Tea fertilizer preparation method based on microbial fermentation

Abstract

The invention discloses a tea fertilizer preparation method based on microbial fermentation, and particularly relates to the field of tea compost, tea waste is crushed and wetted, and a nitrogen source and trace elements are added to optimize the carbon nitrogen ratio, so that a foundation is laid for the fermentation process; then, selected microbial strains are proliferated and purified, and the treated waste materials are uniformly inoculated with the selected microbial strains; in the fermentation process, the stability of fermentation conditions is ensured by controlling the temperature and the humidity; the tannin concentration and the pH value are monitored in real time, when the tannin concentration exceeds a preset value and the pH deviates from a normal range, the abnormal state of tannin degradation is evaluated and identified through a reaction activity index, an interference source is positioned through a sparse principal component analysis algorithm, and noise signals are removed; and after the interference source is positioned, the fermentation condition is adjusted in a targeted manner, so that the tannin degradation efficiency reaches the expectation, and the compost is maturely fermented and meets the fertilizer use standard.

Description

Technical Field

[0001] The invention relates to the technical field of tea composting, and more specifically to a method for preparing tea fertilizer based on microbial fermentation. Background Art

[0002] In the application of tea waste composting fermentation, the existing technology mainly relies on the microbial decomposition process. However, due to the complex composition of tea, especially the presence of tannins, cellulose and other substances that are difficult to decompose, the degradation efficiency during the fermentation process is often limited, and it is difficult to obtain the ideal fertilizer quality. In addition, the activity of microorganisms during the composting fermentation process is easily affected by environmental factors, especially the accumulation of acidic products, changes in metal ion concentrations and other factors, which may further inhibit the decomposition efficiency of microorganisms. Therefore, how to effectively control the key parameters in the fermentation process and avoid the interference factors in the environment from affecting the fermentation effect is a problem that needs to be solved in the current technical field.

[0003] However, existing methods have limitations in identifying the mutual interference between tannins and metabolites during the fermentation process. They fail to accurately locate the source of interference, resulting in untimely reaction adjustment and abnormal fluctuations in the fermentation process. This defect manifests itself in actual use as unstable fermentation effects and inconsistent product quality during fertilizer preparation, affecting the practicality and commercial value of the fertilizer. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for preparing tea fertilizer based on microbial fermentation. Through real-time monitoring and analysis, the interference sources of tannins and metabolites in the fermentation process are identified, and the fermentation conditions are adjusted to ensure the stable quality of the fertilizer, thereby solving the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for preparing tea fertilizer based on microbial fermentation, comprising:

[0006] Before fermentation, the tea waste is pulverized, water is added to moisten it, and nitrogen sources and trace elements are added according to a preset ratio to optimize the carbon-nitrogen ratio of the tea waste;

[0007] Selecting a microbial strain for decomposing tea waste, purifying and proliferating the microbial strain; after the strain is prepared, inoculating the strain into the treated tea waste and mixing;

[0008] After fermentation begins, the temperature and humidity of the fermentation pile are maintained according to the preset values ​​of temperature and humidity;

[0009] During the fermentation of tea piles, the tannin concentration and the pile fermentation liquid are monitored in real time. When the tannin concentration in the tea fermentation pile is higher than the preset tannin concentration threshold, and the pH value of the pile fermentation liquid deviates from the preset pH value range threshold, it is determined to be an abnormal state of tannin decomposition; otherwise, it is a normal state;

[0010] When the tannin decomposition is in an abnormal state, the reaction activity information is obtained, and a reaction activity index is established based on the reaction activity information. The reaction activity index is used to evaluate whether the degradation efficiency of tannins in the fermentation process meets expectations; when the reaction activity index result does not meet the set threshold range, the current state is determined to be a preliminary warning state of the reaction interference between tannins and metabolites; otherwise, it is a normal state;

[0011] After monitoring the initial warning state of the reaction interference between tannins and metabolites, the sparse principal component analysis algorithm is used to locate the source of the reaction interference. The sparse principal component analysis algorithm includes constructing an input data matrix, feature extraction, dimensionality reduction decomposition, sparse matrix weight construction, noise filtering, principal component screening and outputting interference source location results. The sparse principal component analysis algorithm separates the tannin signal from the metabolite signal and eliminates irrelevant noise components, thereby locating the source of the reaction interference.

[0012] After locating the source of reaction interference, adjust the fermentation conditions until the tannin degradation efficiency returns to the expected level, the pile fermentation matures, and meets the fertilizer usage standards.

[0013] In a preferred embodiment, when selecting microbial strains for decomposing tea waste, an inoculation ratio R is set. 菌种 is the mass ratio of microorganisms to waste, which is used to calculate the amount of bacteria required for actual inoculation:

[0014]

[0015] Where R 菌种 M is the inoculation ratio, indicating the amount of bacteria required; 废料 represents the mass of tea waste after treatment; f is the inoculation coefficient, which is used to adjust the proliferation effect of microorganisms; C 菌种 It indicates the degradation capacity per unit strain;

[0016]

[0017] Among them A 微生物 Represents the activity coefficient of microorganisms; S 废料 Indicates the specific surface area of ​​the crushed tea waste; H 堆体 Indicates the actual humidity of the pile, H 理想 Indicates the ideal humidity of the pile, H 堆体 and H 理想 Adjust humidity through ratio; is the humidity adjustment item; T 环境 Indicates ambient temperature; C 废料 Indicates the carbon content in the waste; η 接触 is the contact efficiency, which indicates the contact affinity between tea waste and strains.

[0018] In a preferred embodiment, when the tannin decomposition is abnormal, the reaction activity information is obtained, and the reaction activity information includes the tannin degradation rate, the accumulation of acidic products, the conductivity change rate, and the redox potential fluctuation range; a reaction activity index is established based on the reaction activity information, and the reaction activity index is used to evaluate whether the degradation efficiency of tannin in the fermentation process reaches the expectation;

[0019] The proposed tannin degradation rate is V tan The tannin degradation rate is not only affected by the initial tannin concentration and time, but also by the microbial activity coefficient k mic and environmental adjustment factor k env To calculate the tannin degradation rate:

[0020]

[0021] where k mic represents the microbial activity coefficient; k env represents the environmental adjustment coefficient; T tan，初、 T tan，现 represent the initial concentration of tannin and the current concentration of tannin respectively; t 现 represents the current time, i.e. the time point at which the tannin degradation rate is measured; t 初 represents the initial time, i.e., the time point when the tannin degradation process begins;

[0022] The cumulative amount of acidic products is assumed to be Q acid , Q acid Reflects the total amount of acidic products produced by microbial metabolism during the fermentation process. The cumulative amount of acidic products is based on the diffusion coefficient of metabolites D met and the reaction rate constant k acid , tracking the diffusion and generation of acidic products in the pile:

[0023]

[0024] Where P acid (t) represents the concentration of acidic products, which changes with time; V pile is the total volume of the fermentation pile; D met k is the diffusion coefficient of metabolites, which indicates the diffusion capacity of acidic products in the pile; acid is the rate constant for the formation of acidic products, which is affected by microbial metabolism; t 現 Indicates the current time; t 初 Indicates the initial time; It indicates that as time goes by, the amount of acidic products in the pile decreases; dt is the time differential;

[0025] The proposed conductivity change rate is R σ , the conductivity change rate refers to the charge concentration ρ ion and environmental conductivity k cond , used to reflect the dynamic changes in ion concentration:

[0026]

[0027] where σ 现 Indicates the current conductivity; σ 初 represents the initial conductivity; k cond represents the environmental conduction coefficient, k cond Adjust with temperature and humidity; ρ ion represents the ion concentration, ρ ion Affected by the production of metabolites in the fermentation reaction; 初 Refers to the starting time point of conductivity measurement, that is, the reference time when the conductivity change rate is calculated; t 现 is the current time, that is, the current conductivity measurement time point monitored in real time during the fermentation process;

[0028] The proposed redox potential fluctuation amplitude is ΔE orp , the fluctuation amplitude of redox potential introduces the oxygen diffusion rate v O2 and the reduction metabolite generation coefficient k red , to capture changes in the redox environment:

[0029] ΔE orp =(E orp，最大 -E orp，最小 )·v O2 ·k red

[0030] Where E orp，最大 Indicates the maximum value of redox potential; E orp，最小 Indicates the minimum value of redox potential; v O2 Indicates the diffusion rate of oxygen, used to reflect the aerobic or anaerobic state of the pile; k red Represents the reduction metabolite formation coefficient.

