DOI: https://doi.org/10.52091/EVIK-2022/2-1-ENG

Received: January 2022 - Accepted: March 2022

¹ Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences
² Pécsi Brewery
³ Department of Dietetics and Nutritional Sciences, Semmelweis University, Faculty of Health Sciences

Keywords

taste perception, single nucleotide polymorphism, electric impedance, Body Mass Index, food preferences

2. Introduction

Humans perceive their environment and its relation to them through their sense organs and senses. Five major senses are distinguished: sight, hearing, touch, olfaction, and gustation. There are further channels of sensations also known, e.g. balance, hunger, thirst, pain or discomfort [1]. Perception of taste and flavours are related to the oral and nasal area, including the sense of smell and the trigeminal sensation through the chemosensory system. It belongs to the chemical senses, and it focuses on the perception of the chemicals in our environment. Taste receptors detect the chemicals in the consumed food, which are generally called tastants. These are usually water-soluble molecules, which provide information on the quality and safety of food [2].

Taste perception is a direct contact process, which takes place in the oral cavity. The receptors can be found on the surface of the tongue, in the pharynx, on the palate and in the upper part of the oesophagus. Receptors are organized in the taste buds, which are located in the taste papillae. The sensory information is transferred through the VII; IX. and X. cranial nerves, then the brainstem’s and the thalamus’ nuclei and finally arrives to the frontal operculum and the gustatory cortex of the insula. These areas and the nuclei of tractus solitarius in the brainstem are linked with the hypothalamus and the amygdala, thus probably influencing hunger and satiety, homeostatic reactions to eating and any emotions linked to eating [2, 3].

Bitter taste often triggers a rejection, which is an innate human reaction. On one hand, this aversive reaction is due to the fact, that many bitter tasting compounds (secondary plant metabolites, e.g. alkaloids, some inorganic and synthetic compounds, and in case of food the rancid fat) are toxic, thus consuming them might be harmful, or life-threatening [4].

On the other hand, several bitter tasting compounds are known, which have beneficial effect from the pharmacological or nutritional point of view. These compounds are for example the glucosinolates and their decomposition products, the isocyanates, which are found in cabbage, broccoli or brussels sprouts (all belong to the Brassicaceae family). Coffee, tea, and cocoa contains methylated xanthine derivatives, like caffeine, theophylline, and theobromine; in beers we find the alpha-acids, which originate from the hop and are mainly responsible for the bitter taste. In case of the vegetable species, the bitter taste note might trigger rejection, in the case of the latter products; bitterness is an expected part of their sensory character [5, 6, 7].

In the field of taste perception, five basic tastes are distinguished: sweet, salty, sour, bitter and umami. This last one was accepted as a basic taste following the discovery of its specialized taste receptor in 2002 [8]. Among the five basic quality, the detection of bitter taste is the most complex; the TAS2R gene family, which consists of 25 functional genes, performs its regulation. These genes are coding the TAS2Rs receptors, which structurally bind to given bitter taste compounds (ligands), however in case of several receptors, their ligands is not identified yet [7].

Phenylthiocarbamide (PTC, also known as 1-phenylthiourea) and the 6-n-propylthiouracil (PROP) are colourless or white, crystalline, bitter tasting organic compounds: both have sulphur containing (SCN) functional group. Their use is different: phenylthiocarbamide is used as an industrial additive, colorant, while the propylthiouracil is applied as an antithyroid agent in case of hyperthyroidism [9, 10]. The structure of PTC and PROP shown in the figure 1.

Peculiarity of these two compounds, that they trigger a bimodal reaction in humans: a part of the population is able to perceive their bitter taste, while others not. Its discovery is linked to the chemist Arthur Fox. In 1931, Fox working in a laboratory of the DuPont chemical company accidentally released some fine crystalline PTC to the atmosphere of the room. A colleague working nearby complained on perceiving bitter taste. Fox did not perceive any bitter taste, despite the fact that he directly contacted the fine dust. After this occasion, he tested his family and friends, and categorized the individuals as ‘taster’ or ‘non-taster’. Laurence Hasbrouck Synder geneticist, who identified that the inheritance of the non-taster status is a recessive phenomenon according to the Mendelian genetics [11], strengthened his results.

In the 1960’s the issue of changing of PTC to PROP has risen, because of the strong, sulphuric odour of PTC. In the 1980’s toxicological information also questioned the use of PTC, so researchers started to work with PROP after the comparison of the two compounds and measuring the threshold concentration of PROP [12].

Bartoshuk and co-workers discovered in 1991, that the non-taster group gives relatively homogenous responses, while the reaction of tasters were much more different, and one of their subgroups perceived the bitter taste of PROP much more intensively. Individuals, belonging to that subgroup were called supertasters. The supertaster status is not influenced by the genotype responsible for the taster status, but this discovery resulted in a third type of classification label, medium taster [13].

Taster status is defined by some variations of the genetic domain; in this case the single nucleotid polymorphisms (SNP). SNP’s are DNA sequence variations that affect one nucleotide, which are identified between the genetic domains of two individuals belonging to the same species. Each human genome has a unique SNP pattern, but these changes might be called SNP, if they show up at least in 1% of the total population. SNP’s are usually the results of errors during the DNA replication, or caused by DNA damage. They might be located in genes (both in coding and in non-coding sections), and between genes (intergenetically), thus might cause change in structure or in functions [14].

A database (dbSNP) is collecting these SNP’s, was created in 1999 by the American National Centre for Biotechnology Information and the National Human Genome Research Institute. The number of discovered SNP’s was dramatically increased by the Human Genome Project, which mapped the whole humane genome in 2003, thus resulting a total number of more than 650 million SNP’s in the database up to date (ncbi.nlm.nih.gov/sn/) [15].

In case of PTC or PROP sensitivity the SNP’s of TAS2R28 gene (responsible for bitter taste perception) define, whether the individual perceives bitter taste or not. This gene codes a heptahelical (including seven transmembrane domain), G-protein coupled bitter taste perceiving receptor, which binds to the N-C=S group of the compounds. In this case, the gene contains 1002 nucleotides, from which 3 are functionally missense-coding SNP’s, which cause a non-synonym changes, thus modifying the structure of the coded protein.

The amino acid sequence of this protein is shown in Table 1.

The two most frequent haplotype are the PAV and AVI. Individuals having dominant PAV/PAV, or PAV/AVI diplotype are usually belong to the taster group, while the recessive AVI/AVI diplotypes are non-tasters. With a much lower occurrence (1-5%), AAI, PAI, PVI and AAV haplotypes also occur in some ethnics and populations. In case of PVI and AAV the two status is usually balanced. Based on the studies it might can be concluded that the occurrence of the taster status varies between 55% and 85%, depending on the investigated population [16, 17, 18].

In Hungary, György Forray paediatrician and György Bánkövi mathematician performed a survey on children aged 7-15, in Budapest in 1967. During their study, they applied the Harris-Kalmus method with PTC solutions in order to measure the taste threshold of the children, and thus they concluded their taster status. According to their results 67.8% of the children belonged to the taster group, but they did not find a significant correlation between gender and taster status. They have published their research in the journal Orvosi Hetilap [19].

From the anatomic point of view the polymorphysm has a relationship with the number of taste buds: tasters have more fungiform papillae and more taste pores [12].

The study of PTC and PROP sensitivity’s effect on other factors have started in the 1960’s. The psycho-pharmacologist researcher Roland Fischer (born in Hungary) was the first, who assumed that there might be a relationship between taste perception and food preference [20]. Even until now several researchers study the relationship between taster status (and its haplo- and diplotypes) and body mass index [17, 21], food preference and frequencies of different food consumption (e.g. alcoholic drinks [22, 23], vegetables, especially the Brassicales [24, 25], coffee, tea [26], sweeteners [27]), and some diseases (e.g. Parkinson- disease, gastrointestinal tumours, chronic rhinosinusitis) and their symptoms [28, 29, 30].

3. Scope

The scope of the current research is to investigate correlations between taster status, body composition and the consumption frequency of bitter tasting foods. To achieve that we have performed PTC status survey, bioimpedance-based body composition measurement and used a food frequency questionnaire focused on bitter tasting foods.

4. Methods

Data collection took place in February and March of 2019, participants were volunteers from the Food Science Faculty of Szent István University, and Faculty of Health Sciences, Semmelweis University (students and staff), altogether 170 people. In the taster status survey 170 people participated, in the body composition study we had 96 participants, the food frequency questionnaire (FFQ) was filled out by 170 individuals. All data were recorded anonymously. To link the different type of data, all participants received an individual code. Participants were informed on the data handling according to the general GDPR guidelines (Regulation (EU) 2016/679).

Taster status was defined with PTC-impregnated paper strips (Precision Europe, Northampton, United Kingdom). PTC is present at 20 micrograms per strip. Individuals were assigned to the taster or non-taster category based on their responses after tasting the paper strips.

The body composition was measured with an InBody 770 (InBody USA, Cerritos, California) device, which works based on bioelectric impedance analysis (BIA). This method relies on the different levels of conductivity of the human body’s tissues. The measurement is simple and non-invasive, which provides accurate data for several anthropometric parameters, e.g. percentage of body fat, and its distribution [31]. From the recorded data set we have used the body mass index (BMI, kg/m2), the body fat percentage (PBF, %) and the visceral fat area (VFA, cm2) for further analysis [32, 33, 34]. The FFQ questionnaire involves a list of specific foods or food types, and respondents have to indicate the consumption frequency of these items [35]. Our questionnaire was assembled including bitter tasting food types, consumption frequencies were measured with category scales. The final forms were implemented through the Google Forms platform, data recording was performed online. From the recorded data in this study we report the values concerning coffee and tea consumption, not only the frequency indices, but its type and flavorings also. In order to provide transparent data, the FFQ categories were merged into three major categories (see Table 2).

5. Statistical analyses

To analyse the recorded datasheet, we applied descriptive statistical methods (mean, standard deviation, percentages). Afterwards, data were transformed into category variables, thus suitable for contingency table analysis, multiple correspondence analysis (MCA) and Mann-Whitney test at 5% significance level [36]. XLStat 2020.1.3. and Microsoft® Office Excel® 2016 softwares were used for data analysis.

6. Results

6.1. Demographic parameters

55 males and 115 females participated in this study, so the ratio of genders are 32.5% male and 67.65% female. The youngest respondent was 19 years old, while the eldest was 40 years old, the average age was 23.85±3.05 years. Based on their residence 44.70% lived in the capital of Hungary (Budapest), 55.30% lived in other locations. In the latter group 24.46% lived in Pest County (relating it to the total data that was 13.53%). There were only two Hungarian counties (Zala and Csongrád-Csanád) which were not indicated in any of the respondents.

6.1.1. Taster status

The distribution of taster status data (Table 3.) showed that 72.94% of the respondents were tasters, while 27.06% were non-tasters. The ratio of non-tasters among males was 23.63%, while in case of females it was 28.69%. Based on the results of the contingency table analysis there is no significant relationship between the gender and the taster status (χ²(1, n=170)=0.483, p=0.48).

6.1.1.1. Results of investigation of body composition analysis and its relation to the taster status

Body composition analysis was performed in case of 23 males and 73 females, altogether on 96 individuals. The averaged data of these values are listed in Table 4.

BMI data showed that among the males 11 individuals were obese (BMI from 25.0 to 29.9) and three individuals were overweight (BMI > 30.0). The percentage of body fat values showed obesity in case of 6 people (PBF > 27%), while the visceral fat are was higher than the upper limit of 100 cm2 value in the case of 5 people.

Among the females the BMI showed undernourishment for 5 individuals (BMI < 18.5), 7 were obese, and 3 were overweight. The percentage of body fat data showed that 18 people was obese, and the visceral fat area was higher than 100 cm2 for 15 participants.

Based on the statistical evaluations we did not find significant relationships in case of any of the obesity-indicating parameters and the taster status (BMI: χ²(3, n=96)=0.42, p=0.93; PBF: χ²(1, n=96)=0.45, p=0.50; VFA: χ²(1, n=96)=0.01, p=0.90). The multiple correspondence analysis results on Figure 2 shows that the obesity indicating parameters have relationships with each other. The patterns show that non-tasters are positioned closer to the categories of normal body composition and body weight. Outcomes of the contingency table analysis showed that on the basis of BMI values the ratio of overweight individuals (compared to the normal weighted ones) were significantly higher among males, than among females (χ²(3, n=96)=21.52, p<0.0001).

6.1.1.2. Relationship of coffee consumption and taster status

Among the FFQ respondents, 27 individuals do not consume coffee, so their data was removed from the analysis. Flavouring categories were the following: ‘with milk’ (referring to the use of milk, dairy products, or milk substitutes) and ‘with sweetener’ (referring to the use of any sweeteners (sugar, natural or artificial sweeteners). The ‘mixed’ coffee variety indicated the consumption of both Arabica and Robusta (individually or as a blend). From the 143 consumers 24 individuals drink their coffee black (without sweetener, milk, or milk substitute).

Based on the contingency table analysis there is no significant relationship among taster status and coffee consumption (χ²(1, n=170)=0.02, p=0.88), consumption frequency (χ²(1, n=143)=2,57, p=0,10) and the consumed type of coffee (χ²(3, n=143)=4.21, p=0.24). Similarly there was no significant relationship between the type of consumption, like black (χ²(1, n=143)=0.60, p=0.43), with milk (χ²(1, n=143)=0.28, p=0.59) or sweetened (χ²(1, n=143)=0.17, p=0.67) and the taster status.

The patterns of multiple correspondence analysis (Figure 3) shows that non-tasters consume coffee less frequently than the tasters, and they are unable to specify the type of coffee they consume. When the non-tasters consume coffee, they prefer the sweetened way. Tasters use Arabica type, and they usually do not add sweetener to it. Even if they add milk, it is not necessarily means the addition of sweetener. There is a clear distinction among genders: there are significantly more coffee consumers among women (χ²(1, n=143)=3.65, p=0.05), furthermore females have their coffee with milk and sweetener, while males prefer to drink it without milk (black). This is supported with the outcomes of contingency analysis (drinking coffee black: χ²(1, n=143)=3.46, p=0.05; with milk: χ²(1, n=143)=6.51, p=0.01).

6.1.1.3. Relationship among taster status and tea consumption

Fourteen respondents reported that they do not consume tea, so their results were not analysed. The major categories were ‘Several types including black tea’ (consuming several tea types, including black tea); ‘Several types, but no black tea’ (consuming regularly other type of tea than black). The ‘Sweetened’ label refers to the use of any sweeteners (sugar, artificial and natural sweeteners) for tea consumption.

The ‘Flavouring – Variegated’ category means the use of several ways of flavouring (sometimes with sugar, with lemon and sometimes without sugar), while the ‘Flavouring – More items’ refers to the use of sweetener and lemon. Among the 156 tea consumers 57 individuals drink their tea without flavouring (no sweetener, no lemon added).

During our analysis we did not find significant relationship among taster status and tea consumption (χ²(1, n=170)=1.26, p=0.26), its frequency (χ²(1, n=156)=0.95, p=0.32), the consumed tea types (χ²(5, n=156)=2.57, p=0.76) and the flavouring types of the tea (χ²(4, n=156)=5.13, p=0.27). There were also no significant differences among genders.

Pattern of the multiple correspondence analysis (Figure 4) shows that females and tasters consume tea more frequently, especially black teas and herbal infusions, both flavoured, or non-flavoured. Males and non-tasters consume tea less frequently, they prefer green tea, flavoured with lemon and sweetener, or only with lemon. It was not typical among the respondents that they might consume only fruit infusions.

7. Discussion

The ratio of tasters and non-tasters in our study is in accordance with those reported in the literature, namely 70% vs. 30% in the American and Caucasian population [6, 37]. We did not find relationship between taster status and BMI value, similarly to previous studies [17, 38]. Contrary to these results, some researchers were able to find significant correlations among these parameters [39]. Generally, the results on this field are controversial; there is no consensus among the researchers. Our new outcomes did not show relationships between taster status, body fat percentage and visceral fat area. However, our results showed significant differences between the genders in the overweight BMI category. The reason behind this is the muscle weight of the two genders: the BMI does not differentiate between fat tissue and non-fat tissue and does not take into consideration the distribution of body fat. Therefore, the BMI value’s specificity is high, but its sensitivity is low [40]. In case of the male participants the skeletal muscle mass was significantly higher (Mann-Whitney U=1664, n1 =23, n2 = 73, p<0.0001, two-sided), so more of these individuals were put into the overweight category.

Although we did not find significant relationships in case of coffee consumption, we have observed trends, patterns according to the multiple correspondence analysis. Non-tasters consume coffee less frequently, and they are unable to specify its exact type. These two factors are probably related to each other, since those people who are less interested in coffee consumption, are also less interested in the exact type of coffee. When these individuals consume coffee, they usually add sweeteners, this is less typical in case of tasters, which is supported with literature data [41]. The difference among genders in flavouring or not flavouring the coffee might be related to a social expectation, that the espresso shot is more masculine, while the latte type drinks (e.g. milk espresso) is more feminine [42].

In case of tea consumption, we did not find significant relationships, but several trends were recognized, which are in accordance with the international literature, stating that tasters prefer green tea in a smaller extent [43, 44].

The limitation of our study, that it was not representative from the demographic point of view. During the tests, we have worked with commercially available paper strips, while using PTC or PROP solutions might lead to results that are more precise.

8. Conclusions

Both literature data and our own results show that there might be some level of relationships among genotype, body composition and food choice. It is very likely, that not the genotype, but the phenotype (taster - non-taster) will be the factor which indirectly, through the food choice and food preferences might contribute to obesity, and its related diseases. Since eating habits and food preferences are influenced by other factors (like sociodemographic or psychological ones), these effects might overwrite the expected consequences of the phenotype (preference or aversion toward bitter taste). Furthermore, representative studies with larger sample size are necessary to confirm these hypotheses.

