A method for quality control in the preparation of a ficus microcarpa probiotic product

Abstract

This invention relates to the field of fermentation engineering technology, specifically disclosing a quality control method in the preparation process of a *Ficus hirta* probiotic product, comprising: obtaining a lactic acid concentration time series; obtaining a lactic acid production rate series based on the lactic acid concentration time series; and determining the fermentation metabolic stage interval based on the positive and negative changes in the lactic acid production rate value; obtaining a colony formation unit time series; matching and segmenting the data within the colony formation unit time series according to the fermentation metabolic stage interval to form a colony formation unit subsequence; obtaining and analyzing the total stage fluctuation based on the data within the colony formation unit subsequence to determine the microbial community fluctuation interval; obtaining an anaerobic state parameter time series; obtaining an anaerobic deviation intensity series based on the anaerobic state parameter time series; segmenting the anaerobic deviation intensity series according to the fermentation metabolic stage interval and obtaining the total stage anaerobic deviation; and determining the anaerobic deviation interval based on the total stage anaerobic deviation.

Description

Technical Field

[0001] This invention relates to the field of fermentation engineering technology, specifically to a quality control method in the preparation process of a five-finger peach probiotic product. Background Technology

[0002] The existing preparation process of fermented products of *Ficus hirta* (a type of peach) usually relies on fixed fermentation time or a single lactic acid concentration index for quality judgment. This method can only reflect the local results of the fermentation process and is difficult to characterize the dynamic trend of lactic acid concentration changes over time. When there are differences in the composition of raw materials, initial bacterial count, or fermentation environment of different batches of *Ficus hirta*, even if the lactic acid accumulation level is similar, the metabolic stage of the bacterial community may be different. Existing technology is difficult to dynamically divide the fermentation metabolic stage based on the lactic acid production rate, which makes it difficult to accurately identify states such as enhanced acid production, continuous acid production, slowed acid production, acid production decline, or abnormal consumption. Subsequent quality judgment lacks a reliable time stage basis.

[0003] Meanwhile, existing methods are rather crude in judging the stability of viable cell counts. They usually evaluate the viable cell count status based on the colony formation unit value at a single time point, which is difficult to reflect whether there are continuous fluctuations or abnormal fluctuations in the viable cell count within the same fermentation and metabolic stage. If the changes in colony formation units are directly compared without distinguishing between fermentation and metabolic stages, normal changes between different stages are easily misjudged as abnormalities in the microbial community, and the latent instability reflected by short-term continuous fluctuations within the same stage may also be missed.

[0004] In addition, the stability of the reducing environment during anaerobic fermentation directly affects the acid production efficiency and viable bacteria stability of lactic acid bacteria. Existing monitoring methods usually do not perform time correlation analysis between the excess range and duration of redox potential values ​​and the lactic acid production process, making it difficult to identify hidden anomalies such as oxygen exposure, abnormal tank sealing, sampling disturbance, or destruction of anaerobic conditions in a timely manner.

[0005] Furthermore, existing technologies lack a comprehensive judgment mechanism that integrates fermentation metabolic stages, fluctuations in viable cell counts, and deviations in anaerobic states along a unified timeline. Abnormalities in a single indicator may be caused by detection errors, normal metabolic stage transitions, or short-term environmental disturbances. Directly adjusting based on these factors can easily lead to misjudgments and over-adjustment, making it difficult to establish clear and reliable abnormal quality control intervals and to provide accurate time windows and quantitative basis for anaerobic fermentation parameter regulation.

[0006] Therefore, the present invention provides a quality control method in the preparation process of Five-Finger Peach Probiotics products. Summary of the Invention

[0007] The purpose of this invention is to provide a quality control method in the preparation process of Five-Finger Peach Probiotics products to solve the aforementioned background problems.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] A quality control method for the preparation process of a *Ficus hirta* probiotic product includes:

[0010] During the fermentation of *Prunus pubescens* lactic acid bacteria fermented products in a fermenter, a lactic acid concentration time series was obtained. Based on the lactic acid concentration time series, a lactic acid production rate series was obtained, and the fermentation metabolic stage interval was determined according to the positive and negative changes in the lactic acid production rate value.

[0011] The time series of colony formation units was obtained, and the data within the time series of colony formation units were matched and segmented according to the fermentation and metabolic stage intervals to form colony formation unit subsequences. The total stage fluctuation was obtained and analyzed based on the data within the colony formation unit subsequences to determine the fluctuation range of the microbial community.

[0012] Obtain the time series of anaerobic state parameters, obtain the anaerobic deviation intensity series based on the anaerobic state parameter time series, segment the anaerobic deviation intensity series according to the fermentation metabolic stage interval and obtain the total anaerobic deviation of each stage, and determine the anaerobic deviation interval based on the total anaerobic deviation of each stage.

[0013] The fermentation metabolism phase interval, microbial community fluctuation interval, and anaerobic deviation interval are aligned on the time axis. The start and end times of the negative rate phase interval, microbial community fluctuation interval, and anaerobic deviation interval are compared to screen out the quality control abnormal intervals. Based on the recorded results of the quality control abnormal intervals, anaerobic fermentation parameter regulation signals are generated.

[0014] As a further technical solution of the present invention, the process of obtaining the lactic acid concentration time series is as follows:

[0015] Fermentation broth samples are obtained from the fermenter using an online sampling device according to a preset sampling cycle, and the corresponding sampling time points are recorded simultaneously.

[0016] The fermentation broth sample was centrifuged, filtered, and the supernatant was processed and then sent to the lactic acid detection module.

[0017] The lactate concentration value output by the lactate detection module is linked to the corresponding sampling time point, and then appended to the lactate concentration time series in chronological order of sampling time.

[0018] As a further technical solution of the present invention, the process of obtaining the lactate production rate sequence is as follows:

[0019] The lactic acid production rate was determined by extracting the difference between adjacent sampling time points in the lactic acid concentration time series and combining it with the time interval between adjacent sampling time points.

[0020] Each lactate production rate value is associated with its corresponding adjacent sampling time interval and appended to the lactate production rate sequence.

[0021] A further technical solution of the present invention is as follows: The process of obtaining the time series of colony formation is as follows:

[0022] Starting from the first acquisition of colony count time point and colony formation unit value, for each acquisition of colony count time point and colony formation unit value, the colony formation unit value is associated with the corresponding colony count time point. Then, according to the chronological order of the colony count time points, the associated colony formation unit value and the corresponding colony count time point are added to the colony formation unit time series of the current batch of fermented Five-Finger Peach Lactic Acid Bacteria fermented product.

[0023] A further technical solution of the present invention is as follows: The process of determining the fermentation metabolic stage interval is as follows:

[0024] The fermentation metabolic phase interval includes a non-negative rate phase interval and a negative rate phase interval;

[0025] Compare the lactic acid production rate value with a preset negative production rate tolerance threshold;

[0026] If the lactic acid generation rate is greater than or equal to the preset negative generation rate tolerance threshold, then the corresponding adjacent sampling time interval will be marked as the non-negative rate time interval.

[0027] If the lactic acid generation rate is less than the preset negative generation rate tolerance threshold, the corresponding adjacent sampling time interval will be marked as the negative rate time interval.

[0028] After obtaining multiple non-negative rate time intervals and multiple negative rate time intervals, the multiple consecutive non-negative rate time intervals are merged into one non-negative rate stage interval, and the multiple consecutive negative rate time intervals are merged into one negative rate stage interval.

[0029] A further technical solution of the present invention is as follows: The process of obtaining the time series of colony formation is as follows:

[0030] Fermentation broth samples are obtained according to a preset colony counting sampling cycle. Colony formation unit (CFU) values ​​are obtained by counting the fermentation broth samples on culture medium plates. After establishing a relationship between the CFU values ​​and the corresponding colony counting sampling time points, a CFU time series is formed according to the chronological order of the colony counting sampling time points.

[0031] As a further technical solution of the present invention, the process of obtaining the microbial community fluctuation range is as follows:

[0032] The colony-forming unit values ​​were matched to the fermentation and metabolic stage intervals according to the corresponding colony count sampling time points to form colony-forming unit subsequences.

