Beer Flavor Research Articles

Allergenic Potential of Common Hops (Humulus lupulus L.) in the Context of Cross-Reactions with Pollen Allergens.

Common hops (Humulus lupulus L.) play a key role in brewing, providing the bitterness, flavor, and aroma of beer, and are widely used in supplements for their antibacterial, anti-inflammatory, and antioxidant properties. However, despite their broad applications, the allergenic potential of common hops remains underexplored, particularly when compared to the closely related Humulus japonicus. This preliminary study aimed to investigate the allergenic potential of common hops and their potential cross-reactivity with common pollen allergens. The immunoreactivity of hop stalks, leaves, and cones was assessed using antibodies against major allergens from birch (Bet v1a), mugwort (Art v1), and timothy grass (Phl p5b), as well as three sera from pollen-allergic patients. Slot Blot analysis was performed using phosphate-buffered saline extracts from the stalks, leaves, and cones of three hop cultivars, while Western Blotting followed SDS-PAGE protein separation. The results revealed significant immunoreactivity in native hop proteins, with diminished reactivity observed in denatured proteins. Cross-reactivity between hop proteins and major pollen allergens was confirmed, indicating that hop proteins may contribute to allergic sensitization in pollen-sensitive individuals. These findings underscore the potential allergenic risks associated with the consumption or exposure to hop-containing products.

Survival of the probiotic strain Lacticaseibacillus paracasei subsp. paracasei F19 in high-hopped beers

This study aims to enhance understanding of probiotic lactic acid bacteria (LAB) survival in high-hopped beer formulations and their interactions with different yeasts and highlights the fermentation processes, microbial metabolism, and production of distinctive beer flavors. For this, this research used Lacticaseibacillus paracasei F19 (F19), Saccharomycodes ludwigii, and Saccharomyces cerevisiae strains US-05 (US-05) and Kveik (Kveik) for brewing. Bacterial and yeast cultures were prepared, fermented in wort, and analyzed in different hop concentrations (International Bitterness Units − IBU 0, 20, 40). Methods included physicochemical analysis, yeast and bacterial counts, RT-qPCR for gene expression, statistical analysis, and sensory evaluation by sommeliers following BJCP guidelines. Physicochemical analysis showed efficient fermentation across all hop concentrations (IBU 0, 20, 40), with decreasing SG and pH over time due to lactic acid bacteria and yeast metabolism. Higher hop levels (IBU 20 and 40) resulted in less acidic beer, indicating hop interference with bacterial activity. Yeast populations remained stable regardless of hop content, with Saccharomyces cerevisiae and Saccharomycodes ludwigii performing well. Probiotic strain F19 exhibited robust viability in all formulations. Sensory analysis favored higher hop content beers, suggesting consumer acceptance and potential health benefits of probiotic, high-hop beers. Higher hop content hindered sour beer production as only hop-free beers reached low pH levels. Probiotic strain F19 remained viable under high IBU formulations (20 and 40), with these being preferred by sommeliers using BJCP methodology. All yeast strains supported F19 survival. Further studies are needed on gastrointestinal resistance and clinical benefits.

A Preliminary Study on the Effect of Adding Sugarcane Syrup on the Flavor of Barley Lager Fermentation.

This study focuses on the diversified utilization of the sugarcane industry, and sugarcane syrup, as a by-product of the sugarcane industry, is a good raw material for fermentation. Bringing sugarcane syrup into beer is conducive to the enrichment of the sugar industry, and it can improve the flavor of beer and make it more aromatic. This study determined the optimal fermentation process for beer. By analyzing the consumption rate of the carbon and nitrogen sources of raw materials, the nutrient utilization of yeast, and the causes of differences in flavor substances, the flavor composition and flavor stability of beer were determined by SPME-HS-GC-MS technology. The results showed that beer brewed with sugarcane syrup as an auxiliary raw material met the basic specifications of beer. The addition of sugarcane syrup to the wort base increased the utilization of amino acids by the yeast, and LS (lager with added cane syrup) increased the nine flavor compounds of the beer, which constituted the basic flavor of the beer, bringing new flavor compounds compared with the normal all-barley beer. Forced aging experiments showed that LS produced fewer aging compounds than OWBL. Various experiments have shown that it is feasible to ferment beer with sugarcane syrup instead of partial wort.

