Method and system for dynamically regulating and controlling growth environment of agricultural edible mushrooms

Abstract

The invention relates to the technical field of edible mushroom environment regulation and control, in particular to an agricultural edible mushroom growth environment dynamic regulation and control method and system. The method comprises the following steps: acquiring a regulation and control instruction of an edible mushroom growth environment and growth environment parameters within a period of time; based on the regulation and control instruction and the growth environment parameters, determining a growth control response curve of the edible mushrooms within a period of time; determining a curve deviation degree based on the control response curve and a preset health response curve; comparing the curve deviation degree with a preset deviation threshold value to obtain a curve deviation result; and based on the curve deviation result and a preset regulation and control strategy, obtaining a regulation and control scheme for regulating and controlling the growth of the edible mushrooms. The invention aims to solve the problems that in the prior art, edible mushroom infection pathogens in a culture room cannot be recognized in time, the pathogens diffuse in the culture room, the growth environment of edible mushrooms is difficult to regulate and control in time, and large-range infection of the edible mushrooms is caused.

Description

Technical Field

[0001] The present invention relates to the technical field of edible fungus environment regulation, and in particular to a method and system for dynamically regulating the growth environment of agricultural edible fungi. Background Art

[0002] In modern agricultural mushroom cultivation plants, edible fungi grow in enclosed chambers. Dynamically controlling the environment in these chambers ensures consistent and standardized production year-round. Current dynamic environmental control systems utilize sensors deployed within the chambers, such as temperature, humidity, CO2 concentration, and light intensity, to continuously collect data on the mushroom growth environment and transmit it to a controller. Based on preset target ranges for environmental parameters specific to the mushroom variety and growth stage, the controller activates actuators such as pest control, heating, cooling, humidification, and ventilation to maintain these parameters within optimal ranges.

[0003] However, closed culture chambers and edible mushrooms themselves harbor various pathogenic microorganisms (such as molds and bacteria) and pests. The onset of edible mushroom diseases often has an incubation period, during which the local metabolic activity of pathogens can cause extremely subtle changes in the temperature, humidity, or gas composition of the surrounding microenvironment. Existing environmental control systems primarily monitor and regulate average environmental parameters throughout the entire culture chamber. Their accuracy and deployment density are insufficient to reliably capture localized, weak environmental signal disturbances caused by early, small-scale pathogen activity. Edible mushroom production management often relies on manual, scheduled inspections to detect established, visible lesions. This leads to significant lags, missing the optimal opportunity to identify edible mushroom disease infections and preventing timely regulation of the mushroom growth environment. Consequently, early-stage diseases within the culture chamber go undetected and untreated, allowing pathogens to spread and infect Trichoderma mycelium on a large scale, resulting in reduced yield and quality and increased production costs. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for dynamically controlling the growth environment of agricultural edible fungi, which is used to solve the problem that the existing technology cannot timely identify pathogens that infect edible fungi in the culture room, the pathogens spread in the culture room, and it is difficult to timely control the growth environment of edible fungi, resulting in large-scale infection of edible fungi.

[0005] To achieve the above-mentioned object, the present invention adopts the following technical solution: a method for dynamically controlling the growth environment of agricultural edible fungi, comprising: Obtaining control instructions for the edible fungus growth environment and growth environment parameters over a period of time; Determining a control response curve for the growth of edible fungi over a period of time based on the control instructions and growth environment parameters; determining a curve deviation based on the control response curve and a preset health response curve; Comparing the curve deviation with a preset deviation threshold to obtain a curve deviation result; Based on the curve deviation results and the preset control strategy, a control scheme for controlling the growth of edible fungi is obtained.

[0006] According to one embodiment of the present invention, the step of constructing the preset health response curve includes: Obtain standard regulatory instructions for disease-free edible fungi and standard growth environment parameters over a period of time; Based on the standard control instructions and standard growth environment parameters, a preset health response curve is obtained.

[0007] According to one embodiment of the present invention, before the step of obtaining the standard control instructions for disease-free edible fungi and the standard growth environment parameters within a period of time, the step of verifying that the growth environment is in a healthy state is also included, including: Before placing disease-free edible fungi into the growth environment, two environmental verification curves are obtained based on standardized control instructions that are opposite to the execution instruction operations; Based on the two environmental verification curves, extracting key characteristic parameters from the two environmental verification curves; Calculating the ratio between the key characteristic parameters in the two environmental verification curves to obtain an environmental ratio; Based on the environmental ratio and the environmental threshold, if the environmental ratio is less than or equal to the environmental threshold, a verification result is obtained that the growth environment is in a healthy state.

[0008] According to one embodiment of the present invention, based on the two environmental verification curves, the step of extracting key characteristic parameters from the two environmental verification curves includes: Based on the two environmental verification curves, key characteristic parameters including slopes and corresponding time constants in the two environmental verification curves are extracted.

