Method and system for enhancing water-retaining property of koji block in intelligent koji making process

Abstract

The invention relates to a method and system for enhancing the water-retaining property of a yeast block in an intelligent yeast making process, and the method comprises the following steps: S1, collecting the ambient temperature of a yeast room, the temperature of the yeast block and the water content data of the yeast block in a yeast fermentation process; s2, performing data processing and correlation analysis on the acquired data of the environment temperature of the koji room, the temperature of the koji blocks and the water content of the koji blocks; s3, according to the data after data processing and correlation analysis, establishing a relation model between the water content of the koji blocks and the environment temperature of the koji room or between the water content of the koji blocks and the temperature of the koji blocks; and S4, controlling the yeast fermentation process according to the relation model so as to enhance the water-retaining property of yeast blocks. According to the method, reasonable and effective temperature and humidity control can be carried out on the yeast fermentation process through the constructed relation model, and the yeast fermentation quality is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent koji-making, and particularly to a method and system for enhancing the water retention of koji blocks during the intelligent koji-making process. Background Art

[0002] The brewing process of Chinese liquor is essentially a growth and metabolism process of brewing microorganisms. Its microbial sources are rich, and the microorganisms carried by koji, fermented grains, pit mud, etc. may all participate in the production of unique flavor base liquor. And during the fermentation process of Chinese liquor, the microorganisms mainly come from koji, which has the reputation of "koji is the bone of liquor". Daqu is the saccharifying agent and fermenting agent in the production process of Daqu liquor, and it is a mixed preparation containing various microorganisms and enzyme systems.

[0003] High-temperature Daqu is the fermenting agent for Maotai-flavor Chinese liquor. Compared with medium- and low-temperature koji, the top temperature of Maotai-flavor high-temperature Daqu can reach 55°C. Only with more water and high humidity can the continuous, stable high temperature during koji-making and the normal progress of biochemical reactions be ensured. In high-temperature koji-making, in addition to meeting the physiological needs of microorganisms, forming koji blocks, and maintaining the air humidity in the koji room, water is importantly used to maintain the high temperature of high-temperature koji. Therefore, the water content for making high-temperature Daqu is about 3% more than that for medium-temperature Daqu (the water content for making medium-temperature koji is 37%, and that for high-temperature koji is 40%). And the water content of the finished high-temperature Daqu is usually about 3% higher than that of the medium-temperature Daqu (the water content of the finished medium-temperature Daqu is less than 13%, and that of the finished high-temperature Daqu is less than 15%). So during the fermentation process of Daqu, temperature and humidity are two important factors affecting the quality of Daqu. If the temperature is too high, the microorganisms will die or their activities will slow down, resulting in the stop of fermentation and affecting the quality; if the temperature is too low, the fermentation speed will become slow and the product quality will deviate; in the initial stage of cultivation, it is required that the humidity in the koji room is high, which is beneficial to the growth of microorganisms. If the humidity is too small, the water on the surface of the koji blank will evaporate quickly, and thick-skinned koji is likely to appear, affecting the quality of Daqu. In the later stage of cultivation, it is required that the humidity in the koji room is relatively small, which is beneficial to the volatilization of water in the koji blank and the drying of koji. If the humidity is too high, it is easy to cause mildew.

[0004] Most traditional koji-making is to control the fermentation of Daqu by manual labor combined with their own koji-making experience. The temperature and humidity in the koji room are mainly regulated by traditional methods such as manually adjusting doors and windows, covering with straw fences, and sprinkling water. This regulation method depends on experience, does not have a unified standard, and is restricted by manual technology and environmental factors. It is very difficult for workers to accurately control the temperature and humidity in the koji room to ensure that the water content of the koji blocks remains appropriate during the three stages of Daqu fermentation (slow start, stable middle, and slow end), thus it is difficult to ensure the quality of the finished Daqu. Although intelligent koji room fermentation can solve some problems, the research on the influence between the environmental temperature and humidity in the koji room and the temperature and humidity of the koji blocks, and how to accurately control the environmental temperature and humidity in the koji room to ensure the water content of the koji blocks is not deep enough and needs to be further studied. Summary of the Invention

[0005] To this end, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the research on the fermentation of Daqu by an intelligent koji-making room is not deep enough, and the environmental temperature and humidity of the koji-making room cannot be accurately controlled to ensure the water content of the koji blocks.