Differences in structure, stability and antioxidant activity of melanoidins from lager and ale beers

Beer melanoidins, the final products of the Maillard reaction (MR), play a critical role in determining the flavor stability of beer due to their antioxidant properties. This study investigated the structure, stability, and antioxidant activity of lager beer melanoidins (LBM) and ale beer melanoidins (ABM). The results revealed that ABM possessed a higher browning index and molecular weight, attribute to its relatively intense MR. However, this intensity also led to a more unfolded and disordered structure in ABM. Conversely, LBM outperformed ABM in the FAST index, thermal stability, and total antioxidant activity because the low alcohol content in lager beer reduced oxidation and thermal degradation while boosting the stability and antioxidant activity of melanoidins. As a result, it would offer a novel possibility to improve beer flavor stability by optimizing the brewing process to modify the structural and functional characteristics of melanoidins.

Advances and Challenges in Analytical Strategies for Fruity Thiol Profiling in Beer: From Sensitivity Optimization to Ecologically Responsible Methodologies

The fruity thiols in beer, such as 3SH, 3SHA, 4MMP, and 3S4MP, constitute significant components of its volatile profile, playing a pivotal role in shaping the overall flavor alongside hydrocarbons and oxygen-containing compounds. This paper, drawing extensively on relevant literature, presents a comprehensive summary of the composition, aroma contribution, challenges in thiol detection, and advancements in analytical methods and technologies for these compounds. It outlines the limitations and attempted improvements of direct measurement approaches, the innovations and evolution of derivatization methods, and the integration of various specific sample preparation techniques (e.g., SPE, SPME, LLE, and derivatization) with modern, advanced detection equipment, accompanied by an evaluation of the precision and inclusivity of these methods. Concluding the discussion, the article offers a perspective on the future refinement of thiol determination in the brewing industry. This review aims to serve the objective of more precise beer flavor modulation.

Examination of internal metabolome and VOCs profile of brewery yeast and their mutants producing beer with improved aroma

Volatile organic compounds (VOCs) are metabolites pivotal in determining the aroma of various products. A well-known VOC producer of industrial importance is Saccharomyces cerevisiae, partially responsible for flavor of beers and wines. We identified VOCs in beers produced by yeast strains characterized by improved aroma obtained in UV-induced mutagenesis. We observed significant increase in concentration of compounds in strains: 1214uv16 (2-phenylethyl acetate, 2- phenylethanol), 1214uv31 (2-ethyl henxan-1-ol), 1214uv33 (ethyl decanoate, caryophyllene). We observed decrease in production of 2-phenyethyl acetate in strain 1214uv33. Analysis of intracellular metabolites based on 1H NMR revealed that intracellular phenylalanine concentration was not changed in strains producing more phenylalanine related VOCs (1214uv16 and 1214uv33), so regulation of this pathway seems to be more sophisticated than is currently assumed. Metabolome analysis surprisingly showed the presence of 3-hydroxyisobutyrate, a product of valine degradation, which is considered to be absent in S. cerevisiae. Our results show that our knowledge of yeast metabolism including VOC production has gaps regarding synthesis pathways for individual metabolites and regulation mechanisms. Detailed analysis of 1214uv16 and 1214uv33 may enhance our knowledge of the regulatory mechanisms of VOC synthesis in yeast, and analysis of strain 1214uv31 may reveal the pathway of 2-ethyl henxan-1-ol biosynthesis.

Effect of Hanseniaspora vineae and Saccharomyces cerevisiae co-fermentations on aroma compound production in beer

In recent years, the boom of the craft beer industry refocused the biotech interest from ethanol production to diversification of beer aroma profiles. This study analyses the fermentative phenotype of a collection of non-conventional yeasts and examines their role in creating new flavours, particularly through co-fermentation with industrial Saccharomyces cerevisiae. High-throughput solid and liquid media fitness screening compared the ability of eight Saccharomyces and four non-Saccharomyces yeast strains to grow in wort. We determined the volatile profile of these yeast strains and found that Hanseniaspora vineae displayed a particularly high production of the desirable aroma compounds ethyl acetate and 2-phenethyl acetate. Given that H. vineae on its own can't ferment maltose and maltotriose, we carried out mixed wort co-fermentations with a S. cerevisiae brewing strain at different ratios. The two yeast strains were able to co-exist throughout the experiment, regardless of their initial inoculum, and the increase in the production of the esters observed in the H. vineae monoculture was maintained, alongside with a high ethanol production. Moreover, different inoculum ratios yielded different aroma profiles: the 50/50 S. cerevisiae/H. vineae ratio produced a more balanced profile, while the 10/90 ratio generated stronger floral aromas. Our findings show the potential of using different yeasts and different inoculum combinations to tailor the final aroma, thus offering new possibilities for a broader range of beer flavours and styles.

