Resource optimization allocation method and system for environmental control in the industrialized cultivation of Ganoderma lucidum

Abstract

This invention provides a resource optimization allocation method and system for environmental control in the industrialized cultivation of Ganoderma lucidum. By dividing the industrialized cultivation cycle of Ganoderma lucidum into stages and determining the environmental parameter thresholds for each stage, the growth characteristics of each stage are accurately matched, providing a quantifiable basis for environmental judgment. Based on historical Ganoderma lucidum cultivation data, a correlation model is established between environmental parameter deviations and resource adjustment amounts at each stage to ensure the rationalization of resource supply. By collecting real-time environmental parameters of industrialized Ganoderma lucidum cultivation, the deviation between the real-time environmental parameters and the environmental parameter thresholds of the current stage is determined, and the resource optimization parameters corresponding to the deviation values ​​are determined based on the correlation model, enabling timely resource control. By operating according to the resource optimization parameters and iteratively adjusting during the operation until the real-time environmental parameters meet the standards, the environmental parameters at each stage throughout the entire cultivation cycle are ensured to remain within the threshold range.

Description

Technical Field

[0001] This invention relates to the field of environmental control technology for Ganoderma lucidum cultivation, and particularly to a resource optimization allocation method and system for environmental control in the industrialized cultivation of Ganoderma lucidum. Background Technology

[0002] With the promotion of industrialized cultivation of Ganoderma lucidum, smart modular greenhouses and other models are widely used due to their small footprint, short fruiting cycle, and high efficiency. However, existing technologies have a core flaw—a disconnect between environmental control and resource allocation, specifically manifested as follows:

[0003] Disconnect between growth stage and parameter control: Ganoderma lucidum has significantly different environmental requirements at different growth stages, but the existing system only uses fixed parameter control without adjusting the resource supply for different stages. For example, water is supplied according to the high humidity requirements of the fruiting body stage during the mycelial growth stage, resulting in water waste; and low power temperature control is used according to the normal temperature stage during the low temperature season, which requires the running time to reach the standard and increases power consumption.

[0004] Resource allocation is not linked to environmental needs: The existing system allocates resources such as the power of temperature control equipment and the amount of water supplied for irrigation based only on preset fixed values. It does not establish a correlation between environmental parameter deviations and resource adjustments. For example, when the temperature is detected to be below the threshold, the temperature control equipment is directly operated at maximum power instead of calculating the optimal power based on the degree of deviation, resulting in excessive energy consumption. Irrigation is carried out only according to a fixed cycle without adjusting the water supply based on the dryness of the mushroom substrate, resulting in water waste.

[0005] Low resource utilization: The above-mentioned disconnect directly leads to insufficient utilization of energy and water resources, which not only increases planting costs, but also contradicts the core advantages of smart modular cabins in saving space and achieving good efficiency, thus restricting the large-scale cost reduction and efficiency improvement of Ganoderma lucidum factory cultivation.

[0006] Therefore, there is an urgent need for a technical solution that takes the growth stage of Ganoderma lucidum as the core and achieves dynamic matching between environmental regulation and resource allocation, so as to solve the problem of resource waste in the existing system. Summary of the Invention

[0007] This invention provides a resource optimization allocation method and system for environmental control in the industrialized cultivation of Ganoderma lucidum, in order to solve the problems mentioned in the background art.

[0008] Resource optimization allocation methods for environmental control in the industrialized cultivation of Ganoderma lucidum include:

[0009] S1: The industrialized cultivation cycle of Ganoderma lucidum is divided into stages, namely the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturation stage, and the environmental parameter thresholds for each stage are determined.

[0010] S2: Based on historical Ganoderma lucidum cultivation data, establish a correlation model between environmental parameter deviations and resource adjustment amounts at each stage;

[0011] S3: Real-time collection of environmental parameters for the industrialized cultivation of Ganoderma lucidum, determination of the deviation between the real-time environmental parameters and the current stage environmental parameter threshold, and determination of the resource optimization parameters corresponding to the deviation based on the correlation model;

[0012] S4: Run the program according to the resource optimization parameters and make iterative adjustments during the operation until the real-time environmental parameters meet the standards.

[0013] Preferably, in step S1, the industrialized cultivation cycle of Ganoderma lucidum is divided into stages, namely, the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturation stage, including:

[0014] Based on the prior analysis of Ganoderma lucidum growth data, the growth characteristics and time proportions of the mycelial growth stage, fruiting body formation stage, and fruiting body maturation stage were determined.

[0015] Based on the aforementioned growth characteristics and time proportions, the judgment criteria for each stage are determined;

[0016] Based on the criteria for each stage, the industrialized cultivation cycle of Ganoderma lucidum is divided into stages: mycelial growth stage, fruiting body formation stage, and fruiting body maturation stage.

[0017] Preferably, in step S1, determining the environmental parameter thresholds for each stage includes:

[0018] Based on the correspondence between historical growth data and historical environmental data of Ganoderma lucidum, initial environmental parameter thresholds were set for each stage.