9. Statements

Financial support: The project was supported by the grant EFOP-3.6.3-VEKOP-16-2017-00005. It was also supported by the Ministry of Innovation and Technology grant number ÚNKP-19-3-I-SZIE-65 New National Excellence Program. The authors thank the support of the National Research, Development, and Innovation Office of Hungary (OTKA, contracts No FK 137577).

Contribution of authors: Experimental design: BB, AL, MVB, AG; Data acquisition: BB, DK, AL, MVB, ZK; Data analysis: BB, AG; Preparation of manuscript: BB, AG, ZK; Supervision and approval of manuscript: BB, AG, DK, AL, MVB, ZK.

Conflicts of interest: The authors have no conflicts of interest.

Acknowledgements: Barbara Biró thanks the support of the Hungarian University of Agriculture and Life Sciences, Doctoral School of Food Science. Attila Gere thanks the support of the Premium Postdoctoral Program and the National Research, Development and Innovation Office (project number K134260). The authors thank the cooperation of the test participants.

10. References

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DOI: DOI: https://doi.org/10.52091/EVIK-2022/2-2-ENG

Received: December 2021 – Accepted: March 2022

¹ Novel Food Kft.
² Eurofins Food Analytica Kft.

Keywords

Beer, bottling machine hygiene, small-scale brewing, lactic acid bacteria, Enterobacteriaceae, Bacillus, Pectinatus, Megasphera, wild yeast, fungi, CIP cleaning system, alpha acids

2. Introduction

2.1. Small-scale brewing

In legal terms, breweries that produce less than 200,000 hectoliters of beer per year has been called small-scale breweries in Hungary since 2017. Regulation before 2017 drew the line at 8,000 hectoliters, under which breweries benefited from a 50% excise tax rebate [3].

2.2. Fruit beers

The category fruit beer includes beers that are made with some kind of fruit or a combination of several fruits. Here the word fruit is used in a culinary rather than a botanical sense: fleshy, seed-associated plant structures that are sweet or sour and can be eaten raw. These include, for example, pome fruits (apples, pears, quinces), stone fruits (cherries, plums, peaches, apricots, mangoes, etc.), as well as fruits that have “berry” in their English names (strawberries, raspberries, blueberries), currants, citrus fruits, dried fruits (dates, prunes, raisins, etc.), tropical fruits (banana, pineapple, guava, papaya, fig, pomegranate, cactus figs, etc.) [7].

Flavored beer: Beer for which other flavoring substances may be used instead of or in addition to hops to create a flavor effect. The detailed characteristics of these products are recorded in the product data sheet.

In the case of flavored beers, the flavoring substances are added to the wort or the beer during the brewing operations, at the latest during maturation or filtration. As a result of the flavoring substance added during maturation or filtration, the original gravity of the finished beer may not increase by more than 1/3 [8].

2.3. Launching production in a small-scale brewery

Ideally, the main sub-processes of launching production in a small-scale brewery are as follows:

1. Conducting official licensing procedures
2. Construction of the production plant and auxiliary facilities
3. Product development
4. Installation of brewing technology
5. Product manufacturing
6. Product sales

It is important to emphasize that during an efficient and cost-optimized production launch, product development precedes the acquisition of brewing technology, a sub-process specifically based on the experience of the former. This sequence can be achieved with the involvement of a service organization specializing in product development, which has the professional and technological background required for the process.

2.4. Technological equipment involved in our project

For the small-scale production of fruit beer, the following main technological equipment were installed:

• Malt mill
• Mash house equipment
• Combined mashing/filtering tub
• Universal hop kettle - Whirlpool tub
• Electric control panel for the brewing process
• Wort cooling and recuperation equipment
• Heat supply equipment
• Mash house auxiliary equipment
• Fermentation area equipment
• Barrel washing and filling equipment
• Diatomaceous earth filter
• Beer pasteurization equipment
• Bottling machine
• Compressed air supply equipment
• Refrigeration technology equipment
• Brewery ancillary equipment

In the above list, equipment which is specifically used to ensure or improve the microbiological stability of beer or have an above-average effect on it are highlighted.

3. Microbiological production control

3.1. Microbiological stability of beer

The biological stability of beer is compromised by any microorganism that is able to multiply in beer, cause turbidity or form bottom sediments, and damage the beer through its metabolites. The number of these microorganisms is small, as only lactic acid bacteria and yeasts are able to grow under the given anaerobic conditions due to the alcohol content, carbon dioxide content, bitterness and low pH of beer. There is a certain period of time between the infection and turbidity caused by these microorganisms and the appearance of the bottom sediment, the length of which depends on the degree of infection, the virulence of the organisms, the quality of the beer, the access of oxygen and the storage temperature.

Microbiological stability can be ensured by the use of biologically sound adjusting yeasts with high fermentation potential, the concentrated culture of which and the thorough washing, cleaning and disinfection of the tanks, lines and equipment have been checked.

Automatic cleaning equipment deserves special attention. Sharp filtration, together with pumping with the exclusion of ambient air and the use of containers cleaned with sufficient thoroughness, allows the beer to be dispensed without pasteurization. Close microbiological control is required at each stage, such as fermentation, maturation, filtration and pumping. [4]

3.2. Factors influencing the microbiological stability of beer

From a microbiological point of view, beer is a relatively stable beverage. The beer parameters that contribute to this stability are as follows:

• Ethanol content (up to 10%, sometimes even higher): exposure to 5% ethanol has been shown to increase the permeability of the cell membrane and thus to interfere with the proton-driving force across the membrane (which is important for energy production). This means that most microbes do not survive or multiply in beer at this alcohol level.
• Carbon dioxide content (~0.5% v/v): dissolved CO2 creates an anaerobic environment, preventing the growth of microorganisms that cause aerobic deterioration.
• Low pH (pH 3.8-4.7): many microorganisms are unable to grow at low pH (pH<5) because they cannot maintain intracellular pH homeostasis at these low pH values.
• Iso-alpha acids (15-100 µg/L, the concentration may be different from this): iso-alpha acids exert an antimicrobial effect by increasing the permeability of bacterial cell membranes.
• Decreased nutrient availability (most fermentable sugars are metabolized by yeast): many important nutrients, such as carbohydrates, amino acids and some vitamins B are present in very low concentrations in beer as they are consumed by the yeast during fermentation. Any increased nutrient levels (e.g., carbohydrates in low-alcohol beers) pose a risk of proliferation of microorganisms that cause spoilage.
• Low oxygen content (preferably below 0.1 µg/L): anaerobic conditions reduce the risk of potential growth of microorganisms that cause aerobic spoilage.

In modern brewing, a number of techniques are used to prevent the entry of microbiological contaminants or their survival during the brewing process, as well as during filling/packaging, in order to increase microbiological stability. Some examples:

• Boiling the mash, pasteurization, or sterile filtration before packaging.
• Well-designed brewing equipment that resists aggressive hygiene practices, such as CIP (Clean-In-Place) cleaning.
• Elimination of many traditional (and microbiologically risky) production processes (e.g., spontaneous fermentation or open fermentation vessels).

3.3. Causes of infection

Pediococcus cerevisiae in the form of mono- and diplococci, or tetracocci, clouds the beer and gives it an acidic, diacetyl taste reminiscent of butter.

Lactic acid bacteria produce lactic acid, formic acid and acetic acid. They also cause turbidity and, in part, form bottom sediment.

Wild yeasts are rare. They make the beer cloudy, form a juicy bottom sediment and also impart a mostly aromatic, distinct, partly coarsely bitter taste.

Cultured yeasts cause turbidity, bottom sediment, or only separate yeast colonies in the pumped off beer. Even if they remain only imperfectly in the beer after filtration, they can multiply after the rich oxygen uptake during pumping, especially if there is a large difference between the final degree of fermentation of the beer and the dispensed degree of fermentation [4].

3.4. Spoilage microorganisms

3.4.1. Microorganisms most often associated with brewing and beer

Each raw material (e.g., malt, hops, water or additives) carries its own specific microorganisms. The proliferation of these microorganisms during one of the brewing steps results in the formation of metabolites that cause aftertastes. In the event that these microorganisms survive all steps of the brewing process, including pasteurization, if used, they may be present in the bottled beer as potential spoilage agents. Yeast used for the fermentation can also be a source of contamination.

It has been observed that during yeasting, the yeast can be contaminated with small amounts of bacteria and wild yeast. To avoid this, proper treatment of brewer’s yeast is required.

Additional sources of contamination can be the brewing equipment (vessels, lines) if they are not properly cleaned and maintained. Until packaging is completed, the final steps in the manufacturing process (after fermentation) may also be prone to contamination by microorganisms that are airborne or present in the filling apparatus (e.g., due to high humidity).

Spoilage microorganisms most often found in breweries and in beer are listed in Figure 1.

Contaminating bacteria in beer are mostly lactic acid bacteria belonging to the genera Lactobacillus and Pediococcus (accounting for more than 80% of the bacterial infections in beer), but other anaerobic bacteria such as Pectinatus and Megasphaera are sometimes also found in spoiled beer. [2]

3.4.1.1. Lactic acid bacteria [6]

Lactic acid bacteria are strictly fermentative, facultative anaerobic Gram-positive, non-spore-forming rods or cocci that belong to the order Lactobacillales. Most Gram-positive bacteria are inhibited by iso-alpha acids however some are resistant to these antibacterial compounds. The two most common lactic acid bacteria in beer are Lactobacillus brevis and Pediococcus damnosus. These bacteria produce acetic acid and lactic acid, and also compounds responsible for various aftertastes, such as diacetyl (“buttery” flavor). Pediococcus in particular is known to produce large amounts of vicinal diketones. Pediococcus also has a relatively high alcohol tolerance: it can proliferate even at ethanol concentrations above 10%. In addition, lactic acid bacteria also produce exopolysaccharides (EPS), which cause so-called silky turbidity in beer due to the increased viscosity and mucous appearance.

The most important Lactobacillus species are L. brevis and L. lindneri; less common are L. rossiae, L. buchneri, L. coryniformis, L. casei and L. backii. L. brevis often develops longer, parallel-walled, single or double rods with a round end (0.7 × 4 μm), with the double rods often being bent. It does not form cell chains, but extremely long rods (up to 50 μm) can sometimes be found in beer. Common characteristics of L. brevis are (hetero-fermentative) gas formation, fermentation of pentoses and melibioses, as well as the ability to cleave arginine. This is the most common beer spoilage bacterium, causing turbidity and sediment, while also lowering the pH perceptibly, which in turn gives beer an acidic taste. However, it does not produce diacetyl. It often appears as a secondary contaminant.

L. bucherni is able to ferment melisitose, unlike L. brevis. L. lindneri forms short, slightly irregular or coccoid cells that are arranged in longer chains. Sometimes long rods are formed. Heterofermentative species mainly ferment glucose and maltose and do not cleave arginine. Mild sedimentation and turbidity may be observed in the beer however taste defects do not usually occur. This is a typical primary contaminant that is often found in yeast factories or in the fermentation area, but can also pass through the filters, being very small cells.

L. rossiae has similar properties and is mucus-forming. Facultative heterofermentative species, such as L. casei, L. coryniformis and L. plantarum form shorter rods that are often arranged in chains. They are mostly found in weaker hop beers (e.g., wheat beer) and cause obvious taste defects due to diacetyl formation. They often appear only as secondary contaminants. The obligate homofermentative beer spoilage L. backii ferments mannose, mannitol and sorbitol. It also differentiated from the other species by the absence of fermentation of maltose and gluconate.

P. damnosus is characterized by the formation of tetrads. It is typically a primary contamination that often occurs in cultured yeast and unfiltered beer. The cells can also be transferred to the bottled beer through the filter. Contamination results in strong diacetyl formation (buttery taste) and a decrease in pH, and beers are often slightly turbid and exhibit noticeable sedimentation. Two other Pediococcus species that cause beer spoilage, P. inopinatus and P. claussenii, behave similarly, although both species are less common. The latter causes mucus formation in the beer.

3.4.1.2. Enterobacteriaceae [6]

Enterobacteriaceae is a facultative anaerobic Gram-negative bacterial family. The two genera commonly associated with brewing are Citrobacter and Rahnella (most likely to be introduced with the water used for brewing). These bacteria are responsible for the production of a number of compounds causing aftertastes, such as VDKs (e.g., diacetyl), 2,3-butanediol, DMS, acetaldehyde and lactic acid. These compounds are produced at the beginning of the fermentation.

3.4.1.3. Bacillus [6]

Gram-positive, facultative anaerobic, spore-forming bacteria. Due to spore formation, they survive heat treatment, including pasteurization. Bacillus also poses a risk because it can reduce nitrate to nitrite, which can lead to the formation of N-nitrosamines (classified as carcinogenic, teratogenic and mutagenic substances). Since certain Bacillus species are able to produce large amounts of lactic acid, they can also cause acidification. Most Bacillus species (but not their spores) are susceptible to the iso-alpha acids from hops.

3.4.1.4. Pectinatus [6]

These Gram-negative, strictly anaerobic bacteria can produce large amounts of acetic acid and acetoin, and hydrogen sulfide production (rotten egg aroma) has also been reported.

Pectinatus cerevisiiphilus and P. frisingensis are also strictly anaerobic, catalase-negative, Gram-negative bacteria, and have similar negative effects as the species listed so far. The cells are slender (0.8 × 4 μm), parallel-walled with a pointed end, slightly bent or serpentine or corkscrew-like, and serially flagellated on one side. Similarly to M. cerevisiae, they grow in the range of 15 to 40 °C (with the optimum being between 28 and 32 °C). They ferment various sugars, sugar alcohols and organic acids (mainly pyruvate and lactate). The primary metabolites are propionic acid, acetic acid, pyruvic acid, acetoin and CO₂. Beers contaminated with them (pH above 4.3, alcohol content below 5% vol.) exhibit not only serious sedimentation and turbidity problems, but also unpleasant odor and taste defects (sewage odor). Similarly to M. cerevisiae, these are typically secondary contaminants that occur primarily in the bottling area.

3.4.1.5. Megasphaera

Megasphaera species can appear as Gram-negative, strictly anaerobic contaminants in both wort and finished beer. They cause turbidity in beer and produce large amounts of hydrogen sulfide and a number of short-chain fatty acids (“cheesy” aroma). [2]

Catalase-negative, strictly anaerobic, Gram-negative Megasphaera cerevisiae forms large oval or round cells (1.2 – 1.6 μm) that exist in the form of diplococci and short chains. They ferment fructose, pyruvic acid and lactic acid, in particular. [6]

The primary metabolites are butyric acid, acetic acid, propionic acid, valeric acid, as well as CO₂ and hydrogen gas. Only a slight turbidity is exhibited by the beer; however, due to the above-mentioned metabolites, there can be significant odor and taste defects (sewage odor). The species is sensitive to alcohol (below 5% vol.) and prefers a higher pH value (above 4.4). The secondary contaminant that is present primarily in the vicinity of the bottling equipment are typically favorable to these bacterial species [6].

3.4.1.6. Wild yeast

Any strain of yeast, except the selected Saccharomyces yeast, is a contaminant. These yeast contaminants are usually referred to by brewers as wild yeast, which may be Saccharomyces cerevisiae or non-Saccharomyces strains, such as Brettanomyces bruxellensis, Candida or Pichia. Proliferation of wild yeast can carry a safety risk: the alcohol content can increase due to the metabolism of the infecting yeast. These wild yeasts are sometimes able to ferment dextrins and starch into ethanol (so-called superattenuation). Along with the production of ethanol, the CO₂-content, and thus the bottle pressure increases, which can pose a safety risk due to the bursting of the bottles. In addition, wild yeast can ruin the beer through the production of ester or phenolic aftertaste (e.g., 4-vinylguaiacol), as well as turbidity or sediment formation. It is important to note that acid washing of the yeast cells does not remove these wild yeast contaminants [5].

3.4.1.7. Fungi

Field infestation by Fusarium fungi poses a serious food safety risk to cereals. Almost all parts of the plant (germ, root, stalk, stem, leaf pod, leaf, ear and grain) can become affected. Severely infected plants produce less and lower quality crops, toxins are produced in the diseased grains, their germination vigor is reduced. The pathogens that cause the disease are different Fusarium species with various infectivity and toxin production, which can be greatly related to environmental factors, such as temperature and humidity. The toxins can be present throughout the entire brewing process, up to the bottled finished product. Certain Aspergillus species can also produce mycotoxins. Both Fusarium and Aspergillus species produce hydrophobic compounds, which are small surfactant proteins that cause foaming [6].

4. Cleaning, disinfection

Cleaning and disinfection of the lines, tanks and equipment is key in a brewery. All surfaces and equipment must be clean, the presence of contaminating bacteria, yeasts and fungi must be eliminated.

Examples of possible contaminants in a brewery:

• Beer left over from previous brewing
• Microbiological contaminants (yeasts, bacteria, fungi)
• Hop residues
• Calcium oxalate (beer stone that can be removed with acids)
• Lipids, proteins (removal with bases)
• Mineral deposits in the water circuit

In this regard, it is important to distinguish between cleaning agents and disinfectants.

Cleaning agents remove product residues and deposits, such as lipids and proteins. Depending on their pH value, these cleaning agents can be classified as alkaline, acidic or neutral cleaning agents. In order to further increase the cleaning capacity, additives, e.g., surfactants can be added. These are water-soluble molecules that reduce the surface tension of water, making it easier to remove contaminants.

Disinfectants are used to destroy most microbial contaminants. Here again, it is important to point out that bacterial spores are very difficult to destroy, which is why this process is called disinfection, not sterilization. Examples of disinfectants:

• Halogenated disinfectants, for example NaOCl (sodium hypochlorite). NaOCl is a commonly used product, but unstable above 40 °C (with increased risk of corrosion).
• Oxidizing agents, such as H₂O₂.
• Quaternary ammonium compounds (often called quats). Quats are cationic surfactants. Despite their good properties, quats are not used in breweries very often because they typically from foams and difficult to rinse, which endangers the quality of the beer, e.g., may impair the stability of the foam.
• Steam disinfection.
• Critical points include the so-called dead spaces (pipe ends, branches in the lines, sampling points, poor welding, etc.). Lines and tanks are best cleaned with an integrated CIP system.