[0031] In a preferred embodiment, the tannin degradation rate V tan , Cumulative amount of acidic products Q acid , conductivity change rate R σ and the redox potential fluctuation amplitude ΔE orp Constructing the Reactivity Index I react , Ireact Used to evaluate the degradation efficiency of tannins during fermentation and to warn of reaction interference:

[0032] I react =α·V tan -β·Q acid -γ·R σ -δ·ΔE orp

[0033] Where α, β, γ, and δ represent V tan , Q acid , R σ and ΔE orp The weight coefficient is used to balance the contribution of each parameter.

[0034] In a preferred embodiment, constructing the input data matrix includes: constructing an input data matrix X, the matrix X is used for sparse principal component analysis; the matrix X contains four parameters reflecting the interference source, and the four parameters reflecting the interference source are: volatile organic acid concentration C VOA , Tannin structural isomer ratio R isoT , pH fluctuation range ΔpH range and free metal ion conductivity change ΔEC metal ;

[0035]

[0036] Among them C VOA (t i ) represents the time point t i The volatile organic acid concentration measured at 1 ℃ indicates the cumulative effect of acidic metabolites; R isoT (t i ) represents the time point t i The ratio of tannin structural isomers generated at ΔpH indicates abnormal reaction pathways during tannin degradation; range (t i ) represents the time point t i The pH fluctuation range at that time is used to reflect the impact of acidic products on the environment; ΔEC metal (t i ) represents the time point t i The change in conductivity caused by the free metal ions during the reaction reflects the interference of the ion concentration fluctuation on the reaction.

[0037] Feature extraction includes: extracting features from the input data matrix X to amplify the changing characteristics of different parameters in the time series; feature extraction removes the baseline level of each parameter;

[0038]

[0039] Where X特征 Represents the data matrix after feature extraction, removing the average value of the data in order to highlight the characteristic changes of each parameter; represents the column mean matrix of X, representing the average level of each parameter;

[0040] Dimensionality reduction decomposition includes: the matrix X after feature extraction 特征 Dimensionality reduction is performed on the data to concentrate on retaining the characteristic information in the data. The purpose of dimensionality reduction is to reduce the dimension of the data while retaining the parameter change information.

[0041] X 降维 =X 特征 ·P

[0042] Where X 降维 represents the data matrix after dimensionality reduction; P represents the dimensionality reduction projection matrix;

[0043] Sparse matrix weight construction includes: using the reduced dimension matrix X 降维 Construct a sparse matrix weight W; the sparse matrix weight is used to identify the contribution of different parameters to interference, and the key parameters are highlighted by setting the sparsity;

[0044]

[0045] Where W represents the sparse matrix weight, which is used to characterize the interference feature weight of each parameter; S represents the sparse principal component matrix; ∥·∥ F Represents the Frobenius norm, which is used to calculate the reconstruction error of the matrix; ∥·∥ 1 Indicates L 1 norm, used to control the sparsity of W so that the matrix retains non-zero elements; λ represents the sparsity adjustment parameter, used to control sparsity;

[0046] Noise filtering includes: performing noise filtering on the sparse principal component matrix S to remove noise signals and obtain principal component signals;

[0047] S 滤波 =S-σ(E)

[0048] Where S 滤波 represents the principal component matrix after noise filtering; σ(E) represents the noise estimation matrix, which is obtained by deviation calculation;

[0049] Principal component screening includes: filtering the principal component matrix S from the noise 滤波 Screen out the components that affect tannin degradation; locate the interference signals through screening;

[0050] S 关键 = argmax k (S 滤波

[0051] Where S 关键 represents the key principal component matrix, retaining the signals related to the interference sources of tannin degradation; argmax k It means selecting the principal component signal whose first k values ​​have a significant proportion in the data range;

[0052] The output interference source positioning results include: the key principal component matrix S selected by analysis 关键 , output interference source, through S 关键 The fluctuation and change trend analysis can identify the interference sources that lead to abnormal tannin degradation.

[0053] In a preferred embodiment, according to the results of locating the reaction interference source, if the volatile organic acid concentration C VOA If the pH value is higher than the preset value, it indicates that the accumulation of acidic metabolites has disturbed the fermentation environment, resulting in a decrease in microbial activity. Therefore, alkaline neutralizers can be gradually added to reduce the impact of acidic metabolites and adjust the pH value to the ideal range.

[0054] The adjustment formula is as follows:

[0055] pH 调整 =pH 当前 +α·C 中和

[0056] pH 调整 Indicates the adjusted pH value to ensure that the fermentation pile returns to the target acid-base balance; pH 当前 Indicates the current pH value of the pile; α indicates the adjustment coefficient, which is used to control the amount of neutralizer added; C 中和 Indicates the concentration of alkaline regulator added to neutralize acidic metabolites;

[0057] According to the results of the location of the reaction interference source, if the ratio of tannin structural isomers R isoT The increase indicates that a non-ideal reaction path occurs during the tannin degradation process, indicating that the oxygen supply is insufficient, resulting in an abnormal tannin degradation path. Therefore, by increasing the oxygen flow rate and optimizing the oxygen supply to the fermentation pile, the aerobic metabolic efficiency of microorganisms can be improved, thereby promoting the degradation of tannins.

[0058] The adjustment formula is as follows:

[0059] O 2 =O 2 +β·ΔO 2

[0060] Among them, 2 Indicates the current oxygen flow rate; β indicates the oxygen flow rate adjustment coefficient; ΔO 2 Indicates the amount of oxygen that needs to be increased calculated based on the interference source positioning result;

[0061] In interference source analysis, if pH fluctuation amplitude ΔpH is detected range If the pH value exceeds the preset range, it indicates that there is unstable acid-base fluctuation in the fermentation process, which will inhibit the degradation activity of microorganisms. Therefore, the amount of buffer added is increased to stabilize the acid-base balance in the fermentation pile and keep the pH fluctuation within the preset range.

[0062] The adjustment formula is as follows:

[0063] ΔpH 调整 =ΔpH 当前 -γ·C 缓冲剂

[0064] Where ΔpH 调整 Indicates the pH fluctuation range after adjustment; ΔpH 当前 represents the current pH fluctuation amplitude; γ represents the buffer adjustment coefficient, which is used to control the amount of buffer added; C 缓冲剂 Indicates the concentration of buffer added to stabilize pH fluctuations;

[0065] If the conductivity of free metal ions changes by ΔEC metal Abnormal increase indicates that the accumulation of metal ions has an inhibitory effect on the activity of microorganisms; in this case, chelating agents are added to bind excess free metal ions, thereby reducing the interference of metal ions and restoring the normal activity of microorganisms;

[0066] The adjustment formula is as follows:

[0067] ΔEC 调整 =ΔEC 当前 -δ·C 螯合剂

[0068] Where ΔEC 调整 represents the adjusted conductivity change; ΔEC 当前 Indicates the current conductivity change; δ indicates the chelating agent adjustment coefficient, which is used to control the amount of chelating agent added; C 螯合剂 It indicates the concentration of chelating agent added to bind free metal ions;

[0069] After the adjustment is completed, the tannin degradation rate R in the pile is continuously monitored. 降解 , so that it can gradually return to the expected target, R 降解 Used to determine whether the fermentation of the pile has reached the maturity standard; reached the set degradation threshold R 目标 After that, it indicates that the decomposition of tannins in the pile has reached an ideal state, and fermentation is progressing smoothly.