[0006] To solve the above technical problems, the present invention provides a method for enhancing the water retention of koji blocks during the intelligent koji-making process, including:

[0007] Step S1: During the fermentation process of Daqu, collect data on the environmental temperature of the koji-making room, the temperature of the koji blocks, and the water content of the koji blocks;

[0008] Step S2: Perform data processing and correlation analysis on the collected data of the environmental temperature of the koji-making room, the temperature of the koji blocks, and the water content of the koji blocks;

[0009] Step S3: Establish a relationship model between the water content of the koji blocks and the environmental temperature of the koji-making room, or between the water content of the koji blocks and the temperature of the koji blocks according to the data after data processing and correlation analysis;

[0010] Step S4: Control the fermentation process of Daqu according to the relationship model to enhance the water retention of the koji blocks.

[0011] In an embodiment of the present invention, in Step S1, the temperature of the koji blocks is measured by an infrared radiometer, and the sensor is calibrated using a modified form of the Stefan-Boltzmann equation, and then the target temperature is calculated. The formula is:

[0012] T T =(T D +mS D +b) 1 / 4 -273.15

[0013] In the formula, T T is the target temperature (k), T D is the detector temperature (k), S D is the millivolt signal emitted by the detector, m is the slope, b is the intercept, and -273.15 is the Kelvin temperature of zero degrees Celsius.

[0014] In an embodiment of the present invention, the formula for calculating the water content of the koji blocks in Step S1 is:

[0015] W=(m0 - m1) / m0

[0016] In the formula, W is the water content of the koji blocks, m0 is the mass of the sample before drying, and m1 is the constant weight of the sample after drying.

[0017] In one embodiment of the present invention, the method for processing the data of the temperature of the koji-making room environment, the temperature of the koji blocks, and the moisture content of the koji blocks collected in step S2 includes: after summing the data in the sampling sequence through the mean filtering algorithm, taking the average value as the result, and the formula is:

[0018]

[0019] In the formula, h d-j represents the temperature of the koji-making room environment or the temperature of the koji blocks or the moisture content of the koji blocks at the j-th point on the d-th day, j = 0, 1, 2,....., 23; n + 1 is the number of times of interval measurement within each hour, and T i is all the values of the temperature of the koji-making room environment or the temperature of the koji blocks or the moisture content of the koji blocks measured on the d-th day, aj represents the temperature of the koji-making room environment or the temperature of the koji blocks or the moisture content of the koji blocks at the j-th point of the daily change of the koji blocks, and m is the number of observation days.

[0020] In one embodiment of the present invention, the method for performing correlation analysis on the data of the temperature of the koji-making room environment, the temperature of the koji blocks, and the moisture content of the koji blocks collected in step S2 includes: constructing a correlation coefficient r, the output range of r is from -1 to +1, 0 represents no correlation, a negative value is negative correlation, and a positive value is positive correlation, and retaining the values in the correlation coefficient R within the ranges of [-0.5, 1] and [0.5, 1];

[0021] The formula for the correlation coefficient r is:

[0022]

[0023] where y represents the dependent variable, representing the moisture content of the koji blocks; x represents the independent variable, representing the temperature of the koji blocks or the temperature of the koji-making room environment, and n represents the number of observations of each independent variable.

[0024] In one embodiment of the present invention, the relationship model between the moisture content of the koji blocks and the temperature of the koji-making room environment, or the relationship model between the moisture content of the koji blocks and the temperature of the koji blocks in step S3 includes: the relationship model between the moisture content of the koji blocks and the temperature of the koji-making room environment, or the relationship model between the moisture content of the koji blocks and the temperature of the koji blocks in the middle and early stages of daqu fermentation, and the formula is:

[0025]

[0026] where W1 represents the moisture content of the koji blocks in the middle and early stages of daqu fermentation, T is the temperature of the koji blocks or the temperature of the koji-making room environment, and a1, b1, c1, d1 are the fitting parameters in the middle and early stages of daqu fermentation, and the middle and early stages of daqu fermentation include the early slow stage and the middle steady stage.