[0033] Within the same fermentation metabolic stage interval, the fluctuation of adjacent colony formation units is obtained and accumulated to obtain the total stage fluctuation.

[0034] Compare the total fluctuation of the stage with the preset colony fluctuation threshold;

[0035] If the total fluctuation of a stage exceeds the preset colony fluctuation threshold, the corresponding fermentation metabolism stage interval will be recorded as the colony fluctuation interval.

[0036] If the total fluctuation of a stage is less than or equal to the preset colony fluctuation threshold, the corresponding fermentation metabolism stage interval will not be recorded as the colony fluctuation interval.

[0037] As a further technical solution of the present invention, the process of obtaining the anaerobic deviation intensity sequence is as follows:

[0038] The redox potential value is obtained by setting a redox potential probe in the fermenter, and the redox potential value is linked with the corresponding anaerobic state detection time point. Then, the anaerobic state parameter time series is formed according to the chronological order of the anaerobic state detection time points.

[0039] By using adjacent sampling time intervals corresponding to lactic acid production rate values ​​as time references, time matching is performed on the time series of anaerobic state parameters. Then, based on the extent and duration of the exceedance of redox potential values ​​relative to the preset upper limit threshold of anaerobic redox potential within adjacent sampling time intervals, the anaerobic deviation intensity value is determined to form an anaerobic deviation intensity sequence.

[0040] As a further technical solution of the present invention, the process of obtaining the anaerobic deviation range is as follows:

[0041] The anaerobic deviation intensity sequence was segmented and arranged according to the fermentation metabolic stage interval to form the stage anaerobic deviation subsequence;

[0042] The total anaerobic deviation is obtained by summing the anaerobic deviation intensity values ​​in the anaerobic deviation subsequences of each stage.

[0043] Compare the total deviation of anaerobic phase with the preset anaerobic deviation threshold;

[0044] If the total anaerobic deviation of a stage exceeds the preset anaerobic deviation threshold, the corresponding fermentation metabolic stage interval will be recorded as the anaerobic deviation interval.

[0045] If the total anaerobic deviation of a stage is less than or equal to the preset anaerobic deviation threshold, the corresponding fermentation metabolic stage interval will not be recorded as an anaerobic deviation interval.

[0046] As a further technical solution of the present invention, the process of screening abnormal intervals in quality control is as follows:

[0047] Map the negative rate phase interval, microbial community fluctuation interval, and anaerobic deviation interval to the same fermentation time axis;

[0048] By comparing the start and end times of the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval, the common overlapping time period that is simultaneously within the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval and whose duration meets the preset minimum overlap duration threshold is selected as the quality control abnormal interval.

[0049] As a further technical solution of the present invention, the process of generating anaerobic fermentation parameter control signals is as follows:

[0050] Based on the total stage fluctuation, total stage anaerobic deviation, preset colony fluctuation threshold, preset anaerobic deviation threshold, and corresponding negative rate stage interval corresponding to the quality control abnormal interval, at least one control signal is generated, including inert gas replacement, tank sealing detection, maintenance of micro-positive pressure inside the tank, adjustment of stirring intensity, adjustment of fermentation temperature, or adjustment of pH control range.

[0051] The beneficial effects of this invention are as follows:

[0052] This invention acquires a time series of lactic acid concentration and constructs a lactic acid production rate series. It then divides fermentation metabolic stages based on the change in lactic acid production rate relative to a preset negative tolerance threshold. This allows fermentation stage identification to no longer rely on fixed fermentation time or a single lactic acid endpoint value, enabling dynamic identification of states such as enhanced acid production, continuous acid production, slowing acid production, declining acid production, or abnormal consumption. Furthermore, it limits colony formation unit values ​​to the same fermentation metabolic stage interval for segmented arrangement and cumulative fluctuation analysis, avoiding misjudging changes in the number of normal viable bacteria between different metabolic stages as abnormalities in the microbial community. It also identifies unstable states of viable bacteria numbers within stages that are difficult to reflect with a single colony formation unit value. Furthermore, it utilizes oxidation... A time series of anaerobic state parameters was constructed using reduction potential values. Adjacent sampling time intervals corresponding to lactic acid production rate values ​​were used as time bases. Cumulative analysis of the extent and duration of redox potential exceedances was performed to determine anaerobic deviation intervals, thereby identifying latent anomalies such as oxygen exposure, abnormal tank sealing, sampling disturbances, or disruption of the anaerobic state. Finally, the negative rate phase interval, microbial community fluctuation interval, and anaerobic deviation interval were mapped to the same fermentation time axis. The overlapping of these three types of intervals was used to screen for quality control anomalies, and anaerobic fermentation parameter adjustment signals were generated accordingly. This provides a clear anomaly time window and quantitative basis for the fermentation control system, improving the accuracy of quality control, the stability of viable cell count, the stability of acid production efficiency, and the consistency of product quality. Attached Figure Description

[0053] The invention will now be further described with reference to the accompanying drawings.

[0054] Figure 1This is a flowchart of a quality control method in the preparation process of a five-finger peach probiotic product according to an embodiment of the present invention;

[0055] Figure 2 This is a logic judgment diagram of the microbial community fluctuation range in a quality control method for the preparation process of a Five-Finger Peach Probiotic product as described in an embodiment of the present invention.

[0056] Figure 3 This is an anaerobic deviation interval logic judgment diagram of a quality control method in the preparation process of a five-finger peach probiotic product as described in an embodiment of the present invention. Detailed Implementation

[0057] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0058] Example 1

[0059] Please see Figure 1 - Figure 3 As shown in the embodiment of the present invention, a quality control method for the preparation process of a five-finger peach probiotic product mainly includes the following steps:

[0060] Step 1: During the fermentation preparation of the lactic acid bacteria fermented product of Prunus pubescens in a fermenter, the lactic acid concentration time series is obtained, the lactic acid production rate series is obtained based on the lactic acid concentration time series, and the fermentation metabolic stage interval is determined according to the positive and negative changes of the lactic acid production rate value.

[0061] In step one, the process of obtaining the lactate concentration time series is as follows:

[0062] In some embodiments, the fermentation process of the five-finger peach lactic acid bacteria fermented product is carried out in a fermentation tank equipped with an online sampling port, and an online sampling device is connected to the online sampling port.

[0063] Within the fermentation monitoring time range corresponding to the current batch of fermented products of Five-Finger Peach Lactic Acid Bacteria, the online sampling device continuously samples from the fermentation tank and outputs fermentation liquid samples according to the preset sampling cycle;

[0064] Each time a fermentation broth sample is collected and output, the timing module in the online sampling device synchronously records the sampling time point corresponding to the fermentation broth sample.

[0065] It should be noted that the fermentation monitoring time range is determined by the fermentation start time and fermentation end time, wherein the fermentation end time is determined by the preset total fermentation time;

[0066] The preset sampling period is set comprehensively based on the preset total fermentation time, the rate of change of lactic acid concentration, the time consumed by the lactic acid detection module for a single detection, and the accuracy requirements for identifying the fermentation metabolic stage.

[0067] After each fermentation broth sample is output, the fermentation broth sample is preprocessed and then sent to the lactic acid detection module. The lactic acid detection module obtains the acid-base titration result based on the acid-base titration method, and further determines and outputs the lactic acid concentration value.

[0068] Among them, the pretreatment of fermentation broth samples refers to the treatment of fermentation broth samples by centrifugation, filtration and taking the supernatant to remove the influence of solid particles of Prunus pubescens raw material on the acid-base titration results.

[0069] Specifically, the process for determining a single lactic acid concentration value is as follows:

[0070] Let the sampling time point i be sampling time point Ti, the volume of standard titrant consumed at sampling time point Ti be Vi, the volume of standard titrant consumed for the blank sample be V0, the fermentation broth sample volume be Vs, the concentration of the standard titrant be N, the sample dilution factor be F, and the lactic acid equivalent conversion factor be M. Then the formula for determining the lactic acid concentration Ci at sampling time point Ti is:

[0071] Ci = N × (Vi - V0) × M × F / Vs

[0072] Where Vi, V0 and Vs use the same volume unit, Vi is the volume of standard titrant consumed when the fermentation broth sample reaches the titration endpoint, V0 is the volume of standard titrant consumed when the same titration operation is performed using a blank sample, M is determined according to the equivalence relationship between lactic acid and standard titrant, and F is the dilution factor of the fermentation broth sample before detection.

