays and celebrations. CONCLUSIONS: Lower strength products were seen as targeting non-traditional consumers (pregnant women) and occasions (weekday lunchtimes), suggesting these products may be perceived as extensions to regular strength alcoholic drinks rather than as substitutes for them.

Análise físico-química de cervejas artesanais comercializadas em Guaratinguetá-SP / Physical-chemical analysis of artisan beverages marketed in Guaratinguetá-SP

A cerveja é a bebida alcoólica mais consumida no mundo, sendo que as artesanais têm ampliado sua participação no mercado. Este trabalho objetivou caracterizar físico-quimicamente e agrupar cervejas artesanais de diferentes estilos encontradas no comércio da cidade de Guaratinguetá-SP. Foram analisadas 5 cervejas artesanais denominadas de A, B, C, D e E, em duplicata. A acidez total variou de 28,42 a 42,63 mEq/L, o teor de sólidos solúveis de 4,8 a 8,0 °Brix e o teor alcoólico de 5,90 a 9,25 % (v/v), sendo que todas as amostras apresentaram valores superiores ao descrito no rótulo. O valor médio do pH foi de 4,55 e a cor oscilou de 12,67 a 38,77 EBC. Pelas análises exploratórias PCA e HCA observou-se que os estilos Weissbier e Irish Red Ale apresentaram uma menor distinção entre os parâmetros físico-químicos analisados.

Fast and direct amperometric analysis of polyphenols in beers using tyrosinase-modified screen-printed gold nanoparticles biosensors.

In this work it is explored a real applicability of miniaturised and portable biosensing technology for the estimation of total phenolic content in 15 different commercial beers by applying direct amperometry. Gold nanoparticles screen-printed electrodes were thoroughly modified with tyrosinase (Tyr-AuNPS-SPCEs), which was immobilised on the surface by crosslinking with glutaraldehyde. All chemical and instrumental variables involved in the electrochemical method were optimised to develop a reliable and powerful tool to estimate rapidly the content of phenolic compounds in complex beer samples. Catechol, phenol, caffeic acid and tyrosol were analysed individually using the proposed methodology and good analytical and kinetic performances were obtained. Total phenolic content in tested beers (high fermented, low fermented and non-alcoholic) were expressed as mg L-1 of tyrosol, which is one of the major phenolic compound reported in beer. Moreover, the developed amperometric methodology was successfully benchmarked against standardised Folin-Ciocalteau spectrophotometric method with a good Pearson correlation (r = 0.821, p < 0.01). Hierarchical Cluster Analysis (HCA) was also applied on electrochemical results and a good capability to group tested beers based on their tyrosol concentration was demonstrated.

Unveiling the lager beer volatile terpenic compounds.

Beer volatile terpenic compounds arise from a network of variables, namely from plant raw-materials metabolism, yeast metabolism, among others, and may suffer modifications during brewing. In order to increase the molecular understanding of beer volatile terpenic compounds, this work intends to perform a comprehensive characterization of these molecules on lager beer, using an advanced multidimensional chromatographic methodology. This research comprises the most detailed screening of lager beer terpenic compounds through the putative identification of 94 mono and sesquiterpenic compounds, distributed over 6 chemical families: alcohols, aldehydes, esters, ketones, hydrocarbons, and oxides. The terpenic profiles allowed the beer terpen-typing according to samples' category clustering: macro and micro-brewer beers. This study adds further insight to the lager beer terpenic volatile composition, and could be applied in large-scale studies in different contexts, namely for understanding the distinctive beer styles or for beer typing.

Influence of malt source on beer chemistry, flavor, and flavor stability.

