DEVELOPING COLLOIDAL STRUCTURE OF BEER BY GRAIN ORGANIC COMPOUNDS
Abstract and keywords
Abstract (English):
The present article introduces the problem of determining the general structure of beer as a complex system of related biomolecules. The objective was to establish the correlation of various quantities of organic compounds in beer formulation. The research featured samples of filtered pasteurized beer obtained from a retail chain shop in Moscow (Russia). The experiment relied on standard research methods, including instrumental methods of analysis, e.g., high-performance liquid chromatography (HPLC). The obtained experimental data underwent a statistical analysis using the Statistica software (StatSoft, 2016). The research established the correlation between the type of grain (barley or wheat malt) and the content of organic compounds, e.g., β-glucan, polyphenols, soluble nitrogen, etc. The research also revealed some patterns in the distribution of proteins, which served as a framework for the system of organic compounds. The distribution of thiol proteins proved to depend on the dissolution degree of the grain and was different in barley light, barley dark, and wheat malt samples. The fraction distribution of β-glucan depended on the color of the malt. In light beer samples, it concentrated in high- and medium-molecular fractions of nitrogenous substances, in dark beer – in low-molecular fractions (≤ 63%). Initial wort density and alcohol content affected the amount of catechins and total polyphenols. Nitrogenous compounds depended on the color, initial extract, and alcohol content. The nitrogenous structure and other organic compounds of beer proved to depend on protein substances. The research also revealed a number of factors that affected the fraction distribution of biomolecules in different beer sorts.

Keywords:
Beer, nitrogenous compounds, polyphenols, β-glucan, fractioning, structure
Text
Publication text (PDF): Read Download

