A liquor lower sand round grain distiller's grains rapid diagnosis and stacking process parameter real-time adjustment method

Abstract

The application discloses a liquor lower sand cycle grain distiller's grains rapid diagnosis and stacking process parameter real-time adjustment method, and belongs to the liquor brewing technical field. The method comprises the following steps: S1, rapid detection: obtaining three state indexes of the grain distiller's grains to be stacked, including cooked grain texture index, initial wine gas production rate index and grain distiller's grains electrical property index; S2, real-time diagnosis: inputting the three state indexes measured in S1 into a preset diagnosis rule base to obtain corresponding grain distiller's grains state modes; the diagnosis rule base is constructed based on historical production data, and the historical production data contains grain distiller's grains detection indexes, corresponding stacking process parameters and final fermentation results; S3, adjustment execution: generating and executing a stacking process parameter adjustment instruction for the current batch of grain distiller's grains according to the grain distiller's grains state mode output in S2. The technical scheme can realize rapid diagnosis of lower sand grain distiller's grains and real-time adjustment of stacking parameters, solve the detection lag problem, get rid of experience dependence and stabilize fermentation quality.

Description

Technical Field

[0001] This application belongs to the field of baijiu brewing technology, specifically relating to a method for rapid diagnosis of grain mash in the next fermentation batch and real-time adjustment of stacking process parameters. Background Technology

[0002] The fermentation process of Maotai-flavor baijiu is a crucial step in the brewing process, directly determining the quality of the base liquor and the yield. Currently, the industry mainly controls the quality of the mash by testing biochemical indicators such as moisture, acidity, and reducing sugars. However, laboratory testing is time-consuming, and the results lag behind the fermentation process, making pre-emptive intervention impossible. Furthermore, traditional monitoring indicators are mostly static chemical components, which are difficult to directly translate into adjustment instructions for process parameters such as bulk density and height. Production relies heavily on manual experience, resulting in extensive and unstable control. In summary, existing technologies suffer from significant diagnostic lag and a disconnect between indicators and control, urgently requiring a technical solution that can quickly diagnose the state of the mash and provide real-time guidance for process adjustments. Summary of the Invention

[0003] This application provides a method for rapid diagnosis of grain mash in the first fermentation cycle of baijiu production and real-time adjustment of stacking process parameters. This method aims to solve the existing technical problems of delayed diagnosis of grain mash in the first fermentation process, time-consuming testing, disconnect between static biochemical indicators and stacking process control, reliance on experience, and poor stability. It provides a method for rapid diagnosis and real-time adjustment of stacking process parameters.

[0004] In a first aspect, embodiments of this application provide a method for rapid diagnosis of grain mash in the next fermentation cycle of baijiu production and real-time adjustment of stacking process parameters. This method is executed at the process node after the grain mash is mixed with yeast and before stacking fermentation. The method includes: S1. Rapid detection: Obtain three state indicators of the grain mash to be piled up, including cooked grain texture indicators, initial alcohol production rate indicators, and grain mash electrical characteristics indicators. S2. Real-time diagnosis: Input the three status indicators measured in S1 into a preset diagnostic rule base to obtain the corresponding grain mash status mode; the diagnostic rule base is constructed based on historical production data, which includes grain mash detection indicators, corresponding stacking process parameters and final fermentation results; S3. Adjustment Execution: Based on the grain mash status mode output by S2, generate and execute the stacking process parameter adjustment instructions for the current batch of grain mash.

[0005] Furthermore, the cooked grain texture index in S1 is obtained by detecting the elastic modulus or hardness value of the grain after cooking using a texture analyzer. The initial alcohol production rate index is obtained by detecting the rate of increase in ethanol gas concentration per unit time above the grain mash using a headspace gas sensor. The electrical properties of the grain mash are obtained by detecting the conductivity or impedance value of the grain mash at a specific frequency using an impedance analyzer.

[0006] Furthermore, the reference range for the cooked grain texture index is an elastic modulus between 150 kPa and 250 kPa; if the cooked grain texture index is less than 150 kPa, it is determined to be soft; if the cooked grain texture index is greater than 250 kPa, it is determined to be hard. The reference range for the initial alcohol production rate index is 0.5 ppm / min to 2.0 ppm / min; if the initial alcohol production rate index is less than 0.5 ppm / min, it is determined that the microbial activity is insufficient; if the initial alcohol production rate index is greater than 2.0 ppm / min, it is determined that the microbial activity is excessive. The reference range for the conductivity of the grain mash at a test frequency of 1kHz is 1.2mS / cm to 1.8mS / cm. If the conductivity of the grain mash is less than 1.2mS / cm, it is determined that the microenvironment is abnormally low. If the conductivity of the grain mash is greater than 1.8mS / cm, it is determined that the microenvironment is abnormally high.