[0070] The formula is as follows:

[0071] R 降解 ≥R 目标

[0072] Where R 降解 represents the current tannin degradation rate; R 目标 It indicates the set target value of tannin degradation rate, ensuring that the degradation efficiency of tannin reaches the fertilizer use standard; by confirming that the fermentation adjustment has reached the target conditions, it indicates that the maturity of the pile fermentation has reached the fertilizer use standard.

[0073] Technical effects and advantages of the present invention:

[0074] 1. By monitoring and controlling the reaction activity index during tannin degradation, the abnormal state of tannin decomposition can be effectively identified, and the fermentation conditions can be adjusted in time to ensure that the fermentation process is stable and efficient. When this function is actually implemented, a comprehensive multi-dimensional monitoring system can be established to track the changes in key chemical parameters in real time during the composting process, avoid the accumulation of interference factors in the tannin decomposition process that affect the microbial activity, and achieve the improvement of fertilizer quality.

[0075] 2. The sparse principal component analysis algorithm is used to separate interference source signals, effectively separate tannin signals from metabolite signals, avoid the influence of irrelevant factors on degradation efficiency, eliminate noise data through feature extraction and dimensionality reduction, accurately locate interference sources that cause abnormal degradation, and provide technical support for refined management of the fermentation process to ensure effective degradation of tannins.

[0076] 3. Construct a parameter matrix based on volatile organic acid concentration, tannin structural isomer ratio, pH fluctuation amplitude and free metal ion conductivity changes to make the location of reaction interference sources more accurate; through real-time monitoring and algorithm analysis of these key parameters, abnormal changes in the fermentation environment can be dynamically identified, effectively supporting the stability and consistency of the fertilizer preparation process;

[0077] 4. A reaction activity index was proposed and applied to comprehensively evaluate the degradation efficiency of tannins. By integrating multiple parameters such as tannin degradation rate, acid product accumulation, conductivity change rate, redox potential fluctuation range, etc., it can sensitively monitor the dynamic changes of the fermentation environment, timely warn of possible interference, and ensure that the fermentation environment is in the optimal state;

[0078] 5. A quantitative feedback regulation mechanism is introduced to adjust key factors such as oxygen flow, pH value and chelating agent concentration based on real-time monitoring results and interference source location results to ensure the activity of microorganisms and the decomposition efficiency of tannins; this mechanism makes the preparation of fertilizers more convenient and improves the stability and reliability of the fermentation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0080] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] Refer to the instruction manual Figure 1 A method for preparing tea fertilizer based on microbial fermentation according to an embodiment of the present invention comprises:

[0082] Before fermentation, the tea waste is crushed, and a proper amount of water is added to moisten it. Nitrogen sources and trace elements are added according to a preset ratio to optimize the carbon-nitrogen ratio of the tea waste, providing an ideal environment for the activity of microorganisms.

[0083] Selecting microbial strains for decomposing tea waste, purifying and proliferating the microbial strains; after the strains are prepared, inoculating the strains into the treated tea waste and mixing them to ensure full contact and fermentation efficiency of the bacterial flora, ensuring that the inoculated waste is evenly mixed, so as to promote uniform reproduction of microorganisms and full fermentation reaction of the waste, and create a good environment for the next fermentation reaction; the microorganisms commonly used for tea waste include specific cellulose decomposing bacteria, polyphenol degrading bacteria and amino acid metabolizing bacteria, etc., which can effectively decompose cellulose, lignin and tannin components in tea waste;

[0084] After fermentation begins, the temperature and humidity of the fermentation pile are maintained according to the preset values ​​of temperature and humidity. The fermentation temperature usually needs to be controlled within a specific range to keep the microbial activity efficient. The humidity should be adjusted within a specific range. The humidity is controlled by turning the pile and spraying water to make the pile moist but not too wet or waterlogged. Waterlogging will cause the pile to become sticky and corrupt. To ensure the uniformity of fermentation, the pile can be turned regularly, which not only helps to evenly distribute the temperature and humidity, but also enhances the ventilation effect of the pile, so that the microorganisms in the pile are adequately supplied with oxygen and promote aerobic fermentation.

[0085] During the fermentation of tea piles, the tannin concentration and the pile fermentation liquid are monitored in real time. When the tannin concentration in the tea fermentation pile is higher than the preset tannin concentration threshold and the pH value of the pile fermentation liquid deviates from the preset pH value range threshold, it is determined to be an abnormal state of tannin decomposition; otherwise, it is a normal state. In addition, this condition is judged in order to timely identify abnormal conditions of tannin decomposition during the fermentation process. By monitoring the tannin concentration and the pH value of the pile fermentation liquid, when the tannin concentration exceeds the preset threshold and the pH value deviates from the normal range, the abnormal state of the tannin decomposition process can be quickly determined, so as to adjust the fermentation conditions in time to avoid unfavorable fermentation results.

[0086] When the tannin decomposition is in an abnormal state, the reaction activity information is obtained, and a reaction activity index is established based on the reaction activity information. The reaction activity index is used to evaluate whether the degradation efficiency of tannins in the fermentation process meets expectations; when the reaction activity index result does not meet the set threshold range, the current state is determined to be a preliminary warning state of the reaction interference between tannins and metabolites; otherwise, it is a normal state;

[0087] After monitoring the initial warning state of the reaction interference between tannins and metabolites, the sparse principal component analysis algorithm is used to locate the source of the reaction interference. The sparse principal component analysis algorithm includes constructing an input data matrix, feature extraction, dimensionality reduction decomposition, sparse matrix weight construction, noise filtering, principal component screening and outputting interference source positioning results. The sparse principal component analysis algorithm separates the tannin signal from the metabolite signal and removes irrelevant noise components, thereby locating the source of the reaction interference. It should be noted that the reaction activity index can be used to preliminarily evaluate the degradation efficiency of tannins in the fermentation process and determine whether it meets the expected standard. If it does not reach the set threshold, it indicates that there may be tannin degradation. The interference between tannin and metabolites is an early warning of potential problems. In order to deeply analyze the source of interference, the sparse principal component analysis algorithm is further introduced. This algorithm can perform feature extraction, dimensionality reduction and noise filtering on complex multi-dimensional data, separate tannin signals from metabolite signals, and thus clarify the specific source of interference signals. Through sparse principal component analysis, the most interfering components can be effectively screened out, helping to locate the specific interference source, thereby providing an accurate basis for the subsequent adjustment of fermentation conditions. The reason why this method is applicable is that the sparse principal component analysis algorithm can remove redundancy while maintaining the main information, ensuring the accuracy and reliability of the positioning results;

[0088] After locating the source of reaction interference, adjust the fermentation conditions until the tannin degradation efficiency returns to the expected level, the pile fermentation matures, and meets the fertilizer usage standards.

