Multi-stage parameter high-temperature yeast fermentation quality evaluation method and system

Abstract

The invention relates to the technical field of white spirit brewing, in particular to a multi-stage parameter high-temperature yeast fermentation quality evaluation method and system and a computer readable storage medium, and the method comprises the following steps: in a yeast blank preparation stage, constructing a yeast blank raw material quality and forming evaluation system; in a koji block fermentation stage, constructing a koji block fermentation process quality evaluation system; the yeast block fermentation stage is divided into an early stage, a middle stage and a later stage from time, and yeast blocks in the yeast block fermentation stage are divided into an upper layer, a middle layer and a lower layer in space; respectively constructing a substrate consumption model, a microbial growth model and a metabolic enzyme generation model for each yeast layer of each fermentation stage of the yeast blocks; and re-evaluating the fermentation quality of the koji blocks by judging whether the koji block fermentation process accords with a substrate consumption model, a microbial growth model and a metabolic enzyme generation model or not. The invention provides an objective quantitative yeast fermentation evaluation standard, and can improve the quality and production efficiency of white spirit fermentation.

Description

Technical Field

[0001] The present invention relates to the technical field of Baijiu brewing, and in particular to a method, system and computer-readable storage medium for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters. Background Art

[0002] Chinese Baijiu has significant category diversity, among which Maotai-flavor Baijiu is famous for its unique Maotai flavor, elegant and delicate taste, and the characteristic of lasting fragrance in the empty cup. The formation of this typical style essentially stems from the microbial metabolic regulation mechanism of high-temperature Daqu.

[0003] High-temperature Daqu is a multi-functional microbial preparation prepared by using wheat as raw material and inoculating mother Daqu, followed by high-temperature fermentation (60 - 70 °C). Its fermentation is a process of ternary coordination of material system - bacterial system - enzyme system. The material system (chemical components) serves as the main line of metabolism, the bacterial system (microorganisms) constitutes the functional core, and the enzyme system (biological enzymes) plays the role of metabolic bridge. The three jointly determine the quality of high-temperature Daqu in the time dimension. Due to the influence of the spatial structure of the koji room, the Daqu in different vertical layers in the same koji room shows significant spatial heterogeneity. However, the current quality evaluation system lacks evaluation in the spatial dimension, relies on subjective experience judgment, and lacks objective quantitative standards, which will affect the stability and consistency of Daqu quality, resulting in uneven quality of Baijiu fermentation, reducing production efficiency, and being unfavorable for enterprises to stabilize product quality and carry out standardized production. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the problems in the prior art that the evaluation of Daqu fermentation lacks the spatial dimension, relies on subjective experience judgment, lacks objective quantitative standards, resulting in uneven quality of Baijiu fermentation and reducing production efficiency.

[0005] To solve the above technical problem, the present invention provides a method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters, including:

[0006] In the stage of koji embryo preparation, a quality and forming evaluation system for koji embryo raw materials is constructed to evaluate the quality of koji embryo raw materials, including: core parameters of the quality of primary wheat raw materials, control parameters of secondary pretreatment processes, and physical property parameters of tertiary formed koji embryos;

[0007] In the stage of koji block fermentation, a quality evaluation system for the koji block fermentation process is constructed to preliminarily evaluate the quality of koji block fermentation, including: primary environmental parameters, secondary physicochemical parameters, and tertiary flavor substance parameters;

[0008] According to the temperature of the koji blocks, the koji block fermentation stage is divided into the early stage, the middle stage and the late stage in terms of time; according to the growth of strains, the consumption of substrates and the production of products, the koji blocks in the koji block fermentation stage are divided into the upper layer, the middle layer and the lower layer in terms of space; substrate consumption models, microbial growth models and metabolic enzyme production models are respectively constructed for each koji layer in each fermentation stage of the koji blocks;

[0009] The quality of koji block fermentation is re-evaluated based on whether the koji block fermentation process conforms to the substrate consumption model, the microbial growth model and the metabolic enzyme production model.

[0010] Preferably, in the koji embryo raw material quality and forming evaluation system, the core parameters of the first-class wheat raw material quality include the fat content, starch content and bulk density of wheat; the control parameters of the second-class pretreatment process include the degree of pulverization, moisture content of tempering wheat, inoculation ratio and koji pressing strength; the physical property parameters of the third-class formed koji embryo include koji block hardness, plasticity, porosity and cohesion.

[0011] Preferably, in the quality evaluation system of the koji block fermentation process, the first-class environmental parameters include the initial fermentation environment temperature and humidity of each koji layer, the temperature and humidity of the koji blocks, and the proportion of the air components in the fermentation environment; the second-class physicochemical parameters include the abundance of microorganisms, microbial metabolic function indexes and substrate consumption indexes; the third-class flavor substance parameters include tetramethylpyrazine and 3-methylthiopropanol.

[0012] Preferably, among the second-class physicochemical parameters, the abundance of the microorganisms includes the change amount of the relative proportion of molds, bacteria and yeasts; the microbial metabolic function indexes include saccharifying power, liquefying power and fermenting power; the substrate consumption indexes include the degradation rates of raw material crude starch, crude protein, fat and cellulose.

[0013] Preferably, the early stage of the koji block fermentation stage is the temperature rising stage;

[0014] In the upper layer of the koji blocks in the early stage, the substrate with the largest consumption proportion is the carbon source, the growing strains are Bacillus and Thermus, and the produced products are protease and amylase;

[0015] In the middle layer of the koji blocks in the early stage, the substrate with the largest consumption proportion is the carbon source, the growing strains are Multispora and Thermus, and the produced products are protease and amylase;

[0016] In the lower layer of the koji blocks in the early stage, the substrate with the largest consumption proportion is the carbon source, the growing strains are Weissella and Saccharomycopsis, and the produced products are protease and amylase.

[0017] Preferably, the middle stage of the koji block fermentation stage is the temperature dropping stage;

[0018] In the upper layer of the koji blocks in the middle stage, the substrates with the largest consumption proportions are the carbon source and the nitrogen source, the growing strains are Bacillus and Thermus, and the produced products are protease and amylase;

[0019] In the middle layer of the koji block during the middle stage, the substrates with the largest consumption proportion are carbon sources and nitrogen sources. The growing strains are Corynebacterium kribbense and Thermus, and the generated products are protease and amylase.