[0007] Furthermore, the diagnostic rule base mentioned in step S2 includes at least one of the following diagnostic rules: If all three indicators are within the optimal range, the diagnosis is: moderate structure, good activity, and normal microenvironment. If the texture is relatively soft, the gas production rate is too high, and the electrical conductivity is too high, then it is diagnosed as having a soft skeleton, high activity, and a tendency to acidify. If the texture is too hard and the gas production rate is too low, it is diagnosed as having a compact structure and low activity. If only the conductivity deviates significantly, it is diagnosed as a significant deviation in the microenvironment.

[0008] Furthermore, the adjustment of the stacking process parameters in step S3 includes at least one of the following: If the skeleton is soft, highly active, and prone to acidification, then reduce the packing density and / or reduce the packing height; If the structure is compact and the activity is low, increase the packing density or increase the packing height and extend the packing time. If the microenvironment deviates significantly, adjust the stacking position to a stable area in the middle of the drying hall.

[0009] Furthermore, the entire process from step S1 to step S3 is controlled within 15-30 minutes.

[0010] Furthermore, the diagnostic rule base supports iterative updates based on subsequently added production data to optimize the accuracy of state pattern matching and the adaptability of adjustment instructions.

[0011] Secondly, embodiments of this application provide a device for rapid diagnosis of grain mash in the next fermentation cycle of baijiu (Chinese liquor) and real-time adjustment of stacking process parameters. The device is configured to be executed at a process node after the grain mash has been mixed with yeast and before stacking fermentation. The device includes: The detection module is used for rapid detection: obtaining three state indicators of the grain mash to be piled up, including the cooked grain texture indicator, the initial alcohol production gas rate indicator, and the grain mash electrical characteristics indicator. The diagnostic module is used for real-time diagnosis: the three status indicators measured by S1 are input into a preset diagnostic rule base to obtain the corresponding grain mash status mode; the diagnostic rule base is constructed based on historical production data, which includes grain mash detection indicators, corresponding stacking process parameters and final fermentation results; The adjustment module is used to adjust the execution: based on the grain mash status mode output by S2, it generates and executes the stacking process parameter adjustment instructions for the current batch of grain mash.

[0012] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0013] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0014] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0015] The technical solution provided in this application rapidly detects three indicators before the initial fermentation of the mash: the texture of the cooked grain, the initial rate of alcohol production, and the electrical properties of the mash. Combined with a pre-set diagnostic rule base, this allows for real-time determination of the mash's state, enabling precise and real-time adjustment of the fermentation process parameters. This method forms a closed loop between detection, diagnosis, and control, requiring only 15-30 minutes throughout the entire process. It effectively solves the problems of delayed traditional biochemical detection and the inability to intervene beforehand. Furthermore, this solution uses rapid detection of physical and physicochemical indicators, eliminating the need for complex chemical analysis. The results can be directly converted into executable commands such as stacking density, height, and position, freeing it from reliance on human experience. By specifically adjusting the fermentation process, the mash can be actively guided into the ideal fermentation path, significantly reducing the rate of abnormal fermentation batches, improving the stability of the initial fermentation process, and providing a reliable guarantee for the production of high-quality base liquor. Attached Figure Description

[0016] Figure 1This is a flowchart illustrating the method for rapid diagnosis and real-time adjustment of stacking process parameters of grain mash in the next fermentation round of baijiu production, as provided in Embodiment 1 of this application. Figure 2 This is a schematic diagram of the device for rapid diagnosis and real-time adjustment of the stacking process parameters of the grain mash in the second embodiment of this application for baijiu production; Figure 3 This is a schematic diagram of the structure of the electronic device provided in Embodiment 3 of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0018] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0019] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0020] The following, in conjunction with the accompanying drawings, provides a detailed explanation of the method for rapid diagnosis and real-time adjustment of the stacking process parameters of the grain mash in the next distillation round of baijiu production, through specific embodiments and application scenarios.

[0021] Example 1 Figure 1 This is a flowchart illustrating the method for rapid diagnosis and real-time adjustment of stacking process parameters of grain mash in the fermentation batch of baijiu, as provided in Embodiment 1 of this application. Figure 1 As shown, the specific steps include the following: S1. Rapid detection: Obtain three state indicators of the grain mash to be piled up, including cooked grain texture indicators, initial alcohol production rate indicators, and grain mash electrical characteristics indicators. "Pending fermentation of grain mash" refers to the solid material in the fermentation process of Maotai-flavor liquor, which has been steamed, cooled, and mixed with yeast, but has not yet been piled up for fermentation. For example, it can be sorghum-based fermented grain mash mixed with yeast, or it can be a mixed raw material grain mash that meets the fermentation standards.

[0022] The three state indicators can be three key parameters that comprehensively reflect the physical structure, microbial activity, and microenvironmental conditions of the grain mash. These include, for example, the texture of the cooked grain, the initial rate of alcohol production, the electrical properties of the grain mash, and other similar equivalent physical and physicochemical indicators.

[0023] Among them, the cooked grain texture index refers to the quantitative parameters that characterize the softness, elasticity, and degree of cooking of grains after steaming or cooking. Specifically, these can include elastic modulus, hardness value, etc.