5. Laboratory tests

5.1. General experience

During the microbiological testing of the sour cherry beer samples and the sour cherry concentrates, we found the following:

• Filtering of the sour cherry beer samples was not possible due to the high fiber content.
• Also, when testing the beers, in the case of the plate casting process, when covering 10 ml of the sample with a suitable layer thickness of 3 to 5 mm of PCA (for microbial count test) or DRBC (for yeast count test) culture medium in a large Petri dish (140 x 14.8 mm), the agar did not gel because of the low pH of the sample. Therefore, in these tests, the test volume was first reduced from 10 ml to 1 ml.
• Then the microbiological study of the sour cherry concentrates was started, due to the expected sterility of the raw material, using our own method for the detection of presence/absence.
• This method was further modified to include the testing of beers. As the issue was not the sterility of the beer but its practical shelf life, as a final, modified solution, the presence/absence of reproducible microorganisms was tested by an enrichment method in both cases, with the same amount of inhibitor as prescribed in the recipe of the finished beer (0.02 g/L potassium sorbate). In this way, it was practically modelled whether the microorganisms that may be present in the beer can reproduce at a high nutrient content.

5.2. Description of the test methods of sour cherry beers

5.2.1. Microbial count, plate casting, colony counting (MSZ EN ISO 4833-1:2014, accredited method)

The stock suspension and the decimal dilutions are prepared from the sample according to the international standard MSZ EN ISO 6887. Using a sterile pipette, 1 ml of the sample (for liquid samples) or stock suspension is added to two Petri dishes. The procedure is repeated with additional dilutions, if necessary. 12 to 15 ml of 44 to 47 °C PCA agar is added to each Petri dish. The Petri dishes are inverted and incubated in a thermostat at 30 °C for 72±3 hours.

5.2.2. Yeast count, surface spreading, colony counting, water activity >0.95 (MSZ EN ISO 21527-1:2013, accredited method)

The stock suspension and the decimal dilutions are prepared from the sample according to the international standard MSZ EN ISO 6887. 1 ml of the sample (for liquid samples) or stock suspension is added evenly in 3 portions to the surface of the DRBC agar filled in Petri dishes, and the sample portions are spread on the surface of the agar. The procedure is repeated with an additional degree of dilution and, if necessary, with additional dilutions. The dishes are inverted after 15 minutes and incubated in a thermostat at 25 °C for 3 to 5 days.

5.2.3. Presence/absence detection of reproducible microbes, enrichment technique (own method)

In the case of a 0.33-liter bottle of beer, the sample is divided into 3 equal portions and the sample portions are incubated for 72 hours at 30 C° in 3 x 100 ml stock broth containing 0.02 g/liter of potassium sorbate. At the end of the culture period, 1 µl of each enriched sample portion is applied to a PCA plate, and the plates are incubated for 72 hours at 30 °C. If no increase in the colonies is observed on the plate, the result is reported as ‘negative/100 ml’, while if colonies do form, the result is reported as ‘positive/100 ml’.

Composition of the PCA (Plate Count Agar) culture medium for microbial count determination:

• tryptone 5 g/l
• yeast extract 2.5 g/l
• glucose 1 g/l
• agar 9 g/l
• pH: 7.0±0.2 (25 °C)

5.2.4. Presence/absence detection of reproducible yeast, enrichment technique (own method)

In the case of a 0.33-liter bottle of beer, the sample is divided into 3 equal portions and the sample portions are incubated for 72 hours at 25 °C in 3 x 100 ml of malt broth containing 0.02 g/liter of potassium sorbate. At the end of the culture period, 1 µl of each enriched sample portion is applied to a DRBC agar plate, and the plates are incubated for 72 hours at 25 °C. If no increase in the colonies is observed on the plate, the result is reported as ‘negative/100 ml’, while if colonies do form, the result is reported as ‘positive/100 ml’.

Composition of the DRBC (Dichloran Rose-Bengal Chloramphenicol) agar:

• enzymatically digested animal and plant tissues 5 g/l
• glucose 10 g/l
• potassium dihydrogen phosphate 1 g/l
• magnesium sulfate 0.5 g/l
• dichloran (2,6-dichloro-4-nitroaniline) 0.002 g/l
• Rose Bengal 0.025 g/l
• agar 15.0 g/l
• pH: 75.6±0.2 (25 °C)

Composition of the Takács stock broth (MSZ 3640/13-76):

• tryptone 4 g/l
• meat extract 4 g/l
• yeast extract 2 g/l
• sodium chloride 2 g/l
• disodium hydrogen phosphate 2 g/l
• pH 7.2-7.4 (25 °C)

Laboratory tests were carried out by the laboratory of EUROFINS Food Analytica Kft.

6. Relationships between the microbiological state of the finished product and the bottling machine

In all cases, the control tests applied during product development and subsequent production were extended to the examination of the microbiological condition of the technological equipment. At the same time, the possible effects of the microbiological condition of the equipment on product quality were explored.

In the course of the project, by examining the bottling machine, manufacturing defects of the machine were brought to light, which were later acknowledged and eliminated by the manufacturer based on the results of our tests.

• The manufacturer’s CIP (Cleaning-In-Place) cleaning and disinfection program was set on the pneumatic branch lines of the taps with insufficient exposure time
• The foaming water supply was not connected to the CIP system
• The beer druck tank could not be cleaned adequately due to the dead spaces it contained
• The CO2 inlet branch line of the beer druck tank was not connected to the CIP system

The results of the comprehensive microbiological testing of the bottling machine used in our project before conversion are summarized in Table 1, while the results of the microbiological testing of the beer bottled using this machine are summarized in Table 2. The microbiological tests were performed by the laboratory of EUROFINS Food Analytica Kft., a testing laboratory accredited by NAH (National Accreditation Authority) under reg. no. NAH-1-1582/2021. Objectionable results are highlighted in the table in red.

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Prior to the conversion, the quality defects of bottled fruit beer that could be attributed to its microbiological condition were: taste defects (ester aftertaste), increase in CO2 content and thus in bottle pressure, gushing (foaming beer squirting when the bottle is opened).

At our suggestion, the following modifications were made to the bottling machine by the manufacturer:

• Increased operating time of the CIP program on the pneumatic branch lines of the taps
• Connection of the foaming water supply to the CIP system
• Elimination of the dead spaces of the beer druck tank
• Connection of the CO₂ inlet line of the beer druck tank to the CIP system

The results of the comprehensive microbiological testing of the bottling machine used in our project after conversion are summarized in Table 3, while the results of the microbiological testing of the beer bottled using this machine are summarized in Table 4.

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Test method – yeast count: MSZ ISO 21527-1:2013 [9]
Test method – microbial count: MSZ EN ISO 4833-1:2014 [10]

Following the conversion, the hygienic condition of the bottling machine became satisfactory (Table 3), and the previously observed quality defects of the bottled fruit beer related to its microbiological condition were eliminated, as shown by the test results in Table 4. Due to the achieved microbiological stability, the preservation of the quality of the product could be ensured.

7. References

[1] Növekedes.hu (2020): A kisüzemi sörfőzdék piaci részesedése 5-6 százalékra nőhet az új törvény hatására. (Hozzáférés: 2021. 10.16.)

[2] 2020. évi CXL. törvény a kereskedelemről szóló 2005. évi CLXIV. törvény módosításáról

[3] A Tanács 92/83/EGK Irányelve (1992. október 19.) az alkohol és az alkoholtartalmú italok jövedéki adója szerkezetének összehangolásáról. 1. szakasz, 4. cikk

[4] Ludwig Narziss (1981): A sörgyártás. Mezőgazdasági Kiadó, Budapest.

[5] KULeuvenX (2021): Beer: the science of brewing. BrewingX. KU Leuven, Leuven, Belgium

[6] Hans Michael Eßlinger (2009): Handbook of Brewing: Processes, Technology, Markets. WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

[7] Beer Judge Certification Program, Inc. (BJCP) (2015): 2015 Style Guidelines

[8] Magyar Élelmiszerkönyv Bizottság (2013): 2-702 számú irányelv (régi 2-96 számú irányelv) Sör. Magyar Élelmiszerkönyv - Codex Alimentarius Hungaricus. Magyar Élelmiszerkönyv Bizottság, Budapest

[9] MSZ ISO 21527-1:2013 Élelmiszerek és takarmányok mikrobiológiája. Horizontális módszer az élesztők és a penészek számlálására. 1. rész: Telepszámlálásos technika a 0,95-nél nagyobb vízaktivitású termékekre (Microbiology of food and animal fedding stuffs. Horizontal method for teh enumeration of yeasts and moulds. Part 1: Colony count technique in products with water activity greater than 0,95)

[10] MSZ EN ISO 4833-1:2014 Az élelmiszerlánc mikrobiológiája. Horizontális módszer a mikroorganiz-musok számlálására. 1. rész: Telepszámlálás 30 °C-on lemezöntéses módszerrel (ISO 4833-1:2013) (Microbiology of the food chain. Horizontal method for the enumeration of microorganisms. Part 1: Colony count at 30 degrees C by the pour plate technique (ISO 4833-1:2013)

DOI: https://doi.org/10.52091/EVIK-2022/1-2-ENG

Received: November 2021 – Accepted: February 2022

¹ South Ural State University (national research university), Chelyabinsk, Russian Federation
² South Ural State Agrarian University, Troitsk, Russian Federation
³ LLC „Antey”

Keywords

adulteration, fruit and berry raw materials, chemical composition of fruits, organic acids profile, mineral elements.

2. Introduction

The modern consumer market of edible raw materials and foods is extremely important strategic part of the modern economy of the Russian Federation. In recent years, the spread of adulterated goods there has reached such a level that it threatens Russia’s national security. Adulteration of agricultural raw materials should be regarded as one of the most dangerous types of fraudulent practices, because it creates favorable conditions for unfair competition, leading to stagnation, loss of export potential of domestic food producers and, consequently, to the decrease in the investment appeal of the industry.

Fresh juicy berries and fruits are natural sources of biologically active substances. However, these are seasonal, perishable products. So, to level the seasonal nature of consumption, increase the shelf life of the finished product and reduce the transportation and storage costs, they are often processed and dried [1, 2].

Strawberry (Fragaria x ananassa, D.) is known as a berry with high content of organic acids (citric, malic, quinic, salicylic, as well as succinic and traces of shikimic and glycolic upon ripening), vitamins C, PP, E, B₁, B₂, B₆, B₉, K, carotene, pectin and other substances. Strawberry is rich in phenolic compounds which have antioxidant, anti-inflammatory, and anticancer action [3, 4]. Ripe raspberry (Rubus іdaeus L.) contains free organic acids (citric, malic, salicylic), minerals (Co, Cu, K, Na, Fe, Ca, Mg, P) [1, 5], vitamins (B-group, PP, C, provitamin A), tanning substances [6]. Raspberry has diuretic, choleretic, anti-anemic effect, helps strengthen the walls of blood vessels and promotes intestinal health [14]. Melon fruits (Cucumis melo) contain proteins, carbohydrates (sugars, starch, fiber), organic acids, vitamins (B-group, PP, A, C, β-carotene), minerals (K, Na, Fe, Ca, Mn, Mg, Zn). Melon is especially recommended in case of exhaustion, anemia, atherosclerosis, and some other cardiovascular diseases. Melon enhances the effect of antibiotics reducing their toxicity [7].

Rich chemical composition of dried fruit and berry raw materials allows to use them in the production of dairy and baked goods, confectionery, snacks, salads, ketchups, seasonings in order to enrich them with vitamins, minerals, organic acids, fiber, etc. [8]. Knowing the chemical composition of fruit and berry raw materials, identifying components forming the organoleptic characteristics not only constitutes a prerequisite for the production of competitive products, but also makes it possible to identify adulteration. The purpose of the research was to assess the quality and to identify the chemical composition of fruit and berry powders. Research objectives were to study organoleptic properties, physical and chemical parameters, as well as nutrient composition of fruit and berry powders comparing them with commonly known data; to identify the profile of organic acids and mineral composition of the plant material under study.

3. Materials and methods

The investigated products were fruit powders of strawberry, raspberry and melon produced by a Russian company. According to the declaration of the manufacturer, the composition of these powders is 100% corresponding natural raw materials containing no preservatives, dyes, or artificial flavorings.

Organoleptic characteristics of the fruit powders were studied according to GOST 8756.1-2017. Moisture content was determined according to GOST 33977-2016, fat and protein content – according to MU 4237-86 guidelines, non-volatile acids – according to M 04-47-2012, sugars – according to M 04-69-2011, metal and foreign impurities, contamination with grain pests – according to GOST 15113.2-77, food fibers – using the generally accepted method [9], minerals – according to MUK 4.1.1482-03 and MUK 4.1.1483-03 guidelines. All measurements were carried out in three replications.

4. Results and discussion

Sensory evaluation of the quality of the studied materials showed the following: in appearance, the samples of processed strawberries, raspberries, and melons were finely ground homogeneous loose odorless powders, which is uncharacteristic of each type of the original natural raw material. The colour was identified as intense, uniform throughout the mass of the powders, uncharacteristic of dried products, with the following tones: pink with a gray hue for the strawberry powder, light burgundy for the raspberry powder, and light yellow for the melon powder. A sweet taste was noted in the strawberry and melon, and a sour taste in the raspberry material.

According to the results of physical and chemical study of plant materials, no deviations were found from the normal values. Thus, the moisture content of the powders under study was within the range of 4.2-5.1% (in various literature data, the range is 4-12% [1], no infestation with grain pests or presence of metallic and foreign impurities were found.

Fruits and berries have rich chemical composition, which makes them unique elements of a healthy diet [5]. In this regard, we investigated the main nutrients contained in the studied samples of fruit and berry powders.

To begin with, we compared the obtained test results with the information on the product packaging. We found that the actual levels of protein and lipids content did not correspond to the ones stated in the labeling, which indicates misinformation of the consumers. Thus, the amount of proteins and fats in the strawberry powder was 26 and 3.5 times lower, in the raspberry powder – 8 and 60 times higher, respectively, in the melon powder, contrary, it was slightly higher, as for protein in particular – by 55% (Table 1) than the labelling of the products.

Taking into account the fact that drying significantly increases the concentration of dry substances and, consequently, biologically active components [1, 2], it was determined that not all samples of the plant powders contained protein and fat even within the generally known range for fresh raw materials. For example, the amount of protein and lipids in the strawberry powder should be 7.0 g/100 g and 1.0 g/100 g, respectively [1]. The obtained results were far below.

Note: *content indicated on the packaging of fruit and berry powders, **in terms of dry matter. ^a Karkh et al., 2014, / ^b Akimov et al., 2020, / ^c Akimov et al., 2021, / ^d Sannikova, 2009, / ^e Erenova, 2010, / ^f Dulov, 2021, / ^g Pochitskaya et al., 2019, / ^h Baygarin et al., 2015, / ⁱ Medvedkov et al., 2015.

The most important indicator of the quality of fruits and berries is their sugar content, which depends on both the characteristics of a certain variety and weather conditions in the period of crop formation [5, 7]. It is known that for fresh raspberries, the content of sugars is 4-10 %, for dried berries - 34.5-42.2% [5]. Fresh strawberries contain 7.3-11.7% of sugars, which, as in raspberries, are represented mainly by fructose, glucose, and sucrose; their amount varies from 5.9 to 8.9 % [3, 4]. In the fruits of cultivated melon, the level of sugars is 7.0-21.0% [7, 10].

It was found that the ratio of mono- and disaccharides in the studied raw materials did not correspond to the data obtained by a number of scientists in practical studies [5, 6, 10, 11, 12, 13]. As for sugar content in strawberries, fructose should prevail significantly, in melon – sucrose, whereas in raspberries fructose and glucose content should be equivalent. It was revealed that in all samples of plant materials sugars were 80-97% represented by sucrose, and its high level indicated 40.4-52.3% addition of white sugar. In addition, the quantitative levels of monosaccharides in the strawberry powder did not even fall within the lower limits of their content established for fresh berries.

Plant material is distinguished first of all by the presence of dietary fiber, regular consumption of which contributes to the prevention of overweight and obesity, gastrointestinal, cancer, and cardiovascular diseases.

It was determined that by the content of dietary fiber, the studied samples of vegetable material were closer to the levels of characteristic of fresh juicy berries and fruits, since it is known, for example, that the amount of dietary fiber in dried chopped strawberries is not less than 8.0 g/100 g [5]. In our case the dietary fiber content of our samples were only 3.91±0.20 g/100 g.

It is well known that berry and fruit raw materials are characterized by a specific profile of organic acids and macronutrients, and the analysis of their content allows to determine adulteration or to prove its natural character [8]. So, these characteristics were studied in more detail. According to a number of authors, citric acid predominates in raspberry, while the content of malic acid is significantly lower. Salicylic acid in raspberries, which has bactericidal, antipyretic, and analgesic action, is of particular importance [5, 6]. Strawberries contain malic, benzoic, citric, tartaric, oxalic, succinic, and salicylic acids with the predominance of citric and malic ones [11]. Organic acids in cultivated varieties of melon are represented by malic and succinic acids, whereas citric and glucuronic acids appear during storage [10]. According to the test results, the amount and ratio of organic acids in the studied fruit powders did not correspond to the profile of natural raw materials (Table 2). Thus, oxalic and tartaric acids were absent in the strawberry powder, malic acid – in the raspberry raw material, and citric acid – in the melon material (their concentration stayed below the limit of detection).

Notes: *according to TR CU 021/2011, ** in terms of dry matter.

^a Stepanov et al., 2013, / ^b Karkh et al., 2014, / ^c Akimov et al., 2020, / ^d Akimov et al., 2021, / ^e Sannikova, 2009, / ^f Erenova, 2010, / ^g Dulov, 2021, / ^h Pochitskaya et al., 2019 / ⁱ Medvedkov et al., 2015

Strawberries and raspberries are known to be rich in macro- and micronutrients. Thus, 100 g of strawberries cover 330% of the daily demand in Si, 264% in B, 40% in Co; 100 g of raspberries – 120% of the daily demand in Si, 250% in B [11]. Si is involved in the metabolism of most mineral elements and vitamins. It’s lack leads to the decrease of digestibility of Ca, Fe, Co, Mn and metabolic disturbance. B plays an important role in the prevention and treatment of bone disease.

