A method for evaluating the bitterness of beer

Abstract

The application discloses a beer bitterness evaluation method, and relates to the technical field of analysis and detection, which comprises the following steps: detecting bitter substances in beer by using an instrument method and establishing a prediction model, detecting the content of bitter substances humulone, hulupones and iso-alpha acids in granular hops and beer products by using a high performance liquid chromatography, detecting the content of bitter substance alpha-acid in granular hops and the bitterness value in wort, fermentation broth and beer by using a spectrophotometer method, and establishing a prediction model according to the content of bitter substances in granular hops and beer respectively. Compared with sensory evaluation, the method has the advantages of rapidness, accuracy and low cost. In combination with statistical data analysis technology, a prediction model of the bitterness value from raw materials to process semi-finished products and products is established according to the content of bitter substances in raw materials, precise addition of hops and effective regulation of beer bitterness are realized.

Description

Technical Field

[0001] This invention relates to the field of analytical testing technology, specifically a method for evaluating the bitterness of beer. Background Technology

[0002] Beer is a carbonated, effervescent, low-alcohol fermented beverage made primarily from malt and water, with the addition of hop pellets (including hop products), and fermented with yeast. Bitterness is a key characteristic of beer, mainly imparted by the hop pellets (including hop products) used in brewing. For a long time, it was generally believed that the bitterness in beer came from iso-α-acids formed by the isomerization of α-acids from hop resins in the hop pellets. Typically, the main indicator for measuring beer bitterness was the bitterness value, or BU value; a higher BU value indicated a stronger sensory bitterness. However, with a deeper understanding of the bitter substances in hops, it has been discovered that the bitter substances in hops are not only iso-α-acids, but other substances from the isomerization of α-acids and products of β-acid oxidation can also contribute bitterness, such as humulone and helixone.

[0003] In practical production applications, discrepancies between BU values ​​and perceived bitterness frequently arise, especially during fermentation, where the inaccurate evaluation of bitterness in the fermentation broth and beer becomes increasingly prominent with dry-feeding pellet hops. Furthermore, hop products such as hops and pellet hops originate from agricultural production; different varieties, origins, and climatic conditions all influence hop quality. Therefore, establishing methods for predicting and evaluating bitter substances in beer fermentation broth and beer products based on hop addition will effectively solve the problem of precise addition of pellet hops and other products during beer brewing, and is of great significance for ensuring the stability of beer bitterness. Summary of the Invention

[0004] The purpose of this invention is to provide a method for evaluating the bitterness of beer, so as to solve the problem of the deviation between the bitterness value and the bitterness perception of beer.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for evaluating the bitterness of beer, comprising the following steps:

[0007] 1) Instrumental methods were used to detect bitter substances in beer, including: (1) high performance liquid chromatography was used to detect the content of bitter substances humulone, shiluone and iso-α-acid in particulate hops and beer products; (2) spectrophotometry was used to detect the content of bitter substances α-acid in particulate hops and the bitterness value in wort, fermentation liquid and beer.

[0008] 2) Based on the content of bitter substances in hop pellets and beer, prediction models are established respectively. The prediction models include: (1) a prediction model of bitterness in wort, fermentation liquid and beer after adding hop pellets during the beer brewing saccharification process; (2) a prediction model of bitterness in fermentation liquid and beer products after dry feeding of hop pellets during the beer fermentation process.

[0009] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0010] In one alternative: In step 1), the method for detecting bitter substances in hop pellets is to accurately weigh 5g of hop pellets (accurate to 0.0001g), place them in an iodine flask, add 100mL of anhydrous ethanol, stopper the flask, place it on a shaker, and extract for 1 hour.

[0011] In one alternative approach: after the hop pellet extraction is completed, the mixture is allowed to stand, and the supernatant is filtered through a 0.22 μm filter membrane. The filtrate is then placed in a sample bottle and tested to obtain the contents of humulone, hexulone, and iso-α-acid. The content of bitter substances α-acid in the hop pellets and the bitterness values ​​in the wort, fermentation broth, and beer are determined by spectrophotometry.

[0012] In one alternative: In step 1), the method for detecting bitter substances in beer products is as follows: Take 100ml of beer, filter it through filter paper to remove gas, activate the C18 SPE column by passing it through 6mL of acetonitrile and pure water sequentially, take 9mL of degassed beer and pass it through the SPE-C18 column; filter the eluent through a 0.22μm filter membrane, put the filtrate into a sample bottle and test it to obtain the content of humulone, hexylone and iso-α-acid in beer.