[0020] In the lower layer of the koji block during the middle stage, the substrates with the largest consumption proportion are carbon sources and nitrogen sources. The growing strains are Bacillus and Thermus, and the generated products are protease and lipase.

[0021] Preferably, the later stage of the koji block fermentation stage is the temperature drop stage.

[0022] In the upper layer of the koji block during the later stage, the substrates with the largest consumption proportion are carbon sources and nitrogen sources. The growing strain is Bacillus, and the generated products are protease, amylase and cellulase.

[0023] In the middle layer of the koji block during the later stage, the substrates with the largest consumption proportion are carbon sources and nitrogen sources. The growing strain is Bacillus, and the generated products are protease, amylase and cellulase.

[0024] In the lower layer of the koji block during the later stage, the substrates with the largest consumption proportion are carbon sources and nitrogen sources. The growing strain is Corynebacterium kribbense, and the generated products are protease, lipase and cellulase.

[0025] Preferably, the substrate consumption model adopts the Boltzmann model, the microbial growth model adopts the Dose Resp model, and the metabolic enzyme generation model adopts the SGompertz model.

[0026] The present invention also provides a multi-level parameter high-temperature Daqu fermentation quality evaluation system, including:

[0027] A koji embryo raw material quality and molding evaluation system construction module, which is used to construct a koji embryo raw material quality and molding evaluation system during the koji embryo preparation stage to evaluate the quality of koji embryo raw materials, including: the core parameters of the first-level wheat raw material quality, the control parameters of the second-level pretreatment process, and the physical characteristics parameters of the third-level formed koji embryo.

[0028] A koji block fermentation process quality evaluation system construction module, which is used to construct a koji block fermentation process quality evaluation system during the koji block fermentation stage to preliminarily evaluate the quality of koji block fermentation, including: the first-level environmental parameters, the second-level physical and chemical parameters, and the third-level flavor substance parameters.

[0029] A model construction module, which is used to divide the koji block fermentation stage into the early stage, the middle stage and the later stage according to time based on the koji block temperature; divide the koji block in the koji block fermentation stage into the upper layer, the middle layer and the lower layer in space according to the growth of strains, substrate consumption and generated products; and respectively construct a substrate consumption model, a microbial growth model and a metabolic enzyme generation model for each koji layer in each fermentation stage of the koji block.

[0030] An evaluation module is used to re-evaluate the quality of the Qu block fermentation based on whether the Qu block fermentation process conforms to the substrate consumption model, the microbial growth model, and the metabolic enzyme generation model.

[0031] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters are realized.

[0032] The above technical solution of the present invention has the following beneficial effects compared with the prior art:

[0033] The method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters according to the present invention realizes the transformation of the process parameter system from experience-driven to data-driven by establishing a quality evaluation system for Qu embryo raw materials and forming evaluation system and a quality evaluation system for the Qu block fermentation process including three-level parameters; aiming at the vertical space heterogeneity in the Qu room, after dividing the fermentation stage in time, the Qu blocks in the fermentation stage are further divided in space, and a substrate consumption model, a microbial growth model, and a metabolic enzyme generation model are respectively constructed for each Qu layer in each fermentation stage, realizing the quantitative evaluation and optimized control of the fermentation quality of high-temperature Daqu at the spatio-temporal scale. The present invention combines the quality evaluation system for Qu embryo raw materials and forming evaluation system, the quality evaluation system for the Qu block fermentation process, and the substrate consumption model, the microbial growth model, and the metabolic enzyme generation model, better describes the changes and correlations of substrate consumption, microbial growth, and product generation during the fermentation process, systematically and standardly establishes the differences in fermentation quality between different times and different Qu layers, provides an objective and quantitative evaluation standard for Daqu fermentation, can improve the quality and production efficiency of Baijiu fermentation, and provides support for subsequent intelligent Daqu fermentation. Description of the Drawings

[0034] In order to make the content of the present invention easier to be clearly understood, the following further details the present invention according to the specific embodiments of the present invention in conjunction with the drawings, where:

[0035] Figure 1 is a flowchart of the method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters of the present invention;

[0036] Figure 2 is a schematic diagram of the change of starch content in different Qu layers;

[0037] Figure 3 is a schematic diagram of the change of protein content in different Qu layers;

[0038] Figure 4 is a schematic diagram of the change of fat content in different Qu layers. Detailed Embodiments

[0039] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the exemplified embodiments are not intended to limit the present invention.

[0040] Embodiment 1

[0041] Referring to Figure 1 as shown, the present invention provides a method for evaluating the quality of multi-level parameter high-temperature Daqu fermentation, including:

[0042] S1: In the stage of preparing the koji embryo, a quality and forming evaluation system for the koji embryo raw materials is constructed to evaluate the quality of the koji embryo raw materials, including: the core parameters of the quality of the first-level wheat raw materials, the control parameters of the second-level pretreatment process, and the physical property parameters of the third-level formed koji embryo.

[0043] In the quality and forming evaluation system of the koji embryo raw materials, the core parameters of the quality of the first-level wheat raw materials include the fat content, starch content, and bulk density of wheat; the control parameters of the second-level pretreatment process include the degree of pulverization, moisture content of conditioned wheat, inoculation ratio, and koji pressing strength; the physical property parameters of the third-level formed koji embryo include the hardness, plasticity, porosity, and cohesion of the koji block.

[0044] S2: In the stage of koji block fermentation, a quality evaluation system for the koji block fermentation process is constructed to preliminarily evaluate the quality of the koji block fermentation, including: the first-level environmental parameters, the second-level physical and chemical parameters, and the third-level flavor substance parameters.

[0045] In the quality evaluation system of the koji block fermentation process, the first-level environmental parameters include the initial fermentation environment temperature and humidity of each koji layer, the temperature and humidity of the koji block, and the proportion of CO2 and O2 components in the fermentation environment air; the second-level physical and chemical parameters include the abundance of microorganisms, the microbial metabolic function indexes, and the substrate consumption indexes; the third-level flavor substance parameters are the flavor substances that form the characteristic "rich sauce aroma and elegant and delicate" style of sauce-flavored liquor, including tetramethylpyrazine and 3-methylthiopropanol.