[0027] In one embodiment of the present invention, the relationship model between the moisture content of the koji block and the temperature of the koji room environment, or between the moisture content of the koji block and the temperature of the koji block in step S3 includes: the relationship model between the moisture content of the koji block in the slow fermentation period after the large-scale koji fermentation and the temperature of the koji room environment, or between the moisture content of the koji block and the temperature of the koji block. The formula is:

[0028]

[0029] Among them, W2 represents the moisture content of the koji block in the slow fermentation period after the koji fermentation, T is the temperature of the koji block or the temperature of the koji room environment, and a2, b2, c2, and d2 are the fitting parameters in the slow fermentation period after the large-scale koji fermentation.

[0030] To solve the above technical problems, the present invention provides a system for enhancing the water retention of koji blocks in the intelligent koji-making process, including:

[0031] A collection module: used to collect data on the temperature of the koji room environment, the temperature of the koji block, and the moisture content of the koji block during the large-scale koji fermentation process;

[0032] A data processing module: used to perform data processing and correlation analysis on the collected data of the temperature of the koji room environment, the temperature of the koji block, and the moisture content of the koji block;

[0033] A construction module: used to establish a relationship model between the moisture content of the koji block and the temperature of the koji room environment, or between the moisture content of the koji block and the temperature of the koji block according to the data after data processing and correlation analysis;

[0034] A control module: used to control the large-scale koji fermentation process according to the relationship model to enhance the water retention of the koji block.

[0035] To solve the above technical problems, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the method for enhancing the water retention of koji blocks in the intelligent koji-making process as described above are implemented.

[0036] To solve the above technical problems, the present invention provides a computer-readable storage medium, on which a computer program is stored. The feature is that when the computer program is executed by a processor, the steps of the method for enhancing the water retention of koji blocks in the intelligent koji-making process as described above are implemented.

[0037] The above technical solutions of the present invention have the following advantages compared with the prior art:

[0038] The method for enhancing the water retention of koji blocks in the intelligent koji-making process according to the present invention, by constructing a relationship model between the moisture content of the koji block and the temperature of the koji room environment, or between the moisture content of the koji block and the temperature of the koji block, can more vividly illustrate the influence of temperature on the moisture content of the koji block through the relationship model, and then can control the large-scale koji fermentation process according to the relationship model, providing a certain reference standard for the water retention of the koji block;

[0039] The present invention analyzes the measured data of the temperature, temperature of the koji blocks, humidity, etc. in the koji-making room and the obtained relationship model to obtain the moisture content of the koji blocks, compares it with the moisture content (standard) of high-quality koji blocks, and finally adjusts the temperature and humidity in the koji-making room through the temperature and humidity control system to keep the moisture content of the koji blocks at an ideal value. It can also monitor the environment of the koji-making room and the quality of the koji blocks at any time through the intelligent terminal, and perform remote control and management;

[0040] Based on big data analysis technology, the present invention collects and processes a large amount of production data, optimizes and adjusts the parameters of the relationship model according to historical data and real-time feedback, improves the efficiency and quality of koji block processing, reduces resource waste and human errors; realizes the standardization, automation and intelligence of the solid-state brewing industry, establishes a new type of large koji fermentation equipment system, and enhances the technological content and competitive advantage of liquor enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] 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.

[0042] Figure 1 is the method flow chart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The following further describes the present invention in conjunction with the 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 embodiments cited do not limit the present invention.