[0009] According to one embodiment of the present invention, the step of establishing the preset deviation threshold comprises: Obtain each control and cultivation instruction and each growth and cultivation parameter of the complete healthy cultivation cycle of edible fungi in the growth environment; Determining a plurality of growth response curves within a complete healthy culture cycle based on each of the control culture instructions and each of the growth culture parameters; Based on each segment of the complete response curve, a preset deviation threshold is determined.

[0010] According to one embodiment of the present invention, after the step of determining the preset deviation threshold based on each segment of the complete response curve, the method further includes: Obtain each control and cultivation instruction and each growth and cultivation parameter of the previous batch of edible fungi during a complete and healthy cultivation cycle in the growth environment; determining a plurality of growth response curves for the previous batch based on each control culture instruction and each growth culture parameter of the previous batch; determining a correction deviation threshold based on each segment of the complete response curve of the previous batch; Comparing the correction deviation threshold with a preset deviation threshold to obtain a correction difference; The correction difference is compared with the correction threshold to obtain the judgment result of the preset deviation threshold.

[0011] According to one embodiment of the present invention, the step of obtaining a control scheme for controlling the growth of edible fungi based on the curve deviation result and the preset control strategy includes: Based on the curve deviation result, obtaining environmental information representing the growth environment of the edible fungi and information on the current growth stage of the edible fungi; Based on the environmental information, the current growth stage information of the edible fungi and the preset control strategy, a control scheme for controlling the growth of the edible fungi is obtained.

[0012] According to one embodiment of the present invention, the step of obtaining environmental information representing the growth environment of the edible fungi and information about the current growth stage of the edible fungi based on the curve deviation result includes: Based on the curve deviation result, environmental information of temperature, humidity and carbon dioxide representing the growth environment of the edible fungi and information on the current growth stage of the edible fungi are obtained.

[0013] According to one embodiment of the present invention, the step of obtaining a control scheme for controlling the growth of edible fungi based on the environmental information, the current growth stage information of the edible fungi, and the preset control strategy includes: Based on the environmental information and the current growth stage information of the edible fungi, a plurality of selected control schemes stored in a preset control strategy and a curve deviation result within a predetermined period after each of the control schemes is executed are obtained; Prioritizing the selected multiple control schemes stored in the preset control strategy and the curve deviation results within a predetermined period after each control scheme is executed to obtain a scheme ranking result; The optimal solution from the solution ranking results is selected, and the optimal solution is used as the control solution for controlling the growth of edible fungi.

[0014] The present application also provides a system for dynamically controlling the growth environment of agricultural edible fungi, the system comprising: An acquisition module is used to obtain control instructions for the edible fungus growth environment and growth environment parameters over a period of time; A curve determination module, configured to determine a control response curve of the growth of edible fungi over a period of time based on the control instructions and growth environment parameters; a deviation acquisition module, configured to determine a curve deviation based on the control response curve and a preset health response curve; A comparison module, configured to compare the curve deviation with a preset deviation threshold to obtain a curve deviation result; The scheme determination module is used to obtain a control scheme for controlling the growth of edible fungi based on the curve deviation result and the preset control strategy.

[0015] Compared with the prior art, the method and system for dynamically controlling the growth environment of agricultural edible fungi of the present invention have the following advantages: The present invention uses an environmental control system to obtain control instructions for the edible fungus growth environment and growth environment parameters collected by environmental sensors. It can determine the actual dynamic response of the edible fungus growth environment to the control instructions over a period of time, generating a control response curve. This curve reflects the growth status of the edible fungi under the current growth environment. By comparing the actual control response curve with a preset health response curve, the curve deviation is determined, and the difference between the two curves is quantified using the curve deviation. The curve deviation can capture subtle changes in the growth environment caused by early or localized pathogen activity. The curve deviation is evaluated using a preset deviation threshold. If the curve deviation exceeds the preset deviation threshold, an abnormal curve deviation is obtained, indicating that the current state of the edible fungus growth environment is abnormal. If the curve deviation does not exceed the preset deviation threshold, a normal curve deviation is obtained, indicating that the current state of the edible fungus growth environment is normal. Based on the curve deviation results, a preset control strategy is applied to control the edible fungus growth environment. This enables dynamic monitoring, abnormality identification, and automatic control of the edible fungus growth environment, thereby preventing widespread infection of edible fungi. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention, the following briefly introduces the drawings required for use in the specific embodiments. In all the drawings, each element or part is not necessarily drawn according to the actual scale.

[0017] Figure 1 The present invention is a flow chart of a method for dynamically controlling the growth environment of agricultural edible fungi.

[0018] Figure 2 This is a structural block diagram of a dynamic control system for the growth environment of agricultural edible fungi according to the present invention.

[0019] In the figure: an acquisition module 210, a curve determination module 220, a deviation acquisition module 230, a comparison module 240, and a solution determination module 250.