[0019] Obtain the current cultivation scenario of Ganoderma lucidum, determine the correction coefficient based on the cultivation scenario, and correct the initial environmental parameter thresholds based on the correction coefficients to obtain the environmental parameter thresholds for each stage.

[0020] Preferably, in step S2, based on historical Ganoderma lucidum cultivation data, a correlation model is established between environmental parameter deviations and resource adjustment amounts at each stage, including:

[0021] Historical environmental parameter deviation values ​​were obtained from historical Ganoderma lucidum cultivation data, and combined with the environmental parameter thresholds for each stage, the influence coefficient of historical environmental parameter deviation values ​​on the growth of Ganoderma lucidum was calculated.

[0022] Based on historical Ganoderma lucidum cultivation data, stage labels and batch characteristics were set corresponding to the growth impact coefficient;

[0023] Based on historical Ganoderma lucidum cultivation data, historical resource adjustment cases were obtained, and the resource adjustment ratio was defined as the target variable.

[0024] Based on the stage characteristics, the interaction between the growth influence coefficient and key indicators of each stage is analyzed to obtain the interaction characteristics of the growth influence coefficient, where:

[0025] During the mycelial growth stage, the growth influence coefficient and 1 / humidity deviation are used as the interaction characteristics of the growth influence coefficient. During the fruiting body formation stage, the product of the growth influence coefficient and the mushroom bud density is used as the interaction characteristics of the growth influence coefficient. During the fruiting body maturation stage, the product of the growth influence coefficient and the fruiting body diameter is used as the interaction characteristics of the growth influence coefficient.

[0026] The interaction features of the growth impact coefficient, stage labels, batch features, and target variables are used as training data, and the evaluation results of historical resource adjustment cases are used as indicator data to train the initial gradient boosting tree model, thereby obtaining the correlation model between the growth impact coefficient and the amount of resource adjustment.

[0027] Preferably, historical environmental parameter deviation values ​​are obtained from historical Ganoderma lucidum cultivation data, and combined with the environmental parameter thresholds for each stage, the influence coefficient of historical environmental parameter deviation values ​​on the growth of Ganoderma lucidum at each stage is calculated, including:

[0028] The formula for calculating the growth influence coefficient of mycelial growth stage is as follows:

[0029] ;

[0030] in, This represents the growth influence coefficient at different stages of mycelial growth. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the mycelial growth stage. This indicates the rate of mycelial spread during the mycelial growth stage. This indicates the standard spread rate of mycelium during the mycelial growth stage. Indicates the historical environmental parameter deviation values ​​at different stages of mycelial growth;

[0031] The formula for calculating the growth influence coefficient during the fruiting body formation stage is as follows:

[0032] ;

[0033] in, This represents the growth influence coefficient during the fruiting body formation stage. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the sub-entity formation stage. This represents the historical environmental parameter deviation value during the sub-entity formation stage. This indicates the rate of deformed mushroom buds during the mycelial growth stage;

[0034] The formula for calculating the growth influence coefficient of the fruiting body maturation stage is as follows:

[0035] ;

[0036] in, This represents the growth influence coefficient at the fruiting body maturity stage. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the maturity stage of a sub-entity. This represents the historical environmental parameter deviation value at the maturity stage of the sub-entity. This represents the standard daily increase in the diameter of a child body during its mature stage. This represents the daily increase in the diameter of a child entity during its mature stage.

[0037] Preferably, in step S3, real-time environmental parameters of the Ganoderma lucidum industrial cultivation are collected, and the deviation between the real-time environmental parameters and the current stage environmental parameter threshold is determined, including:

[0038] Real-time environmental parameters are obtained by collecting data in real time from sensors pre-installed in the cultivation area of ​​Ganoderma lucidum in a factory setting.

[0039] A preset number of real-time environmental parameters are continuously sampled as the target real-time environmental parameters.

[0040] The deviation value is obtained by comparing the target's real-time environmental parameters with the environmental parameter thresholds of the current stage.

[0041] Preferably, in step S3, determining the resource optimization parameters corresponding to the deviation value based on the correlation model includes:

[0042] The deviation value and the corresponding stage are input into the correlation model, and the resource optimization parameters are output.

[0043] Preferably, in step S4, the process is performed according to the resource optimization parameters, and iterative adjustments are made during the operation until the real-time environmental parameters meet the standards, including:

[0044] The system operates according to the resource optimization parameters and collects the latest environmental parameters. The latest deviation between the latest environmental parameters and the environmental parameter threshold is then determined.

[0045] Based on the magnitude of the latest deviation value, determine the adjustment strategy for resource parameters.

[0046] Preferably, the adjustment strategy for resource parameters is determined based on the magnitude of the latest deviation value, including:

[0047] If the latest deviation value is greater than the first deviation threshold, iterative adjustments are immediately performed to increase the adjustment range of resource parameters;

[0048] If the latest deviation value is between the second deviation threshold and the first deviation threshold, it is monitored again after a preset period. If the latest deviation value monitored again is still between the second deviation threshold and the first deviation threshold, an adjustment is triggered to increase the adjustment range of the resource parameters, and the adjustment range is not greater than the preset threshold.

[0049] If the latest deviation value is less than the second deviation threshold, no adjustment is triggered, and the current resource optimization parameters are maintained.