INTRODUCTION
Alcoholic beverages have a colloidal structure that
depends on primary plant raw materials or secondary
organic compounds. Secondary organic compounds
are a product of the microbial activity. They appear as
a result of various biochemical or chemical processes
presupposed by the particular production technology.
The combination of primary and secondary organic
compounds affects the sensory profile of the beverage
and, consequently, its demand on the food market.
Similarly, beer is an alcoholic drink with a complex
colloidal structure formed by organic biomolecules of
various molecular weights, which are interconnected
by hydrogen, covalent, disulfide, and other bonds [1, 2].
Nitrogenous compounds, phenols, and carbohydrate
biomolecules shape both the sensory profile of beer and
its stability as a fermented drink (Fig. 1) [2]. However,
flavor profile development is a versatile process. It
depends both on the primary biomolecules that get
hydrolyzed during wort production and on the secondary
biomolecules that appear as a result of biomodification
in the Krebs cycle during fermentation [3].
Depending on the size and fraction, some organic
compounds develop both the sensory profile and
consumer characteristics of beer, while others are
responsible for haze.
319
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
Foam stability and settling time are important
consumer characteristics that are associated with
the quality of beer [4]. Foam quality depends on
protein fractions, bitter hop resins, pentosans, gum
substances, and other fractions of plant materials that
produce carbon dioxide bubbles on beer surface [5].
Protein biomolecules play the key role in foam
development during brewing. Some proteins possess
foaming properties, while others are responsible for
stabilizing [6]. The composition of beer foam is strongly
associated with lipid carrier proteins (LTP1). Their
molecular weight is 9.7 kDa, and they include 91 amino
acids. Other foam-related proteins are protein Z (40 kDa)
and various derivatives of hordein (10–30 kDa) [7].
Beer foam has a complex composition, which
consists not only of protein fractions but also of ligand
compounds. Ligands are formed by bitter isoforms
of α-bitter acids found in hop. The carboxyl group of
the asparagine residue in the LTP1 protein molecule
is linked by covalent bonds with the hydroxy group of
resin, flavonoids, phytosterols, etc. [8]. Foam stability
always correlates with the degree of malt dissolution and
sometimes with another protein Z fraction [9].
Protein Z is part of the fraction of hordein proteins.
Good solubility of malt stimulates the release of this
protein into the liquid fraction and causes haze [10, 11].
Similarly, the intensity of haze depends on the content of
fractions with a molecular weight of 8–14 kDa in barley
malt and < 7 kDa in wheat malt [12].
The last 40 years of beer studies have established
a partial similarity in the composition of the protein
fractions of the foam and the body of beer. It includes
three groups of protein molecules of 40, 10, and 8 kDa
(proteins and peptides), which are similar to barley
nitrogenous compounds [13].
Non-starch polysaccharides also affect the taste of
beer [14]. For instance, maltodextrins and β-glucan can
enhance flavor profile. The molecular weight of β-glucan
in barley is 150–1937 kDa, in malt – 800–1220 kDa, and
in beer – 10–10 000 kDa [15]. The content of β-glucan in
the initial barley affects that of malt, and the content of
β-glucan in malt affects that in wort. The correlation is
different for different types of barley. For instance, the
correlation coefficient was 0.9717 for barley malt and
0.9998 for barley wort colloids [15].
Phenolics are other important compounds of beer.
Catechins, non-condensed phenolic compounds, and
monophenolic acids have a positive effect on the flavor
profile of beer, while proanthocyanidins spoil both
its taste and stability [16]. In fact, proanthocyanidins
possess an extraordinary reactivity and condense
into large globules, dragging along proteins and other
biomolecules [2].
Thus, the effect of grain organic compounds on the
finished product is diverse and quantitatively unclear.
For instance, the issue of the interrelation between grain
biomolecules and other plant materials still remains
understudied in the brewing industry. The research
objective was to establish the correlation between
the biomolecules of beer plant raw materials to cast
light upon the general structure of beer as a colloidal
system. The research will make it possible to update the
methodology for quality control in the brewing industry.
Non-starch polysaccharides (β-glucan)
Polyphenols
Hop compounds (prenylchalcones,
iso- α-acids)
Nitrogenous compounds (LTP 1-,
Z-proteins, hordein fraction of malt)
Aroma
Non-starch di-, tri-, and mono polysaccharides
Starch carbohydrates (dextrins)
Hop compounds (sesquiterpenes, ester oils)
Amino acids
Polyphenols (catechins, rutins, quercetins and their homologues,
phenols, phenolic acids, and aldehydes)
Foam formation
Palate fullness
Nitrogenous compounds (LTP 1-, Z-proteins, hordein fraction of malt)
Non-starch polysaccharides (β-glucan, dextrins of arabinoxylans)
Mineral substances in raw materials and water
Figure 1 Colloidal structure of beer
320
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
STUDY OBJECTS AND METHODS
Beer samples. Samples of filtered pasteurized beer
were purchased from a retail network in Moscow and
stored in the dark at temperature 15 ± 20°C and air
humidity W ≤ 75 ± 2%. The list included light beers
(45 samples), dark beers (10 samples), wheat beers
(10 samples), and non-alcoholic beers (5 samples), five
bottles or cans per each sort.
Fractioning the organic compounds of beer. To
preserve the spatial structure of the protein fractions
of biomolecules, the protein fractioning was carried
out by two methods. High-molecular proteins and
related organic compounds were precipitated with a 2%
tannin aqueous solution. High-molecular and mediummolecular
nitrogenous compounds were precipitated
using a 50% sodium molybdate (Na2MoO4) solution
in an acid medium. The fractions of nitrogenous
compounds, polyphenols, and β-glucans in the filtrate
were determined as described below.
An aliquot (62 cm3) of decarbonated beer was taken
into two volumetric flasks of 100 cm3. Into the first flask,
we added 35 cm3 of distilled water, followed by 2 cm3
of concentrated sulfuric acid, which made it possible
to establish the acidic pH of the medium. The solution
was stirred, mixed with a 2% tannin aqueous solution,
and filtered. Into the other flask, we added 30 cm3 of
distilled water, followed by 5 cm3 o f 5 0% Na2
MoO4
solution. The mix was brought to the mark with distilled
water, followed by another 5 cm3 of concentrated