Co is a coenzyme of many enzymes, it activates the metabolism of fats and synthesis of folic acid [11]. The berries also contain Fe, Zn, Mn, Cu, Mo etc. It was determined that the strawberry powder under study did not contain in detectable amount of intrinsic essential macro- and microelements, namely Ca, Mg, B, Co, the amount of Si, Fe, K was at the trace level, indicating that the material was not natural. The raspberry powder turned out to be devoid of Co, K, whereas the amount of B, Ca, Cu, Mg, Mn, Si, important for the plant life, was residual. The mineral composition of melon fruit includes K, Ca, Mg, P, Nа, Fe. K is of extreme importance in the mineral nutrition of melon. The higher level of potassium nutrition increases productivity, disease resistance, accumulation of ascorbic acid and sugars [15]. The content of Fe, which plays a leading role in the formation of red blood cells – carriers of oxygen – is 17 times higher in melon than in milk [16]. When testing the mineral profile of the melon powder, it was found that it lacked the plant physiologically “obligatory” amount of K, Fe, Ca, Co, Cu, Mg, Mn, which does not correspond to the fundamental laws of physiology of the plant itself. The results allowed us to conclude about the qualitative adulteration of this plant material.

5. Conclusions

The results of physical and chemical tests of the studied raw materials showed deviations from the norms. Studying the levels of proteins and fats of products of strawberry, raspberry, and melon powders confirmed the fact of adulteration. The data obtained during organoleptic evaluation of quality and identification of profile of sugars, organic acids, and mineral elements allowed us to conclude that the powders under study were not natural fruit and berry raw materials.

6. Conflicts of interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the content of this paper.

7. Thanks

The work was supported by Act 211 of the Government of the Russian Federation, contract No. 02.A03.21.0011.

8. References

[1] Ermolaev, V. A. (2019): Low-temperature vacuum drying as the method of draining of plant raw materials. The Bulletin of KrasGAU, 1 (142), pp. 160-166.

[2] Mizberidze, M. Sh., Chakvetadze, Sh. M., Pruidze, M. R. (2017): Intensification of drying processes of berries in the field of infrared rays. Aeconomics: Economics and Agriculture, 8 (20), p. 5.

[3] Stepanov, V. V., Tikhonov, S. L., Mikryukova, N. V. (2013): The analysis of strawberry’s quality during the storage, grown in vivo and micropropagation. Agrarian Bulletin of the Urals, 12 (118), pp. 58-62.

[4] Karkh, D. A., Stepanov, V. V., Tikhonova, N. V., et al. (2014): Expansion of the fortified foodstuffs production as a basis of food security. Journal of Ural State University of Economics, 1 (51), pp. 118-121.

[5] Akimov, M. Yu., Bessonov, V. V., Kodentsova, V. M., et al. (2020): Biological value of fruits and berries of Russian production. Problems of Nutrition, 89 (4), pp. 220-232. DOI

[6] Akimov, M. Yu., Koltsov, V. A., Zhbanova, E. V., et al. (2021): Nutritional value of promising raspberry varieties. IOP Conf. Series: Earth and Environmental Science, 640, 022078. DOI

[7] Sannikova, T. A. (2009): Scientific foundations of resource-saving, waste-free technology of melon cultivation: dissertation for the degree of Doctor of Agricultural Sciences. Astrakhan. 316 p.

[8] Rudenko, O. S., Kondratiev, N. B., Osipov, M. V., et al. (2020): Evaluation of fruit raw materials chemical composition by the content of organic acids and macronutrients. Proceedings of the Voronezh State University of Engineering Technologies, 82 (2), pp. 146-153. DOI

[9] Skurikhin, I. M., Tutelyan, V. A. (1998): Guide to methods for analysis of food quality and safety. Moscow, Brandes, Medicine, 342 p.

[10] Erenova, B. E. (2010): Scientific basis for the production of products on a religious basis: thesis abstract for the degree of Doctor of Technical Sciences. Almaty, 33 p.

[11] Dulov, M. I. (2021): Harvesting, storage and processing of raspberries and strawberries. Petrozavodsk. In the book: innovative technologies in science and education, pp. 4-24.

[12] Pochitskaya, I. M., Roslyakov, Yu. F., Komarova, N. V., et al. (2019): Sensory Components of Fruits and Berries. Food Processing: Techniques and Technology, 49 (1), pp. 50-61.

[13] Baygarin, E. K., Vedischeva, Yu. V., Bessonov, V. V., et al. (2015): The content of dietary fiber in various food products of plant origin. Problems of Nutrition, 84 (5), p. 15.

[14] Ermolina, G. V., Ermolin, D. V., Zavaliy, A. A., et al. (2018): Substantiation of modes of infrared drying of raspberries and blackberries. Transactions of Taurida Agricultural Science, 14 (177), pp. 112-118.

[15] Kosolapova, G. N. (2006): Biochemical composition of raspberry in conditions of the Kirov region. Agricultural Science Euro-North-East, 8, pp. 47-49.

[16] Medvedkov, E. B., Admaeva, A. M., Erenova, B. E., et al. (2015): Chemical composition of melon fruits of mid-season varieties of Kazakhstan. Agricultural sciences and agro-industrial complex at the turn of the century, 12, pp. 36-43.

DOI: https://doi.org/10.52091/EVIK-2022/1-4-HUN

Received: December 2021 – Acceptes: February 2022

¹ Hungarian University of Agriculture and Life Sciences, Institute of Food Science and Technology

Keywords

honey, pollen, nutrient content, botanical origin, moisture content, sugar content, ash content, amino acid composition, HMF, color characteristics

2. Introduction

Honey is one of our oldest foods and is still a popular sweetener around the world. According to the definition of the Hungarian Food Codex, „Honey is a natural sweet substance collected by Apis mellifera bees from plant nectar or the sap of live plant parts, or by insects that suck plant sap from the secreted material of live plant parts, which is collected by the bees, converted by the addition of their own substances, then stored, dehydrated and matured in honeycombs” [1]. Its energy content is provided by easily absorbed carbohydrates, but it also contains many other nutrients such as minerals, phenolic compounds and amino acids. Thanks to its natural aroma substances, honey has pleasant organoleptic properties, so it can be characterized by a high level of enjoyment [2]. Honey is also used for medicinal purposes, mainly due to its anti-inflammatory and antibacterial effects [3].

The pollen cluster is a little-known apiculture product that is of growing interest, especially among health-conscious consumers. The pollen cluster is formed by bees moistening the pollen adhering to their bodies with nectar and their glandular secretions, then compacting it into spherical pellets and transporting them to their hives in their “baskets” on their hind legs. This product can be collected by the beekeeper using a perforated device mounted in front of the hive entrance [4]. The product is usually preserved by drying or freezing. Pollen contains relatively high concentrations of nutrients essential for the body and can therefore be used as a dietary supplement [5] or a functional food raw materials [6]. According to some research, pollen has immunostimulatory and antioxidant effects, and thus plays an important role in apitherapy [3]. As the demand for apiculture products (honey, pollen, bee bread, propolis, wax) has increased, so has the number of scientific studies on honey. The number of studies on honey and pollen has increased exponentially since the 1990s [7]. From a food safety point of view, apiculture products have been the focus of research, as they may contain a number of risk factors, including pesticides, toxic metals, molds, mycotoxins, pyrrolizidine alkaloids, allergens, genetically modified organisms, and so on. The food safety risks of pollens are presented in detail in the review article of Végh et al. [8].

There is a tradition of beekeeping in Hungary, as the climatic and landscape conditions of the Carpathian Basin allow the production of high quality honey. Bees visit more than 800 plant species, several of which are suitable for the production of singe flower honey [9]. The two main products of the domestic honey market are mixed flower honey and acacia honey. The latter is considered a hungaricum, as there are large acacia forests in Hungary, and acacia honey is a high quality, sought-after product both at home and abroad [10]. The production of rapeseed and sunflower honey is widespread throughout the country, but smaller amounts of other single flower honeys such as chestnut, linden, phacelia, hawthorn, goldenrod, lavender, buckwheat and milkweed honey are also produced by Hungarian beekeepers. In addition to honey, other apiculture product also add color to the product range of beekeepers, of which one of the most popular is pollen cluster.

Examining export and import data, Mucha et al. proved that Hungary has a comparative advantage in the European Union in terms of honey production [11]. A significant part of the total honey production of the EU comes from Hungary, which, in addition to environmental conditions, is due to the relatively high bee density of the Carpathian Basin. The number of bee colonies is constantly increasing, which also indicates the effectiveness of the National Beekeeping Programs. Nevertheless, it is a serious challenge for the sector that Hungarian honey is behind world competitors in the price competition, especially compared to lower quality honey from China [11, 12]. According to the in-depth interviews of Oravecz and Kovács with consumers, Hungarian honey buyers can be divided into two distinct groups based on where they get their product: some consumers buy only from primary producers, while other look for readily available, cheaper products online or on store shelves [13]. According to the majority of the consumers surveyed, honey from Hungarian producers is not only more reliable, but also tastes better and is healthier than imported honey.

The regulation of honey quality is dealt with in the Hungarian Food Codex (Codex Alimentarius Hungaricus): specification 1-3-2001/110 contains the definitions and compositional requirements of honeys, guideline 2-100 the requirements and characteristics of honey types with a distinctive quality mark, while guideline 3-2-2009/1 the sampling and analytical methods of honey [1, 14, 15]. The Hungarian Food Codex does not cover the quality requirements of other apiculture products. There are currently no specific regulations for pollen clusters at the international level, however, product standardization was initiated by one of the working groups of the International Organization for Standardization, Technical Committee Food Products, Subcommittee Bee Products (ISO/TC34/SC19/WG 3) in 2018 [16].

The nutritional value and organoleptic properties of honeys and pollen are mainly determined by the botanical origin, but are also influenced by the geographical origin, the climatic conditions of the collection area, the bee species producing the product, as well as the processing and storage conditions [2, 3, 5, 9, 17]. In our research, domestic and foreign honeys of different plant origin were compared, based on their moisture, reducing sugar, ash, free amino acid and hydroxymethylfurfural (HMF) contents and pH. Our work also included the study of the macronutrient composition of pollen clusters from plants typical of the Hungarian flora. The color of honey and pollen samples was also investigated, as this property plays an extremely important role in the consumer perception of foods and in consumer decisions [6, 18].

3. Materials and methods

3.1 Samples examined

The products involved in the study included eight honey from Hungary and eight honeys from abroad. The plants indicated as the nectar sources of the Hungarian honeys were acacia, linden, chestnut, goldenrod, rapeseed and phacelia, and a forest (honeydew) honey and a mixed flower honey were also included in the study. The foreign samples included products that are considered specialties in Hungary such as thyme (Spain), wild lavender (Portugal), coriander (Bulgaria), buckwheat (EU), larch (Czech Republic), coffee flower (Guatemala) and orange blossom honey (Mexico), and a mixed flower honey from Ghana. These products were purchased in a specialty store in Budapest, while the mixed flower honey from Ghana was obtained from the market in the country of origin. The pollen clusters used in the study were purchased from Hungarian beekeepers and stores. The products were dried at 38±2 °C for 20 hours, and then ten subsamples were formed by color sorting and their botanical composition was determined. Honey and pollen samples were stored at room temperature (20±2 °C) in the dark.

3.2 Methods used

An Abbe refractometer was used to determine the moisture content of the honeys [19]. Reducing sugar content was determined by the Schoorl-Regenbogen method [20], while ash content was determined by incineration [21]. The determination of the free amino acid content was carried out with an INGOS AAA 400 amino acid analyzer. HMF content was measured by the method of White [22, 23]. to determine the pH value of the honeys, a Radelkis universal pH meter (OP-204/1) was used [24]. The botanical origin of the pollen clusters was determined by microscopic pollen analysis. Moisture content of the samples was analyzed by the vacuum drying method [25]. To determine the protein content, the classical Kjeldahl method was used. Crude fat content was determined by Soxhlet extraction [25]. Ash content was determined by incineration [26], while the following formula was used to calculate the carbohydrate content:

Carbohydrate(%) = 100 - Moisture(%) - Protein(%) - Raw fat(%) - Ash(%)

Color characteristics of the honeys and pollen were examined with a Minolta CR-100 instrument. The results are expressed with the coordinates of the CIE-Lab color space, where „L” is the perceptual lightness, while „a*” and „b*” are values for red-green and blue-yellow colors respectively. Each analysis was carried out in three parallel measurements.

4. Results and evaluation

4.1 Honey test results

4.1.1. Moisture content

Moisture content is one of the most basic parameters determining the quality of honey, which affects the viscosity, color, taste and crystallization of the product, as well as significantly affecting its shelf life. The moisture content of honeys generally varies between 15 and 21%, depending on the species of the source plant, the dehydration processes taking place in the hive and the way the honey is processed and stored [17]. Honeys produced in a dry, warm environment generally have a lower moisture content than those coming from countries with cool, humid climates [27]. According to specification 1-3-2001/110 of the Hungarian Food Codex, the moisture content of honeys must not exceed 20% [1].

The moisture content of the honey samples examined by us ranged from 17.5 to 21.8% (Figure 1). Of the honeys originating from Hungary, the moisture content of rapeseed honey and mixed flower honey, and of the foreign honeys, the moisture content of buckwheat honey exceeded the current limit value in Hungary. According to Czipa et al., a moisture content above the permissible limit indicates that the bees were not able to thicken he honey properly due to heavy carrying, so these honeys should be considered immature [28]. However, the water absorption capacity of the honeys is also influenced by their botanical origin, so the high moisture content of buckwheat honey may be traced back to this.

4.1.2. Reducing sugar content

Approximately 95% of the dry matter content of honey consists of carbohydrates, of which simple reducing sugars are present in high concentrations: fructose accounts for 32-44% of the weight of honey, while glucose accounts for 23-38% [29]. The fructose and glucose present in honey are derived from the sucrose content of the nectar through the action of the enzyme invertase produced by the bees [2, 9]. According to the Hungarian Food Codex, flower honeys must have a fructose and glucose content of at least 60%, while forest (honeydew) honeys at least 45% [1]. Smaller amounts of various disaccharides, oligosaccharides and polysaccharides may also be present in the products. Lower reducing sugar and higher sucrose contents may be characteristic of the plant, but may also indicate the immaturity of the honey or the feeding of bees with sugar syrup [28, 29].

The reducing sugar content of the samples examined by us ranged from 64.50 to 75.25% (Figure 2). Foreign samples contained 3% more reducing sugars than Hungarian honeys on average. The highest value was obtained for wild lavender honey, while the lowest was obtained for forest (honeydew) honey. According to literature data, it is a special feature of honeydew honeys that they contain higher proportions of complex sugars, mainly raffinose and melezitose, than honeys made from flower nectar [30].

4.1.3. Ash content

According to literature data, the ash content of honeys of nectar origin is generally between 0.02 and 0.3%, while forest (honeydew) honeys contain inorganic substances in a concentration of about 1% [29]. The amount of minerals depends on the geographical and botanical origin of the honey, the composition of the soil and the extent of contamination in the vicinity of the source plant, so honey can also be considered an environmental bioindicator [31]. According to research, the ash content of dark-colored honeys is generally higher than that of lighter honeys [17, 32]. Our results (Figure 3), in line with literature data, showed that forest honey contains an outstanding amount (0.97%) of minerals. Of honeys of nectar origin, larch, goldenrod and linden had an ash content of more than 0.3%. Acacia, rapeseed, phacelia, mixed flower from Ghana, thyme and orange blossom honeys on the other hand had relatively low levels of inorganic matter, less than 0.1%. No close correlation was observed between the color and ash content of the products. The forest, larch and goldenrod honeys with the highest ash content were dark in color, but linden and chestnut honeys, despite their high mineral content, were characterized by a light color. Buckwheat honey and the mixed flower honey from Ghana had a very dark color and a low ash content.

4.1.4. Amino acid composition

Some of the amino acid content of honeys comes from the nectar or the pollen, according to which the amino acid composition may be an indicator of botanical origin [29, 33, 34]. Nevertheless, free amino acids also enter honey as a result of bee secretion processes, which increases the variability in the amino acid content of honeys from the same source plant [35]. The amino acid composition of nectar, and thus of honey, is also affected by the time of the year it is collected by the bees: in spring, when the trees are budding, and in autumn, when the color of the leaves changes, the concentration of amino acids and nitrogen containing compounds in the phloem increases significantly [36]. The variability of the amino acid content of the same type of honey is also increased by the fact that their amount decreases during storage [37] and upon heat treatment [38].

Most amino acids are present in honey in bound form. The free amino acid content accounts for approximately one-fifth of the total amino acid content [29]. Proline makes up 50-85% of the amino acids present, the amount of which decreases continuously during storage, so it can also be an indicator of the aging of honey [39]. Some of the proline enters the honey due to secretion processes in the bees [9], while another part is of plant origin, as both nectar [40] and pollen [5] have a high proline content. There is no clear regulation of its amount in Hungary, so the minimum limit value of 180 mg/kg in force in Germany is generally taken into account [39].

The average free amino acid concentration in the honeys studied by us was 663.3 mg/kg. Foreign honeys had a slightly higher average amino acid content (787.6 mg/kg) than products from Hungary (539.0 mg/kg). The concentration of free amino acids in coriander, wild lavender and goldenrod honey exceeded 1,000 mg/kg, while in acacia honey only 162.2 mg/kg was detected (Table 1). Research has sown that acacia honeys are generally characterized by a relatively low amino acid content [33, 41]. The high amino acid content of goldenrod honey can be traced to the fact that the flowering period of the plant can last from August to the end of October.