[0013] In one alternative approach: In step 2), SPSS statistical software is used to propose a predictive model for the amount of hops added and the bitterness of the wort based on the amount of hops used during the brewing process. The regression model is: Y = 2.315 + 0.312*A - 0.955*B - 0.204*C + 0.472D, where humulone A, helixone B, iso-α-acid C, and α-acid D are independent variables, and the R value is 0.984.

[0014] In one alternative: multiple hop varieties are used together, with humulone A, shiluone B, iso-α-acid C, and α-acid D representing the sum of the concentrations of hops added to the wort for brewing. That is, the sum of the concentrations of humulone among different hop varieties is A, the sum of the concentrations of shiluone is B, the sum of the concentrations of iso-α-acid is C, and the sum of the concentrations of α-acid is D.

[0015] In one alternative approach: using SPSS statistical software, a predictive model is proposed for the bitter substances provided by dry-hopped beer in a given volume of fermentation broth, and the bitterness value model for the fermentation broth after 7 days of storage at 0℃ is: Y投 =11.617+0.018*A+0.012*B+0.012*C, where humulone A, shiluone B, and iso-α-acid C are independent variables, and the R value is 0.896.

[0016] In one alternative approach: during actual calculations, the bitterness value Y from the pre-fermentation broth after dry hopping needs to be added. 前 When calculating the bitterness of beer after dry hopping, the bitterness value should be: Y 总 =Y 投 +Y 前 , where Y 总 Y represents the bitterness value of dry-hopped beer products. 投 Y represents the bitterness value provided by dry-hopped hops. 前 The bitterness value is the value of the pre-fermentation liquid from dry-hopped hops.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0018] This invention provides a method for predicting and evaluating the bitterness intensity of beer products. Compared with sensory evaluation, it has the advantages of being fast, accurate, and low-cost, and can be practically applied to the bitterness evaluation of beer products. It provides an effective solution for detecting bitter substances in beer through modern analytical techniques. Combined with statistical data analysis techniques, it establishes a predictive model for bitterness values ​​from raw materials to semi-finished products and finished products based on the content of bitter substances in the raw materials, thereby achieving precise addition of hops and effective control of beer bitterness. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1

[0021] In this embodiment of the invention, a method for predicting and evaluating the bitterness intensity of beer products is provided. The experimental method used in the embodiment is the national standard method of "Beer Analysis Methods" (GB / T 4928-2008). In the quantitative experiments in the following embodiments, 2-3 repeated experiments are set up, and the average value of the results is taken.

[0022] 1) Prediction model for bitterness value in saccharified wort

[0023] (1) Detection of bitter substances in hop pellets

[0024] Accurately weigh 5g of hops on a precision balance (0.0001). The moisture content of the hops is calculated as 7%. Place them in an iodine flask, add 100mL of anhydrous ethanol, stopper the flask, place it on a shaker, and extract for 1 hour.

[0025] After standing, the supernatant was filtered through a 0.22 μm filter membrane, and the filtrate was placed in a sample bottle. The humulone, shiluone and iso-α-acid were determined by high performance liquid chromatography.

[0026] ①Chromatographic conditions:

[0027] Chromatographic column: Agilent C18 (150mm × 4.6mm, 5µm); column temperature: 30℃; detection wavelength: 260nm; injection volume: 10µL; mobile phase A: 0.05% chromatographic grade phosphoric acid solution, filtered and degassed by sonication; mobile phase B: 100% chromatographic grade acetonitrile, degassed with high-purity He; flow rate: 1.0mL / min;

[0028] ② Gradient elution procedure:

[0029] 0~40min, 90%~48%A; 40~45min, 48%A; 45~49min, 48%~25%A; 49~55min, 25%~15%A; 55~56.5min, 15%A; 56.5~57.5min, 15%A~90%A; 57.5~65min, 90%A;

[0030] ③ The retention times of each component of humulone, shiluone, and iso-α-acid are calculated as follows:

[0031] Humulinone: 33.34 min, 37.369 min, 39.326 min, 39.84 min;

[0032] Shirrudone: 34.575 min, 36.662 min;

[0033] Iso-α-acids: 48.537 min, 49.647 min, 49.967 min;

[0034] ④ Preparation of standard solutions

[0035] Using the external standard method, the concentration of the iso-α-acid standard (DCHA-Iso, ICS-14) was known to be 65.2% (calculated as 2 / 3).

