Soural et al. (2015) tested different temperatures and different maceration times for the extraction of resveratrol from vine shoots with different solvents. The time intervals tested for maceration at laboratory temperature were 8 h, 2.4 and 7 days. The results obtained after this test showed an increasing slope for the concentration of resveratrol until day 4, the day when the maximum amount of resveratrol extracted was reached, after which it started to decrease slightly. This was observed for both solvents used in the extraction, methanol and acetone [39]. These results are in agreement with the result of this study.

The effect of the contact time (respectively 1, 4, 7 and 10 days) and variation of ethanol concentration of the solvent (0, 4, 7.5 and 13%) on extraction of the phenolics was tested by Gambuti et al. (2009) on the skins and seeds of the grapes of Uva di Troia and Aglianico variety (*Vitis vinifera*). The results indicate that many compounds reach a maximum concentration on 4th day of maceration, compounds such as anthocyanins, vanillin reactive flavones, phenolics and proanthocyanidins [48]. These results validate the findings of this study.

#### *4.4. Granulosity Selection*

The material of the grounded vine shoots was sieved in 12 separate sieves and was macerated under the same conditions and with the same solvent to determine whether the granulosity of the material has an effect on the extraction content of trans-resveratrol (Figure 5).

Figure 4 shows that there were significant disparities in yield depending on the granulosity of the material, highlighting the material with 500 μm–350 μm granulosity, with a yield of 205.16 mg/kg D.W. Unexpectedly, the lowest yield (23.67 mg/kg D.W.) was recorded for the least granular material—125 μm. This is unexpected, because the surface area for mass transfer is larger than that of other materials. An amount of 55.1% of the chemical composition of vine prunings is represented by holocellulose (31.9% α-cellulose and 23.2% hemicellulose), followed by lignin, with 38.5% [49]. These differences in the extraction yield can be attributed to the non-uniformity of the chemical composition in the

composition of the shoots. This result highlights the fact that it is not necessary for the solid material to be grinded to fine particles in order to obtain a superior extraction yield. Thus, in the process of obtaining trans-resveratrol from vine shoots, the grinding of the material can be carried out through an energy-saving process by grinding the material up to 350 μm.

Soural et al. (2015) compared the resveratrol content of extracts for cut material (~1 cm) and powdered material (>1 mm) from vine shoots using methanol and preceding the extraction at laboratory temperature. Although the dimensions of the extraction material used in this study are different, a slight positive difference was recorded (4189.0 μg/g D.W. for the cut material and 4109.0 μg/g D.W. for the powdered material) [39].

#### *4.5. Number of Extractions on the Same Material*

The second extraction managed to extract another 5% resveratrol content compared to the first extraction, and the third only 0.67%. The next four extracts did not contain resveratrol (Figure 6).

From an economical point of view, further extractions on the same material are not advantageous. The use of solvents, time and manufacture practice are not economical for the second and third extraction, which together add up to only 5.67% out of the total content of trans-resveratrol from vine shoots. This attempt to increase the amount of trans-resveratrol extracted from the same material highlights the fact that the optimal parameters of the first extraction are well chosen, thus extracting 94.33% of the amount of resveratrol available.

Soural et al. (2015) conducted multiple Soxhlet extractions with methanol on vine shoots and compared the extraction yield of stilbene for each extraction. The yield of stilbene for the second extraction is under 5%, and the yields of the third and further extractions were under 1% [39]. These results are the same with the result obtained by conventional maceration with diethyl ether–ethanol 1:4 ratio.

#### *4.6. Optimization of Extracting Parameters*

The experimental results of trans-resveratrol content at different solid–liquid ratios (1:20, 1:35 and 1:50 g/mL), time (2, 4 and 6 days) and granulosity (<125, 500–350 μm and >1000 μm) were placed to the quadratic equation using the response surface analysis. The equation for trans-resveratrol content is displayed in Equation (1):

### Trans − resveratrol

= 205.16 + 41.27 × A + 1.15 × B + 17.68 × C + 24.08 × AB + 29.56 × AC − 7.85 × BC −67.75 × A2 − 27.41 × B2 − 41.30 × C2 (1)

where A—solid/liquid ratio g/mL, B—Time, C—particle size interval.

The analysis of variance indicated that the quadratic regression model is statistically significant (*p* < 0.05) with a coefficient of regression R2 = 0.90. Figure 7 displays the 3D evolution of trans-resveratrol content in the function of the parameters employed (Table 2).

According to Figure 7, the highest trans-resveratrol content is recorded at the correlation of the following parameter values 1:35 g/mL solid:liquid ratio, 4 days with 500–350 μm (148.55 mg/kg D.W.), having as extraction solvent ethanol:diethyl ether in a ratio of 4:1. At these conditions, the predicted response for the optimized value is the same as the measured response, namely a resveratrol content of 205.16 mg/kg dry weight. The lowest value was observed at 1:20 g/mL solid–liquid ratio, 6 days with 500–350 μm (43.70 mg/kg D.W.). These results are in compliance with those reported by Soural et al. (2015) on the extraction of resveratrol from vine shoots [39] and Gambuti et al. (2009) on the extraction of resveratrol from skin and seeds of grape [48], regarding obtaining a maximum yield on day 4 of extraction. Additionally, Garcia et al. (2014) reported an optimum solid–liquid of sample/solvent ratio of 1:40 for extracting resveratrol from peanut grass *Aracis repens* [47], results that are near the results obtained, namely an optimal ratio of 1:35 solid/liquid.

The predicted optimum conditions for trans resveratrol extraction (Table 3) were very similar to the experimental concentration achieved under these conditions. Any increase or decrease in the value of the extraction parameters negatively affected the extraction yield.

#### **5. Conclusions**

Numerous studies have highlighted the evidence of the therapeutic effect of transresveratrol on the human body. Due to the fact that vine wastes are recently considered a valuable source of this compound through the high amount that they contain, the optimization of the extracting parameter is needed. Various extracting conditions were applied to determine the optimal method.

The results of the present study showed that the solvent ethanol:diethyl ether in a ratio of 4:1 is recommended for the extraction of trans-resveratrol from vine shoots, obtaining by its use the highest yield compared to other solvents (147.14 mg/kg D.W.). By increasing the diethyl ether quantity, the extraction yield was negatively affected. Acetone was a weak solvent for extracting trans-resveratrol, resulting in lower quantities extracted. Among the ethanol and methanol series, Et 80% (66.86 mg/kg D.W.) and Met 99.9% (84.06 mg/kg D.W.) had a good yield, but it was almost half that of the solvent with diethyl ether. Adding HCl to Met 99.9% positively improved the extraction yield, being the second solvent by the quantity extracted (92.06 mg/kg D.W.).

Among the different reports of the solid liquid, 1:35 liquid:solid ratio had extracted the highest content of trans-resveratrol (43.91 mg/kg D.W.). The optimal time of extraction was 4 days (167.74 mg/kg D.W.) and the optimal granulosity of the grinded vine shoots was 500 μm–350 μm (205.16 mg/kg D.W.).

With the extraction method described above, the yield of trans-resveratrol extraction was 94.33%. Economically, another extraction on the same material is not recommended.

The result obtained was confirmed by optimization of extracting parameters according to Box–Behnken design, in which the predicted response was similar to the obtained response. The highest trans-resveratrol content was recorded at the association of the following parameter values: 1:35 g/mL solid:liquid ratio, 4 days with 500–350 μm (148.55 mg/kg D.W.).

**Author Contributions:** Conceptualization, A.L.C. and G.G.; methodology, A.L.C.; validation, A.L.C. and G.G.; formal analysis, A.L.C.; investigation, A.L.C.; resources, A.L.C. and G.G.; data curation, A.L.C.; writing—original draft preparation, A.L.C.; writing—review and editing, A.L.C.; visualization, G.G.; supervision, G.G.; project administration, G.G.; funding acquisition, G.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** All data related to this study are explicitly plotted in the figures in this article.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

### *Article* **The Use of Vacuum Impregnation of Barley Grain in the Production of Malt for Wort**

**Leszek Rydzak 1, Renata Rózyło ˙ 2,\*, Tomasz Guz 2, Marcin Natoniewski 1 and Kostiantyn Vasiukov 1**

**Featured Application: This study shows that the use of the vacuum impregnation process of barley grain for the production of light malt significantly reduces the soaking time of the grain, which speeds up the malt production process without causing significant negative changes in the parameters of wort. Vacuum impregnation is not used in industrial beer production. However, it can be quickly implemented with a small investment, i.e., the purchase of a vacuum pump and vacuum chamber.**

**Abstract:** In this study, the process of the vacuum impregnation of Kangoo barley grain, at the stage of soaking, was used in the production of light malt. The influence of vacuum impregnation on the speed of the water uptake by the barley, at temperatures of 12, 14, 16 and 18 ◦C, was also analyzed. At this stage of the research, the grain was soaked in water to obtain a moisture content of approximately 42%. The samples for the moisture content tests were taken every 2 h. The grain intended for malt was soaked in an air–water system and was kept submerged in water for 6 h. It was then removed from the water and kept for 18 h. The grain was aerated during the soaking process. The malting and soaking lasted eight days at temperatures of 12, 14, 16 and 18 ◦C. The samples for further testing were taken daily. Then, each of the samples was dried, following the same procedure. The sprouts were removed immediately after the dried samples contained approximately 4% moisture. Following a 3-month maturation process, the congress wort was produced from the malt. The pH and the extract content in the wort were tested. It was found that the process of vacuum impregnation significantly accelerates the uptake of water by the grain. In almost all cases, the influence of the tested factors on the pH of the wort and the extract content was also observed.

**Keywords:** vacuum impregnation; malt; barley; wort

#### **1. Introduction**

Impregnation, i.e., filling materials with additional liquid components, has been a known and widely used process for over 100 years. Since the end of the 1960s, the appearance of and the expansion in the use of the impregnation process under reduced pressure conditions can be observed on an industrial scale. Such impregnation is called vacuum impregnation, in both the scientific and trade literature. Its importance can be proven by the fact that it is among the processes covered by the standards of the American defense industry (MIL-STD-276A) [1].

In traditional applications, the purpose of impregnation is to ensure tightness and to eliminate the porosity of various materials. It is mostly used in the production of engine blocks and cylinder heads in the automotive industry, as well as in power systems, brake systems and landing gear components in the aviation industry. The knowledge already gathered allows us to state that impregnation is a process that modifies the structure and the sensory and functional properties of products and increases their physicochemical

**Citation:** Rydzak, L.; Rózyło, R.; Guz, ˙ T.; Natoniewski, M.; Vasiukov, K. The Use of Vacuum Impregnation of Barley Grain in the Production of Malt for Wort. *Appl. Sci.* **2023**, *13*, 1628. https://doi.org/10.3390/ app13031628

Academic Editors: Adriana Dabija, Georgiana Gabriela Codină and Lăcrămioara Rusu

Received: 14 December 2022 Revised: 24 January 2023 Accepted: 25 January 2023 Published: 27 January 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

stability by creating a coating of liquid material on the surface of a solid body [2,3]. In recent years, there has been a rapid development of a new branch of food engineering, referred to as the food matrix engineering (spatial architecture) of materials [4,5].

In comparison to vacuum impregnation, it was demonstrated that freezing/thawing and compression caused more changes in the internal microstructure of apple tissue, resulting in the formation of cell cavities [6]. Regardless of the changes in the microstructure caused by vacuum impregnation, the integrity of the plant tissue cells is unaffected [7,8].

Vacuum impregnation can be carried out in many ways:

In the course of vacuum impregnation, two groups of related phenomena can be distinguished:

Many different factors influence the impregnation process. Most often, they are divided into two groups: the external and internal factors [13].

In the group of external factors, the most important is the impregnation pressure (p1). It is the driving force behind the entire process. Most often, in the impregnation of biological materials, pressures ranging from 50 to 600 hPa are used [12–19].

The t1 and t2 times are identified in the literature as important factors. The longer the time, the lower the pressure is maintained and the lesser the weight loss, which results in a greater degree of impregnation [20]. In the scientific literature on impregnation, the ranges of the t1 and t2 time variations, assumed by the researchers, are quite extensive. Some apply pressure in the range from 0 to 10 min, others conduct research in the range from 10 to 120 min [17,18,21,22]. The viscosity index, temperature and concentration of the impregnating liquid also affect the effectiveness of the impregnation [2,13,17,22].

Among the internal factors, the properties of the impregnated material and its structure should be mentioned. Porous materials with numerous voids in their tissues, such as fruit and vegetables, are particularly susceptible to impregnation. They show a higher degree of porosity compared to meat, fish and cheese [10,14,15,23].

There are many studies on the use of vacuum impregnation in food production [12–15,17–19] and there are many reports on the beneficial effect of vacuum impregnation on the structure of tissues. The use of this treatment reduces the probability of thermal damage to the organic tissue and also prevents the loss of the aroma and color of fruit and vegetables [24]. This is only possible by removing oxygen from the pores, without the need for antioxidants.