[0020] The implementation and advantages of the functions of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] The following diagrams illustrate various embodiments of the present invention. For clarity, many practical details are included in the following description. However, it should be understood that these practical details are not intended to limit the present invention. In other words, in some embodiments of the present invention, these practical details are not essential. Furthermore, to simplify the drawings, some commonly used structures and components are depicted in simplified schematic form.

[0022] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0023] In addition, in the present invention, descriptions such as "first" and "second" are only used for descriptive purposes and do not specifically refer to the order or sequence, nor are they used to limit the present invention. They are only used to distinguish components or operations described with the same technical terms, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0024] In order to further understand the content, features and effects of the present invention, the following embodiments are given as examples and described in detail with reference to the accompanying drawings: See also Figure 1 The present invention provides a method for dynamically controlling the growth environment of agricultural edible fungi, comprising the following steps: S100: Obtain control instructions for the edible fungus growth environment and growth environment parameters over a period of time. Control instructions refer to operational commands issued by the environmental control system to the actuator, such as instructions for heating, cooling, humidification, dehumidification, ventilation, or supplemental lighting within the closed culture chamber, thereby changing specific parameters of the edible fungus growth environment. Growth environment parameters are actual state data of the edible fungus growth environment collected by sensors, such as parameters such as temperature, humidity, carbon dioxide concentration, and light intensity. They reflect the edible fungi's response to the control instructions and the current state of the edible fungi's growth environment.

[0025] S200. Based on the control instructions and growth environment parameters, determine the control response curve of the edible fungus growth within a period of time. The control response curve can be obtained by data fitting, machine learning models or empirical curves. The period of time is 6 hours, 12 hours, 24 hours, 36 hours or 48 hours; 24 hours is preferred in this embodiment. If the control instruction is a heating instruction, the heating mechanism uses 80% power to heat for 120 seconds; based on the growth environment parameters including temperature, humidity, carbon dioxide concentration and light intensity within 24 hours, the control response curve of the edible fungus growth is obtained, thereby understanding the dynamic characteristics of the edible fungus growth environment.

[0026] S300: Determine a curve deviation based on the control response curve and the preset health response curve. The preset health response curve represents the dynamic response pattern of the environment to control instructions in a healthy growth environment for edible fungi, thereby determining whether the current environmental state is abnormal. The curve deviation is a quantitative indicator of the degree of difference between the actual control response curve and the preset health response curve, measuring the degree of deviation of the current environmental dynamic characteristics from a healthy baseline.

[0027] S400: Compare the curve deviation with a preset deviation threshold to obtain a curve deviation result. If the curve deviation exceeds the preset deviation threshold, a curve deviation abnormality result is obtained.

[0028] S500. Based on the curve deviation result and the preset control strategy, a control scheme for controlling the growth of edible fungi is obtained. In this embodiment, the result of the curve deviation abnormality is determined, and the preset control strategy is such as strong ventilation and dehumidification in the closed culture room. The fresh air fan and dehumidifier are operated at maximum power for 120 seconds, so that the indoor relative humidity drops rapidly from 90% to 70% in a short period of time, accompanied by a brief cooling. The drastic transient change in the growth environment is a fatal blow to the fragile Trichoderma mycelium in the early germination stage, but it is within the safe stress range for the more tolerant Pleurotus eryngii mycelium. Thereby, the growth environment of edible fungi can be regulated.

[0029] By acquiring control commands for the edible fungus growth environment and the growth environment parameters collected by environmental sensors through an environmental control system, the actual dynamic response of the edible fungus growth environment to the control commands over a period of time can be determined, generating a control response curve. This curve reflects the growth status of the edible fungi under the current growth environment. By comparing the actual control response curve with a preset health response curve, the curve deviation is determined, and the difference between the two curves is quantified using the curve deviation. The curve deviation can capture subtle changes in the growth environment caused by early or localized pathogen activity. The curve deviation is evaluated using a preset deviation threshold. If the curve deviation exceeds the preset deviation threshold, an abnormal curve deviation is detected, indicating that the current state of the edible fungus growth environment is abnormal. If the curve deviation does not exceed the preset deviation threshold, a normal curve deviation is detected, indicating that the current state of the edible fungus growth environment is normal. Based on the curve deviation results, a preset control strategy is applied to control the edible fungus growth environment. This enables dynamic monitoring, abnormality identification, and automatic control of the edible fungus growth environment.

[0030] In some of the above embodiments, the present application further proposes that the steps of constructing the preset health response curve include: Obtain standard control instructions for disease-free edible fungi and standard growth environment parameters over a period of time. Disease-free edible fungi refer to individuals or groups of edible fungi that are in an ideal healthy growth state and are not invaded by pathogens. They can be determined by manual screening, pathological testing, or based on growth performance evaluation. Standard control instructions refer to a sequence of control signals sent by the environmental control system to the actuator under ideal conditions to ensure the healthy growth of disease-free edible fungi. They can be obtained by using a pre-set control program, instructions input by expert experience, or an instruction sequence generated by an optimization algorithm. Standard growth environment parameters refer to a set of numerical values ​​of various environmental indicators that change over time in the growth environment of disease-free edible fungi, collected by sensors when executing standard control instructions. They can be obtained using data collected by temperature sensors, humidity sensors, carbon dioxide sensors, etc.