[0046] Among the second-level physical and chemical parameters, the abundance of the microorganisms includes the change amount of the relative proportions of molds, bacteria, and yeasts; the microbial metabolic function indexes include saccharifying power, liquefying power, and fermenting power; the substrate consumption indexes include the degradation rates of raw material crude starch, crude protein, fat, and cellulose.

[0047] S3: According to the temperature of the koji block, the koji block fermentation stage is divided into the early stage (low-temperature bacteria cultivation period), the middle stage (high-temperature bacteria cultivation period), and the late stage (ripening and flavor generation period) in terms of time; according to the growth of strains, substrate consumption, and generated products, the koji blocks in the koji block fermentation stage are divided into the upper layer, the middle layer, and the lower layer in terms of space.

[0048] The early stage of the koji fermentation stage is the temperature rising stage; in the upper layer of the koji block in the early stage, the substrate with the largest consumption proportion is carbon source, the growing strains are Bacillus and Thermophilic bacteria, and the generated products are protease and amylase; in the middle layer of the koji block in the early stage, the substrate with the largest consumption proportion is carbon source, the growing strains are Multispora and Thermophilic bacteria, and the generated products are protease and amylase; in the lower layer of the koji block in the early stage, the substrate with the largest consumption proportion is carbon source, the growing strains are Weissella and Saccharomycopsis, and the generated products are protease and amylase.

[0049] The middle stage of the koji fermentation stage is the temperature dropping stage; in the upper layer of the koji block in the middle stage, the substrates with the largest consumption proportions are carbon source and nitrogen source, the growing strains are Bacillus and Thermophilic bacteria, and the generated products are protease and amylase; in the middle layer of the koji block in the middle stage, the substrates with the largest consumption proportions are carbon source and nitrogen source, the growing strains are Corynebacterium kribbense and Thermophilic bacteria, and the generated products are protease and amylase; in the lower layer of the koji block in the middle stage, the substrates with the largest consumption proportions are carbon source and nitrogen source, the growing strains are Bacillus and Thermophilic bacteria, and the generated products are protease and lipase.

[0050] The late stage of the koji fermentation stage is the temperature dropping stage; in the upper layer of the koji block in the late stage, the substrates with the largest consumption proportions are carbon source and nitrogen source, the growing strain is Bacillus, and the generated products are protease, amylase and cellulase; in the middle layer of the koji block in the late stage, the substrates with the largest consumption proportions are carbon source and nitrogen source, the growing strain is Bacillus, and the generated products are protease, amylase and cellulase; in the lower layer of the koji block in the late stage, the substrates with the largest consumption proportions are carbon source and nitrogen source, the growing strain is Corynebacterium kribbense, and the generated products are protease, lipase and cellulase.

[0051] S4: Respectively construct a substrate consumption model, a microbial growth model and a metabolic enzyme generation model for each koji layer in each fermentation stage of the koji block.

[0052] Based on the quality differences among different stages and different koji layers, respectively construct a substrate consumption model, a microbial growth model and a metabolic enzyme generation model according to multi-level parameters from raw material evaluation to the fermentation process.

[0053] The substrate consumption model adopts the Boltzmann model, and the model formula is Among them, y1 represents the response variable, i.e., the substrate consumption; A1 represents the maximum response value, i.e., the maximum possible value of the response variable y when the independent variable x approaches positive infinity; A2 represents the minimum response value, i.e., the minimum possible value of the response variable y when the independent variable x approaches negative infinity; x represents the independent variable, such as substrate concentration, temperature, etc.; x0 represents the midpoint, i.e., the x value corresponding to when the response variable y changes by half from A2 to A1; dx represents the slope of the curve, indicating the rate of change of the y value. Thus, the bacteria can grow and produce corresponding metabolic enzymes. The metabolic enzymes in high-temperature Daqu include protease, amylase, lipase, cellulase, etc.

[0054] The growth of microorganisms mainly targets dominant microorganisms including bacteria and fungi. The model used is the Dose Resp model, and the model formula is Among them, y2 represents the response variable, i.e., the growth of bacteria; A1 represents the maximum response value, i.e., the maximum possible value of the response variable y when the independent variable x approaches positive infinity; A2 represents the minimum response value, i.e., the minimum possible value of the response variable y when the independent variable x approaches negative infinity; x represents the independent variable, such as substrate concentration, temperature, etc.; x0 represents the half-saturation constant, i.e., the x value corresponding to when the response variable y reaches the midpoint of A1 and A2; p represents the slope of the curve, indicating the rate of change of the y value.

[0055] The metabolic enzyme generation model uses the SGompertz model, and the model formula is y3 = αe - e (-k(x-xc)) , where y3 represents the response variable, i.e., the enzyme activity; α represents the maximum response value, i.e., the maximum possible value of the response variable y when the independent variable x approaches positive infinity; e represents the base of the natural logarithm, approximately equal to 2.71828; k represents the growth rate constant, indicating the rate of change of the y value; x represents the independent variable, such as time, substrate concentration, etc.; xc represents the lag time or starting point, i.e., the x value corresponding to when the response variable y starts to increase significantly.

[0056] Through model fitting, the optimized range of secondary parameters at different stages (early / mid / late) and different levels (upper / middle / lower) is obtained, and the establishment and analysis are carried out at different stages and different levels.

[0057] S5: Re-evaluate the quality of the Qu block fermentation based on whether the Qu block fermentation process conforms to the substrate consumption model, the microorganism growth model, and the metabolic enzyme generation model.

[0058] Based on the selection of the above first-, second-, and third-level parameters and the establishment of the model, by using an artificial intelligence system to identify the fermentation state of the koji blocks and predict the fermentation trend, connecting the control in the first- and second-level indicators with the third-level parameters, adjusting the control parameters, and responding to the characterization parameters, finally, by studying the kinetic relationship and the law of change over time among environmental factors, substrate consumption, microbial growth, and metabolic activities, a digital, standardized, and intelligent evaluation system for quantifying the high-temperature Daqu fermentation quality at each stage through multiple levels of parameters is formed.