[0044] Embodiment 1

[0045] Referring to Figure 1 as shown, the present invention relates to a method for enhancing the water retention of koji blocks in the intelligent koji-making process, including:

[0046] Step S1: During the large koji fermentation process, collect the data of the temperature in the koji-making room, the temperature of the koji blocks, and the moisture content of the koji blocks;

[0047] Step S2: Perform data processing and correlation analysis on the collected data of the temperature in the koji-making room, the temperature of the koji blocks, and the moisture content of the koji blocks;

[0048] Step S3: Establish a relationship model between the moisture content of the koji blocks and the temperature in the koji-making room, or between the moisture content of the koji blocks and the temperature of the koji blocks according to the data after data processing and correlation analysis;

[0049] Step S4: Control the large koji fermentation process according to the relationship model to enhance the water retention of the koji blocks.

[0050] In this embodiment, the Daqu fermentation includes three stages: the early slow stage, the middle steady stage, and the late slow stage. Among them, in the early slow stage: 2 - 5 days, in the middle steady stage: 6 - 14 days, and in the late slow stage: 15 - 35 days. In the early slow stage, the temperature of the Qu room environment and the Qu block slowly rises, and the water content of the Qu block slowly decreases; in the second stage, the middle steady stage, it is required that the temperature can be maintained, and the temperature of the Qu block and the Qu room environment should be kept at about 55 °C. In this stage, the water content of the Qu block also slowly decreases; the last stage is the late slow stage. In this stage, the temperature of the Qu room environment and the Qu block gradually decreases, and the water content of the Qu block continues to decrease. Finally, the water content of the finished Qu block is less than 15%. In order to better analyze the correlation between the temperature of the Qu room environment and the Qu block and the water content of the Qu block, in this embodiment, the first two stages are combined into the early and middle stages. Therefore, the entire Daqu fermentation process is summarized into two stages: the early and middle stages and the late slow stage.

[0051] Further, in step S1, the temperature of the Qu block is measured by an infrared radiometer. This infrared radiometer can measure the temperature of an object without directly contacting the object surface. The output of the detector follows the basic physical principle of the Stefan - Boltzmann law, and the sensor is calibrated using a modified form of the Stefan - Boltzmann equation, and then the target temperature is calculated. The formula is:

[0052] T T =(T D +mS D +b) 1 / 4 -273.15

[0053] In the formula, T T is the target temperature (k), T D is the detector temperature (k), S D is the millivolt signal emitted by the detector, m is the slope, b is the intercept, and -273.15 is the Kelvin temperature of zero degrees Celsius.

[0054] Further, the calculation formula for the water content of the Qu block in step S1 is:

[0055] W=(m0 - m1) / m0

[0056] In the formula, W is the water content of the Qu block, m0 is the mass of the sample before drying, and m1 is the constant weight of the sample after drying.

[0057] Further, in step S2, data processing is performed on the collected data of the Qu room environment temperature, Qu block temperature, and Qu block water content. The methods include: after summing the data in the sampling sequence through the mean filtering algorithm, then taking the average value as the result. The formula is:

[0058]

[0059] In the formula, h d-jRepresents the temperature of the koji-making room, the temperature of the koji block, or the moisture content of the koji block at time j on day d, where j = 0, 1, 2,....., 23; n + 1 is the number of times of interval measurement within each hour, aj represents the temperature of the koji-making room, the temperature of the koji block, or the moisture content of the koji block at time j of the daily change of the koji block, and m is the number of observation days.

[0060] Further, in step S2, correlation analysis is performed on the data of the temperature of the koji-making room, the temperature of the koji block, and the moisture content of the koji block collected. The most commonly used is Pearson correlation analysis. The method includes: calculating the covariance and standard deviation of the sample to obtain the Pearson correlation coefficient r. When r is less than 0, it is a negative correlation; when r is greater than 0, it is a positive correlation. Usually, during the large-scale koji fermentation, the first and middle stages show a negative correlation, and the last stage shows a positive correlation. In this embodiment, the values of the correlation coefficient r in the ranges [-0.5, 1] and [0.5, 1] are retained;

[0061] The formula for the correlation coefficient r is:

[0062]

[0063] Among them, y represents the dependent variable, representing the moisture content of the koji block; x represents the independent variable, representing the temperature of the koji block and the temperature of the koji-making room, and n represents the number of observations of each independent variable.

[0064] It should be noted that in this embodiment, correlation analysis is only required when building the model for the first time. After the subsequent relationship model is constructed, there is no need to perform correlation analysis on the data.