[0073] If Vi-V0 is less than 0, the fermentation broth sample corresponding to the sampling time point Ti will be retested;

[0074] If Vi-V0 is still less than 0 after retesting, the lactic acid concentration value Ci corresponding to the sampling time point Ti will be counted as 0 in the lactic acid concentration time series.

[0075] In the current fermentation process of the fermented products of Five-Finger Peach lactic acid bacteria, starting from the first sampling time point and lactic acid concentration value, after each sampling time point and lactic acid concentration value is obtained, the lactic acid concentration value is associated with the corresponding sampling time point, and the associated lactic acid concentration value and the corresponding sampling time point are added to the lactic acid concentration time series according to the sampling time sequence, so that the lactic acid concentration time series is dynamically updated with the fermentation process;

[0076] When the fermentation termination time is reached, the update of the lactic acid concentration time series is stopped, and the complete lactic acid concentration time series corresponding to the current fermentation batch of the Five-Finger Peach Lactic Acid Bacteria fermented product is obtained.

[0077] It should be noted that: the lactic acid concentration value represents the cumulative content of lactic acid in the fermentation broth at the corresponding sampling time point, and reflects the acid production level of the fermentation system of Prunus pubescens lactic acid bacteria fermentation product at the corresponding sampling time point;

[0078] Lactic acid concentration time series characterizes the dynamic evolution of lactic acid concentration in the fermentation batch of the current Five-finger Peach lactic acid bacteria fermented product with fermentation time. By associating and storing the lactic acid concentration values ​​corresponding to different sampling time points in the order of sampling time, the acid production change trajectory of the current Five-finger Peach lactic acid bacteria fermented product can be obtained.

[0079] In step one, the process of obtaining the lactate production rate sequence is as follows:

[0080] When there are at least two lactate concentration values ​​and two sampling time points in the obtained lactate concentration time series, start acquiring lactate generation rate values ​​and construct a lactate generation rate series;

[0081] Specifically, the process for obtaining the lactic acid production rate value is as follows:

[0082] Let the (i-1)th sampling time point in the lactic acid concentration time series be sampling time point Ti-1, and the ith sampling time point be sampling time point Ti, where i = 2, 3, ..., n;

[0083] Take Ti-1 as the lower limit of the interval and Ti as the upper limit of the interval, and construct the adjacent sampling time interval [Ti-1, Ti] corresponding to the sampling time point Ti-1 and the sampling time point Ti;

[0084] Obtain the duration of the sampling time interval between sampling time point Ti-1 and sampling time point Ti;

[0085] Extract the lactic acid concentration value Ci corresponding to the sampling time point Ti, and the lactic acid concentration value Ci-1 corresponding to the sampling time point Ti-1;

[0086] The difference between lactic acid concentration Ci and lactic acid concentration Ci-1 is calculated to obtain the adjacent difference of lactic acid concentration, i.e., ΔCi=Ci-Ci-1, where ΔCi represents the adjacent difference of lactic acid concentration.

[0087] The ratio of adjacent lactic acid concentration differences to the sampling time interval is calculated to obtain the lactic acid generation rate value Ri corresponding to adjacent sampling time intervals [Ti-1,Ti].

[0088] The lactate production rate value Ri is associated with the corresponding adjacent sampling time interval [Ti-1,Ti], and the associated lactate production rate value Ri and the corresponding adjacent sampling time interval [Ti-1,Ti] are appended to the lactate production rate sequence according to the chronological order of the corresponding adjacent sampling time intervals.

[0089] Based on the above, a lactic acid generation rate sequence is constructed. Whenever a lactic acid generation rate value is obtained, the lactic acid generation rate value is associated with the corresponding adjacent sampling time interval, and the associated lactic acid generation rate value and the corresponding adjacent sampling time interval are added to the lactic acid generation rate sequence. As the data in the lactic acid concentration time series is updated in real time, the lactic acid generation rate sequence is dynamically updated.

[0090] When the fermentation termination time is reached, the update of the lactic acid production rate sequence is stopped, and the complete lactic acid production rate sequence corresponding to the current fermentation batch of Prunus pubescens lactic acid bacteria fermentation product is obtained.

[0091] It should be noted that the lactic acid production rate sequence characterizes the rate and direction of change of lactic acid concentration over time in each adjacent sampling time interval in the current batch of fermented products of Prunus cerasifera lactic acid bacteria.

[0092] Each lactic acid production rate value corresponds to an adjacent sampling time interval, which is used to reflect the change in lactic acid concentration within the corresponding adjacent sampling time interval;

[0093] It should be noted that during the fermentation process of the current batch of Five-Finger Peach lactic acid bacteria fermented products, whenever a new sampling time point and its corresponding lactic acid concentration value are added to the lactic acid concentration time series, if there are already at least two lactic acid concentration values ​​in the current lactic acid concentration time series, a new lactic acid generation rate value is calculated based on the new lactic acid concentration value and the lactic acid concentration value corresponding to its previous sampling time point, and the new lactic acid generation rate value and its corresponding time interval are added to the lactic acid generation rate series of the current fermentation batch.

[0094] In step one, the process of determining the fermentation metabolic stage interval is as follows:

[0095] It should be noted that the fermentation metabolic phase includes both the non-negative rate phase and the negative rate phase.

[0096] When there is at least one lactate generation rate value in the lactate generation rate sequence, the lactate generation rate value is compared with the preset negative generation rate tolerance threshold according to the time sequence of the corresponding adjacent sampling time intervals.

[0097] If the lactic acid generation rate value is greater than or equal to the preset negative generation rate tolerance threshold, it indicates that the corresponding lactic acid generation rate value has not shown a negative change exceeding the lactic acid generation rate tolerance range. That is, the lactic acid concentration has not experienced a reliably identifiable decrease within the corresponding adjacent sampling time interval. In this case, the corresponding adjacent sampling time interval is marked as a non-negative rate time interval.

[0098] If the lactic acid generation rate value is less than the preset negative generation rate tolerance threshold, it indicates that the corresponding lactic acid generation rate value has shown a negative change exceeding the lactic acid generation rate tolerance range. That is, the lactic acid concentration in the corresponding adjacent sampling time interval has decreased reliably, and the corresponding adjacent sampling time interval is marked as the negative rate time interval.

[0099] It should be noted that the preset negative threshold for the generation rate tolerance represents the negative boundary of the allowable fluctuation range of the lactic acid generation rate near zero. It is used to determine whether the lactic acid generation rate value has significantly fallen below zero. The preset negative threshold for the generation rate tolerance is a negative preset generation rate tolerance threshold, which is determined based on the rate fluctuation value corresponding to the repeatability error of the lactic acid detection module, the rate fluctuation value corresponding to the blank sample, and the maximum detection fluctuation value near zero rate in historically stable fermentation batches. For example, the largest value among the rate fluctuation value corresponding to the repeatability error of the lactic acid detection module, the rate fluctuation value corresponding to the blank sample, and the maximum detection fluctuation value near zero rate in historically stable fermentation batches is taken as the preset generation rate tolerance threshold.

[0100] The non-negative time interval of the rate indicates that the fermentation system of Prunus pubescens lactic acid bacteria fermentation product is in a state of enhanced acid production, continuous acid production, and slowing down acid production but without significant decline.

[0101] The negative time interval of the rate indicates that the fermentation system of Prunus pubescens lactic acid bacteria fermentation product may enter a state of weakened acid production capacity, metabolic transition, metabolic decline or abnormal consumption.

[0102] Based on the above, after obtaining multiple non-negative rate time intervals and multiple negative rate time intervals, the multiple consecutive non-negative rate time intervals are merged into one non-negative rate stage interval, and the multiple consecutive negative rate time intervals are merged into one negative rate stage interval.

[0103] When one of two adjacent sampling time intervals is marked as a non-negative rate time interval and the other is marked as a negative rate time interval, the sampling time point shared between the two adjacent sampling time intervals is used as the switching sampling time point for dividing the fermentation metabolic stage interval, and the target start time point and target end time point corresponding to each fermentation metabolic stage interval after division are recorded.