[0050] A resource optimization allocation system for environmental control in the industrialized cultivation of Ganoderma lucidum includes:

[0051] The phase division and data acquisition module is used to divide the industrialized cultivation cycle of Ganoderma lucidum into phases, obtaining the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturity stage, and determining the environmental parameter thresholds for each stage.

[0052] The Deviation and Resource Analysis module is used to establish a correlation model between environmental parameter deviations and resource adjustments at each stage based on historical Ganoderma lucidum cultivation data.

[0053] The resource optimization module is used to collect real-time environmental parameters of Ganoderma lucidum factory cultivation, determine the deviation between the real-time environmental parameters and the environmental parameter threshold of the current stage, and determine the resource optimization parameters corresponding to the deviation based on the correlation model.

[0054] The iterative adjustment module is used to run according to the resource optimization parameters and to perform iterative adjustments during the operation until the real-time environmental parameters meet the standards.

[0055] Compared with the prior art, the present invention has achieved the following beneficial effects:

[0056] By dividing the industrialized cultivation cycle of Ganoderma lucidum into stages—mycelial growth, fruiting body formation, and fruiting body maturation—and determining the environmental parameter thresholds for each stage, the growth characteristics of each stage are precisely matched. This breaks the limitations of fixed parameters throughout the entire cycle, providing quantifiable criteria for environmental judgment and laying the foundation for subsequent resource regulation. Based on historical Ganoderma lucidum cultivation data, a correlation model is established between environmental parameter deviations and resource adjustments at each stage, ensuring rational resource supply and avoiding resource waste. By collecting real-time environmental parameters during industrialized Ganoderma lucidum cultivation, the deviation between real-time environmental parameters and the current stage's environmental parameter thresholds is determined. Based on the correlation model, the corresponding resource optimization parameters are determined, enabling timely resource regulation and ensuring accuracy and timeliness. Simultaneously, manual operation costs are reduced. By operating according to the resource optimization parameters and iteratively adjusting during operation until the real-time environmental parameters meet the standards, iterative adjustments ensure that environmental parameters at each stage throughout the entire cultivation cycle remain within the threshold range, achieving the dual goals of minimizing resource waste and guaranteeing yield.

[0057] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0058] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0059] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0060] Figure 1 This is a flowchart of a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum in this invention.

[0061] Figure 2 This is a flowchart illustrating the stage division of the industrialized cultivation cycle of Ganoderma lucidum in this embodiment of the invention.

[0062] Figure 3 This is a structural diagram of the resource optimization allocation system for environmental control in the industrialized cultivation of Ganoderma lucidum in an embodiment of the present invention. Detailed Implementation

[0063] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0064] Example 1:

[0065] This invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum, such as... Figure 1 As shown, it includes:

[0066] S1: The industrialized cultivation cycle of Ganoderma lucidum is divided into stages, namely the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturation stage, and the environmental parameter thresholds for each stage are determined.

[0067] S2: Based on historical Ganoderma lucidum cultivation data, establish a correlation model between environmental parameter deviations and resource adjustment amounts at each stage;

[0068] S3: Real-time collection of environmental parameters for the industrialized cultivation of Ganoderma lucidum, determination of the deviation between the real-time environmental parameters and the current stage environmental parameter threshold, and determination of the resource optimization parameters corresponding to the deviation based on the correlation model;

[0069] S4: Run the program according to the resource optimization parameters and make iterative adjustments during the operation until the real-time environmental parameters meet the standards.

[0070] In this embodiment, the environmental parameter thresholds include temperature threshold, humidity threshold, mushroom stick moisture content threshold, ventilation frequency threshold, and carbon dioxide concentration threshold.

[0071] In this embodiment, the resource adjustment amounts include, for example, temperature control power adjustment, water supply adjustment, ventilation duration adjustment, and carbon dioxide concentration supply adjustment.

[0072] In this embodiment, the real-time environmental parameters are real-time temperature, real-time humidity, real-time moisture content of the mushroom sticks, real-time ventilation frequency, and real-time carbon dioxide concentration, which are obtained based on sensor detection.

[0073] The beneficial effects of the above design scheme are as follows: By dividing the industrialized cultivation cycle of Ganoderma lucidum into stages, the mycelial growth stage, fruiting body formation stage, and fruiting body maturity stage are obtained, and the environmental parameter thresholds for each stage are determined. This accurately matches the growth characteristics of each stage, breaking the limitations of fixed parameters throughout the entire cycle. It provides a quantifiable basis for environmental judgment standards, laying the foundation for subsequent resource regulation. By establishing a correlation model between environmental parameter deviations and resource adjustments at each stage based on historical Ganoderma lucidum cultivation data, the rationalization of resource supply is ensured, and resource waste is avoided. By collecting real-time environmental parameters of industrialized Ganoderma lucidum cultivation, the deviation between real-time environmental parameters and the environmental parameter thresholds of the current stage is determined, and the resource optimization parameters corresponding to the deviation values ​​are determined based on the correlation model. This enables timely resource regulation, ensuring the accuracy and timeliness of resource regulation. At the same time, it reduces manual operation costs. By operating according to the resource optimization parameters and iteratively adjusting during the operation until the real-time environmental parameters meet the standards, iterative adjustments ensure that the environmental parameters at each stage throughout the entire cultivation cycle remain within the threshold range, achieving the dual goals of no resource waste and guaranteed yield.