Other researchers present the possibility of introducing antioxidants or antimicrobial agents into the structure of the material, which can extend shelf life [3]. The results of studies on the application of impregnation as a pretreatment before freezing are available [25]. Impregnation is often used as a pretreatment that precedes heat treatment [26,27].

There is a scarcity of scientific data on the vacuum impregnation of cereal grains in the scientific literature [28].

Barley is subjected to steeping. In this phase, the barley reaches a moisture content of 42 to 44% [29].

Steeped barley is then directed to the malting department called the sprouting room. In modern malting houses, sprouting boxes or drums are used for sprouting barley, in which the process is completely mechanical. The barley sprouting cycle lasts 5–8 days at a temperature of 12–20 ◦C. The duration of the process depends on the variety of barley, the method of malting and the sort of malt [29,30].

Kilning takes place at a temperature of 30–85 ◦C, measured in the malt, and lasts 12–36 h for light malt, depending on the kilning method. Munich-type dark malt is kilned for 48 h, and the temperature in the final phase of this process should be 105 ◦C. Next, the rootlets are removed [29,30].

The use of vacuum impregnation at the steeping stage can significantly speed up this process, which can shorten the malt production cycle, because it significantly accelerates mass transfer processes in the liquid–solid system [10].

The aim of this study was to establish the effects of vacuum impregnation on the steeping process and the structural changes in barley grains in relation to some of the selected parameters of wort.

#### **2. Materials and Methods**

#### *2.1. Materials*

The research material used was malting barley grain of the Kangoo variety (Soufflet Agro Poland Ltd., Ko´scian, Poland). The grain used for the research was uniform in variety. The grain was cleaned and sorted, using a sieve-pneumatic separator. The grains with a fraction over 2.5 mm were tested. The moisture content of the barley was 13.7%, the protein content was 10.9% d.m. and the weight of 1000 grains was 49.8 g.

#### *2.2. Methodology of the Vacuum Impregnation of the Grain*

Water was used as an impregnating liquid in all of the cases. Wet vacuum impregnation (WVI) was applied. The process was run in a 2 dm3 chamber coupled with a vacuum pump, facilitating the adjustment of the pressure in the chamber in the range of 5–100 kPa. To ensure complete immersion, all grains were placed in a special container. The investigations were carried out at a temperature of 20 ◦C, the same as that of the impregnating liquid. The grain samples were placed in a chamber filled with the liquid and, after closing the chamber, the pressure was reduced to 5 kPa, at a rate of 30 kPa·s−1. Immediately after the pressure reduction, the atmospheric pressure was restored in the chamber, at a rate of 30 kPa·s−1, and the grains were separated from the chamber. The duration of the vacuum period and the relaxation time were therefore reduced to a minimum. Concurrently, the impregnation at an atmospheric pressure (about 100 kPa), which served as a reference system, was carried out.

#### *2.3. Methodology of the Malt Preparation*

The barley was soaked in the two-phase air–water system. The water phase lasted 6 h, and the air phase lasted 18 h. The air–water soaking took place in three such cycles. In the water phase, half of the grains were soaked under atmospheric pressure. The remaining raw material, in the final stage of the water soaking, was subjected to vacuum impregnation. During the water soaking, the grain was aerated. Then, the grain was subjected to malting, which took place in a climate chamber at temperatures of 12, 14, 16 and 18 ◦C. The germinating grain bed was periodically mixed. The malt samples were taken once a day for the next eight days. The collected samples were subjected to convection drying, gradually increasing the temperature from 40 ◦C to 60 ◦C, at a rate of about 1 ◦C/h. Next, the temperature was increased, at a rate of 1 ◦C/min from 60 ◦C to 75 ◦C. For the final 5 h, the malt was dried at a constant temperature of 75 ◦C. Immediately after drying, the rootlets were separated, using a sieve with a mesh size of 1 mm. The samples prepared in this way were matured for a period of 3 months.

These experiments were carried out in triplicate.

#### *2.4. Methodology of the Mashing*

After 3 months of maturation, the malt was ground in an ML 155 laboratory mill and was subjected to mashing, to produce a congress wort.

In the congress mashing, each portion of the ground malt was transferred to a mash beaker and thoroughly mixed with a spatula. A portion of 50 g was weighted in the mash beaker. The mashing bath was set to 45 ◦C. A volume of 200 mL of water was stirred into each beaker and the mash was mixed using a glass rod, to avoid balling. The temperature of the mash was maintained at 45 ◦C for exactly 30 min. Next, the temperature of the mash was increased at 1 ◦C per minute for 25 min, up to 70 ◦C. When the temperature reached 70 ◦C, a further 100 mL of water with a temperature of 70 ◦C was added. The saccharification rate was measured from this point (after 55 min from the beginning of the mashing). A drop of the mash was transferred to a spot on the porcelain plate, and a drop of an iodine solution was added. This test was repeated at 2 min intervals until the saccharification was completed: that is, when a clear yellow spot was obtained. Following the saccharification, the mashing was terminated [31].

The mash was then filtered and cooled to 20 ◦C. The spent grains were washed with a small amount of water, dried outside of the beaker, and then the contents of the beaker were replenished to 450 g, with the addition of water. Then, the pH and the extract content were determined.

The determinations of the extract content in the wort were established, according to the Analytica EBC methods (2019) [31]. These parameters were expressed using a PAL1 digital refractometer. The measurements of the pH value of the congress wort were also obtained, by Analytica EBC (2019). The Elmetron CP-411 pH meter, with an accuracy of 0.01, was used to measure the pH of the wort. All testing procedures followed the Analytica EBC methods (2019).

#### *2.5. Methodology of Measuring the Rate of the Increase in the Grain Moisture Content*

Tests on the speed of the water uptake by the barley grain subjected to vacuum impregnation and soaked under atmospheric pressure were also carried out. During these tests, the grain was kept under water and aerated throughout the entire period. The grain was subjected to vacuum impregnation periodically, every 30 min. The tests were carried out at temperatures of 12, 14, 16 and 18 ◦C. The barley moisture content was tested with samples taken every 2 h [31]. The determinations were performed in triplicate. The moisture content was measured, according to the PN EN ISO 712:2012 standard [32].

#### *2.6. Statistical Analysis*

The statistical analysis was performed using Statistica version 13.3. A three-stage statistical analysis was performed to evaluate the statistical significance of the differences in the examined properties of the wort. In the first stage, the Shapiro–Wilk test was performed, in order to confirm that the probability distribution of the examined parameters was normal. In the second stage, multivariate analysis of variance (ANOVA) was performed, and finally, all of the results were analyzed for significance by means of Tukey's reasonable significant difference (HSD) test, at a significance level of α = 0.05, because this test is considered to be less conservative than the Scheffé test but more conservative than the Newman–Keuls test.

#### **3. Results**

Figure 1 shows the changes in the moisture content of the Kangoo barley grain, which was vacuum-impregnated every 30 min and soaked under atmospheric pressure at the tested temperatures.

The grain subjected to cyclic vacuum impregnation did not lose its viability and absorbed more water in a shorter amount of time. The vacuum impregnation of the grain during the soaking in the tested temperatures of 12, 14, 16 and 18 ◦C made it possible to obtain the moisture levels required for malting after approximately 30 h, i.e., around 6 h faster than in the case of the non-impregnated grain. Table 1 presents the results of Tukey's reasonable significant difference (HSD) test used to assess the significance of the effect of the grain moistening conditions on the final moisture content.

**Figure 1.** Changes in the moisture content during the barley grain moistening at the tested temperatures. (K12I, K14I, K16I and K18I: vacuum-impregnated grain, soaked at 12, 14, 16 and 1 ◦C, respectively; K12A, K14A, K16A and K18A: grain not subjected to vacuum impregnation, soaked at 12, 14, 16 and 18 ◦C, respectively).

**Table 1.** The results of the analysis of Tukey's reasonable significant difference (HSD) test of the influence of the selected factors on the moisture content of the tested barley grain cultivars.

\* Different letters mean statistically significant differences at the level of α = 0.05.

The influence of the factors tested on the moisture content showed statistically significant differences. The temperature changes in the range of 12–16 ◦C did not cause significant changes in the final moisture content. Rather, the changes in the final moisture content observed in the case of the soaking grain at 18 ◦C showed statistically significant differences. Figure 2 shows the changes in the pH value of the congress wort obtained from the

Kangoo malted barley at the tested temperatures.

**Figure 2.** Changes in the pH value of the congress wort obtained from the malt created from the Kangoo variety barley. (K12I, K14I, K16I and K18I: vacuum impregnated grain, soaked at 12, 14, 16 and 18 ◦C, respectively; K12A, K14A, K16A and K18A: grain not subjected to vacuum impregnation, soaked at 12, 14, 16 and 18 ◦C, respectively). a, b, c, ... - different letters mean statistically significant differences at the level of α = 0.05.

The pH value is one of the most important parameters in the production of wort. The tested parameter changed its values, depending on the temperature and the malt production model. The highest pH value (6.2) was recorded for the wort obtained from kilned malt from barley, steeped in the atmospheric conditions, and malted for one day at a temperature of 16 ◦C.

The wort from the malt obtained from the grain steeped and impregnated under a pressure of 5 kPa showed a greater decrease in the value of the tested parameter. The lowest pH value was found in the wort obtained from grain steeped under atmospheric pressure and malted at 14 ◦C.

Figure 3 shows a diagram of the changes in the extract content in the congress wort obtained from the Kangoo variety malt that was vacuum impregnated at a temperature of 12–18 ◦C, under an atmospheric pressure of 5 kPa.

**Figure 3.** Changes in the extract content in the congress wort obtained from the malt created from the Kangoo variety barley. (K12I, K14I, K16I and K18I: vacuum-impregnated grain, soaked at 12, 14, 16 and 18 ◦C, respectively; K12A, K14A, K16A and K18A: grain not subjected to vacuum impregnation, soaked at 12, 14, 16 and 18 ◦C, respectively). a, b, c, ... - different letters mean statistically significant differences at the level of α = 0.05.

Table 2 presents the results of Tukey's reasonable significant difference (HSD) test used to assess the significance of the effect of the steeping and malting conditions on the pH and extract content.

**Table 2.** The results of the analysis of Tukey's reasonable significant difference (HSD) test on the influence of the selected factors on the extract content and the pH.

\* Different letters mean statistically significant differences at the level of α = 0.05.

The course of changes in the extract content for the wort obtained from the malt created from the Kangoo barley variety that was steeped under atmospheric pressure and malted at 12 ◦C shows an increasing linear trend with values above 8◦Bx, except for the kilned malt samples obtained after the first day of malting, where the extract content in the wort was 6.6◦Bx. In the case of the malt obtained from grain steeped and impregnated at a pressure of 5 kPa, the lowest value of the wort extract content was 7.1◦Bx, and then it increased slightly to 8.3◦Bx for the kilned malt sampled on the last day of the malting. The extract content in the individual congress wort samples differed from each other by about 0.5◦Bx in all of the tested samples within eight days of malting.

The malt produced at higher temperatures behaved in a similar way. Table 2 presents the results of the statistical analysis of the influence of the examined experimental factors on the extract content and pH values.

The influence of the examined factors showed statistically significant differences. The temperature changes in the range of 16–18 ◦C did not cause any significant changes in the extract content. To the contrary, the changes in the extract content observed at 12 ◦C showed statistically significant differences.

#### **4. Discussion**

The analysis performed in this study revealed no negative effects of vacuum impregnation on the brewing process or on the final product quality. In our previous studies, vacuum impregnation did not cause significant changes in the germination efficiency of the tested cereals, i.e., barley, wheat and rye. It was found that the impregnation did not affect the internal structure of the grain [28]. Other authors noticed that the integrity of plant tissue cells is unaffected despite changes in microstructure caused by vacuum impregnation [7,8].

In the current study, a decrease in the pH of the congress wort was observed during malting. Wort from malt obtained from vacuum-impregnated grain, under a pressure of 5 kPa, showed a greater decrease in pH. This has been confirmed in other studies that the optimum pH for α-amylase is 5.6 to 5.8, and for β-amylase, it is 5.4 to 5.5. Higher pH values are considered unfavorable, in contradistinction to lower pH values. At a low pH, higher amounts of fermentable sugars are obtained, which results in an increase in the degree of fermentation [30]. The pH values of the wort produced from malt, which was created from impregnated grain, were slightly lower than optimal. These low pH values do not cause enzyme inactivation and may only slightly slow down the starch saccharification process.

The literature does not indicate the optimal extract content. It should be as high as possible. In the case of malt obtained from impregnated grain, the extract content was slightly lower, but at further stages of beer production, during beer brewing, the extract content can be increased [29,30]. To produce high-quality beer, the malting industry requires malt with a high extract yield. Brewing barley is the primary raw material used in the production of beer, and its quality is critical. To meet these requirements, the barley must be able to germinate vigorously [33]. The extract is one of the most important malt quality parameters. During the mashing stage, it determines the amount of received soluble solids. The extract content slowly decreases at mash-in temperatures higher than 65 ◦C [34].