[0104] Specifically, R2, R3, R4, R5, and R6 are all lactic acid production rate values. When R2, R3, and R4 are all greater than or equal to a preset negative production rate tolerance threshold, and R5 and R6 are all less than the preset negative production rate tolerance threshold, then the adjacent sampling time intervals corresponding to R2, R3, and R4 are recorded as multiple consecutive non-negative rate time intervals and merged into one non-negative rate stage interval. The start and end times of the corresponding non-negative rate stage interval are recorded as the target start and end times. Similarly, the adjacent sampling time intervals corresponding to R5 and R6 are recorded as multiple consecutive negative rate time intervals and merged into one negative rate stage interval. The start and end times of the corresponding negative rate stage interval are recorded as the target start and end times.

[0105] It should be noted that: the non-negative rate phase interval indicates that the fermentation system of Prunus pedatus lactic acid bacteria fermentation product is in a continuous fermentation state of enhanced acid production, continuous acid production, and acid production slowing down but not significantly declining.

[0106] The negative rate phase interval indicates that the fermentation system of Prunus pubescens lactic acid bacteria fermentation product may enter a continuous fermentation state with weakened acid production capacity, metabolic transition, metabolic decline or abnormal consumption.

[0107] It is understandable that the purpose of step one is to obtain the time series of lactic acid concentration and the lactic acid production rate, and to use the positive and negative changes in the lactic acid production rate as the basis for dividing the metabolic stages, thereby dividing and obtaining the fermentation metabolic stage intervals, so that subsequent microbial community fluctuation analysis, anaerobic deviation analysis and screening of abnormal quality control intervals all have a unified time stage basis.

[0108] Step 2: Obtain the time series of colony formation units, and match and segment the data within the time series of colony formation units according to the fermentation metabolic stage interval to form subsequences of colony formation units. Based on the data within the subsequences of colony formation units, obtain and analyze the total stage fluctuation and determine the fluctuation range of the microbial community.

[0109] In step two, the process of obtaining the colony formation unit time series is as follows:

[0110] In some embodiments, within the fermentation monitoring time range corresponding to the current batch of fermented product of *Prunus pedatus* lactic acid bacteria, fermentation broth samples are continuously obtained from the fermenter according to the preset colony counting sampling cycle, and culture medium plate counting is performed on the fermentation broth samples. According to the culture medium plate counting method, the colony count on the culture medium plate, the dilution factor conversion value and the inoculation volume are used to obtain the colony formation unit value.

[0111] Each time a fermentation broth sample is obtained, the corresponding colony count sampling time point is recorded simultaneously.

[0112] After the culture is completed and the plate count results are obtained, the colony formation unit value is correlated with the corresponding colony count sampling time point;

[0113] It should be noted that the preset colony counting sampling cycle is set separately in advance based on the culture time required for plate counting, the rate of change in the number of bacteria, the accuracy requirements for identifying the fermentation and metabolic stages, and the requirements for controlling the number of viable bacteria in the product.

[0114] The colony formation unit value represents the number of viable bacteria in the fermentation broth sample at the corresponding colony counting sampling time point. The colony formation unit value can reflect the state of the number of viable bacteria in the fermentation system of the *Prunus pubescens* lactic acid bacteria fermentation product at the corresponding colony counting sampling time point.

[0115] In the current fermentation process of the fermented batch of Five-Finger Peach lactic acid bacteria fermented products, starting from the first acquisition of the colony count sampling time point and colony formation unit value, for each colony count sampling time point corresponding to the colony formation unit value, the colony formation unit value is associated with the corresponding colony count sampling time point, and the associated colony formation unit value and the corresponding colony count sampling time point are added to the colony formation unit time series according to the chronological order of the colony count sampling time points;

[0116] Once the fermentation termination time is reached and the counting of culture medium plates containing the fermentation broth samples is completed, the update of the colony formation unit time series is stopped, and the complete colony formation unit time series corresponding to the current batch of fermented Prunus pubescens lactic acid bacteria product is obtained.

[0117] It should be noted that: the colony formation unit time series characterizes the dynamic evolution of the number of live bacteria in the fermentation batch of the current Five-finger Peach lactic acid bacteria fermentation product as fermentation time changes. By associating and storing the colony formation unit values ​​corresponding to different colony counting sampling time points in chronological order, the trajectory of the change in the number of live bacteria in the current fermentation batch can be obtained.

[0118] In step two, the process of obtaining the colony-forming unit subsequence is as follows:

[0119] Extract the fermentation metabolic stage intervals, where each fermentation metabolic stage interval records the corresponding target start time point and target end time point;

[0120] Based on any colony formation unit value, the corresponding colony counting sampling time point is extracted, and the colony counting sampling time point is compared with the target start time point and target end time point corresponding to each fermentation metabolic stage interval;

[0121] If the colony count sampling time point falls within a certain fermentation and metabolic stage interval, then the colony formation unit value will be assigned to the corresponding fermentation and metabolic stage interval.

[0122] Based on the above, the above fermentation metabolism stage interval matching operation is performed on each colony formation unit value in the colony formation unit time series to obtain the colony formation unit subsequence corresponding to each fermentation metabolism stage interval;

[0123] It should be noted that: a colony-forming unit subsequence refers to a sequence of multiple colony-forming unit values ​​arranged in chronological order of colony count sampling time points within the same fermentation metabolic stage interval;

[0124] Specifically, for a certain fermentation metabolic stage interval [Ta, Tb], if the colony counting sampling time points Tp1, Tp2, and Tp3 all fall within the fermentation metabolic stage interval [Ta, Tb], then the colony forming unit values ​​Pp1, Pp2, and Pp3 corresponding to the colony counting sampling time points Tp1, Tp2, and Tp3 are arranged in chronological order to form a colony forming unit subsequence corresponding to a certain fermentation metabolic stage interval;

[0125] It should be noted that: dividing the colony formation unit value into segments according to the fermentation and metabolic stages can limit the subsequent analysis of microbial community fluctuations to the same metabolic stage, and avoid misjudging the changes in the number of normal viable bacteria between different fermentation and metabolic stages as abnormal microbial community fluctuations.

[0126] In step two, the process of obtaining the total fluctuation amount for each stage is as follows:

[0127] Obtain the subsequence of the colony-forming unit corresponding to any fermentation metabolic stage interval;

[0128] If there are at least two colony-forming unit values ​​within the colony-forming unit subsequence, then extract the two adjacent colony-forming unit values ​​according to the order of the colony counting sampling time points, perform a difference operation on the two adjacent colony-forming unit values, and take the absolute value of the difference to obtain the fluctuation amount of adjacent colony-forming units;

[0129] After obtaining the fluctuation of adjacent colony formation units corresponding to each of the two adjacent colony formation unit values ​​within the same fermentation metabolic stage interval, the fluctuation of each adjacent colony formation unit is accumulated one by one to obtain the total stage fluctuation of the corresponding fermentation metabolic stage interval.

[0130] The total fluctuation of a stage represents the cumulative fluctuation intensity of the number of viable bacteria within the corresponding fermentation and metabolic stage interval. The larger the total fluctuation of a stage, the more drastic the change in the colony-forming units within the corresponding fermentation and metabolic stage interval, and the worse the stability of the bacterial population. The smaller the total fluctuation of a stage, the more stable the change in the colony-forming units within the corresponding fermentation and metabolic stage interval, and the better the stability of the bacterial population.

[0131] It should be noted that if there are fewer than two colony formation units (CFU) values ​​in a certain fermentation metabolic stage interval, the fluctuation of adjacent CFU values ​​cannot be calculated for the corresponding fermentation metabolic stage interval, and the result of the microbial fluctuation interval for the corresponding fermentation metabolic stage interval will not be output. If the fermentation process is still ongoing, the above judgment will be performed again after the newly added CFU values ​​are obtained in the next colony counting sampling cycle. If the fermentation process has ended and the corresponding fermentation metabolic stage interval is still less than two CFU values, the corresponding fermentation metabolic stage interval will not participate in the microbial fluctuation interval screening.

[0132] In step two, the process of obtaining the microbial community fluctuation range is as follows:

[0133] After obtaining the total stage fluctuation corresponding to any fermentation metabolic stage interval, the total stage fluctuation is compared with the preset colony fluctuation threshold.

