Method for evaluating quality of high-quality soy sauce wine brewing sorghum

Abstract

The invention discloses a method for evaluating the quality of high-quality Maotai liquor brewing sorghum, and belongs to the technical field of liquor brewing. The method comprises the following steps: carrying out multi-point sampling on sorghum entering a factory, and detecting the total starch content, amylopectin proportion, tannin content and potassium ion content; according to a preset standard, each index is subjected to single scoring, a comprehensive score is calculated through a comprehensive evaluation model, and the single scores are single scores of starch, amylopectin, tannin and potassium ions. The comprehensive scores are high-quality, qualified and unqualified. The rapid detection technology is adopted, the total consumed time is shorter than or equal to 4 hours, the problems that a traditional method depends on a single index and is low in efficiency and lack of a quantitative model are solved, the high-quality sorghum can be accurately screened, the high-quality liquor rate and the liquor yield of the Maotai liquor are increased, and the production stability is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of liquor brewing, and specifically provides a quality evaluation method for brewing high-quality Jiang-flavor liquor. BACKGROUND

[0002] As a main raw material for Jiang-flavor liquor, sorghum not only provides nutrients and energy for microbial growth and metabolism, but also contains a large amount of flavor and flavor precursor substances. The quality of sorghum will directly affect the quality of base liquor. However, the current industry's quality evaluation model for sorghum only includes sorghum component indicators and the data is relatively broad, which is not conducive to screening high-quality Jiang-flavor liquor sorghum and cannot guarantee the stability of liquor rate. The main problems are as follows: Firstly, it relies on a single indicator and only focuses on moisture content, starch content or the proportion of amylopectin, ignoring the synergistic effect of flavor precursors (such as tannin and potassium elements); Secondly, the detection efficiency is low, and the test materials and manpower have an impact. Only one sample is taken from a batch of sorghum for detection. The detection of amylopectin relies on enzyme hydrolysis method, and it takes 4 hours to detect 10 samples, resulting in a small total amount of samples, a long detection period and a deviation between the detection result and the true level. Thirdly, there is a lack of quantitative model, which cannot dynamically correlate the characteristics of sorghum with the flavor output of Jiang-flavor liquor. The above three problems restrict the establishment of the quality evaluation method for high-quality sorghum and are not conducive to screening high-quality Jiang-flavor liquor sorghum and guaranteeing the stability of liquor quality and liquor rate. SUMMARY

[0003] In view of this, the present application provides a quality evaluation method for brewing high-quality Jiang-flavor liquor sorghum. The method can quickly detect key indicators representing quality such as starch, the proportion of amylopectin, tannin and potassium ion combination by sampling sorghum, and then score each indicator according to the single indicator scoring standard. Finally, the comprehensive quality evaluation model is used to obtain the comprehensive score of sorghum quality according to the single indicator score value of each indicator. The method provides a reference for screening high-quality Jiang-flavor liquor sorghum and guarantees the stability of liquor quality and liquor rate in workshop production.

[0004] The technical scheme of the present application is as follows: The present application provides a quality evaluation method for brewing high-quality Jiang-flavor liquor sorghum. The method realizes accurate evaluation of the quality of brewing sorghum through rapid detection, quantitative scoring and weighted comprehensive model of multi-dimensional key indicators, solves the problems of relying on a single indicator, low detection efficiency and lack of quantitative model in the prior art, and provides technical support for screening high-quality Jiang-flavor liquor sorghum and stable production. The evaluation method comprises the following steps: For the same batch of incoming sorghum, the conventional multi-point sampling method is used: at least 5 sampling points are randomly selected from the upper, middle and lower layers and the periphery of the sorghum pile, an equal amount of sample is taken from each sampling point, mixed and then divided into 4 parts, each part weighing ≥100g, the final representative sample is obtained, the sample quantity is adjusted according to the batch size to ensure the overall quality of the batch. All samples must be tested within 24 hours after threshing to avoid changes in components caused by grain respiration, and each sample must be tested in parallel for 3 times, the average value is taken after excluding the maximum and minimum values for starch detection, and the arithmetic mean value is taken for the rest of the indicators to reduce the detection error.