[0024] The initial alcohol production rate index refers to the rate parameter of ethanol gas production by microorganisms in the initial stage of metabolism after the addition of yeast. Specifically, it can be the rate of increase in ethanol concentration or the initial metabolic activity rate, etc.

[0025] The electrical properties of grain mash refer to electrical parameters that comprehensively reflect the moisture content, ion concentration, and microenvironment of the grain mash. Examples include conductivity and impedance.

[0026] This solution allows for the direct collection of three status indicators of grain mash at the Xiasha workstation using dedicated rapid testing equipment, eliminating the need to send the mash to a laboratory and enabling real-time on-site data collection.

[0027] S2. Real-time diagnosis: Input the three status indicators measured in S1 into a preset diagnostic rule base to obtain the corresponding grain mash status mode; the diagnostic rule base is constructed based on historical production data, which includes grain mash detection indicators, corresponding stacking process parameters and final fermentation results; A pre-built diagnostic rule base refers to a set of structured rules that are constructed in advance and stored in the control system. For example, it can be built based on historical production data, which includes grain mash detection indicators, corresponding stacking process parameters, and final fermentation results. Specifically, it can be formed through machine learning cluster analysis or expert experience summaries.

[0028] The grain mash state model refers to the comprehensive state type of grain mash classified according to the combination characteristics of three indicators. For example, it can be an ideal model with moderate structure, good activity and normal microenvironment, or a risk model with a soft skeleton, excessive activity and tendency to acidification.

[0029] This solution can use the detection data to call the pre-set diagnostic rule library for matching calculations and automatically output the corresponding grain mash status mode, achieving real-time diagnosis without delay.

[0030] S3. Adjustment Execution: Based on the grain mash status mode output by S2, generate and execute the stacking process parameter adjustment instructions for the current batch of grain mash.

[0031] Stacking process parameter adjustment instructions refer to directly executable process operation instructions generated based on the state mode of grain mash. For example, they can be quantitative adjustment values ​​for stacking density and stacking height, or operation instructions for stacking location and stacking time.

[0032] This solution can automatically generate precise adjustment instructions based on the state of the grain mash. On-site operators can directly adjust the stacking process of the current batch of grain mash according to the instructions without relying on experience.

[0033] The technical solution provided in this embodiment establishes detection, diagnosis, and control mechanisms before the initial fermentation of the mash, precisely addressing the industry pain points of lagging traditional biochemical testing and the inability to promptly intervene in fermentation. This solution employs rapid detection of physical and physicochemical indicators, replacing time-consuming laboratory tests, and enabling real-time on-site data collection and diagnosis. Furthermore, this solution directly maps the state of the mash to adjustment instructions for the fermentation process parameters, eliminating reliance on manual experience and achieving refined and standardized control. This effectively guides the mash into the ideal fermentation path, reduces the rate of abnormal batches, stabilizes the quality of the initial fermentation process, and lays a solid foundation for the year-round production of high-quality base liquor for Maotai-flavor liquor.

[0034] In one embodiment, optionally, the cooked grain texture index in S1 is obtained by detecting the elastic modulus or hardness value of the grain after cooking using a texture analyzer. The initial alcohol production rate index is obtained by detecting the rate of increase in ethanol gas concentration per unit time above the grain mash using a headspace gas sensor. The electrical properties of the grain mash are obtained by detecting the conductivity or impedance value of the grain mash at a specific frequency using an impedance analyzer.

[0035] Texture analyzers are specialized testing equipment used to determine the mechanical properties of materials. For example, they can be food texture analyzers or material mechanical property testers, used to accurately quantify the softness, hardness, and elasticity of grains.

[0036] Elastic modulus is a mechanical parameter that measures a material's resistance to elastic deformation, measured in kPa. It directly reflects the degree of cooking and the structural strength of grains. Hardness value is an indicator of a material's resistance to indentation by external forces and can be used as an equivalent quantitative parameter for the texture of cooked grains.

[0037] A headspace gas sensor is a sensor used to detect the concentration of gas components at the top of a confined space. It can capture changes in the concentration of ethanol gas above grain mash in real time, characterizing the initial activity of microorganisms.

[0038] The rate of increase in ethanol gas concentration refers to the change in ethanol concentration above the grain mash per unit time, expressed in ppm / min. It directly reflects the strength of microbial metabolic activity in alcohol production after the addition of yeast.

[0039] An impedance analyzer is a precision instrument used to determine the electrical impedance characteristics of materials. It can measure the electrical parameters of grain mash at specific frequencies, reflecting the microenvironmental state.

[0040] A specific frequency refers to a fixed frequency value set during testing. It can be 1kHz or other test frequencies adapted to the electrical characteristics of the grain mash.

[0041] Electrical conductivity is an indicator of a material's ability to conduct electric current, measured in mS / cm. It comprehensively reflects the moisture content, ion concentration, and pH level of the grain mash.

[0042] Impedance value refers to the parameter that hinders the flow of electric current through a material, and can be used as an equivalent quantitative indicator of the electrical characteristics of grain mash.