[0134] If the total fluctuation of a stage is greater than the preset colony fluctuation threshold, it indicates that the number of live bacteria in the corresponding fermentation metabolism stage interval has a cumulative fluctuation that exceeds the normal stable range. The corresponding fermentation metabolism stage interval is recorded as the colony fluctuation interval, and the target start time, target end time, total stage fluctuation, and preset colony fluctuation threshold of the corresponding fermentation metabolism stage interval are recorded simultaneously.

[0135] If the total fluctuation of a stage is less than or equal to the preset colony fluctuation threshold, it indicates that the fluctuation of the number of live bacteria in the corresponding fermentation metabolism stage interval has not exceeded the normal stable range. Therefore, the corresponding fermentation metabolism stage interval will not be recorded as a microbial community fluctuation interval, and the target start time, target end time, total stage fluctuation, and preset colony fluctuation threshold of the corresponding fermentation metabolism stage interval will not be recorded synchronously.

[0136] It should be noted that the preset colony fluctuation threshold is set in advance according to the same preset colony counting sampling period, the same stage division rules, the same range of difference items, and the fluctuation range of colony formation units in historically stable batches of fermented products of *Prunus pedatus* lactic acid bacteria. It represents the upper limit of normal cumulative fluctuation of the number of live bacteria in the same fermentation metabolic stage in historically stable batches of fermented products of *Prunus pedatus* lactic acid bacteria.

[0137] Based on the above, multiple fermentation and metabolic stage intervals were traversed, and the records of microbial community fluctuation intervals corresponding to each fermentation and metabolic stage interval were obtained.

[0138] It should be noted that the microbial community fluctuation interval recording result can include one or more microbial community fluctuation intervals; if there is no fermentation metabolism stage interval that meets the recording conditions, the microbial community fluctuation interval recording result will be empty. Each recorded microbial community fluctuation interval shall include at least the target start time point, target end time point, total stage fluctuation, and preset colony fluctuation threshold of the corresponding fermentation metabolism stage interval.

[0139] Understandably, the purpose of step two is to: based on the fermentation metabolism stage interval, obtain and analyze the colony formation unit value and the corresponding colony count sampling time point, further obtain the total stage fluctuation, and then obtain the record results of the microbial community fluctuation interval by comparing the total stage fluctuation with the preset colony fluctuation threshold. This can identify the unstable state of viable bacteria quantity that is difficult to reflect by a single colony formation unit value, and provide a basis for judging the stability dimension of viable bacteria quantity for subsequent quality control abnormal interval screening.

[0140] Step 3: Obtain the time series of anaerobic state parameters, obtain the anaerobic deviation intensity sequence based on the anaerobic state parameter time series, segment the anaerobic deviation intensity sequence according to the fermentation metabolic stage interval and obtain the total anaerobic deviation of each stage, and determine the anaerobic deviation interval based on the total anaerobic deviation of each stage.

[0141] In step three, the process of obtaining the time series of anaerobic state parameters is as follows:

[0142] In some embodiments, within the fermentation monitoring time range corresponding to the current batch of fermented five-finger peach lactic acid bacteria fermented product, the redox potential value in the fermentation liquid is detected by an redox potential probe set in the fermenter according to a preset redox potential detection cycle or a preset continuous acquisition frequency.

[0143] Each time a redox potential value is acquired, the corresponding anaerobic state detection time point is recorded simultaneously.

[0144] It should be noted that under anaerobic fermentation conditions, the oxidation-reduction potential value characterizes the stability of the reducing environment of the fermentation system. The greater the deviation of the oxidation-reduction potential value from the preset anaerobic control range, the more obvious the degree to which the current fermentation system deviates from the anaerobic state.

[0145] In the current fermentation process of the fermented batch of Five-Finger Peach lactic acid bacteria fermented products, starting from the first time the anaerobic state detection time point and the redox potential value are obtained, each time an anaerobic state detection time point and a redox potential value are obtained, the redox potential value is associated with the corresponding anaerobic state detection time point, and the associated redox potential value and the corresponding anaerobic state detection time point are added to the anaerobic state parameter time series according to the chronological order of the anaerobic state detection time points.

[0146] It should be noted that the time series of anaerobic state parameters consists of the redox potential value and its corresponding anaerobic state detection time point, which characterizes the dynamic evolution of the reducing environment of the fermentation system in the current fermentation batch as fermentation time changes.

[0147] When the fermentation termination time is reached, the update of the anaerobic state parameter time series is stopped, and the complete anaerobic state parameter time series corresponding to the current fermentation batch of Prunus pubescens lactic acid bacteria fermentation product is obtained.

[0148] In step three, the process of obtaining the anaerobic deviation intensity sequence is as follows:

[0149] Extract the adjacent sampling time intervals corresponding to each lactic acid production rate value, and use the adjacent sampling time intervals as the time reference to perform time matching on the time series of anaerobic state parameters.

[0150] Specifically, if the lactic acid production rate value Ri corresponds to the adjacent sampling time interval [Ti-1,Ti], then the adjacent sampling time interval [Ti-1,Ti] is used as the anaerobic deviation intensity calculation interval to determine the redox potential value corresponding to the sampling time point Ti-1 in the adjacent sampling time interval [Ti-1,Ti], and the redox potential value corresponding to the sampling time point Ti.

[0151] If there are corresponding redox potential detection values ​​at both sampling time point Ti-1 and sampling time point Ti, then the redox potential detection values ​​corresponding to each sampling time point Ti-1 and sampling time point Ti are directly used.

[0152] If there is no corresponding redox potential detection value at sampling time point Ti-1 or sampling time point Ti, then linear interpolation is performed based on the adjacent anaerobic state detection time points and redox potential values ​​in the anaerobic state parameter time series to obtain the redox potential values ​​corresponding to sampling time point Ti-1 and sampling time point Ti respectively.

[0153] If linear interpolation cannot be performed on sampling time point Ti-1 or sampling time point Ti based on the anaerobic state parameter time series, then the anaerobic deviation intensity value will not be calculated for the corresponding adjacent sampling time intervals; if the fermentation process is still ongoing, time matching will continue after the newly acquired redox potential value is obtained.

[0154] The average value of the redox potential value at sampling time point Ti-1 and the redox potential value at sampling time point Ti is calculated to obtain the average redox potential value corresponding to adjacent sampling time intervals [Ti-1,Ti].

[0155] Obtain the duration of the time interval between adjacent sampling time intervals [Ti-1, Ti].

[0156] Based on the average redox potential value, the time interval duration, and the preset upper limit threshold of anaerobic redox potential, the threshold over-limit time integration method based on the redox potential over-limit amplitude and over-limit duration is used to determine the anaerobic deviation intensity value corresponding to the adjacent sampling time interval [Ti-1,Ti].

[0157] Under anaerobic fermentation conditions, when the redox potential value is greater than the preset upper limit threshold of anaerobic redox potential, it indicates that the reducing environment of the fermentation system is weakened, and there may be oxygen exposure, abnormal tank sealing, sampling disturbance, or destruction of the anaerobic state.

[0158] If the anaerobic deviation intensity value is greater than 0, it indicates that the fermentation system has an anaerobic state deviation that exceeds the preset anaerobic control range within the corresponding adjacent sampling time interval.

[0159] If the anaerobic deviation intensity value is equal to 0, it indicates that the fermentation system did not show any abnormal redox potential exceeding the preset anaerobic control range within the corresponding adjacent sampling time interval;

[0160] After obtaining each anaerobic deviation intensity value, the anaerobic deviation intensity value is associated with the corresponding adjacent sampling time interval. Then, according to the chronological order of the corresponding adjacent sampling time intervals, the associated anaerobic deviation intensity value and the corresponding adjacent sampling time interval are added to the anaerobic deviation intensity sequence, and the anaerobic deviation intensity sequence is dynamically updated.

[0161] It should be noted that: the anaerobic deviation intensity sequence characterizes the degree of deviation of the fermentation system from the anaerobic state in each adjacent sampling time interval of the current batch of fermented products of Prunus cerasifera lactic acid bacteria.

