30 samples of polyfloral honey (15 samples were directly from urban beekeepers and 15 samples were purchased from retail stores).

Muller Hinton broth, Mueller Hinton agar, Sabouraud dextrose broth, Sabouraud dextrose agar, blanc discs, antibiotics: tigecycline (30 μg per disc), chloramphenicol (30 μg per disc), fluconazole (30 μg per disc) (Oxoid, Basingstoke, UK).

One species of Gram-positive bacteria Enterococcus faecalis CCM 4224, one subspecies of Gram-negative bacteria Salmonella enterica subsp. enterica CCM 4420, and one species of yeast Candida krusei CCM 8271. All tested microorganisms were collected from the Czech Collection of microorganisms (Brno, Czech Republic).

Densitometer (Biosan DEN-1, Riga, Latvia).

The second part of the research was based on a questionnaire survey conducted in 2020. The survey was carried out online in Google forms and was disseminated via emails and social media (mostly Facebook groups) by applying a snowball sampling strategy. The research sample comprised 617 honey consumers living in urban areas. The socio-demographic profile is described in Table 1. The questionnaire involved both close-ended questions and open-ended questions regarding consumption patterns, purchasing behavior, and consumer´s awareness of the healing properties of honey.

The antimicrobial activity of honey samples was conducted in triplicate and recorded with standard deviations. T-test for Equality of means was used for testing differences between honey samples from stores and urban beekeepers. In consumer research, there were applied non-parametric tests such as the Chi-square test of Independence, Friedman test, and multiple pairwise comparisons using Nemenyi’s procedure. The significance level was set to 0.05. All statistical analysis was carried out in statistical software SPSS Statistics v.25, IBM.

Results showed that antimicrobial activity was found in all tested kinds of honey (50% concentration). The highest antimicrobial activity in commercial kinds of honey was found against E. faecalis followed by S. enteritidis and C. krusei, while in kinds of honey from urban beekeepers was the order as follows: E. faecalis > C. krusei > S. enteritidis (see Table. 2). In addition, we formulated the first hypothesis, which assumes that there exist significant differences in antimicrobial activity between honey samples from urban beekeepers and those purchase from retail stores. T-test for Equality of Means confirmed statistically significant differences in all three types of microorganisms (p ≤0.001). Moreover, the antibacterial activity of kinds of honey with a concentration of 25% was found only in one type of examined microorganism and only of few honey samples. Eight honey samples from urban beekeepers inhibited E. faecalis (10.75 ±0.43) while only two honey samples from stores inhibited S. enteritidis (4.5 ±0.23). Antibacterial activity of honey with a concentration of 12.5% was found only in the case of 5 samples from urban beekeepers and it was against E. faecalis (6.9 ±0.97). Antibacterial activity is the most evaluated and investigated biological activity of honey and its presence has been proven in several tested samples of honey from the different botanical and geographical origin that were the object of examination of numerous studies which were orientated on the antibacterial activity (Al-Jabri et al., 2003; Al-Waili, 2004; Bucekova et al., 2019; Bucekova et al., 2018; Cilia et al., 2020). The mentioned statement confirms our achieved results related to antimicrobial activity. The similar results with samples of Slovak honey were obtained by Šedík et al. (2018) and by Kačániová et al. (2012).

The questionnaire survey showed that Slovak consumers living in urban areas have the following annual consumption patterns: 39.7% consume only up to 1 kg and honey is mostly consumed occasionally or only during illness; 32.4% consume 1 or 2 kg in certain frequencies (few times per month or week). The rest 27.8 % consume ≥3 kg mostly every day or few times per week. Based on the realized survey in Romania Pocol (2011) identify that 11.0% of consumers do not consume honey, while consumption of honey at the level of a maximum of 750 g per year is recorded in a group of approximately 35% of the population. Pocol (2011) also added that the average consumption, between 750 g and 2 kg per year, has a rate of approximately 27%, while 20% of the population consumes over 2 kg of honey per year. Furthermore, by applying the Chi-square test of independence we confirmed (p-value = <0.0001) the statistically significant differences in honey consumption per year among different age segments (H2). Lower honey consumption (only up to 1 kg) is more frequent for younger consumers (18 – 30 years). The highest annual consumption has consumers older than 50 years (see Figure 1). Kopała, Balcerak and Kuźnicka (2019) also found that elder respondents declared honey consumption more often than young people. Moreover, Żak (2017) realized the survey in Poland and reports that 83% of Poles over 65 years consume 500 g of honey in a month. In the context of the above Pocol and Moldovan-Teselios (2012) stated that young people up to 30 years consume rather small quantities of honey, consumers in the age category 32 – 45 years present a “normal” consumption behavior which is similar that the entire population, consumers between 46 – 60 years prefer consumption of average and large quantities of honey, being under-represented among non-consumers and the last category of consumers, consumers older than 61 years, consume medium quantities of honey.