[0031] Based on the standard control instructions and standard growth environment parameters, a preset health response curve is obtained. The preset health response curve is a curve model constructed based on the standard control instructions and standard growth environment parameters, representing the dynamic response of environmental parameters to the control instructions in a disease-free edible fungus growth environment. The curve can be derived using methods such as data fitting, machine learning models, or empirical curves. The preset health response curve captures how environmental parameters dynamically change in response to control instructions under a healthy state. The preset health response curve serves as a benchmark for determining whether the actual growth environment deviates from a healthy state. By comparing the actual collected control response curve with the preset health response curve, the curve deviation is calculated. This ensures that the preset health response curve more accurately reflects the true dynamic characteristics of a healthy state, rather than a static or empirical benchmark. This makes anomaly detection and control based on curve deviation possible and more accurate, improving the effectiveness and reliability of the entire dynamic control method. It can also better adapt to the dynamic changes in the edible fungus growth process, improving the ability to detect subtle anomalies early on.

[0032] In some of the above embodiments, the present application further proposes that before the step of obtaining the standard control instructions for disease-free edible fungi and the standard growth environment parameters for a period of time, the step of verifying that the growth environment is in a healthy state is also included, including: Before introducing disease-free edible fungi into the growth environment, two environmental verification curves are obtained based on standardized control instructions that execute opposite operations. Specifically, for example, the standardized control instructions that execute opposite operations are heating and cooling instructions, or humidification and dehumidification instructions. By executing these opposite instructions and recording the changes in environmental parameters over time, a curve reflecting the environmental response to the opposite control is obtained. The two curves are then compared and analyzed, and potential weak abnormal signals in the environment are amplified through the opposite stimulation, thereby improving the sensitivity and accuracy of the verification.

[0033] Based on the two environmental verification curves, key characteristic parameters are extracted from the two environmental verification curves. For example, the maximum slope of the curve, the time required to reach a stable state, or the integrated area of ​​the curve are extracted to reflect the response speed, amplitude, and stability of the environment. This simplifies the complex curve information into quantifiable indicators, facilitating subsequent calculations and comparisons.

[0034] The environmental ratio is obtained by calculating the ratio of the key characteristic parameters in the two environmental verification curves, such as the ratio of the maximum slope of the first verification curve to the maximum slope of the second verification curve, or the ratio of the response time of the first verification curve to the response time of the second verification curve.

[0035] Based on the environmental ratio and the environmental threshold, if the environmental ratio is less than or equal to the environmental threshold, a verification result is obtained that the growth environment is in a healthy state.

[0036] By verifying that the growth environment is in a healthy state, a preliminary assessment of the edible fungus growth environment is conducted before formal standard data collection to ensure that the growth environment itself does not have any pollution or abnormalities that affect the accuracy of the data, and to ensure the reliability of the standard control instructions and standard growth environment parameters subsequently obtained.

[0037] In some of the above embodiments, the present application further proposes that the step of extracting key characteristic parameters from the two environmental verification curves based on the two environmental verification curves includes: Based on the two environmental verification curves, key characteristic parameters, including the slope and corresponding time constant, are extracted from the two environmental verification curves. For example, a curve showing the temperature rising over time after a cooling command is applied is used. To extract the slope, multiple data points are selected within a specific time period of the curve and the rate of temperature change between adjacent data points is calculated. Alternatively, a linear fit is performed on the curve for that time period, with the slope of the fitted line being used as the slope for that time period. To extract the time constant, the time required for the curve to change from an initial value to a certain percentage of its final value is determined. Extracting key characteristic parameters, including the slope and corresponding time constant, from the two environmental verification curves can provide richer and more representative information from the dynamic response of the environment. The slope reflects the rate of change of the environmental parameter, while the time constant reflects the speed of change. Comprehensively analyzing these two parameters allows for a more comprehensive and accurate assessment of the health of the growth environment, identifying early, weak abnormal signals, and providing a more reliable basis for subsequent disease warning and control, avoiding the difficulty of relying solely on a single environmental parameter to comprehensively assess the health of the environment.