Beverage quality in the brewing industry is heavily influenced by ingredient properties. The contribution of raw ingredients such as yeast and hops to beer flavor is well understood. However, the influence of barley genotype and/or environment on flavor (the malt 'source') is largely unexplored. Here, a study was performed to determine (i) if there are metabolite differences among six commercial malt sources, (ii) if differences in malt chemistry are reflected in the chemistry of the beer, and (iii) if the differences in the beer chemistry impact sensory attributes of beer, through flavor and flavor stability. Six distinct sources of malts (six varieties from three maltsters) were brewed into six beers using a recipe designed to evaluate differences in flavor. Metabolomics and ionomics was used to characterize chemical variation among the six malts and beers using UHPLC- and HILIC-MS (non-volatile metabolites), HS-SPME/GC-MS (beer volatiles), and ICP-MS (malt metals). These analyses detected a total of 5042 compounds in malt, of which 217 were annotated and included amines, amino acids, fatty acids/lipids/fatty acyls, saccharides/glucosides/sugar acids/sugar alcohols, carboxylic acid derivatives, organic acids, phenolics/benzenoids, purines, pyrimidines/pyridines, terpenes, and organosulfurs. A total of 4568 compounds were detected in beer, of which 246 were annotated and included esters, aldehydes, and alcohols. Statistical analysis revealed chemical variation among the six malts (50/217 malt metabolites varied) and beers (150/246). The six beers were evaluated for flavor using a modified descriptive analysis for 45 sensory traits at 0, 4, and 8 weeks of storage at 4 °C. Principal component analysis of the sensory data revealed flavor differences among the six beers at 8 weeks, and the malt-type Full Pint was described as fruity and Meredith as corn chip. The metabolite and sensory data were integrated and revealed associations between flavor profiles in beer and the annotated malt and beer. The fruity or corn chip flavor profiles in beer were associated beer purines/pyrimidines, volatile ketones, amines, and phenolics, and malt lipids, saccharides, phenols, amines, and alkaloids. Taken together, these data support a role of malt source in beer flavor and flavor stability. As a raw ingredient, malting barley genotypes can be evaluated for a contribution to flavor, and this may be a future target for plant breeding, agronomy, and malting efforts to selectively improve flavor, flavor stability, and quality in beer.

Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers.

Biological and biochemical fingerprints were investigated for the first time for the feasibility of effect-directed classification, and thus, to allow the choice of a distinct beer with regard to beneficial health effects. A high-performance thin-layer chromatography method was newly developed and combined with in situ effect-directed analysis for profiling 50 German beers for multipotent active compounds, and thus, their health-related potential. Discovered multipotent active zones were online eluted and characterized by high resolution mass spectrometry. For example, isoxanthohumol, iso-α-ad/n-humulone or its isomers, desdimethyl-octahydro-isocohumulone and ad/n-humulone were proven as antimicrobial compounds, isoxanthohumol as an acetylcholinesterase inhibitor, and isoxanthohumol and iso-α-ad/n-humulone or its isomers as radical scavengers. Investigating multivariate data analysis of effect-directed fingerprints for the first time, the pattern recognition and classification results showed the power of clustering non-alcoholic beers from other types of beer, or it showed the differentiation of dark and non-alcoholic beers.

Tracing the origin of beer samples by NMR and chemometrics: Trappist beers as a case study.

An NMR and chemometric analytical approach to classify beers according to their brand identity was developed within the European TRACE project (FP6-2003-FOOD-2-A, contract number: 0060942). Rochefort 8 Trappist beers (47 samples), other Trappist beers (76 samples) and non-Trappist beers (110 samples) were analyzed by 1 H NMR spectroscopy. Selected NMR signals were measured and used to build classification models. Three different classification problems were identified, namely Trappist versus non-Trappist, Rochefort versus Non-Rochefort, and Rochefort 8 versus non-Rochefort 8. In all the three cases, both a discriminant and a modeling approaches were followed, using partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA), respectively, leading to very high classification accuracy as evaluated by external validation. Information regarding chemical composition was also obtained: Trappist beers contain a higher amount of formic and pyruvic acids and a lower amount of acetic acid and alanine with respect to non-Trappist ones. Rochefort beers turned out to have also a higher content of propanol and isopentanol with respect to non-Rochefort samples. Finally, Rochefort 8, shows the highest content of pyruvic acid and the lowest content of gallic, fumaric, acetic acids, adenosine, uridine, 2-phenylethanol, GABA, and alanine.