[0005] Detection environment control The whole process environmental temperature is controlled at 25±1℃; among them, the relative humidity needs to be ≤40% when detecting amylopectin proportion, the relative humidity is controlled at 40%±5% when detecting total starch, and there is no special requirement for humidity when detecting tannin and potassium ion, but it needs to avoid the influence of extreme humid environment on the stability of reagents.

[0006] Total starch content detection Sample pretreatment: take the sorghum kernels within 24 hours after threshing, crush them with a cyclone crusher at a speed of 10000 rpm for 20 seconds, pass them through a 0.6 mm standard sieve, and place the undersize material in a constant temperature and humidity box at 25℃±1℃ and RH 40%±5%, balance the moisture for 30 minutes to ensure stable moisture and avoid affecting the spectral detection.

[0007] Detection operation: weigh 15.0g±0.2g of the treated sorghum powder, load it into the near-infrared spectrometer, set the wavelength range to 1100-2500nm, rotate the sample cup, and use the scraper to flatten the surface; after preheating the instrument for 15 minutes, perform background correction, place the sample cup into the sample chamber, select the "total starch analysis" mode, and automatically collect the reflectance spectrum at 1930nm (starch O-H bond frequency absorption peak) and 2100nm (C-O bond secondary frequency).

[0008] Calculation method: the system calculates the total starch content (%) = (A 1930 / A 2100 )×K+B, where K=0.873±0.005, B=12.36, the model R 2 =0.98, the model is calibrated by 100+ sorghum samples with known starch content, and the fitting degree is high.

[0009] Amylopectin proportion detection Sample pretreatment: take the sorghum sample within 24 hours after threshing, crush it with a cyclone crusher at a speed of 12000 rpm for 15 seconds, pass it through a 0.5 mm standard sieve, and balance the moisture in the desiccator to avoid the influence of humidity on the structure of starch molecules.

[0010] Detection operation: take 10.0 g ± 0.1 g of sorghum powder, lay flat on the bottom of the near-infrared spectrometer sample cup, wavelength range 1200-2400 nm, use the sample press to compact to a flat surface without cracks under 20 N pressure; preheat the instrument for 10 minutes, place the sample in the sample chamber and close the light shield cover, select the "starch component analysis" mode, automatically collect the reflectance spectrum at 1680 nm (amylose characteristic peak) and 2180 nm (amylopectin characteristic peak).

[0011] Calculation method: amylopectin proportion (%) = [A 2180 / (A 1680 +A 2180 )] x β, where β = 1.052 ± 0.003, calibrated by comparison with high performance liquid chromatography.

[0012] Tannin content detection Extraction operation: take 20 g of ground sorghum sample, place it in a 500 ml round-bottom flask, add 300 ml of 70% ethanol solution, connect the reflux condenser device, heat in a 60°C water bath for 2 hours to ensure complete dissolution of the tannins; cool the extract to room temperature, then filter it with a medium-speed qualitative filter paper in a Buchner funnel, and collect the filtrate.

[0013] Color development and detection: turn on the UV-visible spectrophotometer, preheat for 20 minutes for calibration, set the wavelength scan range to 400-600 nm; take 10 ml of the filtrate into a 50 ml volumetric flask, add 5 ml of 5% vanillin-methanol solution, then quickly add 5 ml of concentrated hydrochloric acid, shake well, and then place it in a 25°C constant temperature incubator for 30 minutes in the dark to ensure complete color development; use a 1 cm cuvette, prepare a blank control with 70% ethanol solution following the same color development steps, measure the absorbance at 490 nm, and take the average of three parallel measurements.

[0014] Calculation method: according to the gallic acid standard curve, concentration 0-2.0 g / 100 g, R 2 = 0.99, calculate the tannin content (unit: g / 100 g).

[0015] Potassium ion content detection Extraction operation: take 5 g of ground sorghum sample (accurate to 0.0001 g) passed through a 60 mesh sieve, place it in a 250 ml triangular flask, add 100 ml of deionized water, seal with a sealing film, and shake extract on a 25°C, 150 r / min shaker for 2 hours to promote potassium ion dissolution; transfer the extract to a centrifuge tube, centrifuge at 4000 r / min for 10 minutes, and use the supernatant.