sulfuric acid. The resulting phosphomolybdic acid in the
medium made it possible to precipitate protein nitrogen
from beer. The initial samples of beer, post-tannin
fraction, and post-molybdate fraction were tested for
the mass concentrations of soluble nitrogen, nitrogenous
compounds with unoxidized disulfide bonds, β-glucan,
catechins, and polyphenolic compounds.
The content of organic compounds in the high
molecular weight fraction was calculated as the
difference between the total amount of a particular
compound and its content in the post-tannin extract. The
low molecular weight fraction was determined in the
postmolybdate filtrate. The average molecular fraction
was calculated as the difference between the total
amount of the substance and the sum of the high and low
molecular weight fractions.
Determining the nitrogenous compounds.
The Kjeldahl method for determining total soluble
nitrogen was used according to the European Brewery
Convention method No. 4.9.3 [17].
Determining the total content of polyphenols.
The mass concentration of polyphenols was measured
according to the European Brewery Convention method
No. 9.9 [18].
Determining the mass concentration of catechins.
The content of catechins was determined by highperformance
liquid chromatography (HPLC). The
procedure involved an Agilent Technologies 1200
device (Agilent, USA) with a diode array detector and
a Hypersil 5u C18 250×4.6 mm 5 μm column (Thermo,
USA) with a wavelength of 280 nm. According to
the procedure, 0.001 cm3 of samples and all standard
solutions were injected into a reverse phase column
at 30°C. The mobile phase for HPLC was prepared
as follows. Solution A included 0.1 mL of phosphoric
acid dissolved in 900 cm3 of HPLC water. The volume
was brought up to 1000 cm3 with water. The solution
was filtered through a 0.45-μm membrane filter and
degassed in an ultrasonicator for 3 min. Solution B was
acetonitrile. The mobile phase used gradient elution: at
0.01 min – 11% B; 30 min – 25% B; 35–39 min – 100% B;
40–50 min – 11% B. The flow rate of the mobile
phase was 1.0 cm3/min, and the injection volume was
0.001 cm3 [19].
Determining the mass concentration of
nitrogenous compounds with disulfide groups. The
Ellman method detected nitrogenous compounds that
contained unoxidized sulfhydryl (thiol) groups [20].
The procedure was based on the reaction of thiol
with dithiobisnitrobenzoic acid, which formed a
mixed disulfide and 2-nitro-5-thiobenzoic acid. They
were quantified by anion absorption at 412 nm in a
spectrophotometer. A number of reagents made it
possible to determine the concentration of thiol groups.
The list included 0.1 and 0.2M phosphate buffer
and Ellman’s reagent that consisted of 37 mg of
dithiobisnitrobenzoic acid dissolved in 10 cm3 of 0.1M
phosphorus buffer with pH = 7.0 and 15 mg of NaHCO3.
The experiment was prepared as follows. First, 3 cm3 of
the protein solution was poured into a test tube, followed
by 2 cm3 of a 0.2M phosphate buffer solution and 5 cm3
of distilled water. The aliquot (3 cm3) was poured into
another tube, followed by 0.02 cm3 of Elman’s reagent.
After 3 min, the optical density was measured at 412 nm
against the control solution. The control solution was
prepared similarly, but 0.02 cm3 of distilled water was
added to 3 cm3 in another test tube at the last stage.
The mass concentration of thiol-containing nitrogenous
compounds (mol/dm3) was calculated by the
following formula:
Сs-s = D·P/11,400 (1)
where D is the optical density at 412 nm; Р is the
dillution.
Determining the mass concentration of β-glucan.
The mass concentration of β-glucan was determined by
the enzymatic European Brewery Convention method
No. 8.13.1 [21].
Statistical analysis. All experiments were
performed in five repetitions. The obtained values
were presented as mean ± standard deviation (SD). The
Student’s t-test was applied to test the homogeneity of
the samples. The multivariate models in the correlationregression
analysis were checked using the Fisher test
(P ≤ 0.95). The data were processed using Statistica
software (StatSoft, Redmond, WA, USA, 2006).
321
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
RESULTS AND DISCUSSION
Relationship between the beer quality and
the quantity of organic compounds in grain. The
first stage of the research was aimed at finding the
quantitative characteristics of the main organic
compounds that shape the colloidal structure of beer.
The list included nitrogenous compounds, polyphenols,
and a non-starch carbohydrate β-glucan. Together with
divalent metal ions, hop resins, and melanoidins, these
compounds are responsible for both haze and beer
quality [22]. The dual behavior of biomolecules can
be explained by their grain origin: they originate in
malted or unmalted grain and pass into the liquid phase
during processing. Table 1 illustrates the quantitative
characteristics of the main organic compounds.
Non-alcoholic and light beer had a similar content of
solids in the initial wort (Table 1). As a result, they both
were poor in β-glucan, polyphenols, and soluble nitrogen.
Apparently, this fact can be explained by the technology
of removing alcohol from beer by thermal or membrane
methods.
Thermal de-alcoholization processes include vacuum
evaporation, vacuum distillation, and centrifugation.
They have a negative effect on the sensory profile of
beer, which loses in aroma and palate fullness while
acquiring new unwanted aromas [23]. Adsorption
extraction is another de-alcoholization method. It
involves adsorbents, e.g., zeolites. Their surface has
charged sites that have an affinity for polar organic
substances, which means they can adsorb them. Zeolites
often have an affinity for Ca2+ and Mg2+ ions [24].
Molecules of nitrogenous substances, polyphenols, and
β-glucan can be connected to other biomolecules via
Ca2+ and Mg2+ bridges [25]. Nanofiltration can decrease
both the level of alcohol and some polyphenolic
compounds [23].
Thus, differences between the de-alcoholization
methods can reduce the mass concentration of these
compounds. This fact can explain the decrease in the
level of non-starch polysaccharides, polyphenols, and
soluble nitrogen in non-alcoholic beer, compared to light
varieties.
In light beer, β-glucan, polyphenols, and soluble
nitrogen are proportional to the increase in the solids of
the initial wort (Table 1).
In dark beer, the content of β-glucan was 30%,
and the content of soluble nitrogen was two times
higher. This effect might have been caused by colored
malt, which has higher dissolving properties during
germination [26]. Colored malt is also responsible for
the lower total amount of polyphenols because they
contain lower amounts of such polyphenols as catechin,
prodelphinidin B3, procyanidin B3, and ferulic acid [27].
Wheat beer with 12–15% of solids in the initial malt