Obtaining the wort with the highest extract and the desired pH is the main goal of mashing. The pH value is crucial for the quality of the beverage produced. The lowest extract value was obtained in the wort produced from 100% Special X malt, whereas the highest extract values were obtained from the wort produced from 100% Vienna malt and 100% Melanoidin malt. Surprisingly, the combination of Caramel pils and Special X malt also resulted in the high extract of the wort produced. The use of a mixture of Vienna malt, melanoidin malt and Special X malt resulted in the highest extract of the wort produced from ternary mixtures. The pH values obtained by the researchers were very diverse and ranged from 6.5 to 8.4 [35].

O'Rourke [36] states that the optimum pH of the wort should be 5.6 ± 0.2. Based on the results obtained, the optimal parameters of the wort can be obtained by combining Vienna and Melanoidin malts in a 2:1 ratio.

It is an issue of utmost importance to control the pH value within the desired range in the different phases of beer production. Mash pH is an important factor affecting the isomerization and solubility of α-acids, yeast flocculation, enzymatic activity and extract yield. When it comes to beer, pH affects its flavor (acidity), flavor stability, non-biological stability and biological stability [37].

Both the raw materials at the various stages of beer production and the final product should be tested for pH. Its value has a decisive influence on the taste, prevents the development of microorganisms and is a key factor influencing the maturation of beer, its stability and its durability [38,39].

#### **5. Conclusions**

Based on the obtained research results and their analysis, the following conclusions were formulated:

**Author Contributions:** Conceptualization, L.R.; methodology, L.R.; software, T.G.; validation, L.R. and R.R.; formal analysis, L.R. and R.R.; investigation, M.N. and T.G.; resources, K.V.; data curation, M.N.; writing—original draft preparation, L.R. and M.N.; writing—review and editing, L.R. and R.R.; visualization, M.N.; supervision, L.R.; project administration, L.R.; funding acquisition, L.R. and M.N. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

### *Article* **Use of Unmalted and Malted Buckwheat in Brewing**

**Marius Eduard Ciocan 1, Rozália Veronika Salamon 2, Ágota Ambrus 3, Georgiana Gabriela Codină 1,\*, Ancut,a Chetrariu 1 and Adriana Dabija 1,\***

**Abstract:** With the goal of introducing specialty beers with full flavor and effective processing, craft and functional beer have revived old assortments and established new assortments in countries throughout the world. These unique selections are produced utilizing various ingredient combinations or changes to the brewing process. Given the rise in celiac disease sufferers in recent years, research investigations on the use of buckwheat in brewing, particularly gluten-free beer, have intensified. In this study, malted and unmalted buckwheat were proposed for use in brewing, and the results were contrasted with those of beer made entirely of malted barley. Commercial enzymes were added to the technical mashing process in order to optimize it and increase output yield. It was simple to incorporate buckwheat in the technological process to produce a final product that, in many respects, resembled conventional beer, making buckwheat suitable for regular beer drinkers. In terms of original extract, apparent extract, alcohol content, and energy value, the beer obtained from 100% barley malt differs from the final beer, but only minor variations were found in color, pH, and bitterness value. Ethyl alcohol, a particularly significant distinguishing characteristic, was impacted by the use of buckwheat malt and unmalted buckwheat. The beer made from buckwheat was acceptable from a sensory perspective in terms of flavor, aroma, texture, bitterness, etc. The results demonstrate that the researched raw materials can be successfully used in the production of beer, both in malted and unmalted forms. For the latter option, it is recommended to use enzyme preparations to speed up the mashing and filtration of the wort.

**Keywords:** gluten-free beer; buckwheat; malted buckwheat; brewing; beer properties

#### **1. Introduction**

Beer production is a well-established sector with a long history. It is currently the third most consumed beverage worldwide, behind tea and water, and the most popular alcoholic beverage [1–5]. Consumers today seek out authentic, original products made from ingredients that give the completed product a distinct flavor and a touch of uniqueness [6–8]. The addition of new ingredients represents a constant challenge for the beer industry, through creativity and innovation, responds to the changing demands of consumers [4,9,10].

The traditional ingredients for beer are barley malt, water, hops, and yeast. Unmalted cereals, pseudocereals, and possibly exogenous enzymes may also be used [11–13].

The beer market is continually expanding, and producers use new raw materials in the both malted and unmalted forms to make new varieties of beer, such as other grains such as sorghum, corn, rice, and millet, as well as pseudocereals such as buckwheat, amaranth, and quinoa [8,14–16]. Every raw material is different, and its composition qualities can add a new sensory element and have both favorable and unfavorable effects on brewing. Currently, it is thought that between 85 and 90 percent of the world's beer production uses

**Citation:** Ciocan, M.E.; Salamon, R.V.; Ambrus, Á.; Codin ˘a, G.G.; Chetrariu, A.; Dabija, A. Use of Unmalted and Malted Buckwheat in Brewing. *Appl. Sci.* **2023**, *13*, 2199. https://doi.org/ 10.3390/app13042199

Academic Editor: Antonio Valero

Received: 6 December 2022 Revised: 3 February 2023 Accepted: 7 February 2023 Published: 8 February 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

locally sourced adjuncts, which, in addition to saving money, provide authentic goods of higher quality with distinct flavors and aromas [8,12,17,18].

In studies on the topic of the production of malts and gluten-free beers, as well as functional beers, buckwheat is one of the pseudocereals that is most frequently cited as a raw material because it has consistently demonstrated outstanding results in terms of productivity, enzymatic activity, and chemical composition of the final product [13,19,20]. For the production of biscuits, snacks, pasta, and other food items, as well as bakery, pastry, and confectionery products, buckwheat is frequently utilized in the food industry as flour or grits. Without gliadin and glutenin (gluten-generating proteins) in their composition, it is used as a source of protein for products designed for patients with celiac disease [9,13,19].

The method of brewing using unmalted and malted buckwheat has been the subject of several studies: Wijngaard et al. (2005, 2006) have published results of their own research on the optimization of the process of malting buckwheat and brewing from unmalted and malted buckwheat [20–22]. Phiarais et al. (2010) obtained a beer from 100% buckwheat malt with characteristics such as wheat beer in terms of pH, nitrogen content, degree of fermentation, and alcohol content [23]. Duli ´nski et al. (2019, 2020, 2021) studied the use of different enzymes in the technology of buckwheat beer production [24–26]. Brasil et al. (2020) showed that unmalted buckwheat could be used as a beer adjunct in association with barley malt in proportion a 45–55% (m/m) [19]. According to Cela et al. (2022), brewing with 40% unmalted buckwheat created a final product with acceptable quality attributes [18]. It was discovered that the physico-chemical composition and sensory qualities of the final product are all impacted by the use of this raw material in brewing. Because of this, buckwheat contains a higher level of proteins and polyphenols of significant importance that can generate noticeable variations in the final beer [19,27,28].

Researchers who malted buckwheat came to the conclusion that the malt's amylolytic activity was lower than that of barley malt [13]. The ability of amylolytic enzymes to hydrolyze non-fermentable starch into simple carbohydrates makes them essential for the brewing process [29]. Buckwheat malt also displayed a low percentage of fermentable carbohydrates in wort and a high friability when compared to barley malt. Exogenous enzymes may be used to promote starch breakdown and boost alcohol content to correct this issue [19,30]. On the other hand, malting requires a lot of energy. Thus brewing with a proportion of non-malting adjuncts has grown in appeal. As a result, the use of buckwheat as an unmalted adjunct in brewing has also been investigated in order to enable the creation of novel products with particularly desirable properties [31]. Since these enzyme systems are activated and generated during the malting process, the biggest disadvantage in terms of processability when including unmalted buckwheat is the decrease in enzyme activity (amylolytic, proteolytic, and cytolytic) [31].

The quality of beer made entirely from buckwheat malt has shown promise in research to date, but further research is required to optimize the malting and brewing processes. Additionally, the physicochemical and sensory characteristics of final buckwheat beer as well as buckwheat malt, have not been thoroughly studied [32]. The aim of our research was to use buckwheat grown in our country to produce a variety of gluten-free beers because making beer from unmalted and malted buckwheat is a novelty in Romania.

This study's objective was to evaluate the effects of using unmalted and malted buckwheat on the physicochemical and sensory properties of wort and beer samples. The results were compared to those of beers made entirely with barley malt.

#### **2. Materials and Methods**

#### *2.1. Raw Materials*

Buckwheat (*Fagoporium esculentum*) grown in the NE part of Romania from the 2020 harvest and buckwheat malt from the Pennsylvania Craft Malt, USA, were used in the experiments. For the comparative study, barley from the 2020 harvest and Pilsner-type barley malt from Slovakia from the Osivo Company (Zvolen, Slovakia) were used.

Also, to obtain the beer in laboratory conditions, Amarillo Yachima Chief hops (Yakima, WA, USA), 2019 harvest, Fermentis brewer's yeast type 74/30 (Marquette-lez-Lille, France), and enzyme preparation from the Novozyme Company (Bagsvaerd, Denmark), namely Termamyl Classic with thermostable α-amylase, were used.

The raw materials used in the manufacturing recipes were initially weighed, mixed, and then subjected to grinding.

#### *2.2. Obtaining Beer in Laboratory Conditions*

All the mash samples were obtained in Mash Bath R12 with PC connection (1-CUBE, Havlíckuv Brod, Czech Republic) according to EBC method 4.5.1. (Analytica EBC, European Brewery Convention, 2004) [33]. Physical and chemical analyses of wort produced by the Congress method (for samples of barley malt) and the modified Congress method (for samples of buckwheat malt) were used to determine the quality of the malt. The initial variants of the tested brewing recipes are depicted in Table 1, with variant 0 representing brewing with 100% buckwheat malt. The proportion of unmalted buckwheat used in these experiments ranged from 0 to 30%, while buckwheat malt made up the difference up to 100% (70–100%). The enzyme Termamyl Classic proportions from Table 1 were added based on recommendations from the specialized literature and industrial experience (the ideal amount of the enzyme used industrially when producing beer from unmalted and malted barley and barley is 2%). The enzyme was added at the beginning of the mashing at a temperature of 35 ◦C.

**Table 1.** Variant mashing recipes used in experiments.

The variants shown in Table 2 were suggested for the manufacturing of beer based on the preliminary findings obtained for the mashing recipes described in Table 1.

**Table 2.** Experimental variants of obtaining beer in laboratory conditions.

The proposed brewing recipes were developed using knowledge from both the specialized literature and the author's own experimental brewing results. These buckwheat beers (B1, B2, B3, B4) obtained were compared with beer obtained exclusively from 100% barley malt (CS).

All laboratory experiments, both for mashing variants and for beer production, had been repeated at least three times.

#### 2.2.1. Mashing

The malt and buckwheat samples were subjected to milling with a laboratory disc mill (the gap between the grinding discs 0.20 mm) type Perten LM 3310 (Cheltenham, UK). The Congress method was applied to the barley malt (EBC method 4.5.1) (Figure 1) [33]. The

modified Congress method, shown in Figure 2, has been used with buckwheat malt and buckwheat as an unmalted ingredient [22].

**Figure 1.** Congress mashing.

**Figure 2.** Modified Congress mashing.

The saccharification rate was determined with a negative iodine test—a yellow color is produced with iodine rather than a violet color. After keeping variant 0 at 72 ◦C for 60 min, the sample with 100% buckwheat malt did not become saccharified.

This experiment's findings suggest that using enzyme preparations to shorten the duration of saccharification of mash should be tried. Finding the right amount of enzyme for brewing needed more investigation.

#### 2.2.2. Mash Filtration

After mashing, the contents of each mash beaker were brought to 450 g with distilled water, followed by homogenization and separate filtration through a folded filter (Sartorius with diameter 290 mm, 1602 N grade). The first 100 mL of wort was returned to the filter to give a high clarity of the obtained Congress wort. Before boiling, the quality characteristics of the wort were separately determined.

#### 2.2.3. Wort Boiling

The obtained Congress wort from three mash beakers (2–2.2 L) was boiled with hops (1.52–1.54 g Amarillo hops with 7.8% alpha bitter acids) in Erlenmeyer flasks for 1 h. The aimed wort bitterness was 20 IBU. After boiling, the wort (1.5–1.7 L) was cooled to 20 ◦C and left to rest for 30 min in order to allow sedimentation of the hot tub and decanted into glass fermentation vessels with a capacity of 2 L equipped with CO2 exhaust valves. Before inoculation with yeast, the wort was analyzed.

#### 2.2.4. Fermentation

After cooling to 12 ◦C, the wort (1.5 L) was inoculated with 25 g of yeast type 74/30 Fermentis, the quality of which was previously determined using the Nucleocounter YC-100 (ChemoMetec A/S, Allerod, Denmark), the number of total cells being 24 × 108/mL biomass, of which dead cells 1.42%. The primary fermentation took place in glass fermentation vessels type Erlenmayer (Brand with 2 L volume) to 12 ◦C for 6 days, in an industrial refrigerator with the possibility of digital regulation, after which the young beer was bottled and subjected to secondary fermentation and maturation for 30 days at 4 ◦C in the same refrigerator industrial. Each beer recipe was repeated three times.