Field-isolated brewing yeast produces wheat beer flavor without wheat ingredients

This study explored the potential of 120 wild yeasts obtained from eight different fruits, with particular emphasis on Saccharomyces cerevisiae S-1. This strain demonstrated remarkable attributes, notably its superior alcohol tolerance when compared to the conventional yeast, US-05. Significantly, the S-1 yeast unveiled its ability to produce three distinct aroma compounds—isoamyl acetate, β-phenylethyl acetate, and ethyl decanoate— not typically found in beer brewed with US-05 stain. These compounds are essential for enriching the sensory experience of beer drinkers. Further investigation revealed that the diminsihed expression of Leu2 in US-05 hindered metabolite synthesis, resulting in the absence of these aroma compounds. In contrast, S-1 exhibited approximately three times higher Leu2 expression, which may explain the observed differences in aroma compounds production. This sheds light on the potential mechanism behind the disparity in aroma profiles between the two strains. Overall, the study highlighted S-1's capacity to enhance beer flavor and aroma. It suggested that wild yeast strains, such as S-1 yeast isolated from grapes, present innovative opportunities for the brewing industry. The hightened Leu2 expression and synthesis of unique aroma compounds in S-1 yeast underscore the latent capabilities of wild yeast strains in elevating beer characteristics.

Machine learning boosts beer flavor

Machine learning boosts beer flavor

Predicting and improving complex beer flavor through machine learning

The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models that allow predicting flavor and consumer appreciation. For each beer, we measure over 200 chemical properties, perform quantitative descriptive sensory analysis with a trained tasting panel and map data from over 180,000 consumer reviews to train 10 different machine learning models. The best-performing algorithm, Gradient Boosting, yields models that significantly outperform predictions based on conventional statistics and accurately predict complex food features and consumer appreciation from chemical profiles. Model dissection allows identifying specific and unexpected compounds as drivers of beer flavor and appreciation. Adding these compounds results in variants of commercial alcoholic and non-alcoholic beers with improved consumer appreciation. Together, our study reveals how big data and machine learning uncover complex links between food chemistry, flavor and consumer perception, and lays the foundation to develop novel, tailored foods with superior flavors.

Modelling of beer sensory staleness based on flavour instability parameters

Why was the work done: The deterioration of the flavour of fresh beer is challenging for the brewing industry. Despite extensive research on flavour instability, the focus has centred on a limited set of parameters, rather than taking a broader approach.
 How was the work done: in this study, the intent was to produce a flavour stable beer. Using a low kilning temperature, malt of low staling potential was used in combination with best brewing practice to produce three batches of unpasteurised top fermented pale beers at a pilot scale. Forty-three markers were analysed in the fresh and aged beers (30°C for 15, 30, 60 and 90 days). Staleness was evaluated by a trained sensory panel and multivariate data analysis was used to explore how the markers contribute to staleness.
 What are the main findings: Repeatability was achieved between replicate brews and, subsequently, staling. Polyphenols, haze, total reactive antioxidant potential (TRAP), iso-α-acids, colour, furfural, 2-methylpropanal and 2-methylbutanal showed a strong correlation with staleness. Staleness doubled after 60 days of storage at 30°C, despite volatile aldehydes remaining below their sensory thresholds, implying a synergistic effect of carbonyls contributing to staleness. A Partial Least Square (PLS) model was established, modelling the sensory staleness from 2-methylpropanal, furfural, TRAP and the trans-/cis-iso-α-acids ratio.
 Why is the work important: The staling phenomena could be reproduced in beers from parallel brewing trials with only minor variations. The four parameters in PLS modelling indicate that beer staling involves a combination of oxidative and non-oxidative pathways.

Barley variety interacts positively with floor malting to produce different malts and beers

Why was the work done: Floor malting maintains a small but notable market share due to its reputed contributions to beer flavour. These malts are viewed as premium products and are produced in both historic and contemporary floor maltings. Despite this, little work has been performed on floor malting to evaluate its effect on malt and subsequent beer quality and flavour. Accordingly, this work investigated whether floor malting produces distinct malts and beers relative to pneumatic maltings. How was the work done: A mini-floor malting protocol was developed to malt small quantities of grain in a repeatable system that produces malt comparable to the production scale. Two winter barley varieties (Lontra and Thunder) were used to understand whether there was a malting type by variety interaction effect on beer flavour. What are the main findings: Both floor and pneumatic malts produced similar malts and beers based on quality metrics and the differences found between malts were more attributable to variety and the respective rate of proteolysis. Sensory results showed that there was a significant malting type by variety interaction driving hedonic and descriptive sensory results. Why is the work important: These results suggest that while the different malting types produce analytically similar malt, selection of barley variety can be used to optimise the floor malting process to produce distinct beer flavour profiles.