[0043] In this solution, a texture analyzer, headspace gas sensor, and impedance analyzer can be used to conduct targeted tests on the grain mash according to standard operating procedures, read and record the corresponding parameter values, and quickly obtain three status indicators.

[0044] This technical solution clearly defines the dedicated testing equipment and quantitative parameters corresponding to the three status indicators, providing a standardized and feasible technical path for rapid testing. The selected equipment is adapted to the brewing environment, is easy to operate, and responds quickly, requiring no complex sample pretreatment, thus significantly improving testing efficiency. The quantitative parameters accurately correspond to the maturity of the mash, microbial activity, and microenvironmental state, ensuring high data reliability and avoiding the subjective bias of traditional sensory judgment. This solution can provide a stable and consistent data foundation for subsequent diagnosis, ensuring the accuracy and stability of the entire control process.

[0045] In one embodiment, optionally, the reference range for the cooked grain texture index is an elastic modulus between 150 kPa and 250 kPa; if the cooked grain texture index is less than 150 kPa, it is determined to be soft; if the cooked grain texture index is greater than 250 kPa, it is determined to be hard. The reference range for the initial alcohol production rate index is 0.5 ppm / min to 2.0 ppm / min; if the initial alcohol production rate index is less than 0.5 ppm / min, it is determined that the microbial activity is insufficient; if the initial alcohol production rate index is greater than 2.0 ppm / min, it is determined that the microbial activity is excessive. The reference range for the conductivity of the grain mash at a test frequency of 1kHz is 1.2mS / cm to 1.8mS / cm. If the conductivity of the grain mash is less than 1.2mS / cm, it is determined that the microenvironment is abnormally low. If the conductivity of the grain mash is greater than 1.8mS / cm, it is determined that the microenvironment is abnormally high.

[0046] Soft texture refers to cooked grains with an elastic modulus below the lower limit of the optimal range. Overcooked grains have weak skeletal support, are prone to sticking together, have poor air permeability, and are at risk of rancidity. Hard texture refers to cooked grains with an elastic modulus above the upper limit of the optimal range. Insufficiently cooked grains have a dense structure, making subsequent fermentation and enzymatic hydrolysis difficult and leading to slow fermentation.

[0047] Insufficient microbial activity refers to an initial rate of alcohol production below the lower limit of the optimal range. After adding yeast, microbial metabolism slows down, delaying fermentation initiation and affecting subsequent fermentation cycles and flavor development. Excessive microbial activity refers to an initial rate of alcohol production above the upper limit of the optimal range. Overly rapid microbial metabolism and concentrated heat production can easily cause localized overheating of the grain mash, increased acidity, and damage to the base liquor's style.

[0048] The 1kHz test frequency refers to the standard frequency set when testing the electrical conductivity of grain mash. It is suitable for the complex system of grain mash containing water and ions, ensuring the stability and comparability of electrical parameter testing.

[0049] An abnormally low microenvironment refers to a state where the conductivity is below the lower limit of the optimal range. Insufficient moisture and low ion concentration in the grain mash limit microbial growth and metabolism, resulting in weak fermentation activity. An abnormally high microenvironment refers to a state where the conductivity is above the upper limit of the optimal range. High moisture content in the grain mash easily leads to increased acidity, promoting abnormal microbial proliferation and posing a risk of rancidity and contamination by other microorganisms.

[0050] This solution can automatically output the results of grain mash texture, microbial activity, and microenvironment status by comparing the measured index values ​​with preset reference ranges. The judgment criteria are clear and free from subjective bias.

[0051] This technical solution establishes precise reference ranges and grading standards for three indicators, providing a clear basis for the quantitative diagnosis of grain mash status. The reference ranges are derived from historical high-quality production data, aligning with the characteristics of the fermentation process in Maotai-flavor liquor, and the judgment results are directly related to fermentation risk. The grading standards refine different abnormal states, accurately distinguishing between texture (soft or hard), activity level, and degree of microenvironment deviation, avoiding ambiguous judgments. This achieves standardized and quantitative assessment of grain mash status, providing a direct basis for subsequent precise matching and adjustment instructions, and improving the accuracy of diagnosis and control.

[0052] In one embodiment, optionally, the diagnostic rule base in step S2 includes at least one of the following diagnostic rules: if all three indicators are within the optimal range, the diagnosis is moderate structure-good activity-normal microenvironment. If the texture is relatively soft, the gas production rate is too high, and the electrical conductivity is too high, then it is diagnosed as having a soft skeleton, high activity, and a tendency to acidify. If the texture is too hard and the gas production rate is too low, it is diagnosed as having a compact structure and low activity. If only the conductivity deviates significantly, it is diagnosed as a significant deviation in the microenvironment.

[0053] Among them, "moderate structure, good activity, and normal microenvironment" refers to the ideal state in which all three indicators are within their optimal range. The physical framework of the grain mash is stable, the microbial activity is moderate, the microenvironment is suitable, the fermentation path is controllable, and the quality of the base liquor is stable.