[0162] Each anaerobic deviation intensity value corresponds to an adjacent sampling time interval, and forms a corresponding relationship with the lactic acid production rate value corresponding to the same adjacent sampling time interval;

[0163] When the fermentation termination time is reached, the anaerobic deviation intensity sequence is stopped from being updated, and the complete anaerobic deviation intensity sequence corresponding to the current fermentation batch of Prunus pubescens lactic acid bacteria fermentation product is obtained.

[0164] In step three, the process of obtaining the total anaerobic deviation during the stage is as follows:

[0165] Extracting multiple fermentation metabolic phase intervals;

[0166] Each fermentation metabolic stage interval is recorded with a corresponding target start time and target end time.

[0167] Based on any fermentation metabolic stage interval, extract the anaerobic deviation intensity values ​​in the anaerobic deviation intensity sequence that fall within the corresponding fermentation metabolic stage interval in the adjacent sampling time intervals, and arrange them in the chronological order of the corresponding adjacent sampling time intervals to form the stage anaerobic deviation subsequence corresponding to the fermentation metabolic stage interval.

[0168] It should be noted that: the stage anaerobic deviation subsequence refers to a sequence of multiple anaerobic deviation intensity values ​​arranged in the order of adjacent sampling time intervals within the same fermentation metabolic stage interval;

[0169] Each anaerobic deviation intensity value represents the cumulative extent to which the redox potential value exceeds the preset upper limit threshold of anaerobic redox potential within its corresponding adjacent sampling time interval;

[0170] After obtaining the anaerobic deviation subsequence corresponding to any fermentation metabolic stage interval, if there is at least one anaerobic deviation intensity value in the anaerobic deviation subsequence, the anaerobic deviation intensity values ​​in the anaerobic deviation subsequence are accumulated one by one to form the total anaerobic deviation of the corresponding fermentation metabolic stage interval.

[0171] The total deviation of anaerobic phase represents the cumulative intensity of the fermentation system deviating from the anaerobic environment within the corresponding fermentation metabolic phase interval. The greater the total deviation of anaerobic phase, the higher the cumulative degree to which the redox potential value exceeds the preset upper limit threshold of anaerobic redox potential within the corresponding fermentation metabolic phase interval. The more obvious the weakening of the reducing environment of the fermentation system, the more likely there are situations such as oxygen exposure, abnormal tank sealing, sampling disturbance, or destruction of the anaerobic state.

[0172] It should be noted that if there is no anaerobic deviation intensity value corresponding to the adjacent sampling time interval within a certain fermentation metabolic stage interval, or if there is no anaerobic deviation intensity value that can be accumulated within the stage anaerobic deviation subsequence, then the total anaerobic deviation of the corresponding fermentation metabolic stage interval cannot be calculated, and the anaerobic deviation interval result of the corresponding fermentation metabolic stage interval will not be output. If the fermentation process is still ongoing, the above judgment will continue after obtaining the newly added redox potential value in the next detection cycle. If the fermentation process has ended and the total anaerobic deviation of the corresponding fermentation metabolic stage interval still cannot be formed, then the corresponding fermentation metabolic stage interval will not participate in the anaerobic deviation interval screening.

[0173] In step three, the process of obtaining the anaerobic deviation range is as follows:

[0174] After obtaining the total anaerobic deviation corresponding to any fermentation metabolic stage interval, the total anaerobic deviation is compared with the preset anaerobic deviation threshold.

[0175] If the total anaerobic deviation of a stage is greater than the preset anaerobic deviation threshold, it indicates that there is an anaerobic state deviation in the fermentation system within the corresponding fermentation metabolic stage interval that exceeds the normal stable range. The corresponding fermentation metabolic stage interval is recorded as the anaerobic deviation interval, and the target start time, target end time, total anaerobic deviation of the stage, and preset anaerobic deviation threshold of the corresponding fermentation metabolic stage interval are recorded simultaneously.

[0176] If the total anaerobic deviation of a stage is less than or equal to the preset anaerobic deviation threshold, it indicates that the anaerobic state deviation within the corresponding fermentation and metabolism stage interval has not exceeded the normal stable range. Therefore, the corresponding fermentation and metabolism stage interval will not be recorded as an anaerobic deviation interval, and the target start time, target end time, total anaerobic deviation of the stage, and preset anaerobic deviation threshold of the corresponding fermentation and metabolism stage interval will not be recorded synchronously.

[0177] It should be noted that the preset anaerobic deviation threshold represents the cumulative upper limit of the normal anaerobic state deviation that can occur within the same fermentation metabolic stage in a historically stable batch of *Prunus cerasifera* lactic acid bacteria anaerobic fermentation. It is determined in advance based on the fluctuation range of redox potential values, redox potential detection cycle, preset upper limit threshold of anaerobic redox potential, anaerobic state maintenance requirements, fermenter sealing status, and anaerobic control process requirements in the historically stable batch of *Prunus cerasifera* lactic acid bacteria anaerobic fermentation.

[0178] Specifically, under the same redox potential detection method, the same preset upper limit threshold of anaerobic redox potential, the same preset sampling period, the same fermentation metabolic stage division rules, and the same anaerobic deviation intensity value calculation method, the total anaerobic deviation of each corresponding fermentation metabolic stage interval in multiple historically stable batches of five-finger peach lactic acid bacteria anaerobic fermentation is counted, and the average value plus the preset multiple standard deviation is taken as the preset anaerobic deviation threshold.

[0179] Based on the above, multiple fermentation metabolic stage intervals were traversed, and the anaerobic deviation interval records corresponding to each fermentation metabolic stage interval were obtained.

[0180] It should be noted that the anaerobic deviation interval recording results can include one or more anaerobic deviation intervals. If there is no fermentation metabolism stage interval that meets the recording conditions, the anaerobic deviation interval recording results will be empty. Each recorded anaerobic deviation interval should include at least the target start time point, target end time point, total anaerobic deviation of the corresponding fermentation metabolism stage interval, and preset anaerobic deviation threshold.

[0181] The anaerobic deviation range indicates that within the same fermentation metabolic stage range, the cumulative extent to which the redox potential value exceeds the preset upper limit threshold of the anaerobic redox potential has exceeded the normal fluctuation range allowed by historically stable anaerobic fermentation batches.

[0182] Understandably, the purpose of step three is to: obtain the redox potential value and use the adjacent sampling time intervals corresponding to the lactic acid production rate value as the time reference to perform cumulative analysis on the redox potential exceeding the limit and the duration of exceeding the limit, determine the anaerobic deviation interval, thereby identifying the weakening of the reducing environment, oxygen exposure, abnormal tank sealing or destruction of the anaerobic state that are difficult to detect when observing lactic acid concentration or colony formation unit value alone, and provide a basis for judging the anaerobic environment stability dimension for subsequent screening of abnormal intervals in quality control;

[0183] Step 4: Align the fermentation metabolism phase interval, microbial community fluctuation interval, and anaerobic deviation interval with the time axis, and compare the start and end times of the negative rate phase interval, microbial community fluctuation interval, and anaerobic deviation interval to screen out the quality control abnormal intervals, and generate anaerobic fermentation parameter regulation signals based on the recorded results of the quality control abnormal intervals.

[0184] In step four, the timeline alignment process is as follows:

[0185] In some embodiments, all fermentation metabolic stage intervals are extracted, wherein each fermentation metabolic stage interval is recorded with a corresponding target start time point and target end time point;

[0186] Extract all microbial community fluctuation intervals, where each microbial community fluctuation interval includes at least the target start time point, target end time point, total fluctuation of the corresponding fermentation and metabolic stage interval, and preset colony fluctuation threshold.

[0187] Extract all anaerobic deviation intervals, where each anaerobic deviation interval includes at least the target start time, target end time, total anaerobic deviation of the corresponding fermentation metabolic stage interval, and preset anaerobic deviation threshold.

[0188] Using the fermentation start time of the current batch of Five-Finger Peach Lactic Acid Bacteria Fermented Products as the zero point of the unified time axis, the target start time and target end time in all fermentation metabolic stage intervals, microbial community fluctuation intervals, and anaerobic deviation intervals are mapped to the same fermentation time axis.