#### *2.3. Methods of Analysis*

#### 2.3.1. Analysis of Raw Materials and Wort

The raw materials and wort properties were determined for the barley and buckwheat samples according to the standard procedures of the latest versions of Analytica EBC by the European Brewery Convention. The moisture (EBC 4.2) [34], foreign matters (EBC 4.22) [35], saccharification rate and filtration speed (EBC 4.5.1) [33], the color of wort (EBC 4.7.1) [36] and free amino nitrogen in wort (FAN, EBC 8.10.1) [37] with spectrophotometer Hach Lange DM 6000 (Hach Lange GmbH, Düsseldorf, Germany); pH of wort (EBC 8.17) WTW Inolab 720 table pH meter (Xylem Analytics, Ingolstadt, Germany) [38], original extract (EBC 8.3) [39], extract of malt, Congress mash (EBC 8.2.1) [40], fermentability, final attenuation of laboratory wort from malt (EBC 4.11.2) [41] with Anton Paar Alex (Anton Paar Austria 158 GmbH, Graz, Austria); Total nitrogen of malt (EBC 4.3.1) [42], soluble nitrogen of malt (EBC 4.9.1) [43], with Velp Scientifica UDK129 (Velp Scientifica Srl, Usmate, Italy).

Each mashing, a beaker was made for analytical determination, and the result presents the mean and standard deviation. The determinations from the same sample were performed in triplicate for analysis, and the mean values were used in this report.

#### 2.3.2. Analysis of Beer

For the final beer, the following physico-chemical analyses were performed according to the standard procedures of the latest versions of Analytica EBC by the European Brewery Convention: the original extract and density (EBC 9.43.2) [44], the alcohol content (% *v*/*v*, % m/m; EBC 9.2.1) [45], turbidity, turbidity S25/S0, turbidity S90/S0; EBC 9.29) [46], pH (EBC 9.35) [47], CO2 content (EBC 9.28.3) [48], O2 content (EBC 9.37.1) [49], calories kJ/100 mL (EBC 9.45) [50] Anton Paar modular DMA meter (Anton Paar Austria 158 GmbH, Graz, Austria), color (EBC 9.6) [51] and bitterness (EBC 9.8) [52] with spectrophotometer Hach Lange DM 6000 (Hach Lange GmbH, Düsseldorf, Germany).

Three determinations from the same sample were performed in parallel for analysis, and the mean value was used in this study.

#### 2.3.3. Sensory Analysis

The sensory analysis of the beer samples was conducted with the help of a semi-trained panel of 54 evaluators. A 9-point hedonic scale was used to evaluate the beer samples from 1 to 9, where: 1—dislikes extremely, 5—neither like nor dislike, and 9—like extremely. Nine attributes were evaluated for each beer sample as follows: appearance, color, aroma, general taste, bitterness, carbonation, body, mouthfeel, and general acceptability. The test was performed in the Sensory Analysis Laboratory of the Stefan cel Mare University of Suceava, Faculty of Food Engineering. Approximately 70 mL of beer samples coded with three-digit numbers were served to the panelists in random order at 8 ◦C in glass cups. Between samples, the panelists used unsalted crackers and water to cleanse their mouths to reduce taste transfer from one sample to another. The tasting area and equipment were in concordance with EBC 13.2 [53].

#### 2.3.4. Statistical Analysis

The results were the mean of three values ± standard deviation. For the statistical evaluation of the data, we performed a one-way analysis of variance (ANOVA) and Tukey's HSD test for multiple comparisons. The differences between the means were considered statistically significant for *p* values ≤ 0.01. The data showing the variation of beer parameters according to the various levels of buckwheat flour and buckwheat malted flour were plotted using the design of experiment software (DOE) (Design Expert, trial version, Stat-Ease, Inc., Minneapolis, MN, USA). Using Microsoft Excel, the evaluators' mean value of the sensory data was graphically represented (Microsoft, Redmond, WA, USA). Principal component analysis (PCA) was performed using the software XLSTAT (version 2020.3.1., Addinsoft, Paris, France) to underline the correlations and differences between sensory and physicochemical characteristics of beers and their variability according to these variables.

#### **3. Results and Discussion**

#### *3.1. Evaluation of the Quality of Buckwheat and Buckwheat Malt*

The first step in assessing the potential of buckwheat as an unmalted raw material and buckwheat malt in brewing was their analysis. In Table 3, the raw materials, unmalted buckwheat, and unmalted barley, are compared in terms of their quality attributes.

**Table 3.** Results of the physico-chemical evaluation of the unmalted barley and buckwheat samples used in the experiments.

Results represent mean values ± standard deviation (SD), *n* = 3.

It is seen that the moisture content of buckwheat grains (10.63%) is lower than the moisture content of barley grains (11%). This is a small difference and may be due to transport and storage conditions. The content of foreign matter is double in buckwheat compared to barley, which can be explained by the fact that the buckwheat came from a small producer who did not have the equipment to clean it, but this does not mean that if controlled quality buckwheat from a large producer is used, the losses will be of this magnitude.

The starch content is higher in buckwheat (67%) compared to barley (62%), which will contribute to obtaining a malt with a higher extract content. In the specialized literature, the content of starch varies between 62–91%; and the content in starch for barley varies between 52.10–69.08%. The low used buckwheat content of starch can be explained by the fact that the starch content is influenced by variety, production area, and crop year [13,14,16]. Correlated with the high content of starch, the two raw materials have a lower content of protein substances, namely barley 10.8%, and buckwheat 11.3%, which will be beneficial to the malting process. The results obtained for buckwheat are consistent with those of the studies conducted by Bobkov, S. (2016), Pirzadah et al. (2020), and Huda et al. (2021) [54–56]. Table 4 summarizes the quality characteristics of buckwheat malt and barley malt used in the study.

**Table 4.** Physico-chemical characteristics for barley malt and buckwheat malt.

Results represent mean values ± standard deviation (SD), *n* = 3.

A traditional malt analysis can be subdivided into five key groups: starch conversion, carbohydrate conversion, extract content, color, and enzyme potential. Malt analysis guides the brewer in many ways by advising them on how to adjust the mashing or grinding conditions in order to prevent challenges in the technological process [57]. The obtained buckwheat malt presents comparative values with barley malt in terms of moisture and pH of the wort, with lower values being recorded for the content in the extract and the Kolbach Index. Given that the durations of saccharification and filtration were substantially longer than they were in the case of barley malt, it was suggested that enzyme preparations be used in the experiments in order to shorten these durations. Wijngaard et al. (2005) explained that due to the botanical differences between barley and buckwheat, enzyme production and, therefore, the malting process would differ, and the finished malt product would have some different physicochemical characteristics [20]. It is well known that barley is a monocotyledonous plant, and buckwheat is a dicotyledonous plant. The levels of amylolytic activity and, therefore, the yield in the extract is low compared to barley malt, but the brewing process can be optimized by adding commercial enzyme preparations [19,54]. For example, Nic Phiarais et al. (2006) showed that the addition of commercial enzyme preparations improved the filtration process and the quality of buckwheat beer by increasing extract content, yield, and total fermentable extract [58]. These effects were also obtained by Wijngaard & Arendt (2006), who developed a mashing diagram for 100% buckwheat malt by perfecting the two important parameters, temperature, and mashing time [13,22]. Myncke E. et al. (2022) investigated additionally, 40% of unmalted buckwheat mashes' lautering was enhanced by grinding the unmalted buckwheat more finely or by adding brewing enzymes, which contain α-amylase, protease, and β-glucanase. Finally, the small-scale lautering of 40% unmalted buckwheat mashes was enhanced by the addition of other enzyme solutions (β-amylase and β-glucanase). The mash filtration was unaffected by protease, in contrast [59].

#### *3.2. Experimental Brewing with Buckwheat Malt and Buckwheat*

At the start of brewing, the ground ingredients were mixed with water to form the mash. During the gradual increase in temperature (infusion mash), the enzymes in the malt and those added according to the recipe broke down the complex compounds into smaller molecules [60]. The saccharification rate indicator is a general measure of malt starch degradation, dependent on the activity of amylolytic enzymes in the mash. It is known that a particularly important factor in starch decomposition is its gelatinization temperature [60]. Giménez-Bastida et al. (2015) reported that gelatinization temperatures of buckwheat malts ranged from 65.76–67.12 ◦C [61].

The values of the determinations made on the resulting wort for all eight variants of brewing recipes studied are summarized in Table 5. Variant 0 is missing from Table 5 because the parameters are presented in Table 4 under the name of buckwheat malt.

**Table 5.** Physico-chemical properties of Congress wort for mashing variants.

Results represent mean values ± standard deviation (SD), *n* = 3.

The duration of saccharification for each of the versions examined, independent of the amount of buckwheat malt used, was found to be 5 min during the experiment, with the exception of variant 8 (utilizing 100% buckwheat malt and 2% Termamyl enzyme), for which the duration of saccharification was 10 min. Following the mashing, the EBC method called for cooling the mash to 20 ◦C and adding water up to a weight of 450 g. The duration of filtration depends on the composition of the raw material, the content of β-glucans, other fibers, high molecular weight proteins, starches, and the viscosity of the mash. In studies of unconventional brewing raw materials or adjunct additives, a significant increase in the viscosity of the wort was seen, resulting in a longer filtration than when using barley malt or wheat malt [30,62]. Also, β-glucans can decrease the yield in the extract and lead to an increase in the risk of turbidity of the finished beer [30]. In this case, the specialized literature recommends the use of exogenous enzymes (β-glucanase) that allow the decomposition of β-glucans [18,63]. Recent studies showed very low levels of β-glucans for alternative cereals and pseudocereals [16,59]. The most important indicator of malt, which affects the efficiency of beer production, is the extract yield. The obtained results showed that buckwheat malt and unmalted buckwheat could be used to obtain beer. In other studies, for buckwheat malt, the mean extract yield levels were around 65% compared to 80% for the control sample (barley malt) [22]. Comparable results were obtained by Phiarais et al. (2006), who obtained an extract yield between 61.8% and 69.2% [58]. Moreover, the research conducted emphasizes the fact that the wort obtained from buckwheat and buckwheat malt presented low fermentability values and high levels of viscosity compared to the wort obtained from barley malt [22,23,64]. The color of the wort presented close values for all eight variants; the lowest value was recorded for variant 1 (7.54 EBC), and the highest value was presented by variant 5 (8.36 EBC). All variants showed higher values for color than barley malt (3.1 EBC, shown in Table 4). The pH for all variants studied showed close values in the range of 6.07–6.16, while the pH of barley Congress wort varies from 6.00–6.10, which shows that pH does not seem to have an important influence on beer quality. Lowering the pH of the wort is beneficial because many processes occur faster and better at lower pH [60]. For instance, the pH level affects the mash's viscosity, enzymatic decomposition processes, the solubilization of proteins, bitter hop compounds, and the color of the boiling wort. The pH of the wort and that of the beer produced from it are correlated. Beers with high pH values are exposed to physico-chemical disturbances due to insufficient protein coagulation during boiling. Although variant 8 showed higher values for saccharification rate and filtration speed, no considerable differences were observed for the other parameters at variants 2–7. We considered that increasing the percentage of the enzyme (3–5%) will not lead to a significant increase in extract, so from an economic point of view does not make sense. For this reason, we chose the beer recipes presented in Table 2. because we wanted to see how the mixtures of unmalted buckwheat and buckwheat malt would behave by adding only 2% Termamyl enzyme.

#### *3.3. Study on the Production of Beer from Buckwheat and Buckwheat Malt under Laboratory Conditions* The physico-chemical parameters of beer wort in all experimental variants are summarized in Table 6.

**Table 6.** Physico-chemical properties of wort for the second experiment.

Results represent mean values ± standard deviation (SD), *n* = 3; Different letters indicate (a, b, c, d) that the result presents significant differences from the control (CS) at *p* < 0.01 level; Different letters indicate (A, B, C, D) that the result presents significant differences between the variants (B1, B2, B3, B4) at *p* < 0.01 level.