[0054] A soft-structured, highly active, and acidification-prone state refers to a complex risk condition characterized by soft texture, excessively high gas production rate, and high electrical conductivity. Grain mash is prone to sticking together, has poor air permeability, exhibits excessive microbial metabolism, heats up quickly, and easily increases acidity, posing a risk of rancidity.

[0055] Compact structure and low activity refer to a low-activity state characterized by a hard texture and excessively low gas production rate. A compact grain mash structure and weak microbial activity result in slow fermentation initiation and insufficient enzymatic hydrolysis, easily leading to low alcohol yield and inadequate flavor.

[0056] Significant deviation from the microenvironment refers to a single abnormal state where only the electrical conductivity deviates significantly from the normal range. Abnormal moisture or ion concentration in grain mash directly affects microbial growth, easily leading to fermentation instability and flavor defects.

[0057] This solution can accurately output the comprehensive state pattern of grain mash by calling the combined judgment logic in the rule base, matching the measured values ​​of three indicators, and realizing multi-dimensional and high-precision state recognition.

[0058] This technical solution constructs multi-dimensional, combined diagnostic rules, covering both ideal and typical abnormal states, to accurately identify the overall state of grain mash. The rules are formulated based on the direct correlation between indicators and fermentation risk, closely aligning with the actual risk scenarios of the fermentation process, and the diagnostic results directly correspond to potential fermentation problems. It distinguishes between complex risks and single anomalies, avoiding misjudgments based on a single indicator and improving diagnostic reliability. The rules have clear logic and strong scalability, adaptable to different raw materials and different seasons in fermentation production, providing clear state-based criteria for precise control and effectively mitigating fermentation risks.

[0059] In one embodiment, optionally, the adjustment of the stacking process parameters in step S3 includes at least one of the following: If the skeleton is soft, highly active, and prone to acidification, then reduce the packing density and / or reduce the packing height; If the structure is compact and the activity is low, increase the packing density or increase the packing height and extend the packing time. If the microenvironment deviates significantly, adjust the stacking position to a stable area in the middle of the drying hall.

[0060] Bulk density refers to the weight of a unit volume of grain mash. It directly affects the air permeability and heat dissipation efficiency of the grain pile. If the density is too high, it will easily become stuffy and rancid, while if it is too low, it will easily dissipate heat too quickly and fermentation will be insufficient.

[0061] The stacking height refers to the vertical height of the grain pile, which affects the internal temperature distribution and heat preservation effect. If the height is too high, the temperature rises quickly and heat dissipation is difficult; if the height is too low, the heat preservation is poor and fermentation is slow.

[0062] The piling time refers to the duration of fermentation of grain mash. This affects the reproduction of microorganisms and the degree of enzymatic hydrolysis. Insufficient time results in incomplete fermentation, while excessive time can easily lead to increased acidity and deterioration of flavor.

[0063] The stacking location refers to the area where grain is placed in the drying hall. The central part of the drying hall has a stable environment with little fluctuation in temperature and humidity, while the edges are easily affected by the external environment and have poor stability.

[0064] The stable central area of ​​the drying hall refers to the area in the center of the drying hall, away from the edges. This area has uniform temperature and humidity, and moderate ventilation, which is conducive to stable fermentation of the grain mash and reduces external interference.

[0065] Specifically, based on the adjustment instructions output by the system, the stacking process parameters can be precisely adjusted by loosening or compacting the grain mash, adjusting the stack height, extending the stacking time, and moving the grain pile position.

[0066] This solution targets different grain mash states and matches corresponding stacking process parameter adjustment strategies to achieve precise control. The adjustment measures directly address the root causes of abnormal states, such as loose, highly active grain mash, compacted, low-activity grain mash, and grain mash with abnormal microenvironments, precisely resolving issues like adhesion, rapid temperature rise, and slow fermentation. The adjustment instructions are specific, directly executable, require no experience-based interpretation, and have a high degree of standardization. Through targeted adjustments, it proactively guides the grain mash back to the ideal fermentation path, significantly reducing the risks of spoilage, slow fermentation, and other abnormalities, stabilizing the quality of the initial fermentation, and ensuring the quality of the base liquor and the yield.

[0067] In one embodiment, optionally, the total execution time of steps S1 to S3 is controlled within 15-30 minutes.

[0068] This solution, from S1 rapid detection, through S2 real-time diagnosis, to S3 adjustment command generation, can be completed within a total time of 15-30 minutes. This short processing time allows for an optimal duration that adapts to the pace of fermentation at the site. It ensures both the accuracy of detection and diagnosis and intervenes before the grain mash microorganisms enter vigorous metabolism, preventing irreversible fermentation.

[0069] This technical solution takes 15-30 minutes for the entire process, precisely aligning with the critical intervention window before sand accumulation, fundamentally solving the pain points of traditional detection methods that are slow and miss adjustment opportunities. It effectively avoids the risk of irreversible subsequent fermentation, while enabling rapid intervention and precise control, maximizing the stability of the sand accumulation process.

[0070] In one embodiment, optionally, the diagnostic rule base supports iterative updates based on subsequently added production data to optimize state pattern matching accuracy and adjust instruction adaptability.