had twice as much β-glucan as light barley beer. The
amount of polyphenols in these samples was higher
by 30% and that of soluble nitrogen (lower limit) – by
33% (Table 1). In [28], wheat beer also contained a
greater amount of non-starch polysaccharides with a
structure-dependent difference and a higher degree of
polymerization, compared to light barley beer. Barley
malt has a β-glucan polymerization of 38–48, while
wheat malt has a polymerization of 38–83 [28]. In
wheat beers with 16÷20% solids, the content of nonstarch
polysaccharide was 1.5 times higher (upper
limit), polyphenols – 1.3–1.6 times higher, protein – by
5.0÷32% higher than in the samples of barley-malt beer,
which was probably caused by wheat malt [29].
Distribution of biomolecules of grain raw
materials by nitrogenous fractions. The content of
soluble nitrogen in beer samples was more significant.
Thus, the structure of beer was studied depending
on the ratio of different groups of biomolecules with
protein substances. The beer samples were tested
for nitrogen with thiol groups and catechins. Table 2
shows the averaged data, while Fig. 2 demonstrates the
quantitative distribution of biomolecules by fractions of
nitrogenous compounds.
The catechin content confirmed the data obtained by
Maia et al. [30]. No correlations between thiol groups
Table 1 Quantitative profile of beer compounds
Beer Solids in
initial wort, %
Content* of organic substances, mg/dm3
β-glucan Polyphenols Soluble nitrogen
From To From To From To
Non-alcoholic,
barley-malt, light
7÷8 69.8 ± 4.9 93.0 ± 6.5 32.8 ± 3.0 65.6 ± 5.9 440.0 ± 6.6 864.0 ± 13.0
Light, barley-malt 10÷11 31.0 ± 2.2 93.0 ± 6.5 70.4 ± 6.3 217.0 ± 19.5 560.0 ± 8.4 920.0 ± 13.8
11÷15 45.0 ± 3.2 125.0 ± 8.8 85.5 ± 7.7 225.0 ± 20.2 580.0 ± 8.7 880.0 ± 13.2
15÷23 78.0 ± 5.5 180.0 ± 12.6 100.0 ± 9.0 305.0 ± 27.5 850.0 ± 12.8 1350.0 ± 20.3
Dark, barley-malt 10÷11 76.5 ± 5.4 125.0 ± 8.8 102.0 ± 9.2 172.0 ± 15.5 1200.0 ± 18.0 1780.0 ± 26.7
15÷23 120.0 ± 8.4 180.0 ± 12.6 110.0 ± 9.9 180.0 ± 16.2 1200.0 ± 18.0 1800.0 ± 27.0
Light, wheat-malt 12÷15 95.0 ± 6.7 240.0 ± 16.8 110.0 ± 10.0 290.0 ± 26.0 770.0 ± 11.6 890.0 ± 13.4
16÷20 125.0 ± 8.8 280.0 ± 19.6 145.0 ± 13.0 290.0 ± 26.0 1150.0 ± 17.3 1380.0 ± 20.7
* Each value is the mean ± standard deviation of five independent experiments
322
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
were detected. However, dark beer had more catechins
because the malt had better dissolution and antioxidant
activities. As a result, catechins did not oxidize until the
final stage of beer production [30].
Table 2 shows a high level of nitrogen with thiol
groups in dark and light barley-malt beers with a lot of
initial wort solids. This fact was probably associated
with the antioxidant capacity of these samples, which
retained thiol groups in unoxidized form.
Light wheat beers contained a relatively low amount
of nitrogen with thiol groups (8.80–11.4 μm) compared
to barley-malt light beers (12.7–16.4 μm), as confirmed
by other studies [31].
The fraction distribution of organic compounds
(Fig. 2a–h) depended on the type of beer.
The high-molecular fraction of soluble nitrogen
ranged from 7 to 15% of the total amount. Its minimal
amount was in dense light barley-malt beers, where
the solids content in the initial wort was 15÷23%. The
maximal amount was in light barley-malt beer with the
solids content of 11÷15%.
The average molecular fraction correlated with
the density. The biggest amount of soluble nitrogen
(8÷40 kDa) was registered in the beer samples with
initial wort solids content ≥ 23%: it was 20–34% of the
total amount of protein compounds. The low molecular
fraction of soluble nitrogen was inversely related to the
density of beer. For all samples, the higher the content
of dry matter in the initial wort, the lower the content of
protein compounds with a molecular weight of ≤ 8 kDa.
The distribution of thiol groups of nitrogenous
substances was as follows. In light barley-malt beers, the
maximal amount was in the medium molecular weight
fraction (8÷40 kDa). In dark barley-malt beers, it was
in the low molecular weight fraction (≤ 8 kDa). In light
wheat-malt beer, it was in the high molecular weight
fraction (40÷100 kDa).
The β-glucan dextrins differed in distribution. In
light barley-malt beer, 58–68% of the total content of
non-starch polysaccharide fractions accounted for the
protein fraction with a molecular weight of 8÷40 kDa.
In dark barley-malt beer, 59–63% of β-glucan molecules
were concentrated in the fraction of nitrogenous
substances of ≤ 8 kDa, and 73–79% of its total
content was distributed in nitrogenous substances of
40÷100 kDa.
Catechins did not depend on the type and
composition of beer: 45–74% of the total content
accumulated in the high molecular weight fraction
of soluble nitrogen. However, the total content of
polyphenols showed strong correlation with the type of
beer.
Table 3 shows the correlation between the total
polyphenol content and the catechin content.
Table 3 revealed a strong correlation between the
total polyphenols and catechins and the type of beer.
According to the determination coefficient, the total
polyphenols depended on the content of catechins when
the latter was 50 99%. Therefore, some unknown factors
affected the total polyphenols in different beer samples.
The lowest determination coefficient was registered
in light barley-malt beers 15÷23%, dark beers 15÷23%,
and wheat-malt beers 16÷20%. When the solids in the
initial wort was high, the composition of polyphenolic
compounds experienced a stronger impact from
anthocyanogens, phenolic acids, aldehydes, hop resins,
and prenylflavanoids. Apparently, strong beer requires a
greater proportion of hops, which, like grain, is a source
of polyphenolic compounds [32]. On the other hand,
the stability of phenolic compounds depends on many
factors, e.g., temperature, pH, coactivating substances,
polar solvents, etc., which makes the amount of alcohol a
more significant factor for strong beer sorts [33].
Table 4 illustrates the dependence of the distribution
of thiol groups and catechins.
Table 4 shows that the change in β-glucan was 50%,
while the content of thiol groups and catechins changed
by 80%, which depended on the parameters of the plant
material, i.e., barley or wheat malt. On the one hand, this
fact can be traced back to grain varieties. On the other
hand, non-starch polysaccharides can develop colloidal
suspensions and links with other beer compounds,
which leads to product losses and affects the content of
β-glucan [15, 34].
Table 2 Thiol nitrogen-containing compounds and catechins in beer samples
Beer type Solids in initial wort, % Content in beer
Protein with thiol groups, μmoL/dm3 Catechins, mg/dm3
Non-alcoholic barley malt 7÷8 5.61 ± 0.56 2.25 ± 0.23