[0016] Standard curve drawing: take 0.1907 g of potassium chloride reference reagent dried at 105°C for 2 hours, dissolve in a 100 ml volumetric flask and dilute to volume, concentration 1000 μg / ml; take 0 ml, 1 ml, 2 ml, 4 ml, 6 ml, 8 ml of the solution into a 100 ml volumetric flask and dilute to volume, respectively, to obtain 0 μg / ml, 10 μg / ml, 20 μg / ml, 40 μg / ml, 60 μg / ml, 80 μg / ml standard solution; after preheating for 30 minutes, the flame photometer is used to determine the absorbance from low concentration to high concentration, and the standard curve is automatically generated, R 2 ≥ 0.995.

[0017] Calculation method: dilute the supernatant appropriately to ensure that the concentration is within the range of the standard curve, determine the concentration after measuring the absorbance, and calculate according to the formula: potassium ion content (mg / kg) = C x V x n / m (C is the concentration found μg / ml, V = 100 ml, n is the dilution multiple, and m is the sample mass g), and the result is rounded to three significant digits.

[0018] In some embodiments, the single indicator scoring standard includes: Total starch content (W): > 67.0% for 100 points, 65.0% < value ≤ 67.0% for 90 points, 63.0% < value ≤ 65.0% for 80 points, 61.0% < value ≤ 63.0% for 70 points, ≤ 61.0% for 60 points, and a score ≥ 80 points is a single pass, ensuring sufficient fermentation substrate.

[0019] Amylopectin ratio (X): > 95.0% for 100 points, 93.0% < value ≤ 95.0% for 90 points, 90.0% < value ≤ 93.0% for 80 points, 85.0% < value ≤ 90.0% for 70 points, ≤ 85.0% for 60 points, and amylopectin is more easily decomposed by microorganisms, so a high ratio is beneficial to improve the liquor yield.

[0020] Tannin content (Y): 1.5% < value ≤ 1.8% for 100 points, 1.2% < value ≤ 1.5% for 90 points, 0.9% < value ≤ 1.2% for 80 points, 0.6% < value ≤ 0.9% for 70 points, ≤ 0.6% or ≥ 1.8% for 60 points, too low tannin flavor is insufficient, too high tannin inhibits microorganisms, and this range is the optimal interval.

[0021] Potassium ion content (Z): ≥ 4500 mg / kg for 100 points, 4200 mg / kg < value ≤ 4500 mg / kg for 90 points, 3900 mg / kg < value ≤ 4200 mg / kg for 80 points, 3600 mg / kg < value ≤ 3900 mg / kg for 70 points, ≤ 3600 mg / kg for 60 points, potassium ion is an essential element for microbial metabolism, and high content promotes fermentation.

[0022] In some embodiments, the comprehensive quality evaluation model comprises: The comprehensive score F=0.3*W+0.2*X+0.3*Y+0.2*Z, and the weight is determined according to the influence degree of each index on the 'liquor quality+liquor yield' of Jiang liquor: starch and tannin contribute most to the flavor, each accounting for 30%; amylopectin and potassium ion significantly affect the fermentation efficiency, each accounting for 20%.

[0023] In some embodiments, the grading and application rules are as follows: F≥90: high-quality brewing sorghum, used for brewing high-grade Jiang liquor, and the high-grade liquor yield is significantly improved; 80≤F<90: qualified brewing sorghum, used for brewing first-grade Jiang liquor; F<80: unqualified sorghum, downgraded for brewing ordinary liquor or rejected to avoid affecting the stability of liquor quality.

[0024] Starch provides the energy basis for fermentation, the proportion of amylopectin affects the fermentation conversion rate, tannin determines the flavor complexity, potassium ion promotes microbial metabolism, and the four work together to directly affect the 'liquor yield+high-grade rate' of Jiang liquor, and none of them can be omitted.