[0074] Example 2:

[0075] Based on Example 1, this invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum, such as... Figure 2 As shown, in step S1, the industrialized cultivation cycle of Ganoderma lucidum is divided into stages, namely, the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturation stage, including:

[0076] Based on the prior analysis of Ganoderma lucidum growth data, the growth characteristics and time proportions of the mycelial growth stage, fruiting body formation stage, and fruiting body maturation stage were determined.

[0077] Based on the aforementioned growth characteristics and time proportions, the judgment criteria for each stage are determined;

[0078] Based on the criteria for each stage, the industrialized cultivation cycle of Ganoderma lucidum is divided into stages: mycelial growth stage, fruiting body formation stage, and fruiting body maturation stage.

[0079] In this embodiment, the growth characteristics during the mycelial growth stage are that the mycelium in the substrate grows from germination to covering the entire substrate bag without any visible mushroom buds, accounting for 30%-35% of the time. The established criteria are that the surface of the substrate is white, feels firm to the touch, and is free from contamination by other microorganisms.

[0080] In this embodiment, the growth characteristics during the fruiting body formation stage are the appearance of small white mushroom buds on the surface of the substrate, which gradually develop into small mushroom bodies of 1-3cm, accounting for 30%-35% of the time. The established criteria are: the number of mushroom buds is stable, there are no deformities, and the cap has not unfolded.

[0081] In this embodiment, the growth characteristics of the fruiting body maturation stage are that the small mushroom body swells, the cap expands to a diameter of 5-8cm, and the flesh is thick. This stage accounts for 30%-40% of the time. The established judgment criteria are that the edge of the cap is slightly rolled inward, there is no aging, and the harvesting standard is met.

[0082] The beneficial effects of the above design scheme are: by dividing the industrialized cultivation cycle of Ganoderma lucidum into stages, we can obtain the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturation stage, which provides a basis for determining the environmental parameter thresholds in stages.

[0083] Example 3:

[0084] Based on Example 2, this embodiment of the invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum. In step S1, determining the environmental parameter thresholds for each stage includes:

[0085] Based on the correspondence between historical growth data and historical environmental data of Ganoderma lucidum, initial environmental parameter thresholds were set for each stage.

[0086] Obtain the current cultivation scenario of Ganoderma lucidum, determine the correction coefficient based on the cultivation scenario, and correct the initial environmental parameter thresholds based on the correction coefficients to obtain the environmental parameter thresholds for each stage.

[0087] In this embodiment, for example, the smart modular cabin has strong thermal insulation, and the temperature fluctuation can be controlled within ±0.5℃ when cooling in summer and heating in winter. Therefore, the optimal temperature range is narrowed—for example, the optimal temperature during the mycelial stage is revised from 18~22℃ to 19~21℃, making it easier to control stably and reducing energy consumption.

[0088] The beneficial effects of the above design scheme are as follows: by establishing the correspondence between historical growth data and historical environmental data of Ganoderma lucidum, the initial environmental parameter thresholds for each stage are set, the current planting scenario of Ganoderma lucidum is obtained, the correction coefficient is determined based on the planting scenario, and the initial environmental parameter thresholds are corrected based on the correction coefficients to obtain the environmental parameter thresholds for each stage. This accurately matches the growth characteristics of each stage, breaks the limitation of fixed parameters throughout the entire cycle, and provides a quantifiable basis for environmental judgment standards, thus providing a foundation for subsequent resource regulation.

[0089] Example 4:

[0090] Based on Example 1, this embodiment of the invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum. In step S2, based on historical Ganoderma lucidum cultivation data, a correlation model is established between environmental parameter deviations and resource adjustment amounts at each stage, including:

[0091] Historical environmental parameter deviation values ​​were obtained from historical Ganoderma lucidum cultivation data, and combined with the environmental parameter thresholds for each stage, the influence coefficient of historical environmental parameter deviation values ​​on the growth of Ganoderma lucidum was calculated.

[0092] Based on historical Ganoderma lucidum cultivation data, stage labels and batch characteristics were set corresponding to the growth impact coefficient;

[0093] Based on historical Ganoderma lucidum cultivation data, historical resource adjustment cases were obtained, and the resource adjustment ratio was defined as the target variable.

[0094] Based on the stage characteristics, the interaction between the growth influence coefficient and key indicators of each stage is analyzed to obtain the interaction characteristics of the growth influence coefficient, where:

[0095] During the mycelial growth stage, the growth influence coefficient and 1 / humidity deviation are used as the interaction characteristics of the growth influence coefficient. During the fruiting body formation stage, the product of the growth influence coefficient and the mushroom bud density is used as the interaction characteristics of the growth influence coefficient. During the fruiting body maturation stage, the product of the growth influence coefficient and the fruiting body diameter is used as the interaction characteristics of the growth influence coefficient.