Light, barley malt 10÷11 12.7 ± 1.26 6.33 ± 0.65
11÷15 16.4 ± 1.55 8.14 ± 0.80
15÷23 36.7 ± 3.60 14.4 ± 1.40
Dark barley malt 10÷11 28.0 ± 2.80 14.9 ± 1.50
15÷23 35.5 ± 3.50 18.0 ± 1.80
Light, wheat malt 12÷15 11.4 ± 1.00 1.98 ± 0.20
16÷20 8.80 ± 0.90 6.90 ± 0.70
Each value is the mean ± standard deviation of five independent experiments
323
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
Figure 2 Distribution of compounds by fractions of soluble nitrogen: (a) non-alcoholic barley-malt beer; (b) light barley-malt beer
with 11÷12% initial wort solids; (c) light barley-malt beer with 12÷15% initial wort solids; (d) light barley-malt beer with 15÷ 23%
initial wort solids; (e) dark barley-malt beer with 10÷11% initial wort solids; (f) dark barley-malt beer with 15÷23% initial wort
solids; (g) light wheat-malt beer with 12÷15% initial wort solids; (h) light wheat-malt beer with 16 ÷ 20% initial wort solids
Figures 3 and 4 illustrate the analysis of correlations
and regressions, which registered the presence and
degree of the relationship between the content of soluble
nitrogen and other parameters. The analysis established
a close and logical relationship between the amount of
raw materials (solids in the initial wort) and the content
of alcohol and polyphenols, which was confirmed by
previous studies [32, 33]. Fermentation and the content
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa 80 100
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
a b
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
20 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
c d
0 20 40 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
%
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100 120
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
e f
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
0 20 40 60 80 100
soluble nitrogen
thiol groups
β-glucan
polyphenols
catechins
Content, %
40÷100 kDa 8÷40 kDa ˂ 8 kDa
g h
324
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
Table 3 Analysis of correlation and regression between components and beer parameters
Beer type Solids in initial
wort, %
Correlation
coefficient (r)
Equation of dependance Correlation according to
Chaddock scale
Determination
coefficient
Non-alcoholic
barley malt
7÷8 0.744 y = 48.2 – 2.56 x Direct, high 0.553
Light, barley malt 10÷11 0.713 y = 77.4 + 6.22 x Direct, high 0.508
11÷15 0.975 y = 54.9 + 12.2 x Direct, high 0.952
15÷23 0.517 y = 81.9 + 15.3 x Direct, moderate 0.267
Dark barley malt 10÷11 0.999 y = –133 + 19.4 x Functional 0.999
15÷23 0.556 y = 294.7 – 8.9 x Direct, moderate 0.310
Light, wheat malt 12÷15 0.959 y = 19.8 + 38.7 x Direct, high 0.919
16÷20 0.557 y = 225.5 – 2.1 x Direct, moderate 0.310
Significance level ≤ 0.05
x – type of beer; y – total polyphenols and catechins
Table 4 Analysis of correlation and regression between beer parameters and raw material
Component
Correlation
coefficient (r)
Equation of dependance Correlation according to
Chaddock scale
Determination coefficient
Thiol-containing Proteins 0.920 y = –9.8 + 1.9 x Direct, high 0.846
Catechins 0.896 y = –4.0 + 0.8 x Direct, high 0.803
β-glucan 0.708 y = 19.5 + 9.8 x Direct, high 0.501
*Significance level ≤ 0.05
x – solids in initial wort; y – component amoun
of polyphenols in the finished product also proved
closely interconnected. This fact has been described in
different publications [32].
The content of soluble nitrogen proved to depend
on the color (type) of beer. This result was quite
predictable since a greater degree of dissolution of
colored malt means a greater effect of low molecular
weight nitrogenous compounds on colored compounds.
Similar conclusions were obtained by Castro et al. and
Filipowska et al. [26, 35]. Partial correlation coefficients
(Fig. 4) were based on the changes in the pair correlation
of the corresponding features (Y and Xi), provided they
experienced no effect from other factors (Xj). This
aspect demonstrated much deeper dependencies of
the analyzed indicators. The change in the content of
soluble nitrogen was confirmed by the conclusion about
the correlation with the color (type) of beer, as well as
correlation coefficients YX3, YX5, and X5. The experiment
confirmed the hypothesis about the relationship of
nitrogenous fractions of nitrogenous substances with
polyphenolic and non-starch compounds. X2, X4,
and Y also appeared to correlate, which means that
polyphenolic compounds affected soluble nitrogen
fraction. Polyphenols transformed when the parameters
of young beer changed during fermentation while pH
became more acidic, oxygen dissolved, carbon dioxide
accumulated, etc.
The calculations represented in Figs. 3 and 4 resulted
in the following multiple regression equation (2):
Y = 117.2991 – 33.1413 · X1 + 15.1575 · X2 +
+ 34.8177 · X3 + 2.6063 · X4 + 7.7755 · X5 (2)
Color or type of beer (X3) was the most significant
parameter in the regression equation. This result
confirmed our previous conclusion that the fraction
distribution of biomolecules depended on the type
of beer (Fig. 2). The overall coefficient of multiple
correlation R equaled 0.9073, while the multiple
determination coefficient R2 equaled 0.82. The
difference indicates that the change in the content
of soluble nitrogen depended the abovementioned
parameters by 82%.
The study of the protein fractionation could be
used to determine the accompanying groups of organic
molecules. The acidic extraction regime of biomolecules
was quite sparing. Different conditions, e.g., alkaline pH,
organic polar solvents, etc., disrupt the equilibrium
of nitrogenous substances, polyphenols, and other
compounds. As they oxidize, their amount in equilibrium
systems cannot be determined [36, 37].
The behavior of organic compounds in the colloidal
system of beer revealed a strong correlation between the
technological conditions and the low amount of β-glucan,
polyphenols, and soluble nitrogen. In particular,
thermal or adsorption de-alcoholization had a great
impact on the abovementioned substances, which
is consistent with data obtained Muller et al. and
Yassue-Cordeiro et al. [23, 24].
325
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
Figure 3 Correlation coefficients of beer parameters
Figure 4 Pair correlation coefficients of beer parameters
The distribution of biomolecules by types of beer
also revealed an obvious connection between the
type of beer and the biochemical composition of the
raw materials (barley or wheat malt), production
technology, and the amount of mashed grain
(Table 1). These results are consistent with other
publications [26–30].
The quantitative assessment of organic compounds
and their biochemical properties resulted in the
hypothesis about the structural character of nitrogenous
substances in the colloidal system of beer. This
experiment also made it possible to trace the changes