[0059] A method for evaluating the high-temperature Daqu fermentation quality with multiple levels of parameters according to the present invention realizes the transformation of the process parameter system from experience-driven to data-driven by establishing an evaluation system for the quality and forming of koji embryo raw materials and an evaluation system for the quality of the koji block fermentation process, which includes three levels of parameters; aiming at the vertical spatial heterogeneity in the koji-making room, after dividing the fermentation stage in terms of time, the koji blocks in the fermentation stage are further divided in terms of space, and a substrate consumption model, a microbial growth model, and a metabolic enzyme generation model are respectively constructed for each koji layer in each fermentation stage, so as to realize the quantitative evaluation and optimal control of the fermentation quality of high-temperature Daqu at the spatio-temporal scale. The present invention combines the evaluation system for the quality and forming of koji embryo raw materials, the evaluation system for the quality of the koji block fermentation process, and the substrate consumption model, the microbial growth model, and the metabolic enzyme generation model, better describes the changes and correlations among substrate consumption, microbial growth, and product generation during the fermentation process, systematically and standardly establishes the differences in fermentation quality among different times and different koji layers, provides an objective and quantitative evaluation standard for Daqu fermentation, can improve the quality and production efficiency of Baijiu fermentation, and provides support for subsequent intelligent Daqu fermentation.

[0060] Example Two

[0061] This example provides a specific example of a method for evaluating the high-temperature Daqu fermentation quality with multiple levels of parameters, including:

[0062] S11: Construct an evaluation system for the quality and forming of koji embryo raw materials.

[0063] In this embodiment, on the basis of the traditional process, the primary and secondary indicators in the koji embryo preparation stage are clearly divided and the core parameters are analyzed, so as to establish an evaluation system for the quality of koji embryo raw materials and their forming. The koji embryo preparation includes the first, second, and third level parameters in the raw material evaluation system. The first level parameters in the raw material evaluation system are divided into the raw material preparation stage before fermentation, the second level parameters are divided into the pretreatment process, and the third level is divided into the physical properties of the formed koji embryo. The cross-regional stratified sampling strategy is adopted to collect raw material samples and koji embryos from distilleries in multiple regions. Five different regions of wheat raw materials are collected and numbered 1-5. For the koji blocks during the fermentation process, the sampling ranges are the upper layer (defined as layers 1-3), the middle layer (defined as layers 4-6), and the lower layer (defined as layers 7-9). The sampling time points are 2, 8, 16, 24, and 30 days, with all-weather humidity and temperature monitoring. The first level parameters in the raw material evaluation system are specifically divided into the starch content in wheat (51.33-67.33%), the fat content (1.17-2.23%), and the bulk density (819.3-820.6 g L -1 ). The second level parameters are specifically divided into the grinding degree (11.35-12.36%), the moisture content of conditioned wheat (5-8%), the inoculation ratio (6-8%), and the mechanical koji-making pressure (5500-6200 N). The third level parameters in the raw material evaluation system mainly analyze the quality of the koji blocks during the fermentation process, mainly from the physical properties of the koji blocks, including the hardness of the koji blocks (2137-6304), the moisture content (15-28%), the porosity (25-35%), and the cohesion (43-60 kPa).

[0064] The analysis results of the quality traits of different raw material wheat grains, the raw material pretreatment process, and the analysis results of the change ranges of the physical properties of different koji layers at different sampling time points are respectively referred to Table 1, Table 2, and Table 3.

[0065] Table 1 Analysis results of the quality traits of different raw material wheat grains

[0066]

[0067] Table 2 Raw material pretreatment process

[0068]

[0069] Table 3 Analysis results of the change ranges of the physical properties of different koji layers at different sampling time points

[0070]

[0071]

[0072] S21: Construct an evaluation system for the quality of the koji block fermentation process.

[0073] In this implementation case, samples were collected from distilleries in multiple regions at time points of 2, 8, 16, 24, and 30 days. The sampling range of the koji blocks was divided into the upper layer (1 - 3), the middle layer (4 - 6), and the lower layer (7 - 9), and the humidity and temperature were monitored all day long. Based on the traditional process, the primary, secondary, and tertiary indicators in the in-house fermentation stage were clearly defined, and the physicochemical and quality core indicators during fermentation were analyzed, thereby establishing a quality evaluation system for the koji block fermentation process. The koji block fermentation stage covers the initial fermentation environment temperature and humidity indicators, koji block temperature and humidity, and the proportion of air components in the fermentation environment among the primary parameters; the koji block fermentation stage covers the quality characterization indicators among the secondary parameters, mainly targeting the abundance and metabolic function indicators of microorganisms, specifically reflected in the changes in the content of raw material crude starch, crude protein, fat, and cellulose in the substrate consumption indicators during the fermentation process. The change in the microbial abundance is divided into the changes in the relative proportions of molds, bacteria, and yeasts, and the microbial metabolic function indicators are divided into saccharifying power, liquefying power, and fermenting power. The important microbial metabolic enzymes include protease, amylase, lipase, and cellulase. The tertiary evaluation parameters are divided into tetramethylpyrazine and 3-methylthiopropanol. The environmental monitoring indicators for different koji layers refer to Table 4

[0074] Table 4 Environmental Monitoring Indicators for Different Koji Layers

[0075]

[0076] Furthermore, the utilization degree of the components in wheat during the high-temperature koji fermentation process in different koji layers was determined by chemical methods. The changes in starch, protein, and fat in different koji layers over the fermentation time are as Figures 2 to 4 shown

[0077] S31: According to the koji block temperature, the koji block fermentation stage is divided into the early stage (low-temperature incubation period), the middle stage (high-temperature incubation period), and the late stage (post-ripening and flavor-generating period) in terms of time; according to the growth of strains, substrate consumption, and generated products, the koji blocks in the koji block fermentation stage are divided into the upper layer, the middle layer, and the lower layer in terms of space