The amount of proline was remarkably high in all samples. In addition, most honeys had relatively high levels of aspartic acid, glutamic acid, asparagine, glutamine and phenylalanine. Relatively high levels of serine, alanine, valine and tyrosine were observed in some samples. Buckwheat honey had extremely high methionine, threonine and valine contents, while wild lavender honey had outstanding amounts of phenylalanine, tyrosine and arginine.

*Mixed flower honey, Hungary
** Mixed flower honey, Ghana

Figure 4 shows the ratio of proline to the amount of total free amino acids. According to Hermosín, proline accounts for at least two-thirds of the amino acid content of fresh honey [34]. Half of the honeys examined by us showed a lower proline ratio. Of domestic honeys, the proline ratio was 56% in mixed flower honey, while it was less than 66% in all foreign honeys, with the exception of coriander honey. Average proline content values were determined by Kaskoniené and Venskutonis for single-flower honeys of great economic importance in Europe, taking into account hundreds of test results per variety. Based on their results, thyme (Thymus spp.) honeys have an outstanding proline content (956±196 mg/kg), however, the thyme honey examined by us contained relatively little proline [33]. The average proline content of acacia (Robinia pseudacacia L.) honeys was approximately twice the value detected by us. Linden (Tilia spp.), chestnut (Castanea sativa Miller) and forest (honeydew) honeys had on average 20-30% proline contents than the samples examined by us. Concentrations similar to those reported by the authors were obtained by us for rapeseed (Brassica napus L.) honey. Of the honey samples, coriander honey had the highest proline content (943.8 mg/kg), but this was significantly lower than the value (2,283 mg/kg) reported by Czipa [9]. The differences are presumably due to the longer storage time. With the exception of the acacia honey, the mixed flower honey from Ghana and the coffee flower honey, all products complied with the minimum value of 180 mg/kg required in Germany.

4.1.5. Hydroxymethylfurfural content

Hydroxymethylfurfural (HMF) is formed in an acidic medium by the decomposition of hexoses. The maturity of honey can be inferred from its concentration, since this compound is present in minimal amounts in fresh honey. HMF content increases during the heating and storage of honey, but high acid, moisture and sugar contents also accelerate its formation [9, 29]. Its concentration also depends on the type of honey: tropical and subtropical honeys from warm environments have inherently high HMF content [27]. Specification 1-3-2001/110 of the Hungarian Food Codex prescribes a limit of 40 mg/kg for honeys in general, while the limit value is 80 mg/kg for honeys of tropical origin [1].

The HMF content of the honeys examined by us varied widely (Figure 5): its concentration was only 3.98 mg/kg in acacia honey, while the mixed flower honey from Ghana had an extremely high HMF content (140.42 mg/kg). All honeys from Hungary complied with the limit value in force. Of foreign honeys, the mixed flower honey from Ghana significantly exceeded the limit set for tropical honeys. According to its tropical origin, the coffee flower honey from Guatemala can also be characterized by a high HMF content (64.41 mg/kg).

4.1.6. pH

The pH of honeys is usually below 6, mainly due to the organic acids found in them. The amount of organic acids is less than 0.5%, but they significantly affect the color, aroma and shelf life of the product. Certain acids (e.g., citric acid, malic acid, oxalic acid) come from nectar and honeydew, while others (e.g., formic acid) are formed by enzymatic processes during maturation and storage [29]. A significant proportion of the organic acids in honey is gluconic acid, which is formed from glucose by the enzyme glucose oxidase. The pH of honey does not depend directly on the amount of organic acids, which is mainly due to the honey components with buffer capacity [9].

The pH of the honey samples examined by us varied between 2.85±0.02 and 4.60±0.04 (Figure 6). The lowest value was obtained for phacelia honey, while the highest value was measured for forest (honeydew) honey. Our results support the finding of Tischer Seraglio et al. that the pH of honeydew honeys is relatively high, generally between 3.8 and 4.6 [30]. This is due to the fact that the minerals and amino acids in them buffer the acidic pH [9].

4.1.7. Color characteristics

The color of honey is an important organoleptic parameter, as it significantly influences consumer decisions. In most countries, high quality is associated with light honey, but in Germany, Switzerland and Greece, for example, darker products are more popular. Honey ranges in color from colorless to dark amber, sometimes with a greenish or reddish tinge. The color of honey is influenced, for example, by the plant and geographical origin, climatic conditions, soil condition of the source plant, storage time, exposure to light, possible heat treatment, certain enzymatic reactions and crystallization processes [17, 29]. This property is related to, among other things, moisture content and the concentrations of minerals, carotenoids, phenolic compounds and sugars [18].

The values of L (brightness), a* (green-red color) and b* (blue-yellow color) obtained for the honeys examined by us were plotted on a three-dimensional diagram (Figure 7). The darkest samples were the buckwheat honey and the mixed flower honey from Ghana, while the lightest were the acacia, linden and phacelia honeys. Based on the a* value, most of the honeys were more or less reddish in color, but the acacia, linden and phacelia honeys exhibited a very slight greenish hue. In several cases, an inverse relationship was observed between the lightness value and HMF content of the honeys: goldenrod honey, forest honey and the mixed flower honey from Ghana were characterized by relatively low L values and high HMF content, while the lightest honeys had low HMF content. The reason for this is that some of the HMF is formed during the Maillard reaction [9, 17].

4.2. Test results of pollen clusters

4.2.1. Botanical origin

The results of the microscopic pollen analysis confirmed that the pollen clusters used in the research had a lead pollen content of more than 80%, i.e. they could be considered monofloral [42]. The pollen cluster samples are shown in Figure 8, and their pollen composition is summarized in Table 2.

4.2.2. Macronutrient composition

The nutritional value of the pollen clusters showed great heterogeneity, as the proportion of nutrients is significantly influenced by the botanical origin. Summarizing the results of more than one hundred scientific studies, Thakur and Nanda concluded that the products contained an average of 54.2% (18.5-84.3%) carbohydrates, 21.3% (4.5-40.7%) protein, 5.3% (0.4-13.5%) lipid and 2.9% (0.5-7.8%) ash [5]. Their moisture content in the fresh state was between 20 and 30%. Dried products, in an optimal case, contained 4-8% water, as this range is suitable from both a food safety and organoleptic point of view [43].

The pollen clusters analyzed had a moisture content between 4.9 and 8.2%, which ensures adequate microbiological stability. The carbohydrate content of our samples was on average 12% higher than the average value reported by Thakur and Nanda [5]. The difference is mainly due to the fact that, when examining the average concentration, the authors took into account the results obtained not only for dried but also fresh pollen. The protein content of the samples ranged from 14.5 to 26.7%. The most protein-rich pollen clusters came from phacelia and rapeseed, which are strong attractants for bees [43]. In terms of crude fat content, dandelion pollen, also preferred by bees, exhibited outstanding concentrations, but rapeseed pollen was also found to be rich in lipids. The ash content of the pollen clusters ranged from 1.0 to 3.2%. The most minerals were contained in the samples from musk thistle and cherry. Our results (Table 3) are consistent with literature data [5, 42].

4.2.3. Color characteristics

The color of pollen clusters from different plants varies widely: they are most often yellowish and orange in color, but there are also blue, green, red, black, brown and white pollens [44]. The color of pollens is primarily determined by their botanical origin. Since bees usually collect pollen from a single plant species at a given time, each pollen cluster can be characterized by a homogeneous color [4]. The color characteristics of the product are also affected by the geographical origin, climatic conditions, the time of collection, the age and nutrient supply of the source plant, the preservation method of the pollen, as well as the duration and conditions of storage [6].

The values of L (brightness), a* (green-red hue) and b* (blue-yellow hue) obtained for the pollen clusters are shown in Figure 9. The darkest samples were musk thistle, phacelia and common poppy, the other samples had relatively high L values. The light samples can be divided into three groups based on their a* values: rapeseed, cherry and blackberry pollens had a slight greenish tinge, old man’s beard was slightly reddish, while rockrose, sunflower and dandelion exhibited a stronger reddish hue. The value of b* was positive in all cases, indicating that the yellow color dominated in the samples. Phacelia pollen, which is relatively common in the domestic market, is strikingly dark in color. This pollen is characterized by a lighter shade of yellow compared to the also dark common poppy, and a weaker shade of red compared to the musk thistle.

5. Summary

In the course of our research, domestic and foreign honeys were compared on the basis of the parameters determining their quality, and the macronutrient composition and color characteristics of several pollen clusters from the plants characteristic of the flora of the Carpathian Basin were also determined. Of the honeys examined, the moisture content of two Hungarian and one foreign sample exceeded the limit value in force in Hungary. The reducing sugar content of the honeys ranged from 64.5 to 75.3%. Our results support the observation that honeydew honeys have a lower reducing sugar content, a higher ash content and pH, and can be characterized by a darker color than nectar-derived honeys. Proline was the dominant amino acid in the honeys, but its proportion was lower in several cases than the values reported in the literature. Of domestic honeys, the proline content of acacia honey and mixed flower honey did not reach the minimum limit of 180 mg/kg, while in the case of foreign honeys, the same was true for the coffee flower honey. In terms of the HMF content, large differences were observed. All of the domestic honeys met the requirements, but the mixed flower honey from Ghana contained an extremely high concentration of this compound. The color yellow dominated the honeys. Most of the products could be characterized by a reddish hue, but some of the honey samples had a slightly greenish tinge. In several cases, an inverse relationship was observed between the brightness value and the HMF content of the honeys.

By examining the botanical composition of the dried pollen clusters included in the study, it was confirmed that least 80% of the samples used were from the plant species named as the source plant. In line with literature data, the products contained 57.9-74.0% carbohydrates, 14.5-26.7% protein, 1.4-10.5% cruse fat and 1.0-3.2% ash. Their moisture content ranged from 4.9 to 8.2%, which meets the requirements from both an organoleptic and microbiological point of view. In terms of their color characteristics, the products exhibited great variation, but in most cases the yellow hue dominated their color.

6. Acknowledgment

Kutatásunk az EFOP-3.6.3-VEKOP-16-2017-00005 projekt, valamint az „OTKA” Fiatal kutatói kiválósági program (FK_20, azonosítószám 135700) segítségével valósult meg. A szerzők köszönik Rőzséné dr. Büki Etelka segítségét a virágporcsomók botanikai eredetének meghatározásában.

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DOI: https://doi.org/10.52091/EVIK-2021/3-4-ENG

Received: 2020. November – Accepted: 2021. March

¹ South Ural State University (national research university), Chelyabinsk, Russian Federation

Keywords

semi-finished products from meat of broiler chickens, freeze-dried ground apples, Brazil nuts

2. Introduction

Poultry meat is a dietary product with a high content of easily digestible proteins, low content of fat and cholesterol, it costs less than other meat, takes little time to cook and suits well for daily consumption [1]. However, today consumers tend to prefer “healthy” products, which makes producers expand the range of foods enriched with nutrients. This explains the relevance of using plant-based natural additives in meat processing industry, because they improve the quality characteristics of raw meat, and also increase nutritional and biological value of finished products [2].

It is a known fact that apple powder is rich in vitamins, organic and phenol carboxylic acids, monosaccharides, pectins, and dietary fiber, while the Brazil nut is considered a great source of complete protein, such mineral nutrients as Se, Cu, Mn, I, and fatty acids [3, 4, 5, 6, 7]. That is why, these plant raw materials are separately used in cakes, bread, chocolate, cutlets, curd cheese, cereal bars, nut and seed butters [8, 9, 10, 11, 12, 13, 14] to increase their nutrient density. The aim of our research was to study the possibility of combined use of freeze-dried ground apples and Brazil nut kernels in the technology of stuffed meat products with increased nutritional value.

3. Materials and methods

The following was used as materials of the research:

• Chilled broiler chicken legs manufactured by OAO Turbaslinskiye Broilery (Republic of Bashkortostan, Blagoveshchensk) in accordance with GOST 31962-13;
• Freeze-dried ground apples manufactured by PAO Sibirskiy Gostinets (Pskov Region, Moglino) in accordance with TU 10.39.25-001-34457722-18;
• Kernels of Brazil nuts of Bolivian origin manufactured by OOO Komservis (Moscow Region, Mytishchi) in accordance with TU 9760-002-76440635-16;
• Letniy Sad food additive manufactured by OOO Kulmbakh-D (Moscow Region, Krasnoarmeysk) in accordance with TU 10.89.19-008-58251238-20. Ingredients: dill, garlic, mustard, table salt, maltodextrin, dextrose, E621, dill extract, caraway extract, E100;
• Chicken pockets with butter and herbs cooked according to TU 9214-013-64474310-12 by way of baking stuffed broiler chicken legs at 200 ˚C for 20 minutes.

Control samples were cooked according to a traditional recipe (Table 1), test samples were cooked adding 7% dried ground apples, 5% crushed Brazil nut kernels and 4% less butter.

The dosages of the plant raw materials were chosen taking into account the known data published in a number of scientific papers [8, 9, 10, 11, 12, 13, 14] The test samples of chicken pockets were cooked using deboned chicken legs with skin, flat in shape, with a longitudinal cut in the form of a pocket filled with butter, mixed herbs, ground dried apples, and Brazil nut kernels. The cut was joined with skewers.

The plant raw materials were tested for the content of protein and fat according to MU 4237-86, sugar – GOST 8756.13-87, table salt – GOST 15113.7-77, starch – using standard approach [15]. The meat and meat products were tested for protein according to GOST 25011-2017, fat – GOST 23042-2015, moisture – GOST 9793-2016, table salt – GOST 9957-2015. Sensory evaluation of the laboratory samples was carried out according to GOST 9959-2015. The content of dietary fiber in all samples was determined using the traditional approach [15], content of organic acids – according to М 04-47-12, mineral elements – using iCAP 7200 DUO emission spectrometer.

All measurements were carried out in three replications. Statistical analysis was performed using Microsoft Excel XP and Statistica 8.0 software package. The statistical error of the data did not exceed 5% (at 95% confidence level).

4. Results and discussions

Analyzing the nutritional composition of the non-traditional plant raw materials in comparison with poultry meat (Table 2), it was found that Brazil nut kernels contained a relatively high amount of lipids (11 times more), which made it possible to reduce the amount of butter in the recipe, and hence to decrease cholesterol content in the test samples.

Apple powder proved to have relatively high levels of sugars, dietary fiber, and organic acids, in comparison with both raw meat and other plant components. It is well known that non-volatile acids in fruits not only determine taste and aroma of finished products, but also contribute to the production of gastric juice and have a choleretic effect [16], while insoluble (lignin, cellulose, chitin) and soluble (pectin, inulin) dietary fiber is able to effectively bind heavy metal ions and organic substances [17]. All these factors a priori suggest that this new component in the chicken pockets recipe should have a positive effect on the human organism.

The amino acid content in Letniy Sad food additive was due to sodium glutamate (E621) in its composition, while the presence of table salt at the level of 34.9 ± 2.2% allowed not to introduce any more of it.

The mineral composition of all plant components turned out to be richer than that of broiler chicken legs in terms of the number of elements (Table 3). In terms of the content of micronutrients, which have great physiological importance for the human organism, the Brazil nut contained 12 times more Ca, 7.4 times more Fe, 7.2 times more Se, 6.3 times more Mg, 3.6 times more P and Zn, but the Cu, Mn and Co content were also higher than in the poultry meat. Similarly, the dried ground apple powder contained 2.4 time more Fe, 2 times more Ca and 2.7 times more Si, additionally it’s Ag, Au, B, Be, Cu, Ga, Mn, Mo contain were also higher, than the content of poultry meat. Considering 0.5% dosage of Letniy Sad food additive as per the recipe, its contribution to the total mineral value of ready chicken pockets can be considered significant only in terms of Na content, which was 38 times more than in raw meat.

The levels of heavy metals in nuts – As, Cd, Pb, not found in semi-finished meat products, did not exceed the regulated norms of TR CU 021/2011.

Chilled chicken legs had a relatively high content of K, Si, as well as Na.

Thus, it was proved efficient to use such plant components in the technology of baked meat products in order to increase their nutritional value.

Tasting of the laboratory samples of chicken pockets established that apple and nut raw materials in the specified ratio had a positive effect on the consumer characteristics of the product. At the same time, the control sample did not have outstanding taste and aromatic properties, with creamy tones predominant, leveling the characteristics of a meat product. The mixture of the plant materials accounted for the formation of apple and nut notes in the smell and a slight sour-sweet tone in the taste of the products. The color on the cut acquired a caramel shade. The appearance, consistency, and juiciness of all samples were consistently high.

When testing physical and chemical indicators, it was found that the samples under study did not differ significantly in moisture, fat, and sodium chloride content (Table 4). However, the test samples contained slightly more protein (by 2.1 %), as well as dietary fiber and organic acids, which is a benefit from the standpoint of modern nutritional science.

The study of the mineral composition of the laboratory samples revealed that the test samples exceeded the control ones in terms of the amount of most macro- and microelements (Figures 1, 2). Specifically, as for macronutrients, baked samples with a modified recipe contained more Ca (1.7 times), Mg (35.4 %), and P (20 %); as for microelements – more Mo (473 times), Au (132 times), Cu (56 times), B and Mn (28 times), W (20 times), Be (17 times), Sn (15.8 times), Fe and Ti (1.5-1.6 times), Se (1.4 times), Zn (23.1 %), etc.

Furthermore, the amounts of microelements established according to MR 2.3.1.2432-08 satisfy the daily demand of an adult in Mo by 30.4 %, Cu - by 4.3%, Mn - by 2.1 % if one eats 100 g of baked poultry meat products with the added apple powder and Brazil nut.

Minerals are essential for the human body. They are a part of tissues, hormones, enzymes, intracellular fluid. They are needed for the formation of blood and bone cells, functioning of the nervous system, regulation of muscle tone, processes of energy generation, growth and recovery of the body [18, 19].

5. Conclusions

The nutrient composition of the raw materials and finished products was studied. We found that it is possible to use freeze-dried ground apples (in an amount of 7%) and Brazil nut kernels (in an amount of 5 %) together in the recipe of stuffed meat products. Modifying the recipe for chicken pockets, we obtained a product with improved consumer properties, increased nutrition value, and a decrease in the amount of butter by 4%.