It is seen that, compared to the control sample (CS), the four experimental samples have close values in terms of wort pH, total nitrogen, and apparent degree of fermentation. Significant differences were obtained in saccharification rate, filtration speed, extract content, wort color, extract yield, soluble nitrogen, Kolbach index, and FAN. Between the variants, the saccharification rate, pH, and total nitrogen content are not had significant differences (at *p* < 0.01 level). The filtration speed is the best in B4 (1:1, unmalted buckwheat:buckwheat malt with 2% Termamyl enzyme). These data show that unmalted buckwheat has a positive effect on speed filtration. This variant shows smaller extract and extract yield, FAN content, and apparent degree of fermentation. Cela et al. (2022) showed that the yield in the extract depends on the chemical composition of the raw materials, mainly on the content of sugars and dextrin, and also on the content of nitrogenous compounds [18]. Comparing buckwheat malt to other gluten-free malts, Buiatti et al. (2018) found that buckwheat malt produced the highest extract yields for beer (40%) [65]. For this parameter, we achieved higher values between 61.53% and 64.33%. The latter is an important source of nutrition for yeast during fermentation and influence the physical and sensory properties of beer, such as colloidal stability, foam stability, and flavor profile [66]. The total nitrogen content of the wort will depend on both the raw materials used during brewing and the parameters of the brewing process [67]. The results obtained are consistent with those highlighted in other research carried out on unmalted buckwheat and buckwheat malt as raw materials in the beer industry [18,65,68]. The wort obtained was subjected to the boiling process with hops. The physico-chemical characteristics of wort after boiling with hops are summarized in Table 7.

After 60 min of boiling the samples with hops, a slight decrease in pH was observed compared to the same samples before boiling. The extracted content increased in B1, B2, B3, and B4 samples as a result of the boiling operation due to water evaporation. Compared to the wort obtained from barley malt, where the content in the extract increased after boiling to the value of 11◦P, all four wort samples had the content in the extract lower, between 11 and 12◦P. To improve the extracted content of wort, Cela et al. (2022) propose the gelatinization of unmalted raw materials during brewing [18]. Boiling led to an increase in color of all tested buckwheat samples from about 7–8 EBC to 11–12 EBC. After cooling to 12 ◦C, the wort was

inoculated with yeast. The primary fermentation lasted 6 days, after which the young beer was bottled and subjected to secondary fermentation and maturation for 30 days. The final beer presented the physico-chemical characteristics displayed in Table 8.

**Table 7.** Physico-chemical properties of wort after boiling.

Results represent mean values ± standard deviation (SD), *n* = 3; Different letters indicate (a, b, c, d) that the result presents significant differences from the control (CS) at *p* < 0.01 level; Different letters indicate (A, B, C, D) that the result presents significant differences between the variants (B1, B2, B3, B4) at *p* < 0.01 level.

**Table 8.** Physico-chemical characteristics of beer final product.

Results represent mean values ± standard deviation (SD), *n* = 3.

Insignificant differences were found in color, pH, and bitterness value. However, the beers obtained by the four variants differ from the control sample in terms of original extract, apparent extract, alcohol content, and energy value. The amount of ethyl alcohol, a crucial distinguishing factor, was influenced by utilizing buckwheat malt and unmalted buckwheat. Beer color is a consequence, among others, of products resulting from the Maillard reaction between FAN compounds and reducing carbohydrates [60]. In the study conducted by Steiner et al. (2012), a higher FAN content in 100% barley malt caused an increase in beer color due to the Maillard reaction [69]. The results obtained are in accordance with those obtained by Agu et al. (2012) and Deng et al. (2019) in their works [66,70]. For example, a study realized by Deng et al. (2019) concluded that doubling the amount of buckwheat malt as a brewing adjunct (from 20% to 40%) led to a further increase in beer color to approximately 5.1 EBC [66]. The bitter value of buckwheat beer decreased slightly compared to that of 100% barley malt beer. These differences may be due to evaporation losses when boiling the wort with hops. Because the same hopping regime was used, the isohumulone content was similar among the four varieties. The estimated global overall influence of unmalted buckwheat and buckwheat malt on the original extract, apparent extract, alcohol content, and density of the beer is shown in Figure 3.

**Figure 3.** The graphical representations of the original extract (**a**), apparent extract (**b**), alcohol content (**c**), and density (**d**) as affected by the levels of unmalted buckwheat and buckwheat malt used in the beer recipe.

When the amount of unmalted buckwheat in the beer recipe is increased, the original and apparent extract of the beer rises; however, when buckwheat malt is added in large quantities, it falls. The beer's extract concentration is a significant qualitative indicator of it. Nitrogenous substances and carbohydrates make up the majority of their composition. The data obtained regarding the content in the extract are unexpected, and we believe that this aspect is due exclusively to the enzyme used in the mashing process (Termamyl classic). Besides these, the beer extract also contains glycerine, mineral substances, bitter substances, tannins, dyes, and organic acids. During the fermentation of wort, the alcoholic fermentation of carbohydrates takes place with the formation of ethyl alcohol and carbon dioxide. By transforming the sugars into alcohol, the density of the wort decreases, and that way, the dynamics of the fermentation can be checked by measuring the concentration of the wort extract.

A graphical representation of the beer turbidity and carbon dioxide levels is shown in Figure 4.

**Figure 4.** The graphical representations of the beer turbidity (**a**), turbidity S25/S0 (**b**), turbidity S90/S0 (**c**), and carbon dioxide (**d**) as affected by the levels of unmalted buckwheat and buckwheat malt used in a beer recipe.

All turbidity readings followed a similar trend, with values falling as unmalted buckwheat malt addition levels increased. This may be explained by the fact that unmalted buckwheat contains more soluble nitrogen and polyphenolic tannins than malted buckwheat and is, therefore, more protein-rich, favoring the appearance of a beer with a higher turbidity value [71]. Proteins and other particles smaller than 1 μm, which are measured under 90◦ and shown in Figure 4c, scatter light predominantly. The majority of forwardscattered light is caused by particles larger than 1 μm, such as diatomaceous earth and yeast, which are measured under 25◦ and are shown in Figure 4b. Since our samples were analyzed in an unfiltered form, the greater turbidity S25/S0 values can be explained. Brewing with raw materials with a high Kolbach Index (which is higher for wort with high levels of unmalted buckwheat than for those with a high level of buckwheat malt), causes an increase in turbidity of the beer [18]. The absence of a malting process for buckwheat will lead to a decrease in its proteolytic activity. Therefore, when unmalted buckwheat is used in brewing as a partial replacement for buckwheat malt, there is a decrease in low-molecular nitrogen compounds and protein content, preventing haze formation. The carbon dioxide content of the beer samples varies between 4.36–4.49 g/L, while the control sample (CS) had 5.12 g/L. The absorption capacity of carbon dioxide in beer is influenced

by its composition, especially by the colloid's distribution with a high contact surface [72]. For instance, some protein macromolecules may be important in stabilizing carbon dioxide, which appears to occur more frequently in malted flours [73].

Figure 5 shows the values of pH, color, bitterness, and oxygen content according to the various proportions of unmalted and malted buckwheat used in the beer recipe. There is no conclusive trend in color, pH, bitterness, and oxygen values depending on the dose of malted or unmalted buckwheat used. Bitterness is a cause of α-acids isomerization from hops during boiling. No definite trend based on the brewing recipe was seen because the identical hopping regime was followed for the manufacture of all beers. Similar findings were also reported by Phiarais et al. (2010), who came to the conclusion that the color of the beer made from buckwheat malt was likely similar to that of beers made from natural grains because no significant changes between malted and unmalted buckwheat grain were seen [23]. Since all laboratory-scale productions employed the same brewing regime, the pH and oxygen content readings were comparable across beers.

When creating products that live up to consumer expectations, sensory analysis plays a key role. As a result, studies exploring the addition of nutritious functional ingredients such as buckwheat to conventional recipes are frequently supplemented by evaluations of overall quality, appearance, scent, taste, and texture using standardized techniques involving professional judges or consumer panels. The sensory evaluation of flavor is frequently accompanied by analytical workflows aimed at isolating and determining the concentration of volatile compounds in food and determining the impact of food components on overall flavor intensity and/or final product perception. Flavor is of particular importance in influencing consumer preferences [74,75]. The sensory analysis data are shown in Figure 6.

The CS sample earned the greatest for overall acceptability, whereas the B2 sample scored the lowest, according to the data collected. All of the beer samples were enjoyed to a certain extent by the panelists. The CS, B1, and B4 samples obtained a like very much score of 8.1, 7.8, and 7.6, respectively, whereas the B3 and B2 samples obtained a mean like moderate score of 7.0 and 6.6, respectively. These results are consistent with those found by Sebestyén et al. (2013), who determined in the sensory analysis that the buckwheat beer had the aroma of roasted sunflower seeds and a chestnut-like aroma and was positively evaluated by the tasters [76]. Also, Phiarais et al. (2005) have reported that buckwheat beers were acceptable regarding taste purity, odor, mouthfeel, bitterness, and tingling [77]. The sensory characteristics that contributed to the general acceptability varied depending on the recipe for beer making. The best sensory results were obtained for the CS sample. However, for the color parameter, gluten-free beer samples obtained better sensory results. These data were in disagreement with those obtained by Brasil et al. (2020) who reported a paler beer with an increased level of buckwheat malt addition in the beer recipe [19]. From non-gluten beer samples, the highest acceptability was recorded for B1 samples which contained the highest level of buckwheat malt in its recipe. These data were in agreement with those reported by Dezelak et al. (2014), who concluded that beer from buckwheat malt has high scores from the sensory point of view [78].

**Figure 5.** The graphical representations of the beer pH (**a**), color (**b**), bitterness (**c**), and oxygen (**d**) as affected by the levels of unmalted buckwheat and buckwheat malt used in the beer recipe.

**Figure 6.** Sensory characteristics of the beer samples.

#### *3.4. Principal Component Analysis of the Physico-Chemical and Sensory Characteristics of the Beer Samples*

Principal Component Analysis (Figure 7) highlighted the correlation between physicochemical data and sensory characteristics of the beer samples. The first two principal components explain 69.47% of the total variance (PC1 = 37.82% and PC2 = 31.65%). The PCA graph shows a clear distinction between the beer samples in terms of their physiochemical and sensory properties. Beer made from malted barley (CS) is positioned on the graph's right side among the sensory qualities, indicating that these qualities are crucial to understanding how to appreciate it. These characteristics have a high association with this sample since, based on previously collected data, this beer was the one that consumers liked the most. These samples had a similar score for overall acceptability from consumers and were the most well-liked non-gluten beer. Due to the fact that all of the B1, B4, and CS samples are alongside the PC2 component on the PCA graph, these samples were also the closest to a malted barley beer from a sensory and physico-chemical perspective. The placement of B2 beer in the primary component area indicates that it is the most distinctive from the other beers, with this sample receiving the lowest consumer approval.

**Figure 7.** Principal component analysis of the physicochemical and sensory characteristics of the beer samples.

B2 and B3 are both samples that are most closely related to the PC2 component of the PCA graph, and both are located near the top of the graph. This result is consistent with the observation that both the B3 and B2 samples received similar levels of consumer appreciation based on our prior research. Relationships between physico-chemical and sensory values of beer samples show that is a good correlation between original extract and alcohol content with an r = 0.962, between body and original extract with an r = 0.968 between appearance and color (r = 0.877), between alcohol content and energy value (r = 0.999) for a level of 0.01. The original extract is one of the most important parameters from a financial point of view. This serves as an indicator of the amount of dry matter in the wort used to make the examined beer. This will have an impact on the beer's body, which consumers will feel as being heavier or denser on the tongue [18]. Also, with respect to the first principal component PC2, it may be seen direct positive correlations between body and density (r = 0.625), original extract (r = 0.968), and alcohol content (r = 0.917). During alcohol fermentation, chemical reactions take place, which transforms fermentable sugars into alcohol and carbon dioxide. Therefore, the higher the quantity of real extract is, the higher the alcohol content is. The highly significant correlation between energy value, alcohol content (r = 0.999), and original extract (r = 0.949) may be explained by the fact that the energetical value of a beer is calculated according to its alcohol content and original extract value [79]. The two plots underline a close association between the physico-chemical trait carbon dioxide and sensory carbonatation (r = 0.942) which was explainable given that beer carbonatation is experienced as a burning and stinging sensation on the tongue, being influenced by the amount of carbon dioxide and the size of the bubbles [18]. Other notable correlations were found between sensory characteristics such as general acceptability, general taste, aroma, mouthfeel, and bitterness, as well as between the measured sensory bitterness and the analytically determined bitterness characteristics (r = 0.884). In evaluating the sensory quality of beer, the highest rating was the taste and its impact on the consumers [80]. The sensory quality of beer taste is correlated to some extent with all the elements strongly associated with general acceptance (aroma, mouthfeel, bitterness).

#### **4. Conclusions**

The technological method of making beer from buckwheat and buckwheat malt is effortless, and the final product is essentially equivalent to a standard beer in many ways, making buckwheat a potential raw material for habitual beer drinkers who are looking for new sensory experiences.

The different fermentation profile for buckwheat beer with a higher first concentration of glucose is crucial for alcohol and other fermentation products, positively changing its aroma and taste. However, its high content of polyphenolic compounds can cause a slightly astringent taste and a spicy and sweet aroma appreciated by tasters.