[0096] The interaction features of the growth impact coefficient, stage labels, batch features, and target variables are used as training data, and the evaluation results of historical resource adjustment cases are used as indicator data to train the initial gradient boosting tree model, thereby obtaining the correlation model between the growth impact coefficient and the amount of resource adjustment.

[0097] In this embodiment, stage labels such as [1,0,0] represent the mycelial stage, and [0,1,0] represent the fruiting body formation stage.

[0098] In this embodiment, batch characteristics include seasonal characteristics, batch quality score of spawn bags, and type of planting carrier. For example, winter = 1.2 and summer = 0.8, reflecting differences in environmental conditions. The batch quality score of spawn bags is 0~10 points, calculated based on historical contamination rate and fruiting rate. Among the types of planting carriers, 24㎡ container = 1 and 100㎡ greenhouse = 0.6, reflecting differences in space insulation and ventilation.

[0099] In this embodiment, the resource adjustment ratio is, for example, the temperature control power adjustment ratio, the single water supply adjustment ratio, the ventilation duration adjustment ratio, etc.

[0100] In this embodiment, the greater the impact of historical environmental parameter deviations on the growth of Ganoderma lucidum, the larger the corresponding growth influence coefficient.

[0101] In this embodiment, during the mycelial growth stage, the high humidity during the mycelial stage makes it easy to get contaminated. The influence of humidity deviation on the growth influence coefficient is that the growth influence coefficient increases sharply when the humidity is too high. That is, a small change in humidity causes a large growth impact. This product makes the model more sensitive to slight deviations when the humidity is close to the upper limit of the threshold, and early intervention can avoid a sharp increase in risk.

[0102] During the fruiting body formation stage, the higher the density of mushroom buds per unit area, the more concentrated the fruiting bodies become, and the more sensitive they are to environmental fluctuations. The core requirement during the fruiting body formation period is environmental stability. Especially when the mushroom buds are dense, excessive adjustments can lead to a sudden drop in local humidity, causing batch deformities. The product of the growth influence coefficient and the mushroom bud density allows the model to identify conservative adjustment needs in dense scenarios. The larger the product, the more moderate the impact but the more sensitive the group is. The model will automatically select a more conservative adjustment strategy.

[0103] During the maturation stage of the fruiting body, the core objective of the maturation period is to ensure the final quality. Fruiting bodies with larger diameters are far less tolerant of environmental adjustments than those with smaller diameters. The larger the product here, the more minor the impact but the higher the maturity. The model will actively reduce the adjustment range to ensure quality.

[0104] The beneficial effects of the above design scheme are as follows: by calculating the growth impact coefficients at each stage, the correlation logic shifts from being driven by environmental deviations to being driven by growth needs, making the correlation logic more aligned with the essence of planting; by setting stage labels and batch features, the model's adaptability to each stage and each batch feature type is improved; by defining the resource adjustment ratio as the target variable, it adapts to planting scenarios of different scales; by constructing interactive features of growth impact coefficients in stages, it strengthens the stage-differentiated correlation; by training the initial gradient boosting tree model with specific training data and indicators, it balances growth assurance and resource conservation, outputs the optimal solution, and ultimately ensures the rationalization of resource supply and avoids resource waste.

[0105] Example 5:

[0106] Based on Example 4, this embodiment of the invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum. It obtains historical environmental parameter deviation values ​​from historical Ganoderma lucidum cultivation data and, combined with environmental parameter thresholds for each stage, calculates the influence coefficient of historical environmental parameter deviation values ​​on the growth of Ganoderma lucidum at each stage, including:

[0107] The formula for calculating the growth influence coefficient of mycelial growth stage is as follows:

[0108] ;

[0109] in, This represents the growth influence coefficient at different stages of mycelial growth. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the mycelial growth stage. This indicates the rate of mycelial spread during the mycelial growth stage. This indicates the standard spread rate of mycelium during the mycelial growth stage. Indicates the historical environmental parameter deviation values ​​at different stages of mycelial growth;

[0110] The formula for calculating the growth influence coefficient during the fruiting body formation stage is as follows:

[0111] ;

[0112] in, This represents the growth influence coefficient during the fruiting body formation stage. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the sub-entity formation stage. This represents the historical environmental parameter deviation value during the sub-entity formation stage. This indicates the rate of deformed mushroom buds during the mycelial growth stage;

[0113] The formula for calculating the growth influence coefficient of the fruiting body maturation stage is as follows:

[0114] ;

[0115] in, This represents the growth influence coefficient at the fruiting body maturity stage. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the maturity stage of a sub-entity. This represents the historical environmental parameter deviation value at the maturity stage of the sub-entity. This represents the standard daily increase in the diameter of a child body during its mature stage. This represents the daily increase in the diameter of a child entity during its mature stage.

[0116] In this embodiment, the historical environmental parameter deviation value is calculated based on the difference between the actual value and the optimal threshold among the environmental parameter thresholds.