[0038] In some of the above embodiments, the present application further proposes that the step of constructing the preset deviation threshold includes: Obtain each control and cultivation instruction and each growth and cultivation parameter of a complete and healthy cultivation cycle of edible fungi in the growth environment. Among them, a complete and healthy cultivation cycle refers to the entire process of edible fungi from mycelial growth to mature fruiting body picking, during which the edible fungi are free of disease and the environmental control system operates normally. It is determined by recording the start and end time of the cultivation batch and combining it with manual observation or disease detection results. Control and cultivation instructions refer to the control signals or set values ​​sent by the environmental control system to the actuators, which are used to adjust the environmental parameters. This is achieved by reading the control system log file or real-time monitoring of the instruction information on the control bus. Growth and cultivation parameters refer to the various physical or chemical indicators in the edible fungi growth environment collected by sensors, such as temperature, humidity and carbon dioxide concentration, etc. This is achieved by connecting to the environmental sensor network and receiving sensor data streams.

[0039] Based on each of the control and cultivation instructions and each of the growth and cultivation parameters, a multi-segment growth response curve is determined over a complete healthy cultivation cycle. The multi-segment growth response curve refers to a curve depicting the change of environmental parameters over time within each time period, based on the control and cultivation instructions and growth and cultivation parameter data, by dividing the complete healthy cultivation cycle into multiple time periods according to time or growth stage. This curve is achieved using data segmentation processing and curve fitting techniques.

[0040] Based on each complete response curve, a preset deviation threshold is determined. The preset deviation threshold is a threshold used to determine whether the degree of deviation between the actual growth response curve and the preset health response curve is abnormal. This threshold is dynamically determined based on data in a healthy state and is determined using existing statistical analysis methods or machine learning methods.

[0041] For example, by reading historical log files from an environmental control system and connecting to an environmental sensor network to obtain historical data, each control and cultivation instruction and each growth and cultivation parameter for a complete healthy cultivation cycle of edible fungi in an environment can be obtained. Next, the complete healthy cultivation cycle is divided into growth stages (e.g., mycelial growth, fruiting, and fruiting body maturity). Within each growth stage, for a specific control and cultivation instruction (e.g., ventilation activation), the corresponding growth and cultivation parameter (e.g., carbon dioxide concentration) is extracted over time to determine the growth response curve for that stage. Finally, based on the healthy growth response curve data for each growth stage, the mean and standard deviation of the curve under a healthy state are calculated. A preset deviation threshold is set as the mean plus or minus a certain multiple of the standard deviation, or the upper and lower envelopes of the healthy curve are calculated, with the area outside the envelopes serving as the deviation threshold. Preset deviation thresholds are dynamically constructed based on actual growth data over the complete healthy cultivation cycle of edible fungi. Preset deviation thresholds can adapt to changes in the growth environment and cultivation conditions over time and across batches. Compared to static thresholds, dynamic thresholds more accurately reflect actual health standards. Improve the accuracy of judging the growth status of edible fungi and reduce the occurrence of misjudgment and missed judgment.

[0042] In some of the above embodiments, the present application further proposes that after the step of determining a preset deviation threshold based on each segment of the complete response curve, the method further includes: Obtain each control and cultivation instruction and each growth and cultivation parameter of the previous batch of edible fungi during a complete and healthy cultivation cycle in the growth environment.

[0043] Based on each control culture instruction and each growth culture parameter of the previous batch, a plurality of growth response curves of the previous batch are determined.

[0044] Based on each complete response curve of the previous batch, a correction deviation threshold is determined. The correction deviation threshold refers to the deviation threshold calculated based on the growth response curve of the previous batch of edible fungi during the complete healthy cultivation cycle, which serves as a reference standard for historical health status.

[0045] The corrected deviation threshold is compared with the preset deviation threshold to obtain a corrected difference. The corrected difference refers to the difference between the preset deviation threshold determined for the current batch and the corrected deviation threshold determined for the previous batch, reflecting the degree of deviation in the health response characteristics of the current batch from the previous batch.

[0046] The correction difference is compared with the correction threshold to determine whether the deviation is within the preset threshold. The correction threshold is a preset judgment limit used to assess whether the correction difference is within the acceptable range.

[0047] Specifically, the system can store complete healthy cultivation cycle data for multiple batches of edible fungi. After determining the preset deviation threshold for the current batch, the system can automatically retrieve the complete cultivation data for one or more recent healthy batches. For example, it can obtain all control and cultivation instructions and corresponding growth and cultivation parameter records for the previous batch of edible fungi under the growth environment. Based on this historical record, the growth response curve of the previous batch at each control stage is recalculated, and a corrected deviation threshold value representing the health status of the previous batch is further calculated. Suppose the preset deviation threshold calculated for the current batch is A, and the corrected deviation threshold calculated for the previous batch is B. The system calculates the corrected difference, such as the absolute value |AB|. This difference is then compared with a pre-set corrected threshold C. If |AB| > C, a deviation from the preset deviation threshold is detected, triggering a warning or suggesting that the user manually review or recalculate the threshold. If |AB| ≤ C, the preset deviation threshold is considered normal and can be used for subsequent curve deviation determinations. This effectively reduces the problem of threshold inaccuracy caused by batch differences or environmental changes, allowing the preset deviation threshold to more accurately reflect the actual situation of the current growth environment, thereby improving the accuracy of anomaly detection based on this threshold and providing a basis for the subsequent generation of more effective control plans.