[0189] It should be noted that the start and end times of each interval can be represented by minutes, hours, or other uniform time units within the same fermentation timeline;

[0190] By using a unified time coordinate, the recording results of fermentation metabolism stage intervals, microbial community fluctuation intervals, and anaerobic deviation intervals can be compared under the same time reference.

[0191] In step four, the process of screening for quality control anomaly intervals is as follows:

[0192] Based on the entire fermentation metabolic phase interval, the negative rate phase interval is extracted;

[0193] Based on the fluctuation range of all bacterial communities, extract any fluctuation range of any bacterial community.

[0194] Based on all anaerobic deviation intervals, extract any one of them;

[0195] The target start time point and target end time point corresponding to the extracted negative rate phase interval, microbial community fluctuation interval and anaerobic deviation interval are compared one by one to determine whether there are any overlapping time periods in the negative rate phase interval, microbial community fluctuation interval and anaerobic deviation interval.

[0196] Specifically, for example, let the negative rate phase interval be [As, Ae], where As represents the target start time point of the negative rate phase interval and Ae represents the target end time point of the negative rate phase interval.

[0197] Let the range of bacterial community fluctuation be [Bs, Be], where Bs represents the target start time of the range of bacterial community fluctuation and Be represents the target end time of the range of bacterial community fluctuation.

[0198] Let the anaerobic deviation interval be [Ds, De], where Ds represents the target start time of the anaerobic deviation interval and De represents the target end time of the anaerobic deviation interval;

[0199] The formula for determining the starting time point Ts of the overlapping portion of the three types of intervals is:

[0200] Ts=max(As,Bs,Ds)

[0201] The formula for determining the end time Te of the overlapping portion of the three types of intervals is:

[0202] Te=min(Ae,Be,De)

[0203] If the starting time point Ts is less than the ending time point Te, it indicates that there is a common overlapping time period with a duration between the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval. The common overlapping time period [Ts,Te] is taken as the candidate quality control abnormal interval.

[0204] If the start time Ts is greater than or equal to the end time Te, it indicates that there is no common overlapping time period with duration between the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval, and the corresponding interval combination is not recorded as a candidate quality control abnormal interval.

[0205] To avoid false alarms caused by instantaneous contact at boundary time points, a preset minimum overlap duration threshold is set.

[0206] Obtain the duration between the start time point Ts and the end time point Te as the comparison overlap duration;

[0207] If the overlap duration is greater than or equal to the preset minimum overlap duration threshold, the common overlap time period [Ts,Te] will be recorded as a quality control abnormal interval.

[0208] If the overlap duration is less than the preset minimum overlap duration threshold, the common overlap time period [Ts,Te] will not be recorded as a quality control abnormal interval.

[0209] It should be noted that the preset minimum overlap time threshold is preset based on the lactic acid detection sampling cycle, the colony counting sampling cycle, the redox potential detection cycle, and the minimum effective control time allowed by the fermentation control system.

[0210] Traverse all negative rate intervals, all microbial community fluctuation intervals, and all anaerobic deviation intervals. Perform the above operation on each combination of intervals between negative rate intervals, microbial community fluctuation intervals, and anaerobic deviation intervals to obtain the quality control abnormal interval record results corresponding to the fermentation batch of the current Five-Finger Peach Lactic Acid Bacteria Fermentation Product.

[0211] It should be noted that if there is no negative rate phase interval, microbial community fluctuation interval, or anaerobic deviation interval in the current fermentation batch, the three types of intervals will not be judged to overlap, and the results of the quality control abnormal interval record will not be output. If the fermentation process is still ongoing, the above judgment will continue after adding lactic acid concentration value, colony formation unit value, or redox potential value.

[0212] The abnormal quality control interval must simultaneously fall within the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval.

[0213] If a certain time interval is only in the negative rate phase interval, but not in the microbial community fluctuation interval and the anaerobic deviation interval at the same time, then this time interval will not be recorded as a quality control abnormal interval.

[0214] If a certain time interval is only in the microbial community fluctuation range or only in the anaerobic deviation range, but not simultaneously in the negative rate phase range, then this time interval will not be recorded as a quality control abnormality range.

[0215] If a certain time interval is simultaneously in the microbial community fluctuation interval and the anaerobic deviation interval, but not in the negative rate phase interval, then this time interval will not be recorded as a quality control abnormal interval.

[0216] Therefore, only when the same time period simultaneously shows a negative change in lactic acid production rate, abnormal fluctuation in the cumulative number of viable bacteria, and abnormal deviation in anaerobic state, can the corresponding time period be identified as an abnormal quality control interval.

[0217] After obtaining at least one quality control anomaly interval, sort them from earliest to latest according to the start time point corresponding to each quality control anomaly interval, and assign a corresponding anomaly interval number to each quality control anomaly interval.

[0218] For each quality control abnormality interval, record the abnormality interval number, the start time of the abnormality interval, the end time of the abnormality interval, the corresponding rate negative stage interval number, the corresponding microbial community fluctuation interval number, the corresponding anaerobic deviation interval number, the total stage fluctuation, the preset microbial community fluctuation threshold, the total stage anaerobic deviation, and the preset anaerobic deviation threshold.

[0219] If the time interval between two adjacent quality control abnormal intervals is less than the preset merging interval, the two adjacent quality control abnormal intervals will be merged into one continuous quality control abnormal interval, and the earlier start time point will be used as the start time point of the merged quality control abnormal interval, and the later end time point will be used as the end time point of the merged quality control abnormal interval.

[0220] When merging two adjacent quality control abnormal intervals, the total stage fluctuation and total stage anaerobic deviation corresponding to the merged quality control abnormal interval can be the maximum value or cumulative value in the merged interval, or the total stage fluctuation and total stage anaerobic deviation of each original abnormal interval can be retained. The specific recording rules are determined by the preset control rule table of the fermentation control system and are kept consistent within the same fermentation batch.

[0221] It should be noted that the preset merging interval is preset based on the lactic acid detection sampling cycle, colony counting sampling cycle, redox potential detection cycle, or the minimum control interval allowed by the fermentation control system.

[0222] In step four, the process of generating anaerobic fermentation parameter control signals is as follows:

[0223] Input the results of the quality control anomaly interval recordings into the fermentation control system;

[0224] The fermentation control system calls the preset control rule table and generates anaerobic fermentation parameter adjustment signals based on the total stage fluctuation, total stage anaerobic deviation, preset colony fluctuation threshold, preset anaerobic deviation threshold and corresponding rate negative stage interval corresponding to the quality control abnormal interval.

[0225] It should be noted that the purpose of generating anaerobic fermentation parameter control signals is to intervene in a timely manner within the abnormal quality control range when fermentation states simultaneously exhibit negative changes in lactic acid production rate, abnormal fluctuations in the cumulative number of viable bacteria, and abnormal increases in redox potential. This allows the fermentation system to restore or maintain a reducing environment adapted to the anaerobic metabolism of lactic acid bacteria, thereby inhibiting further fluctuations in the number of bacteria, reducing the impact of deviations from the anaerobic state on acid production efficiency and viable bacteria stability, preventing the fermentation system from developing from local abnormalities to overall instability, and ensuring the stability of viable bacteria count, acid production efficiency, and product quality consistency of the fermented products of *Prunus cerasifera*.

[0226] Specifically, for example, when the total fluctuation of a stage within the abnormal quality control range exceeds the preset colony fluctuation threshold, and the total deviation of the stage anaerobic process exceeds the preset anaerobic deviation threshold, the fermentation control system sends a control signal to the inert gas replacement unit to increase the inert gas replacement flow rate or extend the inert gas replacement time, sends a sealing status detection signal to the tank sealing detection unit, sends a control signal to the exhaust valve or pressure regulating unit to maintain a slight positive pressure inside the tank, sends a control signal to the stirring device to reduce or adjust the stirring intensity to reduce oxygen entrainment, sends a control signal to the temperature control unit to adjust the fermentation temperature, or sends a control signal to the pH adjustment unit to adjust the pH control range.

[0227] It should be noted that the inert gas replacement flow rate, inert gas replacement time, micro-positive pressure range inside the tank, stirring intensity adjustment range, fermentation temperature adjustment range, and pH control range adjustment range are determined based on the specific lactic acid bacteria strain, the composition of the *Prunus pedatus* fermentation substrate, the fermenter volume, the anaerobic fermentation process objectives, and the preset control rule table.