[0117] The beneficial effects of the above design scheme are: by calculating the growth influence coefficient at each stage, the correlation logic is shifted from being driven by environmental deviations to being driven by growth needs, making the correlation logic more in line with the essence of planting, and by using the main growth characteristics of each stage as the calculation parameters for the growth influence coefficient, the adaptability of the growth influence coefficient to the growth stage is guaranteed, and the accuracy of the growth influence coefficient is guaranteed.

[0118] Example 6:

[0119] Based on Example 1, this embodiment of the invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum. In step S3, real-time environmental parameters for the industrialized cultivation of Ganoderma lucidum are collected, and the deviation between the real-time environmental parameters and the current stage's environmental parameter threshold is determined, including:

[0120] Real-time environmental parameters are obtained by collecting data in real time from sensors pre-installed in the cultivation area of ​​Ganoderma lucidum in a factory setting.

[0121] A preset number of real-time environmental parameters are continuously sampled as the target real-time environmental parameters.

[0122] The deviation value is obtained by comparing the target's real-time environmental parameters with the environmental parameter thresholds of the current stage.

[0123] In this embodiment, the sensors include temperature sensors, humidity sensors, carbon dioxide concentration detection sensors, etc., each corresponding to an environmental parameter.

[0124] The beneficial effects of the above design scheme are as follows: real-time environmental parameters are obtained by collecting data in real time through sensors pre-set in the planting area of ​​Ganoderma lucidum industrialized cultivation; a preset number of real-time environmental parameters are continuously sampled as target real-time environmental parameters, and the target real-time environmental parameters are compared with the environmental parameter threshold of the current stage to obtain the deviation value. This enables real-time monitoring and determination of environmental parameters and real-time deviation values ​​during the cultivation of Ganoderma lucidum, providing a basis for timely regulation of resources.

[0125] Example 7:

[0126] Based on Example 6, this embodiment of the invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum. In step S3, the resource optimization parameters corresponding to the deviation values ​​are determined based on an association model, including:

[0127] The deviation value and the corresponding stage are input into the correlation model, and the resource optimization parameters are output.

[0128] The beneficial effects of the above design scheme are: based on the correlation model, the resource optimization parameters corresponding to the deviation value are determined, so as to realize timely regulation of resources, ensure the accuracy and timeliness of resource regulation, and at the same time, reduce the cost of manual operation.

[0129] Example 8:

[0130] Based on Example 1, this embodiment of the invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum. In step S4, the method operates according to the resource optimization parameters and iteratively adjusts the process until the real-time environmental parameters meet the standards, including:

[0131] The system operates according to the resource optimization parameters and collects the latest environmental parameters. The latest deviation between the latest environmental parameters and the environmental parameter threshold is then determined.

[0132] Based on the magnitude of the latest deviation value, determine the adjustment strategy for resource parameters.

[0133] The beneficial effects of the above design scheme are: by running according to the resource optimization parameters and collecting the latest environmental parameters, the latest deviation value between the latest environmental parameters and the environmental parameter threshold is determined, and based on the magnitude of the latest deviation value, the adjustment strategy for the resource parameters is determined to ensure that the environmental parameters at each stage throughout the entire planting cycle remain within the threshold range, thereby achieving the dual goals of no resource waste and guaranteed yield.

[0134] Example 9:

[0135] Based on Example 8, this embodiment of the invention provides a resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum. Based on the magnitude of the latest deviation value, an adjustment strategy for resource parameters is determined, including:

[0136] If the latest deviation value is greater than the first deviation threshold, iterative adjustments are immediately performed to increase the adjustment range of resource parameters;

[0137] If the latest deviation value is between the second deviation threshold and the first deviation threshold, it is monitored again after a preset period. If the latest deviation value monitored again is still between the second deviation threshold and the first deviation threshold, an adjustment is triggered to increase the adjustment range of the resource parameters, and the adjustment range is not greater than the preset threshold.

[0138] If the latest deviation value is less than the second deviation threshold, no adjustment is triggered, and the current resource optimization parameters are maintained.

[0139] In this embodiment, the adjustment range of the latest deviation value being greater than the first deviation threshold is greater than the adjustment range of the latest deviation value between the second deviation threshold and the first deviation threshold.

[0140] In this embodiment, the first deviation threshold is greater than the second deviation threshold.

[0141] The beneficial effects of the above design scheme are: by classifying and determining strategies according to the magnitude of deviation, it accurately matches the core needs of Ganoderma lucidum industrial cultivation for environmental stability, resource conservation, and efficient regulation. This not only solves the problems of existing systems either over-regulating and wasting resources or lagging regulation and affecting growth, but also fits the high environmental sensitivity of Ganoderma lucidum, thereby avoiding excessive resource consumption and insufficient regulation, and reducing long-term operating costs.

[0142] Example 10:

[0143] This invention provides a resource optimization allocation system for environmental control in the industrialized cultivation of Ganoderma lucidum, such as... Figure 3 As shown, it includes:

[0144] The phase division and data acquisition module is used to divide the industrialized cultivation cycle of Ganoderma lucidum into phases, obtaining the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturity stage, and determining the environmental parameter thresholds for each stage.

[0145] The Deviation and Resource Analysis module is used to establish a correlation model between environmental parameter deviations and resource adjustments at each stage based on historical Ganoderma lucidum cultivation data.