[0071] Iterative updates refer to the process of continuously optimizing the rule base based on new production data. Specifically, this can involve adding new rule entries, adjusting indicator thresholds, optimizing matching logic, and improving diagnostic accuracy.

[0072] The newly added production data refers to the data accumulated in subsequent batches of Xiasha production, including testing indicators, process parameters, and fermentation results. This can continuously enrich the sample size and cover more operating scenarios.

[0073] State pattern matching accuracy refers to the degree to which the diagnostic rule base accurately identifies the true state of the grain mash. The higher the accuracy, the stronger the consistency between the diagnostic results and the actual fermentation state, and the better the control effect.

[0074] Adjustment command adaptability refers to the degree to which adjustment commands match the abnormal state of the grain mash and the on-site working conditions. The stronger the adaptability, the more precise the adjustment measures, and the more significant the improvement in fermentation.

[0075] In this solution, newly added production data can be collected periodically, input into the system for machine learning or expert review, and the thresholds and logic of the diagnostic rule base can be updated to continuously improve diagnostic accuracy and instruction adaptability.

[0076] This technical solution enables continuous optimization. Based on iterative updates using actual production data, the rule base can continuously adapt to different raw material, seasonal, and equipment conditions during the fermentation process, covering more abnormal scenarios. It continuously optimizes matching accuracy, reduces diagnostic misjudgment rates, and improves control precision; it also optimizes command adaptability, making adjustment measures more aligned with actual on-site conditions and significantly improving fermentation results.

[0077] To enable those skilled in the art to better understand this solution, this application also provides a preferred embodiment.

[0078] To address the technical problems of existing technologies, such as severe lag in diagnosis and the use of single indicators that are disconnected from control, this invention provides a method for rapidly diagnosing the state of grain mash before the fermentation process in Maotai-flavor liquor production, and immediately making targeted real-time adjustments to the fermentation process. This method closes the loop of detection, diagnosis, and control, transforming "post-event inspection" into "pre-event prevention," thereby improving process stability.

[0079] A rapid diagnosis and real-time adjustment method for the fermentation process of Maotai-flavor liquor, implemented at the stage after the grain mash is mixed with yeast and before pile fermentation, includes the following steps: Rapid detection: Quickly obtain three physical and physicochemical state indicators of the grain mash before it is piled up. Cooked grain texture: Characterizes the softness and elasticity of grains after cooking. It can be measured using a texture analyzer to measure its elastic modulus or hardness value. Based on historical high-quality production data, a reference range for the elastic modulus can be set. For example, the optimal range is 150-250 kPa, <150 kPa is considered soft, and >250 kPa is considered hard.

[0080] Initial alcohol production rate: Characterizes the initial metabolic activity of microorganisms after the addition of koji (fermentation starter). It is measured by a headspace gas sensor at the rate of increase in ethanol gas concentration above the grain mash over a fixed time period. Example reference range: 0.5-2.0 ppm / min indicates normal activity, <0.5 ppm / min indicates insufficient activity, and >2.0 ppm / min indicates excessive activity.

[0081] Electrical properties of grain mash: This comprehensively reflects the microenvironmental state of the grain mash. It is measured using an impedance analyzer at a specific frequency, determining its conductivity or impedance value. For example, the reference range for conductivity at 1kHz is: 1.2-1.8 mS / cm is normal, <1.2 mS / cm is abnormally low, and >1.8 mS / cm is abnormally high.

[0082] Real-time diagnostics: The three measured indicators are input into a pre-set diagnostic model or rule base in real time. This model / rule base is constructed based on historical production data (including detection indicators, corresponding stacking processes, and final fermentation results) through machine learning cluster analysis or expert experience summarization. It can map the combined state of the three indicators into several typical grain mash "state patterns." The model / rule base contains explicit diagnostic rules, such as: Rule R1: If all three indicators are within the optimal range, the diagnosis is "moderate structure - good activity - normal microenvironment".

[0083] Rule R2: If the texture is too soft, the gas production rate is too high, and the electrical conductivity is too high, it is diagnosed as a state of "soft skeleton - high activity - acidification tendency", indicating the risk of adhesion and rancidity.

[0084] Rule R3: If the texture is too hard and the gas production rate is too low, it is diagnosed as a "compact structure - low activity" state, indicating a risk of slow fermentation start-up.

[0085] Rule R4: If only the conductivity deviates significantly from the normal range, it is diagnosed as a "significant deviation from the microenvironment" state.

[0086] Adjustment Decision and Execution: Based on the diagnosed "status pattern," immediately generate and execute adjustment instructions for the current batch of grain mash stacking process parameters. The adjustment of these stacking process parameters includes at least one or more of the following: If the diagnosis indicates that the grain mash is "too soft, has a high risk of sticking together, or is too active," then reduce the bulk density (e.g., loosen the grain pile) and / or reduce the bulk height to enhance heat dissipation and ventilation, and prevent excessive temperature rise and rancidity. If the diagnosis indicates that the grain mash is "too hard, has a dense structure, or lacks activity", then increase the bulk density or increase the bulk height, and extend the bulking time to facilitate heat preservation, moisture retention, and promote microbial reproduction and enzymatic hydrolysis. If the diagnosis indicates that the grain mash has an "abnormal microenvironment" (such as electrical properties that deviate significantly from normal values), then adjust its stacking location (such as moving it from the edge of the drying hall to a more stable area in the middle).