[0025] In some embodiments, the detection efficiency is guaranteed as follows: The total time consumption of the whole sample detection process is ≤4 hours, and the specific time allocation is: 30 minutes for sampling and pretreatment, 10 minutes for total starch detection per sample, 8 minutes for amylopectin detection per sample, 30 minutes for tannin detection per sample, and 25 minutes for potassium ion detection per sample. The detection period is greatly shortened by replacing traditional methods such as starch hydrolysis and chromatographic analysis with fast detection technologies such as near-infrared spectroscopy.

[0026] The present application has the following beneficial effects compared with the prior art: Through the present application, first, the quality evaluation of brewing sorghum is upgraded from the traditional single physicochemical detection or experience judgment to a multi-dimensional key index fast detection combined with mathematical model quantitative evaluation system, and a dynamic evaluation system of sorghum-Jiang liquor brewing adaptability is first established (non-isolated index detection), solving the problem that the traditional method cannot accurately quantify the comprehensive quality of sorghum and is highly subjective; second, the detection efficiency is greatly improved, the traditional sorghum quality detection needs starch hydrolysis, amylopectin chromatographic analysis, tannin colorimetry and potassium ion atomic absorption, and the total time consumption is about 20 hours, while the present application uses fast detection technology combined with model calculation, and the total time consumption can be shortened to less than 4 hours, the efficiency is improved by 80%, meeting the needs of the distillery for rapid screening of raw materials; third, the weight coefficient is scientifically distributed to accurately reflect the influence weight of each index on the liquor quality, the first digital evaluation standard of Jiang liquor sorghum quality in the industry is established, and the "one score value determines the grade" is realized to guide the grading and use of sorghum. The actual application shows that the high-quality sorghum brewed by the present model has improved high-grade liquor yield and liquor yield. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present application will be clearly and completely described in combination with the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which embodiments of the application belong. If the definitions set forth in this section are contrary to or otherwise inconsistent with the definitions set forth in the patents, patent applications, published patent applications, and other publications that are herein incorporated by reference, the definitions set forth in this section prevail over the definitions that are incorporated herein by reference.

[0029] The methods used in the following examples are conventional unless otherwise stated. The materials, reagents and instruments used are conventional in the art unless otherwise stated, and are available to those skilled in the art through commercial channels.

[0030] When a range, preferably a range, or a range defined by a series of upper preferred values and lower preferred values of other values or parameters is expressed, it should be understood that all ranges formed by any pair of upper or lower range or preferred values, regardless of whether the range is disclosed separately, are specifically disclosed. For example, when the range "1 to 5" is disclosed, the described range should be interpreted as including the range "1 to 4", "1 to 3", "1 to 2", "1 to 2 and 4 to 5", "1 to 3 and 5", etc. When a numerical range is described herein, unless otherwise stated, the range is intended to include its end values and all integers and fractions within the range. In the specification and claims of this application, range definitions can be combined and / or interchanged, unless otherwise stated, and these ranges include all sub-ranges contained therein.

[0031] Example 1 Comparison of efficiency and evaluation results of different detection methods Sample preparation: In November 2023, samples of Gengji Maotai Town Distillery's incoming sorghum (variety: Hongyingzi) were taken. According to the conventional multi-point sampling method, 5 sampling points were randomly selected from the upper, middle and lower layers and the periphery of the sorghum pile, and 500g of sample was taken from each sampling point. After mixing, the sample was divided into 10 representative samples (Nos. 1-10) by the four-part method. All samples were degranulated and tested within 24 hours.

[0032] Control group Traditional detection method is used to detect: Detection index and standard: moisture (≤13.0%), starch (≥63%), amylopectin ratio (≥90%), bulk density (≥740 g / L), thousand seed weight (≥16 g / thousand seeds), all indicators meet the standard, that is, qualified.

[0033] Detection method: starch uses acid hydrolysis method, amylopectin uses high performance liquid chromatography, moisture uses oven drying method, bulk density uses bulk density meter, and thousand seed weight uses number and weight method.

[0034] Results: The detection results and time consumption of 10 samples are shown in the following table, the average detection time of each sample is 1448 minutes, and the unqualified products are 2 (No. 8, 10), and the unqualified product rate is 20%.