Complex Ancestries of Lager-Brewing Hybrids Were Shaped by Standing Variation in the Wild Yeast Saccharomyces eubayanus.

Lager-style beers constitute the vast majority of the beer market, and yet, the genetic origin of the yeast strains that brew them has been shrouded in mystery and controversy. Unlike ale-style beers, which are generally brewed with Saccharomyces cerevisiae, lagers are brewed at colder temperatures with allopolyploid hybrids of Saccharomyces eubayanus x S. cerevisiae. Since the discovery of S. eubayanus in 2011, additional strains have been isolated from South America, North America, Australasia, and Asia, but only interspecies hybrids have been isolated in Europe. Here, using genome sequence data, we examine the relationships of these wild S. eubayanus strains to each other and to domesticated lager strains. Our results support the existence of a relatively low-diversity (π = 0.00197) lineage of S. eubayanus whose distribution stretches across the Holarctic ecozone and includes wild isolates from Tibet, new wild isolates from North America, and the S. eubayanus parents of lager yeasts. This Holarctic lineage is closely related to a population with higher diversity (π = 0.00275) that has been found primarily in South America but includes some widely distributed isolates. A second diverse South American population (π = 0.00354) and two early-diverging Asian subspecies are more distantly related. We further show that no single wild strain from the Holarctic lineage is the sole closest relative of lager yeasts. Instead, different parts of the genome portray different phylogenetic signals and ancestry, likely due to outcrossing and incomplete lineage sorting. Indeed, standing genetic variation within this wild Holarctic lineage of S. eubayanus is responsible for genetic variation still segregating among modern lager-brewing hybrids. We conclude that the relationships among wild strains of S. eubayanus and their domesticated hybrids reflect complex biogeographical and genetic processes.

Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence, UV and visible spectroscopies.

We report an application of data fusion for chemometric classification of 135 canned samples of Chinese lager beers by manufacturer based on the combination of fluorescence, UV and visible spectroscopies. Right-angle synchronous fluorescence spectra (SFS) at three wavelength difference Δλ=30, 60 and 80 nm and visible spectra in the range 380-700 nm of undiluted beers were recorded. UV spectra in the range 240-400 nm of diluted beers were measured. A classification model was built using principal component analysis (PCA) and linear discriminant analysis (LDA). LDA with cross-validation showed that the data fusion could achieve 78.5-86.7% correct classification (sensitivity), while those rates using individual spectroscopies ranged from 42.2% to 70.4%. The results demonstrated that the fluorescence, UV and visible spectroscopies complemented each other, yielding higher synergic effect.

Beer classification by means of a potentiometric electronic tongue.

In this work, an electronic tongue (ET) system based on an array of potentiometric ion-selective electrodes (ISEs) for the discrimination of different commercial beer types is presented. The array was formed by 21 ISEs combining both cationic and anionic sensors with others with generic response. For this purpose beer samples were analyzed with the ET without any pretreatment rather than the smooth agitation of the samples with a magnetic stirrer in order to reduce the foaming of samples, which could interfere into the measurements. Then, the obtained responses were evaluated using two different pattern recognition methods, principal component analysis (PCA), which allowed identifying some initial patterns, and linear discriminant analysis (LDA) in order to achieve the correct recognition of sample varieties (81.9% accuracy). In the case of LDA, a stepwise inclusion method for variable selection based on Mahalanobis distance criteria was used to select the most discriminating variables. In this respect, the results showed that the use of supervised pattern recognition methods such as LDA is a good alternative for the resolution of complex identification situations. In addition, in order to show an ET quantitative application, beer alcohol content was predicted from the array data employing an artificial neural network model (root mean square error for testing subset was 0.131 abv).