[0089] When selecting microbial strains for decomposing tea waste, the inoculation ratio R 菌种 is the mass ratio of microorganisms to waste, which is used to calculate the amount of bacteria required for actual inoculation:

[0090]

[0091] Where R 菌种 M is the inoculation ratio, indicating the amount of bacteria required; 废料 represents the mass of tea waste after treatment; f is the inoculation coefficient, which is used to adjust the proliferation effect of microorganisms; C 菌种 It indicates the degradation capacity per unit strain;

[0092]

[0093] Among them A 微生物 It represents the activity coefficient of microorganisms, that is, the proliferation efficiency of bacteria under the current temperature and humidity; S 废料 It represents the specific surface area of ​​the crushed tea waste, that is, the total surface area on which microorganisms can attach after crushing. The finer the particles, the larger the surface area that microorganisms can contact, and the greater the inoculation coefficient. 堆体 Indicates the actual humidity of the pile, H 理想 Indicates the ideal humidity of the pile, H 堆体 and H 理想 Adjust humidity through ratio; is the humidity adjustment item, which means that the closer the pile humidity is to the ideal value, the more active the microorganisms are and the better the inoculation effect is; T 环境 Indicates the ambient temperature. Suitable temperature can promote the activity and reproduction rate of microorganisms; C 废料 Indicates the carbon content in the waste, which is used to control the nutrient concentration. Too much carbon may hinder the proliferation of microorganisms, so the inoculation coefficient needs to be lowered; η 接触 The contact efficiency indicates the contact affinity between tea waste and the strain. If the waste surface and the strain are not easy to contact, the inoculation coefficient will become smaller.

[0094] When the tannin decomposition is abnormal, the reaction activity information is obtained, including the tannin degradation rate, the accumulation of acidic products, the conductivity change rate, and the redox potential fluctuation range; a reaction activity index is established based on the reaction activity information, and the reaction activity index is used to evaluate whether the degradation efficiency of tannin in the fermentation process meets expectations;

[0095] The proposed tannin degradation rate is V tan The tannin degradation rate is not only affected by the initial tannin concentration and time, but also by the microbial activity coefficient k mic and environmental adjustment factor k env To calculate the tannin degradation rate:

[0096]

[0097] where k micrepresents the microbial activity coefficient, k mic It is related to the growth stage of microorganisms and ranges from 0 to 1, indicating different levels of microbial activity; k env Represents the environmental adjustment coefficient, which changes dynamically according to fermentation conditions such as temperature and humidity; t 现 represents the current time, i.e. the time point at which the tannin degradation rate is measured; t 初 represents the initial time, i.e. the time point when the tannin degradation process begins; T tan,初、 T tan,现 represent the initial concentration of tannin and the current concentration of tannin respectively. By introducing the microbial activity coefficient k mic and environmental adjustment factor k env , this formula can better reflect the tannin degradation rate under different fermentation environmental conditions, among which the microbial activity coefficient and the environmental regulation coefficient can affect the tannin degradation efficiency from two aspects: the microbial growth state and the fermentation environmental conditions. The microbial activity coefficient can be derived from the growth curve of the microorganism, and the value reflects the activity of the microorganism in the fermentation process. It usually reaches a peak when the microorganism enters the rapid reproduction period, and then gradually decreases when it enters the stable period. This coefficient can be comprehensively determined based on the biomass data, microbial community composition and its metabolite generation rate in the fermentation. The environmental regulation coefficient is generated based on the real-time monitoring values ​​of fermentation conditions such as temperature, humidity, and oxygen concentration, reflecting the impact of environmental conditions on microbial activity and tannin degradation. The closer the environmental conditions are to the optimal range of the microorganism, the higher the coefficient, thereby amplifying the degradation effect of the microorganism on tannin.

[0098] The cumulative amount of acidic products is assumed to be Q acid , Q acid Reflects the total amount of acidic products generated by microbial metabolism during the fermentation process; these acidic products may include metabolites such as organic acids. Excessive accumulation will affect the pH balance of the pile, thereby inhibiting the activity of microorganisms and the degradation efficiency of tannins. In order to more accurately calculate the accumulation of these products, the accumulation of acidic products is based on the diffusion coefficient of metabolites D met and the reaction rate constant k acid , tracking the diffusion and generation of acidic products in the pile:

[0099]

[0100] Where P acid (t) represents the concentration of acid products, which changes with time. The generation and accumulation of acid products are directly related to the metabolic intensity of microorganisms. acid (t) can be obtained by chemical analysis or online monitoring equipment, which is the core basis for the accumulation of acidic products; V pileThe total volume of the fermentation pile will affect the distribution of metabolites and the acid-base balance of the pile environment. A larger pile volume will often lead to more extensive accumulation of acidic products and diffusion inside the pile, which will more easily affect the overall pH value of the pile. met k is the diffusion coefficient of metabolites, which indicates the diffusion capacity of acidic products in the pile. The value of the diffusion coefficient depends on the physical structure, temperature, humidity and other conditions of the pile. A higher diffusion coefficient means that the acidic products diffuse faster in the pile, which may lead to more uniform changes in local acidity, but it may also cause acid accumulation to affect microbial activities in a larger range. acid k is the rate constant for acid product formation, which is affected by microbial metabolism and reflects the activity of a specific microorganism in generating acid products under the current fermentation conditions. acid The value indicates that the microorganisms metabolize faster and the accumulation of acid products increases faster. acid At the same time, environmental factors such as temperature and pH in the pile are taken into consideration, so its value will be dynamically adjusted according to the fermentation conditions; the accumulated amount of acidic products Q acid By comprehensively considering the diffusion and reaction rate of metabolites, the accumulation of acidic products is made more dynamic, which is suitable for the generation and accumulation analysis of acidic products in different fermentation processes; 現 Indicates the current time, t 現 The current time point represents the end time of the accumulation calculation, that is, the latest data of the acid product concentration, diffusion and generation rate observed during the calculation; t 初 represents the initial time, t 初 It is the starting time point of acid product accumulation, that is, the time point when the fermentation process starts or the monitoring starts. 現 and t 初 The time difference can monitor the dynamic changes of acid products during the fermentation process and reflect the accumulation of acid products in the middle or late stage of fermentation. It indicates that as time goes by, the acidic products in the pile may decrease due to other reactions, such as being slowly neutralized by alkaline products. The process of partial digestion or inhibition of acid products during a long period of accumulation is simulated, which helps to more realistically reflect the dynamic changes of acid products in the pile; dt is the time differential, which represents a small change in time and is used for integration operations to obtain the cumulative contribution of acid products in each small time interval; this formula integrates multiple factors such as the concentration of acid products, the volume of the fermentation pile, the diffusion coefficient and the generation rate through integration and accumulation to obtain a total amount of acid products that changes with time. The change of each parameter will affect the accumulation rate and magnitude of the acid products. This accumulation is the core indicator for subsequent judgment of the acid level of the fermentation environment and the interference of tannin degradation;

[0101] The proposed conductivity change rate is R σ , the conductivity change rate refers to the charge concentration ρ ion and environmental conductivity k cond , used to reflect the dynamic changes in ion concentration:

[0102]

[0103] where σ 现 Indicates the current conductivity; σ 初 represents the initial conductivity; k cond represents the environmental conduction coefficient, k cond Adjust with temperature and humidity; ρ ion represents the ion concentration, ρ ion Affected by the production of metabolites in the fermentation reaction; 初 Refers to the starting time point of conductivity measurement, that is, the reference time when the conductivity change rate is calculated; t 现 is the current time, that is, the current conductivity measurement time point monitored in real time during the fermentation process; the conductivity change rate is used to measure the dynamic change of ion concentration in the pile, and is calculated by dividing the difference between the current and initial conductivity by the time difference. In order to more accurately reflect the fluctuation of conductivity, this change rate also takes into account the influence of environmental conductivity coefficient and ion concentration. The environmental conductivity coefficient depends on the temperature and humidity conditions and can dynamically adjust the change range of conductivity; the ion concentration reflects the amount of metabolites produced during the fermentation process, especially the generation of acidic metabolites. Overall, the conductivity change rate combines the initial value and real-time measurement value of conductivity, environmental characteristics, and ion generation, providing a sensitive indicator for judging whether metabolites have accumulated to a degree that may affect the decomposition of tannins during the fermentation process;