[0146] The resource optimization module is used to collect real-time environmental parameters of Ganoderma lucidum factory cultivation, determine the deviation between the real-time environmental parameters and the environmental parameter threshold of the current stage, and determine the resource optimization parameters corresponding to the deviation based on the correlation model.

[0147] The iterative adjustment module is used to run according to the resource optimization parameters and to perform iterative adjustments during the operation until the real-time environmental parameters meet the standards.

[0148] In this embodiment, the environmental parameter thresholds include temperature threshold, humidity threshold, mushroom stick moisture content threshold, ventilation frequency threshold, and carbon dioxide concentration threshold.

[0149] In this embodiment, the resource adjustment amounts include, for example, temperature control power adjustment, water supply adjustment, ventilation duration adjustment, and carbon dioxide concentration supply adjustment.

[0150] In this embodiment, the real-time environmental parameters are real-time temperature, real-time humidity, real-time moisture content of the mushroom sticks, real-time ventilation frequency, and real-time carbon dioxide concentration, which are obtained based on sensor detection.

[0151] The beneficial effects of the above design scheme are as follows: By dividing the industrialized cultivation cycle of Ganoderma lucidum into stages, the mycelial growth stage, fruiting body formation stage, and fruiting body maturity stage are obtained, and the environmental parameter thresholds for each stage are determined. This accurately matches the growth characteristics of each stage, breaking the limitations of fixed parameters throughout the entire cycle. It provides a quantifiable basis for environmental judgment standards, laying the foundation for subsequent resource regulation. By establishing a correlation model between environmental parameter deviations and resource adjustments at each stage based on historical Ganoderma lucidum cultivation data, the rationalization of resource supply is ensured, and resource waste is avoided. By collecting real-time environmental parameters of industrialized Ganoderma lucidum cultivation, the deviation between real-time environmental parameters and the environmental parameter thresholds of the current stage is determined, and the resource optimization parameters corresponding to the deviation values ​​are determined based on the correlation model. This enables timely resource regulation, ensuring the accuracy and timeliness of resource regulation. At the same time, it reduces manual operation costs. By operating according to the resource optimization parameters and iteratively adjusting during the operation until the real-time environmental parameters meet the standards, iterative adjustments ensure that the environmental parameters at each stage throughout the entire cultivation cycle remain within the threshold range, achieving the dual goals of no resource waste and guaranteed yield.

[0152] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this application and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A resource optimal allocation method for environmental regulation of Ganoderma lucidum factory planting, characterized in that, include: S1: The industrialized cultivation cycle of Ganoderma lucidum is divided into stages, namely the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturation stage, and the environmental parameter thresholds for each stage are determined. S2: Based on historical Ganoderma lucidum cultivation data, a correlation model is established between environmental parameter deviations and resource adjustments at each stage, including: Historical environmental parameter deviation values ​​were obtained from historical Ganoderma lucidum cultivation data, and combined with the environmental parameter thresholds for each stage, the influence coefficient of historical environmental parameter deviation values ​​on the growth of Ganoderma lucidum was calculated. Based on historical Ganoderma lucidum cultivation data, stage labels and batch characteristics were set corresponding to the growth impact coefficient; Based on historical Ganoderma lucidum cultivation data, historical resource adjustment cases were obtained, and the resource adjustment ratio was defined as the target variable. Based on the stage characteristics, the interaction between the growth influence coefficient and key indicators of each stage is analyzed to obtain the interaction characteristics of the growth influence coefficient, where: During the mycelial growth stage, the product of the growth influence coefficient and 1 / humidity deviation is used as the interaction feature of the growth influence coefficient. During the fruiting body formation stage, the product of the growth influence coefficient and mushroom bud density is used as the interaction feature of the growth influence coefficient. During the fruiting body maturation stage, the product of the growth influence coefficient and the fruiting body diameter is used as the interaction feature of the growth influence coefficient. The interaction features of the growth impact coefficient, stage labels, batch features, and target variables are used as training data, and the evaluation results of historical resource adjustment cases are used as indicator data to train the initial gradient boosting tree model, thereby obtaining the correlation model between the growth impact coefficient and the amount of resource adjustment. S3: Real-time collection of environmental parameters for the industrialized cultivation of Ganoderma lucidum, determination of the deviation between the real-time environmental parameters and the current stage environmental parameter threshold, and determination of the resource optimization parameters corresponding to the deviation based on the correlation model; S4: Run the program according to the resource optimization parameters and make iterative adjustments during the operation until the real-time environmental parameters meet the standards.

2. The resource optimization allocation method for the factory-scale cultivation environment regulation of Ganoderma lucidum according to claim 1, characterized in that, In step S1, the industrialized cultivation cycle of Ganoderma lucidum is divided into stages, namely, the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturation stage, including: Based on the prior analysis of Ganoderma lucidum growth data, the growth characteristics and time proportions of the mycelial growth stage, fruiting body formation stage, and fruiting body maturation stage were determined. Based on the aforementioned growth characteristics and time proportions, the judgment criteria for each stage are determined; Based on the criteria for each stage, the industrialized cultivation cycle of Ganoderma lucidum is divided into stages: mycelial growth stage, fruiting body formation stage, and fruiting body maturation stage.