[0087] Compared with the prior art, the present invention has the following significant advantages: 1. High real-time performance, transforming "post-event inspection" into "pre-event control": Rapid detection and decision-making can be completed before accumulation (the entire process can be controlled within 15-30 minutes), allowing intervention during the critical window of fermentation initiation, fundamentally solving the industry pain points of traditional methods such as delayed diagnosis and inability to remedy the situation.

[0088] 2. Forming a closed loop of detection and control: It is the first to directly and quickly link the rapid detection signals before stacking with the stacking process operation, realizing refined and personalized control based on real-time status, replacing the traditional extensive mode of fixed operation based on experience.

[0089] 3. Intuitive indicators and fast response: The texture, gas production rate and electrical characteristics used are all physical or instrumental signals that can be obtained quickly, without the need for complicated and time-consuming chemical tests, making them suitable for on-site production applications.

[0090] 4. Effectively stabilizes process quality: By adjusting the stacking process in real time, grain mash in different states can be actively guided to the ideal fermentation path, significantly reducing abnormal fermentation batches, improving the success rate and stability of the fermentation process, and laying a solid foundation for the production of high-quality base liquor throughout the year.

[0091] The following section further describes this technical solution in a specific application scenario, where the method of this invention was applied during the 2025 summer production season of a certain Maotai-flavor liquor enterprise.

[0092] 1. Traditional process: After a batch of grain mash was mixed with yeast, it was directly piled up according to a fixed operation. About 24 hours later, the reducing sugar content was found to be abnormally low. However, the grain mash had already heated up by then, and it was impossible to adjust it effectively. As a result, the alcohol yield of this batch was low.

[0093] 2. Application of the technical solution of this invention: S1 Rapid Testing: Another batch of grain mash was rapidly tested after mixing with yeast and before stacking. The elastic modulus measured by the texture analyzer was 120 kPa (below the standard range); the initial alcohol production rate measured by the headspace gas sensor was 1.2 ppm / min (within the normal range); and the conductivity at 1 kHz measured by the impedance analyzer was 1.9 mS / cm (slightly above the upper limit of the normal range).

[0094] S2 Real-time Diagnosis: Input the data into the system's pre-set diagnostic rule base. Based on the rules (corresponding to the example of rule R2 in the supplementary content), the system determines that the batch of grain mash is in a state of "soft skeleton - high activity - acidification tendency", which poses a risk of weak physical skeleton support, poor adhesion and air permeability, and acidic microenvironment.

[0095] S3 Adjustment Decision and Execution: The system immediately generates the instruction: "Determined to be a loose, high-activity risk mode, execute the reduction of stacking density, reduce stacking height by 15%, and stack the grain mash in a better-ventilated area." The on-site operators immediately execute the instruction, changing the originally planned large stack of grain into a smaller, looser stack.

[0096] The batch of grain mash maintained a stable temperature during the subsequent stacking process, without any localized overheating or rancidity. After stacking was completed, tests showed that all biochemical indicators were within excellent ranges, indicating normal subsequent fermentation.

[0097] After applying the technical solution of this invention, the batch abnormality rate of the fermentation process in this work group decreased from approximately 8% to below 2%, and the process stability was significantly improved. The diagnostic model can be iteratively optimized based on subsequent continuous production data feedback.

[0098] Example 2 Figure 2 This is a schematic diagram of the device for rapid diagnosis and real-time adjustment of fermentation process parameters for baijiu (Chinese liquor) fermentation in Embodiment 2 of this application. The device is configured to execute at the process node after the grain mash is mixed with yeast and before fermentation in the fermentation pile, such as... Figure 2 As shown, the device includes: The detection module 201 is used for rapid detection: acquiring three state indicators of the grain mash to be piled up, including the cooked grain texture indicator, the initial alcohol production rate indicator, and the grain mash electrical characteristics indicator. The diagnostic module 202 is used for real-time diagnosis: it inputs the three status indicators measured by S1 into a preset diagnostic rule base to obtain the corresponding grain mash status mode; the diagnostic rule base is constructed based on historical production data, which includes grain mash detection indicators, corresponding stacking process parameters and final fermentation results; The adjustment module 203 is used to adjust the execution: based on the grain mash status mode output by S2, it generates and executes the stacking process parameter adjustment instructions for the current batch of grain mash.

[0099] The device for rapid diagnosis of grain mash and real-time adjustment of stacking process parameters in the baijiu fermentation process of this application embodiment can be a system, or a component, integrated circuit, or chip in a terminal. The system can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network-attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0100] The device for rapid diagnosis of grain mash and real-time adjustment of stacking process parameters in the baijiu fermentation process of this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit it.