[0036] Preparation of standard solution: Weigh 0.005 g of hop iso-α-acid standard, add it to a 25 ml volumetric flask, dissolve it with methanol and dilute to the mark, then transfer it to a sample vial for instrumental analysis;

[0037] The concentration of iso-α-acid in the standard is the sum of (iso-humulone + iso-humulone + iso-humulone);

[0038] The concentration of iso-α-acid in the standard sample, C = 0.005 g / 25 ml × 2 / 3 = 133.3 mg / L;

[0039] ⑤ Result Calculation

[0040] The humulone, helirulon, and iso-α-acid in hop pellets are calculated according to formulas 1, 2, and 3, respectively:

[0041] Formula 1: X1=S1 / S×C×10 / 5

[0042] Formula 2: X2 = S2 / S × C × 10 / 5

[0043] Formula 3: X3=S3 / S×C×10 / 5

[0044] Wherein: X1—Humulin ketone content in hop pellets, mg / g;

[0045] X2—Sherluconone content in hop pellets, mg / g;

[0046] X3—Iso-α-acid content in hop pellets, mg / g;

[0047] S1—The sum of the peak areas of all components of hummus ketone in the hop extract;

[0048] S2—The sum of the peak areas of all components of shinglosone in the hop extract;

[0049] S3—The sum of the peak areas of all components of iso-α-acid in hop extract;

[0050] C—Concentration of iso-α-acid in the standard, mg / L;

[0051] S—The sum of the peak areas of all components of the iso-α-acid in the standard;

[0052] ⑥ Test results

[0053] Table 1. Bitter substance content (based on water content) in different varieties of hop pellets

[0054] Unit: mg / g

[0055] Hop varieties 1# 2# 3# 4# 5# 6# Humulinone 62.19 48.00 44.47 32.97 60.39 66.92 Shirodone 14.75 4.97 7.46 4.16 15.78 18.96 Iso-α-acids 19.78 21.59 25.89 11.63 15.59 29.30 α-acids 70.97 24.73 30.11 72.04 75.27 78.49

[0056] Table 2. Bitter substance content of different varieties of hops in 2L wort

[0057] Unit: mg / L

[0058] Pellet Hops Humulinone Shirodone Iso-α-acids α-acids 1# 86.76 20.58 27.59 99.00 2# 66.96 6.93 30.12 34.50 3# 62.03 10.41 36.11 42.00 4# 45.99 5.81 16.23 93.00 5# 84.24 22.02 21.75 105.00 6# 93.36 26.45 40.88 109.50

[0059] The bitter substances content in the hop pellets in the table refers to the concentration added to the wort, and the calculation method is as follows:

[0060] Concentration of bitter substances in wort = Bitter substance content in hops (mg / g) × Amount of hop pellets added (g) × (1 - Moisture content of hop pellets (%)) / Volume of wort (L)

[0061] (2) Wort preparation

[0062] Six varieties of hop pellets were weighed out in batches of 3g each and added to six 2L worts. After boiling for 60 minutes, water was added to bring the volume up to 2L, and the bitterness value of the wort was measured.

[0063] The method for detecting bitterness is described in the national standard "Analytical Methods for Beer" (GB / T 4928-2008), and the specific procedure is as follows:

[0064] ① Sample processing

[0065] Using a pipette tip with one drop of octanol, pipette 10 mL of undextrose cold beer sample (10°C) into a 50 mL centrifuge tube. Add 1 mL of HCl solution (3 mol / L) and 20 mL of analytical grade isooctane. Tighten the cap and shake on an electric shaker for 15 min (it should be milky). Then transfer it to a centrifuge and centrifuge at 4000 rpm for 10 min to separate the layers. Quickly aspirate the upper layer (isooctane layer) and measure the absorbance at 275 nm using a 10 mm cuvette with isooctane as a reference solution.

[0066] ② Result Calculation

[0067] The bitterness value of the sample was calculated according to Formula 4.

[0068] Formula 4: X4 = A 275 ×50

[0069] In the formula: X4—the bitterness content of the sample, in bitterness units (BU);

[0070] A 275 —The absorbance of the sample was measured at a wavelength of 275 nm;

[0071] 50—Conversion factor;

[0072] The result is rounded to one decimal place.

[0073] ③ Test results

[0074] Table 3. Bitterness values ​​of wort prepared from different varieties of hop pellets.

[0075] Pellet Hops 1# 2# 3# 4# 5# 6# Bitterness rating (BU) 46.79 28.65 22.52 51.95 54.53 51.27

[0076] Using SPSS statistical software, a predictive model for the relationship between hop addition and wort bitterness was proposed based on the amount of hops used during brewing. Humulin A, helixone B, iso-α-acid C, and α-acid D were used as independent variables in the model, resulting in the following regression model:

[0077] Y=2.315+0.312*A-0.955*B-0.204*C+0.472D.