6. Acknowledgement

The work was supported by Act 211 of the Government of the Russian Federation, contract № 02.A03.21.0011.

7. References

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[5] Kantoroeva, A. K. (2019): Analysis of the development of the world market for nut crops. Economics and Management: Problems, Solutions. 2(3), pp. 147-154.

[6] Klimova, E. V. (2008): Comparative study of total oil content, fatty acid profile, peroxide value, concentration of tocopherol, phytosterol and squalene in the kernels of Brazil nuts, pecans, pine nuts, pistachios and cashews. Food and processing industry. Abstract journal. 2, p. 369.

[7] Martins, M., Klusczcovski, A.M., Scussel, V.M. (2014): In vitro activity of the brazil nut (bertholletia excelsa h. b. k.) oil in aflatoxigenic strains of aspergillus parasiticus. European food research and technology. 239(4), pp. 687-693.

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[13] Patent No. 2706159 RF. Cereal bar for nutrition of those working with harmful compounds of arsenic and phosphorus. Kazan National Research University. Gumerov T. Yu., Gabdukaeva L. Z., Shvink K. Yu. Application dd. 14.05.2019; published 14.11.2019.

[14] Patent No. 2603892 RF. Method for preparing nut-like mass. Rodionova N. S., Popov E. S., Alekseeva T. V., Sokolova O. A., Shakhov A. S. Application dd. 01.07.2015; published 10.12.2016.

[15] Skurikhin, I.M., Tutelyan, V.A. (1998): A guide to the methods of analyzing food quality and safety. Moscow, Brandes, Medicine, p. 342.

[16] Nechaev, A. P., Traubenberg, S. E., Kochetkova, A. A., et al. (2012): Food Chemistry: 5th edition, revised and expanded. – SPb.: Giord, p. 670.

[17] Nikiforova, T. E., Kozlov, V. A., Modina, E. A. (2010): Solvation-coordination mechanism of sorption of heavy metal ions by cellulose-containing sorbent from aqueous media. Chemistry of plant raw material. 4, pp. 23-30.

[18] Dydykina, I. S., Dydykina, P. S., Alekseyeva, O. G. (2013): Trace elements (copper, manganese, zinc, boron) and healthy bone: prevention and treatment of osteopenia and osteoporosis. Effective Pharmacotherapy. 38, pp. 42-49.

[19] Krutenko, V. V. (2013): A close look at the role of gold trace element in the human body. Bulletin of problems of biology and medicine. 2(3), pp. 19-24.

DOI: https://doi.org/10.52091/JFI-2021/1-3-ENG

Received: 2020. September – Accepted: 2020. December

¹ Széchenyi István University, Faculty of Food and Agricultural Sciences, Department of Food Science, Mosonmagyaróvár, Hungary

Keywords

yogurt making, microwave irradiation, fruit drying, microbiological parameters, total viable count, yeast count, mold count, Escherichia coli, coliform

2. Introduction and literature review

Milk has been a mainstay in the human diet since the beginning of human history. Its useful ingredients have a beneficial effect on a person’s healthy physical and mental development. The ingredients of milk are physiologically beneficial, one of the outstanding features being its high calcium content, therefore it plays a role in the bone formation of developing organisms [1], and it also contains proteins that are important and easy to use for the body. Due to all these properties, dairy products can be considered as staple foods in the human diet. In the food industry, the milk of many farm animals (sheep, goats, cattle) is processed, but in Hungary cow’s milk is consumed in the largest amount.

Yogurt is a dairy product consumed all over the world. Nutrition science professionals believe that this sour milk product has a high nutritional value (a significant part of its lactose content is broken down during fermentation and it has a significant concentration of Ca++) and beneficial bioactive effects (prebiotic ingredients and probiotic bacteria). Natural yogurt is made by adding lactic acid bacteria that induce lactic acid fermentation in the culture medium during their basic physiological activities. Of all products manufactured from milk, yogurt is the most popular worldwide [2].

In the case of fruit yogurt, when dried fruit or dried pieces are added to the yogurt, the dried products tend to absorb some of the free water in the yogurt gel, thus helping to separate the whey of the product during storage [3]. It is also an advantage of adding fruit that, according to some studies [4], the addition of 10 v/v% of fruit significantly improves the physico-chemical properties of the product. The interior of healthy plant tissues does not contain microorganisms, so the primary microbiota of plant raw materials comes mainly from the soil, water, air and, occasionally, from insects or animals. Plant parts developing in the soil (tubers, roots) and in the vicinity of the soil are usually heavily contaminated, their microflora composition is practically identical to that of the soil. Microorganisms are present on fruit surfaces in the amount of roughly 10³ to 10⁵ CFU/g, a significant part of which are lactic acid and acetic acid bacteria. However, the largest part of the microbiota is made up of yeasts, the most common of which are Hensaniaspora, Torulaspora, Pichia, Saccharomyces, Candida and Rhodotorula species. Common spoilage microorganisms in fruits include Alternaria, Aspergillus, Fusarium, Monilia and Mucor species. Fruits are excellent culture media for molds, including many mycotoxin-producing ones. Contamination of the raw material and improper storage conditions often also allow the formation of toxic metabolites. For example, patulin, a toxic substance (mycotoxin) produced by Aspergillus and Penicillum fungi, can be detected in moldy fruits (mainly apples and pears) [5].

During the technological processing of fruits, cutting, slicing, chopping and peeling increase the likelihood of cross-contamination from other materials, tools and equipment at different stages of production. In addition, the increased availability of sugars and other nutrients in minimally processed fruits contributes to the change in the microbiota and increases its population [6, 7]. The main factors in the microbiota of the raw material are the hygiene of the surface of the materials used in the production and the processing equipment, as well as the hygiene of the production environment and the food handlers, which determine the microbiological quality and safety of the final product [8, 9, 10]. The authors of a study on minimally processed plant-based foods detected high total aerobic microorganism counts on food contact surfaces, especially on peelers, knives and cutting boards [10]. The same researchers also reported high levels of facultative anaerobic bacteria of the Enterobacteriaceae family on cutting tables and cutting boards [10]. Although washing and other decontamination procedures are used in the manufacturing processes of all processing plants, it is still difficult to achieve a significant reduction in microbial contamination [11]. Favorable conditions for the growth of microorganisms present in fruits and vegetables can also develop during the packaging and storage periods. Lehto et al. discovered a large number of aerobic microorganisms in surface sampling of vegetable processing plants on devices and equipment in contact with already cleaned vegetables, as well as in the air space of storage, processing and packaging rooms [10].

In the food industry, heat treatment processes are the most important determinants of food safety. Heat treatment of milk is necessary to guarantee its microbiological safety by killing pathogenic microorganisms in milk. Several heat treatment methods are used in the food industry. The efficiency of the heat treatment is ensured by strictly defined temperatures and holding times. In addition to the raw materials of the products, it is also important to ensure the appropriate microbiological properties of the additives. „Heat treatment is an operation related to the warming or heating of milk, cream, etc., the objective of which is to reduce the number of or destroy microorganisms” [12]. Heat treatment during milk processing is a general technological step aimed at improving the shelf life of milk by inactivating microorganisms and enzymes. The use of a raw material with a favorable microbiological condition can also improve the texture quality of certain dairy products, such as yogurt [13].

Microwave technology as a heat treatment process is primarily used in households. In the food industry, it can currently only be used reliably in certain areas. The reason for this is that heat transfer is uneven in microwave equipment, and underheated or overheated places develop in the product. In the case of liquids flowing in a pipe, e.g., when treating milk with microwave energy, this can be avoided [5]. where this technique can be used, it is an advantage, as the time of treatments applied to foods can be reduced, thus making the technique economical. In addition to cost-effectiveness, an additional advantage is that the directions of heat and material transport are the same, so that a dry crust that prevents flow is not formed [14]. Areas of application include drying, thawing of frozen meat, tempering, pasteurization, sterilization and prevention of food discoloration [15, 16].

Sterilizing and antimicrobial effects are also attributed to microwave radiation. In Pozar’s experiments [17], this effect could be achieved using a frequency of 2,450 MHz, and in some cases even using a frequency of 915 MHz. Radiation increases the shelf life of foods by killing the microbes in the food and/or inhibiting their growth.

The effect of microwave radiation on microbes has been investigated in a wide variety of foods and food raw materials, especially in meats. The spreading of microwave pasteurization [18] has been facilitated by the fact that its use in foods does not cause significant damage, as opposed to traditional heat transfer methods. The reason for this is the short heat treatment and irradiation times [19, 20].

Compared to the microwave treatment technology, drying is a more traditional method, the essence of which is the extraction of most of the water content from the fruit, less often, from the vegetable, by gentle heat transfer, which leaves behind an intensely flavored concentrate of significantly lower weight and size that the starting material. Thus, microscopic organisms that remain on the dried fruit lose their viability and ability to reproduce due to a lack of available water. Fresh fruits contain 90 to 95% water, which drops below 15% after drying. In this way, spoilage caused by bacteria and molds can be prevented while retaining certain nutrients, roughage and minerals, such as iron. Compared to fresh fruits, dried fruits contain a lot of carbohydrates, fiber and antioxidants, flavonoids, phenolic acids, carotenoids and vitamins in a concentrated form [21, 22].

The food industry produces yogurt products of various compositions, but the technological processes used in their production are almost the same until the inoculation of milk. Milk is usually inoculated with a 2 to 3% starter culture and incubated at 40 to 45 °C. In this temperature range, the desired final acidity is reached in 3 to 4 hours. If a lower temperature (30-37 °C) is used, the operation takes longer (7-8 hours), but in this case excessive acidification of the product can be prevented [23].

The bacterium Streptococcus thermophilus is primarily responsible for the taste, aroma and texture of the yogurt, and is in fact able to ferment pasteurized milk on its own into yogurt, however, in addition to Streptococcus, Lactobacillus bulgaricus is also used for the fermentation to produce the acids that from in the product. S. thermophilus and L. bulgaricus are usually used simultaneously, in a 1:1 ratio, when inoculating the milk (pH 6.6). Their proportion changes as the fermentation progresses [24].

3. Materials and methods

Manufacture of the products

For the manufacture of the products, raw, untreated milk and 2.8% fat UHT drinking milk (Mizo) were used, which were mixed in a 2:1 ratio before making the yogurts. Raw milk was pasteurized on a hot plate at 75 °C for 15 minutes to achieve adequate initial microbiological safety, and then the drinking milk was added. After heat treatment, the temperature of the milk was allowed to drop to 30 °C, it was inoculated with the amount of thermophilic yogurt culture (Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus, YF-L812, Chr. Hansen, France) according to the instructions for use, and then it was stirred for 15 minutes to ensure proper homogeneity. The inoculated milk was dispensed into 2 dl plastic yogurt cups and the cups were placed in a 43 °C thermostat (Binder, Germany), where they were allowed to curdle for 7 hours (pH 4.6). After acid curdling, the fruits treated with the following procedures were mixed into the yogurts.

In our experiment, with the exception of the control sample, two types of heat treatment procedures were used for the fruits, microwave irradiation and a conventional heat treatment method (drying).

The samples prepared in the course of the experiment:

• Sample 1: fruit yogurt with the addition of raw apples (Ny-A)
• Sample 2: fruit yogurt with the addition of raw bananas (Ny-B)
• Sample 3: fruit yogurt with the addition of dried apples (A-A)
• Sample 4: fruit yogurt with the addition of dried bananas (A-B)
• Sample 5: fruit yogurt with the addition of microwave-treated apples (MH-A)
• Sample 6: fruit yogurt with the addition of microwave-treated bananas (MH-B)

Raw fruits were processed in a clean, impeccable condition free of bruises and defective parts, at the optimum degree of ripeness.

For the microwave treatment, a MARS 5 (CEM Corporation, USA) microwave digestion oven was used. Diced raw apples and bananas were placed in the sample holder of the microwave apparatus and subjected to microwave irradiation. The energy transfer program on the device was set to heat the fruits to 55 °C when a power of 800 W with 100% efficiency and with a holding time of 10 minutes was applied, in a total of 15 minutes. Temperature detection and control was performed using a sensor (RTP 300) introduced into the sample holder.

The fruits used in the drying process were cut into pieces of equal size (0.5 cm), so that the drying time would be the same, and then they were placed in a drying apparatus for 24 hours at 55 °C. The dried and microwave-treated fruits were then ground. The knives and the grinder were treated with Mikrozid disinfectant before use. 5 grams each of the ground fruits were added to 150 ml of the already prepared yogurt samples. Until further analysis, the yogurt-dried fruit mixtures were stored in a refrigerator at 4 °C.

3.2. Product shelf-life analysis

The product were tested for 4 weeks in terms of shelf life. Analyses were carried out on days 0, 7, 14, 21 and 28. Microbiological properties (total viable count, yeast/mold count, E. coli/coliform count) were tested every week from the time of production. The experiment was carried out with 3 parallel measurements (n=3) on each sampling day, i.e., with 15 samples for each original sample (Ny-A; Ny-B, A-A; A-B; MH-A; MH-B), meaning that a total of 90 samples were processed.

A plate pouring method was used to grow the microorganisms. From food safety and technological hygiene point of view, a total viable count of 10⁵/cm³ is the critical limit for raw milk, because normal pasteurization procedures can still be used with sufficient efficiency at this microbe count.

The determination of the total viable count was carried out on a PC (Plate Count, Biolab) medium, with an incubation time of 72 hours at 30±1 °C [25]. By culturing on a selective medium prescribed in standard MSZ ISO 7954:1999 at 25 °C, yeasts and molds form colonies. YGC agar (Yeast Extract Glucose Chloramphenicol Agar, Biolab) was used for their detection, as prescribed by the standard. This selective medium is suitable for isolating and counting yeasts and filamentous fungi from milk and dairy products. Plates were incubated at 25±1 °C for 48 hours, after which the colonies developed on the plates were counted [26].

Co-determination of the coliform count and the E. coli count can be accomplished using CC agar (ChromoCULT Coliform Agar, Biolab). Differentiation between the colonies is aided by the fact that coliform colonies are salmon red, while the color of E. coli colonies ranges from dark blue to violet. Incubation parameters for E. coli/coliform were 24 hours and 35-37 °C [27].

Our measurement results were plotted using Microsoft Office Excel 2016®. During the evaluation of the microbiological results, microbe counts were displayed in a logarithmic form: the slope values of the lines fitted to each point characterize the exponential growth phase of the microorganisms.

4. Results and evaluation

4.1. Test results of the yogurt samples with apples

4.1.1. Total viable count

According to Figure 1, on days 0, 7 and 14 of the measurement, the total viable count showed almost the same results for the yogurt with dried apples and the yogurt with microwave-treated apples. The yogurt with raw apples already showed higher total viable count values in the second measurement (day 7) compared to the other two samples. Here we already saw a significant difference between the cell counts, which difference only increased over time (day 14). In the case of yogurts with microwave-treated apples and dried apples, the rates of increase in cell counts were approximately the same. This result is also supported by the slope values marked in Figure 1a.

4.1.2. Yeast/mold count

Based on Figure 2, it can be concluded that from the first measurement data to the last measurement result, the yogurts with microwave-treated apples and with dried apples showed significantly lower yeast counts than the yogurt with raw apples. There was no difference of the same order of magnitude between samples MH-A and A-A, however, on day 21 of the measurement, there was a clear, significant difference in favor of sample MH-A. Based on this, microwave heat treatment proved to be more effective in inhibiting the activity of yeasts, using the treatment settings applied by us.

In the case of yogurts with apples, it is clear that the microwave technology proved to be the best treatment for both the total viable count and the yeast/mold count. The yogurt with dried fruit exhibited similar cell counts and growth tendencies. However, at the end of the storage time, larger differences between the cell counts developed here. In terms of shelf life, the worst results were obtained for the samples with raw fruit. Differences of an order of magnitude were measured compared to the other two samples, there were significant differences (p≤0.05).

On day 21, at the third sampling time, with the exception of yogurts with microwave-treated apples, yogurts with raw and dried apples were spoiled. After the third measurement, in addition to the high yeast count, a significant mold count was also detected in the yogurts with raw or dried apples. In contrast, in yogurts with microwave-treated apples, no mold colonies could be detected after the third measurement.

For the mold count, under the current regulation [27], the level of compliance (m) is 10² CFU/cm³ for fermented milk, dairy products, sour dairy products, cottage cheese and cottage cheese products, while the rejection limit value (M) is 5*10³ CFU/cm³.

In terms of mold count, the presence of no molds was detected in yogurts with apples during the first two measurements, on days 0 and 7. On day 14 of the experiment, colonies of mold appeared in the samples with raw and dried apples, already with a value above the rejection limit as defined by the regulation in the case of raw apples (3*104 CFU/cm3). However, in the case of the product with dried apples, the number of mold colonies remained at an acceptable level (2.2*10² CFU/cm³) according to the relevant regulations [27].

4.2. Test results of the yogurt samples with bananas

4.2.1. Total viable count

In the case of yogurts with bananas, it was found that the two types of treatment procedures (drying, microwave) also have an effect on the microbial count. In the case of the microwave-treated sample, the increase in the total viable count was not significant until day 21 of the experiment compared to the initial TVC (Figure 3). On the other hand, the total viable count increased from week to week for the yogurts supplemented with raw or dried fruits. In addition, it was also found that the total viable count of the sample supplemented with dried fruit had the highest total viable count, and the most intense increase in the TVC was also observed in this sample. Already on day 7 of the storage experiment, there were significant differences between the test results of the samples, with an order of magnitude difference between sample A-B and samples Ny-B and MH-B. On day 14 of the experiment, orders of magnitude differences were observed between the date of all three samples. In terms of total viable count, the increase in TVC was the lowest in the case of sample MH-B.

4.2.2. Yeast/mold count

Based on the yeast count results (Figure 4), it was found that there was no significant difference between the yogurts with raw and microwave-treated bananas in terms of the colony counts of the samples and the growth trends of the microorganisms. However, yogurts with dried apple were characterized by a rapid increase in cell number, which also affected the organoleptic properties of the product. From day 7 of the experiment, there were already significant differences between samples MH-B and Ny-B and samples A-B and Ny-B. Microwave treatment proved to be the most effective in this case as well.