The beer made with 50% unmalted buckwheat and 50% buckwheat malt with 2% Termamyl Classic enzyme had the best results out of all the studied recipes in terms of the key physico-chemical traits: original extract was 10.65%, apparent extract was 3.13%, alcohol content was 3.97% (*v*/*v*), and turbidity was 1.98 EBC. The sample made entirely of unmalted buckwheat with 2% Termamyl Classic enzyme was the most well-liked from a sensory perspective. We achieved our research objective to create a final beer that had good physico-chemical properties, was well-liked by consumers, and was produced at the lowest cost.

As a result of the findings, it is suggested that in subsequent experiments, beer only be produced from unmalted buckwheat with enzyme addition, which is much more advantageous from an economic and technological standpoint. This is because it is possible to produce beer from buckwheat without it being malted by simply adding enzyme preparations to the brewing process.

**Author Contributions:** Conceptualization, M.E.C., A.D., R.V.S. and G.G.C.; Methodology, A.C., R.V.S. and Á.A.; Formal Analysis, A.C. and A.D.; Investigation, M.E.C., R.V.S. and Á.A.; Resources, G.G.C.; Writing—Original Draft Preparation, A.D., R.V.S., G.G.C. and M.E.C.; Writing—Review and Editing, A.C. and A.D. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Ministry of Research, Innovation, and Digitalization within Program 1—Development of national research and development system, Subprogram 1.2— Institutional Performance—RDI excellence funding projects, under contract no. 10PFE/2021.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available in this article.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

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### *Article* **Comparison of the Spreadability of Butter and Butter Substitutes**

#### **Małgorzata Ziarno 1,\*, Dorota Derewiaka 2, Anna Florowska 3 and Iwona Szyma ´nska 4**

**Abstract:** There are many types of butter, soft margarine, and blends, e.g., a mixture of butter and vegetable fats, on the market as bread spreads. Among these, butter and blends of butter with vegetable fats are very popular. The consumer's choice of product is often determined by functional properties, such as texture, and the physicochemical composition of butter and butter substitutes. The aim of this study was to compare sixteen market samples of butter and butter substitutes in terms of spreadability and other selected structural (spreadability, hardness, adhesive force, and adhesiveness) and physicochemical parameters (water content, water distribution, plasma pH, color, acid value, peroxide number, saponification number, and instrumentally measured fatty acid profile) to investigate their correlation with spreadability. The parameters determined here were correlated with factors such as the type of sample, measuring temperature, and physicochemical composition. The statistical analysis revealed a very strong positive correlation between hardness and spreadability for all samples tested at 4 ◦C, as well as between hardness and spreadability for all samples tested 30 min after removal from the refrigerator; however, the interpretation of the results was different if the butter and butter substitute samples were subjected to a multivariate analysis separately.

**Keywords:** spreadable fats; texture; hardness; adhesive force; adhesiveness; fatty acid profile; multivariate analysis; functional food

#### **1. Introduction**

Butter is a high-fat product with at least 80%, but no more than a 90% fat content, and it is obtained from cow's milk by whipping previously obtained cream or sour cream. However, the assortment of spreads for bread on the market consists of different types of butter, soft margarine, and blends such as a mixture of butter and vegetable fats. Among the wide range of edible fats, in addition to butter and margarine, products called butter mixtures with vegetable fats are of great interest. All of these edible fats are water-inoil emulsions [1]. The decision as to which fat to consume in spreads can therefore be somewhat difficult for some consumers, since these fats differ not only in their calorific value and therefore in their chemical composition but also in their functional properties, such as spreadability [2–5].

The study comparing the spreadability of butter and butter substitutes makes a significant scientific contribution to the field of food science and technology. Understanding the spreadability of food products is essential, as it plays a critical role in consumer acceptance and product functionality. In order to improve the spreadability of butter, several technological steps are taken, starting with the selection of raw materials with a fixed

**Citation:** Ziarno, M.; Derewiaka, D.; Florowska, A.; Szyma ´nska, I. Comparison of the Spreadability of Butter and Butter Substitutes. *Appl. Sci.* **2023**, *13*, 2600. https://doi.org/ 10.3390/app13042600

Academic Editors: Georgiana Gabriela Codină, Adriana Dabija and Lăcrămioara Rusu

Received: 25 January 2023 Revised: 12 February 2023 Accepted: 15 February 2023 Published: 17 February 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

fatty acid composition, followed by technological treatments, including parameters for the physical ripening of the cream, enrichment with a low-melting-point milk fat fraction or repeatedly churning the butter [6–10]. The spreadability of butter and blends of butter and vegetable fats can be assessed based on the solid fat content (SFC) in the temperature range of 4–10 ◦C. In order to achieve good spreadability at a refrigeration temperature, the SFC of butter should be below 32% (by comparison, pure butterfat has an SFC of 38.8–32.4% at 5–10 ◦C) [6]. In addition, the textural properties of butter are determined by a number of interrelated parameters, such as the concentration, size, shape, and distribution of structural elements: fat crystals, fat globules, air bubbles, and water phase droplets [3,10–19].

Butter and butter substitutes have different physical and chemical properties, and it is important to understand how these differences affect the spreadability of these products. This study can help identify the factors that influence spreadability such as fat content, viscosity, and solid fat content. The scientific contribution and specific significance of the study comparing the spreadability of butter and butter substitutes lies in its potential to improve our understanding of the properties that affect the spreadability of food products and to inform the development of new and improved products for the food industry. A real downside to butter is its hard-to-spread texture. Many authors have attempted to study the spreadability of butter, soft margarine, mixtures of butter and vegetable fats, and shortenings using various instruments such as a penetrometer and texture analyzer (textrometer) with a penetration test, a shear test, a compression test, a texture profile analysis (TPA), DSC methods, EPR spectroscopic methods and the back extrusion test [2,9,11,16,20–31]. The results of such studies can be used to model the relationship between the structure, rheological properties, and textural properties of fat products, taking into account the morphology of the fat crystal network, the solid fat content of the product, and the properties of the fat crystal networks [10].

The aim of this study was to compare market samples of butter and butter substitutes in terms of spreadability and other selected structural, physicochemical, and chemical parameters to investigate their correlation with spreadability. The results of the study can be used to develop new and improved butter and butter substitutes that have similar spreadability characteristics without sacrificing other important properties such as flavor, texture, and nutritional value. In addition, the results of this study can have practical applications in the food industry, helping manufacturers to improve the quality and performance of their products. It can also provide valuable information to consumers to help them make informed choices when buying food.

#### **2. Materials and Methods**

#### *2.1. Materials*

The study material consisted of eight butter samples coded as follows—LMK, LaME, LoME, MEG, MEH, MMP, PME, and PrME—and eight samples of butter substitutes (spreadable fats, consisting of blends of butter with vegetable oils) coded as follows: FM, LuPM, LaM, PaEM, RMTM, SSO, ZaM, and BGP (Table 1).

These products were available in the Polish food market at the time of the analysis.  After purchase, the product samples, packed in insulating bags, were transported to the laboratory within 0.5 h, where they were stored in a refrigerator at 4 ◦C until the analyses were carried out. Three independent purchases of each butter and butter substitute sample were made, representing independent replicates from three different suppliers.

*Appl. Sci.* **2023**, *13*, 2600

**1.**Declaredcompositionandnutritionalvalueoftestedbutterandbuttersubstitute

#### *2.2. Texture Characteristics of Butter and Butter Substitutes*

Spreadability. The tests were performed with a TA.HD.Plus Texture Analyzer (Stable Micro Systems, Toru ´n, Poland). This was measured using penetration analysis with a "spreadability ring" spreadability test unit [31]. During the analysis, the upper cone was inserted into the lower container (in the form of an inverted cone) at a speed of 3 mm/s until a gap of one millimeter was obtained between the two elements of this fixture. All samples were analyzed in triplicate. Samples at 20 ◦C were placed in the bottom reservoir of the attachment without bubbles.

Hardness, adhesive force, and adhesiveness. The tests were performed with a TA.HD. Plus Texture Analyzer (Stable Micro Systems, Toru ´n, Poland). The procedure consisted of testing the penetration force at a depth of 14 mm applied to a given sample at a speed of 2 mm/s using a P/5 cylinder probe [31]. The samples were analyzed at given time intervals: straight from the fridge (at 4 ◦C), 30 min after removal from the refrigerator, and at 20 ◦C for each type of butter sample and butter substitute. All samples were analyzed in triplicate. Hardness was expressed as the maximum force necessary to obtain accurate probe deformation (N). The adhesion force was expressed as the force necessary to overcome the forces of attraction between the surface of the sample and the surface of other materials with which the food came into contact (N). Adhesiveness was expressed as the product of the force required to pull the probe from the sample and the pull time (N × s).

#### *2.3. Physicochemical Properties of Butter and Butter Substitutes*

Water content. The weight loss was calculated by determining the weight of the sample after it was dried with appropriately prepared sea sand and calculating the percentage of water content in the product [32,33]. A sample was dried in a laboratory oven at 102 ± 2 ◦C until a constant mass was obtained. All samples were analyzed in triplicate. Formula (1) used for the calculation was:

$$\text{BW} = 100 - \frac{\text{B} \times 100\%}{\text{A}}\tag{1}$$

where W represents the water content of the sample [%]; A represents the sample weight before drying (g); and B represents the sample weight after drying (g).

Water distribution. The main principle of the method of water distribution in samples is to apply indicator paper soaked with an indicator to the freshly cut sample surface [32,34]. The indicator paper turns dark blue where it meets water droplets. All the samples were analyzed in triplicate. A point scale of 0–3 was used to determine the degree of water distribution, after which the samples were classified using the criteria given in Table 2. The analysis was carried out using commercially available indicator paper (Dysperwod, LABLACTA, Olsztyn, Poland) according to the manufacturer's instructions. This method enables the determination of whether the butter and butter substitutes had been properly kneaded and the water droplets properly dispersed in the butter and butter substitute matrix.

Plasma pH. The determination consisted of melting a 40.0 g weight of the butter or butter substitute sample in a water bath at 50 ◦C, followed by centrifugation in a laboratory centrifuge at 1100× *g* at 20 ◦C for 10 min to separate the aqueous phase (plasma) [32]. The pH of the separated aqueous phase of the butter and butter substitutes was measured with a CPO-505 pH meter (Elmetron, Zabrze, Poland) with a conventional electrode at 25 ◦C. All samples were analyzed in triplicate.

Color. Color components were measured at 3 or 4 locations for each sample using the reflectance method, using a Minolta CR-200 camera (Konica Minolta, Tokyo, Japan) with a D65 illuminant, 2◦ observer angle, and 8 mm aperture size. The parameters measured were lightness (*L*\*), taking values from 0 (black) to 100 (perfect white); redness (*a*\*), taking negative values for green color shades and positive values for red color shades; and yellowness (*b*\*), the proportion of blue or yellow color in the sample, taking negative values for blue and positive values for yellow. All samples were analyzed in triplicate. To determine the color differences between the butter and butter substitutes, they were compared to a predetermined standard. The standard was compared to the average results of the *a*\*, *b*\*, and *L*\* components obtained in the color test. The standard table (Table 3) for comparing the test samples was taken from the publication of Chudy et al. [35].

**Table 3.** The standard table for comparing the test samples was taken from the publication of Chudy et al. [35].

To assess the changes in CIE*Lab* color, a delta E (Δ*E*) calculated according to Formula (2) was used to describe the difference between the two sample colors as follows:

$$
\Delta \mathbf{E} = \sqrt{\left(\Delta \mathbf{L}\right)^2 + \left(\Delta \mathbf{a}\right)^2 + \left(\Delta \mathbf{b}\right)^2} \tag{2}
$$

where Δ*L* is the difference in *L*\* components between the butter standard (Table 2) and the test sample; Δ*a* is the difference in *a*\* components between the butter standard (Table 2) and the test sample; and Δ*b* is the difference in *b*\* components between the butter standard (Table 2) and the test sample.

#### *2.4. Additional Characteristics of Butter Milk Fat*

Determination of the acid value. The tests were only carried out on butter fat samples according to [36]. The procedure consisted of neutralizing the free fatty acids present in the fat sample to be analyzed with a standard potassium hydroxide solution. The 10 g butter sample was weighed to the nearest 0.01 g in a 200–300 mL Erlenmeyer flask. The sample was then melted using a water bath (at 40 ◦C). Then, 50 mL of neutralized alcohol–ether mixture was added to the flask (it was neutralized to phenolphthalein with a KOH solution before use, to a pale pink color that did not disappear within 30 s) and mixed thoroughly. It was further titrated from the buret with a 0.1 M KOH versus phenolphthalein to give a pale pink color which persisted for 30 s. All samples were analyzed in triplicate. The acid number was calculated using Formula (3):

$$\text{LK} = \frac{(\text{a} \times \text{5.611})}{\text{m}} \tag{3}$$

where LK is acid value (mg KOH/g fat); a is the amount of 0.1 M KOH solution used for the titration (mL); m is the sample fat weight (g); and 5.611 is the amount of KOH contained in 1 mL of 0.1 M KOH solution (mg).