[0078] The changes in the microbial community have obvious spatio-temporal succession characteristics. The high-throughput sequencing technology was used to analyze the changing trends of microorganisms in the early stage (upper layer, middle layer, lower layer), middle stage (upper layer, middle layer, lower layer), and late stage (upper layer, middle layer, lower layer). The chemical method was adopted to determine the changes in liquefaction ability, saccharification ability, esterification ability, and fermentation ability. The content of tetramethylpyrazine and 3-methylthiopropanol at different positions in the late stage was only determined by GC-MS for the functional active substances. In the early stage, Bacillus and Thermus were the dominant flora in the upper layer, accounting for 30.99%-44.67% and 18.32%-42.11% of the total respectively. In the middle layer, Multispora and Thermus were the dominant flora, accounting for 36.32% and 17.78%-54.85% of the total respectively. In the lower layer, Weissella and Saccharomycopsis were the dominant flora, accounting for 28.49% and 43.40% of the total respectively. The saccharification ability of the basic fermentation index in the upper layer in the early stage was 830-410 mg / (g·h) -1 、the liquefaction ability was 0.011-0.02 g / (g·h) -1 、the fermentation ability was 0.41-0.2 g / (g·72·h) -1 ;The saccharification ability of the basic fermentation index in the middle layer in the early stage was 820-550 mg / (g·h) -1 、the liquefaction ability was 0.02-0.13 g / (g·h) -1 、the fermentation ability was 0.2-0.52 g / (g·72·h) -1 ;The saccharification ability of the basic fermentation index in the lower layer in the early stage was 900-850 mg / (g·h) -1 、the liquefaction ability was 0.02-0.3 g / (g·h) -1 、the fermentation ability was 0.41-0.52 g / (g·72·h) -1 ;For the metabolic enzyme activity index, in the early stage, amylase in the upper layer accounted for 38% of the total metabolism, protease accounted for 37% of the total metabolism, and cellulase accounted for 3.9% of the total metabolism; in the middle layer, amylase accounted for 35% of the total metabolism, protease accounted for 50% of the total metabolism, and cellulase accounted for 5.9% of the total metabolism; in the lower layer, amylase accounted for 33% of the total metabolism, protease accounted for 42% of the total metabolism, and cellulase accounted for 5.3% of the total metabolism.

[0079] In the middle stage, Bacillus and Thermus were the dominant flora in the upper layer, accounting for 30.99%-44.67% and 18.32%-42.11% of the total respectively. Corynebacterium and Thermus were the dominant flora in the middle layer, accounting for 32.16%-40.82% and 17.78-54.85% of the total respectively. Bacillus and Thermus were the dominant flora in the lower layer, accounting for 27.75% and 30.33% of the total respectively. The saccharification ability of the basic fermentation index in the upper layer in the middle stage was 820-420 mg / (g·h) -1 、the liquefaction ability was 0.02-0.3 g / (g·h)-1 The fermenting power is 0.03 - 0.17 g / (g·72 h) -1 ; For the intermediate-stage middle-layer basic fermentation index, the saccharifying power is 820 - 750 mg / (g·h) -1 The liquefying power is 0.22 - 0.38 g / (g·h) -1 The fermenting power is 0.2 - 0.63 g / (g·72 h) -1 ; For the intermediate-stage lower-layer basic fermentation index, the saccharifying power is 1000 - 850 mg / (g·h) -1 The liquefying power is 0.38 - 0.5 g / (g·h) -1 The fermenting power is 0.42 - 0.65 g / (g·72 h) -1 ; For the metabolic enzyme activity index, in the intermediate-stage upper layer, amylase accounts for 42% of the total metabolism, protease accounts for 39% of the total metabolism, and cellulase accounts for 4.3% of the total metabolism; in the intermediate-stage middle layer, amylase accounts for 38% of the total metabolism, protease accounts for 53% of the total metabolism, and cellulase accounts for 6.2% of the total metabolism; in the intermediate-stage lower layer, amylase accounts for 36% of the total metabolism, protease accounts for 47% of the total metabolism, and cellulase accounts for 6.1% of the total metabolism.

[0080] In the later stage, Bacillus and Thermus are the dominant flora in the upper layer, accounting for 30.99% - 44.67% and 18.32% - 42.11% of the total respectively; Bacillus and Thermus are the dominant flora in the middle layer, accounting for 18.73% - 30.01% and 17.78% - 54.85% of the total respectively; Corynebacterium kutscheri and Larsenella are the dominant flora in the lower layer, accounting for 36.86% and 21.05% of the total respectively. For the later-stage upper-layer basic fermentation index, the saccharifying power is 980 mg / (g·h) -1 The liquefying power is 0.38 - 0.41 g / (g·h) -1 The fermenting power is 0.17 - 0.2 g / (g·72 h) -1 . For the later-stage middle-layer basic fermentation index, the saccharifying power is 850 - 800 mg / (g·h) -1 The liquefying power is 0.4 g / (g·h) -1 The fermenting power is 0.2 - 0.22 g / (g·72 h) -1 ; For the later-stage lower-layer basic fermentation index, the saccharifying power is 1100 - 1000 mg / (g·h) -1 The liquefying power is 0.6 - 1.4 g / (g·h) -1 The fermenting power is 0.75 - 0.8 g / (g·72 h) -1; The metabolic enzyme activity indexes are as follows: in the later stage, amylase in the upper layer accounts for 39% of the total metabolism, protease accounts for 37% of the total metabolism, and cellulase accounts for 3.9% of the total metabolism; in the middle layer in the later stage, amylase accounts for 37% of the total metabolism, protease accounts for 49% of the total metabolism, and cellulase accounts for 5.2% of the total metabolism; in the lower layer in the middle stage, amylase accounts for 35% of the total metabolism, protease accounts for 44% of the total metabolism, and cellulase accounts for 5.9% of the total metabolism. In the later stage, the content of tetramethylpyrazine in the upper layer is 450 - 500 μg / g, and the content of 3-methylthiopropanol is low or not detected; in the middle layer, the content of tetramethylpyrazine is 550 - 880 μg / g, and the content of 3-methylthiopropanol is medium; in the lower layer, the content of tetramethylpyrazine is 160 - 210 μg / g, and the content of 3-methylthiopropanol is high.