[0048] Specifically, the determination of the preset deviation threshold not only relies on statistical analysis of the complete culture data of one or more recent healthy batches, but also incorporates a strategic adjustment mechanism to address the more complex interference factors in actual production environments. Specifically, those skilled in the art will appreciate that in the very early stages of pathogen infection, the subtle perturbations to environmental parameters caused by pathogens can sometimes be difficult to accurately distinguish morphologically from normal physiological fluctuations caused by differences in edible fungi's individual development and nutrient absorption. If the threshold is set too strictly, it may trigger unnecessary false alarms due to normal individual differences, disrupting production. To this end, an effective implementation strategy is to moderately relax the threshold's determination range after determining the preset deviation threshold based on data from a complete healthy culture cycle, i.e., setting a relatively looser deviation tolerance range as the subsequent preset deviation threshold. Because the healthy growth differences of edible fungi themselves are generally limited and regular, the magnitude of their impact on the control response curve is within a controllable range. However, once common pathogens such as molds establish their reproduction, their metabolic activities often exhibit rapid, continuous, and disordered exponential growth characteristics.

[0049] By setting the above-mentioned deviation tolerance range, most of the harmless curve deviations caused by normal growth differences can be effectively filtered out, greatly reducing the system's false alarm rate and avoiding unnecessary production interventions, thereby significantly improving the stability of the entire control system and its credibility in practical applications. Although this setting will sacrifice the sensitivity of capturing the weakest and earliest abnormal signals, due to the exponential reproduction characteristics of pathogens, it is ensured that the deviation caused by them will eventually significantly and continuously break through the set deviation tolerance range, thereby ensuring reliable and timely early warning and response before the disease causes serious economic losses. Ultimately, this strategy achieves a high technical balance between sensitivity, accuracy and robustness, making the present invention have greater practical value in the changing agricultural production field.

[0050] In some of the above embodiments, the present application further proposes the steps of obtaining a control scheme for controlling the growth of edible fungi based on the curve deviation results and the preset control strategy, including: Based on the curve deviation result, environmental information representing the growth environment of the edible fungi and information about the current growth stage of the edible fungi are obtained. The environmental information describes a set of parameters representing the current state of the edible fungi's growth environment, which can be represented by parameters such as temperature, humidity, gas concentration, or light intensity. The current growth stage information of the edible fungi indicates an identifier or data indicating the current developmental stage of the edible fungi, which can be represented by stage identifiers such as mycelial growth stage, physiological maturity stage, or fruiting body growth stage.

[0051] Based on the environmental information, the current growth stage information of the edible fungi and the preset control strategy, a control scheme for controlling the growth of edible fungi is obtained. Specifically, the preset control strategy stores a knowledge base of control rules or schemes for different growth states, environmental conditions and growth stages, which can be in the form of a lookup table, a decision tree or an expert system. The control scheme for controlling the growth of edible fungi is used to adjust the specific instructions or operation sequences of the parameters of the edible fungi growth environment, which can be represented by instructions such as adjusting the temperature setting value, the humidity setting value, the ventilation intensity, the light duration, etc. By incorporating the actual environmental information of the edible fungi growth environment and the current growth stage information of the edible fungi into the generation process of the control scheme, the generated control scheme can more accurately reflect the actual state and environmental conditions of the current edible fungi, avoid the limitations of simply controlling according to the degree of deviation, improve the pertinence and effectiveness of the control scheme, and thus improve the growth quality and yield of the edible fungi.

[0052] In some of the above embodiments, the present application further proposes that the steps of obtaining environmental information representing the growth environment of edible fungi and information on the current growth stage of edible fungi based on the curve deviation result include: Based on the curve deviation results, environmental information characterizing the temperature, humidity, and carbon dioxide levels in the edible fungi's growth environment, as well as information about the current growth stage of the edible fungi, is obtained. By obtaining these environmental information, which characterizes the temperature, humidity, and carbon dioxide levels in the edible fungi's growth environment, and information about the current growth stage of the edible fungi, based on the curve deviation results, the specific environmental factors (temperature, humidity, and carbon dioxide) causing the deviation, as well as the specific growth stage of the edible fungi, can be further analyzed from the curve deviation, which reflects the overall system state. Because edible fungi respond differently to environmental factors at different growth stages, specific environmental anomalies (such as excessively high temperatures) will manifest as specific deviation patterns in the control response curve. By conducting a more in-depth analysis of the curve deviation results, such as identifying characteristics such as shape, amplitude, and duration, and matching them with a pre-set library of patterns associated with specific environmental anomaly types and growth stages, specific environmental issues and growth stages can be identified, making subsequent control plans more targeted and improving control effectiveness.