Approximately 78% of respondents answered that honey is consumed by the whole family. The household consumption of honey is on average 6,5 kg per year. The results of the study of Roman, Popiela-Pleban and Kozak (2013) showed that 7.2% of respondents declared that honey is not consumed in their households and emphasized that only 20.6% of respondents stated a daily consumption of this product while almost 39% of respondents stated that they consumed it only occasionally. Regarding the purpose of honey, it can be stated that honey as food is used by 68% and as medicine by 44% of consumers. Only 10% indicated cosmetics purpose. The purpose of honey also confirmed the survey realized by Ismaiel et al. (2014) and stated that the major motives of consumers for purchasing and consuming honey were to use it as medicine, food, a sweetener, or for other uses. In addition, the Chi-square test of independence confirmed (H3) significant dependence between respondent's age and purpose of use (p-value = <0.0001). Young consumers use honey more as medicine while the older generation uses it more as food (see Figure. 2).

Honey is mostly consumed as follows: sweetener in beverages > ingredient in the recipe > directly from a jar. Around 1/2 of respondents consume this product all over the year and around 43% only during the winter period to support their health. Moreover, 31% use honey regularly as a healthier alternative to sugar, and approximately 60% only sometimes.

Distribution of honey takes place primarily through producer-consumer or manufacturer-retailer-consumer channels (Borowska, 2011; Kumar, Sharma and Singh, 2012). Results of our study showed that the honey is mostly purchased as follows: directly from beekeeper > shops and retail stores > farmer markets > specialty shops. The least frequent place of purchase was e-shops. These results are also confirmed by Roman, Popiela-Pleban and Kozak (2013) who found that more than 60.0% of respondents prefer to buy honey from beekeepers, and by Ciric, Ignjatijević and Cvijanovic (2015) who identified more than 40% of consumers has a habit of purchasing honey directly from the manufacturer of honey. Pocol and Bolboaca (2013) concluded, that local producers were preferred to purchase honey, but on the other hand, respondents also purchase honey and bee products in regional markets, hypermarkets or supermarkets, fairs and exhibitions, specialized shops for organic products, and other places. Marzec (2003) in her research showed that 84% of consumers purchase honey at the store and only 21% directly from the beekeeper. Krystallis, Petrovici and Arvanitoyannis (2007) state that the most usual channel for frequent food purchases for more than half of the sample is small local stores and open markets, while supermarkets are preferred for occasional food purchases. The optimal price per 1 kg of honey was considered 7 € (22%), 8 € (20%), or 6 € (17%). In comparison with other studies, we could state that consumers from other countries also most prefer honey up to 10 € per 900 g (Kos Skubic, Erjavec and Klopčič, 2018). In addition, respondents evaluated the importance of selected factors during honey purchase using 7 points scale, where 1 = the most important and 7 = the least important. Based on the Friedman test (p-value = <0.0001) it can be stated that there exist statistically significant differences in the evaluation of selected factors (H4). These differences were identified by Nemenyi´s procedure and are illustrated in Table 3. The most important factors are the following: honey quality > honey taste > honey origin > hone type > consistency. The least important were honey packaging and price.

In the context of quality as the most important factor during honey purchase is important to emphasize that honey quality is connected with food safety, credence dimension, quality mark, honey taste, as well as nutritional value (Borodin, Arion and Muresan, 2013; Röhr et al., 2005). According to Ványi, Csapo and Karpati (2010), the most important properties in the process of honey purchasing are the taste, quality, and color of honey.

Oravecz et al. (2020) found that consumers consider honey as a trusted product, which is confirmed by the fact that the source and the quality are the most important factors that influence the purchase of honey. The results of a study conducted by Wu et al. (2015) emphasizes that the origin of honey is a very important attribute when choosing purchased honey and that even consumers are willing to pay a higher price for local honey, which also confirms our result that price is not a decisive factor in the process of honey purchase. On the one hand, Gyau et al. (2014) realized the descriptive analysis of the main attributes of honey and they showed that price, packaging, and color are the three key attributes that strongly influence a consumer’s choice of honey. On the other hand, they emphasized that quantity, taste, and the origin of the honey have a moderate influence on the choice, whereas the production process does not influence consumer preferences.

In addition, the survey focused also on consumer awareness and perception towards honey and its biological properties. Approximately 97% of respondents think that honey has healing properties, however, 1/3 of them were not able to answer the specific ones. The interesting result is that more than 40 % of them were younger than 30 years. The rest of the respondents listed various properties and effects. The most frequent were the following ones: immunity booster (22.7%), healing effects in case of cold, flu, or sore throat (12.5%), antibacterial activity (11.2%), antiinflammatory (8.4%), and others. Based on the results, it can be concluded that the consumer´s awareness about the antibacterial activity is very low. A similar situation is with medical honey which is unknown for 72% of urban consumers. The rest of them perceived it as honeydew honey, honey used in hospitals, in medicine, or as clean, pure honey used for healing wounds.

In general, consumers are interested in the liquid consistency of honey, which was proved by Cosmina et al. (2016). Due to this fact, crystallized honey is usually liquified by applying thermal treatment. Increasing temperature of honey can decrease its antibacterial activity (Pimentel-González et al., 2015). The last hypothesis (H5) assumes that more than 50% of respondents are not aware of the maximum temperature for heating honey without decreasing biological active compounds. The survey showed that only 18% knows the correct answer – 42 degree. The rest of them either do not know (48%) or has incorrect information (34%).