3. The resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum mushrooms according to claim 2, characterized in that, In step S1, determining the environmental parameter thresholds for each stage includes: Based on the correspondence between historical growth data and historical environmental data of Ganoderma lucidum, initial environmental parameter thresholds were set for each stage. Obtain the current cultivation scenario of Ganoderma lucidum, determine the correction coefficient based on the cultivation scenario, and correct the initial environmental parameter thresholds based on the correction coefficients to obtain the environmental parameter thresholds for each stage.

4. The resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum mushrooms according to claim 1, characterized in that, Historical environmental parameter deviation values ​​were obtained from historical Ganoderma lucidum cultivation data. Combined with environmental parameter thresholds for each stage, the influence coefficient of historical environmental parameter deviation values ​​on the growth of Ganoderma lucidum at each stage was calculated, including: The formula for calculating the growth influence coefficient of mycelial growth stage is as follows: ； in, This represents the growth influence coefficient at different stages of mycelial growth. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the mycelial growth stage. This indicates the rate of mycelial spread during the mycelial growth stage. This indicates the standard spread rate of mycelium during the mycelial growth stage. Indicates the historical environmental parameter deviation values ​​at different stages of mycelial growth; The formula for calculating the growth influence coefficient during the fruiting body formation stage is as follows: ； in, This represents the growth influence coefficient during the fruiting body formation stage. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the sub-entity formation stage. This represents the historical environmental parameter deviation value during the sub-entity formation stage. This indicates the rate of deformed mushroom buds during the mycelial growth stage; The formula for calculating the growth influence coefficient of the fruiting body maturation stage is as follows: ； in, This represents the growth influence coefficient at the fruiting body maturity stage. This represents the difference between the maximum and minimum values ​​of the environmental parameter thresholds during the maturity stage of a sub-entity. This represents the historical environmental parameter deviation value at the maturity stage of the sub-entity. This represents the standard daily increase in the diameter of a child body during its mature stage. This represents the daily increase in the diameter of a child entity during its mature stage.

5. The resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum mushrooms according to claim 1, characterized in that, In step S3, real-time environmental parameters of the Ganoderma lucidum industrial cultivation are collected, and the deviation between the real-time environmental parameters and the current stage environmental parameter threshold is determined, including: Real-time environmental parameters are obtained by collecting data in real time from sensors pre-installed in the cultivation area of ​​Ganoderma lucidum in a factory setting. A preset number of real-time environmental parameters are continuously sampled as the target real-time environmental parameters. The deviation value is obtained by comparing the target's real-time environmental parameters with the environmental parameter thresholds of the current stage.

6. The resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum mushrooms according to claim 5, characterized in that, In step S3, the resource optimization parameters corresponding to the deviation values ​​are determined based on the correlation model, including: The deviation value and the corresponding stage are input into the correlation model, and the resource optimization parameters are output.

7. The resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum mushrooms according to claim 1, characterized in that, In step S4, the process is run according to the resource optimization parameters, and iterative adjustments are made during the run until the real-time environmental parameters meet the standards, including: The system operates according to the resource optimization parameters and collects the latest environmental parameters. The latest deviation between the latest environmental parameters and the environmental parameter threshold is then determined. Based on the magnitude of the latest deviation value, determine the adjustment strategy for resource parameters.

8. The resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum mushrooms according to claim 7, characterized in that, Based on the magnitude of the latest deviation value, determine the adjustment strategy for resource parameters, including: If the latest deviation value is greater than the first deviation threshold, iterative adjustments are immediately performed to increase the adjustment range of resource parameters; If the latest deviation value is between the second deviation threshold and the first deviation threshold, it is monitored again after a preset period. If the latest deviation value monitored again is still between the second deviation threshold and the first deviation threshold, an adjustment is triggered to increase the adjustment range of the resource parameters, and the adjustment range is not greater than the preset threshold. If the latest deviation value is less than the second deviation threshold, no adjustment is triggered, and the current resource optimization parameters are maintained.

9. A resource optimization allocation system for environmental control in the industrialized cultivation of Ganoderma lucidum, specifically used to implement the resource optimization allocation method for environmental control in the industrialized cultivation of Ganoderma lucidum as described in claim 1, characterized in that, include: The phase division and data acquisition module is used to divide the industrialized cultivation cycle of Ganoderma lucidum into phases, obtaining the mycelial growth stage, the fruiting body formation stage, and the fruiting body maturity stage, and determining the environmental parameter thresholds for each stage. The Deviation and Resource Analysis module is used to establish a correlation model between environmental parameter deviations and resource adjustments at each stage based on historical Ganoderma lucidum cultivation data. The resource optimization module is used to collect real-time environmental parameters of Ganoderma lucidum factory cultivation, determine the deviation between the real-time environmental parameters and the environmental parameter threshold of the current stage, and determine the resource optimization parameters corresponding to the deviation based on the correlation model. The iterative adjustment module is used to run according to the resource optimization parameters and to perform iterative adjustments during the operation until the real-time environmental parameters meet the standards.

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