[0035]

[0036] Test group The method of the application is used: Detection index: starch content, amylopectin ratio, tannin content, potassium ion content Detection environment control The whole process of environmental temperature control is at 25±1℃; among them, the relative humidity needs to be ≤40% when detecting amylopectin ratio, the relative humidity is controlled at 40%±5% when detecting total starch, there is no special requirement for humidity when detecting tannin and potassium ion, but it needs to avoid the influence of extreme humid environment on the stability of reagent.

[0037] Total starch content detection Sample pretreatment: take sorghum kernels within 24 hours after threshing, crush with a cyclone crusher at a speed of 10000 rpm for 20 seconds, pass through a 0.6 mm standard sieve, take the undersize and place it in a constant temperature and humidity box at 25℃±1℃, RH 40%±5%, balance the moisture for 30 minutes to ensure stable moisture and avoid affecting the spectrum detection.

[0038] Detection operation: take 15.0 g of treated sorghum powder, load it into a near-infrared spectrometer, the wavelength range is 1100-2500 nm, rotate the sample cup, and scrape the surface with a scraper; after preheating the instrument for 15 minutes, perform background correction, place the sample cup into the sample chamber, select the "total starch analysis" mode, and automatically collect the reflection spectrum at 1930 nm (starch O-H bond frequency absorption peak) and 2100 nm (C-O bond secondary frequency).

[0039] Calculation method: the system calculates the total starch content (%) = (A 1930 / A 2100 )×K+B, wherein K=0.873, B=12.36, the model R 2 =0.98.

[0040] Amylopectin proportion detection Sample pretreatment: Take the degranulation sorghum sample within 24 hours, crush it with a cyclone crusher at a speed of 12000 rpm for 15 seconds, pass it through a 0.5 mm standard sieve, and take the undersize and place it in a desiccator to balance the moisture, avoiding humidity affecting the starch molecular structure.

[0041] Detection operation: Take 10.0 g of sorghum powder, lay it flat on the bottom of the near-infrared spectrometer sample cup, and press it flat with a sample press at a pressure of 20 N to make the surface smooth and crack-free; preheat the instrument for 10 minutes, place the sample in the sample chamber and close the light shield cover, select the "starch component analysis" mode, and automatically collect the reflectance spectrum at 1680 nm (amylose characteristic peak) and 2180 nm (amylopectin characteristic peak).

[0042] Calculation method: Amylopectin proportion (%) = [A 2180 / (A 1680 +A 2180 )] x β, where β = 1.052, calibrated by comparison with high performance liquid chromatography.

[0043] Tannin content detection Extraction operation: Take 20 g of ground sorghum sample and place it in a 500 ml round-bottom flask, add 300 ml of 70% ethanol solution, connect the reflux condenser device, heat in a 60°C water bath for 2 hours to ensure complete dissolution of tannins; cool the extract to room temperature, filter it with a medium-speed qualitative filter paper in a Buchner funnel, and collect the filtrate.

[0044] Color development and detection: Turn on the ultraviolet-visible spectrophotometer, preheat for 20 minutes, and calibrate it; set the wavelength scan range to 400-600 nm; take 10 ml of the filtrate into a 50 ml volumetric flask, add 5 ml of 5% vanillin-methanol solution, then quickly add 5 ml of concentrated hydrochloric acid, shake well, and let it stand at 25°C in the dark for 30 minutes to ensure complete color development; use a 1 cm cuvette, prepare a blank control with 70% ethanol solution following the same color development steps, and measure the absorbance at 490 nm, taking the average of three parallel measurements.

[0045] Calculation method: According to the gallic acid standard curve, concentration 0-2.0 g / 100 g, R 2 = 0.99, calculate the tannin content (unit: g / 100 g).

[0046] Potassium ion content detection Extraction operation: take 5 g of sorghum sample crushed and passed through a 60 mesh sieve (accurate to 0.0001 g), place it in a 250 ml flask, add 100 ml of deionized water, seal with sealing film, and shake at 25°C, 150 r / min for 2 hours to promote potassium ion dissolution; transfer the extract to a centrifuge tube, centrifuge at 4000 r / min for 10 minutes, and take the supernatant for standby.