An integrative multi-omics approach aimed to gain insight on the effect of composition, style, yeast, and wheat species on wheat craft beer flavour

This study was aimed to unravel the effect of raw materials (barley and wheat), wheat concentration (0, 25, 40, and 100 %), wheat species (common and durum), beer style (Blanche and Weiss), and yeast (US-05 and WB-06) on the chemical composition, volatiles, and sensory profile of wheat craft beers by using a multivariate statistical approach. Beer samples were analysed for their composition, volatiles and sensory profile and data were processed using unsupervised multivariate analyses, PLS regression and a multi-omics approach using multi-block PLS-DA. Multi-block variable sparsification was used as an embedded dimension reduction step. The adopted multi-omics approach permitted to correctly classify beers with different styles and wheat concentration, and to accurate classify (95 % accuracy) beers according to yeast type. Wheat species was of lower importance since it permitted a classification with 49 % accuracy which increased to 74 % in Blanche beers, thus suggesting that malting flattened differences determined by wheat species.

Effect of cherry products addition on beer fermentation

Fruits has been used in brewing as a source of sugars, colour and flavour. Cherry (Prunus avium L.) products such as juice and pomace can be used in brewing in order to increase beer biological value. In this study, cherry juice and pomace in concentration of 15 % were added at first and seventh day of beer fermentation. The effect of cherry products addition was investigated by measuring the content of yeast metabolites (ethanol, aldehydes, higher alcohols, esters, and vicinal diketones) in cherry beers and control sample without cherries. The alcohol content in all the cherry beers was higher than the control sample. The cherry juice addition at the beginning of fermentation led to the formation of more secondary metabolites than the control. Cherry juice addition at the seventh day of fermentation resulted in a decrease in higher alcohols and esters concentration, but in an increase in carbonyls concentration compared to the control. Cherry pomace addition led to a significant increase in esters and vicinal diketones concentration. Aldehydes concentration was not affected by cherry pomace addition. Higher alcohols were influenced only by pomace addition at the seventh day of fermentation. Sensory evaluation was also made because yeast metabolites affected beer flavour and aroma.

Frontiers of machine learning in smart food safety.

Integration of machine learning (ML) technologies into the realm of smart food safety represents a rapidly evolving field with significant potential to transform the management and assurance of food quality and safety. This chapter will discuss the capabilities of ML across different segments of the food supply chain, encompassing pre-harvest agricultural activities to post-harvest processes and delivery to the consumers. Three specific examples of applying cutting-edge ML to advance food science are detailed in this chapter, including its use to improve beer flavor, using natural language processing to predict food safety incidents, and leveraging social media to detect foodborne disease outbreaks. Despite advances in both theory and practice, application of ML to smart food safety still suffers from issues such as data availability, model reliability, and transparency. Solving these problems can help realize the full potential of ML in food safety. Development of ML in smart food safety is also driven by social and industry impacts. The improvement and implementation of legal policies brings both opportunities and challenges. The future of smart food safety lies in the strategic implementation of ML technologies, navigating social and industry impacts, and adapting to regulatory changes in the AI era.

Advances in Extraction Techniques for Beer Flavor Compounds

Owing to the unique chemical properties exhibited by beer flavor compounds, different extraction methods have been utilized to extract these compounds from the sample matrix. Carbonyl compounds, which significantly contribute to flavor instability in beer, pose challenges in detection due to their low concentrations and reactivity. Consequently, the analysis of beer flavor compounds has focused on improving sensitivity and specificity through techniques that minimize sample preparation requirements and reduce interactions between factors involved in the analysis. Notably, extraction techniques such as headspace solid-phase microextraction (HS-SPME), stir bar sorptive extraction (SBSE), and gas diffusion microextraction (GDME) have been successfully applied to the analysis of carbonyl compounds in alcoholic beverages, including beer. Derivatization agents like 2,4-dinitrophenylhydrazine (DNPH) and O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine (PFBHA) enhance the volatility and stability of analytes, facilitating their separation and detection in gas chromatography and high-performance liquid chromatography. Chromatographic separation methods, particularly gas chromatography and liquid chromatography, are extensively employed to identify and quantify aroma/flavor compounds in various foodstuffs, including beer. This review provides a comprehensive overview of extraction techniques and chromatographic methods used in the analysis of beer compounds.