Determination of the peroxide number. The tests were only carried out on butter fat samples according to [37]. The method consisted of the quantitative determination of iodine released from potassium iodide by the action of peroxides present in the fat under study. The released iodine was titrated with a standard solution of sodium thiosulphate (VI). Approximately 1 g of butter was weighed to the nearest 0.001 g into an Erlenmeyer flask

with a ground-glass stopper. Immediately, 25 mL of the chloroform–acetic acid mixture and 1 mL of saturated potassium iodide solution were added. The flask was quickly stoppered and mixed thoroughly. It was left in the dark for 5 min. After this time, 75 mL of distilled water was added using a cylinder, the stopper was rinsed thoroughly and a few drops of starch were added; after mixing, the solution was immediately titrated with 0.002 M sodium thiosulfate standard solution until the solution remained discolored for at least 30 s. At the same time, a reagent test was carried out. All samples were analyzed in triplicate. The peroxide number was calculated using Formula (4):

$$\text{LOO} = 1000 \times \frac{(\text{a} - \text{b}) \times \text{T}}{\text{m}} \tag{4}$$

where a is the volume of sodium thiosulphate solution used to titrate the sample (mL); b is the volume of sodium thiosulphate solution used to titrate the reagent sample (mL); m is the sample fat weight (g); T is the molality of the sodium thiosulphate solution used; and 1000 is the conversion factor for the volume used (mL) of sodium thiosulphate per milliequivalent of oxygen in 1 kg of fat.

Determination of the saponification number. Tests were carried out only in butter fat samples according to [38]. The method involved saponification of esterified and neutralized free fatty acids with an excess of potassium hydroxide solution, followed by quantification of unbound KOH by titration with HCl solution. A total of 2 g of butter was weighed to the nearest 0.001 g into a 100 mL ground-glass Erlenmeyer flask. The sample was then melted using a water bath. A total of 25 mL of alcoholic potassium hydroxide solution was pipetted into the sample. An aftercooler was fitted to the flask, and the flask was placed in the water bath for 30 min with occasional stirring. After this time, the aftercooler was removed and the hot solution was titrated against phenolphthalein with 0.5 M hydrochloric acid solution until the indicator color disappeared. If the volume of the solution decreased during heating, it was made up of the original volume with ethanol before titration. At the same time, a reagent test was carried out under the same conditions. All the samples were analyzed in triplicate. The saponification number was calculated using Formula (5):

$$\text{LZ} = \frac{(\text{a} - \text{b}) \times 28.055}{\text{m}} \tag{5}$$

where LZ is the saponification number (mg KOH/g fat); a is the volume of standard HCl solution used to titrate the reagent sample (mL); b is the volume of standard HCl solution used to titrate the sample (mL); m is the sample weight (g); and 28.055 is the amount of KOH present in 1 mL of 0,5 M KOH solution (mg).

Chromatographic determination of the fatty acid profile. Tests were carried out only in butter fat samples according to [39]. The process consisted of separating the components, which were divided into two phases: one was stationary (stationary phase) and the other was moving in a given direction (mobile phase). The different distribution of the mixture components between the two phases leads to different migration and separation speeds of the components. The effect of the chromatographic separation was plotted in the form of a chromatogram, showing a graph of the signal obtained at the detector as a function of time [39].

The evaporated samples were weighed to the nearest 0.001 g and then dissolved in 2 mL of hexane. A total of 0.5 mL of 2 M KOH in methanol was added to the samples and was then shaken and left for a period of 60 min, with stirring every 10 min for transesterification. Using a syringe, 1 mL of the upper hexane layer containing fatty acid methyl esters was carefully collected and transferred to a glass vial. The sample was then evaporated in a stream of nitrogen, and 0.5 mL of hexane was added.

Determination of fatty acids was carried out using a Shimadzu gas chromatograph coupled to a mass spectrometer GC–MS QP-2010S (SHIM-POL, Warsaw, Poland), using a ZB FFAP column (30 m × 0.25 mm × 0.25 μm; Phenomenex, Torrance, CA, USA). The column operating temperature was initially 40 ◦C for 3 min, with a programmed temperature rise at 4 ◦C/min to 230 ◦C, and finally, isotherm for 5 min. The injection chamber and ion source temperatures were 230 ◦C and 240 ◦C, respectively. The carrier gas was helium and the flow rate was 1.14 mL/min. The GC–MS coupler temperature was 225 ◦C. Fatty acid methyl ester analyses were carried out at an ionization energy of 70 eV. The qualitative analysis (of the obtained fatty acid methyl esters) was carried out based on a comparison of the retention times of available standards and spectra. All samples were analyzed in triplicate.

#### *2.5. Statistical Analysis*

Data were analyzed using a one-way or two-way analysis of variance (ANOVA method). Mean differences between the statistical groups were tested at a significance level of α = 0.05. Tukey's test was used for multiple comparisons (statistical ranking) of mean responses to the sample groups (for α = 0.05). Multivariate analysis was used to describe the relationship of multiple variables for each sample (for α = 0.05). The statistical software Statgraphics Centurion XVII (Kraków, Poland) was used to test the data.

#### **3. Results and Discussion**

#### *3.1. Texture Characteristics of Butter and Butter Substitutes*

Research into the texture characteristics of butter and blends of butter with vegetable fats is relevant to consumers because it can provide information about the performance of these products. The texture is an important attribute for many consumers as it affects the ease of use and enjoyment of the product. By understanding the texture characteristics of butter and butter substitutes, consumers can make informed decisions about which products meet their needs and preferences. Research into the texture characteristics of butter and vegetable fat blends can play an important role in helping manufacturers to create high-quality products that meet consumer needs and preferences. By providing valuable information on the texture and performance of these products, manufacturers can ensure that their products are competitive in the marketplace and are well received by consumers.

Spreadability. The ability to spread the bread spread easily is one of its most important properties [22,40]. It is worth noting that the higher spreadability value of the butter and butter substitutes tested, as shown in Table 4, indicated poorer spreadability of the product on the bread. The highest spreadability value was obtained for the butter samples at 4 ◦C. If the butter was left at ambient temperature for 30 min after removal from the refrigerator, these values hardly approached the parameters obtained for butter substitute samples at 4 ◦C; however, for most butter substitute samples, the spreadability value was still statistically significantly better than for the butter samples. The butter samples coded as MEH and PrME were the exceptions. In their case, the spreadability value at 4 ◦C was the lowest of the results obtained for the butter samples, and 30 min after removal from the refrigerator, the spreadability value reached the same level as the butter substitute samples at 4 ◦C. By bringing the butter samples to 20 ◦C, the spreadability value measured reached the value originally obtained for the butter substitute samples at 4 ◦C.

The texture of spreadable fats, and more importantly their spreadability, is one of the most important differentiators when assessing their quality. The spreadability of butter and butter blends containing vegetable fats is determined by their chemical composition—the type of fat used in their manufacture, as well as the ratio of the aqueous phase to the fat phase and the balance between the liquid and crystalline phases [2,17]. The higher the degree of crystallization of the fat, the poorer the spreadability of the butter [17]. The spreadability of butter can be improved, among other things, by changing the fat composition (e.g., changing the diet of the animals from which the milk is obtained) [41]. Bobe et al. [30] found that butter samples from the milk of cows that had a more unsaturated composition of milk fats due to a special diet had better spreadability.

Hardness. Butter samples at 4 ◦C were characterized by a high hardness that was statistically significantly higher than butter substitutes at the same temperature (Table 4). Increasing the temperature of the butter samples resulted in a decrease in their hardness. Thirty minutes after removing the butter samples from the refrigerator, their hardness was already on a similar level to that of the butter substitute samples at a temperature of 4 ◦C. On the other hand, heating the butter samples to 20 ◦C led to hardness parameters comparable to those of the butter substitute samples 30 min after removal from the refrigerator.

**Table 4.** Texture characteristics of butter and butter substitutes.

**Table 4.** *Cont.*

a,b,c,d,e,f,g,h,i—within a given parameter that is labeled with the same letters do not differ statistically significantly at the level of α = 0.05. 1 The analysis of samples under these conditions was not possible.

The high hardness of the butter samples at 4 ◦C can be explained by the higher proportion of saturated fatty acids, which contribute to the hardness and poor spreadability of butter at refrigerator temperatures, which has been confirmed by several studies [2,8,23,30,31,42–46]. Lower temperatures increase the fat solidity; however, it should be noted that both the butter samples and the butter substitute samples differed in hardness, which could indicate that the technological process parameters also determine this product quality parameter [23,44,46–48]. The results of Glibowski et al. [31] highlighted that samples with a high content of milk fat showed a stronger increase in hardness when changing the temperature conditions from room to cooling temperatures compared with samples that were predominantly vegetable fats. The authors concluded that the presence of milk fat promoted an increase in hardness. Queirs et al. [44] found that the hardness of butter depended on the crystallization of the butter at the manufacturing stage and not only on the storage temperature. Rønholt [48]

found that the ratio between solid and liquid fats and the water content strongly influenced the hardness and spreadability of the product. The presence of unsaturated and liquid fats in the composition of butter and vegetable fat mixtures reduces the hardness of these products. The higher the water content, the more the ratio of solid-to-liquid fat shifts in the direction of the liquid phase, so that less fat contributes to crystal formation and thus influences product hardness and water droplet stability. It should therefore be noted that the butter substitutes included in this study were characterized by a higher water content than the butter samples, as is discussed later in this manuscript. With increasing temperature, the firmness and spreadability of the fat products analyzed decreased, i.e., the spreadability improved. The higher the temperature of the product, the more the product structure approaches that of a liquid. This can be caused, among other things, by the water content of the product [48]. As the water percentage increases, the total fat content decreases, affecting the hardness parameter [48]. As has been noted, the higher water content of the butter/vegetable fat blends allowed for a smoother and therefore more spreadable product.

Adhesive force. Adhesive force is the force between the surfaces of two different bodies to hold them together (a food product is perceived as being sticky when the adhesive force is high) [26]. In the case of butter and butter substitutes, this parameter expresses the force that allows the butter or butter substitute to spread evenly over the surface of the bread. Small statistically significant differences in the adhesive force values were found between the butter samples at 4 ◦C. The same observation was applied to the samples of the butter substitutes at 4 ◦C (Table 4). The study showed that market samples of butter had statistically significantly higher adhesion values than samples of the butter substitutes, which could be related to differences in the fatty acid composition of the butter samples and butter substitute samples [31]. As the temperature of the samples of the tested products was increased, changes in the adhesive force values towards a value close to zero were observed. These changes were statistically significant for both butter and butter substitutes as early as 30 min after removing the samples from the refrigerator.

Adhesiveness. Adhesiveness is the work required to separate a product from the surface being tested; its measurement serves to express the adhesive properties by measuring the force needed to separate them. The greater the force required to separate the two, the stickier the product. The data presented in Table 4 show that the adhesiveness of both butter and butter substitute samples was statistically significantly higher, but it was dependent on the product's temperature. The higher the temperature of the butter or butter substitute, the lower the adhesiveness, i.e., the samples were less sticky. For one of the butter substitute samples (coded as FM) raising the product temperature to 20 ◦C made measurement impossible as the sample had already become liquid rather than sticky. It is also worth noting that the butter and butter substitute samples differed in their adhesiveness, and this was statistically significant.

For the butter and butter substitute samples examined in this study, it can be seen that hardness, adhesive force, and adhesiveness were parameters that were partially correlated with spreadability. If their status changed, the spreadability status would also change. Some correlations between the results of measurements of the rheological properties of edible fats were also found by Glibowski et al. [31]. In their study, spreadability and cohesiveness measured at 5 ◦C correlated very well, but spreadability and cohesiveness at 5 ◦C were not very well correlated. The researchers showed a low correlation coefficient between spreadability at 20 ◦C and spreadability at 5 ◦C, and between hardness at 20 ◦C and hardness at 5 ◦C, which very clearly indicates differences in the rheological properties of edible fats at different temperatures. This was also confirmed by the low correlation coefficients between spreadability at 5 ◦C and apparent viscosity at 20 ◦C, and hardness at 5 ◦C and apparent viscosity at 20 ◦C [31].

The statistical analysis performed in this study of the spreadability, hardness, adhesive force, and adhesiveness of the butter and butter substitute samples (Figure 1a,b) revealed a completely different relationship pattern than those found by Glibowski et al. [31]. Figure 1a,b show the corrgrams (i.e., correlation plots) of the correlation matrix, with the colored cells representing the magnitude of the correlation. Correlation coefficients range from −1 to +1 and measure the strength of the linear relationship between variables (statistically significant correlations occur at the 95.0% confidence level). The colors ranged from blue for strong negative correlations to red for strong positive correlations. The interpretation of the results for butter samples and butter substitutes differed when the samples were subjected to separate multivariate analyses. Few strong correlations (whether positive or negative) were observed for the butter samples (Figure 1a) between hardness measurements at specific temperature conditions (correlation coefficients 0.96–0.86); between adhesiveness and adhesive force for samples tested 30 min after removal from the refrigerator (correlation coefficient 0.87); and between adhesiveness and spreadability or hardness for the samples tested at 20 ◦C (correlation coefficients −0.81 and −0.94, respectively).