[0065] Further, in step S3, based on the data after data processing and correlation analysis, a relationship model between the moisture content of the koji block and the temperature of the koji-making room, or a relationship model between the moisture content of the koji block and the temperature of the koji block is established, including two models for the first and middle stages and the last and slow stages.

[0066] (1) The formula for the relationship model between the moisture content of the koji block and the temperature of the koji-making room, or the relationship model between the moisture content of the koji block and the temperature of the koji block during the first and middle stages of large-scale koji fermentation is:

[0067]

[0068] Among them, W1 represents the moisture content of the koji block during the first and middle stages of large-scale koji fermentation, T is the temperature of the koji block or the temperature of the koji-making room, and a1, b1, c1, d1 are the fitting parameters during the first and middle stages of large-scale koji fermentation, where the first and middle stages of large-scale koji fermentation include the first and slow stages and the middle and stable stages.

[0069] (2) The relationship model between the moisture content of the koji block and the temperature of the koji-making room, or the relationship model between the moisture content of the koji block and the temperature of the koji block during the last and slow stages of large-scale koji fermentation, the formula is:

[0070]

[0071] Among them, W2 represents the moisture content of the koji blocks during the slow fermentation period after koji fermentation, T represents the temperature of the koji blocks or the environmental temperature of the koji room, and a2, b2, c2, and d2 are the fitting parameters during the slow fermentation period after Daqu fermentation.

[0072] Step S4: Control the Daqu fermentation process according to the relationship model. Specifically, the monitoring system of the intelligent koji room monitors the temperature and humidity in real time, and then uploads them to the upper computer through the bus. The intelligent panel that adjusts the input temperature and humidity parameters controls the air blowing system, the automatic window opening and closing system, and the automatic koji turning system to adjust the temperature and humidity in the koji room, so as to keep the moisture content of the koji blocks in the koji room within the appropriate range at each stage and improve the water retention of the finished Daqu.

[0073] The following introduces the present invention in detail through specific structural cases:

[0074] Case 1

[0075] Establishment and model fitting of the temperature and moisture relationship during the early and middle stages of Daqu fermentation

[0076] The raw material for producing high-temperature sauce-flavored Daqu is wheat, and the auxiliary material is rice straw. Select organic wheat produced in the current year, and after a series of operations such as moistening wheat, grinding, adding water, adding mother koji, and mixing materials, it is manually formed into shape. After sweating, it is put into the warehouse for fermentation. Part of the fermentation microorganisms of high-temperature Daqu come from the mother koji, part come from the production site and the fermentation warehouse, and part come from the rice straw.

[0077] In this embodiment, data such as raw materials and koji cultivation are collected from distilleries in multiple regions. The method for detecting the temperature of the koji blanks: Select 3 fermentation warehouses, labeled as Fermentation Warehouse 1, 2, and 3 respectively. Start detecting the temperature of the koji blanks every day from the second day after the raw koji is put into the warehouse until the end of the warehouse exit. For each warehouse, take the middle position from the entrance to the window as the first detection point, take the position 1 / 4 away from the door as the second detection point, and take the position 1 / 4 away from the window as the third detection point. The detection depth is about 80 cm. The final temperature is the average value of the data at the 3 detection points. The detection time points are: from the second day after the raw koji is put into the warehouse to the 30th day. Among them, the second day to the fifth day is the slow fermentation period before Daqu fermentation, the sixth day to the fourteenth day is the middle and stable period of Daqu fermentation, so the second day to the fourteenth day is the early and middle stages, and the fifteenth day to the 30th day is the slow fermentation period after Daqu fermentation.

[0078] The method for sampling the temperature of the koji blocks during the Daqu fermentation process: Continuously track Fermentation Warehouses 1, 2, and 3 from the time of putting into the warehouse, and collect the temperature of the koji blocks in Fermentation Warehouses 1, 2, and 3 with an infrared radiometer according to the above detection time. The determination of the moisture content of the koji blocks: Continuously track Fermentation Warehouses 1, 2, and 3 from the time of putting into the warehouse, and conduct the determination according to the above detection time and the detection method of the moisture content of the koji blocks. Finally, the environmental temperature of the koji room, the temperature of the koji blocks, and the moisture content of the koji blocks are all processed according to the above data processing method. Table 1 shows the data of the early and middle stages of the Daqu fermentation stage.