Manipulation of isocitrate dehydrogenase genes affects the anti-autolytic ability of lager yeast

Yeast autolysis affects the flavor and quality of beer. The regulation of yeast autolysis is a need for industrial beer production. Previous studies on brewer's yeast autolysis showed that the citric acid cycle-related genes had a great influence on yeast autolysis. To explore the contribution of isocitrate dehydrogenase genes in autolysis, the IDP1 and IDP2 genes were destroyed or overexpressed in typical lager yeast Pilsner. The destruction of IDP1 gene improved the anti-autolytic ability of yeast, and the anti-autolytic index after 96 h autolysis was 8.40, 1.5 times higher than that of the original strain. The destruction of IDP1 gene increased the supply of nicotinamide adenine dinucleotide phosphate (NADPH) and the NADPH/NADP+ ratio was 1.94. After fermentation, intracellular ATP level was 1.8 times higher than that of the original strain, while reactive oxygen species (ROS) was reduced by 10%. The destruction of IDP2 gene resulted in rapid autolysis and a decrease in the supply of NADPH. Anti-autolytic index after 96 h autolysis was 4.03 and the NADPH/NADP+ ratio was 0.89. After fermentation, intracellular ATP level was reduced by 8% compared with original strain, ROS was 1.3 times higher than that of the original strain. The results may help understand the regulation mechanism of citric acid cycle-related genes on yeast autolysis and provide a basis for the selection of excellent yeast with controllable anti-autolytic performance.

Hop bitterness in beer evaluated by computational analysis

Beer flavour and aroma are greatly influenced by the hop(s) employed in the brewing process. The iso-α-acids post wort boiling are the major compounds responsible for bitterness, which are detected by the bitter taste receptors (TAS2Rs) in oral taste buds. This family of receptors is activated in the presence of bitter molecules, which send chemical signals to the brain, making it possible to differentiate whether the detected molecules have a pleasant taste (or not). It is of interest to predict the behaviour of hop compounds towards bitter receptors such that the bitterness of different hop varieties can be predicted based on quantitative analysis of composition. Computational simulation, based in high-performance computing (HPC), allow the simulation of interactions of molecules with the various TAS2Rs, enabling the prediction the bitterness of these hop compounds. These techniques, will soon enable the design of beverages with customised flavours, greatly reducing the need for experimental evaluation. In this work, α and β-acids, iso-α-acids, and prenylflavonoids are analysed against the bitter receptors TAS2R10, TAS2R14 and TAS2R46. Using computational blind docking and molecular dynamics, xanthohumol was identified to have the highest bitter profile.

Study on the technology of kumquat grapefruit sour beer

A kumquat-grapefruit acid beer was brewed with Australian barley malt, lactobacillu, D17 yeast, Qingdao hop flower, kumquat concentrated juice and grapefruit concentrated juice as raw materials by using special mash and fermentation process. The effects of acidification degree, the addition amount of kumquat and grapefruit juice concentrate and the addition time on beer flavor were studied in this paper. The results showed that when the pH was adjusted to 3.5 by acidification, the sour beer produced by adding 6% kumquat concentrated juice and 4% grapefruit concentrated juice before the CO2 pressure of the tank rised, the beer has white and exquisite foam with prominent fruit aroma, especially those of kumquat and grapefruit. The beer body was clear and transparent, with about 5% residual sugar. The sweet and sour taste of the beer was balanced. The beer contained unique nutrients of kumquat and grapefruit also, and was especially suitable to drink for brewers and ladies.

Enhancement of dimethyl sulphide separation during wort boiling by a single spinning cone evaporator

Wort boiling is the most energy intensive stage in the brewing process. Novel wort boiling systems have been explored to reduce primary energy consumption and improve wort quality and beer flavor stability. Low thermal stress boiling is proposed for wort boiling, but the content of dimethyl sulphide (DMS) in the wort may exceed the required product threshold. A single spinning cone evaporator (SCE) is proposed to enhance the separation of DMS and minimise the energy consumption for wortboiling. The performance of a SCE was evaluated by measurement of fluid flow, ratio of DMS removal, wort self-evaporation ratio based on sensible heat, and thermal efficiency. The results show that use of a spinning cone evaporator, reduced DMS by up to 90% with 2.1% wort self evaporation ratio with less primary heat consumption. The SCE operation exceeds the evaporation of a gravity film cone. Under reduced pressure, the spinning cone evaporator was less effective in DMS removal.