[0081] S41: For each fermentation stage of the koji block and each koji layer, respectively construct a substrate consumption model, a microbial growth model, and a metabolic enzyme generation model.

[0082] In the early stage of high-temperature Daqu fermentation, it is the temperature rising stage. The upper layer (layers 1 - 3) mainly consumes the carbon source in the substrate to promote the growth of Bacillus and Thermus, and produces protease and amylase; the middle layer (layers 4 - 6) mainly consumes the carbon source in the substrate to promote the growth of Multispora and Thermus, and produces protease and amylase; the lower layer (layers 7 - 9) mainly consumes the carbon source in the substrate to promote the growth of Weissella and Saccharomycopsis, and produces protease and amylase. From the parameter result data, the growth of bacteria, substrate consumption, and product generation are interconnected and interact with each other, being in a linkage state. The substrate consumption kinetic model uses the Boltzmann model to establish a fitting equation for the substrate consumption amount (starch and fat) and calculate the fitting coefficient. The fitting results show that for the upper layer, R 2 is 0.98732 and 0.9988, for the middle layer, R 2 is 0.99875 and 0.9968, for the lower layer, R 2 is 0.99699 and 0.9973. The fitting coefficients are all relatively high, and can well describe the substrate consumption situation in the upper, middle, and lower layers in the early stage; the substrate consumption rate has a direct relationship with the growth of bacteria, belonging to the typical growth "coupled" type. The OD values of the dominant bacteria growth in the upper, middle, and lower layers are used to establish a fitting kinetic equation and calculate the fitting coefficient using the Dose Resp model. For the upper layer, R 2 is 0.99601 and 0.9835, for the middle layer, R 2 is 0.99504 and 0.9785, for the lower layer, R 2 is 0.99607 and 0.97285. The fitting coefficients are all relatively high, and can well describe the growth situation of bacteria; the SGompertz model is used to perform non-linear fitting on the enzyme generation in the upper, middle, and lower layers during the fermentation process. For the upper layer, R 2 is 0.9983 and 0.98632, for the middle layer, R 2are 0.9987 and 0.9765, and the lower layer R 2 are 0.99877 and 0.98793, and the fitting coefficients are both high, which can well describe the enzyme production situation.

[0083] In the early stage of the fermentation stage, the upper, middle and lower layers use each model, and their fitting kinetic equations and fitting coefficients are respectively shown in Tables 5, 6 and 7.

[0084] Table 5 The models, fitting kinetic equations and fitting coefficients used in the upper layer in the early stage of the fermentation stage

[0085]

[0086]

[0087] Table 6 The models, fitting kinetic equations and fitting coefficients used in the middle layer in the early stage of the fermentation stage

[0088]

[0089] Table 7 The models, fitting kinetic equations and fitting coefficients used in the lower layer in the early stage of the fermentation stage

[0090]

[0091]

[0092] In the middle stage of the high-temperature Daqu fermentation, the temperature reaches the peak temperature stage. The upper layer (layers 1-3) mainly consumes the carbon and nitrogen sources in the substrate to promote the growth of Bacillus and Thermus, and produce protease and amylase; the middle layer (layers 4-6) mainly consumes the carbon and nitrogen sources in the substrate to promote the growth of Corynebacterium kribbense and Thermus, and produce protease and amylase; the lower layer (layers 7-9) mainly consumes the carbon and nitrogen sources in the substrate to promote the growth of Bacillus and Thermus, and produce protease and lipase. From the parameter result data, the growth of bacteria, the consumption of substrate and the production of products are interconnected and interact with each other, and are in a linkage state. The substrate consumption kinetic model uses the Boltzmann model to establish a fitting equation and calculate the fitting coefficient for the substrate consumption amount (starch and fat). The fitting results show that the upper layer R 2 are 0.98932 and 0.98987, the middle layer R 2 are 0.9789 and 0.9899, the lower layer R 2 are 0.9873 and 0.98894, and the fitting coefficients are all high, which can well describe the substrate consumption situation in the upper, middle and lower layers in the early stage; the substrate consumption rate is directly related to the growth of bacteria, belonging to the typical growth "coupled" type. The OD values of the dominant bacteria growth in the upper, middle and lower layers use the Dose Resp model to establish a fitting kinetic equation and calculate the fitting coefficient. The upper layer R 2are 0.98837 and 0.9821, for the middle layer R 2 are 0 / 9858 and 0.9722, for the lower layer R 2 are 0.9947 and 0.9874, and the fitting coefficients are all relatively high, which can well describe the growth status of the bacteria; The SGompertz model is used to perform nonlinear fitting on the enzyme production in the upper, middle, and lower layers during the fermentation process. For the upper layer R 2 are 0.99327 and 0.99736, for the middle layer R 2 are 0.9899 and 0.9966, for the lower layer R 2 are 0.9889 and 0.9978, and the fitting coefficients are all relatively high, which can well describe the enzyme production status.

[0093] In the middle stage of the fermentation stage, the use of each model, its fitting kinetic equation, and fitting coefficient for the upper, middle, and lower layers are shown in Tables 8, 9, and 10 respectively.

[0094] Table 8 Models used in the upper layer during the middle stage of the fermentation stage, their fitting kinetic equations, and fitting coefficients

[0095]

[0096]

[0097] Table 9 Models used in the middle layer during the middle stage of the fermentation stage, their fitting kinetic equations, and fitting coefficients

[0098]

[0099] Table 10 Models used in the lower layer during the middle stage of the fermentation stage, their fitting kinetic equations, and fitting coefficients

[0100]

[0101]