[0079] The pre-middle stage of fermentation is the temperature rising stage. Since the low temperature and high humidity are especially suitable for the growth of microorganisms, in this stage, the microorganisms consume the carbon source in the substrate to promote the growth of molds and yeasts, produce protease and amylase, and release biological heat at the same time, resulting in a slow rise in the temperature of the koji blocks. Starting from the second day after entering the warehouse, the koji cultivation temperature can reach above 40°C, and it can reach 55°C on the seventh day after entering the warehouse. At this time, the temperature should be maintained, and the temperature of the daqu should be basically maintained above 55°C to ensure microbial metabolism and convert it into flavor substances. The air temperature in the fermentation warehouse is affected by the rising temperature of koji cultivation fermentation and starts to rise significantly from the second day after entering the warehouse, reaching 32 - 36°C. The moisture content of the raw koji is 36 - 38%. Under the dual action of microbial metabolism and physical volatilization, the moisture content of the koji blocks begins to slowly decrease. According to the Pearson correlation coefficient, in this stage, the moisture content of the koji blocks shows a negative correlation with the temperature of the koji room environment, with a correlation coefficient of -0.814; and it shows a negative correlation with the temperature of the koji blocks, with a correlation coefficient of -0.792, and the correlation is relatively strong.

[0080] Table 1 Data of the pre-middle stage of daqu fermentation

[0081]

[0082]

[0083] Table 2 shows the relationship model constructed for the pre-middle stage of the daqu fermentation stage in this embodiment. The specific fitting coefficients in the relationship model are shown in Table 2.

[0084] Table 2 Models, fitting equations and fitting coefficients used in the pre-middle stage of the fermentation stage

[0085]

[0086] Case Two

[0087] Establishment of the temperature-moisture relationship and model fitting in the post-slow stage of daqu fermentation

[0088] The post-slow stage of fermentation is the stage when the temperature begins to decline, also known as the stage of generating fragrance with the after-fire. The after-fire promotes the volatilization of a small amount of excess moisture in the core of the koji and the presentation of flavor substances. Secondary turning of the koji is carried out on the 14th or 15th day after entering the warehouse. After the secondary turning of the koji, the temperature of the koji blank will rise slowly again and then decline slowly, showing a fluctuating change in the later stage. When secondary turning of the koji is carried out, the temperature of the koji room environment also drops slightly and then rises slowly to 35 - 38°C and begins to decline slowly on the 23rd - 25th day. From secondary turning of the koji to discharging from the warehouse, the moisture content of the koji blank decreases relatively quickly and can reach 12% - 15% when discharging from the warehouse. Table 3 shows the data of the later stage of daqu fermentation. According to the Pearson correlation coefficient, in this stage, the moisture content of the koji blocks shows a positive correlation with the temperature of the koji room environment, with a correlation coefficient of 0.941; and it shows a positive correlation with the temperature of the koji blocks, with a correlation coefficient of 0.876, and the correlations are both relatively strong.

[0089] Table 3 Data during the slowdown period after Daqu fermentation

[0090]

[0091]

[0092] Table 4 shows the relational model constructed during the slowdown period after Daqu fermentation in this embodiment. For the specific fitting coefficients in the relational model, please refer to Table 4.

[0093] Table 4 Models, fitting equations and fitting coefficients used during the slowdown period after the fermentation stage

[0094]

[0095] The control strategy is as follows:

[0096] Based on the correlation and relational model between the temperature of the koji room environment and the moisture content of the koji blocks obtained from the above examples, during the early and middle stages of fermentation, the moisture content of the koji blocks is controlled at 25 - 36%, the temperature of the koji blocks is controlled at 30 - 55 °C, and the blower is used for humidification to keep the environmental humidity greater than 90%; during the slowdown period after fermentation, the moisture content of the koji blocks is controlled at 15 - 20%, the temperature of the koji blocks starts from not less than 45 °C and then gradually decreases, and the relative humidity is less than 80%.