[0078] The model's R-value is 0.984, indicating that the model has good significance and can be used to predict bitterness scores in beer.

[0079] It should be noted that in the actual beer mashing and brewing process, if multiple hop varieties need to be added, then humulone A, helixone B, iso-α-acid C, and α-acid D are the sum of the concentrations of the hops added to the wort for brewing. That is, the sum of the concentrations of humulone among different hop varieties is A, the sum of the concentrations of helixone is B, the sum of the concentrations of iso-α-acid is C, and the sum of the concentrations of α-acid is D.

[0080] 2) Prediction of bitterness value in dry-feed hop fermentation broth or beer during fermentation process

[0081] (1) Preparation of dry-feed hop fermentation broth

[0082] ①Wort Preparation: Weigh 75g of malt powder into a mashing cup, add 200ml of water at 46℃, and keep it in a 45℃ water bath for 30 minutes with constant stirring. Then, heat the water bath at a rate of 1℃ / min, raising it to 70℃ within 25 minutes. Add 100ml of water at 70℃ into the mashing cup, and keep the mash at 70℃ for 1 hour. Then, rapidly cool it to room temperature within 10-15 minutes. Rinse the stirrer with water, wipe the outer wall of the mashing cup dry, and add water to ensure the contents are accurately weighed to 450g. Stir the mashed mash with a glass rod and filter it through medium-speed filter paper to obtain 200ml of 12°P wort.

[0083] ② Wort sterilization and yeast addition: Place the wort in an Erlenmeyer flask in an autoclave, set the sterilization temperature to 105℃, and sterilize for 20 minutes. After sterilization, filter the wort in a sterile room and transfer it to a 500ml clamp bottle. Weigh 0.40g of active dry yeast W34 / 70 in a laminar flow hood and add it to the cooled wort. Gently shake the bottle to ensure the yeast is evenly mixed and completely dissolved, avoiding adhesion to the bottle walls. Wrap the bottle with aseptic sealing film and incubate at 10℃.

[0084] ③ Dry hopping: On the third day of fermentation, 1.2g of each of the six varieties of hop pellets were weighed and added to the fermentation liquid. The mixture was placed in an incubator and fermented at 10℃ for 7 days. After cooling to 0℃, the mixture was taken out and tested for bitter substances such as humulone, shiluone, and iso-α-acid. The bitterness value was also tested.

[0085] (2) Content of bitter substances in hops used for dry hopping

[0086] Table 4. Bitter substance content of different hop varieties

[0087] Unit: mg / g

[0088]

[0089]

[0090] (3) Establishment of a bitterness prediction model after dry hopping

[0091] Table 5. Bitter substances and bitterness values ​​of fermentation broth for six types of dry-poached hops.

[0092] Unit: mg / L

[0093] Humulinone Shirodone Iso-α-acids α-acids 1# 313.37 81.91 80.91 16.93 2# 347.30 98.38 152.06 21.72 3# 539.75 53.96 130.01 23.80 4# 180.62 33.37 107.08 15.91 5# 171.03 47.93 124.49 18.24 6# 323.58 40.85 322.86 20.89

[0094] Note: The bitter substances content of hops in the table refers to the concentration added to wort, and the calculation method is as follows:

[0095] Concentration of bitter substances in fermentation broth (mg / L) = Content of bitter substances in hops (mg / g) × Amount of hops added (g) × (1 - Moisture content of hops (%, calculated as 7%)) / Volume of fermentation broth (L)

[0096] Using SPSS statistical software, a predictive model for the relationship between hop addition and bitterness value in beer fermentation liquid was proposed based on the amount of hops used during the brewing process. Humulin A, hexagon B, and iso-α-acid C were used as independent variables in the model, resulting in the following regression model:

[0097] Y=11.617+0.018*A+0.012*B+0.012*C.

[0098] The model's R-value is 0.896, indicating good significance and its applicability for predicting bitterness in dry-hopped beer. In actual calculations, the bitterness value BUpre- from the pre-fermentation broth after dry hopping needs to be added. Therefore, when calculating the bitterness of beer after dry hopping, the bitterness value should be: Ytotal = Yhopping + Ypre-. Where: Ytotal is the bitterness value of the dry-hopped beer product, Yhopping is the bitterness value provided by dry hops, and Ypre- is the bitterness value in the fermentation broth before dry hopping.

[0099] Example 2

[0100] In this embodiment of the invention, the beer bitterness intensity evaluation model is applied.