[0228] Understandably, the purpose of step four is to map the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval to the same fermentation time axis. By using the overlap of these three types of intervals, abnormal quality control intervals are identified and screened. This allows for cross-validation of the anaerobic state deviations characterized by negative changes in lactic acid production rate, abnormal fluctuations in the cumulative number of viable bacteria, and exceeding the redox potential limit, avoiding misjudgments caused by fluctuations in a single indicator, changes in normal metabolic cycles, or short-term redox potential disturbances. Simultaneously, anaerobic fermentation parameter control signals are generated based on the abnormal quality control intervals, providing a clear abnormal time window and quantitative basis for the fermentation control system, thereby achieving precise quality control of the anaerobic fermentation process of *Prunus cerasifera* lactic acid bacteria fermentation products.

[0229] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A method for quality control during the production of a Ficus suavissima probiotic product, characterized by: Includes the following steps: During the fermentation of *Prunus pubescens* lactic acid bacteria fermented products in a fermenter, a lactic acid concentration time series was obtained. Based on the lactic acid concentration time series, a lactic acid production rate series was obtained, and the fermentation metabolic stage interval was determined according to the positive and negative changes in the lactic acid production rate value. The time series of colony formation units was obtained, and the data within the time series of colony formation units were matched and segmented according to the fermentation and metabolic stage intervals to form colony formation unit subsequences. The total stage fluctuation was obtained and analyzed based on the data within the colony formation unit subsequences to determine the fluctuation range of the microbial community. Obtain the time series of anaerobic state parameters, obtain the anaerobic deviation intensity series based on the anaerobic state parameter time series, segment the anaerobic deviation intensity series according to the fermentation metabolic stage interval and obtain the total anaerobic deviation of each stage, and determine the anaerobic deviation interval based on the total anaerobic deviation of each stage. The fermentation metabolism phase interval, microbial community fluctuation interval, and anaerobic deviation interval are aligned on the time axis. The start and end times of the negative rate phase interval, microbial community fluctuation interval, and anaerobic deviation interval are compared to screen out the quality control abnormal intervals. Based on the recorded results of the quality control abnormal intervals, anaerobic fermentation parameter regulation signals are generated.

2. The method for quality control in the process of preparing Ficus tikoua probiotic product according to claim 1, characterized in that: The process of obtaining the lactate concentration time series is as follows: Fermentation broth samples are obtained from the fermenter using an online sampling device according to a preset sampling cycle, and the corresponding sampling time points are recorded simultaneously. The fermentation broth sample was centrifuged, filtered, and the supernatant was processed and then sent to the lactic acid detection module. The lactate concentration value output by the lactate detection module is linked to the corresponding sampling time point, and then appended to the lactate concentration time series in chronological order of sampling time.

3. The method for quality control in the process of preparing Ficus tikoua probiotic product according to claim 2, characterized in that: The process of obtaining the lactate production rate sequence is as follows: The lactic acid production rate was determined by extracting the difference between adjacent sampling time points in the lactic acid concentration time series and combining it with the time interval between adjacent sampling time points. Each lactate production rate value is associated with its corresponding adjacent sampling time interval and appended to the lactate production rate sequence.

4. The method for quality control in the process of preparing Ficus tikoua probiotic product according to claim 3, characterized in that: The process of determining the fermentation metabolic phase interval is as follows: The fermentation metabolic phase interval includes a non-negative rate phase interval and a negative rate phase interval; Compare the lactic acid production rate value with a preset negative production rate tolerance threshold; If the lactic acid generation rate is greater than or equal to the preset negative generation rate tolerance threshold, then the corresponding adjacent sampling time interval will be marked as the non-negative rate time interval. If the lactic acid generation rate is less than the preset negative generation rate tolerance threshold, the corresponding adjacent sampling time interval will be marked as the negative rate time interval. After obtaining multiple non-negative rate time intervals and multiple negative rate time intervals, the multiple consecutive non-negative rate time intervals are merged into one non-negative rate stage interval, and the multiple consecutive negative rate time intervals are merged into one negative rate stage interval.

5. The method for quality control of a Ficus tikoua probiotic product preparation process according to claim 1, characterized in that: The process of obtaining the time series data of colony formation is as follows: Fermentation broth samples are obtained according to a preset colony counting sampling cycle. Colony formation unit (CFU) values ​​are obtained by counting the fermentation broth samples on culture medium plates. After establishing a relationship between the CFU values ​​and the corresponding colony counting sampling time points, a CFU time series is formed according to the chronological order of the colony counting sampling time points.

6. The quality control method for the preparation process of a five-finger peach probiotic product according to claim 5, characterized in that: The process of obtaining the microbial community fluctuation range is as follows: The colony-forming unit values ​​were matched to the fermentation and metabolic stage intervals according to the corresponding colony count sampling time points to form colony-forming unit subsequences. Within the same fermentation metabolic stage interval, the fluctuation of adjacent colony formation units is obtained and accumulated to obtain the total stage fluctuation. Compare the total fluctuation of the stage with the preset colony fluctuation threshold; If the total fluctuation of a stage exceeds the preset colony fluctuation threshold, the corresponding fermentation metabolism stage interval will be recorded as the colony fluctuation interval. If the total fluctuation of a stage is less than or equal to the preset colony fluctuation threshold, the corresponding fermentation metabolism stage interval will not be recorded as the colony fluctuation interval.

7. The quality control method for the preparation process of a five-finger peach probiotic product according to claim 1, characterized in that: The process of obtaining the anaerobic deviation intensity sequence is as follows: The redox potential value is obtained by setting a redox potential probe in the fermenter, and the redox potential value is linked with the corresponding anaerobic state detection time point. Then, the anaerobic state parameter time series is formed according to the chronological order of the anaerobic state detection time points. By using adjacent sampling time intervals corresponding to lactic acid production rate values ​​as time references, time matching is performed on the time series of anaerobic state parameters. Then, based on the extent and duration of the exceedance of redox potential values ​​relative to the preset upper limit threshold of anaerobic redox potential within adjacent sampling time intervals, the anaerobic deviation intensity value is determined to form an anaerobic deviation intensity sequence.

8. The quality control method in the preparation process of a five-finger peach probiotic product according to claim 7, characterized in that: The process of obtaining the anaerobic deviation range is as follows: The anaerobic deviation intensity sequence was segmented and arranged according to the fermentation metabolic stage interval to form the stage anaerobic deviation subsequence; The total anaerobic deviation is obtained by summing the anaerobic deviation intensity values ​​in the anaerobic deviation subsequences of each stage. Compare the total deviation of anaerobic phase with the preset anaerobic deviation threshold; If the total anaerobic deviation of a stage exceeds the preset anaerobic deviation threshold, the corresponding fermentation metabolic stage interval will be recorded as the anaerobic deviation interval. If the total anaerobic deviation of a stage is less than or equal to the preset anaerobic deviation threshold, the corresponding fermentation metabolic stage interval will not be recorded as an anaerobic deviation interval.

9. The quality control method in the preparation process of a five-finger peach probiotic product according to claim 1, characterized in that: The process of screening for quality control anomaly intervals is as follows: Map the negative rate phase interval, microbial community fluctuation interval, and anaerobic deviation interval to the same fermentation time axis; By comparing the start and end times of the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval, the common overlapping time period that is simultaneously within the negative rate phase interval, the microbial community fluctuation interval, and the anaerobic deviation interval and whose duration meets the preset minimum overlap duration threshold is selected as the quality control abnormal interval.

10. The quality control method in the preparation process of a five-finger peach probiotic product according to claim 9, characterized in that: The process of generating anaerobic fermentation parameter control signals is as follows: Based on the total stage fluctuation, total stage anaerobic deviation, preset colony fluctuation threshold, preset anaerobic deviation threshold, and corresponding negative rate stage interval corresponding to the quality control abnormal interval, at least one control signal is generated, including inert gas replacement, tank sealing detection, maintenance of micro-positive pressure inside the tank, adjustment of stirring intensity, adjustment of fermentation temperature, or adjustment of pH control range.

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