[0097] Enter the temperature and moisture relational models of the two stages of the early and middle stages of fermentation and the slowdown period after fermentation into the input system for full-automatic monitoring and control. When the temperature range of the koji room environment and the koji blocks monitored by the sensor shows abnormalities (indicating abnormal moisture content of the koji blocks), the signal of the transmitter is converted and transmitted to the PLC. After receiving the collected data, the PLC uploads it to the upper computer through the PROFINET fieldbus, and controls the blower system, automatic window opening and closing system, and automatic koji turning system through the intelligent panel that adjusts the input temperature and humidity parameters to adjust the temperature and humidity of the koji room, so as to keep the moisture content of the koji blocks in the koji room within the appropriate range of each stage and improve the water retention of the finished Daqu.

[0098] The present invention is based on big data analysis technology, collects and processes a large amount of production data, and optimizes and adjusts parameters of the relational model according to historical data and real-time feedback, improves the efficiency and quality of koji block processing, and reduces resource waste and human errors.

[0099] The present invention can not only solve the problems that it is difficult to ensure the water content of koji blocks by controlling temperature during the fermentation process of Daqu, thus making it difficult to ensure the quality of koji blocks, but also provides a technical standard for the subsequent "intelligent and modern" brewing.

[0100] Embodiment 2

[0101] This embodiment provides a system for enhancing the water retention of koji blocks during the intelligent koji making process, including:

[0102] Collection module: used to collect data on the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks during the fermentation process of Daqu

[0103] Data processing module: used to perform data processing and correlation analysis on the collected data of the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks

[0104] Model building module: used to establish a relationship model between the moisture content of the koji blocks and the temperature of the koji room environment, or between the moisture content of the koji blocks and the temperature of the koji blocks based on the data after data processing and correlation analysis

[0105] Control module: used to control the fermentation process of Daqu according to the relationship model to enhance the water retention of the koji blocks

[0106] Example 3

[0107] This example provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method for enhancing the water retention of koji blocks in the intelligent koji making process described in Example 1.

[0108] Example 4

[0109] This example provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the method for enhancing the water retention of koji blocks in the intelligent koji making process described in Example 1.

[0110] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. 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. The solutions in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0111] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, as well as the combination of flows and / or blocks in the flowchart and / or block diagram. 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, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more blocks.

[0112] 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, such that the instructions stored in the computer-readable memory generate a manufacture including instruction means that implement the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 or one or more blocks.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 or one or more blocks.

[0114] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0115] 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 variations can be made based on the above description. It is not necessary and impossible to exhaustively list all implementation manners here. And the obvious changes or variations derived therefrom are still within the protection scope of the present invention.

Claims

1. A method for enhancing the water retention of koji blocks during the intelligent koji-making process, characterized in that: Including: Step S1: During the Daqu fermentation process, collect data on the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks. Step S2: Perform data processing and correlation analysis on the collected data of the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks. Step S3: Establish a relationship model between the moisture content of the koji blocks and the temperature of the koji room environment, or between the moisture content of the koji blocks and the temperature of the koji blocks, based on the data after data processing and correlation analysis. Step S4: Control the Daqu fermentation process according to the relationship model to enhance the water retention of the koji blocks.

2. The method for enhancing the water retention of koji blocks during the intelligent koji-making process according to claim 1, wherein: In step S1, the temperature of the koji blocks is measured by an infrared radiometer, and the sensor is calibrated using a modified form of the Stefan-Boltzmann equation to calculate the target temperature. The formula is: T T = (T D + mS D + b) 1 / 4 - 273.15 Where, T T is the target temperature (K), T D is the detector temperature (K), S D is the millivolt signal emitted by the detector, m is the slope, b is the intercept, and -273.15 is the Kelvin temperature of zero degrees Celsius.