Significantly stronger correlations (both positive and negative) were recorded for the butter substitute samples. This plot of correlations revealed the following strong positive correlations (Figure 1b): between spreadability and hardness at specific temperature conditions (correlation coefficients 0.89–1.00); between adhesiveness for samples tested at 20 ◦C and adhesive force for samples tested 30 min after removal from the refrigerator or for samples tested at 20 ◦C (correlation coefficients 0.90 and 0.99, respectively); and between adhesive force for samples tested at 20 ◦C and adhesive force for samples tested 30 min after removal from the refrigerator (correlation coefficient 0.87). Strongly negative correlations were no less important and were observed between spreadability and adhesive force for samples tested 30 min after removal from the refrigerator (correlation coefficient −0.93); between spreadability and adhesive force for samples tested at 4 ◦C (correlation coefficient −0.81); between spreadability for samples tested at 20 ◦C and adhesive force for samples tested 30 min after removal from the refrigerator or adhesive force for samples tested at 20 ◦C or adhesiveness for samples tested at 20 ◦C (correlation coefficients −0.85; −1.00 and −0.98, respectively); between hardness and adhesive force for samples tested at 4 ◦C (correlation coefficient −0.92); between hardness and adhesive force for samples tested 30 min after removal from the refrigerator (correlation coefficient −0.97); and between hardness for samples tested at 20 ◦C and adhesive force for samples tested 30 min after removal from the refrigerator or for samples tested at 20 ◦C or adhesiveness for samples tested at 20 ◦C (correlation coefficients −0.86; −1.00 and −0.98, respectively). However, it is important to remember that a high correlation coefficient does not necessarily indicate causality. It simply indicates that the two variables are related in some way. Further investigation and analysis, such as regression analysis, may be required to determine the nature of the relationship and to establish causality.

(**b**)

(**a**)

**Figure 1.** Graphs of correlation matrix showing the relationship between the spreadability, hardness, adhesive force and adhesiveness of butter and butter substitute samples (**a**) and butter substitute samples alone (**b**) measured at different temperatures (with a confidence level of 95.0%).

#### *3.2. Physicochemical Properties of Butter and Butter Substitutes*

Water content. The water contents of the tested butter (Table 5) did not exceed the set limit of 16 ± 0.5% [49,50], were in line with producers' declarations (Table 1), and, importantly, these values were not statistically significantly different from each other at the significance level α = 0.05. Butter substitutes, on the other hand, were characterized by significantly higher water content values (in the studies presented here, the water content of the butter substitutes samples ranged from 17.93 ± 0.35% to 32.97 ± 0.33%), whereby these samples were divided into three different homogeneous groups with a significance level of α = 0.05.

**Table 5.** Physicochemical properties of butter and butter substitutes.

a,b,c,d,e—values in the same column and marked with the same letters are not statistically significantly different at the α = 0.05 level.

Butter and butter substitutes are physically composed of fat globules, fat crystals, air bubbles, and water droplets, all of which play a role in the physical properties of these products [51,52]. The physical and chemical properties of butter and butter substitutes (including water content and water droplet size, and textural and rheological properties, such as hardness and spreadability) are of great importance as they determine the functionality of these products [17,46,53]. Water content is closely linked to the quality of the end product, such as butter or its vegetable substitutes and blends. As studies [48,54,55] have shown, the water content of butter is influenced by the technological parameters of the creamer process and the kneading of the butter, which aims for an even distribution of water droplets that are as small as possible, in order for the butter to have the right consistency. Rønholt [48] showed that the water content is also decisive for the smear value. The water content influences the crystallization of the fat phase, and thus, also the structure of the butter [56]. The strength of the crystals formed depends on the size of the water droplets and the amount of fat crystallized. As the water content of the product increases, interactions between the water droplets can occur and the textural stability of the butter is consequently lost [57]. Similar effects are observed with butter substitutes [57].

Water distribution. Test samples of butter and butter substitutes received the maximum score in determining the degree of water dispersion (Table 5). The physical composition of butter and its vegetable substitutes varies as the different manufacturing processes result in different microstructures of these products. In addition, butter is less homogeneous and has a more complex chemical composition than its plant substitutes or blends such as

margarine, which requires the use of sophisticated analytical techniques in instrumental analysis to determine water droplet size distribution [58].

The degree of water dispersion is of microbiological importance, as well as being important for the sensory properties of fat products such as butter [59]. The greater the degree of water dispersion, the more difficult it is for unwanted microflora to grow. The water content and degree of distribution can influence the course of fat crystallization, which in turn can influence the texture of the product, and thus, its spreadability [16,48,51,56,57,60].

Plasma pH. The results of the plasma pH measurements of the analyzed samples of butter and butter substitutes are summarized in Table 5. The pH of butter plasma ranged from 5.94 ± 0.18 to 6.77 ± 0.16 and was not statistically significantly different but was dependent on the butter sample. The statistical analysis allowed the butter samples to be distinguished into two groups: (a) MEG and LMK; (b) LMK, LaME, LoME, MEH, MMP, PME, and PrME (Table 5). The plasma acidity of the butter substitutes was statistically significantly different from the pH of the butter plasma and was the same for all butter substitute samples tested.

The plasma pH of butter and its vegetable substitutes (blends with other fats) is a result of the production and storage parameters of the product [61]. An important step in the production of butter, which later influences the pH value of the milk plasma, is the biological maturation of the cream, i.e., its fermentation. The lactose contained therein is converted into lactic acid, which subsequently causes the plasma of the aqueous phase to acidify and thus improves the shelf life of the product. As can be seen from the analysis of the butter samples tested in this work, the pH value indicates that the cream had not undergone biological maturation, i.e., the butter samples were made from sweet cream. The situation is different with butter substitutes, the production of which usually involves regulating the plasma pH value by adding chemical acidity regulators such as citric and lactic acids (what was claimed by some manufacturers, Table 1). It should be noted that the acidity of butter and butter substitutes is a poorly understood parameter in terms of its significant relationship to lubricity values. No available literature data were found on this topic.

Color. It was found that the butter samples tested were different from the chosen standard (Table 6). The mean values of the *L*\* and *b*\* color components for the test samples were higher than the corresponding values of the standard, while the mean value of the *a*\* color component was lower than that of the standard. The measured color of the butter samples according to the standard tended towards slightly greenish and lighter tones. The color component *a*\* did not statistically differentiate the butter and butter substitute samples.

The parameter *b*\* in the color analysis is often used as an indicator of the yellow-blue color bias in a sample. When discussing color results, the color tendency of parameter *b*\* is usually described as the amount of yellow or blue present in the sample. The *b*\* component divided the butter and butter substitutes into seven homogeneous groups at the 0.05 level, with the majority of butter samples ranking above the majority of butter substitutes on the CIELab scale. The magnitude of the *b*\* value would provide a measure of the intensity or saturation of the yellow or blue color. A positive *b*\* value would indicate a yellow color in the butter sample, while a negative *b*\* value would indicate a blue color. A high positive *b*\* value would indicate a strong yellow sample, while a low positive *b*\* value would indicate a lighter yellow color. The samples studied in this work obtained high positive values for the parameter *b*\*, which in most cases were statistically significantly higher for butter than for its substitutes.

Regarding the color component *L*\*, all butter samples and the four butter substitutes (LuPM, LaM, SSO, and ZaM) showed the same value for this parameter, which was statistically significant, while the other three butter substitutes (FM, PaEM, and RMTM) were significantly darker. It is worth noting that the butter substitutes compared to the standard for butter color components *a*\*, *b*\*, and *L*\* gave surprisingly similar results for each component, despite the differences in chemical composition (e.g., different fats used or water content), in textural parameters (e.g., spreadability or hardness) and due to different technological processes.

**Table 6.** Color components of butter and butter substitutes.

a,b,c,d,e,f,g—values in the same column and marked with the same letters are not statistically significantly different at the α = 0.05 level.

The calculated ΔE\* values represented the difference between the color of the test sample and the color of the standard in CIELab space and therefore expressed the magnitude of the color change but not its direction. With regard to the expression of this parameter, the samples of butter and butter substitutes were statistically significantly different in two homogeneous groups at the α = 0.05 level. The calculated Δ*E*\* values for the butter and butter substitute samples ranged in excess of 5, indicating large color differences to the unaided eye of an unexperienced observer between the test butter and butter substitutes and the standard color [35,62].

A multivariate analysis of the spreadability measurements, selected physicochemical properties, and the color components of the butter and butter substitute samples did not reveal any significant strong relationships between these parameters (Figure 2a,b). The only significant correlation found was between the ΔE\* value and b\* color compound for the butter samples (correlation coefficient 0.85). Lapˇcíková et al. [46] also found no general relationship between the content and composition of total fat in the samples and the values of textural parameters (i.e., springiness, cohesiveness, and stringiness). Furthermore, no correlation was to be expected for the color components, since both butter and butter substitutes can be colored (while carotenes annatto, bixin, norbixin, and curcumin are permitted in butter in the EU, as are other fat- and oil emulsions) [63].

(**b**)

**Figure 2.** Graphs of correlation matrix showing the relationship between the spreadability, selected physicochemical properties, and the color components of butter and butter substitute samples (**a**) and butter substitute samples alone (**b**) measured at different temperatures (with a confidence level of 95.0%).

#### *3.3. Additional Characteristics of Butter Milk Fat*

Determination of the acid value. The acid number is defined as the number of milligrams of potassium hydroxide required to neutralize the free fatty acids in a gram of fat sample. The acid number values of the butter samples tested ranged from 1.14 to 1.54 mg KOH/g fat and did not exceed the maximum value of 2 mg KOH/g fat permitted for butter (Table 7). The acid numbers of the butter tested in this study were statistically significantly different (at a significance level of α = 0.05). This may be due to different production dates or because the comparison involves samples from different manufacturers and technologies.

**Table 7.** Characteristics of butter milk fat.

a,b,c,d—values in the same column and marked with the same letters are not statistically significantly different at the α = 0.05 level.

These data are consistent with those of other scientists [64,65]. Similar results were obtained by Bellinazo et al. [64], who examined the properties of butter during storage and obtained an acid number value of 1.08 mg KOH/1 g fat just after production. The acid value increased with the storage time and was 2.74 mg KOH/g fat after storage for 90 days.

Determination of the peroxide number. No peroxides were found at detectable levels in any of the tested samples, which was due to the good quality of the tested products. These results were consistent with the findings of other researchers [66]. This number is a measure of the peroxide content and is considered an indicator of the rancidity of the fat. The butter samples tested were products derived from sweet cream; meanwhile, Khaskheli et al. [67] showed that the peroxide number of market sweet butter (1.56 ± 0.17 mEq O2/kg fat) was significantly higher than the peroxide number of butter derived from fermented cream (1.00 ± 0.08 mEq O2/kg fat), which was determined by changes that were reported to have occurred during the storage of the tested butter samples. In comparison, the peroxide number of butter samples freshly prepared from sweet cream or fermented cream under the laboratory conditions by Khaskheli et al. [67] was 1.00 ± 0.10 mEq O2/kg fat and 1.04 ± 0.11 mEq O2/kg fat, respectively. The observed fluctuations in the peroxide number values of market butter (0.35 ± 0.24 to 1.80 ± 0.36 mEq O2/kg fat) were explained by Gonçalves and Baggio [68] by differences in the way the products were packaged, and thus, their exposure to atmospheric oxygen.

Determination of the saponification number. The saponification number values of the butter tested were in the range of 226.2–231.2 mg KOH/g fat and did not exceed the usual range specified for butter, i.e., 220–236 mg KOH/g fat (Table 7). Although the differences between the values obtained for the different butter samples were small, the values were significantly different (at a significance level of α = 0.05). Similar results were obtained by Kahyao ˘glu and Çakmakçı [69], who studied butter and obtained a saponification number of 228.1 mg KOH/g fat. Another study by Kahyao ˘glu and Çakmakçı [70] showed that the saponification number increased with storage time. As the studies mentioned above have shown, the saponification number (such as the acid number) can be an indicator of the degree of freshness of the fat and, above all, of its shelf life. Determination of the saponification number in fats enables the average molecular weight of the fatty acids to be determined. Its high levels in butter are due to the presence of palmitic acid.

Chromatographic determination of the fatty acid profile. Table 8 provides a summary of the percentage of individual fatty acids found in the butter samples tested. Types of butter, which are products of animal origin, are characterized by a high percentage share of saturated fatty acids (SFA) and a low content of unsaturated fatty acids: monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA). The analyzed kinds of butter contained the following fatty acids in the highest proportion: palmitic acid (C16:0), oleic acid (C18:1 cis 9), stearic acid (C18:0), and myristic acid (C14:0).

a,b,c,d—values in the same row and marked with the same letters are not statistically significantly different at the α = 0.05 level.