[0104] The proposed redox potential fluctuation amplitude is ΔE orp , the fluctuation amplitude of redox potential introduces the oxygen diffusion rate v O2 and the reduction metabolite generation coefficient k red , to capture changes in the redox environment:

[0105] ΔE orp =(E orp,最大 -E orp,最小 )·v O2 ·k red

[0106] Where E orp,最大 Indicates the maximum value of redox potential; E orp,最小 Indicates the minimum value of redox potential; v O2 Indicates the diffusion rate of oxygen, used to reflect the aerobic or anaerobic state of the pile; k redrepresents the reduction metabolite generation coefficient, k red It is related to the amount of reducing compounds produced during fermentation. The formula for the fluctuation amplitude of the redox potential describes the fluctuation amplitude of the redox environment through the oxygen diffusion rate and the generation coefficient of reducing metabolites, which is convenient for capturing abnormal changes in fermentation conditions. The fluctuation amplitude of the redox potential is used to measure the stability and range of changes of the redox environment during the fermentation process of the pile, and to help determine whether the environmental conditions are suitable for the degradation of tannins. By observing the difference between the highest and lowest values ​​of the redox potential in a specific time period, the fluctuation amplitude can reflect the changes in oxygen and reducing metabolites during the fermentation process. If the oxygen diffusion rate is high, the oxidative environment of the fermentation pile will be relatively stable and suitable for the aerobic activity of microorganisms. The generation of reducing metabolites will increase the reducing reaction, resulting in a redox potential. When the fluctuation amplitude is large, it means that the environmental redox state is unstable, and this instability may inhibit the effective degradation of tannins by microorganisms; in addition, the oxygen diffusion rate and the reduction metabolite generation coefficient are formed according to the environmental dynamic characteristics of the fermentation pile; the oxygen diffusion rate depends on factors such as the ventilation conditions, temperature and humidity of the pile, reflecting the oxygen transfer efficiency in the pile; a higher oxygen diffusion rate helps to maintain the oxidative environment of the pile; the reduction metabolite generation coefficient is determined by the metabolic activity of the microorganisms, and is affected by the fermentation process, the carbon-nitrogen ratio of the pile and the type of microorganisms; this coefficient is used to quantify the generation rate of reducing substances; the combination of the two forms the key regulating factor for the fluctuation of the redox potential, which is used to capture the amplitude of changes in the oxidation and reduction states in the pile.

[0107] Tannin degradation rate V tan , Cumulative amount of acidic products Q acid , conductivity change rate R σ and the redox potential fluctuation amplitude ΔE orp Constructing the Reactivity Index I react , I react Used to evaluate the degradation efficiency of tannins during fermentation and to warn of reaction interference:

[0108] I react =α·V tan -β·Q acid -γ·R σ -δ·ΔE orp

[0109] Where α, β, γ, and δ represent V tan , Q acid , R σ and ΔE orpThe weight coefficient is used to balance the contribution of each parameter; the reaction activity index integrates the tannin degradation rate, the accumulation of acidic products, the conductivity change rate and the redox potential fluctuation range to reflect the degradation status of tannin in multiple dimensions; the reaction activity index is a multi-dimensional parameter for comprehensively evaluating the tannin degradation efficiency. By integrating four parameters, it reflects the actual state of tannin degradation during the fermentation process; the setting of each coefficient refers to the key factors in the fermentation system: the coefficient of tannin degradation rate measures the direct contribution of microbial activity to tannin consumption; the coefficient of acidic product accumulation is mainly used to balance the inhibitory effect of acidic metabolites on microbial growth; the coefficient of conductivity change rate characterizes the stabilizing effect of changes in ion concentration in the pile on the fermentation environment; and the coefficient of redox potential fluctuation range focuses on the balance between the aerobic and anaerobic environments of the fermentation pile. The setting of these coefficients enables the reaction activity index to dynamically adapt to different fermentation stages and provide accurate guidance for judging the degradation efficiency of tannins;

[0110] In addition, the reaction activity index can warn of reaction interference because it integrates the dynamic changes of various key factors in the fermentation process and can identify abnormal signals in the tannin degradation process; these abnormal signals may reflect weakened microbial activity, excessive accumulation of acidic products, drastic fluctuations in ion concentration or unstable redox environment, indicating that the fermentation environment is disturbed; specific interference types include pH imbalance caused by excessive accumulation of acidic metabolites, unexpected chemical reactions between tannins and certain metabolites, ion accumulation interference represented by increased conductivity, and microbial activity decline caused by redox potential fluctuations; these interferences will lead to reduced tannin degradation efficiency, delayed fermentation process or imbalance in the fermentation pile environment; therefore, by monitoring the reaction activity index, adverse signals can be captured at the early stage of interference, providing necessary warnings for timely adjustment of fermentation conditions and restoration of tannin degradation process.

[0111] Constructing the input data matrix includes: constructing the input data matrix X, X is the basic data structure of the algorithm, and the matrix X is used for sparse principal component analysis. Each column of the matrix X represents a key parameter, and each row represents a time point, which aims to capture the changes of different parameters in the time series, so as to facilitate the subsequent algorithm to extract the main interference features; the matrix X contains four parameters reflecting the interference source, which are: volatile organic acid concentration C VOA , Tannin structural isomer ratio R isoT , pH fluctuation range ΔpH range and free metal ion conductivity change ΔEC metal ;These parameters are used to reveal abnormal changes in the fermentation process from different dimensions;

[0112]

[0113] Among them CVOA (t i ) represents the time point t i The volatile organic acid concentration measured at 1 ℃ indicates the cumulative effect of acidic metabolites; R isoT (t i ) represents the time point t i The ratio of tannin structural isomers generated at ΔpH indicates possible abnormal reaction pathways during tannin degradation; range (t i ) represents the time point t i The pH fluctuation range at that time is used to reflect the impact of acidic products on the environment; ΔEC metal (t i ) represents the time point t i The conductivity changes caused by the free metal ions at different times reflect the interference of ion concentration fluctuations on the reaction; this matrix provides a basis for subsequent feature extraction by capturing the dynamic changes of these parameters;

[0114] Feature extraction includes: extracting features from the input data matrix X to remove the base level and amplify the changing characteristics of different parameters in the time series; feature extraction removes the base level of each parameter, making the algorithm more sensitive to the fluctuation characteristics of the parameter rather than its absolute value;

[0115]

[0116] Where X 特征 Represents the data matrix after feature extraction, removing the average value of the data in order to highlight the characteristic changes of each parameter; The column mean matrix of X represents the average level of each parameter. By removing the average value, the dynamic change characteristics of each parameter are retained. The subsequent steps will further analyze the key signals based on this matrix.

[0117] Dimensionality reduction decomposition includes: the matrix X after feature extraction 特征 Dimensionality reduction is performed on the data to concentrate on retaining the most important feature information in the data. The purpose of dimensionality reduction is to reduce the dimension of the data while retaining important parameter change information and avoiding interference from irrelevant information in the data.