A study of the antioxidant properties of beers using electron paramagnetic resonance.

The antioxidant properties of various kinds of beers were investigated using electron paramagnetic resonance (EPR) spectroscopy. This was possible by measuring the changes in the intensity of the EPR spectrum that resulted from the interaction of the stable radical DPPH (1,1-diphenyl-2-picrylhydrazyl) with the antioxidants found in a beer sample. The antioxidant capacity was then presented in Trolox Equivalents, e.g. µM trolox in a beer sample of 100ml. The influence of the type, colour, the content of the extract and alcohol on the antioxidant activities of commercial beer samples was investigated using two-way hierarchical clustering and analysis of variance. The results showed that all of the beers investigated exhibit antioxidant properties. By performing an analysis of variance, it was found that the value of the antioxidant capacity significantly (0.05 level of significance) depends on the content of the extract and the colour of the beer. It seems that additives also influence the antioxidant properties to some extent, but neither the alcohol content nor the kind of fermentation affects the antioxidant properties of beer.

Allergy to beer in LTP-sensitized patients: beers are not all the same.

BACKGROUND: Most cases of beer allergy reported so far have been associated with hypersensitivity to the non-specific lipid transfer protein (LTP). In view of the marked differences in brewing processes we assessed IgE reactivity as well as tolerance to many different beers in an allergic patient. METHODS: A 45 year-old man hypersensitive to grass pollen, cat dander and Alternaria tenuis with a history of urticaria and dyspnoea after drinking beer and a weak skin reactivity to commercial corn extract was studied. The patient underwent SPT with 36 different brands of beer and an open challenge with those scoring negative was performed. An immunoblot analysis was carried out using 2 SPT-positive beers, 2 SPT-negative beers, and barley, wheat, and maize extracts using both patient's serum and a maize LTP-specific in-house developed polyclonal antibody from rabbit. Further, the immune reactive LTP of one beer was separated by HPLC and the chromatogram was compared to that of purified maize LTP. RESULTS: Beer SPT scored positive in 30/36 cases. The immunoblot analysis showed IgE reactivity at about 10 kDa against the two SPT-positive beers and against maize with both patient's serum and the polyclonal anti-LTP rabbit serum, whereas the two SPT-negative beers, and barley extract scored negative. The immunodetected protein co-migrated with maize LTP. CONCLUSION: In beer-allergic patients the diagnostic workup may point to the detection of some tolerated products that can be consumed risk-free.

Discrimination and sensory description of beers through data fusion.

Beer samples of the same brand and commercialized as a same product, but brewed in four different factories were analyzed with three techniques, an MS e-nose, a mid-IR optical-tongue and a UV-visible, to see if the factories show differences and to find out if the differences found could be attributed to different sensory properties. The data from the three instruments were fused to improve the ability of classification with respect to the individual use of the techniques. Two levels of data fusion were studied: low and mid level fusion, and the classification was performed by linear discriminant analysis (LDA). Mid-level fusion provided better classification results (above 95% correct classification) than those of low-level fusion and also than those obtained when using the individual techniques. Moreover, by means of the score and loading plots obtained by Fisher-LDA, it was possible to interpret the chemical information provided by the three techniques, and we were able to relate the variables associated to each sensor to the main compounds responsible of the sensory perception.

Decision trees in selection of featured determined food quality.

The determination of food quality, authenticity and the detection of adulterations are problems of increasing importance in food chemistry. Recently, chemometric classification techniques and pattern recognition analysis methods for wine and other alcoholic beverages have received great attention and have been largely used. Beer is a complex mixture of components: on one hand a volatile fraction, which is responsible for its aroma, and on the other hand, a non-volatile fraction or extract consisting of a great variety of substances with distinct characteristics. The aim of this study was to consider parameters which contribute to beer differentiation according to the quality grade. Chemical (e.g. pH, acidity, dry extract, alcohol content, CO(2) content) and sensory features (e.g. bitter taste, color) were determined in 70 beer samples and used as variables in decision tree techniques. This pattern recognition techniques applied to the dataset were able to extract information useful in obtaining a satisfactory classification of beer samples according to their quality grade. Feature selection procedures indicated which features are the most discriminating for classification.