[0102] In the later stage of high-temperature Daqu fermentation, the temperature begins to decline. A large number of heat-intolerant microorganisms go dormant or die, and the remaining main bacteria are heat-resistant Bacillus. The upper layer (layers 1-3) mainly consumes the carbon and nitrogen sources in the substrate to promote the growth of Bacillus, producing protease, amylase, and cellulase; the middle layer (layers 4-6) mainly consumes the carbon and nitrogen sources in the substrate to promote the growth of Bacillus, producing protease, amylase, and cellulase; the lower layer (layers 7-9) mainly consumes the carbon and nitrogen sources in the substrate to promote the growth of Corynebacterium kutscheri, producing protease, lipase, and cellulase. Judging from the parameter result data, the growth of bacteria, substrate consumption, and product formation are interconnected and interact with each other, being in a linkage state. The substrate consumption kinetic model uses the Boltzmann model to establish a fitting equation for the substrate consumption (starch and fat) and calculate the fitting coefficient. The fitting results show that for the upper layer, R 2 is 0.9931 and 0.9524, for the middle layer, R 2 is 0.9678 and 0.9822, and for the lower layer, R 2 is 0.9731 and 0.9798. The fitting coefficients are all relatively high, and can well describe the substrate consumption situation in the upper, middle, and lower layers in the early stage; the substrate consumption rate has a direct relationship with the bacterial growth, belonging to the typical growth "coupled" type. The OD values of the dominant bacteria growth in the upper, middle, and lower layers are used to establish a fitting kinetic equation and calculate the fitting coefficient using the DoseResp model. For the upper layer, R 2 is 0.9937, for the middle layer, R 2 is 0.9885, and for the lower layer, R 2 is 0.9897. The fitting coefficients are all relatively high, and can well describe the growth situation of the bacteria; the SGompertz model is used to perform non-linear fitting on the enzyme production in the upper, middle, and lower layers during the fermentation process. For the upper layer, R 2 is 0.9962, 0.9899, and 0.9857, for the middle layer, R 2 is 0.9897, 0.9968, and 0.9963, and for the lower layer, R 2 is 0.98897, 0.98975, and 0.99745. The fitting coefficients are all relatively high, and can well describe the enzyme production situation.

[0103] In the later stage of the fermentation stage, the models, their fitting kinetic equations, and fitting coefficients used in the upper, middle, and lower layers are respectively shown in Tables 11, 12, and 13.

[0104] Table 11 Models, their fitting kinetic equations, and fitting coefficients used in the upper layer in the later stage of the fermentation stage

[0105]

[0106] Table 12 Models, their fitting kinetic equations, and fitting coefficients used in the middle layer in the later stage of the fermentation stage

[0107]

[0108]

[0109] Table 13 Models Used in the Lower Layer in the Later Fermentation Stage and Their Fitted Kinetic Equations and Fitted Coefficients

[0110]

[0111] S51: Re-evaluate the quality of the Qu Kuai fermentation by whether the Qu Kuai fermentation process conforms to the substrate consumption model, the microbial growth model, and the metabolic enzyme generation model.

[0112] In this embodiment, by specifically using the combination of the quality of the Qu Pei raw materials and the forming evaluation system, the quality evaluation system of the Qu Kuai fermentation process, and the fermentation kinetic model composed of the substrate consumption model, the microbial growth model, and the metabolic enzyme generation model, a method for evaluating the quality of high-temperature Daqu fermentation in each stage is generated. The specific parameters in the raw material pretreatment, Qu Pei forming, and Qu Fang fermentation are combined with the fermentation kinetic model to better describe the changes and interrelationships of substrate consumption, microbial growth, and product generation during the fermentation process. Substitute into the formula to select the preferred core parameters for making high-quality high-temperature Daqu, and then based on the real-time parameter information of the fermentation process obtained from the control model, and based on the models of each link, obtain the corresponding parameter optimization results of each link, and then adjust the production process control parameters corresponding to each link according to the parameter optimization results to achieve the expected optimization goal. Thus, a method for evaluating the quality of high-temperature Daqu fermentation in each stage that is standardized and digitalized is obtained.

[0113] Embodiment III

[0114] Based on the method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters described in Embodiment I, this embodiment further provides a system for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters, including:

[0115] A module for constructing the quality evaluation system of Qu Pei raw materials and forming, which is used to construct the quality evaluation system of Qu Pei raw materials and forming during the Qu Pei preparation stage to evaluate the quality of Qu Pei raw materials, including: the core parameters of the quality of the first-level wheat raw materials, the control parameters of the second-level pretreatment process, and the physical characteristics parameters of the third-level formed Qu Pei;

[0116] A module for constructing the quality evaluation system of the Qu Kuai fermentation process, which is used to construct the quality evaluation system of the Qu Kuai fermentation process during the Qu Kuai fermentation stage to preliminarily evaluate the quality of Qu Kuai fermentation, including: the first-level environmental parameters, the second-level physical and chemical parameters, and the third-level flavor substance parameters;

[0117] A model construction module is used to divide the fermentation stage of the koji blocks into the early stage, the middle stage, and the late stage in terms of time according to the temperature of the koji blocks; divide the koji blocks in the fermentation stage of the koji blocks into the upper layer, the middle layer, and the lower layer in terms of space according to the growth of the strains, the consumption of the substrates, and the generated products; construct a substrate consumption model, a microorganism growth model, and a metabolic enzyme generation model for each koji layer in each fermentation stage of the koji blocks.

[0118] An evaluation module is used to re-evaluate the fermentation quality of the koji blocks based on whether the fermentation process of the koji blocks conforms to the substrate consumption model, the microorganism growth model, and the metabolic enzyme generation model.

[0119] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters are implemented.

[0120] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0121] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0122] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process or multiple processes and / or blocks Figure 1 one or more processes and / or blocks Figure 1 steps of a block or multiple blocks.

[0124] Obviously, the above embodiments are only examples for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation manners here. And the obvious changes or modifications derived therefrom still fall within the protection scope of the present invention.