[0101] 1) Prediction model for bitterness value in saccharified wort

[0102] The addition of hop pellets to two beer products was tested. One beer product had two types of hop pellets added, and the other beer product had one type of hop pellets added. After boiling, the volume of the wort was 100 m3. The amount of hops added to product one was 45 kg and 23 kg, and the amount of hops added to product two was 64 kg. The hop moisture content was calculated as 7%. The bitterness value of the cooled wort was tested. The contents of humulone, hexaflunione, and iso-α-acid in the added hop pellets were substituted into the prediction model Y = 2.315 + 0.312*A - 0.955*B - 0.204*C + 0.472D. The predictable bitterness values ​​are shown in Table 6.

[0103] Table 6. Formula for Adding Granular Hops (Product 1)

[0104]

[0105] Table 6. Formula for Adding Granular Hops (Product 2)

[0106]

[0107] The overall deviation is small, and it can be used to predict bitterness values ​​when adding hop pellets.

[0108] 2) Dry-pouring hop bitterness prediction model

[0109] This study investigated the bitterness of a dry-feed beer product before and after dry-feeding with pellet hops. The product was a dry-feeded hop product, using one type of pellet hop, with a dry-feeding amount of 8 kg. The hop moisture content was 7%, and the fermentation liquid volume was 2 kg. The bitterness of the fermentation liquid before dry-feeding was 5.96. The contents of humulone, hexaflunione, and iso-α-acid in the dry-feeded hops were measured and converted to their concentrations in the fermentation liquid. The bitterness of the beer product was then measured and substituted into a prediction model.

[0110] Y = 11.617 + 0.018 * A + 0.012 * B + 0.012 * C. The predictable bitterness values ​​are shown in Table 8.

[0111] Table 8 Application of the bitterness prediction model for dry-hopped beer products

[0112]

[0113] The overall deviation is small, and it can be used to predict the bitterness score of dry-hopped beer.

[0114] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for evaluating the bitterness of beer, characterized in that, Includes the following steps: 1) Instrumental methods were used to detect bitter substances in beer, including: (1) The contents of bitter substances humulone, shirudin and iso-α-acid in particulate hops and beer products were determined by high performance liquid chromatography; (2) The content of α-acid, a bitter substance in hop pellets, and the bitterness value in wort, fermentation liquid and beer were determined by spectrophotometry. 2) Based on the detection results, predictive models are established for different stages of beer brewing, and the predictive models include: (1) During the saccharification process of beer brewing, a predictive model for the bitterness value in the wort, fermentation liquid and beer is established after the addition of hop pellets; (2) During the beer fermentation process, a predictive model for the bitterness value of the fermentation liquid and beer products is established after dry feeding of granulated hops; In step 2), SPSS statistical software is used to establish a regression prediction model between the amount of hops added and the bitterness value of the wort, based on the amount of hops used during the brewing process and the corresponding detected bitter substance content. The model is as follows: Y=2.315+0.312A-0.955B-0.204*C+0.472D, Among them, humulone A, shiluone B, iso-α-acid C, and α-acid D are independent variables, and A, B, C, and D are the sum of the concentrations of the corresponding bitter substances added to the wort system by hops; Furthermore, during the dry-hop fermentation process, a predictive model for the bitterness value of the fermentation broth provided by dry-hopped hops was established: Yproject = 11.617 + 0.018A + 0.012B + 0.012*C, Where A, B, and C represent the concentrations of bitter substances after dry-added hops are introduced into the fermentation liquid system; In the actual calculation of the bitterness value of beer after dry hopping, the bitterness value Ypre-dry-hop of the fermentation liquid before dry hopping is added together with the contribution value Yhop of the dry hopping hops, to obtain: Y_total = Y_previous + Y_investment.

2. The method for evaluating beer bitterness according to claim 1, characterized in that, The method for detecting bitter substances in hop pellets is as follows: accurately weigh 5g of hop pellets, put them into an iodine flask, add 100mL of anhydrous ethanol, stopper the flask, and place it in a shaker for 1 hour for extraction.

3. The method for evaluating beer bitterness according to claim 2, characterized in that, After extraction of hop pellets, the mixture was allowed to stand. The supernatant was then filtered through a 0.22 μm filter membrane and analyzed to obtain the contents of humulone, hexylone, and iso-α-acid. At the same time, the α-acid content in the hop pellets and the bitterness value in the wort, fermentation broth, and beer were determined by spectrophotometry.

4. The method for evaluating beer bitterness according to claim 1, characterized in that, The method for detecting bitter substances in beer products is as follows: beer samples are degassed and filtered, then purified by solid-phase extraction using a C18 SPE column. The eluent is filtered through a 0.22 μm filter membrane and then analyzed by high-performance liquid chromatography to obtain the content of humulone, hexulone, and iso-α-acid in beer.

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