in polyphenols, carbohydrates, and other compounds
relative to the fraction distribution of nitrogenous
compounds [38].
The results of nitrogenous fractionation (Fig. 2)
showed its obvious correlation with the beer type. The
high molecular weight fraction of soluble nitrogen
(40÷100 kDa) varied in the range of 7÷15%, depending
on the solids in the initial wort. The higher was the
solids content, the lower was the amount of the high
molecular weight fraction of nitrogenous compounds.
High-molecular fractions of nitrogenous substances
are associated with the palate fullness, which is most
Soluble nitrogen
content, mg/L
(Y)
Raw materials
content, %
(X1)
Alcohol
content, %
(X2)
Beer type
(color, EBC)
(X3)
Polyphenols
content, mg/L
(X4)
β-glucan
content, mg/L
(X5)
Y 1 0.33** 0.35 0.74 0.49 0.57
X1 – 1 0.956*** 0.02* 0.79 0.42
X2 – – 1 0.13 0.864 0.30
X3 – – – 1 0.42 0.10
X4 – – – – 1 0.12
X5 – – – – – 1
* – weak bond strength; ** – moderate connection; *** – strong bond
YX1 YX2 YX3 YX4 YX5
Y – – – – –
X1 – 0.156* 0.777*** 0.395 0.501
X2 –0.0502 – 0.748 0.381 0.518
X3 0.462 0.383 – 0.287 0.740
X4 –0.112 –0.148 0.677** – 0.587
X5 0.117 0.239 0.836 0.512 –
X1X2 X1X3 X1X4 X1X5 X2X3
Y 0.952 –0.348 0.769 0.302 –0.204
X1 – – – – 0.395
X2 – –0.376 –0.229 0.500 –
X3 0.963 – 0.865 0.420 –
X4 0.885 –0.566 – 0.540 –0.500
X5 0.961 –0.0229 0.825 – 0.111
X2X4 X2X5 X3X4 X3X5 X4X5
Y 0.847 0.121 0.102 –0.583 –0.218
X1 0.594 –0.410 0.663 0.098 –0.390
X2 – – 0.609 0.0612 –0.282
X3 0.898 0.285 – – 0.085
X4 – 0.384 – 0.053 –
X5 0.874 – 0.413 – –
* – weak bond strength; ** – moderate connection; *** – strong bond
Soluble nitrogen
content, mg/L
(Y)
Raw materials
content, %
(X1)
Alcohol
content, %
(X2)
Beer type
(color, EBC)
(X3)
Polyphenols
content, mg/L
(X4)
β-glucan
content, mg/L
(X5)
Y 1 0.33** 0.35 0.74 0.49 0.57
X1 – 1 0.956*** 0.02* 0.79 0.42
X2 – – 1 0.13 0.864 0.30
X3 – – – 1 0.42 0.10
X4 – – – – 1 0.12
X5 – – – – – 1
* – weak bond strength; ** – moderate connection; *** – strong bond
Soluble nitrogen
content, mg/L
(Y)
Raw materials
content, %
(X1)
Alcohol
content, %
(X2)
Beer type
(color, EBC)
(X3)
Polyphenols
content, mg/L
(X4)
β-glucan
content, mg/L
(X5)
Y 1 0.33** 0.35 0.74 0.49 0.57
X1 – 1 0.956*** 0.02* 0.79 0.42
X2 – – 1 0.13 0.864 0.30
X3 – – – 1 0.42 0.10
X4 – – – – 1 0.12
X5 – – – – – 1
* – weak bond strength; ** – moderate connection; *** – strong bond
326
Gribkova I. N. Foods and Raw Materials. 2022;10(2):318–328
typical for light beers with low density [14, 39]. In the
samples where the content of extractive substances
of the initial wort was 15÷23%, the palate fullness
depended not only on the raw materials but also on the
secondary products of yeast metabolism, i.e., secondary
alcohols, aldehydes, ketones, ethers, and other carbonyl
compounds. Our results were quite similar. The medium
molecular fraction (8÷40kDa), which is responsible for
foam structure, correlated with the density of beer or the
proportion of grain products in it, which is consistent
with some previously obtained data [40]. In all samples,
the low molecular weight fraction of soluble nitrogen
(≤ 8 kDa) developed inversely to the density of beer,
which is consistent with other studies on sensory
perception of beer body [14, 39]. In other words, the
low molecular weight fraction of protein compounds
depended on the yeast metabolism, i.e., the enzyme
systems of the strain.
Thiol groups of nitrogenous substances are
responsible for foam and palate fullness. Their
distribution proved to depend on the grain raw material –
barley or wheat malt. Thus, light barley-malt beer
contained the maximum of thiol groups in the medium
molecular weight fraction, dark barley-malt beer – in
the low molecular weight fraction, and wheat-malt beer –
in the high molecular weight fraction. This finding
indicates a great effect of the type of grain on beer
quality.
The fraction distribution of non-starch β-glucan
depended on the type of malt. In light beers, this
non-starch polyaccharide was mostly represented in
high- and medium-molecular fractions of nitrogenous
substances (Fig. 2). In dark beers, up to 63% of β-glucan
molecules concentrated in low molecular weight
fractions of nitrogenous compounds, which means
they linked to peptides through hydrogen bonds [12].
Probably, this fact can be explained by the competitive
distribution of catechins and their bonding with
nitrogenous biomolecules in high and medium molecular
weight fractions of dark beer (Fig. 2).
The correlation analysis revealed a close and logical
relationship between catechins and total polyphenols
(Table 3) in different types of beer. The amount of
polyphenols depended on the density of the initial wort,
as well as on the increase in the alcohol content, which
stabilized polyphenolic compounds [33].
The analysis of correlation and regression
(Figs. 3 and 4) showed the strong impact of the raw
material factor (light, dark barley, and wheat malt) on
the content of alcohol and polyphenols. This finding was
consistent with the previously obtained research results
(Tables 1 and 2) [32, 33].
The statistical analysis revealed a correlation
between the color (type) of beer and the amount
of nitrogenous compounds in terms of colloidal
structure (Fig. 3). This correlation is associated with
the technology of coloring malts and the degree of
dissolution of malt endosperm during the hydrolysis that
occurs during barley germination [33].
Therefore, the experimental part of the research
confirmed the hypothesis that fractionation of nitrogenous
compounds can be conducted by the method
specified in Study Objects and Methods. Fractions
of soluble nitrogen and polyphenolic compounds
demonstrated a close correlation under various beer
production technologies. This relation can be illustrated
by a multiple correlation equation (2), in which the color
(type) of beer is the most significant parameter.
CONCLUSION
The present research featured the fractionation of
organic compounds in various beers. It established the
dependences and factors affecting the distribution of
nitrogenous compounds in the colloidal system of beer,
as well as the relationship between polyphenolic and
non-starch biomolecules. The study also revealed the
relationship between the fractional composition of beer
and such parameters as contents of solids in the initial
wort, raw materials, alcohol, color, etc.
CONTRIBUTION
I.N. Gribkova designed the research, collected,
analyzed, and interpreted the data. M.N. Eliseev
designed the article, developed the concept, and
interpreted the data. M.A. Zakharov and V.A. Zakharova
collected and analyzed the data. O.A. Kosareva edited
and proofread the manuscript.
CONFLICT OF INTERESTS
The authors declare that there is no conflict of
interests regarding the publication of this article.