[0101] The device for rapid diagnosis of grain mash in the next fermentation round and real-time adjustment of stacking process parameters for baijiu provided in this application embodiment can realize the various processes of the above embodiments. To avoid repetition, it will not be described again here.

[0102] Example 3 like Figure 3 As shown, this application embodiment also provides an electronic device 300, including a processor 301, a memory 302, and a program or instructions stored in the memory 302 and executable on the processor 301. When the program or instructions are executed by the processor 301, they implement the various processes of the above-mentioned method embodiment for rapid diagnosis of grain mash in the next fermentation round of baijiu and real-time adjustment of stacking process parameters, and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0103] It should be noted that the electronic devices in the embodiments of this application include mobile electronic devices and non-mobile electronic devices as described above.

[0104] Example 4 This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described method embodiment for rapid diagnosis and real-time adjustment of the stacking process parameters of the grain mash in the next distillation round of baijiu production, and achieve the same technical effect. To avoid repetition, these will not be described again here.

[0105] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0106] Example 5 This application also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described method embodiment for rapid diagnosis and real-time adjustment of the stacking process parameters of the grain mash in the next distillation round of baijiu production, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0107] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, device chip, chip system, or system-on-a-chip, etc.

[0108] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element. Furthermore, it should be noted that the scope of the methods and systems in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0109] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0110] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms fall within the scope of protection of this application.

[0111] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein. Various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments. Many other equivalent embodiments may be included without departing from the concept of this application, and the scope of this application is determined by the scope of the claims.

Claims

1. A method for rapid diagnosis of grain mash in the fermentation process of baijiu (Chinese liquor) and real-time adjustment of stacking process parameters, characterized in that, The method is performed at the process stage after the grain mash is mixed with koji and before it is piled up for fermentation. The method includes: S1. Rapid detection: Obtain three state indicators of the grain mash to be piled up, including cooked grain texture indicators, initial alcohol production rate indicators, and grain mash electrical characteristics indicators. S2. Real-time diagnosis: Input the three status indicators measured in S1 into a preset diagnostic rule base to obtain the corresponding grain mash status mode; the diagnostic rule base is constructed based on historical production data, which includes grain mash detection indicators, corresponding stacking process parameters and final fermentation results; S3. Adjustment Execution: Based on the grain mash status mode output by S2, generate and execute the stacking process parameter adjustment instructions for the current batch of grain mash.

2. The method according to claim 1, characterized in that, The cooked grain texture index mentioned in S1 is obtained by detecting the elastic modulus or hardness value of the grain after cooking using a texture analyzer. The initial alcohol production rate index is obtained by detecting the rate of increase in ethanol gas concentration per unit time above the grain mash using a headspace gas sensor. The electrical properties of the grain mash are obtained by detecting the conductivity or impedance value of the grain mash at a specific frequency using an impedance analyzer.

3. The method according to claim 2, characterized in that, The reference range for the cooked grain texture index is an elastic modulus between 150 kPa and 250 kPa; if the cooked grain texture index is less than 150 kPa, it is judged to be soft; if the cooked grain texture index is greater than 250 kPa, it is judged to be hard. The reference range for the initial alcohol production rate index is 0.5 ppm / min to 2.0 ppm / min; if the initial alcohol production rate index is less than 0.5 ppm / min, it is determined that the microbial activity is insufficient; if the initial alcohol production rate index is greater than 2.0 ppm / min, it is determined that the microbial activity is excessive. The reference range for the conductivity of the grain mash at a test frequency of 1kHz is 1.2mS / cm to 1.8mS / cm. If the conductivity of the grain mash is less than 1.2mS / cm, it is determined that the microenvironment is abnormally low. If the conductivity of the grain mash is greater than 1.8mS / cm, it is determined that the microenvironment is abnormally high.

4. The method according to claim 3, characterized in that, The diagnostic rule base mentioned in step S2 includes at least one of the following diagnostic rules: If all three indicators are within the optimal range, the diagnosis is: moderate structure, good activity, and normal microenvironment. If the texture is relatively soft, the gas production rate is too high, and the electrical conductivity is too high, then it is diagnosed as having a soft skeleton, high activity, and a tendency to acidify. If the texture is too hard and the gas production rate is too low, it is diagnosed as having a compact structure and low activity. If only the conductivity deviates significantly, it is diagnosed as a significant deviation in the microenvironment.

5. The method according to claim 1, characterized in that, The adjustment of the stacking process parameters in step S3 includes at least one of the following: If the skeleton is soft, highly active, and prone to acidification, then reduce the packing density and / or reduce the packing height; If the structure is compact and the activity is low, increase the packing density or increase the packing height and extend the packing time. If the microenvironment deviates significantly, adjust the stacking position to a stable area in the middle of the drying hall.

6. The method according to claim 1, characterized in that, The entire process from step S1 to step S3 should be completed within 15-30 minutes.

7. The method according to claim 1, characterized in that, The diagnostic rule base supports iterative updates based on newly added production data to optimize the accuracy of state pattern matching and the adaptability of adjustment instructions.

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