Application of artificial neural network in food classification.

Artificial neural network (ANN) classifiers have been successfully implemented for various quality inspection and grading tasks of diverse food products. ANN are very good pattern classifiers because of their ability to learn patterns that are not linearly separable and concepts dealing with uncertainty, noise and random events. In this research, the ANN was used to build the classification model based on the relevant features of beer. Samples of the same brand of beer but with varying manufacturing dates, originating from miscellaneous manufacturing lots, have been represented in the multidimensional space by data vectors, which was an assembly of 12 features (% of alcohol, pH, % of CO(2) etc.). The classification has been performed for two subsets, the first that included samples of good quality beer and the other containing samples of unsatisfactory quality. ANN techniques allowed the discrimination between qualities of beer samples with up to 100% of correct classifications.

Characterization and classification of the aroma of beer samples by means of an MS e-nose and chemometric tools.

An electronic nose based on coupling of headspace (HS) with a mass spectrometer (MS) has been used in this study to classify and characterize a series of beers according to their production site and chemical composition. With this objective, we analyzed 67 beers of the same brand and preparation process but produced in different factories. The samples were also subjected to sensory evaluation by a panel of experts. Linear discriminant analysis (LDA) was used as the classification technique and stepwise LDA based on Wilk's lambda criterion was used to select the most discriminating variables. To interpret the aroma characteristics of the beers from the m/z ions obtained, score and loading bi-plots were obtained by applying canonical variables. Because the beers analyzed were marketed with the same name and brand, we expected to be working with the same product irrespective of its origin. However, results from both sensory evaluation and use of the e-nose revealed differences between factories. With the e-nose it was possible to relate these differences to the presence (and abundance) of characteristic ions of different compounds typically found in beer. These results demonstrate that the HS-MS e-nose is not only an aroma sensor capable to classify and/or differentiate samples but it can also provide information about the compounds responsible for this differentiation.

Volatile compounds and the changes in their concentration levels during storage in beers containing varying malt concentrations.

Volatile compounds in beers brewed with different amounts of malt were analyzed by using the stir bar sorptive extraction-gas chromatography-mass spectrometry method. We identified 90 compounds-25 esters, 17 terpenes, 14 alcohols, 11 acids, 6 furans, 6 aroma compounds, 5 carbonyls, and other compounds. An analysis of aged beer suggested that the concentration levels of stale flavor compounds-beta-damascenone, gamma-nonalactone, ethyl cinnamate, and 2-methoxy-4-vinylphenol-in nonmalt beer were different from those in all-malt and standard beer. Additionally, concentrations of these compounds did not increase during storage in most nonmalt beer analyzed in this study. Nerolidol may be a good marker candidate regardless of the malt content.

Tobacco smoking and alcohol consumption as risk factors for site-specific intraoral epithelial dysplasia.

AIM: The aim of the present study was to evaluate the role of tobacco and alcohol as possible risk factors for oral epithelial dysplasia in the various oral subsites. METHODS: Data were gathered from 630 patients with oral epithelial dysplasia in the United Arab Emirates between 1997 and 2007. Odds ratios for oral epithelial dysplasia at various oral subsites were estimated using multiple logistic regression for each level of exposure of interest. RESULTS: The results showed that in males, oral epithelial dysplasia of the labial mucosa and floor of the mouth were strongly associated with tobacco smoking. In females, oral epithelial dysplasia of the floor of the mouth and tongue were the sites associated with tobacco smoking. Alcohol was not a significant determinant of the sites of oral epithelial dysplasia in either sex. CONCLUSION: Tobacco smoking has a significant role in determining the oral epithelial dysplasia subsites, but alcohol consumption is not a risk factor for oral epithelial dysplasia sites.