3. The method for enhancing the water retention of the koji block during the intelligent koji making process according to claim 1, wherein: The formula for calculating the moisture content of the koji blocks in step S1 is: W = (m0 - m1) / m0 In the formula, W is the moisture content of the koji blocks, m0 is the mass before sample drying, and m1 is the constant weight after sample drying.

4. The method for enhancing the water retention of koji blocks during the intelligent koji-making process according to claim 1, wherein: In step S2, the method for performing data processing on the collected data of the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks includes: after summing the data in the sampling sequence through the mean filtering algorithm, taking the average value as the result. The formula is: Where h d-j represents the temperature of the koji-making room environment, the temperature of the koji block, or the moisture content of the koji block at the j-th point on the d-th day, where j = 0, 1, 2,....., 23; n + 1 is the number of times of interval measurement within each hour, and T i is all the values of the temperature of the koji-making room environment, the temperature of the koji block, or the moisture content of the koji block measured on the d-th day. aj represents the temperature of the koji-making room environment, the temperature of the koji block, or the moisture content of the koji block at the j-th point of the daily change of the koji block, and m is the number of observation days.

5. The method for enhancing the water retention of koji blocks during intelligent koji making according to claim 1, characterized in that: In step S2, for the correlation analysis of the collected data of the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks, the method includes: constructing a correlation coefficient r, the output range of r is from -1 to +1, 0 represents no correlation, negative values represent negative correlation, and positive values represent positive correlation, and retaining the values of the correlation coefficient R within the ranges of [-0.5, 1] and [0.5, 1]. The formula for the correlation coefficient r is: Where y represents the dependent variable, representing the moisture content of the koji blocks; x represents the independent variable, representing the temperature of the koji blocks or the temperature of the koji room environment, and n represents the number of observations of each independent variable.

6. The method for enhancing the water retention of koji blocks during the intelligent koji-making process according to claim 1, characterized in that: In step S3, the relationship model between the moisture content of the koji blocks and the temperature of the koji room environment, or between the moisture content of the koji blocks and the temperature of the koji blocks includes: the relationship model between the moisture content of the koji blocks and the temperature of the koji room environment, or between the moisture content of the koji blocks and the temperature of the koji blocks in the early and middle stages of Daqu fermentation. The formula is: Where W1 represents the moisture content of the koji blocks in the early and middle stages of Daqu fermentation, T is the temperature of the koji blocks or the temperature of the koji room environment, and a1, b1, c1, d1 are the fitting parameters in the early and middle stages of Daqu fermentation, where the early and middle stages of Daqu fermentation include the early slow stage and the middle steady stage.

7. The method for enhancing the water retention of koji blocks during the intelligent koji-making process according to claim 1, characterized in that: In step S3, the relationship model between the moisture content of the koji blocks and the temperature of the koji room environment, or between the moisture content of the koji blocks and the temperature of the koji blocks includes: the relationship model between the moisture content of the koji blocks and the temperature of the koji room environment, or between the moisture content of the koji blocks and the temperature of the koji blocks in the late slow stage of Daqu fermentation. The formula is: Where W2 represents the moisture content of the koji blocks in the late slow stage of fermentation, T is the temperature of the koji blocks or the temperature of the koji room environment, and a2, b2, c2, d2 are the fitting parameters in the late slow stage of Daqu fermentation.

8. A system for enhancing the water retention of koji blocks during the intelligent koji-making process, characterized in that: Including: Acquisition module: used to collect data on the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks during the Daqu fermentation process. Data processing module: used to perform data processing and correlation analysis on the collected data of the temperature of the koji room environment, the temperature of the koji blocks, and the moisture content of the koji blocks. Building module: used to establish a relationship model between the moisture content of the koji block and the temperature of the koji room environment, or between the moisture content of the koji block and the temperature of the koji block based on the data after data processing and correlation analysis; Control module: used to control the process of Daqu fermentation according to the relationship model to enhance the water retention of the koji block.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the method for enhancing the water retention of the koji block in the intelligent koji-making process according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for enhancing the water retention of the koji block in the intelligent koji-making process according to any one of claims 1 to 7.

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