Claims

1. A method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters, characterized in that, Including: In the koji embryo preparation stage, a quality and forming evaluation system for koji embryo raw materials is constructed to evaluate the quality of koji embryo raw materials, including: core parameters of the quality of first-grade wheat raw materials, control parameters of second-grade pretreatment processes, and physical property parameters of third-grade formed koji embryos; In the koji block fermentation stage, a quality evaluation system for the koji block fermentation process is constructed to preliminarily evaluate the fermentation quality of koji blocks, including: first-grade environmental parameters, second-grade physical and chemical parameters, and third-grade flavor substance parameters; According to the koji block temperature, the koji block fermentation stage is divided into the early stage, the middle stage, and the late stage in terms of time; according to the growth of strains, substrate consumption, and generated products, the koji blocks in the koji block fermentation stage are divided into the upper layer, the middle layer, and the lower layer in terms of space; a substrate consumption model, a microorganism growth model, and a metabolic enzyme generation model are respectively constructed for each koji layer in each fermentation stage of the koji block; The fermentation quality of the koji block is re-evaluated based on whether the koji block fermentation process conforms to the substrate consumption model, the microorganism growth model, and the metabolic enzyme generation model.

2. The method for evaluating the quality of multi-level parameter high-temperature Daqu fermentation according to claim 1 is characterized in that, In the quality and forming evaluation system for koji embryo raw materials, the core parameters of the quality of first-grade wheat raw materials include the fat content, starch content, and bulk density of wheat; the control parameters of the second-grade pretreatment process include the degree of pulverization, moisture content of tempering wheat, inoculation ratio, and koji pressing strength; the physical property parameters of the third-grade formed koji embryo include koji block hardness, plasticity, porosity, and cohesion.

3. A method for evaluating the quality of multi-stage parameter high-temperature Daqu fermentation according to claim 1, characterized in that, In the quality evaluation system for the koji block fermentation process, the first-grade environmental parameters include the initial fermentation environment temperature and humidity of each koji layer, the koji block temperature and humidity, and the proportion of air components in the fermentation environment; the second-grade physical and chemical parameters include the abundance of microorganisms, microorganism metabolic function indicators, and substrate consumption indicators; the third-grade flavor substance parameters include tetramethylpyrazine and 3-methylthiopropanol.

4. A method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters according to claim 3, characterized in that, Among the second-grade physical and chemical parameters, the abundance of the microorganisms includes the change amount of the relative proportion of molds, bacteria, and yeasts; the microorganism metabolic function indicators include saccharifying power, liquefying power, and fermenting power; the substrate consumption indicators include the degradation rates of raw material crude starch, crude protein, fat, and cellulose.

5. The quality evaluation method for high-temperature Daqu fermentation with multi-level parameters according to claim 1, characterized in that The early stage of the koji block fermentation stage is the temperature rising stage; In the upper layer of the koji block in the early stage, the substrate with the largest consumption proportion is the carbon source, the growing strains are Bacillus and Thermus, and the generated products are protease and amylase; In the middle layer of the koji block in the early stage, the substrate with the largest consumption proportion is the carbon source, the growing strains are Multispora and Thermus, and the generated products are protease and amylase; In the lower layer of the koji block in the early stage, the substrate with the largest consumption proportion is the carbon source, the growing strains are Weissella and Saccharomycopsis, and the generated products are protease and amylase.

6. The quality evaluation method for high-temperature Daqu fermentation with multi-level parameters according to claim 1, characterized in that, The middle stage of the koji block fermentation stage is the temperature dropping stage; In the upper layer of the koji block in the middle stage, the substrates with the largest consumption proportions are the carbon source and the nitrogen source, the growing strains are Bacillus and Thermus, and the generated products are protease and amylase; In the middle layer of the koji block in the middle stage, the substrates with the largest consumption proportions are the carbon source and the nitrogen source, the growing strains are Corynebacterium kutscheri and Thermus, and the generated products are protease and amylase; In the lower layer of the koji block in the middle stage, the substrates with the largest consumption proportions are the carbon source and the nitrogen source, the growing strains are Bacillus and Thermus, and the generated products are protease and lipase.

7. A method for evaluating the quality of high-temperature Daqu fermentation with multi-level parameters according to claim 1, characterized in that, The late stage of the koji block fermentation stage is the temperature dropping stage; In the upper layer of the koji blocks in the later stage, the substrates with the largest consumption proportions are carbon sources and nitrogen sources. The growing strains are Bacillus, and the products generated are protease, amylase, and cellulase. In the middle layer of the koji blocks in the later stage, the substrates with the largest consumption proportions are carbon sources and nitrogen sources. The growing strains are Bacillus, and the products generated are protease, amylase, and cellulase. In the lower layer of the koji blocks in the later stage, the substrates with the largest consumption proportions are carbon sources and nitrogen sources. The growing strains are Corynebacterium kribbense, and the products generated are protease, lipase, and cellulase.

8. The quality evaluation method for high-temperature Daqu fermentation with multi-level parameters according to claim 1, characterized in that The substrate consumption model adopts the Boltzmann model, the microbial growth model adopts the Dose Resp model, and the metabolic enzyme generation model adopts the SGompertz model.

9. A multi-level parameter high-temperature Daqu fermentation quality evaluation system, characterized in that, Including: A module for constructing an evaluation system for the quality and molding of koji embryo raw materials, which is used to construct an evaluation system for the quality and molding of koji embryo raw materials during the koji embryo preparation stage to evaluate the quality of koji embryo raw materials, including: core parameters of the quality of first-class wheat raw materials, control parameters of second-class pretreatment processes, and physical property parameters of third-class formed koji embryos. A module for constructing an evaluation system for the quality during the koji block fermentation process, which is used to construct an evaluation system for the quality during the koji block fermentation stage to preliminarily evaluate the fermentation quality of koji blocks, including: first-class environmental parameters, second-class physical and chemical parameters, and third-class flavor substance parameters. A model construction module, which is used to divide the koji block fermentation stage into the early stage, the middle stage, and the later stage in terms of time according to the koji block temperature; divide the koji blocks in the koji block fermentation stage into the upper layer, the middle layer, and the lower layer in terms of space according to the growth of strains, substrate consumption, and generated products; and construct a substrate consumption model, a microbial growth model, and a metabolic enzyme generation model for each koji layer in each fermentation stage of the koji block. An evaluation module, which is used to re-evaluate the fermentation quality of koji blocks based on whether the koji block fermentation process conforms to the substrate consumption model, the microbial growth model, and the metabolic enzyme generation model.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the method for evaluating the fermentation quality of high-temperature daqu with multi-level parameters as described in any one of claims 1 to 8.

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