References

1. Humia BV, Santos KS, Barbosa AM, Sawata M, Mendonça MC, Padilha FF. Beer molecules and its sensory and biological properties: A review. Molecules. 2019;24(8). https://doi.org/10.3390/molecules24081568

2. Wannenmacher J, Gastl M, Becker T. Phenolic substances in beer: Structural diversity, reactive potential and relevance for brewing process and beer quality. Comprehensive Reviews in Food Science and Food Safety. 2018;17(4):953-988. https://doi.org/10.1111/1541-4337.12352

3. Pandin C, Darsonval M, Mayeur C, Le Coq D, Aymerich S, Briandet R. Biofilm formation and synthesis of antimicrobial compounds by the biocontrol agent Bacillus velezensis QST713 in an Agaricus bisporus compost micromodel. Applied and Environmental Microbiology. 2019;85(12). https://doi.org/10.1128/AEM.00327-19

4. Lukinac J, Mastanjevic K, Mastanjevic K, Nakov G, Jukic M. Computer vision method in beer quality evaluation - a review. Beverages. 2019;5(2). https://doi.org/10.3390/beverages5020038

5. Kemp B, Condé B, Jégou S, Howell K, Vasserot Y, Marchal R. Chemical compounds and mechanisms involved in the formation and stabilization of foam in sparkling wines. Critical Reviews in Food Science and Nutrition. 2018;59(13):2072-2094. https://doi.org/10.1080/10408398.2018.1437535

6. Gonzalez Viejo C, Fuentes S, Torrico D, Howell K, Dunshea FR. Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms. Journal of the Science of Food and Agriculture. 2018;98(2):618-627. https://doi.org/10.1002/jsfa.8506

7. Nyarko EK, Glavaš H, Habschied K, Mastanjević K. Determination of foam stability in lager beers using digital image analysis of images obtained using RGB and 3D cameras. Fermentation. 2021;7(2). https://doi.org/10.3390/fermentation7020046

8. Moraes AH, Asam C, Almeida FCL, Wallner M, Ferreira F, Valente AP. Structural basis for cross-reactivity and conformation fluctuation of the major beech pollen allergen Fag s 1. Scientific Reports. 2018;8(1). https://doi.org/10.1038/s41598-018-28358-1

9. Kerr ED, Caboche CH, Schulz BL. Posttranslational modifications drive protein stability to control the dynamic beer brewing proteome. Molecular and Cellular Proteomics. 2019;18(9):1721-1731. https://doi.org/10.1074/mcp.RA119.001526

10. Liger-Belair G, Cilindre C. How many CO2 bubbles in a glass of beer. ACS Omega. 2021;6(14):9672-9679. https://doi.org/10.1021/acsomega.1c00256

11. Wang Y, Ye L. Haze in beer: Its formation and alleviating strategies, from a protein-polyphenol complex angle. Foods. 2021;10(12). https://doi.org/10.3390/foods10123114

12. Zheng Y, Du J, Li M. Haze-active protein and turbidity in commercial barley and wheat beers at different storage temperatures. International Food Research Journal. 2020;27(2):295-307.

13. Goldman AR, Beer LA, Tang H-Y, Hembach P, Zayas-Bazan D, Speicher DW. Proteome analysis using gel-LC-MS/MS. Current Protocols in Protein Science. 2019;96(1). https://doi.org/10.1002/cpps.93

14. Krebs G, Müller M, Becker T, Gastl M. Characterization of the macromolecular and sensory profile of non-alcoholic beers produced with various methods. Food Research International. 2019;116:508-517. https://doi.org/10.1016/j.foodres.2018.08.067

15. Loskutov IG, Polonsky VI. Content of β-glucans in oat grain as a perspective direction of breeding for health products and fodder. Agricultural Biology. 2017;52(4):646-657. (In Russ.). https://doi.org/10.15389/agrobiology.2017.4.646eng

16. Habschied K, Lalic A, Horvat D, Mastanjevic K, Lukinac J, Jukic M, et al. β-glucan degradation during malting of different purpose barley varieties. Fermentation. 2020;6(1). https://doi.org/10.3390/fermentation6010021

17. Goiris K, Jaskula-Goiris B, Syryn E, Van Opstaele F, De Rouck G, Aerts G, et al. The flavoring potential of hop polyphenols in beer. Journal of the American Society of Brewing Chemists. 2014;72(2):135-142. https://doi.org/10.1094/ASBCJ-2014-0327-01

18. Ofoedu CE, Akosim CQ, Iwouno JO, Obi CD, Shorstkii I, Okpala CO. Characteristic changes in malt, wort, and beer produced from different Nigerian rice varieties as influenced by varying malting conditions. PeerJ. 2021;9. https://doi.org/10.7717/peerj.10968

19. Dvorakova M, Hulin P, Karabin M, Dostálek P. Determination of polyphenols in beer by an effective method based on solid-phase extraction and high performance liquid chromatography with diode-array detection. Czech Journal of Food Sciences. 2007;25(4):182-188. https://doi.org/10.17221/690-CJFS