[0047] Standard curve drawing: take 0.1907 g of potassium chloride reference reagent dried at 105°C for 2 hours, dissolve in a 100 ml volumetric flask, and dilute to volume, with a concentration of 1000 μg / ml; take 0 ml, 1 ml, 2 ml, 4 ml, 6 ml, and 8 ml of the solution into a 100 ml volumetric flask, respectively, and dilute to volume, to obtain standard solutions of 0 μg / ml, 10 μg / ml, 20 μg / ml, 40 μg / ml, 60 μg / ml, and 80 μg / ml; after preheating the flame photometer for 30 minutes, measure the absorbance from low concentration to high concentration, and automatically generate a standard curve, R 2 ≥0.995.

[0048] Calculation method: dilute the supernatant appropriately to ensure that the concentration is within the range of the standard curve, determine the concentration after measuring the absorbance, and calculate according to the formula: potassium ion content (mg / kg) = C × V × n / m (C is the concentration found in μg / ml, V = 100 ml, n is the dilution multiple, and m is the sample mass in g), with the result rounded to three significant digits.

[0049] Single item scoring standard: Starch: score according to the table below (e.g. 65.4% gets 90 points);

[0050] Amylopectin proportion: score according to the table below (e.g. 92.01% gets 80 points);

[0051] Tannin: score according to the table below (e.g. 1.13% gets 80 points);

[0052] Potassium ion: score according to the table below (e.g. 4026.8 mg / kg gets 80 points).

[0053]

[0054] Comprehensive score calculation: F = 0.3 × W + 0.2 × X + 0.3 × Y + 0.2 × Z (e.g. sample 1: 0.3 × 90 + 0.2 × 80 + 0.3 × 80 + 0.2 × 80 = 83 points).

[0055] Results: The detection results and time consumption of 10 samples are shown in the table below. The average time consumption for each sample is 245 minutes, and 3 samples (No. 2, 8, and 10) are unqualified, with a unqualified product rate of 30%.

[0056]

[0057] The detection efficiency of the test group is improved by 80% (1448 minutes → 245 minutes) compared to the control group; The unqualified product detection rate of the test group (30%) is higher than that of the control group (20%), and the identification of inferior sorghum is more accurate; The test group realizes quality digital grading through comprehensive scores, and the determination results are more intuitive (e.g., sample 5 scores 88 points, better than sample 1's 83 points).

[0058] Example 2 Verification of the influence of the evaluation method on the brewing effect Sample and grouping Select 20 batches of sorghum from Jinhua Maotai Town Winery, randomly divide them into a control group (10 batches) and a test group (10 batches), and evaluate them using traditional methods and the method of the present application, respectively. Qualified samples are used for workshop brewing production.

[0059] Control group: Evaluation criteria: moisture ≤13%, starch ≥63%, amylopectin ratio ≥90%, bulk density ≥740 g / L, and thousand seed weight ≥16 g are considered as qualified.

[0060] Brewing results: Track the liquor yield and superior liquor rate of 10 batches of qualified sorghum, and the results are shown in the table below. The average liquor yield is 55.17%, and the average superior liquor rate is 80.75%.

[0061]

[0062] Experimental group Evaluation criteria: detect and calculate the comprehensive score according to the evaluation method of the experimental group in Example 1, and F ≥80 points is considered as qualified (F ≥90 points is used for superior sauce liquor brewing).

[0063] Brewing results: Track the liquor yield and superior liquor rate of 10 batches of qualified sorghum, and the results are shown in the table below. The average liquor yield is 56.41%, and the average superior liquor rate is 83.91%.

[0064]

[0065] The average liquor yield of the test group is increased by 1.24 percentage points (55.17% → 56.41%) compared to the control group; The average superior liquor rate of the test group is increased by 3.16 percentage points (80.75% → 83.91%) compared to the control group; The method can accurately distinguish the quality difference of sorghum (for example, the 93-point sample has an excellent liquor rate of 84.25%, which is significantly higher than 82.94% of the 86-point sample), guide the classification of sorghum, and stably improve the brewing effect.