The evolution of the mold count during the shelf life was examined also in the case of yogurts with bananas. The results showed that during the first two measurements, on days 0 and 7, no mold colonies developed. However, on day 14 of the experiment, molds appeared in an amount of 1.4*10⁴ CFU/cm³ in the sample with dried bananas, a number which well exceeds the compliance limit value according to the regulation (10² CFU/cm³), moreover, it falls into the rejection category (5*10³ CFU/cm³). For the other two samples (raw and microwave-treated bananas), no molds were present on day 14. On day 21 of the experiment, molds also appeared in the yogurt supplemented with raw bananas in an amount of 3.0*10¹ CFU/cm³, which does not yet exceed the compliance limit value. Mold was still not detectable in sample MH-B. On day 28 of the experiment, the mold count of the yogurt with raw bananas also exceeded the rejection limit value by approximately 1 order of magnitude. No mold could be detected in sample MH-B even on day 28.

The results obtained for dried products suggests that the 24-hour drying with a gentle heat treatment did not sufficiently improve the microbiological condition of the materials used. It can be assumed that the hygienic condition of the air flowing through the drying apparatus was also inadequate. We believe that fruits prepared for yogurt products should only be dried in a room and equipment that has impeccable air, and have exhaust and adequate air filtration systems.

4.2.3. E. coli/coliform results of the yogurts

The bacterium Escherichia coli is the most important microbe in the normal intestinal flora, making it a natural component of the digestive system of all warm-blooded animals and humans. It can enter foods from fruits and vegetables if they had not been cleaned thoroughly enough, but it can also be found in raw milk or dairy products made from it.

Under current regulation [28], the compliance level is (m)<1/CFU/cm³ for fermented milk, dairy products, sour dairy products, cottage cheese and cottage cheese products, while the rejection limit value is (M)<10/CFU/cm³.

During the tests carried out on days 0 and 7 of the experiment, no E. coli bacteria were detected in any of the samples prepared by us. However, on day 21 (week 3) of the experiment, the bacterium became detectable in all yogurts except the samples with raw bananas and microwave-treated bananas. By week 4 of the experiment, E. coli also appeared in the yogurt with raw bananas. Thus, by the end of the study, only the yogurt supplemented with microwave-treated bananas met the legal requirements.

Coliform bacteria are found in wetlands, in soil and on the vegetation, and are usually present in large numbers in the feces of warm-blooded animals.

According to the relevant regulation (EüM decree 4/1998 (XI. 11.) – EÜM: former Ministry of Health Affairs), the compliance level is (m)<10 CFU/cm³ for fermented milk, dairy products, sour dairy products, cottage cheese and cottage cheese products, while the rejection limit value is (M)<102 CFU/cm³.

Coliform bacteria were detected in all samples on day 0 of the experiment, however, the compliance limit value was exceeded only by the results of the yogurt samples supplemented with dried fruits. After 1 week, however, coliforms could only be detected in the yogurt with dried bananas. It is likely that the decrease in the pH value of the yogurt prevented the bacteria from growing and surviving.

At week 3 of the experiment, coliform bacteria were detected in the samples supplemented with raw fruits, they were not present in the other samples. In our case, the samples supplemented with raw fruits reached the M value, so after 21 days the products were not suitable for human consumption.

During the microbiological studies, the determination of Salmonella and Staphylococcus aureus was also performed, as required by the regulation. These tests were negative in all cases.

Schnabel et al. infected raw fruits with seven microbial strains (including the E. coli bacterium also tested by us) with a cell count in the 10⁸ order of magnitude. The samples were then treated with microwave-assisted plasma, which reduced the cell count by 4 orders of magnitude already after 5 minutes of treatment. The treatment was performed under non-thermal conditions (at 30 °C), thus excluding the microbicidal effect of the temperature [29].

Picouet et al. showed that microwave treatments had a similar effect on the E. coli O157: H7 and total viable count values, i.e., a 1.01-1.16 log CFU g^-1 decrease was detected. The same treatment parameters greatly affected L. innocua, with population below the detection limit (10 CFU g^-1) in most cases. In apple puree samples, the total viable count remained stable during storage at 5 °C, with a slight increase on day 14 [30]. This trend was also observed during our own measurements. Our results confirm that the objective of our research was achieved, which was to verify the microbicidal and inhibitory effect of microwave treatment.

Our results are also supported by the fact that 5 to 25 seconds of microwave treatment (65 °C, 1200 W, 2.45 GHz) can reduce the Salmonella cell count in vegetables by 4 to 5 orders of magnitude, thus confirming the stronger microbicidal effect of microwave treatment compared to other ones [31].

5. Conclusions and recommendations

When using fruits as flavoring agents in yogurts, two types of heat treatment were applied to increase the shelf life of the products. The effect of the microwave treatment method on shelf life was characterized by the length of shelf life after the addition of conventional and untreated fruits to yogurt.

Based on the microbiological studies, it was found that microwave treatment was the most effective of the various heat treatments. Of the methods of heat treatment of fruits, microwave irradiation resulted in a lower total viable count compared to untreated fruits and drying technology.

Based on our microbiological results, we believe that the contamination or texture of the raw fruit fundamentally influences the effectiveness of the treatment. After microwave treatment of bananas, the presence of E. coli could not be detected in the yogurt by the end of our experiments (day 28), as opposed to the treated apples, where its presence was already detected on day 14. This may be noteworthy because the presence of E. coli was not detected in either case on the day the products were prepared. It can be assumed that microwave irradiation exerted a more intense germicidal effect in the softer texture of bananas than in apples which have a harder consistency.

It was found that the drying procedure is suitable for the production of microbiologically safe food if the microbiological condition of the air circulating in the equipment is also adequate.

Based o our results, it is hypothesized that microwave irradiation technology can be applied successfully to foods, in this case fruits, to inhibit microorganisms living inside and on the surface of fruits.

While in the case of yogurts flavored with apples, the microbiological characteristics of samples with raw fruit were worse, in the case of bananas, the drying technology proved to be the most unfavorable from a microbiological point of view. The most likely reason for this may be that, compared to apples, bananas contain on average three times more carbohydrates which became more concentrated as the result of drying. This high carbohydrate fruit mixed with the yogurt may have served as a culture medium for various microorganisms.

In order to determine whether or not the use of different microwave temperatures (other than 55 °C), power and treatment times would lead to better shelf-life results, further tests are required.

Of the heat treatment procedures, microwave may be suitable both for treating milk, thus reducing the number of microbes, and for reducing the total viable count of the flavoring agents (spices, fruits, vegetables) used.

6. Acknowledgment

This publication was supported by project no. EFOP-3.6.1-16-2016-00024 titled „Developments for intelligent specialization in cooperation between the University of Veterinary Medicine and the Faculty of Agricultural and Food Sciences of Széchenyi István University. The project was supported by the European Union and co-financed by the European Social Fund.

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[30] Picouet, P. A., Landl, A., Abadias, M., Castellari, M., Viñas, I. (2009): Minimal processing of a Granny Smith apple purée by microwave heating, Innovative Food Science and Emerging Technologies 10 (2009) pp. 545-550. https://doi.org/10.1016/j.ifset.2009.05.007

[31] Vega, M., López, S., Malo, L., Morales, S. (2012): Inactivation of Salmonella typhimurium in fresh vegetables using water-assisted microwave heating. Food Control 26 (1) pp. 19-22. https://doi.org/10.1016/j.foodcont.2012.01.002

DOI: https://doi.org/10.52091/JFI-2021/1-4-ENG

Received: June 2020 – Accepted: October 2020

¹ South Ural State University (national research university), Chelyabinsk, Russian Federation

Keywords

mayonnaise sauce, pine nut oil cake, protein concentrate, functional food product, β-carotene

2. Bevezetés

Mayonnaise sauces, like all mayonnaise products, are among the most popular everyday consumer goods. Main components for mayonnaise sauces involve natural products with high biological value and health-promoting properties. In this regard, the development of mayonnaise product formulas can be viewed as a promising line of research [1, 2].

Hydrocolloids and protein-polysaccharide complexes, plant extracts, vitamin and mineral complexes, dietary fiber, polyunsaturated fatty acids and protein concentrates are the most valuable functional ingredients in the production of emulsion foods for particular nutritional uses. These biologically active components allow you to structure a person’s diet in order to improve metabolism, immunity, nervous and endocrine systems, functioning of individual organs and body systems [3, 4].

Currently, protein concentrates are widely used in production of various sauces, pastes, dairy, and confectionery products. Such popularity of protein concentrates is due to the protein deficiency that more than 60% of people suffer from to a varying degree [5].

At the same time, every year scientists all over the world come up with new sources and methods of protein isolation to create new functional foods enriched with protein concentrates. It has been established that regular consumption of such products helps to increase body’s resistance to harmful factors, strengthen immunity, and improve metabolism [6].

Pine nut oil cake, obtained by extracting oil from pine nut kernels, is a secondary raw material, but it is of great importance as an additional source of complete protein, easily digestible carbohydrates, vitamins, and minerals. With the right choice of the method of its extraction and purification, it is possible to obtain a protein-rich concentrate that can be added to various foods in order to give them functional properties.

The composition of the protein of pine nut oil cake is determined by the composition of the protein of the kernels of pine nuts.

The content of essential amino acids in the protein composition of pine nut kernels ranges from 36 to 40%.

The content of some individual essential amino acids in pine nut protein is specific, which is characteristic of all types of plant materials. It should be noted that in terms of amino acid composition, namely, the content of phenylalanine, tyrosine, histidine, tryptophan, arginine, pine nut oil cake protein is as good as the protein of the major grain and oilseed crops. It is close to dairy protein in terms of tryptophan content, surpassing it in terms of arginine and histidine content.

The composition of the lipid fraction of pine nut oil cake is characterized by a quantitative predominance of polyunsaturated fatty acids – linoleic and γ-linolenic –, belonging to the ω-6 family.

The vitamin and mineral value of pine nut oil cake depends both on the initial chemical composition of the processed nut and on the residual oil content in the oil cake after pressing.

Pine nut oil cake has a high content of tocopherols (11.8 mg/100 g of product), thiamine (0.6 mg/100 g of product), and riboflavin (1.83 mg/100 g of product).

Pine nut oil cake is a concentrate of biologically valuable food substances like proteins, lipids, carbohydrates [7].

3. Materials and methods

The following was used as the material for research:

• ground cake of pine nut kernels, produced in accordance with TU 9146-001-53163736-06 (by “Siberian Product”, supplied by “Altai Dar LLC”, Altai Territory, Barnaul, Russia) [14];
• Beta-carotene 30% os, plant-based, liquid, oil-soluble (by “NATEC”, Moscow);
• reference and test samples of mayonnaise sauces.

Organoleptic characteristics of mayonnaises and mayonnaise sauces must comply with the requirements of GOST 31761-2012 “Mayonnaises and mayonnaise sauces. General specifications” [8]. Testing of organoleptic characteristics was carried out at (20±2) °C after at least 12 hours after production.

Organoleptic indicators were determined in the following sequence: texture, appearance, colour, smell, taste.

The mass fraction of protein was determined by the Kjeldahl titration method.

The stability of the emulsion was determined by centrifugation.

The intact emulsion stability was determined by centrifuging the emulsion for 5 minutes at 1500 rpm.

The dynamic viscosity of the samples was determined using “Reostat-2” rotational viscometer (Germany) at 20 ºС.

The degree of oxidative deterioration was determined by the peroxide number of the oil phase using the iodometric method and calculating the degree of oxidative deterioration of the product [9-11].

All measurements were carried out in three replications. Statistical analysis was performed using Microsoft Excel XP and Statistica 8.0 software package. The statistical error of the data did not exceed 5% (at 95% confidence level).

4. Results and discussion

Mayonnaise sauce is a finely dispersed emulsion product with a fat content of not less than 15%, produced from refined deodorized oil, water, with or without dairy by-products, food additives and other food ingredients (GOST 31761-2012 “Mayonnaises and mayonnaise sauces. General specifications”) [8].

The ingredients of the obtained mayonnaise sauce included refined deodorized cooking oil, egg powder, mustard flour, granulated sugar, table salt, 80% acetic acid, as well as a protein concentrate made of pine nut oil cake, natural β-carotene and water. Introducing β-carotene to the formula of the mayonnaise sauce increased the stability of its fatty phase to oxidation and extended its shelf life [12].

The production technology of the functional mayonnaise sauce was based on the “classic” mayonnaise sauce production technology.

The specified amount of water of 35–40 °C (not taking into account the water used to prepare the acetic acid solution) was poured into the mixer with a steam-water jacket. The mixer was turned on, and dry components – granulated sugar, salt, pine nut oil cake – were heated and added to the mixer. The mass was mixed intensively at 70-80 rpm and heated to 80-85 °C for 25-30 minutes. Then, the resulting suspension was cooled to 35-40 °C, egg powder and mustard flour were added, after which the emulsion was heated to 55-60 °C during 15-20 minutes.

After heating, the emulsion was again cooled to 25-30 °C, the number of revolutions was reduced to 30-40 rpm, and oil with pre-dissolved β-carotene was introduced. Following that, after adding acetic acid solution into the sauce, it was subject to stirring for another 3-5 minutes and subsequently homogenized at a pressure of 0.9-2.5 MPa.

The use of pine nut oil cake made it possible to reduce the content of egg products in the sauce formula, to lower the cholesterol, and to increase the protein content in the finished product.

The use of β-carotene in the sauce formula enhanced the color of natural egg products.

The use of pine nut oil cake not only simplified the mayonnaise sauce production process, but also allowed to obtain a colloidal system consisting of finely dispersed particles of cell walls. Intensive mixing ensured a complete interaction of proteins, fats and carbohydrates with other components, which facilitated emulsion stability, as finely dispersed cell walls of pine nut oil cake formed a solid three-dimensional structure, enhancing the emulsifying and stabilizing effect.

Reducing the mass fraction of egg powder in the formula to less than 1% made it difficult to obtain a stable emulsion, which led to a decrease in the viscosity of the finished product. The consistency of the finished product became watery, its organoleptic characteristics were low [13]. Therefore, we chose 1%, 2% and 3% dosages of pine nut oil cake to be introduced instead of egg powder.

Formulas of mayonnaise sauces are given in Table 1.

Test samples of mayonnaise sauces with pine nut oil cake were tested for organoleptic characteristics (Table 2).

The appearance of mayonnaise sauces is shown in Figure 1.

Physical and chemical indicators are given in Table 3.

The use of pine nut oil cake increased the overall protein content in the finished product. Pine nut oil cake is an effective emulsifier, and in combination with a conventional emulsifier – egg powder – ensured a good, smooth consistency of the sauce and high stability of the emulsion. It allowed to obtain a finished product with a viscosity that meets consumer requirements for compatibility with other ingredients of a dish or food systems.

In the next stage of research we studied how the quality of the mayonnaise sauce changed during storage.

Storing the samples at 20 ºC provoked the oxidation without changing the mechanism of the process and violating the colloidal stability of the product. The dynamics of the peroxide number of the oil phase of mayonnaise sauce samples during the storage at 20 ºC is shown in Figure 2.

The oxidation of the samples during storage was caused by exposure to light. When stored for more than four weeks, the peroxide number of the reference sample exceeded the level of 11 mmol of active oxygen/kg, and as for the test samples, it did not reach the level of 6 mmol of active oxygen/kg.

The use of β-carotene (0.2%) in the mayonnaise sauce can significantly increase the oxidation stability of the product without adding a preservative, as well as enrich the mayonnaise with biologically active substances of plant origin.

Based on all types of studies, it can be concluded that 3% was the most preferable dosage of pine nut oil cake in the formula of the mayonnaise sauce.

5. Conclusions

Using pine nut oil cake, which possesses good emulsifying properties, in the amount of 3%, alongside a conventional egg powder emulsifier, increased the viscosity of the finished product, ensured a smooth texture of the sauce and high stability of the emulsion. The use of pine nut oil cake made it possible to reduce the content of egg products in the sauce formula and lower the amount of cholesterol in the finished product. Besides, the introduction of pine nut oil cake to the sauce formula increased its protein content. The use of β-carotene (0.2%) in the mayonnaise sauce can significantly increase the oxidation stability of the product without adding a preservative and enrich the mayonnaise with biologically active substances of plant origin.

Thus, pine nut oil cake obtained by processing kernels of pine nuts is a promising functional additive. This material is a suitable to produce fat emulsions, including the reduced fat content products, due to the protein and carbohydrate content of oil cake, thus can provide the necessary rheological structure for low-fat products too.

6. Acknowledgement

The work was supported by Act 211 of the Government of the Russian Federation, contract № 02.A03.21.0011.

7. References

[1] Chung, C., Degner, B., McClements, D. J. (2014): Development of reduced-calorie foods: Microparticulated whey proteins as fat mimetics in semi-solid food emulsions. Food Research International, 56, pp. 136–145. http://doi.org/10.1016/j.foodres.2013.11.034.

[2] Emadzadeh, B., Ghorani, B. (2015): Oils and fats in texture modification. In J. Chen, A. Rosenthal (Eds.), Modifying food texture pp. 99–112. Woodhead Publishing.

[3] Cheung, I., Gomes, F., Ramsden, R., Roberts, D. G. (2002): Evaluation of fat replacers Avicel™, N Lite S™ and Simplesse™ in mayonnaise. International Journal of Consumer Studies, 26 (1), pp. 27–33. http://doi.org/10.1046/j.1470-6431.2002.00207.x.

[4] Ma, Z., Boye, J. I. (2013): Advances in the design and production of reduced-fat and reduced-cholesterol salad dressing and mayonnaise: A review. Food and Bioprocess Technology, 6 (3), pp. 648–670.

[5] Sikora, M., Badrie, N., Deisingh, A. K., Kowalski, S. (2008): Sauces and Dressings: A Review of Properties and Applications. Critical Reviews in Food Science and Nutrition, 48 (1), pp. 50-77. http://doi.org/10.1080/10408390601079934.