20. Gottumukkala RVSS, Nadimpalli N, Sukala K, Subbaraju GV. Determination of catechin and epicatechin content in chocolates by high-performance liquid chromatography. International Scholarly Research Notices. 2014;2014. https://doi.org/10.1155/2014/628196

21. Wu M, Cao Y, Lei S, Liu Y, Wang J, Hu J, et al. Protein structure and sulfhydryl group changes affected by protein gel properties: process of thermal-induced gel formation of myofibrillar protein. International Journal of Food Properties. 2019;22(1):1834-1847. https://doi.org/10.1080/10942912.2019.1656231

22. Huismann M, Gormley F, Dzait D, Speers RA, Maskell DL. Unfilterable beer haze Part I: The investigation of an India pale ale haze. Journal of the American Society of Brewing Chemists. 2021;80(1):17-25. https://doi.org/10.1080/03610470.2021.1937460

23. Muller C, Neves LE, Gomez L, Guimaraes M, Ghesti G. Processes for alcohol-free beer production: A review. Food Science and Technology. 2020;40(2):273-281. https://doi.org/10.1590/fst.32318

24. Yassue-Cordeiro PH, Zandonai CH, Genesi BP, Lopes PS, Sanchez-Lopez E, Garcia ML, et al. Development of chitosan/silver sulfadiazine/zeolite composite films for wound dressing. Pharmaceutics. 2019;11(10). https://doi.org/10.3390/pharmaceutics11100535

25. Zambrzycka-Szelewa E, Nalewajko-Sieliwoniuk E, Zaremba M, Bajguz A, Godlewska-Żyłkiewicz B. The mineral profile of Polish beers by fast sequential multielement HR CS FAAS analysis and its correlation with total phenolic content and antioxidant activity by chemometric methods. Molecules. 2020;25(15). https://doi.org/10.3390/molecules25153402

26. Castro LF, Affonso AD, Lehman RM. Impact of specialty malts on wort and beer characteristics. Fermentation. 2021;7(3). https://doi.org/10.3390/fermentation7030137

27. Carvalho DO, Curto AF, Guido LF. Determination of phenolic content in different barley varieties and corresponding malts by liquid chromatography-diode array detection-electrospray ionization tandem mass spectrometry. Antioxidants. 2015;4(3):563-576. https://doi.org/10.3390/antiox4030563

28. Li M, Du J, Zheng Y. Non-starch polysaccharides in wheat beers and barley malt beers: A comparative study. Foods. 2020;9(2). https://doi.org/10.3390/foods9020131

29. Krstanović V, Habschied K, Mastanjević K. Research of malting procedures for winter hard wheat varieties - Part I. Foods. 2021;10(1). https://doi.org/10.3390/foods10010052

30. Maia C, Cunha S, Debyser W, Cook D. Impacts of adjunct incorporation on flavor stability metrics at early stages of beer production. Journal of the American Society of Brewing Chemists. 2021. https://doi.org/10.1080/03610470.2021.1993054

31. Jastrzębska A, Kowalska S, Szłyk E. Determination of free tryptophan in beer samples by capillary isotachophoretic method. Food Analytical Methods. 2020;13(4):850-862. https://doi.org/10.1007/s12161-020-01699-2

32. Boronat A, Soldevila-Domenech N, Rodríguez-Morató J, Martínez-Huélamo M, Lamuela-Raventós RM, de la Torre R. Beer phenolic composition of simple phenols, prenylated flavonoids and alkylresorcinols. Molecules. 2020;25(11). https://doi.org/10.3390/molecules25112582

33. Arczewska M, Kamiński DM, Gieroba B, Gagoś M. Acid-base properties of xanthohumol: A computational and experimental investigation. Journal of Natural Products. 2017;80(12):3194-3202. https://doi.org/10.1021/acs.jnatprod.7b00530

34. Pater A, Zdaniewicz M, Cioch-Skoneczny M, Duliński R. Different methods of mash pH adjustment and its influence on the quality of wort and brewing process performance. Post Techn Przetw Spoż. 2019;1:47-51.

35. Filipowska W, Jaskula-Goiris B, Ditrych M, Bustillo Trueba P, De Rouck G, Aerts G, et al. On the contribution of malt quality and the malting process to the formation of beer staling aldehydes: a review. Journal of the Institute of Brewing. 2021;127(2):107-126. https://doi.org/10.1002/jib.644

36. Honda S, Ishida R, Hidaka K, Masuda T. Stability of polyphenols under alkaline conditions and the formation of a xanthine oxidase inhibitor from gallic acid in a solution at pH 7.4. Food Science and Technology Research. 2019;25(1):123-129. https://doi.org/10.3136/fstr.25.123

37. Munir S, Javed M, Hu Y, Liu Y, Xiong Sh. The effect of acidic and alkaline pH on the physico-mechanical properties of surimi-based edible films incorporated with green tea extract. Polymers. 2020;12(10):1-15. https://doi.org/10.3390/polym12102281

38. Feige MJ, Braakman I, Hendershot LM. Disulfide bonds in protein folding and stability. In: Feige MJ, editor. Oxidative folding of proteins: Basic principles, cellular regulation and engineering. Royal Society of Chemistry; 2018. pp. 1-33. https://doi.org/10.1039/9781788013253-00001

39. Gastl M, Kupetz M, Becker T. Determination of cytolytic malt modification - Part II: Impact on wort separation. Journal of the American Society of Brewing Chemists. 2020;79(1):66-74. https://doi.org/10.1080/03610470.2020.1796155

40. Krebs G, Gastl M, Becker T. Chemometric modeling of palate fullness in lager beers. Food Chemistry. 2021;342. https://doi.org/10.1016/j.foodchem.2020.128253


Login or Create
* Forgot password?