[0053] In some of the above embodiments, the present application further proposes that the steps of obtaining a control scheme for controlling the growth of edible fungi based on the environmental information, the current growth stage information of the edible fungi, and the preset control strategy include: Based on the environmental information and the current growth stage information of the edible fungi, multiple selected control schemes stored in the preset control strategy and the curve deviation results within a predetermined period after each of the control schemes is executed are obtained.

[0054] Prioritize the multiple control schemes selected and stored in the preset control strategy, and the curve deviation results within a predetermined period after each control scheme is executed, to obtain a scheme ranking result. The priority ranking compares and ranks the multiple control schemes and their corresponding curve deviation results based on a preset evaluation standard or algorithm, thereby determining the order of merit of these schemes. The evaluation standard may be based on the degree of improvement in the curve deviation result (e.g., the magnitude or speed of reduction in deviation).

[0055] The optimal solution from the solution ranking results is selected and used as the control solution for controlling the growth of edible fungi. The optimal solution can ensure that the control solution finally implemented has the greatest effectiveness.

[0056] Based on environmental information and the current growth stage of the edible fungi, multiple alternative control schemes are obtained from the preset control strategy. Furthermore, the curve deviation results for each control scheme within a predetermined period after execution are obtained. This eliminates the need for scheme selection to rely solely on preset rules, but instead incorporates historical data on the scheme's actual execution performance. These alternative schemes and their corresponding curve deviation results are then prioritized to produce a scheme ranking result. By quantitatively evaluating and ranking historical performance, it is possible to clearly identify which schemes have performed better in the past. Finally, the optimal scheme from the ranking results is selected as the final control scheme. By selecting the scheme with the best historical performance, the effectiveness and targeted nature of the control measures can be ensured.

[0057] Based on any of the above implementations, please refer to Figure 2 The present application also provides a dynamic control system for the growth environment of agricultural edible fungi, which includes an acquisition module 210, a curve determination module 220, a deviation acquisition module 230, a comparison module 240 and a solution determination module 250.

[0058] The acquisition module 210 is used to obtain control instructions for the edible fungus growth environment and growth environment parameters within a period of time.

[0059] The curve determination module 220 is used to determine a control response curve of the growth of edible fungi within a period of time based on the control instructions and the growth environment parameters.

[0060] The deviation acquisition module 230 is used to determine the curve deviation based on the control response curve and the preset health response curve.

[0061] The comparison module 240 is used to compare the curve deviation with a preset deviation threshold to obtain a curve deviation result; The scheme determination module 250 is used to obtain a control scheme for controlling the growth of edible fungi based on the curve deviation result and the preset control strategy.

[0062] Through the settings of the acquisition module 210, the curve determination module 220, the deviation acquisition module 230, the comparison module 240 and the solution determination module 250, the acquisition module 210 is a unit for receiving or collecting external information, which can be a sensor interface, a data bus interface, a network communication interface or a file reading interface, and its purpose is to provide the system with basic data required for subsequent processing, including external input control instructions and growth environment parameters monitored in real time from the environment; the curve determination module 220 is a unit for converting input data into curve data representing the dynamic characteristics of the system, which can be implemented by using a data processing algorithm, a mathematical model or a lookup table, and its purpose is to associate discrete or continuous environmental parameters with control instructions to form a control response curve that reflects the response process of the edible fungus growth environment to the control behavior; the deviation acquisition module 230 is a unit for quantifying the difference between the actual system behavior and the ideal healthy behavior, which can be implemented by using a curve similarity calculation algorithm, a feature parameter extraction and comparison algorithm or a machine learning model, and its purpose is to calculate the degree of deviation between the actual control response curve and the preset health response curve by comparing the two, thereby providing a quantitative indicator for judging the growth status. Comparison module 240 is a unit used to compare the calculated quantitative indicators with preset judgment criteria. It can be implemented using simple numerical comparison logic, threshold judgment logic, or a rule-based reasoning engine. Its purpose is to determine whether the current growth environment state is within the abnormal range based on whether the curve deviation exceeds the preset deviation threshold, thereby obtaining a curve deviation result. Solution determination module 250 is a unit used to generate specific execution instructions based on the judgment result. It can be implemented using a rule engine, decision tree, expert system, or model-based optimization algorithm. Its purpose is to generate a control solution for the current growth environment state based on the curve deviation result output by comparison module 240 and combined with a preset control strategy, guiding the actuator to make corresponding environmental adjustments.

[0063] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A method for dynamically controlling the growth environment of agricultural edible fungi, characterized in that: include: Obtaining control instructions for the edible fungus growth environment and growth environment parameters over a period of time; Determining a control response curve for the growth of edible fungi over a period of time based on the control instructions and growth environment parameters; determining a curve deviation based on the control response curve and a preset health response curve; Comparing the curve deviation with a preset deviation threshold to obtain a curve deviation result; Based on the curve deviation results and the preset control strategy, a control scheme for controlling the growth of edible fungi is obtained.