[0118] X 降维 =X 特征 ·P

[0119] Where X 降维 It represents the data matrix after dimensionality reduction, which contains the main information components in the data. P represents the dimensionality reduction projection matrix, which is used to project high-dimensional data into low-dimensional space and retain the principal components. Dimensionality reduction simplifies the data dimension and retains the components that have the greatest impact on the interference source, ensuring that the sparse principal component analysis can focus on the core interference signal.

[0120] Sparse matrix weight construction includes: using the reduced dimension matrix X 降维 Construct a sparse matrix weight W; the sparse matrix weight is used to identify the contribution of different parameters to interference, and the key parameters are highlighted by setting the sparsity to eliminate the influence of low-contribution parameters;

[0121]

[0122] Where W represents the sparse matrix weight, which is used to characterize the interference feature weight of each parameter; S represents the sparse principal component matrix, which contains the main interference feature signals; ∥·∥ F Represents the Frobenius norm, which is used to calculate the reconstruction error of the matrix; ∥·∥ 1 Indicates L 1 norm, which is used to control the sparsity of W so that the matrix retains a small number of non-zero elements; λ represents the sparsity adjustment parameter, which is used to control sparsity and ensure that W highlights the features that have the greatest impact on the interference source; by constructing a sparse matrix, the key features of the interference source are extracted, the impact of minor components is reduced, and the subsequent steps are more focused on the core signal; Represents finding the W value that minimizes the objective function value so as to reconstruct the error and the sparsity constraint term λ||W|| 1 Achieve a balance between That is to say, by adjusting W, the entire expression is minimized;

[0123] Noise filtering includes: performing noise filtering on the sparse principal component matrix S to remove noise signals and obtain a purer principal component signal; noise filtering removes high-volatility components in the signal to retain the core interference information;

[0124] S 滤波 =S-σ(E)

[0125] Where S 滤波 represents the principal component matrix after noise filtering, which retains the main components of the interference source; σ(E) represents the noise estimation matrix, which is obtained by deviation calculation to eliminate irrelevant noise signals; through noise filtering, the main signals of interference are retained to ensure that the features screened out next are more accurate and interference-free;

[0126] Principal component screening includes: filtering the principal component matrix S from the noise 滤波 The key principal components that affect tannin degradation are screened out; by screening, the principal components with larger values ​​are focused on, thereby locating the main interference signals;

[0127] S 关键 = argmax k (S 滤波 )

[0128] Where S 关键 represents the key principal component matrix, retaining the most relevant signals for the interference sources of tannin degradation; argmax k It means selecting the principal component signals whose first k values ​​have a significant proportion in the data range; the selected S 关键 Indicates the main components of interference sources, so that the final positioning focuses on the most influential signals;

[0129] The output interference source positioning results include: the key principal component matrix S selected by analysis 关键 , output the main interference source, through S 关键 The fluctuation and change trend analysis was carried out to identify the main interference sources leading to abnormal tannin degradation.

[0130] It should be noted that the main goal of the sparse principal component analysis algorithm is to separate and identify the specific sources that interfere with tannin degradation during the fermentation process through sparse principal component analysis, so as to help us find and solve the root causes of abnormal degradation. The specific steps are explained as follows:

[0131] First, the algorithm builds a data matrix containing the four parameters mentioned above, which reflect how different interference factors change over time. These four parameters include: the concentration of volatile organic acids, which is used to show the accumulation of acidic metabolites; the tannin structural isomer ratio refers to the ratio of different structural isomers formed during tannin degradation, which can indicate abnormalities in the tannin degradation pathway; the pH fluctuation amplitude, which is used to show changes in the acid-base balance during fermentation; and the conductivity changes of free metal ions, which reflects the impact of metal ion concentration on the fermentation reaction;

[0132] Next, through feature extraction, the algorithm will eliminate the baseline value in the data and only retain the dynamic changes of the parameters, thereby highlighting the interference characteristics in the signal; then dimensionality reduction processing is performed to retain the main information in the data in a lower-dimensional space, thereby more concentratedly retaining the information of important interference factors and reducing computational complexity;

[0133] The algorithm then builds a sparse matrix weight, which focuses the signal in the matrix on the interference sources that have the greatest impact on degradation by retaining only a few key interference factors; the algorithm then removes irrelevant signal parts through noise filtering to ensure that the final signal is as clean as possible, allowing us to identify interference more accurately;

[0134] Finally, the algorithm screens the main interfering components and selects signals with higher values, which represent the interfering factors that have the greatest impact on tannin degradation. Ultimately, through these steps, the algorithm can output the main sources of interference, allowing us to clearly see the factors that lead to abnormal degradation and provide precise directions for subsequent adjustments to fermentation conditions. The entire process helps us analyze and confirm interfering factors from multiple angles, ensuring that tannins can be degraded as expected and that the fermentation process is completed smoothly.

[0135] According to the results of the reaction interference source location, if the volatile organic acid concentration C VOA If the pH value is higher than the preset value, it indicates that the accumulation of acidic metabolites has disturbed the fermentation environment, resulting in a decrease in microbial activity. Therefore, alkaline neutralizers can be gradually added to reduce the impact of acidic metabolites and adjust the pH value to the ideal range.

[0136] The adjustment formula is as follows:

[0137] pH 调整 =pH 当前 +α·C 中和

[0138] pH 调整 Indicates the adjusted pH value to ensure that the fermentation pile returns to the target acid-base balance; pH 当前 Indicates the current pH value of the pile; α indicates the adjustment coefficient, which is used to control the amount of neutralizer added; C 中和 Indicates the concentration of alkaline regulator added to neutralize acidic metabolites; this step can adjust the acid-base balance to avoid inhibition of microbial activity due to too low pH value;

[0139] According to the results of the location of the reaction interference source, if the ratio of tannin structural isomers R isoT An increase in the oxygen flow rate indicates that a non-ideal reaction pathway has occurred during the tannin degradation process, which may include insufficient oxygen supply, resulting in abnormal tannin degradation pathways. Therefore, by increasing the oxygen flow rate and optimizing the oxygen supply to the fermentation pile, the aerobic metabolic efficiency of microorganisms can be improved, thereby promoting the effective degradation of tannins.

[0140] The adjustment formula is as follows:

[0141] O 2 =O 2 +β·ΔO 2

[0142] Among them, 2 Indicates the current oxygen flow rate; β indicates the oxygen flow rate adjustment coefficient, ensuring that the oxygen increase is appropriate; ΔO 2 It indicates the amount of oxygen that needs to be increased, calculated based on the interference source location results; this step can adjust the oxygen supply and optimize the microbial activity in fermentation, thereby restoring the normal degradation pathway of tannins;

[0143] In interference source analysis, if pH fluctuation amplitude ΔpH is detected range If the pH value exceeds the preset range, it indicates that there is unstable acid-base fluctuation in the fermentation process, which will inhibit the degradation activity of microorganisms. Therefore, the amount of buffer added is increased to stabilize the acid-base balance in the fermentation pile and keep the pH fluctuation within the preset range.

[0144] The adjustment formula is as follows:

[0145] ΔpH 调整 =ΔpH 当前 -γ·C 缓冲剂

[0146] Where ΔpH 调整 Indicates the pH fluctuation range after adjustment; ΔpH 当前 represents the current pH fluctuation amplitude; γ represents the buffer adjustment coefficient, which is used to control the amount of buffer added; C 缓冲剂 Indicates the concentration of the buffer added, which is intended to stabilize pH fluctuations. This step can reduce the impact of acid-base fluctuations on microorganisms, maintain the stability of the acid-base environment in the pile, and help the smooth degradation of tannins.