[0066] The above merely describes preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating the quality of sorghum used in brewing high-quality sauce-flavored liquor, characterized in that, Includes the following steps: (1) Obtain multiple representative samples from the same batch of sorghum using a multi-point sampling method; (2) The total starch content, amylopectin content, tannin content and potassium ion content in each sample were tested respectively; (3) Score each indicator by comparing its detection value with the preset scoring standard: Total starch content score W: >67.0% gets 100 points, 65.0% < content ≤67.0% gets 90 points, 63.0% < content ≤65.0% gets 80 points, 61.0% < content ≤63.0% gets 70 points, and ≤61.0% gets 60 points. Branched-chain starch percentage score X: >95.0% gets 100 points, 93.0% < percentage ≤95.0% gets 90 points, 90.0% < percentage ≤93.0% gets 80 points, 85.0% < percentage ≤90.0% gets 70 points, and ≤85.0% gets 60 points; Tannin content score Y: 1.5% < content ≤ 1.8% gets 100 points, 1.2% < content ≤ 1.5% gets 90 points, 0.9% < content ≤ 1.2% gets 80 points, 0.6% < content ≤ 0.9% gets 70 points, ≤ 0.6% or > 1.8% gets 60 points; Potassium ion content score Z: >4500mg / kg gets 100 points, 4200<content ≤4500mg / kg gets 90 points, 3900<content ≤4200mg / kg gets 80 points, 3600<content ≤3900mg / kg gets 70 points, ≤3600mg / kg gets 60 points; (4) Calculate the overall quality score F: F = 0.3 × W + 0.2 × X + 0.3 × Y + 0.2 × Z; (5) Classified according to comprehensive score: F≥90: High-quality brewing sorghum; 80≤F<90: Qualified brewing sorghum; F < 80: Unqualified sorghum.

2. The evaluation method as described in claim 1, characterized in that, The total starch content was determined using near-infrared spectroscopy, with reflectance spectra acquired at wavelengths of 1930 nm and 2100 nm. 1930 A represents the absorbance measured at a wavelength of 1930 nm. 2100 The absorbance was measured at a wavelength of 2100 nm and calculated using the formula: Total starch (%) = (A 1930 / A 2100 Calculate K by multiplying K by K and 12.36, and K = 0.873 ± 0.

005.

3. The evaluation method as described in claim 1, characterized in that, The amylopectin percentage was determined using near-infrared spectroscopy, with reflectance spectra collected at wavelengths of 1680 nm and 2180 nm, and calculated according to the formula: Amylopectin (%) = [A 2180 / (A 1680 +A 2180 )]×β is calculated, β=1.052±0.

003.

4. The evaluation method as described in claim 1, characterized in that, The tannin content detection process includes: extraction with 70% ethanol solution under reflux in a water bath at 60°C for 2 hours; filtration of the extract with medium-speed qualitative filter paper after cooling; adding 5ml of 5% vanillin-methanol solution and 5ml of concentrated hydrochloric acid to 10ml of the filtrate, and developing the solution at 25°C in the dark for 30 minutes; measuring the absorbance at a wavelength of 490nm, and calculating the tannin content based on the gallic acid standard curve.

5. The evaluation method as described in claim 1, characterized in that, The detection of potassium ion content includes: extracting the supernatant with deionized water by shaking; determining the potassium ion content by flame photometry and calculating it according to the formula potassium ion (mg / kg) = C × V × n / m, where C is the standard curve concentration (μg / ml), V is the volume of the extract (ml), n is the dilution factor, and m is the sample mass (g).

6. The evaluation method as described in claim 1, characterized in that, In step (2), each sample needs to be tested in parallel 3 times, and the arithmetic mean is taken as the final test value.

7. The evaluation method as described in claim 1, characterized in that, The application rules for the comprehensive score F are as follows: F≥90: Used for brewing premium-grade sauce-flavored liquor; 80≤F<90: Used for first-grade sauce-flavored liquor brewing; F<80: Downgrade or reject.

8. The method according to any one of claims 1-7, characterized in that, The total testing time for all samples is ≤4 hours, and the testing is completed within 24 hours after the samples are threshed.

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