[6] Diftis, N. G., Biliaderis, C. G., Kiosseoglou, V. D. (2005): Rheological properties and stability of model salad dressing emulsions prepared with a dry-heated soybean protein isolate–dextran mixture. Food Hydrocolloids, 19 (6), pp. 1025–1031. http://doi.org/10.1016/j.foodhyd.2005.01.003

[7] Gómez-Ariza, J.L., Arias-Borrego, A., García-Barrera, T. (2006): Multielemental fractionation in pine nuts (Pinus pinea) from different geographic origins by size-exclusion chromatography with UV and inductively coupled plasma mass spectrometry detection. Journal of Chromatography, 1121 (2), pp. 191-199. http://doi.org/10.1016/j.chroma.2006.04.025.

[8] GOST 31761-2012. Mayonnaises and mayonnaise sauces. General specifications. Moscow, 2013. pp. 1-13.

[9] Skurikhin, I.M., Tutelyan, V.A. (1998): A guide to the methods of analyzing food quality and safety. Moscow, Brandes, Medicine, pp. 110–115.

[10] Karas, R., Skvarča, M., Žlender, B. (2002): Sensory quality of standard and light mayonnaise during storage. Food Technology and Biotechnology, 40, pp. 119–127.

[11] Calligaris, S., Manzocco, L., Nicoli, M. C. (2007): Modelling the temperature dependence of oxidation rate in water-in-oil emulsions stored at sub-zero temperatures. Food Chemistry, 101 (3), pp. 1019–1024. http://doi.org/10.1016/j.foodchem.2006.02.056

[12] Cortez, R., Luna-Vital, D. A., Margulis, D., Mejia, E. G. (2017): Natural pigments: stabilization. 6th International Conference on Agriproducts processing and Farming. IOP Conf. Series: Earth and Environmental Science. 422, (20), IOP Publishing. http://doi:10.1088/1755-1315/422/1/012090.

[13] Kishk, Y. F. M., Elsheshetawy, H. E. (2013): Effect of ginger powder on the mayonnaise oxidative stability, rheological measurements, and sensory characteristics. Annals of Agricultural Sciences, 58 (2), pp. 213–220. http://doi.org/10.1016/j.aoas.2013.07.016.

[14] Oil industry by-products. TU catalog. Number: TU 9146-001-53163736-2006. Name: Pine nut kernel cake. Siberian product "; 656055, Altai kr., Barnaul, st. A. Petrova, 1886. http://92.243.65.78/techdocs/kgs/tu/679/info/126955/ (Hozzáférés: 2020. 06. 11.)

DOI: https://doi.org/10.52091/EVIK-2021/2-4-ENG

Submitted: July 2020 – Accepted: December 2020

¹ Hungarian Dairy Research Institute Ltd, Mosonmagyaróvár
² Széchenyi István University, Wittmann Antal Multidisciplinary Doctoral School in Plant, Animal, and Food Sciences, Mosonmagyaróvár
³ Széchenyi István University, Faculty of Agricultural and Food Sciences, Department of Food Science, Mosonmagyaróvár

Keywords

nosocomial infection, Serratia species, Serratia marcescens, pathogen, prodigiosin, pigment, polymerase chain reaction (PCR), food diagnostics

2. Introduction and literature review

Nowadays, the impeccable quality and long shelf life of foods is a basic requirement of consumers. Accordingly, there is a growing demand for ever faster, more accurate and more reliable food diagnostic procedures. In this context, molecular diagnostic methods are gaining ground, for example in the rapid detection of pathogenic microorganisms. Polymerase chain reaction (PCR)-based diagnostic kits suitable for the identification of pathogenic microbes are produced by many manufacturers, and these are also used successfully in Hungarian food testing laboratories. These molecular biological tests are mainly suitable for the detection of microbes hose presence poses a high risk to public health (e.g., Escherichia coli, Salmonella Typhimurium, Listeria spp.). Less attention is paid to pathogens that are not required to be tested by law, such as Serratia species present in raw and pasteurized milk.

Serratia species are found in many places in our environment [1]. They are saprophytes or opportunistic pathogens [2], facultative anaerobic, biofilm-forming organisms [1, 3]. S. marcescens grows particularly well in phosphorus-containing environments (e.g., soaps, shampoos) and is also resistant to certain disinfectants [4, 5], so it can cause various nosocomial diseases [6, 7, 8]. Increasing antibiotic resistance of S. marcescens has also been reported in the literature [8, 9, 10]. The bacterium therefore survives and grows easily, so it may find its way into foods under inadequate hygienic conditions. Presumably, it can enter drinking milk as a result of violating hygiene rules, it can grow there and degrade the quality of food [1, 11, 12]. For some species, spoilage is indicated by a characteristic red hue.

In the case of the Hungarian dairy sector, accurate data are not available on the extent of the prevalence of Serratia species and S. marcescens, and on which species cause the infections and degrade milk quality. Nor is there a Hungarian survey on the extent of Serratia contamination of dairy farms. With the exception of a few publications, the available information on the exposure of the dairy industry to Serratia is also lacking at the international level. Such exceptions are a scientific article on the epidemic of mastitis caused by S. marcescens at Finnish diary farms [1], and an older report discussing the role played by pigment-forming Serratia species in mastitis [13].

The following Serratia species may be responsible for the red discoloration of milk: S. marcescens, S. rubidaea, S. plymuthica and S. nematodiphila (Table 1). According to their incidence, S. marcescens is of greater importance. Their characteristic pigment is the red prodigiosin, a water-insoluble secondary metabolite that is produced under specific environmental conditions [14, 15, 16, 17] (Figure 1). The typical red colonies appearing on the culture medium alone do not provide sufficient information to identify Serratia, as certain species of many other genera, not belonging to Enterobacteria, may also produce prodigiosin [14, 18].

There is currently no ISO standard for the detection of Serratia species in foods. In their 2006 book chapter [9], Grimont and Grimont discuss the characteristics of the genus Serratia, as well as aspects of their isolation and identification. However, identification by classical microbiological methods is rather cumbersome and often ineffective due to the inhibitory effect of the accompanying flora, despite the fact that the pink discoloration of the milk sample is clearly visible to the naked eye. Although culture media are available for the selective growth of the bacterium [47], in practice their use does not provide a satisfactory solution. In addition, conventional methods are time and labor intensive.

There are commercially available rapid methods for the determination of S. marcescens, for example the miniaturized test kit from bioMérieux called Rapid ID 32 E, which satisfies the requirements of standard ISO 7218 [48]. However, a colony growing on a culture medium is required to perform the test. Diagnostic tests based on the PCR method, as mentioned before, could provide a solution to overcome the difficulties of detection. At present, however, only the Genesig product of Primerdesign can be mentioned as a molecular diagnostic kit for the detection of S. marcescens [49].

The literature relevant for the food industry and, in particular, the dairy industry, is rather poor on the detection of Serratia species, including S. marcescens, by either endpoint PCR or real-time PCR methods. Hejazi et al. [50] carried out the serotyping of S. marcescens by the RAPD-PCR technique. Serological samples from patients in need of hospital care were used in their study. Iwaya et al. [6] also tested blood samples for S. marcescens strains using a real-time PCR method. Zhu et al. [51] performed molecular characterization of S. marcescens strains by RFLP and PCR methods, while Joyner et al. [2] detected S. marcescens strains in marine and other aquatic environmental samples (e.g., coral mucus, sponge pore water, sediment, sewage, wastewater and diluted wastewater) by real-time PCR. A study of Bussalleu and Althouse, published in 2018, reports a conventional endpoint PCR technique suitable for the identification of S. marcescens that effectively detects the presence of the microorganism in wild boar semen [52].

Our goal was the set up a classical PCR method suitable for the detection of S. marcescens in milk. The significance of our work lies in the fact that PCR-based methods described in the literature and the primers used were analyzed, then the procedure deemed appropriate was adopted to food hygiene analytical practice. In our experiments, qualitative determination of the possible S. marcescens contamination underlying the discoloration of factory, raw and pasteurized milk samples was performed.

3. Materials and methods

3.1. In silico studies

Based on the literature, three primer pairs (Table 2) were selected, which were evaluated by computer modeling, by so-called in silico analysis, as well as in vitro experiments in order to find the most suitable one for subsequent PCR assays.

In our in silico studies, the specificity of the a primer sequences was verified by comparison with a DNA database (NCBI BLAST) [54]. Comparison with the database allows for homology search (“blasting”). Following this, the suitability of the primers, i.e., whether a possible PCR reaction takes place with the selected genomes, was tested with a molecular biology software (SnapGene 5.1.5.) [55]. In the latter case, positive and negative control genomes were downloaded from the NCBI database, and then the SnapGene software was used, in an in silico way, to investigate whether the PCR reaction would take place with the primer pairs. The positive and negative controls used for reference purposes were whole chromosome genomes (Table 3).

* Primerek: A. Fpfs1 és Rpfs2; B. FluxS1 és RluxS2; C. Serratia2-for és Serratia2-rev.

Jelmagyarázat:

3.2. In vitro experimental studies

To confirm the results of the in silico studies, in vitro were performed in which the selected primer pairs were tested in laboratory PCR analyses on genomic DNA samples of selected strains of bacteria (several S. marcescens strains were used as positive control and Lactobacillus delbrueckii subsp. delbrueckii, Streptococcus thermophilus, Enterococcus faecalis and Micrococcus luteus were used as negative controls). The microorganisms were bacterial strains belonging to the collection of MTKI Kft. and coming from factory environment, determined by genetic identification.

When putting together the components required for the PCR reaction, 5.2 µL of PCR grade sterile water, 10 µL of DreamTaq Green 2× PCR Master Mix (Thermo Fisher Scientific, Waltham, Massachusetts, USA), 0.4 µL (10 pmol/µl) primer and 4 µL of isolated bacterial genomic DNA were used for each reaction. The negative control of the reactions was PCR grade sterile water. The program parameters of the PCR instrument (Mastercycler Nexus Gradient; Eppendorf International, Hamburg, Germany) were as follows: 95 °C for 1 minute, then for 40 cycles 95 °C for 15 seconds, 59.5 °C for 15 seconds, 72 °C for 10 seconds and, finally, 72 °C for 7 minutes [52].

For size separation of the DNA segments formed during the PCR reaction, a 10 µL sample was analyzed on a 2% agarose gel [TBE buffer (Tris-borate-EDTA) (10×), Thermo Fisher Scientific; Agarose DNA Pure Grade, VWR International, Debrecen, Hungary; ECO Safe Nucleic Acid Staining Solution 20.000×, Pacific Image Electronics, Torrance, California, USA]. The DNA size marker was the GeneRuler Low Range DNA Ladder (Thermo Fisher Scientific). Gel documentation was performed using the Gel Doc Universal Hood II gel documentation equipment and software (Bio-Rad, Hercules, California, USA).

3.3. analysis of raw and pasteurized milk samples

On the one hand, we used in our study factory raw and pasteurized milk samples in the case of which S. marcescens contamination was suspected due to their pink discoloration. On the other hand, factory raw and pasteurized milk samples that arrived at the laboratory together with the above samples but not exhibiting discoloration were also tested.

For the DNA digestion and purification process, the NucleoSpin Microbial DNA kit (Macherey-Nagel, Düren, Germany) was used according to the manufacturer’s instructions. The reaction tubes containing the eluted DNA were stored in a freezer at -20 °C.

Next, the suitability of DNA isolation and the amplifiability of the samples were checked by 16S rDNS polymerase chain reaction, using primers 27f (5’-AGAGTTGATCMTGGCTCAG-3’) and 1492r (5’-TACGGYTACCTTGTTACGACTT-3’). The total volume of the PCR reaction for 1 sample was 5.6 µL of PCR grade sterile water, 10 µL DreamTaq Green 2× PCR Master Mix, 0.2 µL (10 pmol/µl) of the primers and 4 µL of isolated bacterial genomic DNA. The negative control of the reactions was PCR grade sterile water. The program parameters of the PCR instrument were as follows: 95 °C for 4 minutes, then for 40 cycles 95 °C for 20 seconds, 54 °C for 30 seconds, 72 °C for 1 minute and, finally, 72 °C for 5 minutes.

For the separation of the DNA segments formed during the PCR reaction, a 5 µL sample was analyzed on a 1% agarose gel. The DNA size marker was the GeneRuler 1 kb Plus DNA Ladder (Thermo Fisher Scientific). The DNA sample tested was judged to be suitable for further PCR analysis if the length of the copies of the amplified DNA fragment was as expected (~1500 bp).

In the next step, samples were subjected to S. marcescens-specific PCR analysis and gel electrophoresis as described in subsection IN VITRO EXPERIMENTAL STUDIES. The results were evaluated on the basis of the presence/absence principle.

In order to check the suitability of the method, PCR results of the milk samples were compared with the few available API (bioMérieux, Budapest, Hungary) test results in a control test. The method was then used to detect the presence of S. marcescens in raw and pasteurized milks.

4. Results

In our in silico studies, when examining the homology of the primers, they showed similarity primarily to S. marcescens chromosome genomes. However, matches were also found in the case of S. rubidaea and S. nematodiphila strains and some non-Serratia species. These results were taken into account during the selection of reference genomes designed for our SnapGene software studies. The need for further investigation was justified by the fact that appropriate homology or the matching of the basis do not automatically mean that the PCR reaction will take place, because the direction of the primers, their melting temperature and the size of the PCR product formed are also critical, among other things.

In the SnapGene test, PCR reactions were predicted with the following parameters: our analyses were performed with at least 15 bases matching and the exclusion of single isolated mismatches. The minimum melting temperature was 50 °C and the maximum length of the fragment obtained as the result of the amplification was 3 kbp.

As shown in Table 3, when matched with the S. marcescens genomes, the primer pair Serratia2-for and Serratia2-rev showed amplification in all cases. The PCR reaction generally resulted in six or seven amplicons on the 16S rDNA sections. The adhesion site of the Fpfs1–Rpfs2 and FluxS1–RluxS2 primer pairs is located outside the 16S rDNA in most S. marcescens strains, but in some cases they did not show in silico amplification, so their sensitivity did not prove to be adequate. In the negative control genomes, the completion of a PCR reaction was predicted by the primer pair Serratia2-for and Serratia2-rev in some cases for certain S. rubidaea and S. nematodiphila strains. Using primers Fpfs1–Rpfs2, the PCR reaction would take place in the case of a S. nematodiphila strain. Primers FluxS1–RluxS2 did not predict the occurrence of a reaction on any of the selected negative control genomes (Table 3).

In S. marcescens genomes selected as positive controls in in vitro experiments, all three primer pairs gave signals according to the expected fragment size, and none gave a signal on the negative controls. The analysis carried out with the primer pair Serratia2-for and Serratia2-rev is shown in Figure 2. In the case of negative samples, the weak signals at around 50 bp are caused by the accumulation of the byproduct aspecific DNA fragments, primer dimers.

Based on the results of in silico analyses and in vitro studies, primers Serratia2-for and Serratia2-rev were considered to be suitable for further work, despite the fact that their specificity was not perfect. The decision was based on the probable frequency of occurrence of S. marcescens on the one hand and the importance of avoiding samples with false negative results on the other.

In order to check the suitability of the method that had been set up, factory milk samples were tested in a control study. Some of the milk samples (n=10) exhibited pink discoloration. Using our test method, nine samples were found to be positive for the microbe sought. We also had API test results for four of the samples. The four API-positive samples were also found to be positive in the PCR assay. The method was then used to detect S. marcescens in raw and pasteurized milks.

Some of the milk samples showed peach-pink discoloration (Figure 3), but it was not clear in many cases due to the pale or yellowish tint. A total of 60 samples were analyzed. Of these, 32 (53.3%) gave positive results and 28 (46.7%) gave negative results for the presence of S. marcescens.

Figure 4 shows the result of one of our assays, the separation by gel electrophoresis. It can be clearly seen that the positive control strain gave a positive signal, while the negative control sample gave a negative signal, and positive signals were obtained for three test samples. The weak signals appearing in the case of negative samples are again caused by the accumulation of primer dimers.

5. Discussion

When evaluating our results, it is important to take into account that the PCR analysis is a method suitable for the amplification and detection of the target DNA in the sample, based on which it is not possible to determine whether the amplified S. marcescens-specific DNA comes from viable, dead or so-called VBNC cells. In the VBNC (“viable but not culturable”) state, the cells are viable, metabolically active, but cannot be propagated by classical culture methods. This condition is reversible.

The objective of our work was to establish a classical PCR method for the detection of S. marcescens. Using the test procedure applied, qualitative determination of the S. marcescens contamination responsible for the discoloration of milk samples can be carried out.

Although the experiments presented here focused on the detection of pigment-producing S. marcescens, a future genus-level study could identify all 20 Serratia species (Table 1). The significance of the detection of other Serratia species is evidenced by the fact that, although the genus Pseudomonas is the main cause of the spoilage of chilled raw milk, the dangers of Serratia species in this respect are also known [56]. In addition to Pseudomonas strains, Serratia strains have also been identified in many cases as causes of milk spoilage. Members of the genus Serratia have been detected in dairy plants [3, 12], in raw milk samples stored at 4° C [56, 57, 58] and in milk containers [59]. It was noted by Grimont and Grimont [9] already a decade and a half ago that raw milk lots can occasionally be contaminated with Serratia species, and the species most often occurring in diary products are S. liquefaciens and S. grimesii.

The presence of psychotrophic Serratia species (e.g., S. liquefaciens) in raw milk can cause spoilage even after heat treatment. Baglinière et al. found that the thermally stable Ser2 protease produced by S. liquefaciens may be a significant factor in the destabilization of UHT milk [11, 60].

In conclusion, it can be stated that a genus-level study would be an interesting research project that would fill a gap, and which would allow the monitoring of raw milk in this respect, the wide detection of Serratia species. Presumably, the results would provide useful information not only to the stakeholders of the dairy economy and the dairy industry, but could also have an impact on Hungarian regulatory and monitoring practice.

6. References

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