2. The method for dynamically controlling the growth environment of agricultural edible fungi according to claim 1, characterized in that: The steps of constructing the preset health response curve include: Obtain standard regulatory instructions for disease-free edible fungi and standard growth environment parameters over a period of time; Based on the standard control instructions and standard growth environment parameters, a preset health response curve is obtained.

3. The method for dynamically controlling the growth environment of agricultural edible fungi according to claim 2, characterized in that: Before the step of obtaining the standard control instructions for disease-free edible fungi and the standard growth environment parameters for a period of time, the step of verifying that the growth environment is in a healthy state is also included, including: Before placing disease-free edible fungi into the growth environment, two environmental verification curves are obtained based on standardized control instructions that are opposite to the execution instruction operations; Based on the two environmental verification curves, extracting key characteristic parameters from the two environmental verification curves; Calculating the ratio between the key characteristic parameters in the two environmental verification curves to obtain an environmental ratio; Based on the environmental ratio and the environmental threshold, if the environmental ratio is less than or equal to the environmental threshold, a verification result is obtained that the growth environment is in a healthy state.

4. The method for dynamically controlling the growth environment of agricultural edible fungi according to claim 3, characterized in that: Based on the two environmental verification curves, the step of extracting key characteristic parameters from the two environmental verification curves includes: Based on the two environmental verification curves, key characteristic parameters including slopes and corresponding time constants in the two environmental verification curves are extracted.

5. The method for dynamically controlling the growth environment of agricultural edible fungi according to claim 1, characterized in that: The step of constructing the preset deviation threshold comprises: Obtain each control and cultivation instruction and each growth and cultivation parameter of the complete healthy cultivation cycle of edible fungi in the growth environment; Determining a plurality of growth response curves within a complete healthy culture cycle based on each of the control culture instructions and each of the growth culture parameters; Based on each segment of the complete response curve, a preset deviation threshold is determined.

6. A method for dynamically controlling the growth environment of agricultural edible fungi according to claim 5, characterized in that: After determining a preset deviation threshold based on each segment of the complete response curve, the method further includes: Obtain each control and cultivation instruction and each growth and cultivation parameter of the previous batch of edible fungi during a complete and healthy cultivation cycle in the growth environment; determining a plurality of growth response curves for the previous batch based on each control culture instruction and each growth culture parameter of the previous batch; determining a correction deviation threshold based on each segment of the complete response curve of the previous batch; Comparing the correction deviation threshold with a preset deviation threshold to obtain a correction difference; The correction difference is compared with the correction threshold to obtain the judgment result of the preset deviation threshold.

7. The method for dynamically controlling the growth environment of agricultural edible fungi according to claim 1, characterized in that: Based on the curve deviation results and the preset control strategy, the steps of obtaining a control scheme for controlling the growth of edible fungi include; Based on the curve deviation result, obtaining environmental information representing the growth environment of the edible fungi and information on the current growth stage of the edible fungi; Based on the environmental information, the current growth stage information of the edible fungi and the preset control strategy, a control scheme for controlling the growth of the edible fungi is obtained.

8. The method for dynamically controlling the growth environment of agricultural edible fungi according to claim 7, characterized in that: The step of obtaining environmental information representing the growth environment of the edible fungi and information about the current growth stage of the edible fungi based on the curve deviation result includes: Based on the curve deviation result, environmental information of temperature, humidity and carbon dioxide representing the growth environment of the edible fungi and information on the current growth stage of the edible fungi are obtained.

9. The method for dynamically controlling the growth environment of agricultural edible fungi according to claim 7, characterized in that: The steps of obtaining a control scheme for controlling the growth of edible fungi based on the environmental information, the current growth stage information of the edible fungi, and the preset control strategy include: Based on the environmental information and the current growth stage information of the edible fungi, a plurality of selected control schemes stored in a preset control strategy and a curve deviation result within a predetermined period after each of the control schemes is executed are obtained; Prioritizing the selected multiple control schemes stored in the preset control strategy and the curve deviation results within a predetermined period after each control scheme is executed to obtain a scheme ranking result; The optimal solution from the solution ranking results is selected, and the optimal solution is used as the control solution for controlling the growth of edible fungi.

10. A dynamic control system for the growth environment of agricultural edible fungi, characterized in that: The system includes: An acquisition module is used to obtain control instructions for the edible fungus growth environment and growth environment parameters over a period of time; A curve determination module, configured to determine a control response curve of the growth of edible fungi over a period of time based on the control instructions and growth environment parameters; a deviation acquisition module, configured to determine a curve deviation based on the control response curve and a preset health response curve; A comparison module, configured to compare the curve deviation with a preset deviation threshold to obtain a curve deviation result; The scheme determination module is used to obtain a control scheme for controlling the growth of edible fungi based on the curve deviation result and the preset control strategy.

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