[0147] If the conductivity of free metal ions changes by ΔEC metal Abnormal increase indicates that the accumulation of metal ions has an inhibitory effect on the activity of microorganisms; in this case, chelating agents are added to bind excess free metal ions, thereby reducing the interference of metal ions and restoring the normal activity of microorganisms;

[0148] The adjustment formula is as follows:

[0149] ΔEC 调整 =ΔEC 当前 -δ·C 螯合剂

[0150] Where ΔEC 调整 represents the adjusted conductivity change; ΔEC 当前 Indicates the current conductivity change; δ indicates the chelating agent adjustment coefficient, which is used to control the amount of chelating agent added; C 螯合剂 Indicates the concentration of the chelating agent added to bind free metal ions; this step reduces the interference with microbial activity by reducing the concentration of metal ions, allowing the degradation activity in the fermentation process to proceed smoothly;

[0151] After the adjustment is completed, the tannin degradation rate R in the pile is continuously monitored. 降解 , so that it can gradually return to the expected target, R 降解 Used to determine whether the fermentation of the pile has reached the maturity standard; reached the set degradation threshold R 目标After that, it indicates that the decomposition of tannins in the pile has reached an ideal state, and fermentation is progressing smoothly.

[0152] The formula is as follows:

[0153] R 降解 ≥R 目标

[0154] Where R 降解 represents the current tannin degradation rate; R 目标 Indicates the set tannin degradation rate target value, ensuring that the tannin degradation efficiency reaches the fertilizer use standard; by confirming that the fermentation adjustment has reached the target conditions, it indicates that the maturity of the pile fermentation has reached the fertilizer use standard;

[0155] That is, after ensuring that the tannin degradation rate has returned to the expected level and other fermentation conditions have been adjusted to the optimal state, the final maturity confirmation is carried out; at this time, it is confirmed that the pile fermentation has been completed and the fertilizer has reached the usable standard, marking the end of the entire fermentation process and can be applied for actual fertilizer use.

[0156] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for preparing tea fertilizer based on microbial fermentation, characterized in that: include: Before fermentation, the tea waste is pulverized, water is added to moisten it, and nitrogen sources and trace elements are added according to a preset ratio to optimize the carbon-nitrogen ratio of the tea waste; Selecting microbial strains for decomposing tea waste, and purifying and proliferating the microbial strains; After the strains are prepared, the strains are inoculated into the treated tea waste and mixed; After fermentation begins, the temperature and humidity of the fermentation pile are maintained according to the preset values ​​of temperature and humidity; During the fermentation of tea piles, the tannin concentration and the pile fermentation liquid are monitored in real time. When the tannin concentration in the tea fermentation pile is higher than the preset tannin concentration threshold, and the pH value of the pile fermentation liquid deviates from the preset pH value range threshold, it is determined to be an abnormal state of tannin decomposition; otherwise, it is a normal state; When the tannin decomposition is in an abnormal state, the reaction activity information is obtained, and a reaction activity index is established based on the reaction activity information. The reaction activity index is used to evaluate whether the degradation efficiency of tannins in the fermentation process meets expectations; when the reaction activity index result does not meet the set threshold range, the current state is determined to be a preliminary warning state of the reaction interference between tannins and metabolites; Otherwise it is in normal state; After monitoring the initial warning state of the reaction interference between tannins and metabolites, the sparse principal component analysis algorithm is used to locate the source of the reaction interference. The sparse principal component analysis algorithm includes constructing an input data matrix, feature extraction, dimensionality reduction decomposition, sparse matrix weight construction, noise filtering, principal component screening and outputting interference source location results. The sparse principal component analysis algorithm separates the tannin signal from the metabolite signal and eliminates irrelevant noise components, thereby locating the source of the reaction interference. After locating the source of reaction interference, adjust the fermentation conditions until the tannin degradation efficiency returns to the expected level, the pile fermentation matures, and meets the fertilizer usage standards.

2. The method for preparing tea fertilizer based on microbial fermentation according to claim 1, characterized in that: When selecting microbial strains for decomposing tea waste, the inoculation ratio R 菌种 is the mass ratio of microorganisms to waste, which is used to calculate the amount of bacteria required for actual inoculation: Where R 菌种 M is the inoculation ratio, indicating the amount of bacteria required; 废料 represents the mass of tea waste after treatment; f is the inoculation coefficient, which is used to adjust the proliferation effect of microorganisms; C 菌种 It indicates the degradation capacity per unit strain; Among them A 微生物 Represents the activity coefficient of microorganisms; S 废料 Indicates the specific surface area of ​​the crushed tea waste; H 堆体 Indicates the actual humidity of the pile, H 理想 Indicates the ideal humidity of the pile, H 堆体 and H 理想 Adjust humidity through ratio; is the humidity adjustment item; T 环境 Indicates ambient temperature; C 废料 Indicates the carbon content in the waste; η 接触 is the contact efficiency, which indicates the contact affinity between tea waste and strains.

3. A method for preparing tea fertilizer based on microbial fermentation according to claim 2, characterized in that: When the tannin decomposition is abnormal, the reaction activity information is obtained, including the tannin degradation rate, the accumulation of acidic products, the conductivity change rate, and the redox potential fluctuation range; a reaction activity index is established based on the reaction activity information, and the reaction activity index is used to evaluate whether the degradation efficiency of tannin in the fermentation process meets expectations; The proposed tannin degradation rate is V tan The tannin degradation rate is not only affected by the initial tannin concentration and time, but also by the microbial activity coefficient k mic and environmental adjustment factor k env To calculate the tannin degradation rate: where k mic represents the microbial activity coefficient; k env represents the environmental adjustment coefficient; T tan，初、 T tan，现 represent the initial concentration of tannin and the current concentration of tannin respectively; t 现 represents the current time, i.e. the time point at which the tannin degradation rate is measured; t 初 represents the initial time, i.e., the time point when the tannin degradation process begins; The cumulative amount of acidic products is assumed to be Q acid , Q acid Reflects the total amount of acidic products produced by microbial metabolism during the fermentation process. The cumulative amount of acidic products is based on the diffusion coefficient of metabolites D met and the reaction rate constant k acid , tracking the diffusion and generation of acidic products in the pile: Where P acid t represents the concentration of acidic products, which changes with time; V pile is the total volume of the fermentation pile; D met k is the diffusion coefficient of metabolites, which indicates the diffusion capacity of acidic products in the pile; acid is the rate constant for the formation of acidic products, which is affected by microbial metabolism; t 現 Indicates the current time; t 初 Indicates the initial time; It indicates that as time goes by, the amount of acidic products in the pile decreases; dt is the time differential; The proposed conductivity change rate is R σ , the conductivity change rate refers to the charge concentration ρ ion and environmental conductivity k cond , used to reflect the dynamic changes in ion concentration: where σ 现 Indicates the current conductivity; σ 初 represents the initial conductivity; k cond represents the environmental conduction coefficient, k cond Adjust with temperature and humidity; ρ ion represents the ion concentration, ρ ion Affected by the production of metabolites in the fermentation reaction; 初 Refers to the starting time point of conductivity measurement, that is, the reference time when the conductivity change rate is calculated; t 现 is the current time, that is, the current conductivity measurement time point monitored in real time during the fermentation process; The proposed redox potential fluctuation amplitude is ΔE orp , the fluctuation amplitude of redox potential introduces the oxygen diffusion rate v O2 and the reduction metabolite generation coefficient k red , to capture changes in the redox environment: ΔE orp =E orp，最大 -E orp，最小 ·v O2 ·k red Where E orp，最大 Indicates the maximum value of redox potential; E orp，最小 Indicates the minimum value of redox potential; v O2 Indicates the diffusion rate of oxygen, used to reflect the aerobic or anaerobic state of the pile; k red Represents the reduction metabolite formation coefficient.

4. The method for preparing tea fertilizer based on microbial fermentation according to claim 3, characterized in that: The degradation rate of tannin V tan , Cumulative amount of acidic products Q acid , conductivity change rate R σ and the redox potential fluctuation amplitude ΔE orp Constructing the Reactivity Index I react , I react Used to evaluate the degradation efficiency of tannins during fermentation and to warn of reaction interference: I react =α·V tan -β·Q acid -γ·R σ -d·ΔE orp Where α, β, γ, and δ represent V tan , Q acid , R σ and ΔE orp The weight coefficient is used to balance the contribution of each parameter.

5. The method for preparing tea fertilizer based on microbial fermentation according to claim 4, characterized in that: Constructing the input data matrix includes: constructing the input data matrix X, the matrix X is used for sparse principal component analysis; the matrix X contains four parameters reflecting the interference source, and the four parameters reflecting the interference source are: volatile organic acid concentration C VOA , Tannin structural isomer ratio R isoT , pH fluctuation range ΔpH range and free metal ion conductivity change ΔEC metal ; Among them C VOA t i Indicates that at time point t i The volatile organic acid concentration measured at 1 ℃ indicates the cumulative effect of acidic metabolites; R isoT t i Indicates that at time point t i The ratio of tannin structural isomers generated at ΔpH indicates abnormal reaction pathways during tannin degradation; range t i Indicates that at time point t i The pH fluctuation range at that time is used to reflect the impact of acidic products on the environment; ΔEC metal t i Indicates time point t i The change in conductivity caused by the free metal ions during the reaction reflects the interference of the ion concentration fluctuation on the reaction. Feature extraction includes: extracting features from the input data matrix X to amplify the changing characteristics of different parameters in the time series; feature extraction removes the baseline level of each parameter; Where X 特征 Represents the data matrix after feature extraction, removing the average value of the data in order to highlight the characteristic changes of each parameter; represents the column mean matrix of X, representing the average level of each parameter; Dimensionality reduction decomposition includes: the matrix X after feature extraction 特征 Dimensionality reduction is performed on the data to concentrate on retaining the characteristic information in the data. The purpose of dimensionality reduction is to reduce the dimension of the data while retaining the parameter change information. X 降维 =X 特征 ·P Where X 降维 represents the data matrix after dimensionality reduction; P represents the dimensionality reduction projection matrix; Sparse matrix weight construction includes: using the reduced dimension matrix X 降维 Construct a sparse matrix weight W; the sparse matrix weight is used to identify the contribution of different parameters to interference, and the key parameters are highlighted by setting the sparsity; Where W represents the sparse matrix weight, which is used to characterize the interference feature weight of each parameter; S represents the sparse principal component matrix; ∥·∥ F represents the Frobenius norm, which is used to calculate the reconstruction error of the matrix; ∥·∥1 represents the L1 norm, which is used to control the sparsity of W so that the matrix retains non-zero elements; λ represents the sparsity adjustment parameter, which is used to control sparsity; Noise filtering includes: performing noise filtering on the sparse principal component matrix S to remove noise signals and obtain principal component signals; S 滤波 =S-σE Where S 滤波 represents the principal component matrix after noise filtering; σE represents the noise estimation matrix, which is obtained by deviation calculation; Principal component screening includes: filtering the principal component matrix S from the noise 滤波 Screen out the components that affect tannin degradation; locate the interference signals through screening; S 关键 =argmax k S 滤波 Where S 关键 represents the key principal component matrix, retaining the signals related to the interference sources of tannin degradation; argmax k It means selecting the principal component signal whose first k values ​​have a significant proportion in the data range; The output interference source positioning results include: the key principal component matrix S selected by analysis 关键 , output interference source, through S 关键 The fluctuation and change trend analysis can identify the interference sources that lead to abnormal tannin degradation.

6. The method for preparing tea fertilizer based on microbial fermentation according to claim 5, characterized in that: According to the results of the reaction interference source location, if the volatile organic acid concentration C VOA If the pH value is higher than the preset value, it indicates that the accumulation of acidic metabolites has disturbed the fermentation environment, resulting in a decrease in microbial activity. Therefore, alkaline neutralizers can be gradually added to reduce the impact of acidic metabolites and adjust the pH value to the ideal range. The adjustment formula is as follows: pH 调整 =pH 当前 +α·C 中和 pH 调整 Indicates the adjusted pH value to ensure that the fermentation pile returns to the target acid-base balance; pH 当前 Indicates the current pH value of the pile; α indicates the adjustment coefficient, which is used to control the amount of neutralizer added; C 中和 Indicates the concentration of alkaline regulator added to neutralize acidic metabolites; According to the results of the location of the reaction interference source, if the ratio of tannin structural isomers R isoT An increase indicates that a non-ideal reaction pathway occurs during tannin degradation, indicating that insufficient oxygen supply leads to abnormal tannin degradation pathways; Therefore, by increasing the oxygen flow rate and optimizing the oxygen supply to the fermentation pile, the aerobic metabolic efficiency of microorganisms can be improved, thereby promoting the degradation of tannins. The adjustment formula is as follows: O2=O2+β·ΔO2 Where O2 represents the current oxygen flow rate; β represents the oxygen flow rate adjustment coefficient; ΔO2 represents the amount of oxygen that needs to be increased calculated based on the interference source positioning result; In interference source analysis, if pH fluctuation amplitude ΔpH is detected range If the pH value exceeds the preset range, it indicates that there is unstable acid-base fluctuation in the fermentation process, which will inhibit the degradation activity of microorganisms. Therefore, the amount of buffer added is increased to stabilize the acid-base balance in the fermentation pile and keep the pH fluctuation within the preset range. The adjustment formula is as follows: ΔpH 调整 =ΔpH 当前 -γ·C 缓冲剂 Where ΔpH 调整 Indicates the pH fluctuation range after adjustment; ΔpH 当前 represents the current pH fluctuation amplitude; γ represents the buffer adjustment coefficient, which is used to control the amount of buffer added; C 缓冲剂 Indicates the concentration of buffer added to stabilize pH fluctuations; If the conductivity of free metal ions changes by ΔEC metal Abnormal increase indicates that the accumulation of metal ions has an inhibitory effect on the activity of microorganisms; in this case, chelating agents are added to bind excess free metal ions, thereby reducing the interference of metal ions and restoring the normal activity of microorganisms; The adjustment formula is as follows: DEC 调整 =ΔEC 当前 -δ·C 螯合剂 Where ΔEC 调整 represents the adjusted conductivity change; ΔEC 当前 Indicates the current conductivity change; δ indicates the chelating agent adjustment coefficient, which is used to control the amount of chelating agent added; C 螯合剂 It indicates the concentration of chelating agent added to bind free metal ions; After the adjustment is completed, the tannin degradation rate R in the pile is continuously monitored. 降解 , so that it can gradually return to the expected target, R 降解 Used to determine whether the fermentation of the pile has reached the maturity standard; reached the set degradation threshold R 目标 After that, it indicates that the decomposition of tannins in the pile has reached an ideal state, and fermentation is progressing smoothly. The formula is as follows: R 降解 ≥R 目标 Where R 降解 represents the current tannin degradation rate; R 目标 It indicates the set target value of tannin degradation rate, ensuring that the degradation efficiency of tannin reaches the fertilizer use standard; by confirming that the fermentation adjustment has reached the target conditions, it indicates that the maturity of the pile fermentation has reached the fertilizer use standard.

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